CRISPR/Cas9-mediated disruption of SHANK3 in monkey leads to drug-treatable autism-like symptoms.

Monogenic mutations in the SHANK3 gene, which encodes a postsynaptic scaffold protein, play a causative role in autism spectrum disorder (ASD). Although a number of mouse models with Shank3 mutations have been valuable for investigating the pathogenesis of ASD, species-dependent differences in behaviors and brain structures post considerable challenges to use small animals to model ASD and to translate experimental therapeutics to the clinic. We have used clustered regularly interspersed short palindromic repeat/CRISPR-associated nuclease 9 to generate a cynomolgus monkey model by disrupting SHANK3 at exons 6 and 12. Analysis of the live mutant monkey revealed the core behavioral abnormalities of ASD, including impaired social interaction and repetitive behaviors, and reduced brain network activities detected by positron-emission computed tomography (PET). Importantly, these abnormal behaviors and brain activities were alleviated by the antidepressant fluoxetine treatment. Our findings provide the first demonstration that the genetically modified non-human primate can be used for translational research of therapeutics for ASD.

A population stereotaxic positron emission tomography brain template for the macaque and its application to ischemic model.

PURPOSE: 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. MATERIALS AND METHODS: 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. RESULTS: 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. CONCLUSION: 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.

Sex- and age-specific percentiles of body composition indices for Chinese adults using dual-energy X-ray absorptiometry.

PURPOSE: The aims of the study were to develop sex- and age-specific percentiles for lean mass index (LMI), appendicular LMI (aLMI), fat mass index (FMI), and body fat distribution indices in Chinese adults using dual-energy X-ray absorptiometry (DXA), and to compare those indices with those of other ethnicities using the US NHANES data. METHODS: Whole-body and regional lean mass and fat mass (FM) were measured using DXA in 5688 healthy males (n = 1693) and females (n = 3995) aged 20-90 years. Body fat distribution indices were expressed as % fat trunk/% fat legs, trunk/appendicular FM ratio (FMR), and android/gynoid FMR. Percentile curves of LMI, aLMI, FMI, and body fat distribution indices were obtained by the Lambda-Mu-Sigma method. RESULTS: The aLMI and LMI were negatively associated with age, decreasing from the fifth decade for males, but were not associated with age in females. Females had more total FM than males, whereas males had greater central adiposity (% fat trunk/% fat legs ratio, trunk/appendicular FMR, and android/gynoid FMR) than females. Moreover, FMI and body fat distribution indices consistently increased with age in both sexes, especially in women. In comparison with white, black, and Mexican populations in the USA, Chinese adults had lower total FM, but had greater central adiposity (% fat trunk/% fat legs ratio and trunk/appendicular FMR). Additionally, older white and Mexican populations showed greater decreases for aLMI and LMI than their Chinese counterparts. CONCLUSIONS: We present the sex- and age-specific percentiles for aLMI, LMI, FMI, and body fat distribution indices by DXA in Chinese adults, which may refine the individual assessment of the nutritional status of Chinese adults.

Comparison of RECIST, EORTC criteria and PERCIST for evaluation of early response to chemotherapy in patients with non-small-cell lung cancer.

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 (18)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.

Relationships between the lean mass index and bone mass and reference values of muscular status in healthy Chinese children and adolescents.

This study aimed to analyze the relationships between the lean mass index (LMI) and bone outcomes in Chinese children and adolescents using dual-energy X-ray absorptiometry (DXA) and to establish sex-specific reference percentile curves for the assessment of muscle status. A total of 1541 Chinese children and adolescents between the ages of 5 and 19 years were recruited from southern China. Body composition was measured by DXA (Lunar Prodigy) to acquire total body and total body less head (TBLH) measures. LMI was calculated as the LM (kg) divided by the height in meters squared. Strong sex gaps were observed after age 14 in total body LMI and appendicular LMI (p < 0.001). LM and LMI values continued to increase for boys up to age 14 compared to girls who plateaued after age 12. For each sex group, total body bone mineral content (BMC) and TBLH BMC were highly correlated with total body LMI and appendicular LMI (r = 0.856-0.916 in boys, and r = 0.651-0.804 in girls, p < 0.001). The appendicular LMI was more strongly associated with total body BMC and TBLH BMC than was total body LMI. The correlations between the BMC values and the LM measures were stronger than the fat mass results. We also present sex-specific percentile curves for LM-age and LMI-age relationships, which could be useful for identifying the LM deficits in this population.

