Advantage workstation

Quantitative image parameters of the primary tumor were obtained for mpMRI and [⁶⁸Ga]PSMA-11 PET. For mpMRI readers acquired the average and minimum ADC values (ADC_mean and ADC_min, mm²/1000 s), the longest capsular contact (LCC, mm), and the tumor volume (cm³). mpMRI LCC (mm) was defined as the maximum curvilinear length of PCa in contact with the prostatic capsule among all axial sections of the T2w-images in which the lesion was visible. On [⁶⁸Ga]PSMA-11 PET readers quantified PSMA uptake with SUV_max and volume-based measures, using a fixed threshold at SUV > 4 to delineate total PSMA uptake (PSMA_tot, g/ml), and PSMA volume (PSMA_vol, cm³). All the PET/CT, PET/MRI, and mpMRI images were analyzed in a dedicated review workstation (Advantage Workstation, Version 4.6 or 4.7, GE Healthcare), which enables the review of the PET, CT, MRI, or mpMRI images side by side and in fused mode. mpMRI images were assessed by SS (Radiologist) and HG (Radiologist and Nuclear Medicine Physician) with 1, and 4 years of experience, respectively. PET/MRI and PET/CT images were assessed by RL and DAF (Nuclear medicine Physicians) with 2 and 2 years of experience, respectively.

FDG PET-CT was performed using the Discovery ST PET-CT system (GE Medical Systems, Milwaukee, WI, USA). Briefly, all patients fasted for 6 h before receiving an intravenous injection of FDG. A low-dose CT scan was performed for attenuation correction 50 min after the FDG injection (5.55 MBq/kg body weight). Then PET images were acquired for 150 s per bed position. Data were reconstructed using ordered subset expectation maximization reconstruction (128 × 128 matrix, 3.27-mm slice thickness; subset: 21, iterations: 2). The degree of FDG uptake was assessed using a semiquantitative technique in which a volumetric region of interest was placed over the FDG-avid lesions, and the highest value was selected (SUVmax). The MTV was measured by applying a fixed SUV threshold of 2.5 as the lowest limit of the segmentation criteria. MTV was measured in the primary site and metastatic lymph nodes (LNs), and the total MTV was defined as the sum of the primary and nodal MTVs. The metabolic parameters were measured on an Advantage Workstation (GE Healthcare, Milwaukee, WI, USA) using PET volume computer-assisted reading software (ver. 1.0).

In this retrospective study, data originated from abdominal CT scans or dedicated CT urography (CTU) scans in two separate institutions comprising unenhanced phases, corticomedullary phases, and nephrographic phases (Vue PACS, Carestream Health Inc & General Electric Advantage Workstation). Ethics committees in both institutions approved this retrospective investigation. Candidate participants included those with renal cysts larger than 1 cm, those with no surgery history (renal needle biopsy, nephrolithotomy, nephrectomy, or partial nephrectomy), those without conditions linked to multiple renal cysts (polycystic disease, Von Hippel–Lindau syndrome, or autosomal dominant polycystic kidney disease), and those with less than 25% solid portion in cystic lesions. Each individual in this study could only include verified cystic renal masses based on the final pathology findings, ensuring a realistic and reliable model’s presentation. The detailed selection process and the pathological results of two cohorts are displayed in Figure 1.

In all cases, preoperative MRI was performed, including gadolinium contrast-enhanced imaging and diffusion-weighted imaging with long-associative tract reconstruction by high angular resolution (3.0 T MRI scanner General Electric Signa HD with 8-channel head coil) to determine if cortical tracts were infiltrated by the tumor. Diffusion tensor imaging protocol included TR = 15,000 ms, TE = minimum, matrix 96 × 96, and FOV = 24 cm, and contained one scan series with b = 1000 and 60 diffusion gradient directions. Processing was carried out using Advantage workstation and READY View software (both from GE Healthcare, Waukesha, WI, USA). Preoperative functional MRI was performed in 20 cases. EOR was defined based on the assessment of pre- and postoperative T1 contrast-enhanced sequences for glioblastomas or T2 FLAIR data for non-contrast-enhancing gliomas. Image assessment was performed by an independent radiologist. Preoperative PET of the brain was not a routine procedure for patients with brain gliomas and was performed only in eight patients.

Background variability (BV) and contrast-to-noise ratio (CNR) were calculated and compared. BV was defined as the SD of the activity concentration in large ROIs (about 4 cm²) located away from the axial plane containing the sphere centers, divided by the mean activity concentration in these background ROIs. CNR was calculated as contrast recovery (CR) divided by BV as follows:
$${\displaystyle \begin{array}{c}\mathrm{C}\mathrm{N}\mathrm{R}=\mathrm{C}\mathrm{R}/\mathrm{B}\mathrm{V}\\ \mathrm{where}\mathrm{C}\mathrm{R}=\frac{\frac{{\mathrm{C}}_{\mathrm{H}}}{{\mathrm{C}}_{\mathrm{B}}}\text{-}1}{\frac{{\mathrm{a}}_{\mathrm{H}}}{{\mathrm{a}}_{\mathrm{B}}}\text{-}1}\end{array}}$$
with C_H and C_B, counts and a_H and a_B, activities in hot spheres and background ROIs, respectively. Image analysis was done on a GE Healthcare Advantage Workstation (AW 3.2 Ext. 3.2, 2019).