Accuracy of Prostate Segmentation on Synthetic MR Images Generated from CT Scans Using a Novel Generative Adversarial Network for High-Dose-Rate Prostate Brachytherapy

Abstract

<h3>Purpose/Objective(s)</h3> For patients undergoing prostate HDR brachytherapy at our institution, both CT and MRI scans are acquired to identify catheters and delineate the prostate, respectively. However, acquiring both scans increases the time and hospital resources needed for treatment. We hypothesized that a synthetic MRI (sMRI) could be generated with sufficiently high soft-tissue contrast from the planning CT using a novel Generative Adversarial Network (GAN) framework with the goal to use sMRI to delineate the prostate without requiring the MRI. <h3>Materials/Methods</h3> Our newly developed PixCycleGAN, a hybrid of Pix2Pix and CycleGAN to maximize the advantage of Pix2Pix and to add the strength of CycleGAN training with paired CT-MRI datasets acquired on the same day for previously treated HDR prostate patients. PixCycleGAN is composed of two Residual Network generators and four discriminators with two transformation cycles. To train PixCycleGAN, 58 paired CT and T2-weighted MRI datasets without metal or motion artifacts were selected. Using 10 independent datasets, the image quality of sMRI was evaluated using metrics including the mean absolute error (MAE), mean squared error (MSE), Peak Signal-to-Noise Ratio (PSNR), and Structural Similarity Index (SSIM). The accuracy of prostate segmentation was evaluated by having radiation oncologists manually delineate the prostate on real MRI (rMRI) and sMRI images. All rMRI and sMRI images were presented in a random order to reduce potential bias in segmentation. The dice similarity coefficient (DSC) and Hausdorff distance (HD) were evaluated for the prostate contours delineated on sMRI vs. rMRI. To estimate interobserver variability (IOV), DSC and HD of prostate contours independently delineated on rMRI by two radiation oncologists were calculated. <h3>Results</h3> Qualitatively, sMRI images showed enhanced soft-tissue contrast on the boundary of the prostate and rectum compared to the CT scans. In addition, sMRI contained features from both MRI and CT showing clear visualization of the boundary of the prostate and the catheters. Image quality metrics were: MAE=0.13±0.03, MSE=0.03±0.01, PSNR=69.2±1.42 (dB), SSIM=0.78±0.07. The DSC of the prostate contour was 0.85±0.05 for sMRI vs. rMRI and 0.84±0.07 for IOV (p=0.13). However, the HD for sMRI vs. rMRI (7.77±1.83 mm) was smaller than the HD for IOV (9.53±2.74 mm). <h3>Conclusion</h3> We developed a novel PixCycleGAN framework to generate a sMRI from the planning CT which depicted enhanced soft-tissue contrast at the boundaries of the prostate. The agreement between DSC of the prostate on sMRI vs. rMRI and DSC of IOV shows that the accuracy of prostate segmentation on sMRI is within the segmentation variation on rMRI between two radiation oncologists. In the future, we will evaluate dosimetric impact of using sMRI in prostate segmentation for HDR treatment planning.