Reference data and percentile curves of body composition measured with dual energy X-ray absorptiometry in healthy Chinese children and adolescents.

Measurements of body composition by dual-energy X-ray absorptiometry (DXA) have evident value in evaluating skeletal and muscular status in growing children and adolescents. This study aimed to generate age-related trends for body composition in Chinese children and adolescents, and to establish gender-specific reference percentile curves for the assessment of muscle-bone status. A total of 1541 Chinese children and adolescents aged from 5 to 19 years were recruited from southern China. Bone mineral content (BMC), lean mass (LM) and fat mass (FM) were measured for total body and total body less head (TBLH). After 14 years, total body LM was significantly higher in boys than girls (p < 0.001). However, total body FM was significantly higher in girls than boys in age groups 13-19 years (p < 0.01). Both LM and FM were consistent independent predictors of total body and subcranial bone mass in both sexes, even after adjustment for the well-known predictors of BMC. The results of multiple linear regression identified LM as the stronger predictor of total body and subcranial skeleton BMC while the fat mass contributed less. For all the subjects, significant positive correlations were observed between total body LM, height, total body BMC and subcranial BMC (p < 0.01). Subcranial BMC had a better correlation with LM than total body BMC. We have also presented gender-specific percentile curves for LM-for-height and BMC-for-LM which could be used to evaluate and follow various pediatric disorders with skeletal manifestations in this population.

Machine learning techniques based on 18F-FDG PET radiomics features of temporal regions for the classification of temporal lobe epilepsy patients from healthy controls.

Background: This study aimed to investigate the clinical application of 18F-FDG PET radiomics features for temporal lobe epilepsy and to create PET radiomics-based machine learning models for differentiating temporal lobe epilepsy (TLE) patients from healthy controls. Methods: A total of 347 subjects who underwent 18F-FDG PET scans from March 2014 to January 2020 (234 TLE patients: 25.50 ± 8.89 years, 141 male patients and 93 female patients; and 113 controls: 27.59 ± 6.94 years, 48 male individuals and 65 female individuals) were allocated to the training (n = 248) and test (n = 99) sets. All 3D PET images were registered to the Montreal Neurological Institute template. PyRadiomics was used to extract radiomics features from the temporal regions segmented according to the Automated Anatomical Labeling (AAL) atlas. The least absolute shrinkage and selection operator (LASSO) and Boruta algorithms were applied to select the radiomics features significantly associated with TLE. Eleven machine-learning algorithms were used to establish models and to select the best model in the training set. Results: The final radiomics features (n = 7) used for model training were selected through the combinations of the LASSO and the Boruta algorithms with cross-validation. All data were randomly divided into a training set (n = 248) and a testing set (n = 99). Among 11 machine-learning algorithms, the logistic regression (AUC 0.984, F1-Score 0.959) model performed the best in the training set. Then, we deployed the corresponding online website version (https://wane199.shinyapps.io/TLE_Classification/), showing the details of the LR model for convenience. The AUCs of the tuned logistic regression model in the training and test sets were 0.981 and 0.957, respectively. Furthermore, the calibration curves demonstrated satisfactory alignment (visually assessed) for identifying the TLE patients. Conclusion: The radiomics model from temporal regions can be a potential method for distinguishing TLE. Machine learning-based diagnosis of TLE from preoperative FDG PET images could serve as a useful preoperative diagnostic tool.

Alterations of apparent diffusion coefficient from ultra high b-values in the bilateral thalamus and striatum in MRI-negative drug-resistant epilepsy.

