Accuracy of tumor segmentation from multi-parametric prostate MRI and ¹⁸F-choline PET/CT for focal prostate cancer therapy applications

Background: The study aims to assess the accuracy of multi-parametric prostate MRI (mpMRI) and ¹⁸F-choline PET/CT in tumor segmentation for clinically significant prostate cancer. ¹⁸F-choline PET/CT and 3 T mpMRI were performed in 10 prospective subjects prior to prostatectomy. All subjects had a single biopsy-confirmed focus of Gleason ≥ 3+4 cancer. Two radiologists (readers 1 and 2) determined tumor boundaries based on in vivo mpMRI sequences, with clinical and pathologic data available. ¹⁸F-choline PET data were co-registered to T2-weighted 3D sequences and a semi-automatic segmentation routine was used to define tumor volumes. Registration of whole-mount surgical pathology to in vivo imaging was conducted utilizing two ex vivo prostate specimen MRIs, followed by gross sectioning of the specimens within a custom-made 3D-printed plastic mold. Overlap and similarity coefficients of manual segmentations (seg1, seg2) and ¹⁸F-choline-based segmented lesions (seg3) were compared to the pathologic reference standard. Results: All segmentation methods greatly underestimated the true tumor volumes. Human readers (seg1, seg2) and the PET-based segmentation (seg3) underestimated an average of 79, 80, and 58% of the tumor volumes, respectively. Combining segmentation volumes (union of seg1, seg2, seg3 = seg4) decreased the mean underestimated tumor volume to 42% of the true tumor volume. When using the combined segmentation with 5 mm contour expansion, the mean underestimated tumor volume was significantly reduced to 0.03 ± 0.05 mL (2.04 ± 2.84%). Substantial safety margins up to 11–15 mm were needed to include all tumors when the initial segmentation boundaries were drawn by human readers or the semi-automated ¹⁸F-choline segmentation tool. Combining MR-based human segmentations with the metabolic information based on ¹⁸F-choline PET reduced the necessary safety margin to a maximum of 9 mm to cover all tumors entirely. Conclusions: To improve the outcome of focal therapies for significant prostate cancer, it is imperative to recognize the full extent of the underestimation of tumor volumes by mpMRI. Combining metabolic information from ¹⁸F-choline with MRI-based segmentation can improve tumor coverage. However, this approach requires confirmation in further clinical studies.