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Abstract Background The purpose of this study was to evaluate both the biodistribution and safety of 64Cu-1,4,7-triazacyclononane-1,4,7-triacetic acid (NOTA)-Trastuzumab, a novel 64Cu-labeled positron emission tomography (PET) tracer for human epidermal growth factor receptor 2 (HER2) in patients with breast cancer. Methods PET images at 1, 24, and 48 h after 296 MBq of 64Cu-NOTA-Trastuzumab injection were obtained from seven patients with breast cancer. Both the primary tumors’ and metastatic lesions’ maximum standardized uptake value (SUVmax) was evaluated. The mean SUVmax (SUVmean) was evaluated in the other organs, including the blood pool, liver, kidney, muscle, spleen, bladder, and the lungs, as well as the bones. Moreover, the internal radiation dosimetry was calculated using the OLINDA/EXM software. Safety was assessed based on feedback regarding adverse reactions and safety-related issues within 1 month after 64Cu-NOTA-Trastuzumab administration. Results 64Cu-NOTA-Trastuzumab PET images showed that the overall SUVmean values in each organ negatively correlated with time. The liver’s average SUVmean values were measured at 5.3 ± 0.7, 4.8 ± 0.6, and 4.4 ± 0.5 on 1 h, 24 h, and 48 h after injection, respectively. The average SUVmean blood values were measured at 13.1 ± 0.9, 9.1 ± 1.2, and 7.1 ± 1.9 on 1 h, 24 h, and 48 h after injection, respectively. The SUVmax of HER2-positive tumors was relatively higher than HER2-negative tumors (8.6 ± 5.1 and 5.2 ± 2.8 on 48 h after injection, respectively). Tumor-to-background ratios were higher in the HER2-positive tumors than in the HER2-negative tumors. No adverse events related to 64Cu-NOTA-Trastuzumab were reported. The calculated effective dose with a 296 MBq injection of 64Cu-NOTA-Trastuzumab was 2.96 mSv. The highest absorbed dose was observed in the liver (0.076 mGy/MBq), followed by the spleen (0.063 mGy/MBq), kidney (0.044 mGy/MBq), and heart wall (0.044 mGy/MBq). Conclusions 64Cu-NOTA-Trastuzumab showed a specific uptake at the HER2-expressing tumors, thus making it a feasible and safe monitoring tool of HER2 tumor status in patients with breast cancer. Trial registration CRIS, KCT0002790. Registered 02 February 2018, https://cris.nih.go.kr

Abstract Purpose For pediatric lymphoma, quantitative FDG PET/CT imaging features such as metabolic tumor volume (MTV) are important for prognosis and risk stratification strategies. However, feature extraction is difficult and time-consuming in cases of high disease burden. The purpose of this study was to fully automate the measurement of PET imaging features in PET/CT images of pediatric lymphoma. Methods 18F-FDG PET/CT baseline images of 100 pediatric Hodgkin lymphoma patients were retrospectively analyzed. Two nuclear medicine physicians identified and segmented FDG avid disease using PET thresholding methods. Both PET and CT images were used as inputs to a three-dimensional patch-based, multi-resolution pathway convolutional neural network architecture, DeepMedic. The model was trained to replicate physician segmentations using an ensemble of three networks trained with 5-fold cross-validation. The maximum SUV (SUVmax), MTV, total lesion glycolysis (TLG), surface-area-to-volume ratio (SA/MTV), and a measure of disease spread (Dmaxpatient) were extracted from the model output. Pearson’s correlation coefficient and relative percent differences were calculated between automated and physician-extracted features. Results Median Dice similarity coefficient of patient contours between automated and physician contours was 0.86 (IQR 0.78–0.91). Automated SUVmax values matched exactly the physician determined values in 81/100 cases, with Pearson’s correlation coefficient (R) of 0.95. Automated MTV was strongly correlated with physician MTV (R = 0.88), though it was slightly underestimated with a median (IQR) relative difference of − 4.3% (− 10.0–5.7%). Agreement of TLG was excellent (R = 0.94), with median (IQR) relative difference of − 0.4% (− 5.2–7.0%). Median relative percent differences were 6.8% (R = 0.91; IQR 1.6–4.3%) for SA/MTV, and 4.5% (R = 0.51; IQR − 7.5–40.9%) for Dmaxpatient, which was the most difficult feature to quantify automatically. Conclusions An automated method using an ensemble of multi-resolution pathway 3D CNNs was able to quantify PET imaging features of lymphoma on baseline FDG PET/CT images with excellent agreement to reference physician PET segmentation. Automated methods with faster throughput for PET quantitation, such as MTV and TLG, show promise in more accessible clinical and research applications.