OBJECTIVE: Subcortical nuclei such as the thalamus and striatum have been shown to be related to seizure modulation and termination, especially in drug-resistant epilepsy. Enhance diffusion-weighted imaging (eDWI) technique and tri-component model have been used in previous studies to calculate apparent diffusion coefficient from ultra high b-values (ADCuh). This study aimed to explore the alterations of ADCuh in the bilateral thalamus and striatum in MRI-negative drug-resistant epilepsy. METHODS: Twenty-nine patients with MRI-negative drug-resistant epilepsy and 18 healthy controls underwent eDWI scan with 15 b-values (0-5000 s/mm2). The eDWI parameters including standard ADC (ADCst), pure water diffusion (D), and ADCuh were calculated from the 15 b-values. Regions-of-interest (ROIs) analyses were conducted in the bilateral thalamus, caudate nucleus, putamen, and globus pallidus. ADCst, D, and ADCuh values were compared between the MRI-negative drug-resistant epilepsy patients and controls using multivariate generalized linear models. Inter-rater reliability was assessed using the intra-class correlation coefficient (ICC) and Bland-Altman (BA) analysis. False discovery rate (FDR) method was applied for multiple comparisons correction. RESULTS: ADCuh values in the bilateral thalamus, caudate nucleus, putamen, and globus pallidus in MRI-negative drug-resistant epilepsy were significantly higher than those in the healthy control subjects (all p < 0.05, FDR corrected). SIGNIFICANCE: The alterations of the ADCuh values in the bilateral thalamus and striatum in MRI-negative drug-resistant epilepsy might reflect abnormal membrane water permeability in MRI-negative drug-resistant epilepsy. ADCuh might be a sensitive measurement for evaluating subcortical nuclei-related brain damage in epilepsy patients. PLAIN LANGUAGE SUMMARY: This study aimed to explore the alterations of apparent diffusion coefficient calculated from ultra high b-values (ADCuh) in the subcortical nuclei such as the bilateral thalamus and striatum in MRI-negative drug-resistant epilepsy. The bilateral thalamus and striatum showed higher ADCuh in epilepsy patients than healthy controls. These findings may add new evidences of subcortical nuclei abnormalities related to water and ion hemostasis in epilepsy patients, which might help to elucidate the underlying epileptic neuropathophysiological mechanisms and facilitate the exploration of therapeutic targets.

A PET-based radiomics nomogram for individualized predictions of seizure outcomes after temporal lobe epilepsy surgery.

PURPOSE: To establish and validate a novel nomogram based on clinical characteristics and [18F]FDG PET radiomics for the prediction of postsurgical seizure freedom in patients with temporal lobe epilepsy (TLE). PATIENTS AND METHODS: 234 patients with drug-refractory TLE patients were included with a median follow-up time of 24 months after surgery. The correlation coefficient redundancy analysis and LASSO Cox regression were used to characterize risk factors. The Cox model was conducted to develop a Clinic-PET nomogram to predict the relapse status in the training set (n = 171). The nomogram's performance was estimated through discrimination, calibration, and clinical utility. The prognostic prediction model was validated in the test set (n = 63). RESULTS: Eight radiomics features were selected to assess the radiomics score (radscore) of the operation side (Lat_radscore) and the asymmetric index (AI) of the radiomics score (AI_radscore). AI_radscor, Lat_radscor, secondarily generalized seizures (SGS), and duration between seizure onset and surgery (Durmon) were significant predictors of seizure-free outcomes. The final model had a C-index of 0.68 (95 %CI: 0.59-0.77) for complete freedom from seizures and time-dependent AUROC was 0.65 at 12 months, 0.65 at 36 months, and 0.59 at 60 months in the test set. A web application derived from the primary predictive model was displayed for economic and efficient use. CONCLUSIONS: A PET-based radiomics nomogram is clinically promising for predicting seizure outcomes after temporal lobe epilepsy surgery.

Age trends of bone mineral density and percentile curves in healthy Chinese children and adolescents.

The clinical utility of dual-energy X-ray absorptiometry (DXA) measurement requires appropriate normative values, designed to be diverse with respect to age, gender and ethnic background. The purpose of this study was to generate age-related trends for bone density in Chinese children and adolescents, and to establish a gender-specific reference database. A total of 1,541 Chinese children and adolescents aged from 5 to 19-years were recruited from southern China. Bone mineral density (BMD), bone mineral content (BMC), and bone area (BA) were measured for the total body (TB) and total body less head (TBLH). The height-for-age, height-for-BA, and BMC-for-BA percentile curves were developed using the least mean square method. TB BMD and TBLH BMD were highly correlated. After 18 years, TB BMD was significantly higher in boys than girls. For TB BMC and TBLH BMC, gender differences were found in age groups 12 years and 16-19 years; however, the TBLH BMD was significantly different between genders >16 years. The head region accounted for 13-52 and 16-49 % of the TB BMC in boys and girls, respectively. Furthermore, the percentages were negatively correlated with age and height. This study describes a gender-specific reference database for Chinese children and adolescents aged 5-19 years. These normative values could be used for clinical assessment in this population.

