Dfig Wind Turbine Matlab

1

Frequency support Scheme based on parametrized power curve for

De-Loaded Wind Turbine Under Various Wind Speed

Cheng Zhong12, Yueming Lv1, Huayi Li1, JiKai Chen1, Yang Li1 1 Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology

Corresponding Author: Cheng Zhong

Abstract: With increased wind power penetration in modern power systems, wind plants are required to provide frequency support similar to conventional plants. However, for the existing frequency regulation scheme of wind turbines, the control gains in the auxiliary frequency controller are difficult to set because of the compromise of the frequency regulation performance and the stable operation of wind turbines, especially when the wind speed remains variable. This paper proposes a novel frequency regulation scheme (FRS) for de-loaded wind turbines. Instead of an auxiliary frequency controller, frequency support is provided by modifying the parametrized power versus rotor speed (Pw-ωr) curve, including the inertia power versus rotor speed curve and the droop power versus rotor speed curve. The advantage of the proposed scheme is that it does not contain any control gains and generally adapts to different wind speeds. Further, the proposed scheme can work for the whole section of wind speed without wind speed measurement information. The compared simulation results demonstrate the scheme improves the system frequency response while ensuring the stable operation of doubly-fed induction generators (DFIGs)-based variable-speed wind turbines (VSWTs) under various wind conditions.

Furthermore, the scheme prevents rotor speed overdeceleration even when the wind speed decreases during frequency regulation control. Index Terms—DFIGs, frequency support, inertia control, power versus rotor speed curve, de-loaded control, the whole

1. Introduction

Wind power generation is the most popular renewable generation technology, and the technology of wind turbine is still improving , such as the improvement of wind turbine cooling system , fault analysis , and so on. In 2020, the new installation of wind power generation was 93 Gw, and the  total  installed  capacity  was  743  Gw  .  Approximately 95% of installed wind turbines (WTs) are Variable speed wind turbines  (VSWTs),  either  DFIGs-based  with  partially  rated converters or PMSGs-based with fully rated converters .

Unlike  conventional  power  generators,  VSWTs  have  no inherent  inertial  response  because  of  the  power  electrical converter interface. VSWTs usually do not participate in the system frequency response for operation in maximum power point tracking (MPPT) mode. Therefore, as the penetration of VSWTs increases, the inertial and frequency regulation ability of  the  whole  power  system  will  degrade,  causing  frequency stability  issues  .  Some  countries  have  required  wind plants to provide frequency support .

Many  research  studies  have  discussed  the  frequency regulation  scheme  (FRS)  for  VSWTs.  The  strategies  can  be classified into inertial response control and de-loaded control .

For inertial response control, the VSWTs still operate in MPPT mode, and the rotational kinetic energy (KE) of VSWTs is  released  to  deliver  temporary  addition  power  during frequency dips. Further, the inertial response control can divide in two subcategories : natural inertial control  and stepwise control .

For  natural  inertial  control,  the  value  of  the  addition power is determined by the frequency measurement, such as the rate of change of frequency (ROCOF) , or the frequency

Deviation  , Or Both Of Them . Considering That

the wind speed is variable and the change of the rotor speed is complicated, the auxiliary frequency controller's gains should be  selected  carefully  with  the  trade-off  considering  the frequency  regulation  performance  and  the  stable  operating range  of  the  wind  turbine.  Therefore,  some  varying  gain methods have been suggested. In , the control gains of FRS under different wind speeds is adjusted based on the wind speed.

However, the pre-determined gains are obtained by the off-line modeling analysis, and the wind speed measurement may not be obtained or inaccuracy. To improve the frequency nadir (FN) and  ensure  stable  operation  of  DFIG,  the  droop  gains  is dynamically  changes  based  on  ROCOF  in  .  In  ,  the gains of additional ROCOF and frequency deviation loops is adaptively tuned depended on the rotor speed measurement.

present  a  time  varying  gains  determined  based  on  desired frequency -response time to raise frequency nadir and eliminate frequency  second  dip.  proposed an adaptive droop gain which is a function of real-time rotor speed and wind power penetration level.

For step-wise control, the addition frequency power is determined by the pre-set power surge function, such as step function , ramp function  or torque limit function .

Compared  with  natural  inertial  response,  the  inertial  power using the step-wise control can be properly tuned according to different  shapes  in  terms  of  its  magnitude  and  duration.  An optimization approaches employing the genetic algorithm are proposed  to  maximize  the  released  energy  from  the  wind turbine during its overproduction period .However, during the  rotor    speed  recovery  period,  the  output  power  of  wind turbine reduced  and may cause a secondary frequency drop [31, 32].In  ,the  incremental  power  varies  with  the  rotor speed  and  wind  power  penetration  levels  during  the overproduction period, and then, the reference power smoothly decreases with time and rotor speed during recovery period.

For inertial response control, because of the limit of the rotor kinetic energy, it only affords for seconds-term frequency support. While, for the de-loaded control, VSWTs reserve a part of  the  active  power  through  pitch  angle  control  , over-speed control , or combination of both . It can provide a minutes-term primary frequency support.

Due  to  rotor  speed  limit,  the  over-speed  de-loaded control is only adapted for low wind range. In , three wind speed modes are defined: low wind speed mode where de-loaded operation is merely by rotor speed control; medium wind speed mode where de-loaded operation is conducted by combining pitch angle control and rotor speed control; and high wind  speed  mode  where  modified  pitch  angle  control  alone.

However, it required accuracy wind speed information to judge the wind speed mode, and the calculation of de-loaded power reference need both parameters of wind turbine and wind speed.

present  a  variable  droop  control  strategy  that  considers optional rotor kinetic energy. However, the rotor kinetic energy estimation required the wind speed information and parameters of  wind  turbine.    proposed  a  comprehensive  frequency control  that  combines  the  temporary  power  injection  control and  power  reserve  control  with  consider  rotor  security  and maximum  extricable  energy  of  wind  turbines.  But,  it  still required  the  parameter  of  wind  turbines.  In    a comprehensive  frequency  regulation  that  combines  the step-wise inertial control and variable-droop control is present.

Actually, in most of the literatures mentioned above, the additional  frequency  regulation  power  is  determined  by  an auxiliary  ROCOF  and  frequency  deviation  loops,  which  is added  to  the  de-loaded  power  reference.  The  gains  of  the auxiliary frequency controller are difficult to set a proper value compromising of the frequency regulation performance and wind turbines rotor security. Moreover, if these schemes are applied to multiple WTGs, difficulties will arise in determining the different gains for all WTGs.  Nevertheless, some adaptive gains  methods  in  ,  the  proper  initial  value  or parameters are also difficult to select , or the gains are determined  by  evaluating  available  energy  which  of  the accurate  parameters  of  wind  turbines  and  wind  speed information are required .

This paper proposes a novel frequency support scheme for  DFIG-based  wind  turbines.  Instead  of  the  auxiliary frequency controller in the most existing scheme, the additional frequency regulation power for wind turbines is determined by the  modified  parametrized  power  versus  rotor  speed  curve.

There  are  three  main  advantages  of  the  proposed  control

Scheme:

(1) There are no control gains in the scheme. Thus, it does not need to carefully select a proper control gains for wind turbines  like  the  existing  scheme.  It  can  generally  adapt  for multiple WTGs with different wind speeds.

(2) It has potential self-adaptive frequency support with wind speed and can continuously ensure that the wind turbine operates within the safe rotor speed range, even in the case of a sudden decrease in wind speed.

(3) It can work for the whole wind speed range and does not need wind speed information. The remainder of this paper is organized as follows: In Section  2,  the  DFIG-based  wind  turbine  model  and  the traditional  frequency  regulation  scheme  are  introduced.  In Section  3,  the  proposed  frequency  regulation  scheme  for DFIG-based wind turbines is presented. In Section 4, compared with the traditional frequency regulation, the proposed control scheme's  performance  is  demonstrated  under  various  wind conditions. Finally, a brief conclusion is drawn in Section 5.

2. Dfig Model Of A Dfig-Based Wind Generation

Fig.  1  shows  the  block  diagram  of  DFIG-based  wind turbines'  simplified  model,  commonly  used  for  frequency control studies and developed in . The mechanical power of

(1)

where  ρ—air  density,  R—radius,  Vw—wind  speed, λ—tip speed ratio, λ=ωrR/Vw, ωr—rotor speed, β—pitch angle, and Cp(λ,β)—power coefficient.

(2)

A "one mass" system has been considered to represent the  rotational  dynamics  of  the  gearbox,  wind  turbine  and electrical  generator  [48,  49],  whose  equivalent  moment  of inertia is Jeq. where T, P, and ω represent torque, power and angular  speed,  respectively;  subscripts  g  and  t  are  used  to indicate the variables referring to the generator and the turbine.

fs, p and n are the grid frequency, the number of pole pairs and the gear ratio of the DFIG, respectively. In addition, the DFIG and the rotor side converter (RSC) are both regarded as a single first-order dynamics actuator, with a time constant τC, whose input is the electromagnetic reference torque from the speed control system Tg*.

Tt

Fig. 1 Block diagram of a simplified model of a DFIG-based

Wind Turbine

2.1. Maximum Power Point Tracking Controller (MPPT) To  capture  the  maximum  wind  power  by  the  wind turbine, a power reference, Pmax is from the maximum power versus rotor speed (Pmax-ωr) curve that can be represented by (3) and illustrated in Fig. 2 (the solid black line).