Abstract Background To propose a personalized therapeutic approach in osteosarcoma treatment, we assessed whether sequential [18F]FDG PET/CT (PET/CT) could predict the outcome of patients with osteosarcoma of the extremities after one cycle and two cycles of neoadjuvant chemotherapy. Methods A total of 73 patients with AJCC stage II extremity osteosarcoma treated with 2 cycles of neoadjuvant chemotherapy, surgery, and adjuvant chemotherapy were retrospectively analyzed in this study. All patients underwent PET/CT before (PET0), after 1 cycle (PET1), and after the completion of neoadjuvant chemotherapy (PET2), respectively. Maximum standardized uptake value (SUVmax) (corrected for body weight) and the % changes of SUVmax were calculated, and histological responses were evaluated after surgery. Receiver-operating characteristic (ROC) curve analyses and the Cox proportional hazards models were used to analyze whether imaging and clinicopathologic parameters could predict event-free survival (EFS). Results A total of 36 patients (49.3%) exhibited a poor histologic response and 17 patients (23.3%) showed events (metastasis in 15 and local recurrence in 2). SUVmax on PET2 (SUV2), the percentage change of SUVmax between PET0 and PET1 (Δ%SUV01), and between PET0 and PET2 (Δ%SUV02) most accurately predicted events using the ROC curve analysis. SUV2 (relative risk, 8.86; 95% CI, 2.25–34.93), Δ%SUV01 (relative risk, 5.97; 95% CI, 1.47–24.25), and Δ%SUV02 (relative risk, 6.00; 95% CI, 1.16–30.91) were independent predicting factors for EFS with multivariate analysis. Patients with SUV2 over 5.9 or Δ%SUV01 over − 39.8% or Δ%SUV02 over − 54.1% showed worse EFS rates than others (p < 0.05). Conclusions PET evaluation after 1 cycle of presurgical chemotherapy can predict the clinical outcome of extremity osteosarcoma. [18F]FDG PET, which shows a potential role in the early evaluation of the modification of timing of local control, can be a useful modality for early response monitoring of neoadjuvant chemotherapy.

Abstract Background We have previously developed a novel and highly consistent PET segmentation algorithm using a multi-level Otsu method (MO-PET). The aim of this study was to evaluate the reliability of MO-PET compared to conventional PET segmentation methods for measuring 18F-FDG (FDG) PET metabolic tumor volume (MTV) in patients with soft tissue sarcoma (STS). Clinical and imaging data were obtained from the Cancer Imaging Archive. Forty-eight STS patients with FDG PET/CT and MR prior to therapy were analyzed. MTV of the tumor using MO-PET was compared to other conventional methods (absolute SUV threshold values of 2.0, 2.5, or 3.0 and percentage of tumor SUVmax values of 30, 40, 50, or 60%) and gradient-based method (PET Edge™). The reference volume was defined as an MR-based gross tumor volume (GTV). Spearman, intra-class correlation, and Bland-Altman analysis were performed to evaluate the correlation and agreement of MTV to GTV. Results MTVs obtained using each conventional SUV parameter, PET Edge™, and MO-PET were highly correlated with the GTV in Spearman and intra-class correlation analysis (p