Precision of quantitative parameters of 18F-FDG PET/CT in a rabbit VX2 tumor model.

Background: The precision reflecting repeated measurement error of quantitative parameters of flourine-18 fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) for evaluating the therapeutic effect of solid tumor can help observe whether a real biologic change in glucose metabolism occurred, or if the change was caused by errors before and after the treatment. Methods: A total of 18 VX2 tumor-bearing male New Zealand rabbits confirmed by pathology were used, three of which were used for determining the best scanning time point after injection and 15 for a precision experiment by repeating PET/CT scans for three consecutive days. The PET volume computer-assisted reading (PET VCAR) software (GE Healthcare) was used to analyze the standardized uptake value (SUV) and total lesion glycolysis (TLG) parameters. The lean body mass (LBM) to calculate the SUV corrected for lean body mass (SUL) parameters was measured using dual energy X-ray absorptiometry (DXA). The precision was represented as the coefficient of variation of root mean square (RMS-CV) and standard deviation of root mean square (RMS-SD). The least significant change (LSC) was also calculated when considering precision. Results: The precision of SUV parameters, including SUVmax, SUVmean and SUVpeak ranged from 18.3% to 18.8%, which was similar to that of the SUL parameters (18.0-18.4%). Using 80% confidence interval (CI), the LSC of SUVmax and SULpeak were 33.1% and 33.3%, respectively; using 95% CI, the LSC of SUVmax and SULpeak were 50.1% and 51.0%, respectively. Conclusions: This research established the method of precision in a rabbit VX2 tumor model, which can be used for monitoring changes to assess the effects of drug treatment on solid tumors in experimental studies with 18F-FDG PET/CT imaging.

Predictive value of metabolic parameters derived from preoperative 18F-FDG positron emission tomography/computed tomography for brain metastases in patients with surgically resected non-small cell lung cancer.

Background: Brain metastases (BMs) are common complications in patients with non-small cell lung cancer (NSCLC). The purpose of this study was to investigate whether the metabolic parameters derived from preoperative 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) can predict BM development in patients with surgically resected NSCLC. Methods: We retrospectively reviewed 128 consecutive patients with stage I-IIIA NSCLC who underwent 18F-FDG PET/CT before curative surgery at The First Affiliated Hospital of Jinan University between November 2012 and October 2021. By drawing a volume of interest (VOI), the maximum standardized uptake values (SUVmax), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) of the primary tumor as well as the mean SUV (SUVmean) of the liver and arterial blood were measured. The tumor-to-liver SUV ratio (TLR) and tumor-to-blood SUV ratio (TBR) were also calculated. Receiver operating characteristic curve analysis was used to determine the best cut-off values for positron emission tomography (PET) parameters to predict BM-free survival, and Cox proportional hazards regression analysis was used to assess the predictive value of clinical variables and PET parameters. Results: The median follow-up duration for survival patients was 23.4 months, and 15 patients (11.7%) experienced BM as the initial relapse site. The cumulative rates of BM over the course of 1, 2, and 5 years were 4.5%, 10.5%, and 17.5%, respectively. The optimal cut-off values for the prediction of BM-free survival were 7.7, 4.9, and 4.5 for SUVmax, TLR, and TBR, and 5.5 mL and 16.1 for MTV and TLG, respectively. In the Cox proportional hazards model, the risk of BM was significantly associated with TLR [hazard ratio (HR) =10.712; 95% confidence interval (CI): 2.958-38.801; P<0.001] and MTV (HR =3.150; 95% CI: 0.964-10.293; P=0.020) after adjusting for tumor stage, clinicopathological factors, and other PET parameters. Conclusions: Preoperative TLR and MTV of the primary tumor may be helpful in predicting BM development in patients with surgically resected NSCLC. Tumor metabolic parameters may potentially be used to stratify the risk of BM and determine individualized surveillance strategies.

