UCSF Hyperpolarized MR Seminar Summer 2019, Lecture #7 "EPSI" Lecturer: Hsin-Yu Chen Sponsored by the NIH/NIBIB-supported UCSF Hyperpolarized MRI Technology Resource Center (P41EB013598) https://radiology.ucsf.edu/research/labs/hyperpolarized-mri-tech

1. Image Analysis Techniques of Hyperpolarized
13C MRI in Clinical Study
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2. Challenges in Clinical Management of Prostate Cancer
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Hyperpolarized-13C Imaging of Treatment Responses on Prostate Cancer Patients using 3D Dynamic CS-
EPSI Techniques
2
Unmet needs include:
▪ Determining Aggressiveness
▪ Monitoring Treatment Response
J Kurhanewicz, DB Vigneron, Magnetic Resonance
Spectroscopy of Prostate Cancer (2016)
MM Shevchuk et al., "The
Pathology of Prostatic
Carcinoma", Springer (2012)
Multiparametric MRI (mp-MRI)
Biopsy

3. Data Handling Pipeline
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HP-13C Human
Data Acquisition
Reconstruction and
Pre-processing
Quantitative
Data Analysis
• Hardware and Coils
• Pulse Sequences
• Imaging Resolution
• FOV Coverage
• Flip Angle Strategy
• Noise Pre-whitening
• Receiver Correction
• Transmitter Correction
• Coil Combination
• Peak Quantification
• Image Display
• SNR Masking
• ROI Analysis
• kPL Estimation
• Bolus Dynamics

4. Processing HP-13C Prostate Data
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5. Peak Quantification
▪ Magnitude data follows Rician noise model
▪ Phased data follows Gaussian noise model
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6. Phased Detection of Spectra
▪ Phased spectrum has zero-mean Gaussian noise
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Phased Spectrum

7. Phase Correction of HP-13C Spectra
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Nonlinear RF
Phase Correction Phase Correction
1st-order
Phase Correction
0th-order
Raw Spectra
On a peak-by-peak
basis

8. Other Quantification Techniques
▪ Lorentzian line fit
▪ LCModel type fit
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O’Haver et al., University of Maryland (1997)

9. Receiver Correction
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Noworolski et.al., JMR (2010); Chen et al., ISMRM (2018)
Receiver Profile
▪ Receiver profile of the endorectal coil simulated using Bio-Savart law
▪ Coil landmarks registered based on T2-FSE images

10. Receiver Correction – Case Study
▪ 68 y/o patient presented with biopsy confirmed G 4+3 prostate cancer in 8/16
cores (20-90% involvement) with PSA 15.4. No prior MRI.
▪ Combined HP-13C + SOC mpMRI at UCSF on 3T.
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T2w
ADC

11. Receiver Correction – Case Study
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Pyruvate
Before
Lactate
Chen et al., ISMRM (2018)
After

12. Receiver Correction – Case Study
▪ Bilateral base and right midgland prostate cancer involving PZ+TZ.
▪ Bilateral SVI, tumor extension to bladder base.
▪ HP-13C + mpMRI can be management-changing!
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13. ▪ B1+ heterogeneity impacts quantification of metabolism
▪ B1+ map can be established from simulation or measurements
Transmitter Considerations
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“Clamshell” 13C Transmitter
Relative B1+
Original B1
+-insensitive
Chen et al., ISMRM (2017)
55Mn Fiducial Markers
Ohliger et al., ISMRM (2017)
Flip Angle Design

14. Image Display
▪ Wide variety of available tools
▪ SIVIC, OsiriX, brImage, ImageJ, MATLAB … and many more
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SIVIC OsiriX

15. Image Display
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brImage
OsiriX + ImageJ + MATLAB
▪ How would you like to show HP-13C images?
Pyruvate Lactate

16. Masking and ROIs
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0.100
0.075
0.050
0.025
0
(sec-1)
Pyruvate-to-Lactate kPL
1000
750
500
250
0
(AU)
Perfusion Maps
▪ Which biomarkers are we looking for?
▪ Metabolism-perfusion mismatch
Chen et al., Cancer Res. (2017)
SNR threshold = 3.5 SNR threshold = 5
0.03
0.02
0.01
0
(sec-1)
kPL

17. Masking and ROIs
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ROI analysis
▪ Statistics within each ROI

18. Quantification of Cancer Metabolism
▪ Pyruvate to lactate conversion kPL
▪ Accounts for metabolic exchange, variable flip angles & T1 relaxation
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0.030
0.025
0.020
0.015
0.010
(sec-1)
kPL
Maidens et al., IEEE Trans. Med. Imag.. (2018)

19. Summary
▪ No rocket science – the techniques are empirical and has plenty of flexibility.
▪ An iterative process between optimizing HP-13C acquisition, data processing
and image analysis.
▪ Develop different strategies based on the biomarkers of interest
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