(3)

where  kopt  is  the  optimization  constant,  whose  value depends on the physical characteristics of the wind turbine. Concerning Fig. 2, the maximum power curve is divided into four segments according to the rotor speed. The segment A-B corresponds to the starting zone. In segment B-D, known as  the  optimization  zone,  the  rotor  speed  is  adjusted  to  the optimal  speed  with  the  optimal  power  coefficient  Cp(λ,β).

Segments D-E are constant rotor speed zones, and the rotor is almost invariable. After the segment after point E is called the constant power zone, Pmax is constant Pnor.

The intersection point of the capture power versus rotor speed curve (Pm-ωr) and the maximum power curve (Pmax-ωr) is an equilibrium point. After some disturbances, the DFIG-WT automatically  converges  to  the  intersection  point,  where  the captured mechanical power Pm is equal to the optimum power Popt, and the rotor equals ωopt.

A  pitch-angle  controller  is  used  to  prevent  the  rotor speed from exceeding ωmax and keep the output power at the rated value when wind speeds are high.

Fig. 2 Maximum power curve and de-loaded power curve for

2.2. The Traditional Frs For Dfig-Based Wt

The most popular FRS for wind turbines is shown in Fig. 3,  as  in    (and  similar  schemes  in  ,  ).  To realize de-loaded control, a de-loaded power versus rotor speed curve (Pde-ωr) replaces the Pmax-ωr curve. This makes the rotor speed  higher  than  the  optimum  rotor  speed.  The  DFIG-WT operates at a suboptimal point below the maximum power point (reserve a part of the active power). A typical Pde-ωr curve is given in Fig. 2 (the blue line).

An  auxiliary  frequency  controller  (AFC)  is  added  to generate  an  additional  power  ΔPf,  as  expressed  in  (4).  It includes  virtual  inertia  response  and  droop  response.  The inertia  response  is  based  on  the  ROCOF,  while  the  droop response is based on the frequency deviation.

(4)

where Kv and 1/R are the gains of the virtual inertia and droop loops, respectively. The pitch angle control not only prevents the rotor speed from  exceeding  ωmax  but  also  helps  to  realize  de-loaded operation  at  medium  and  high  wind  speeds  area  .

According to wind speed, the de-loaded control can be divided into three areas in , as shown in Fig. 2. (1) Low wind speed area: V1-V2, βde=0, ωr<ωmax; only the speed control loop is used to realize de-loaded control.

(2)  Medium  wind  speed  area:  V2-V3,  βde>0, ωr<ωmax. Both the speed control  loop and  pitch  controller are  used to realize de-loaded control.

(3) High wind area: higher than V3, βde>0, ωr=ωmax, only the pitch controller is used to realize de-loaded control. βde is the de-loaded pitch reference for avoiding overspeed.

The control of the pitch angle is shown in Fig. 3(b). βde is obtained from wind turbine modeling by solving Eq. (5).

(B)

Fig. 3 The commonly used frequency regulation controller for

(5)

where λopt is the optimum tip speed ratio and Cp,max is the maximum wind energy capture factor. λref is the reference tip speed ratio in over speed control, λref=ωmaxR/v, and Cp,rated is the wind energy capture coefficient when operating at rated power.

β0 is the pitch angle reference when the wind turbines operate at the rated power. βde is the de-loaded pitch angle in the de-loaded control  mode.  d’%  is  the  real  de-loaded  ratio  of  the  wind

(6)

where  Popt is  the  reference  power  of  the  wind  turbine under MPPT and Pnor is the rated power. However,  there  are  still  some  shortcomings  for  the traditional frequency regulation scheme.

(1) The gains of AFC are challenging to set because of the compromise of the frequency support performance and wind turbines' stable operation. A large gain can improve the frequency regulation while causing overdeceleration of a DFIG.

Conversely, a small gain can prevent overdeceleration, but it provides  a  limited  contribution  to  frequency  supports.  In addition, for multiple WTGs, the available energy is different because the available energy is determined by the wind turbine characteristics and wind speed. There cannot be a single proper value for all different DFIGs.

(2)  Wind  speed  information  is  required  to  realize de-loaded and frequency support control for the whole section of wind speed. As seen in Fig. 3(b), wind speed information V is necessary for the decision of the wind speed area, calculating the maximum power Popt and the optimum tip speed ratio λopt.

3. The Proposed Frequency Regulation Scheme

To  address  the  limitations  mentioned  above,  a  novel frequency  regulation  scheme  for  de-loaded  wind  turbines  is proposed. The whole control diagram of the proposed scheme is illustrated in Fig. 4.

Fig. 4 The Proposed Frequency Regulation Scheme

The  proposed  FRS  includes  two  key  steps.  First,  the de-loaded curve is modified into a droop power curve based on the frequency deviation to provide a droop frequency response.

Second,  the  droop  power  curve  is  further  modified  into  an inertia power curve based on ROCOF to provide both inertia and  droop  frequency  responses.  The  detection  of  dfs/dt  is sensitive to noise and harmonic disturbance. Hence, a washout filter (Tw=0.01)  is used to obtain dfs/dt, as seen in Fig.4.

Then, the power reference PE* can be obtained based on the measurement of the rotor speed ωr. The de-loaded power curve, the droop power curve and the inertia power curve are detailed below.

(7)

where Popt is the maximum available power, Pde is the de-loaded power, and d% is set to 10% in the paper. Similar to the Pmax-ωr curve, the de-loaded curve Pde-ωr

(8)

where  kde is  the  de-loaded  constant  and  Pde  is  the de-loaded power. Noticed that kde does not equal the 0.9kopt. As shown in Fig. 4, for the same wind speed, the rotor speed with 0.9Popt is larger than the optimum rotor speed. By off-line data fitting, it can be obtained that the value of kde with a 10% power reserved ratio is 0.2172. At the maximum rotor speed for the de-loaded power curve, the corresponding wind speed is 10 m/s, instead of 12 m/s for the maximum power curve.

3.2. Droop Power Versus Rotor Curve

The  droop  power  curve,  Pdroop-ωr,  is  shifted  from  the de-loaded curve (Pde-ωr) to the maximum power curve (Pmax-ωr) based on the frequency deviation.

d% is 10% in this paper, and the droop curve Pdroop-ωr is

(10)

Where  kde80%  is  the  de-loaded  constant  with  an  80% power  reserve  for  the  wind  turbine,  which  to  provide  10% power regulation capability for frequency rise event. kde80% is obtains by off-line data fitting and kde80%=0.1956. Δfmax is the allowable frequency deviation and Δfmax=0.5Hz in this paper.

5

The droop power curve is illustrated in Fig. 5. When the frequency dips, the droop curve moves toward the  Pmax-ωr  curve.  Thus,  the  reference  power  with  the  same rotor  speed  is  larger,  i.e.,  more  active  power  from  the  wind turbine is delivered to the system.

The  droop  response  is  a  minute-term  time  response. Thus, the Pmax-ωr curve is the upper limit of the droop power curve. The additional power from the Pdroop-ωr curve does not exceed the maximum available power.

When  Δfs=0,  Pdroop-ωr  is  the  same  as  the  de-loaded power curve. Otherwise, when the frequency rises, the power curve moves down, and the reference power with the same rotor speed changes to a smaller value. Pdrooplimt -ωr is the lower limit droop curve (as seen in Fig. 5) and is near 80% of the maximum power curve.

Therefore,  the  droop  power  curve  provides  droop frequency  support  for  the  wind  turbine,  similar  to  the  droop response in the traditional auxiliary frequency controller.

Note that there  is always an intersection of the droop power curve and the captured wind power curve (equilibrium point).  This  means  that  the  DFIG  always  converges  to  the equilibrium point in any case. Furthermore, the droop power curve definition does not contain any control gains in (9).

3.3. Inertia Power Curve

Furthermore, to provide inertia supports for the system frequency, the droop power curve, Pdroop-ωr, is further modified into an inertia power versus rotor speed curve, called Pin-ωr, based on the ROCOF (dfs/dt).

In this paper, the inertia power curve is defined in (11) as below.

(11)

where Pupinertial-ωr is the upper limit of the inertia power curve, and Plowerinertial-ωr is the lower limit of the inertia power curve. (dfs/dt)max is the maximum measurement dfs/dt during the frequency event process.

To  obtain  (dfs/dt)  max,  a  latch  is  used  to  store  the maximum value. This means that if a new measurement (dfs/dt) value  is  larger  than  the  old  storage  value,  the  new  value replaces the old storage value. Otherwise, the latch keeps the old storage value.

Pupinertial-ωr is defined as in (12), which borrows from . Pupinertial-ωr also shown in Fig. 6.

(12)

PTlim is the torque limit relative to the power curve. ωa is

The Initial Rotor Speed

To avoid the rapid and excessive increase in the output power causing the wind turbine's mechanical torsion, the power limit Plimit and the maximum torque limit Tgmax are often set to 1.1 pu. and 1.07pu .

The minimum torque limit Tgmin are often set to 0. 05pu . The rotor speed increases during the frequency increase event.  Therefore,  the  definition  of  the  Plowerinertial-ωr is  only considered the range of the rotor speed higher than the current rotor ωa . Similarly, the definition of Plowerinertial-ωr is required to prevent  the  speed  rotor  over-accelerating.  the  Pupinertial-ωr  is given in (13), and as the red curve shown in Fig. 6.

