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Background: Standardized uptake value (SUV) normalized by lean body mass ([LBM] SUL) is recommended as metric by PERCIST 1.0. The James predictive equation (PE) is a frequently used formula for LBM estimation, but may cause substantial error for an individual. The purpose of this study was to introduce a novel and reliable method for estimating LBM by limited-coverage (LC) CT images from PET/CT examinations and test its validity, then to analyse whether SUV normalised by LC-based LBM could change the PERCIST 1.0 response classifications, based on LBM estimated by the James PE. Methods: First, 199 patients who received whole-body PET/CT examinations were retrospectively retrieved. A patient-specific LBM equation was developed based on the relationship between LC fat volumes (FVLC) and whole-body fat mass (FMWB). This equation was cross-validated with an independent sample of 97 patients who also received whole-body PET/CT examinations. Its results were compared with the measurement of LBM from whole-body CT (reference standard) and the results of the James PE. Then, 241 patients with solid tumours who underwent PET/CT examinations before and after treatment were retrospectively retrieved. The treatment responses were evaluated according to the PE-based and LC-based PERCIST 1.0. Concordance between them was assessed using Cohen's κ coefficient and Wilcoxon's signed-ranks test. The impact of differing LBM algorithms on PERCIST 1.0 classification was evaluated. Results: The FVLC were significantly correlated with the FMWB (r=0.977). Furthermore, the results of LBM measurement evaluated with LC images were much closer to the reference standard than those obtained by the James PE. The PE-based and LC-based PERCIST 1.0 classifications were discordant in 27 patients (11.2%; κ = 0.823, P=0.837). These discordant patients' percentage changes of peak SUL (SULpeak) were all in the interval above or below 10% from the threshold (±30%), accounting for 43.5% (27/62) of total patients in this region. The degree of variability is related to changes in LBM before and after treatment. Conclusions: LBM algorithm-dependent variability in PERCIST 1.0 classification is a notable issue. SUV normalised by LC-based LBM could change PERCIST 1.0 response classifications based on LBM estimated by the James PE, especially for patients with a percentage variation of SULpeak close to the threshold. [ABSTRACT FROM AUTHOR]

Purpose: To compare the Response Evaluation Criteria in Solid Tumors (RECIST) 1.1, the European Organization for Research and Treatment of Cancer (EORTC) criteria and the Positron Emission Tomography Response Criteria in Solid Tumors (PERCIST) 1.0 using PET volume computer-assisted reading (PET VCAR) for response evaluation in patients with advanced non-small-cell lung cancer (NSCLC) treated with chemotherapy. Methods: A total of 35 patients with NSCLC were included in this prospective study. All patients received standard chemotherapy and underwent F-FDG PET/CT scans before and after treatment. With the assistance of PET VCAR, the chemotherapeutic responses were evaluated according to the RECIST 1.1, EORTC criteria and PERCIST 1.0. Concordance among these protocols was assessed using Cohen's κ coefficient and Wilcoxon's signed-ranks test. Progression-free survival (PFS) was calculated using the Kaplan-Meier test. Results: RECIST 1.1 and EORTC response classifications were discordant in 20 patients (57.1 %; κ = 0.194, P < 0.05), and RECIST 1.1 and PERCIST 1.0 classifications were discordant in 22 patients (62.9 %; κ = 0.139, P < 0.05). EORTC and PERCIST 1.0 classifications were discordant in only 4 patients (11.4 %), resulting in better concordance ( κ = 0.804, P > 0.05). Patients with a partial remission according to RECIST 1.1 had significantly longer PFS ( P < 0.001) than patients with progressive disease, but not significantly longer than patients with stable disease ( P = 0.855). According to both the EORTC criteria and PERCIST 1.0, patients with a partial metabolic response had a significantly longer PFS than those with stable metabolic disease and those with progressive metabolic disease ( P = 0.020 and P < 0.001, respectively, for EORTC; both P < 0.001 for PERCIST 1.0). Conclusion: EORTC criteria and PERCIST 1.0 are more sensitive and accurate than RECIST 1.1 for the detection of an early therapeutic response to chemotherapy in patients with NSCLC. Although EORTC criteria and PERCIST 1.0 showed similar results, PERCIST 1.0 is preferred because detailed and unambiguous definitions are given. We also found that response evaluations with PERCIST 1.0 using a single lesion and multiple lesions gave similar response classifications. [ABSTRACT FROM AUTHOR]

• New radiosynthetic route to a 11C-labeled AMPA ligand. • High radiochemical yield and high molar activity. • Pharmacokinetic profile established for further optimization. The α -amino-3-hydroxyl-5-methyl-4-isoxazolepropionic acid receptors (AMPARs) belong to the family of ionotropic transmembrane receptors for glutamate (iGluRs) that are implicated in the pathology of neurological disorders and neurodegenerative diseases. Inspired by a recently developed positive allosteric modulator of AMPARs, 4-cyclopropyl-7-(3-methoxyphenoxy)-3,4-dihydro-2 H -benzo[ e ][1,2,4]thiadiazine 1,1-dioxide (16 ; EC 50 = 2.0 nM), we designed a new synthetic route for N -protected phenolic precursor 13 and efficiently radiolabeled a PET ligand [11C] AMPA-1905 ([11C] 16) using a modified one-pot two-step strategy in high radiochemical yield and high molar activity. Preliminary in vivo evaluation was carried out to investigate the suitability of [11C] 16 as a potential PET probe for AMPAR imaging. [ABSTRACT FROM AUTHOR]

Positron emission tomography (PET) is a non-invasive imaging tool for the evaluation of brain function and neuronal activity in normal and diseased conditions with high sensitivity. The macaque monkey serves as a valuable model system in the field of translational medicine, for its phylogenetic proximity to man. To translation of non-human primate neuro-PET studies, an effective and objective data analysis platform for neuro-PET studies is needed. A set of stereotaxic templates of macaque brain, namely the Institute of High Energy Physics & Jinan University Macaque Template (HJT), was constructed by iteratively registration and averaging, based on 30 healthy rhesus monkeys. A brain atlas image was created in HJT space by combining sub-anatomical regions and defining new 88 bilateral functional regions, in which a unique integer was assigned for each sub-anatomical region. The HJT comprised a structural MRI T1 weighted image (T1WI) template image, a functional FDG-PET template image, intracranial tissue segmentations accompanied with a digital macaque brain atlas image. It is compatible with various commercially available software tools, such as SPM and PMOD. Data analysis was performed on a stroke model compared with a group of healthy controls to demonstrate the usage of HJT. We have constructed a stereotaxic template set of macaque brain named HJT, which standardizes macaque neuroimaging data analysis, supports novel radiotracer development and facilitates translational neuro-disorders research. • Developing a population stereotaxic PET template, named HJT, for the macaque brain. • Identifying 88 bilateral functional regions in HJT. • Performance of HJT on the platform of commercially available software such as SPM and PMOD. • Application of HJT in voxel-wised analysis of stroke macaque model. [ABSTRACT FROM AUTHOR]