A multi-step coregistration protocol between 68Ga-HBED-CC-PSMA PET/CT and histopathology was implemented (Figure 1 ). In the first step, whole-mount prostate slices were coregistered to the ex-vivo CT in a manner similar to the procedure described by Grosu et al. 21 (link). We used a fixation device (localizer) consisting of a customized cuvette with 4-mm-spaced markers, filled with agarose in which the prostate was embedded and fixated. The basic edges (ventral, dorsal, left, right) of the resected prostate were marked with special ink to support orientation of the prostate in the agarose-filled cuvette. The aim was to position the prostate in a similar orientation as in in-vivo CT. After ex-vivo CT scan of the localizer, the pathologic slices were cut perpendicular to the urethra and along the localizer markers using a customized cutting device (Supplementary Figure 1 ). Parallel 4-mm step-sections were cut in the same angle as the ex-vivo CT slices. PCa and non-malignant tissue was delineated on each histopathological slice by an experienced pathologist. Histopathological slices were than manually matched to the ex-vivo CT, using MITK software (MITK Workbench 2014.10.00, German cancer research center, Germany) under guidance of the 4-mm grid. The contours of PCa (PCa-histo) and non PCa (NPCa-histo) were manually transferred to corresponding CT slices. In the next step, a careful manual coregistration with additional non-rigid deformation (to account for ex-vivo changes) between ex-vivo CT (including PCa-histo and NPCa-histo) and in-vivo CT was performed in MITK by two experienced specialists in consensus.
Subsequently, PCa-histo contours were used to represent the PCa distribution in a 4-mm slice. The voxels in a 3D model were set to discrete values (PCa 1, non PCa 0.1, tissue outside the prostatic gland 0) in PMOD (PMOD v3.6, PMOD Technologies, Switzerland). To account for the obvious (three orders of magnitude) difference between the resolution of PSMA-PET and histology slices for correlation analyses, a Gaussian smoothing (FWHM 7 mm) of the discretized histological data was performed to create a so called histo-PET. Subsequently, rigid mutual information (MI) coregistration between PSMA PET and histo-PET was conducted in PMOD in order to account for minor in-vivo misalignments between PET and CT (i.e. due to bladder or bowel movements) and to overcome possible uncertainties between ex- and in-vivo CT coregistration (low soft-tissue contrast in CT).
Subsequently, PCa-histo contours were used to represent the PCa distribution in a 4-mm slice. The voxels in a 3D model were set to discrete values (PCa 1, non PCa 0.1, tissue outside the prostatic gland 0) in PMOD (PMOD v3.6, PMOD Technologies, Switzerland). To account for the obvious (three orders of magnitude) difference between the resolution of PSMA-PET and histology slices for correlation analyses, a Gaussian smoothing (FWHM 7 mm) of the discretized histological data was performed to create a so called histo-PET. Subsequently, rigid mutual information (MI) coregistration between PSMA PET and histo-PET was conducted in PMOD in order to account for minor in-vivo misalignments between PET and CT (i.e. due to bladder or bowel movements) and to overcome possible uncertainties between ex- and in-vivo CT coregistration (low soft-tissue contrast in CT).