Fig. 6 The Inertia Power Curve

To  explain  the  frequency  regulation  proceeding,  a frequency drop event is taken as an example, and the trajectory of operating point during the frequency regulation process is depicted by the red curve in Fig.6.

At  the  initial  time,  'G'  is  assumed  to  be  the  initial operating point located at the de-loaded curve. Δfs and |dfs/dt| are negative values, and dfs/dt quickly drops to the minimum value.  That  is,  |dfs/dt|  reaches  the  maximum  value.  The de-loaded  power  curve  quickly  turns  into  the  upper  limit inertial  curve,  Pupinertial-ωr.  Thus,  the  operating  point  switch from  the  'G'  to  the  point  'H'.  The  wind  turbine  releases  the maximum allowable power for the supported frequency.

Then,  Δfs  and  |dfs/dt|  decreases.  According  to (9),  the droop power curve moves up with Δfs. Meanwhile, the rotor speed ωr decreases because of the extra active power releasing.

'J'  is  the  corresponding  point  with  ωK  located  at  Pupinertial-ωr curve, while 'I' is the corresponding point with ωK located at Pdroop-ωr curve.  Because  of  the  decrease  of  the  dfs/dt (dfs/dt<(dfs/dt)max),  according  to  (11),  the  operating  point moved from 'H' to 'K' (Pin(ωK),ωK). The additional active power from the wind turbine is gradually decreased. Along with dfs/dt approach  to  zero,  the  operating  point  moves  from  the Pupinertial-ωr curve to the droop power curve.

When dfs/dt=0, the frequency reaches the lowest point. At this time, the inertia power curve turns into the droop power curve. The operating point 'K' will turn into 'L' located into the droop power curve Pdroop2-ωr.

Then, the frequency recovery starts. dfs/dt and Δfs are opposite  in  sign.  Unfortunately,  the  inertia  response  is  not beneficial for frequency recovery. Thus, when dfs/dt >0 and Δfs <0,  the  power  curve  maintains  the  droop  power  curve.  The inertial power curve is only enabled when dfs <0 and dfs/dt<0.

As the frequency recovery (Δfs increase), the Pdroop2-ωr curve will move downward to the Pdroop3-ωr curve.  As illustrated in Fig.6, the operating point will move from 'L' to 'M'.

The Pupinertial-ωr curve and the Pm-ωr curve always has an  intersection  (like  'O'  point  in  Fig.6),  which  also  is  an equilibrium point. Only under the extreme situations that dfs/dt keeps the max value (dfs/dt) max, the wind turbine will converge to  this  intersection.  The  rotor  speed  of  this  intersection  still higher  the  minimum  rotor  speed  limit  ωmin.  Practically,  the dfs/dt  will  gradually  reduce  during  the  frequency  regulation process. Hence, the rotor speed always higher than ωmin. during frequency regulation process. Otherwise, the proceeding of the frequency  rise  event  is  similar.  The  proposed  method  can ensure the wind turbine operate among the safe rotor range and prevents overdeceleration.

Noticeably, there are no control gains in (9) - (11). The output power is determined by the current measurement rotor speed and the modified power curve. Thus, unlike the existing scheme's  difficulty  in  choosing  the  proper  control  gains,  the proposed scheme does not have any control gains.

3.4. Pitch Angle Control

As described in the traditional FRS control (Section II. B), in the medium and high wind areas, pitch angle control is necessary  to  add  to  limit  the  rotor  speed  and  help  de-load control.  However,  in  traditional  control,  wind  speed information  is  required  to  decide  the  wind  speed  area  and calculate the value of the compensation pitch βde. However, the inaccurate  wind  speed  measurement  may  be  harmful  to  the control  performance.  Furthermore,  a  complex  calculation  is needed  to  calculate  βde.In  this  paper,  improved  pitch  angle control is designed.

De-Loaded Power Pde

Fig. 7 Pitch angle and de-loaded power at various wind speeds Fig.  7  shows  the  de-loaded  power,  maximum  power pitch angle βm, de-loaded pitch angle βde, and difference angle (between the aforementioned two angles) Δβ versus wind speed.

The maximum power pitch angle remains zero until the wind speed reaches V2. Then, the pitch angle gradually increases to reduce the capture of wind power.

The de-loaded pitch angle remains zero until the wind speed  reaches  V1.  Then,  the  pitch  angle  increases  to  realize de-loaded  control.  During  V1  and  V2,  which  is  called  the medium  wind  speed  area  aforementioned,  both  pitch  angle control and rotor speed control are  used to realize de-loaded control. At wind speeds higher than V2, only the pitch angle is used to realize de-loaded control.

Observing  Δβ in  Fig.  7,  Δβ can  be  divided  into  three segments: a low wind speed area where the wind speed lowers V1, where it is zero; a medium wind speed area during V1 and V2, where  it  is  a  nonlinear  curve;  and  a  high  wind  speed  area, higher than V2, where it has a constant value (nearly 1.6°in this paper).

Fig. 8 shows the wind power coefficient Cp versus pitch angle under different tip speed ratios. In the vicinity of λopt (λopt=10.5 in this paper), Cp seems not  to  be  influenced  by  the  different  λ.  Therefore,  the  pitch angle is an almost constant value when Cp is not a considerable reduction.  This  is  the  reason  that  in  the  high  wind  area,  Δβ remains almost constant to realize a certain power reserve.

Linearly fitting the λopt curve to obtain the approximate

Cp= -0.0276Β+ 0.44                           (14)

If  the  DFIG  operates  at  a  10%  power  reserve,  β  will increase by approximately 1.6°.

Wind Power Coefficient Cp

Fig. 8 Wind power coefficient Cp versus pitch angle under differ ent tip speed ratios. Further observing Fig. 7 in the low wind area, the Δβ is zero,  where  the  de-loaded  power  is  below  0.38Pnor;  in  the medium  wind  speed  area,  where  the  de-loaded  power  is between  0.38Pnor  and  0.9Pnor,  the  Δβ  varies  with  de-loaded power.  At  high  wind  speeds,  where  the  de-loaded  power remains at 0.9 Pnor, Δβ remains at a constant value of 1.6°.

Fig. 9 Δβ Versus The De-Loaded Power Curve

The Δβ versus the de-loaded power curve is described in Fig. 9. and the polynomial fitting function given in (15).

(15)

According  to  (15),  Δβ  can  be  obtained  based  on  the de-loaded power Pde. Wind speed information is not required. In  the  medium  and  high  wind  speed  areas,  the  pitch angle must be adjusted to release more or less active power for participation  in  frequency  regulation.  The  improved  pitch control diagram is given in Fig. 10 below.

Fig. 10 The Proposed Pitch Angle Control Scheme

As seen in Fig. 10, Δβ is obtained from equation (15), and  a  simple  linear  method  is  used  to  calculate  the

(16)

Δβ' regulate with the system frequency. when Δf=-Δfmax, Δβ' is equal to 0, and βref = βmppt. When Δf=0, Δβ' is equal to Δβ, and βref=βde (the pitch angle in de-loaded mode).

As  shown  in  the  modified  pitch  angle  control description in Fig. 10, wind speed information is not required. The  pitch  angle  can  help  the  de-loaded  operation  and  the frequency regulation of wind turbines in medium and high wind speed areas.

Matlab/

SIMULINK 2018 Student Suite Version, MathWorks, Natick, MA,  USA  are  carried  out  to  verify  the  proposed  frequency regulation scheme's efficacy.

Fig. 11 shows the single bus model of the small isolated power system used in the paper. It includes static loads, one thermal  plant,  one  hydropower  plant,  and  one  aggregated DFIG-based wind power plant. The total capacity of the power systems is 1250 MW.

S=150Mva

Fig. 11 Single-line diagram of test power system for simulation

(B)

Fig. 12 Governor-based models of conventional power plants Simplified governor-based models from  are used to simulate thermal and hydropower plants (see Fig. 12).

The  droop  characteristics  of  conventional  plant  speed governors  have  been  enabled.  The  values  of  the  most significant parameters are summarized in Appendix table2 and 3.

To  simulate  the  wind  power  plant,  an  equivalent generator with 100 times the nominal power of one DFIG is assumed. The parameters of DFIG-based VSWTs are given in Appendix table.1 The performance of the proposed scheme for DFIG-based  VSWTs  is  compared  to  that  of  MPPT,  the conventional FRS with fixed gain under various wind speeds.

In traditional FRS with fixed gain, Kw is set to 30 and 15, while  1/Rw  is  set  to  24  and  7.  Under  medium  wind  speed conditions, when a larger gain is selected, the inertial control performance of  the DFIG can be effectively improved while ensuring  stable  operation.  In  comparison,  a  smaller  gain  is selected  to  maximize  the  lowest  frequency point  (FN)  while ensuring  stable  operation  of  all  DFIGs  under  low  wind conditions. It is worth noting that the values of large gain and small gain are just an example of traditional FRS. If the system changes, these values should be changed appropriately.

Cases 1, 2, and 3 refer to the constant wind speed in the low wind speed area, the medium wind speed area and the high wind speed area, respectively. In cases 4 and 5, the wind speed is assumed to be reduced at the instant of an event, from 9 to 7.5 m/s for 10 and 1 s, respectively. Case 6 is the random wind speed in low wind area. In all cases, if the rotor speed reaches ωmin, the FRS (not including de-loaded control) are disabled by disconnecting the frequency measurement.