Preliminary Exploration of Pseudo-CT-Based Attenuation Correction for Simultaneous PET/MRI Brain Imaging in Nonhuman Primates.

This study aimed to develop a template-based attenuation correction (AC) for the nonhuman primate (NHP) brain. We evaluated the effects of AC on positron emission tomography (PET) data quantification with two experimental paradigms by comparing the quantitative outcomes obtained using a segmentation-based AC versus template-based AC. Population-based atlas was generated from ten adult rhesus macaques. Bolus experiments using [18F]PF-06455943 and a bolus-infusion experiment using [11C]OMAR were performed on a 3T Siemens PET/magnetic resonance-imaging (MRI). PET data were reconstructed with either µ map obtained from the segmentation-based AC or template-based AC. The standard uptake value (SUV), volume of distribution (VT), or percentage occupancy of rimonabant were calculated for [18F]PF-06455943 and [11C]OMAR PET, respectively. The leave-one-out cross-validation showed that the absolute percentage differences were 2.54 ± 2.86% for all region of interests. The segmentation-based AC had a lower SUV and VT (∼10%) of [18F]PF-06455943 than the template-based method. The estimated occupancy was higher in the template-based method compared to the segmentation-based AC in the bolus-infusion study. However, future studies may be needed if a different reference tissue is selected for data quantification. Our template-based AC approach was successfully developed and applied to the NHP brain. One limitation of this study was that validation was performed by comparing two different MR-based AC approaches without validating against AC methods based on computed tomography (CT).

18F-FDG PET/CT and PET/MRI fusion imaging for neuroendocrine carcinoma of the tongue: A case report.

Neuroendocrine carcinoma (NEC) involving the tongue is a rare and aggressive disease that is more common in middle-aged and elderly males. We report a case of a 56-year-old male who presented to our hospital with sore throat and was found to have a mass in the left root of the tongue. 18F-FDG PET/CT revealed intense FDG uptake in the mass of the tongue base, as well as different uptake of FDG in the mid-posterior mediastinal mass, right adrenal gland, and enlarged lymph nodes in the neck and mediastinum. Gadolinium-enhanced MRI clearly showed the extent of the tongue lesion, additionally suggesting the presence of brain metastases. 18F-FDG PET/MRI fusion images of the neck were obtained on the workstation, which may have a higher diagnostic value for tongue NEC. The patient underwent a biopsy of the mass in the left root of the tongue and was pathologically diagnosed with NEC. Whole-body 18F-FDG PET/CT and regional PET/MRI fusion images have complementary roles in the diagnosis of tongue NEC, and the former is mainly applied to determine the clinical stage of the disease and to guide treatment.

Predictive value of baseline metabolic tumor burden on 18F-FDG PET/CT for brain metastases in patients with locally advanced non-small-cell lung cancer.

Objectives: Brain metastases (BMs) are a major cause leading to the failure of treatment management for non-small-cell lung cancer (NSCLC) patients. The purpose of this study was to evaluate the predictive value of baseline metabolic tumor burden on 18F-FDG PET/CT measured with metabolic tumor volume (MTV) and total lesion glycolysis (TLG) for brain metastases (BMs) development in patients with locally advanced non-small-cell lung cancer (NSCLC) after treatment. Methods: Forty-seven patients with stage IIB-IIIC NSCLC who underwent baseline 18F-FDG PET/CT examinations were retrospectively reviewed. The maximum standardized uptake value (SUVmax), MTV, and TLG of the primary tumor (SUVmaxT, MTVT, and TLGT), metastatic lymph nodes (SUVmaxN, MTVN, and TLGN), and whole-body tumors (SUVmaxWB, MTVWB, and TLGWB) were measured. The optimal cut-off values of PET parameters to predict brain metastasis-free survival were obtained using Receiver operating characteristic (ROC) analysis, and the predictive value of clinical variables and PET parameters were evaluated using Cox proportional hazards regression analysis. Results: The median follow-up duration was 25.0 months for surviving patients, and 13 patients (27.7%) developed BM. The optimal cut-off values were 21.1 mL and 150.0 g for MTVT and TLGT, 20.0, 10.9 mL and 55.6 g for SUVmaxN, MTVN and TLGN, and 27.9, 27.4 mL and 161.0 g for SUVmaxWB, MTVWB and TLGWB, respectively. In the Cox proportional hazards models, the risk of BM was significantly associated with MTVN and MTVWB or TLGN and TLGWB after adjusting for histological cell type, N stage, SUVmaxN, and SUVmaxWB. Conclusions: Baseline metabolic tumor burden (MTV and TLG) evaluated from the level of metastatic lymph nodes and whole-body tumors are significant predictive factors for BM development in patients with locally advanced NSCLC.

