MRI‐TRUS registration methodology for TRUS‐guided HDR prostate brachytherapy

Abstract

Purpose: High-dose-rate (HDR) prostate brachytherapy is an established technique for whole-gland treatment. For transrectal ultrasound (TRUS)-guided HDR prostate brachytherapy, image fusion with a magnetic resonance image (MRI) can be performed to make use of its soft-tissue contrast. The MIM treatment planning system has recently introduced image registration specifically for HDR prostate brachytherapy and has incorporated a Predictive Fusion workflow, which allows clinicians to attempt to compensate for differences in patient positioning between imaging modalities. In this study, we investigate the accuracy of the MIM algorithms for MRI-TRUS fusion, including the Predictive Fusion workflow.Materials and Methods: A radiation oncologist contoured the prostate gland on both TRUS and MRI. Four registration methodologies to fuse the MRI and the TRUS images were considered: rigid registration (RR), contour-based (CB) deformable registration, Predictive Fusion followed by RR (pfRR), and Predictive Fusion followed by CB deformable registration (pfCB). Registrations were compared using the mean distance to agreement and the Dice similarity coefficient for the prostate as contoured on TRUS and the registered MRI prostate contour.Results: Twenty patients treated with HDR prostate brachytherapy at our center were included in this retrospective evaluation. For the cohort, mean distance to agreement was 2.1 ± 0.8 mm, 0.60 ± 0.08 mm, 2.0 ± 0.5 mm, and 0.59 ± 0.06 mm for RR, CB, pfRR, and pfCB, respectively. Dice similarity coefficients were 0.80 ± 0.05, 0.93 ± 0.02, 0.81 ± 0.03, and 0.93 ± 0.01 for RR, CB, pfRR, and pfCB, respectively. The inclusion of the Predictive Fusion workflow did not significantly improve the quality of the registration. Conclusions:The CB deformable registration algorithm in the MIM treatment planning system yielded the best geometric registration indices. MIM offers a commercial platform allowing for easier access and integration into clinical departments with

Image-guided Raman spectroscopy navigation system to improve transperineal prostate cancer detection. Part 2: in-vivo tumor-targeting using a classification model combining spectral and MRI-radiomics features

“…HDR brachytherapy allows the delivery of a considerable dose of radiation to the tumor site using temporary implants while reducing the surrounding tissue involvement. 1 , 2 Although using transrectal ultrasound (TRUS)-guided biopsy is the standard of care, it can have up to 30% false-negative rates and does not allow in situ characterization. 3 , 4 It is clear that the efficiency of both techniques relies significantly on accurate localization of the tumor and needle.…”

“…Currently, mpMRI is used by physicians to report tumors (PIRADSv2.1 5 , 7 ) and plan interventions, but it also allows the extraction of quantitative features (radiomics), which could be used as biomarkers. 2 , 8 , 9 However, MRI presents certain limitations to guide interventions due to longer acquisition time, limited compatibility with surgical instruments, and cost. 1 , 10 Multimodal image registration is currently studied and used to take advantage of complementary information of TRUS and MRI to assist HDR brachytherapy and other tumor-targeted prostate interventions.…”