Power,

DFIG-based VSWTs have more difficulty increasing the output power when the frequency dips. Thus, at 60 s, the system load suddenly increases by 0.1 pu and causes a frequency dip event for all cases.

4.1.1 Case1: Low Wind Speed Area

Fig. 13 illustrates the results for a wind speed of 8 m/s in the low wind speed area, where the DFIG-based VSWTs only use overspeed control to realize de-loaded control. 13 shows the result of Case 1.

Authors:

Peder EZ Larson 1, 2,* , Jenna ML Bernard1, James A Bankson 3, Nikolaj Bøgh 4, Robert A Bok1, Albert P. Chen 5, Charles H Cunningham 6,7, Jeremy Gordon1, Jan-Bernd Hövener 8, Christoffer Laustsen 4, Dirk Mayer 9,10, Mary A McLean11 12, Franz Schilling13, James Slater1, Jean-Luc Vanderheyden5, 14, Cornelius von Morze 15, Daniel B Vigneron1, 2, Duan Xu1, 2, and the HP 13C

94143, Usa.

Denmark. 5 GE Healthcare, Menlo Park, California, USA. 6 Physical Sciences, Sunnybrook Research Institute, Toronto, Ontario, Canada.

8 Section Biomedical Imaging, Molecular Imaging North Competence Center (MOIN CC), Medicine, Baltimore, MD, USA. Cambridge, United Kingdom.

14Jlvmi Consulting Llc, Dousman, Wi, Usa

#See Acknowledgements for a list of all HP 13C MRI Consensus Group Members This work was supported by the ISMRM Hyperpolarized Media MR Study Group, the ISMRM Hyperpolarization Methods & Equipment Study Group, and the Hyperpolarized MRI Technology Resource Center (NIH/NIBIB grant P41EB013598).

Abstract

MRI with hyperpolarized (HP) 13C agents, also known as HP 13C MRI, can measure processes such as localized metabolism that is altered in numerous cancers, liver, heart, kidney diseases, and more. It has been translated into human studies during the past 10 years, with recent rapid growth in studies largely based on increasing availability of hyperpolarized agent preparation methods suitable for use in humans. This paper aims to capture the current successful practices for HP MRI human studies with [1-13C]pyruvate - by far the most commonly used agent, which sits at a key metabolic junction in glycolysis. The paper is divided into four major topic areas: (1) HP 13C-pyruvate preparation, (2) MRI system setup and calibrations, (3) data acquisition and image reconstruction, and (4) data analysis and quantification. In each area, we identified the key components for a successful study, summarized both published studies and current practices, and discuss evidence gaps, strengths, and limitations. This paper is the output of the “HP 13C MRI Consensus Group” as well as the ISMRM Hyperpolarized Media MR and Hyperpolarized Methods & Equipment study groups. It further aims to provide a comprehensive reference for future consensus building as the field continues to advance human studies with this metabolic imaging modality.

Keywords: Hyperpolarized MRI, metabolic imaging, carbon-13, pyruvate, dissolution dynamic

Introduction

MRI with hyperpolarized 13C agents, also known as hyperpolarized (HP) 13C MRI, has shown great potential as a novel imaging modality, particularly for its ability to probe metabolic processes in real time. The first human studies with HP [1-13C]pyruvate were performed in 2011 in prostate cancer patients (1).

Since then, there have been over 60 papers published with imaging results of human subjects from 13 different sites, with applications including prostate cancer, brain tumors, breast cancer, kidney cancer, pancreatic cancer, metastatic disease, liver disease, ischemic heart disease, diabetes and cardiomyopathies. The vast majority of these studies used [1-13C]pyruvate (1–63), where [2-13C]pyruvate (64) and 13C-urea (56) have been demonstrated too.

As clinical HP 13C MRI advances, there is a growing need to build consensus for best practices, which are critical for comparing data across sites, performing multi-site trials,deploying methods to new sites, partnering with vendors, and potentially for obtaining broader regulatory approvals.

In March 2022, we initiated an effort to build consensus within the HP 13C MRI community with this opportunity in mind, and it was greeted with strong enthusiasm. The “HP 13C MRI Consensus Group”, containing over 55 members from 27 sites, identified the area of greatest need and opportunity for consensus building to be HP [1-13C]pyruvate human

●

Pyruvate is the most mature and widely used HP agent and has the most significant translational evidence emphasizing the potential clinical impact.

●

Clinical trials, particularly multi-site trials, have the strongest need for consensus methods to ensure that data can be combined across sites. This work is a Position Paper for which the goal is to describe current successful practices and study methods for HP [1-13C]pyruvate human studies along with justification to support those practices. This is divided into four major topic areas: (1) HP 13C-pyruvate preparation, (2) MRI system setup and calibrations, (3) data acquisition and image reconstruction, and (4) data analysis and quantification (Fig. 1). The current successful practices and study methods include a literature review of published peer-reviewed journal papers showing human HP [1-13C]pyruvate study data, up to September 2022 (1–63), as well as new unpublished information from surveys of HP 13C study sites. Based on this information, we also highlight the evidence gaps, strengths, and limitations of current practices which are summarized at the end of each section.

Figure 1: Illustration of the HP 13C MRI human study process, including the 4 major areas covered in this paper: Hyperpolarized 13C-pyruvate preparation, MRI system setup and calibration, Acquisition and Reconstruction, and Data Analysis and Quantification.

Figure 2: Anatomical targets of HP [1-13C]pyruvate MRI human studies published up to September 2022.

Hyperpolarized 13C-Pyruvate Preparation

This section covers the processes for creating the HP agent, 13C pyruvate, and will include many aspects and considerations that are needed to safely and effectively prepare doses for metabolic imaging studies in human subjects. These include material, personnel, equipment and facility, fluid path preparation, quality control, and release.

It is helpful to understand that the specifications of a dose of 13C pyruvate suitable for in vivo MR HP metabolic imaging were shaped in part by early preclinical studies performed by GE HealthCare summarized in Ref. (65). In short, the safety of the two novel drug components, 13C pyruvate and the electron paramagnetic agent (EPA) AH111501, were demonstrated in those studies. The more precise formulation of the dose suitable for human use was then determined from clinical studies (66) that included two Phase 1 clinical trials in young and elderly healthy volunteers without hyperpolarization of the 13C nuclei and another Phase 1/2a dose escalation and imaging feasibility study with HP 13C pyruvate in 31 prostate cancer patients at the With the exception of the first HP 13C imaging clinical trial, which utilized a prototype device in a cleanroom (1), all HP 13C studies performed in humans to date have utilized the SPINlab polarizer (manufactured by GE HealthCare). Consequently all doses of the HP 13C pyruvate delivered by SPINlab have been produced using the “SPINlab Pharmacy Kit” that serves as the container-closure system for the various drug components (13C pyruvic acid and EPA mixture, dissolution medium, and neutralization and dilution medium) during sample polarization, dissolution and quality control (QC) processes. Thus many aspects of the HP sample preparation considerations discussed below are related to the SPINlab instrument and the consumables designed to be used with it (67).

General Considerations

While more than 860 patients or healthy subjects having been injected with HP 13C pyruvate as of January 2022 without reports of any serious adverse events (68), HP 13C pyruvate injection remains an investigational MR contrast agent and can only be administered by those with Investigational New Drug (IND) exemption from the Food and Drug Administration (FDA) in the USA, a Clinical Trial Application (CTA) in Canada, approval from National Research Ethics Committee Services in the UK, or approval from the relevant local regulatory body. Thus, methods and processes involved to produce a dose should have patient safety as the first priority. Since utilizing dissolution dynamic nuclear polarization (dissolution-DNP) for human use is still a relatively new development, there are no existing published regulatory guidelines specifically for this method.

There are two major production styles that determine how various sites approach the agent preparation. In the US, the most common approach is to rely on a sterilizing filter (“Terminal Sterilization”) to ensure sterility of the final product, akin to PET tracer production, where a starting molecule with a radioisotope is processed using various other ingredients to make the final, desired and injectable contrast agent within a necessarily short amount of time (69). For these sites, sterilization of the components and accessories upstream of this filter are not required, although many of them were manufactured and tested following Good Manufacturing Practice (GMP) or Good Laboratory Practice (GLP) requirements. The filling process is usually performed under an ISO 5 laminar flow hood, but a clean room or an isolator is not required.

This approach is typically accompanied by testing the integrity of the sterilizing filter prior to release of the dose for injection. Typically, post release endotoxin and sterility tests are performed using an aliquot reserved from each released dose.

In the UK and EU, the most common approach is to more-closely follow sterile pharmaceutical compounding guidelines (70), where all components and ingredients are required to be sterile or manufactured under GMP guidelines and are assembled and filled within a clean room environment or an isolator system (“Sterile Preparation”). Typically a batch of Pharmacy Kits for HP 13C pyruvate injection are prepared together. The sterility of the final dose is also ensured by batch validation testing, in addition to the sterility of the ingredients and the sterile compounding process. The endotoxin and sterility testing are performed for the process validation but are not performed for each injected dose.

Some institutions fill and assemble the Pharmacy Kit required for a specific study on the same day or the day prior to polarization, dissolution, and patient administration, but others have also demonstrated the feasibility of preparing a batch of kits, keeping them in a -20ºC freezer and using them over a period of a few months.