The precision study of dual energy X-ray absorptiometry for bone mineral density and body composition measurements in female cynomolgus monkeys.

Background: Dual-energy X-ray absorptiometry (DXA) is a well-accepted tool for monitoring skeletal and body composition changes in biomedical studies. The nonhuman primate model is suitable for studies exploring the pathogenesis of and novel treatments for osteoporosis. Our objectives are to determine the precision of DXA detection in cynomolgus monkeys and to identify the difference in precision in lumbar bone mineral density (BMD) with various segment selections. Methods: Thirty adult female cynomolgus monkeys underwent duplicate total body DXA scans. Total body bone mineral density (BMDTB) and body composition, including bone mineral content (BMCTB), lean mass (LMTB), and fat mass (FMTB), were analyzed by enCORE software, while lumbar BMD was obtained by manual region-of-interest analysis. The precision was represented as the root-mean-square standard deviation (RMS-SD) and coefficient of variation (RMS-CV%), and least significant changes (LSCs) were reported. Results: The RMS-SD (RMS-CV%) of the repeated DXA analyses for BMDTB, BMCTB, LMTB and FMTB were 0.002 g/cm2 (0.50%), 0.90 g (0.42%), 0.015 kg (0.49%), and 0.031 kg (2.71%), respectively. The regional BMD precision (RMS-CV%) of the lumbar spine with various combinations ranged from 0.70% to 1.09%, The LSCs with 80% statistical confidence (LSC80) ranged from 1.27% to 1.97%, and LSC95 ranged from 1.94% to 3.01%. Conclusions: DXA provided excellent reproducibility in the measurements of BMD and body composition in nonhuman primates. We find DXA reliable for total and regional measurement in skeletal research and the evaluation of osteoporosis treatment with monkeys as animal models.

A method for evaluation of patient-specific lean body mass from limited-coverage CT images and its application in PERCIST: comparison with predictive equation.

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.

Localizing Epileptic Foci Before Surgery in Patients With MRI-Negative Refractory Epilepsy Using Statistical Parameter Mapping and Three-Dimensional Stereotactic Surface Projection Based on 18F-FDG PET.

Patients with refractory epilepsy are not only free of seizures after resecting epileptic foci, but also experience significantly improved quality of life. Fluorine-18-fluorodeoxyglucose positron-emission tomography (18F-FDG PET) is a promising avenue for detecting epileptic foci in patients with magnetic resonance imaging (MRI)-negative refractory epilepsy. However, the detection of epileptic foci by visual assessment based on 18F-FDG PET is often complicated by a variety of factors in clinical practice. Easy imaging methods based on 18F-FDG PET images, such as statistical parameter mapping (SPM) and three-dimensional stereotactic surface projection (3D-SSP), can objectively detect epileptic foci. In this study, the regions of surgical resection of patients with over 1 year follow-up and no seizures were defined as standard epileptic foci. We retrospectively analyzed the sensitivity of visual assessment, SPM and 3D-SSP based on 18F-FDG PET to detect epileptic foci in MRI-negative refractory epilepsy patients and obtained the sensitivities of visual assessment, SPM and 3D-SSP are 57, 70 and 60% respectively. Visual assessment combined with SPM or 3D-SSP can improve the sensitivity of detecting epileptic foci. The sensitivity was highest when the three methods were combined, but decreased consistency, in localizing epileptic foci. We conclude that SPM and 3D-SSP can be used as objective methods to detect epileptic foci before surgery in patients with MRI-negative refractory epilepsy. Visual assessment is the preferred method for PET image analysis in MRI-negative refractory epilepsy. When the visual assessment is inconsistent with the patient's electroclinical information, SPM or 3D-SSP was further selected to assess the epileptic foci. If the combination of the two methods still fails to accurately locate the epileptic foci, comprehensive evaluation can be performed by combining the three methods.

