15 patients underwent a 60-minute dynamic ⁶⁸Ga-PSMA-11 PET scan (patient 101P had its scan interrupted at 40 min) in list-mode with the field of view over the pelvic area. PET data were reconstructed with a 3D-Ordered-Subsets Expectation Maximization (OSEM) algorithm (3 iteration, 21 subsets, matrix 256x256, 4 mm Gaussian filter) and corrected for decay, scatter and attenuation using Dixon-based MR sequences. The list mode data were reconstructed into 28 frames (10 x 30 s, 5 x 60 s, 5 x 120 s, and 8 x 300 s).
Volumes of interest (VOIs) were outlined on the PET images to derive time-activity curves (TACs) in unit Bq/mL. Tumor lesion TACs were derived from VOIs using isocontour threshold of 40% of maximum SUV on late PET images (last 15 min of scan) with the location confirmed on the T2-weighted MR images. Spherical VOIs of 1 mL were outlined on normal prostate and gluteus muscle to derive normal tissue TACs.
Arterial blood activity was measured by continuous blood sampling from the radial artery during the first 10 min using an automatic blood sampling device with 1 s temporal resolution. Manual arterial blood samples at 6 time points (approximately 3, 7, 15, 25, 40 and 60 min post-injection). The manual blood samples were immediately put on ice and centrifuged to separate plasma. Whole blood and plasma-activities were measured in a gamma counter. The arterial input function was generated from the blood sampler curve corrected for decay, background and dispersion (15 s), merged with the decay-corrected manual whole blood samples to get a 60-min AIF. This whole-blood AIF was converted into a plasma AIF using the average plasma-to-blood activity ratios from the manual samples for each subject.

IDIF were generated by extracting the median PET activity within a vessel mask at each timeframe. The vessel mask was defined by segmentation of both external iliac arteries clearly visible on Dixon MR registered to PET. The IDIF were corrected for spillover of PET activity from surrounding tissue to the arteries and partial volume errors using the approach described in Croteau et al 2010. The IDIF were converted to plasma curves using the average plasma-to-blood ratio determined from the arterial blood sampling.

Included in the data set:- 1 excel file with patient data- 15 text files with blood data xxx_Blood: c_blo: whole-blood TAC, c_inp: plasma TAC (arterial input function)- 12 text files with image-derived blood data xxx_IDIF (patients 101, 152 and 207 excluded): c_blo: whole-blood IDIF TAC, c_inp: plasma IDIF TAC - 14 text files with tissue TACs xxx_TAC (subject 222 did not present any PSMA PET uptake and was excluded from lesion-based analysis): midtime and frame duration in min, uptake data in Bq/mL.

15 patients underwent a 60-minute dynamic ⁶⁸Ga-PSMA-11 PET scan (patient 101P had its scan interrupted at 40 min) in list-mode with the field of view over the pelvic area. PET data were reconstructed with a 3D-Ordered-Subsets Expectation Maximization (OSEM) algorithm (3 iteration, 21 subsets, matrix 256x256, 4 mm Gaussian filter) and corrected for decay, scatter and attenuation using Dixon-based MR sequences. The list mode data were reconstructed into 28 frames (10 x 30 s, 5 x 60 s, 5 x 120 s, and 8 x 300 s).
Volumes of interest (VOIs) were outlined on the PET images to derive time-activity curves (TACs) in unit Bq/mL. Tumor lesion TACs were derived from VOIs using isocontour threshold of 40% of maximum SUV on late PET images (last 15 min of scan) with the location confirmed on the T2-weighted MR images. Spherical VOIs of 1 mL were outlined on normal prostate and gluteus muscle to derive normal tissue TACs.
Arterial blood activity was measured by continuous blood sampling from the radial artery during the first 10 min using an automatic blood sampling device with 1 s temporal resolution. Manual arterial blood samples at 6 time points (approximately 3, 7, 15, 25, 40 and 60 min post-injection). The manual blood samples were immediately put on ice and centrifuged to separate plasma. Whole blood and plasma-activities were measured in a gamma counter. The arterial input function was generated from the blood sampler curve corrected for decay, background and dispersion (15 s), merged with the decay-corrected manual whole blood samples to get a 60-min AIF. This whole-blood AIF was converted into a plasma AIF using the average plasma-to-blood activity ratios from the manual samples for each subject.

IDIF were generated by extracting the median PET activity within a vessel mask at each timeframe. The vessel mask was defined by segmentation of both external iliac arteries clearly visible on Dixon MR registered to PET. The IDIF were corrected for spillover of PET activity from surrounding tissue to the arteries and partial volume errors using the approach described in Croteau et al 2010. The IDIF were converted to plasma curves using the average plasma-to-blood ratio determined from the arterial blood sampling.

Included in the data set:- 1 excel file with patient data- 15 text files with blood data xxx_Blood: c_blo: whole-blood TAC, c_inp: plasma TAC (arterial input function)- 12 text files with image-derived blood data xxx_IDIF (patients 101, 152 and 207 excluded): c_blo: whole-blood IDIF TAC, c_inp: plasma IDIF TAC - 14 text files with tissue TACs xxx_TAC (subject 222 did not present any PSMA PET uptake and was excluded from lesion-based analysis): midtime and frame duration in min, uptake data in Bq/mL.