Beyond the obvious requirements that the process and the facility has to ultimately produce a dose that is safe to inject into a human, regulatory authorities will also focus on the question “Are you in control of your processes?”. To be in control of your process requires an in-depth and broad understanding of all processes involved in pre, post, and during the production process.

Personnel

It is typical and may be required to have licensed personnel involved in the production process depending on local regulations.Typically a pharmacist, radiopharmacist or other similarly qualified person (QP), in charge of the facility where the Pharmacy Kit filling and preparation is taking place, is responsible for the overall process and the release of the injectable dose.

Qualified cleanroom technicians are often involved in the Pharmacy Kit filling under the supervision of the pharmacist or QP. As is required for pharmaceutical compounding or PET tracer production, training requirements and training records for all personnel need to be maintained and available for audit by the FDA or equivalent.

Equipment And Facility

The facility and all equipment need to have standard operating procedures (SOPs) that describe how equipment is used, maintained, and calibrated to comply with relevant legislation. Currently, almost all the filling of the Pharmacy Kit takes place within a compounding laminar flow hood or isolator (typically ISO 5). At some sites, the filling is conducted within a cleanroom, while at others, it is conducted in a dedicated non-cleanroom space, reflecting differences in cleanroom approach and specifications between regulators worldwide (71). Some equipment or facilities, such as the compounding hood or cleanroom, may require external certified laboratories for testing.

Material Handling

Material handling guidelines (69,70) require SOPs detailing a system to track all of the materials involved in the HP production process for a particular patient dose, similar to current good manufacturing practice (cGMP) requirements for material handling for drug compounding. This includes acceptance standards, storage conditions, amount used in the patient dose for each ingredient and materials used in the assembly of the fluid path and Pharmacy Kit. Currently some users choose to open and inspect and sometimes modify the Pharmacy Kits upon arrival, but some users keep them in the sealed packaging until they are required for dose preparation.

Pharmacy Kit Filling And Assembling

As required by an IND or its equivalent, the preparation of the doses of HP 13C agent are detailed in the Chemistry, Manufacturing, and Control (CMC) section of an applicable regulatory submission; an example of this has been made available (72). It describes the processes of filling the Pharmacy Kit with the different components that make up the final drug product, and of assembling the final kit for either storage or immediate use in the polarizer. Special attention should be given to the laser welding process in order to satisfy installation qualification (IQ) and operational qualification (OQ). Typically, the final developed process is validated by process qualification (PQ) runs, during which 3 or more Pharmacy Kits are filled and used and the final HP 13C products are tested for endotoxin and sterility and to confirm that they meet the dose specifications for injections (usually including pyruvate concentration, residual EPA concentration, pH, liquid state polarization level and dose temperature). The data from 3 consecutive PQ runs are submitted as part of the IND submission (or its equivalent), and are often also reviewed by the Institutional Review Board (IRB) where the studies are conducted.

Quality Control And Dose Release

The quality control (QC) and dose release can be separated into two aspects: one is the QC and release of the filled Pharmacy Kit, and second is the QC and release of the HP 13C agent for injection, after polarization and dissolution. For institutions filling a batch of kits and storing them to use over a period of time, typically the batch can be released based on initial validation, environmental monitoring data from the day of kit production, and if filters are used during preparation of any of the components, filter integrity testing. But in some cases one or more kits are used for validation before the batch of kits are released for future use. For institutions that fill only the kits required for specific studies shortly before the experiment, the filled kits often do not go through separate release tests before they are used.

The quality control of the HP 13C pyruvate solution post dissolution is primarily performed to ensure that the agent meets the dose specifications (Table 1) before it is administered to the subject. These specifications target both safety (pH, residual EPA, temperature) and efficacy (pyruvate concentration, polarization, volume). Typically, the pyruvate concentration, residual EPA concentration, pH, dose temperature, dose volume, and liquid state polarization are measured by the QC accessory associated with the SPINlab polarizer. Some users perform a secondary measurement for one of the parameters, such as pH, using a different instrument or pH paper. For sites that do not go through a separate release testing process for batch filled kits, the integrity of the sterilization assurance filter, a part of the Pharmacy Kit, is typically tested as a part of the dose release. It is also common for these users to preserve an aliquot of the final HP 13C pyruvate solution for post-release endotoxin and sterility testing. This testing cannot be completed fast enough to test an individual dose prior to injection, but this is why other processes such as PQ runs and validation testing are done to minimize the chance a subject could be injected with a contaminated dose.

The Final Dose Release And Injection

should be done under the supervision of a licensed professional, based on local regulations.

Some Key Challenges

Many of the challenges associated with HP 13C pyruvate preparation can be attributed to the conditions required for the dissolution-DNP method of high magnetic field (~3-7 T) and very low temperature (~1 K) during polarization, with pressurized and superheated water necessary for the rapid dissolution event. These extreme conditions are quite challenging for the design of the container-closure and fluid path system. In particular, the cryogenic temperature in the polarizer requires special attention to any moisture or ambient (moist) air introduced into that portion of the fluid path, which can form an ice block at ~1 K. This ice can lead to flow restriction during the dissolution event and reduce the strength of the laser welded bond between the cryovial and its cap. This can ultimately produce failures in the dissolution step, including variations in final pyruvate concentration and pH that may fail to meet QC release criteria as well as fluid path ruptures that provide no available dose and result in polarizer down-time.

The polarization of the HP 13C pyruvate sample decays quickly over the span of a few minutes after dissolution, and thus the process of dissolution, QC for release, and injection should be completed as fast as possible to preserve the high polarization level achieved. Any delays in the preparation process, such as transportation time or equipment malfunction, can significantly reduce the final polarization and result in lower quality imaging data.

Current Practices

A summary of data collected from all sites performing clinical trials with HP 13C-pyruvate is shown in Fig. 3 and Table 1, including the specification of the final dose and how the quality control and release of the final dose are performed. There is a split in the Production Style, described in the General Considerations section above, with 8/13 sites using Sterile Preparation versus 5/13 using Terminal Sterilization. While many of the dose specifications show notable differences in acceptable ranges, all of these variations listed in tables have been successfully and safely been used to perform HP 13C pyruvate studies in humans. Their differences depend on the institutions’ preferences, resources and their particular regulatory situation. There is high similarity in pyruvate ranges, temperature ranges, EPA limits, and volume limits. There is modest variability in pH ranges and large variability in the endotoxin test limit. There is a 3-fold difference in acceptable polarization levels, which are measured to ensure a futile dose is not injected since the polarization is directly proportional to SNR. This reflects the decision by several sites to believe that useful data can be still be obtained with suboptimal polarizations.

Figure 3: Hyperpolarized agent preparation methods reported by sites currently performing HP

In House

Table 1: HP 13C-pyruvate preparation parameters, methods, and dose specifications used for quality control testing and release as well as validation. These were obtained from a survey of all sites performing clinical trials with HP [1-13C]pyruvate. The parameters used for product release are noted in bold text, otherwise these parameters are measured for batch validation or other QC measurements. The endotoxin and sterility testing are performed during process validation of the batch and/or post-injection, and largely depends on the agent production approach.

Summary

The overall safety record of HP 13C-pyruvate has been very strong, and the SPINlab hyperpolarizer has proven to provide high polarizations at human sized doses while meeting numerous QC and release criteria. A weakness remains the failure modes of the SPINlab Phamacy Kits (e.g. ice blocks, path ruptures), which are placed under extreme requirements particularly during dissolution. The preparation process still requires a high degree of expertise.

Therefore, there is a significant need to improve the reliability, robustness, and ease of operation for generating HP 13C-pyruvate doses for human studies. Furthermore, there is a divide between manufacturing and sterile compounding style preparation as well as other site-specific practices, resulting in variations in SOPs and justification required to relevant regulatory bodies. There have also been no comparisons between these approaches. It is also unclear what release criteria and QC parameters are truly required to ensure patient safety.

However, all of the reported methods are acceptable and approved by the appropriate regulatory authorities, and have led to the rapid expansion of successful human studies in recent years.

Mri System Setup And Calibrations

This section covers the MRI system setup, including the imaging system, RF coils, phantoms, and prescan calibration methods.

Imaging System

The main prerequisite for a given MRI scanner to be capable of supporting studies with HP 13C is its “broadband” capability to transmit and receive radiofrequency (RF) signal at the frequency of 13C, which is around 4 times lower than 1H. This does not come as a default on clinical MR devices. The transmit power of the broadband amplifier should also be sufficient to support the intended flip angle and RF pulse shape with the employed transmission RF coil(s) for 13C. Most studies to date use relatively low flip angles (< 90 degrees) for HP 13C in order to preserve polarization for time-resolved imaging. The capability to receive 13C signal on multiple channels is also desirable to increase SNR, as discussed further in the “RF coils” section.

The choice of magnetic field strength is primarily dependent on the metabolites’ frequency separation due to chemical shift dispersion and 1H imaging. High field strengths do not enhance hyperpolarized 13C signal as they do for 1H because the signal strength in a HP experiment relies on manipulating the population of quantum energy states outside of the MRI scanner.