Electroclinical and Multimodality Neuroimaging Characteristics and Predictors of Post-Surgical Outcome in Focal Cortical Dysplasia Type IIIa.

Focal cortical dysplasia (FCD) type IIIa is an easily ignored cause of intractable temporal lobe epilepsy. This study aimed to analyze the clinical, electrophysiological, and imaging characteristics in FCD type IIIa and to search for predictors associated with postoperative outcome in order to identify potential candidates for epilepsy surgery. We performed a retrospective review including sixty-six patients with FCD type IIIa who underwent resection for drug-resistant epilepsy. We evaluated the clinical, electrophysiological, and neuroimaging features for potential association with seizure outcome. Univariate and multivariate analyses were conducted to explore their predictive role on the seizure outcome. We demonstrated that thirty-nine (59.1%) patients had seizure freedom outcomes (Engel class Ia) with a median postsurgical follow-up lasting 29.5 months. By univariate analysis, duration of epilepsy (less than 12 years) (p = 0.044), absence of contralateral insular lobe hypometabolism on PET/MRI (p Log-rank = 0.025), and complete resection of epileptogenic area (p Log-rank = 0.004) were associated with seizure outcome. The incomplete resection of the epileptogenic area (hazard ratio = 2.977, 95% CI 1.218-7.277, p = 0.017) was the only independent predictor for seizure recurrence after surgery by multivariate analysis. The results of past history, semiology, electrophysiological, and MRI were not associated with seizure outcomes. Carefully included patients with FCD type IIIa through a comprehensive evaluation of their clinical, electrophysiological, and neuroimaging characteristics can be good candidates for resection. Several preoperative factors appear to be predictive of the postoperative outcome and may help in optimizing the selection of ideal candidates to benefit from epilepsy surgery.

Sequential PET/diffusion-weighted imaging in the evaluation of myocardial perfusion and viability in coronary artery disease: a preliminary study.

OBJECTIVES: To evaluate the utility of sequential F-18 fluorodeoxyglucose PET/diffusion-weighted imaging in assessing myocardial perfusion and viability in coronary artery disease. METHODS: Fourteen coronary artery disease patients and five non-coronary artery disease subjects underwent sequential cardiac F-18 fluorodeoxyglucose PET/diffusion-weighted imaging using a trimodality PET/computed tomography-MRI system. The perfusion data were acquired by measuring low b-values apparent diffusion coefficient using diffusion-weighted imaging. Regional myocardial viability was determined by perfusion/metabolism patterns. The perfusion/metabolism patterns obtained by low b-values apparent diffusion coefficient/fluorodeoxyglucose uptake were analyzed and compared with the results from the combination of rest methoxyisobutylisonitrile (Tc-MIBI) myocardial perfusion single-photon emission computed tomography with F-18 fluorodeoxyglucose PET/computed tomography. RESULTS: Ten coronary artery disease patients and five non-coronary artery disease subjects were included in the final analysis. Low b-values apparent diffusion coefficient defects involved with 25 myocardial regions were demonstrated in nine coronary artery disease patients, while Tc-MIBI defects involved with 21 myocardial regions were shown in the same patients. The agreement between low b-values apparent diffusion coefficient and MIBI uptake was good in coronary artery disease patients (κ = 0.627, P < 0.001) and was better still in the whole subjects (κ = 0.733, P < 0.001). Low b-values apparent diffusion coefficient/fluorodeoxyglucose uptake demonstrated mismatch patterns in six coronary artery disease patients and MIBI/fluorodeoxyglucose uptake revealed mismatch patterns in seven coronary artery disease patients. Agreement in the evaluation of regional myocardial viability between low b-values apparent diffusion coefficient/fluorodeoxyglucose uptake and MIBI/fluorodeoxyglucose uptake was high in coronary artery disease patients (κ = 0.627, P < 0.001) and all subjects (κ = 0.728, P < 0.001). CONCLUSIONS: Low b-values apparent diffusion coefficient/fluorodeoxyglucose uptake is comparable to MIBI/fluorodeoxyglucose uptake in assessing perfusion/metabolism patterns, indicating that microperfusion might dominate the diffusion signal at low b-values and sequential PET/diffusion-weighted imaging might be useful to evaluate myocardial viability in coronary artery disease patients.