Standardized classification schemes in reporting oncologic PET/CT

The imaging report is essential for the communication between physicians in patient care. The information it contains must be clear, concise with evidence-based conclusions and sufficient to support clinical decision-making. In recent years, several classification schemes and/or reporting guidelines for PET have been introduced. In this manuscript, we will review the classifications most frequently used in oncology for interpreting and reporting 18F-FDG PET imaging in lymphoma, multiple myeloma, melanoma and head and neck cancers, PSMA-ligand PET imaging for prostate cancer, and 68Ga-DOTA-peptide PET in neuroendocrine tumors (NET)

Prospective, multisite, international comparison of \u3csup\u3e18\u3c/sup\u3eF-fluoromethylcholine PET/CT, multiparametric MRI, and \u3csup\u3e68\u3c/sup\u3eGa-HBED-CC PSMA-11 PET/CT in men with high-risk features and biochemical failure after radical prostatectomy: Clinical performance and patient outcomes

A significant proportion of men with rising prostate-specific antigen (PSA) levels after radical prostatectomy (RP) fail prostate fossa (PF) salvage radiation treatment (SRT). This study was done to assess the ability of F-fluoromethylcholine ( F-FCH) PET/CT (hereafter referred to as F-FCH), Ga-HBED-CC PSMA-11 PET/CT (hereafter referred to as PSMA), and pelvic multiparametric MRI (hereafter referred to as pelvic MRI) to identify men who will best benefit from SRT. Methods: Prospective, multisite imaging studies were carried out in men who had rising PSA levels after RP, high-risk features, and negative/equivocal conventional imaging results and who were being considered for SRT. F-FCH (91/91), pelvic MRI (88/91), and PSMA (31/91) (Australia) were all performed within 2 wk. Imaging was interpreted by experienced local/central interpreters who were masked with regard to other imaging results, with consensus being reached for discordant interpretations. Expected management was documented before and after imaging, and data about all treatments and PSA levels were collected for 3 y. The treatment response to SRT was defined as a reduction in PSA levels of .50% without androgen deprivation therapy. Results: The median Gleason score, PSA level at imaging, and PSA doubling time were 8, 0.42 (interquartile range, 0.29–0.93) ng/mL, and 5.0 (interquartile range, 3.3–7.6) months. Recurrent prostate cancer was detected in 28% (25/88) by pelvic MRI, 32% (29/91) by F-FCH, and 42% (13/31) by PSMA. This recurrence was found within the PF in 21.5% (19/88), 13% (12/91), and 19% (6/31) and at sites outside the PF (extra-PF) in 8% (7/88), 19% (17/91), and 32% (10/31) by MRI, F-FCH, and PSMA, respectively (P, 0.004). A total of 94% (16/17) of extra-PF sites on F-FCH were within the pelvic MRI field. Intra-pelvic extra-PF disease was detected in 90% (9/10) by PSMA and in 31% (5/16) by MRI. F-FCH changed management in 46% (42/91), and MRI changed management in 24% (21/88). PSMA provided additional management changes over F-FCH in 23% (7/31). The treatment response to SRT was higher in men with negative results or disease confined to the PF than in men with extra-PF disease ( F-FCH 73% [32/44] versus 33% [3/9] [P, 0.02], pelvic MRI 70% [32/46] versus 50% [2/4] [P was not significant], and PSMA 88% [7/ 8] versus 14% [1/7] [P, 0.005]). Men with negative imaging results (MRI, F-FCH, or PSMA) had high (78%) SRT response rates. Conclusion: F-FCH and PSMA had high detection rates for extra-PF disease in men with negative/equivocal conventional imaging results and rising PSA levels after RP. These findings affected management and treatment responses, suggesting an important role for PET in triaging men being considered for curative SRT. 18 18 18 68 18 18 18 18 18 18 18 18 1

Prognostic Value of Sarcopenia and Metabolic Parameters of 18^{18}F-FDG-PET/CT in Patients with Advanced Gastroesophageal Cancer