However, the injected HP 13C-pyruvate and its metabolic products have greater frequency separation at higher fields, and it may thus be easier to separate and quantify these resonances at higher fields. This comes at the cost of a reduction in the achievable T2* and often reduced T1. As the initial polarization is independent of the imaging field strength it has been proposed that the increased T2* at 1.5T can potentially be exploited to increase SNR by adapting the acquisition bandwidth or reduce off-resonance imaging effects in cases when the decay of the transverse magnetization is dominated by T2* (73). In practice, 3T has been used in all published human 13C-pyruvate studies surveyed (Supporting Table S1), and comprises the majority of scanners currently in use for human studies (Table 3). A field strength of 3T is well-suited for 1H MRI anatomical reference and correlative imaging.

Stronger and more rapidly slewing magnetic field gradients support more rapid spatial encoding, particularly for metabolite-specific single-shot imaging using echo-planar imaging (EPI) or spiral imaging (See “Acquisition and Reconstruction”). Although the spatial resolution acquired for HP 13C imaging is typically much coarser than for 1H MRI, the factor of ~4 in gyromagnetic ratio leads to the same reduction factor in performance of the gradient system, so 13C experiments are potentially more limited by gradient hardware performance. To date, all human studies have used the commercially-available integrated gradient systems provided in clinical MRI scanners.

Optimization of scanner design has understandably focused on minimization of artifacts in 1H MRI, where devices such as room lights, the gradient amplifiers, and the motors driving the patient bed are checked to ensure that they do not produce RF interference at the 1H frequency, but artifacts may arise at other frequencies. Eddy current compensation is also not always appropriately adjusted for nuclei at other frequencies (74). In order to optimize for 13C, many sites have performed checks on phantoms for RF interference, gradient artifacts, and eddy currents (74), including the use of post-hoc gradient impulse response function characterisation and correction, and some vendors have fixed these issues as well.

Rf Coils

For HP 13C imaging studies in humans, RF coils for both 1H and 13C nuclei are needed, with 1H MRI providing an anatomical reference for registration and optional additional multiparametric MRI readouts. At the Larmor frequency of 13C nuclei, the relative contributions from coil noise compared to sample noise increase compared to 1H (73,75), although sample noise still is likely the dominant contributor for human-sized coils at 32.1MHz - the resonance frequency of 13C nuclei at 3T.

The key requirement for human 13C-pyruvate RF coils are that the coil geometry and sensitive volume must cover the volume of interest in the subject. Table 2 and Figure 4 shows coil configurations that have been used and optimized for applications in different anatomic regions.

Volume resonators are most commonly used for transmit, as they surround the subject to

Provide B1 Transmit Across The Fov (B1

+). While 1H relies on a large birdcage (“body”) coil built into the scanner, 13C transmit coils must be placed inside the bore. This takes up valuable space within the magnet, and also has led to the use of designs with relatively inhomogeneous

B1

+. Many human studies have used Helmholz pair resonators for transmit, including the “clamshell coil”, which has a notably inhomogeneous B1

+ Profile But Has Been Used Because Of

relatively easy integration into the scanner bore. B1

+ Variation Results In Variations In The Flip

angles that control the use of the hyperpolarized magnetization and creates errors in common HP metrics (9,76). The exception are head coils, where birdcage designs with highly

Homogeneous B1

+ can be placed around the head while easily fitting inside the bore. As with 1H MRI, higher SNR can typically be achieved by smaller receive coil elements, such as surface coils or phased arrays, and the majority of 13C receive coils used have layouts similar to 1H phased arrays.

RF coil quality control is important to ensure proper functioning of the coils to provide consistent imaging quality, especially with limited natural abundance 13C signal in vivo. It typically involves 1) a physical integrity check of the coil cables and connectors and 2) phantom SNR tests to check the coil’s performance and to monitor it over time (see Phantoms below). An useful reference for RF coil quality control is outlined in the MRI accreditation program of the American College of Radiology (77) and can be adapted for 13C coils.

Notably, configurations for brain and prostate studies used dual-tuned 1H/13C coil designs, which greatly simplify workflow and registration of 1H and 13C images, as no switching of coils is needed.

(1)

Table 2: RF coil configurations reported for human HP [1-13C]pyruvate studies.

Tx = Transmit

coil, RX = receive coil. The commonly used “clamshell” TX coil is a Helmholz pair design. For 1H RF configurations, all used the Body coil for TX unless otherwise noted, and “repositioned” indicates the 13C coil was removed for 1H imaging. One representative reference is listed for each configuration. The RF coil configurations reported in the reviewed papers are shown in Supporting Table S1.

Figure 4: Examples of RF coil configurations used for human HP [1-13C]pyruvate brain studies. (A,B) 13C Clamshell TX (Helmholz pair) and 2× 4-channel paddle RX arrays. (C) 13C Birdcage volume TX and 32-channel RX array (RX array slides into TX coil). (D) 13C Birdcage volume TX and 24-channel RX array, combined with a 1H 8-channel RX array. Image reproduced with permission from Ref (16).

Phantoms

Since hyperpolarized magnetization is non-renewable, phantoms containing 13C nuclei are important to: 1) test the multi-nuclear capabilities of the imaging system, including all parts of the signal excitation and receive chain; 2) perform calibration measurements before a scan with hyperpolarized nuclei; and 3) perform necessary pre-scan adjustments (see “Prescan Calibration” section). The phantoms currently in use are listed in Table 3. Their composition must provide sufficient 13C signal, with additional considerations of conductivity, stability, chemical shift(s) present, potential for dynamic imaging, and cost. The phantom geometries are typically either compact, in order to be used alongside the subject during a HP scan, or large enough to mimic the inner volume of a RF coil for system testing.

One popular compact design contains enriched 13C-urea at high concentration, typically 8 M, which provides a single resonance, placed inside a small container ~1 mL. The most common recipe mixes 13C-urea in a 90% water/10% glycerol solution, with glycerol used to increase the urea solubility and doping with a Gd-based contrast agent to shorten T1 which increases the potential SNR per unit time. For example, when Dotarem is added at a 3:1000 volume ratio the 13C-urea T1 is around 500 ms and T2 is around 100 ms. However, when testing pulse sequences influenced by T1 and T2, doping should be used carefully. This phantom is suitable for frequency calibration, transmit gain calibration, sequence testing, and as a fiducial marker when placed next to a patient. However, enriched 13C-urea has a relatively high cost compared to natural abundance compounds.

For larger volumes (>100 ml), the phantoms most often used contain undiluted ethylene glycol, glycerol, or dimethyl silicone. These compounds have sufficiently high carbon concentrations to provide sufficient 13C signal even with the 1.1% natural abundance of 13C. These larger phantoms matching the inner volume of an RF coil are useful for coil testing, including transmit

+) And Receive (B1

-) coil profile mapping, as well as to mimic acquisitions using in vivo FOV requirements. In this case, size and conductivity should match the expected subject size in order to mimic coil loading and get a realistic estimation of B1+. Large-volume natural abundance urea phantoms have also been used by some sites, but suffer from higher conductivity compared to biological tissues. Typically, it is easier to increase the conductivity and hence coil loading of the non-conductive phantom by adding NaCl to match physiological loading (16,78).

Dynamic phantoms that aim to mimic metabolite kinetics have also been developed (79–81), and have the potential to more closely mimic the HP experiment, but so far these are not widely used.

Prescan Calibration

Prior to performing an MRI acquisition, the so-called prescan procedure is used to set the shim parameters to maximize B0 homogeneity over the field of view (FOV) or a specific region of interest (ROI), the scanner center frequency (CF), the RF transmit gain, and the receiver gain.

While this calibration procedure is usually automated for 1H, the lack of sufficient natural abundance 13C signal prevents use of automated methods. (Although natural abundance 13C lipid signal has been detected, there are so far no reports on using this signal for prescan.) Table 3 shows current practices across sites.

Maximizing B0 homogeneity is independent of the nucleus and is therefore performed prior to 13C imaging using the 1H water signal and existing shimming tools, such as by a standard automated process (“Auto Shimming”) or using high order shimming routines. Similarly, the 13C CF can be calculated from the 1H CF using a predetermined scaling factor that depends on the target chemical shift (82). Another common approach used is to have a small, high-concentration 13C phantom, e.g. 8M 13C-urea, integrated in the RF coil or placed next to the scan subject (1). The reference frequency can also be based on real-time measurements after the HP injection but prior to imaging (83). Both the CF and B0 shimming are critical when using spectrally-selective RF pulses, as inmetabolite-specific imaging methods, where the desired excitation bandwidths are typically very narrow and frequency offsets can lead to a failure mode that is only apparent after injection.

The calibration of the RF transmit power is typically performed on a small, high-concentration 13C phantom placed near the region of interest during the scan or on a large 13C phantom of similar size and coil loading as the subject, prior to the subject scan. Reference power is often done by sweeping the power in a pulse-acquire sequence (53,62), or the Bloch-Siegert method (52,84). When using a small phantom, the location of the phantom, B1

+ Inhomogeneity As Well

as any shielding effects, e.g., when the phantom is integrated into a coil (1), may degrade the accuracy. Other methods include real-time Bloch-Siegert method measurements after the HP injection (83), and using the stronger natural abundance 23Na signal that is close enough to the 13C resonance frequency to be detected by 13C coils (82).

The receiver gain is predetermined, either systematically based on independent phantom measurements and assuming the dose and polarization of the HP compound is known prior to injection, or based on past HP imaging studies.

