Preoperative [18]fluorodeoxyglucose-positron emission tomography/computed tomography in early stage breast cancer: Rates of distant metastases

AIM To investigate rates of distant metastases(DM) detected with [18]fluorodeoxyglucose-positron emissiontomography/computed tomography(^(18)FDG-PET/CT) in early stage invasive breast cancer.METHODS We searched the English language literature databases of PubM ed, EMBASE, ISI Web of Knowledge, Web of Science and Google Scholar, for publications on DM detected in patients who had ^(18)FDG-PET/CT scans as part of the staging for early stages of breast cancer(stage Ⅰ?and Ⅱ), prior to or immediately following surgery. Reports published between 2011 and 2017 were considered. The systematic review was conducted according to the PRISMA guidelines.RESULTS Among the 18 total studies included in the analysis, the risk of DM ranged from 0% to 8.3% and 0% to 12.9% for stage Ⅰ?and Ⅱ invasive breast cancer, respectively. Among the patients with clinical stage Ⅱ, the rate of occult metastases diagnosed by ^(18)FDG-PET/CT was 7.2%(range, 0%-19.6%) for stage ⅡA and 15.8%(range, 0%-40.8%) for stage ⅡB. In young patients(< 40-yearold), ^(18)FDG-PET/CT demonstrated a higher prevalence of DM at the time of diagnosis for those with aggressive histology(i.e., triple-negative receptors and poorly differentiated grade).CONCLUSION Young patients with poorly differentiated tumors and stage ⅡB triple-negative breast cancer may benefit from ^(18)FDG-PET/CT at initial staging to detect occult DM prior to surgery.

Discrimination between leucine-rich glioma-inactivated 1 antibody encephalitis and gamma-aminobutyric acid B receptor antibody encephalitis based on ResNet18

This study aims to discriminate between leucine-rich glioma-inactivated 1(LGI1)antibody encephalitis and gammaaminobutyric acid B(GABAB)receptor antibody encephalitis using a convolutional neural network(CNN)model.A total of 81 patients were recruited for this study.ResNet18,VGG16,and ResNet50 were trained and tested separately using 3828 positron emission tomography image slices that contained the medial temporal lobe(MTL)or basal ganglia(BG).Leave-one-out cross-validation at the patient level was used to evaluate the CNN models.The receiver operating characteristic(ROC)curve and the area under the ROC curve(AUC)were generated to evaluate the CNN models.Based on the prediction results at slice level,a decision strategy was employed to evaluate the CNN models’performance at patient level.The ResNet18 model achieved the best performance at the slice(AUC=0.86,accuracy=80.28%)and patient levels(AUC=0.98,accuracy=96.30%).Specifically,at the slice level,73.28%(1445/1972)of image slices with GABAB receptor antibody encephalitis and 87.72%(1628/1856)of image slices with LGI1 antibody encephalitis were accurately detected.At the patient level,94.12%(16/17)of patients with GABAB receptor antibody encephalitis and 96.88%(62/64)of patients with LGI1 antibody encephalitis were accurately detected.Heatmaps of the image slices extracted using gradient-weighted class activation mapping indicated that the model focused on the MTL and BG for classification.In general,the ResNet18 model is a potential approach for discriminating between LGI1 and GABAB receptor antibody encephalitis.Metabolism in the MTL and BG is important for discriminating between these two encephalitis subtypes.

^(18)F-FDG-PET glucose hypometabolism pattern in patients with epileptogenic hypothalamic hamartoma

Epileptogenic hypothalamic hamartoma is characterized by intractable gelastic seizures.A systematic analysis of the overall brain metabolic pattern in patients with hypothalamic hamartoma(HH)could facilitate the understanding of the epileptic brain network and the associated brain damage effects of HH.In this study,we retrospectively evaluated 27 patients with epileptogenic HH(8 female patients;age,2–33 years)by using ^(18)F-fluorodeoxyglucose-positron emission tomography.The correlations among tomography result,seizure type,sex,and structural magnetic resonance imaging were assessed.Whole metabolic patterns and voxel-based morphometry findings were assessed by group analysis with healthy controls.Assessment of the whole metabolic pattern in patients with HH revealed several regional metabolic reductions in the cerebrum and an overall metabolic reduction in the cerebellum.In addition,areas showing hypometabolism in the neocortex were more widely distributed ipsilaterally than contralaterally to the HH.Reductions in glucose metabolism and gray matter volume in the neocortex were predominant ipsilateral to the HH.In conclusion,the glucose hypometabolism pattern in patients with epileptogenic HH involved the neocortex,subcortical regions,and cerebellum.The characteristics of glucose hypometabolism differed across seizure type and sex.Reductions in glucose metabolism and structural changes may be based on different mechanisms,but both are likely to occur ipsilateral to the HH in the neocortex.We hypothesized that the dentato-rubro-thalamic tract and cerebro-ponto-cerebellar tract,which are responsible for intercommunication between the cerebral cortex,subcortical regions,and cerebellar regions,may be involved in a pathway related to seizure propagation,particularly gelastic seizures,in patients with HH.