Pharmacokinetic modeling of 68Ga-PSMA-11 in primary prostate cancer patients

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).<br>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.<br>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.<br><br>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.<br><br>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名患者接受了60分钟动态镓-68标记前列腺特异性膜抗原11（68Ga-PSMA-11）正电子发射断层扫描（Positron Emission Tomography, PET），采用列表模式（list-mode）采集，视野（field of view）覆盖盆腔区域（患者101P的扫描在40分钟时中断）。PET数据采用三维有序子集期望最大化（3D-Ordered-Subsets Expectation Maximization, OSEM）算法重建（迭代次数3次、子集数21个、矩阵尺寸256×256，施加4mm高斯滤波器（Gaussian filter）），并基于Dixon磁共振（Magnetic Resonance, MR）序列进行衰变、散射与衰减校正。列表模式（list-mode）数据被重建成28帧图像：10帧×30s、5帧×60s、5帧×120s及8帧×300s。
研究人员在PET图像上勾画感兴趣体积（Volumes of interest, VOIs）以获取单位为贝可每毫升（Bq/mL）的时间-活性曲线（time-activity curves, TACs）。肿瘤病灶的TACs通过勾画VOI得到：以晚期PET图像（扫描最后15分钟）中最大标准化摄取值（Standardized Uptake Value, SUV）的40%等势面为阈值，并结合T2加权磁共振图像确认病灶位置。在正常前列腺与臀肌组织上勾画1mL球形VOIs，以获取正常组织的TACs。
注射后的前10分钟内，研究人员通过桡动脉（radial artery）连续采血，采用时间分辨率（temporal resolution）为1s的自动采血装置（automatic blood sampling device）测量动脉血活度；另在6个时间点（注射后约3、7、15、25、40及60分钟）采集手动动脉血样本。手动采集的血液样本立即置于冰上并离心分离血浆，全血与血浆活度通过γ计数器（gamma counter）测量。基于校正了衰变、本底（background）与弥散（dispersion，15s）的采血曲线生成动脉输入函数（arterial input function, AIF），并与经衰变校正的手动全血样本合并，得到60分钟的全血AIF。随后利用每位受试者手动样本得到的平均血浆-血液活度比，将全血AIF转换为血浆AIF。
图像衍生动脉输入函数（image-derived blood function, IDIF）通过在每个时间帧内提取血管掩码内的PET活度中位数生成。血管掩码通过分割（segmentation）配准至PET图像的Dixon磁共振上清晰可见的双侧髂外动脉（external iliac arteries）得到。采用Croteau等人2010年报道的方法，对IDIF进行周围组织PET活度向动脉的溢出效应（spillover）与部分容积误差（partial volume errors）校正。随后利用动脉采血得到的平均血浆-血液活度比，将IDIF转换为血浆曲线。
本数据集包含以下文件：
- 1份包含患者信息的Excel文件
- 15份血液数据文本文件，命名格式为xxx_Blood：其中c_blo代表全血TAC，c_inp代表血浆TAC（即动脉输入函数）
- 12份图像衍生血液数据文本文件，命名格式为xxx_IDIF（排除患者101、152与207）：其中c_blo代表全血IDIF TAC，c_inp代表血浆IDIF TAC
- 14份组织TACs文本文件，命名格式为xxx_TAC（患者222未检测到PSMA PET摄取，因此被排除病灶分析）：文件包含各帧的中间时间、帧时长（单位：分钟）以及摄取数据（单位：Bq/mL）。