Power [Kw]

Phantom(s) - during study Phantom(s) - before study 13C Frequency

8

13C-bicarbonate doped with dimethyl silicone, various

Maximum Values

Table 3: Summary of the imaging systems, phantoms, and prescan procedures used at sites currently performing HP 13C-pyruvate human studies. These were obtained from a survey of all sites performing clinical trials with HP [1-13C]pyruvate. *Previously performed studies with a Siemens 3T Tim Trio. The imaging systems, phantoms, and prescan procedures reported in the reviewed papers are shown in Supporting Table S1.

Summary

Commercially available 3T MRI systems are by far the most commonly used for human HP 13C-pyruvate studies, although a systematic investigation of the impact of B0 has only recently been investigated (73). The multi-nuclear RF transmit and receive chain has proven sufficient for current acquisition strategies, although many sites have observed artifacts due to RF interference, gradient interference, and residual eddy currents when operating at the 13C frequency. A variety of 13C RF coils, tailored for numerous anatomical targets, have been successfully demonstrated, with the main limitation that most transmit coils take up a lot of additional space inside the bore and provide relatively inhomogeneous B1

+ Profiles. The

phantoms used have converged into generally 2 categories - small phantoms containing 13C-enriched compounds that can be used during the study and human-sized phantoms containing compounds with high carbon concentrations but without 13C enrichment that are used to test and calibrate the coils. There are no standardized compositions or geometry, and dynamic phantoms that recapitulate in vivo kinetics would be desirable but are still an emerging area. Prescan calibration procedures were not well defined in most publications, so we surveyed individual sites to determine current practices. Calibration procedures for the B0 field (13C CF and shimming) for most sites take advantage of 1H signal and methods, while methods

For Calibration Of B1

+ is more variable across sites, likely a reflection of remaining challenges in how to perform this calibration. Standardization of both phantoms and calibration procedures would synergistically improve the robustness and reproducibility of HP 13C studies.

Acquisition And Reconstruction

Data acquisition strategies in human HP [1-13C]pyruvate MRI studies must account for multiple chemical shifts, efficiently utilize the non-renewable HP magnetization, and acquire data quickly relative to metabolism and relaxation decay processes. These studies require spectral encoding to separate metabolites, necessitating pulse sequences that efficiently encode up to 5D data (3 spatial + 1 spectral + 1 temporal dimension). RF pulses must efficiently sample without immediately saturating the non-renewable HP magnetization, and sequences must acquire data quickly and be robust to both experimental and physiologic variation (e.g. B1

+ Inhomogeneity,

variation in perfusion) to ensure reproducibility and minimize scan-to-scan variability. This section covers current successful practices for data acquisition in human [1-13C]pyruvate studies, and accompanying 1H imaging, from different anatomic regions, including scan parameters and image reconstruction.

Acquisition And Reconstruction Methods

The acquisition methods used in human [1-13C]pyruvate studies can be classified into 3 categories: 1) MR spectroscopy or MR spectroscopic imaging (“MRS/I”), 2) chemical shift encoding methods, and 3) metabolite-specific imaging (Fig. 5).

Mrs/I Methods Specifically

resolve a spectrum that can be analyzed to extract expected as well as unexpected resonances, making this approach very robust. It was used in many initial studies (1).

Chemical Shift

encoding methods, most commonly the Iterative Decomposition of water and fat with Echo Asymmetry and Least-squares estimation (IDEAL) method, use imaging sequences acquired with multiple TEs and rely on a model-based separation of expected chemical shifts (85).

Metabolite-specific imaging methods use specialized RF pulses that are spatially and spectrally selective to excite individual metabolites which are then typically imaged with fast k-space trajectories such as echo planar imaging (EPI) or spirals (86).

Their Application To Different

organ systems is described below. The image reconstruction methods used in human [1-13C]pyruvate studies have typically been conventional methods (e.g. FFT, non-uniform FFT, or equivalent). The incorporation of accelerated imaging and advanced reconstruction methods including parallel imaging (4,57,87) and compressed sensing (7) has also been applied in human studies for improved spatial resolution, temporal resolution and coverage, but have the potential for additional artifacts as well as SNR losses due to ill-conditioning of the reconstruction (e.g. g-factor).

The Majority Of

published studies do not use accelerated imaging indicating the resolution and coverage achievable without acceleration is currently adequate for successful data collection. Performing coil combination, even with fully sampled data has also been shown to have specific challenges for HP human images: using naive sum-of-squares methods suffer from high noise amplification in the relatively low SNR regime of HP [1-13C]pyruvate (compared to 1H), motivating several HP 13C-specific methods that include data-driven coil sensitivity estimation which have shown obvious improvements over sum-of-squares (11).

More recently denoising techniques have been applied as post-processing of human HP data(41,42,44). The techniques applied are based on spatial-temporal singular value decomposition for unsupervised estimation of signal and noise components. They have shown improvements in apparent SNR in the brain and liver, while care must be taken to choose parameters such as the rank threshold to avoid oversmoothing and overfitting to the estimated signal components.

Prostate Studies

Prostate cancer was the first human application of HP [1-13C]pyruvate (1), and data was acquired with MRS/I methods: 1D dynamic MRS, single-slice 2D dynamic echo-planar spectroscopic imaging (EPSI), and single time point 3D EPSI. Advances in imaging strategies led to the development and application of new acquisition schemes, including undersampled 3D EPSI with compressed-sensing (7), model-based chemical shift encoding methods that use a priori information (47,59), and metabolite-specific EPI (10), all of which can provide volumetric whole-organ coverage and dynamic acquisitions.

The pyruvate bolus arrival in the prostate can vary by ± 10 s between patients, necessitating dynamic imaging to reliably and consistently capture the pyruvate bolus (18). For this reason, all currently ongoing studies acquire dynamic data. While MRS/I, chemical shift encoding, and metabolite-specific imaging can all achieve dynamic imaging, chemical shift encoding and metabolite-specific imaging provide greater dynamic and volumetric coverage (85). For scan prescriptions, the FOV is designed to provide full prostate coverage and typically to match the orientation of the anatomic imaging used for registration. Flip angles used in current studies are constant through time, as quantification with a variable-through-time flip scheme is highly sensitive to bolus timing (8) and errors in the RF transmit (B1 +) field (76).

Heart Studies

Data acquisition methods for 13C imaging in the heart must be designed to meet the demands of significant cardiac motion and blood flow. To cope with the periodic cardiac motion, most human heart studies to date used gating to the diastolic window, the longest cardiac cycle interval, which has reduced motion (2,22,28,30,35,36,38,45,52). The duration of the diastolic window limits the available data sampling time, making cardiac acquisitions the most time-constrained of the HP 13C MRI applications. The most common acquisition approach is metabolite-specific imaging with spiral k-space trajectories (2). Their single-shot imaging capability makes these methods particularly robust to motion effects. Furthermore, spiral k-space trajectories provide rapid k-space coverage and relatively benign flow and motion artifacts. The majority of studies have used 2D multi-slice acquisitions, but 3D encoding has also been used successfully (35).

Brain Studies

For HP 13C MRI of the human brain, the majority of studies have also used 2D (slice selective) acquisitions (10–12,14,16,28,33,40,41,44,51,53,60), with a trend toward volumetric coverage using 2D multi-slice metabolite-specific imaging. 3D metabolite-specific imaging of the whole brain, with phase encoding of the slice direction (34,57), has been shown to provide similar SNR efficiency (88) compared with multislice imaging. A number of studies have employed MRS/I (5,6,29,31–33,50,55) resulting in a spectrum from each voxel, which has the advantage of not requiring a priori information about which peaks to encode. This was important in early brain studies when it was not known which peaks would be detectable. Chemical shift encoding, using a set of images with different echo times and an iterative reconstruction of the individual resonances (i.e. the IDEAL approach (85)), has also been used (12,49,54), with the drawback that coverage in the slice direction was limited due to the time required to acquire multiple echo time images.

Abdomen And Breast Studies

The fundamental approaches to data acquisition and reconstruction in the abdomen and breast are largely similar to the aforementioned applications, but demand attention to particular challenges associated with these anatomic regions, especially relating to respiratory motion.

Although it has been shown that a basic 2D MRSI approach based on phase encoding and FID readout can be successfully applied for HP 13C imaging in breast (15) and kidney (13), major advantages in terms of spatiotemporal resolution and coverage have been realized using tailored approaches based on metabolite-specific imaging (43,62) and chemical shift encoding (43), which have facilitated multi-slice or 3D dynamic acquisitions over large FOVs in the abdomen (4,37,46).

The significant respiratory motion encountered in these regions can directly blur 13C images, and has further favored these rapid acquisition strategies. Motion also degrades B0 homogeneity, which can shift frequency-selective excitation profiles and introduce artifacts into rapid imaging readouts. This makes accurate determination of the acquisition center frequency and shimming essential in these regions which often cover large FOVs. (See “Prescan Calibration” section for more information). In some studies, breath-holding was used to minimize motion effects and enforce frame-to-frame data consistency (42). A pragmatic and reasonably effective approach for dealing with respiratory motion during 13C data acquisition is an initial breath-hold (as long as can be tolerated), followed by free-breathing (46,62).

