Voxel-wise correlation of PET/CT with multiparametric MRI and histology of the prostate using a sophisticated registration framework

Abstract

Objectives To develop a registration framework for correlating positron emission tomography/computed tomography (PET/CT) images with multiparametric magnetic resonance imaging (mpMRI) and histology of the prostate, thereby enabling voxel‐wise analysis of imaging parameters.

Patients and Methods In this prospective proof‐of‐concept study, nine patients scheduled for radical prostatectomy underwent mpMRI and PET/CT imaging before surgery. One had PET imaging using 18F‐fluoromethylcholine, five using 68Ga‐labelled prostate‐specific membrane antigen (PSMA)‐HBED‐CC (PMSA‐11), and three using a trial 68Ga‐labelled THP‐PSMA tracer. PET/CT data were co‐registered with mpMRI via the CT scan and an in vivo three‐dimensional T2‐weighted (T2w) MRI, and then co‐registered with ground truth histology data using ex vivo MRI of the prostate specimen. Maximum and mean standardised uptake values (SUVmax and SUVmean) were extracted from PET data using tumour annotations from histology, and Kolmogorov–Smirnov tests were used to compare between tumour‐ and benign‐voxel values. Correlation analysis was performed between mpMRI and PET SUV tumour voxel values using Pearson's correlation coefficient and R2 statistics.

Results PET/CT data from all nine patients were successfully registered with mpMRI and histology data. SUVmax and SUVmean ranged from 2.21 to 12.11 and 1.08 to 4.21, respectively. All patients showed the PET SUV values in benign and tumour voxels were from statistically different distributions. Correlation analysis showed no consistent trend between the T2w or apparent diffusion coefficient values and PET SUV. However, parameters from dynamic contrast‐enhanced (DCE) MRI including the maximum enhancement, volume transfer constant (Ktrans), and the initial area under the contrast agent concentration curve for the first 60 s after injection (iAUGC60), showed consistent positive correlations with PET SUV. Furthermore, R2* values from blood oxygen level‐dependent (BOLD) MRI showed consistent negative correlations with PET SUV‐voxel values.

Conclusion We have developed a novel framework for registering and correlating PET/CT data at a voxel‐level with mpMRI and histology. Despite registration uncertainties, perfusion and oxygenation parameters from DCE MRI and BOLD imaging showed correlations with PET SUV. Further analysis will be performed on a larger patient cohort to quantify these proof‐of‐concept findings. Improved understanding of the correlation between mpMRI and PET will provide supportive information for focal therapy planning of the prostate.