MRI Guided Procedure Planning and 3D Simulation for Partial Gland Cryoablation of the Prostate: A Pilot Study

Abstract

Purpose: This study reports on the development of a novel 3D procedure planning technique to provide pre-ablation treatment planning for partial gland prostate cryoablation (cPGA).Methods: Consecutive patients with magnetic resonance imaging (MRI)-visible (PI-RADS v2 score ³ 3) and biopsy confirmed prostate cancer undergoing partial gland cryoablation (cPGA) (n=20) were prospectively enrolled in an IRB approved study investigating advanced methods of data visualization for treatment planning. All patients enrolled in the study underwent image segmentation of the prostatic capsule, index lesion, urethra, rectum, and neurovascular bundles based upon multi-parametric MRI data. Segmented imaging data were viewed in 3D file format in computer-aided design (CAD) software, and virtual cryotherapy probes with -40°C isotherm volumes were created. Pre-treatment 3D prostate cancer models derived from MRI data were utilized to predict the number of and placement of cryotherapy probes to achieve confluent treatment volume. Treatment efficacy was measured with 6 month post-operative MRI, serum prostate specific antigen (PSA) at 3 and 6 months, and treatment zone biopsy results at 6 months were evaluated. Outcomes from 3D planning were compared to outcomes from a series of 20 patients undergoing cPGA using traditional 2D planning techniques.Results: The number of cryotherapy probes utilized matched the 3D plan in 16/20 (80%) of patients. 3D planning predicted a greater number of cryoprobes than 2D planning. Treatment zone biopsy was performed in 13/17 patients in the 3D cohort and was negative in 12 of these (92.9%). For the 3D group, 6 month biopsy was not performed in 4 (20%) due to undetectable PSA, negative MRI, and negative MRI Axumin PET. For the group with traditional 2D planning, treatment zone biopsy was positive in 3/14 (21.4%) of the patients, p = 0.056). Conclusions: 3D prostate cancer models derived from mpMRI data provide novel guidance for planning confluent treatment volumes for cPGA. This study prompts further investigation into the use of 3D treatment planning techniques.