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Background and purpose: The diagnostic accuracy of new imaging techniques requires validation, preferably by histopathological verification. The aim of this study was to develop and present a registration procedure between histopathology and in-vivo magnetic resonance imaging (MRI) of the prostate, to estimate its uncertainty and to evaluate the benefit of adding a contour-correcting registration.

Materials and methods: For twenty-five prostate cancer patients, planned for radical prostatectomy, a 3D-printed prostate mold based on in-vivo MRI was created and an ex-vivo MRI of the specimen, placed inside the mold, was performed. Each histopathology slice was registered to its corresponding ex-vivo MRI slice using a 2D-affine registration. The ex-vivo MRI was rigidly registered to the in-vivo MRI and the resulting transform was applied to the histopathology stack. A 2D deformable registration was used to correct for specimen distortion concerning the specimen's fit inside the mold. We estimated the spatial uncertainty by comparing positions of landmarks in the in-vivo MRI and the corresponding registered histopathology stack.

Results: Eighty-four landmarks were identified, located in the urethra (62%), prostatic cysts (33%), and the ejaculatory ducts (5%). The median number of landmarks was 3 per patient. We showed a median in-plane error of 1.8 mm before and 1.7 mm after the contour-correcting deformable registration. In patients with extraprostatic margins, the median in-plane error improved from 2.1 mm to 1.8 mm after the contour-correcting deformable registration.

Conclusions: Our registration procedure accurately registers histopathology to in-vivo MRI, with low uncertainty. The contour-correcting registration was beneficial in patients with extraprostatic surgical margins.

Background: Multiparametric magnetic resonance imaging (mpMRI) and positron emission tomography (PET) are widely used for the management of prostate cancer (PCa). However, how these modalities complement each other in PCa risk stratification is still largely unknown. We aim to provide insights into the potential of mpMRI and PET for PCa risk stratification.

Methods: We analyzed data from 55 consecutive patients with elevated prostate-specific antigen and biopsy-proven PCa enrolled in a prospective study between December 2016 and December 2019. [68Ga]PSMA-11 PET (PSMA-PET), [11C]Acetate PET (Acetate-PET) and mpMRI were co-registered with whole-mount histopathology. Lower- and higher-grade lesions were defined by International Society of Urological Pathology (ISUP) grade groups (IGG). We used PET and mpMRI data to differentiate between grades in two cases: IGG 3 vs. IGG 2 (case 1) and IGG ≥ 3 vs. IGG ≤ 2 (case 2). The performance was evaluated by receiver operating characteristic (ROC) analysis.

Results: We find that the maximum standardized uptake value (SUVmax) for PSMA-PET achieves the highest area under the ROC curve (AUC), with AUCs of 0.72 (case 1) and 0.79 (case 2). Combining the volume transfer constant, apparent diffusion coefficient and T2-weighted images (each normalized to non-malignant prostatic tissue) results in AUCs of 0.70 (case 1) and 0.70 (case 2). Adding PSMA-SUVmax increases the AUCs by 0.09 (p < 0.01) and 0.12 (p < 0.01), respectively.

Conclusions: By co-registering whole-mount histopathology and in-vivo imaging we show that mpMRI and PET can distinguish between lower- and higher-grade prostate cancer, using partially discriminative cut-off values.