We investigated the prognostic value of sarcopenia measurements and metabolic parameters of primary tumors derived from $^{18}$F-FDG-PET/CT among patients with primary, metastatic esophageal and gastroesophageal cancer. A total of 128 patients (26 females; 102 males; mean age 63.5 ± 11.7 years; age range: 29-91 years) with advanced metastatic gastroesophageal cancer who underwent $^{18}$F-FDG-PET/CT as part of their initial staging between November 2008 and December 2019 were included. Mean and maximum standardized uptake value (SUV) and SUV normalized by lean body mass (SUL) were measured. Skeletal muscle index (SMI) was measured at the level of L3 on the CT component of the $^{18}$F-FDG-PET/CT. Sarcopenia was defined as SMI < 34.4 cm$^{2}$/m$^{2}$ in women and <45.4 cm$^{2}$/m$^{2}$ in men. A total of 60/128 patients (47%) had sarcopenia on baseline $^{18}$F-FDG-PET/CT. Mean SMI in patients with sarcopenia was 29.7 cm$^{2}$/m$^{2}$ in females and 37.5 cm$^{2}$/m$^{2}$ in males. In a univariable analysis, ECOG (<0.001), bone metastases (p = 0.028), SMI (p = 0.0075) and dichotomized sarcopenia score (p = 0.033) were significant prognostic factors for overall survival (OS) and progression-free survival (PFS). Age was a poor prognostic factor for OS (p = 0.017). Standard metabolic parameters were not statistically significant in the univariable analysis and thus were not evaluated further. In a multivariable analysis, ECOG (p < 0.001) and bone metastases (p = 0.019) remained significant poor prognostic factors for OS and PFS. The final model demonstrated improved OS and PFS prognostication when combining clinical parameters with imaging-derived sarcopenia measurements but not metabolic tumor parameters. In summary, the combination of clinical parameters and sarcopenia status, but not standard metabolic values from $^{18}$F-FDG-PET/CT, may improve survival prognostication in patients with advanced, metastatic gastroesophageal cancer

The Role and Limitations of 18-Fluoro-2-deoxy-d-glucose Positron Emission Tomography (FDG-PET) Scan and Computerized Tomography (CT) in Restaging Patients with Hepatic Colorectal Metastases Following Neoadjuvant Chemotherapy: Comparison with Operative and Pathological Findings

BACKGROUND: Recent data confirmed the importance of 18-fluoro-2-deoxy-d-glucose positron emission tomography (FDG-PET) in the selection of patients with colorectal hepatic metastases for surgery. Neoadjuvant chemotherapy before hepatic resection in selected cases may improve outcome. The influence of chemotherapy on the sensitivity of FDG-PET and CT in detecting liver metastases is not known. METHODS: Patients were assigned to either neoadjuvant treatment or immediate hepatic resection according to resectability, risk of recurrence, extrahepatic disease, and patient preference. Two-thirds of them underwent FDG-PET/CT before chemotherapy; all underwent preoperative contrast-enhanced CT and FDG-PET/CT. Those without extensive extrahepatic disease underwent open exploration and resection of all the metastases according to original imaging findings. Operative and pathological findings were compared to imaging results. RESULTS: Twenty-seven patients (33 lesions) underwent immediate hepatic resection (group 1), and 48 patients (122 lesions) received preoperative neoadjuvant chemotherapy (group 2). Sensitivity of FDG-PET and CT in detecting colorectal (CR) metastases was significantly higher in group 1 than in group 2 (FDG-PET: 93.3 vs 49%, P < 0.0001; CT: 87.5 vs 65.3, P = 0.038). CT had a higher sensitivity than FDG-PET in detecting CR metastases following neoadjuvant therapy (65.3 vs 49%, P < 0.0001). Sensitivity of FDG-PET, but not of CT, was lower in group 2 patients whose chemotherapy included bevacizumab compared to patients who did not receive bevacizumab (39 vs 59%, P = 0.068). CONCLUSIONS: FDG-PET/CT sensitivity is lowered by neoadjuvant chemotherapy. CT is more sensitive than FDG-PET in detecting CR metastases following neoadjuvant therapy. Surgical decision-making requires information from multiple imaging modalities and pretreatment findings. Baseline FDG-PET and CT before neoadjuvant therapy are mandatory

How to Design AI-Driven Clinical Trials in Nuclear Medicine.

Artificial intelligence (AI) is an overarching term for a multitude of technologies which are currently being discussed and introduced in several areas of medicine and in medical imaging specifically. There is, however, limited literature and information about how AI techniques can be integrated into the design of clinical imaging trials. This article will present several aspects of AI being used in trials today and how imaging departments and especially nuclear medicine departments can prepare themselves to be at the forefront of AI-driven clinical trials. Beginning with some basic explanation on AI techniques currently being used and existing challenges of its implementation, it will also cover the logistical prerequisites which have to be in place in nuclear medicine departments to participate successfully in AI-driven clinical trials