1H Imaging

Collection of 1H imaging data is essential both for prescribing the 13C acquisition and for interpretation of the resulting 13C data. Multi-planar 1H scouts are acquired prior to 13C acquisition to enable graphical prescription of the 13C imaging region. All human HP 13C-pyruvate imaging studies acquire conventional MRI scans (e.g. T1- and T2-weighted volumes) for anatomic reference, aiming to cover at least the full 13C FOV. Acquiring these anatomic scans as close as possible to the time of 13C imaging (immediately before or after) minimizes potential misregistration between the data sets. Depending on the application, other advanced 1H sequences are also acquired (e.g. diffusion-weighted imaging for cancer imaging).

When contrast-enhanced data is acquired, it is done after 13C imaging, as paramagnetic contrast agents will accelerate 13C relaxation.

Reported Study Parameters

Figures 5 and 6, and Supporting Table S2 shows the reported acquisition study parameters for human HP [1-13C]pyruvate studies published as of September 2022. Figure 5 shows a mixture of MRS/I, metabolite-specific imaging, and chemical shift encoding methods have been successfully used, where spectroscopy-based methods have become less prevalent in recent studies. Figure 6 shows the acquisition timing, including the important start time and interval/temporal resolution, is quite variable across studies.

Figure 5: Acquisition methods used in published HP [1-13C]pyruvate human studies published up to September 2022, classified into: MR spectroscopy and spectroscopy imaging (MRS/I); chemical shift encoding methods, such as IDEAL, that use multiple TEs and model-based reconstructions; and metabolite-specific imaging methods that use spectrally-selective excitation to image a single resonance at a time.

Figure 6: Temporal acquisition characteristics reported in HP [1-13C]pyruvate human studies published up to September 2022. (a) Reported referencing of acquisition start times.

(B)

Acquisition start times reported when using dynamic imaging and when timing was reported relative to the end of the injection. (c) Temporal resolutions. “Not Applicable” indicates dynamic imaging was not used.

Summary

Three general categories of acquisition strategies have been used successfully for human HP 13C-pyruvate studies: MRS/I, model-based chemical shift encoding (e.g. IDEAL) methods, and metabolite-specific imaging methods. These have enabled successful studies in the prostate, heart, brain, abdomen, and breast. Recent studies increasingly have used the imaging-based strategies of metabolite-specific imaging and chemical shift encoding which are the fastest methods, although a heads-to–head comparison between techniques has not been performed.

Metabolite-specific imaging is quite popular because of its speed and compatibility with single-shot imaging, but is sensitive to B0 field variations and thus requires careful calibrations. Nearly all studies surveyed acquired data dynamically, allowing measurement of the bolus and metabolite kinetics. The exact timings and associated flip angles vary quite widely across reported studies, with no consensus yet as to how to choose these parameters. Image reconstruction is typically done directly using Fourier Transform methods, and accelerated imaging strategies are uncommon.

Data Analysis And Quantification

This section covers the analysis of data from human HP [1-13C]pyruvate studies, including modeling and metrics, visualization, as well as considerations for how to store data and metadata. Depending on study design, the analysis may need to give quantitative or semi-quantitative output reflecting a biological process or may just reflect a contrast between different regions of interest for quantitative evaluation.

Metrics

Figure 7: HP [1-13C]pyruvate raw data (A) have typically been quantified using four categories of metrics depending on the acquisition. Data acquired as a single time point are often quantified using normalized metabolite images or metabolite ratios (B). Dynamic data can be quantified using normalized metabolite images or metabolite ratios (B), or with metabolite timings such as time-to-peak (TTP) or pharmacokinetic (PK) models (C). The latter two require the data to be time-resolved. [1-13C]alanine and 13C-bicarbonate are analyzed similarly to [1-13C]lactate but omitted here for display.

Metabolite images are commonly used as summary metrics for HP MRI data, often including some form of normalization as well as summed over time as an area under the time curve (AUC) (17). These are analogous to the visual evaluation that is most used for routine clinical work (89,90). In these metabolite images, we expect that the [1-13C]pyruvate AUC signal is predominantly weighted towards perfusion and uptake, while [1-13C]lactate, [1-13C]alanine and 13C-bicarbonate AUCs represent metabolic conversion. The strength of this approach lies in its simplicity and relatively few underlying assumptions. Limitations to the use of single-metabolite images or AUCs include sensitivity to inhomogeneous coil profiles (57,87,91), the acquisition strategy and acquisition parameters, pyruvate polarization and concentration level, and signal relaxation rates (92). Further, the reader must be careful to interpret all the images in conjunction to better understand the underlying biology; for example, increased [1-13C]lactate in the presence of decreased [1-13C]pyruvate delivery can have a very different meaning compared to increased [1-13C]lactate with increased [1-13C]pyruvate delivery.

In an attempt to address variations in coil sensitivity, polarization level, and pyruvate delivery, AUC images are often computed by normalizing to a specified parameter, such as the maximum pyruvate or average lactate signals, or presented as a ratio such as lactate/pyruvate or divided by “total Carbon” - the sum total of HP 13C signal observed across all metabolites. The AUC ratios between metabolites and pyruvate are proportional to the corresponding forward kinetic rates (81,93), but are not directly comparable to rate constants when magnetization loss rates (e.g. relaxation and losses due to signal excitation) differ between studies. Similarly, the ratios between the produced metabolites (e.g. bicarbonate/lactate) can reflect the balance between downstream metabolic pathways (12,55). Care must be taken to consider how AUC images are calculated and normalized before comparing values between studies.

To further quantify the interpretation, pharmacokinetic (PK) modeling approaches were developed to compute the apparent kinetics of pyruvate-to-metabolite exchange (92,94–99). These yield semi-quantitative to quantitative apparent rate constants, given in s-1. Some models require a vascular input function, while others avoid this requirement (95). PK models can explicitly account for acquisition-specific details such as excitation angle and repetition time, and thus may reduce the effects of these details on quantification. An input-less model, provided in the Hyperpolarized-MRI-Toolbox (https://github.com/LarsonLab/hyperpolarized-mri-toolbox) (100) and thus frequently employed for human data, has been shown to fit well and robustly to prostate and brain data (8,20). PK models are quantitative in nature, arguably provide more relevant biological information (8,20), and appear to be reproducible across sites (51). However, rate constants derived from PK models are still apparent rates, and likely do not reflect a single biological characteristic.

Some additional considerations include whether complex or magnitude data is used, as the noise behaviors will impact the analysis differently. Additionally, cut-off thresholds or other criteria may be used to identify and avoid voxels with insufficient SNR before analysis to improve robustness (20,41).

Regardless of the analysis approach, the underlying biology is not always clearly represented by the data; instead, the metrics may be influenced by perfusion, barrier permeability, intercellular shuttles, enzyme activities, co-substrate concentrations, or combinations thereof, depending on the organ and disease of interest (19,43,94,101–103). This may be addressed by incorporating complementary information. As an example, HP 13C pyruvate data is influenced by perfusion, and thus addition of perfusion MRI could be important for interpretation (98,104,105).

All the methods outlined above have been explored in clinical studies, described in Supporting Table 3 and summarized in Figure 8. As of September 2022, approximately 52% of studies involving human subjects report rate constants derived from a PK model with a few different models reported. A nearly equal fraction (51%) of the studies report AUC ratio values.

Approximately 66% of these studies report metabolite-specific images or AUC values. About 40% report SNR values; this metric is particularly frequent in manuscripts that describe technical developments for clinical HP MRI. Approximately 16% of these studies summarize model-free metrics, and 10% report measurements from a single timepoint. Most studies report a combination of quantities.

Figure 8: Reported metrics used for analysis in HP [1-13C]pyruvate human studies published up to September 2022.

Visualization

A wide variety of approaches have been used for visualizing data from human HP 13C-MRI studies. The challenges and practical considerations are: 1) choosing the appropriate metrics to display, 2) how to encode the parameters (e.g. the colormap), and 3) choosing how to provide anatomical context and other multi-parametric data. The choice of visualization also depends on the goal which could be for diagnostic interpretation, but also quality control, reproducibility among readers and publication.

Metrics

The choice of HP 13C metrics is described in detail above. At this stage in HP 13C development where there is no standardized metric, often a combination of metabolite images and ratios or PK model parameters are shown.

Parameter Encoding

The mapping function chosen should provide an adequate, often quantitative, impression of the parameter mapped. There is a consensus in the visualization field that perceptually uniform maps are best suited to visualize continuous parameters, like the greyscale typically used by radiologists as well as other monochrome (black to blue) and color ranges (fire-type, rainbow-type) (106,107). Multi-color heatmaps have been the most frequently employed method for HP 13C data, while greyscale has infrequently been used but it ensures there is no coloring-based bias as well as facilitating later reuse (Fig. 9a). Among the color schemes employed in the clinical HP 13C literature, fire-type scheme seems to be the most common [similar to “Plasma” or “Inferno” in matplotlib.org]. Next most commonly employed is the rainbow-type scheme [similar to “Rainbow” in matplotlib.org].

Anatomical Context

HP MRI faces the challenge that it does not necessarily depict the anatomical features, similar to PET, and thus requires an anatomical reference. Most often, a grayscale anatomical image is overlaid with a HP colormap (Fig. 9c,d). This approach is very intuitive, but can skew perception as the grey-scale anatomical reference may affect the brightness of the HP data (e.g. signal in the skull). This bias does not occur when showing adjacent maps (Fig. 9a, b). Here, anatomical outlines may help to provide reference (Fig. 9b).

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