Multimodal Imaging to Delineate Tumor Heterogeneity in Cerebral Gliomas

Purpose: Magnetic resonance imaging (MRI) is the gold standard in visualizing brain tumors and their effects on adjacent structures. However, no reliable information concerning different tumor components and borders between perifocal edema and infiltration areas can be received. The aim of the study was to establish and evaluate a multimodal imaging concept, in order to differentiate different biological tumor components and to determine tumor borders. Materials and Methods: 12 patients with cerebral gliomas (four low and eight high grade) received a “morphological” MRI, a 3D MR spectroscopy and a T2* MR perfusion examination prior to surgery. Data was evaluated by defining different tumor components, which were entitled based upon their multimodal characteristics and histological data. Results: In high grade gliomas different components can be differentiated, which were described as: “true edema”, “cellular proliferation”, “vascular proliferation”, “cellular infiltration”, “tumor” and “necrosis”. In low grade gliomas, four different tumor components were found: “true edema”, “cellular infiltration”, “cellular proliferation” and “tumor”. Conclusion: With the applied multimodal imaging and a novel evaluation concept, it was possible to detect different tumor components, which could be helpful in detecting the optimal sites for tumor biopsy. Especially in morphological “edema appearing” sites, this knowledge could be important for the adaption of tumor resection borders and the planning of radiation therapy. Further studies with more patients and histological correlation are needed.

Advancing Brain Tumor Analysis through Dynamic Hierarchical Attention for Improved Segmentation and Survival Prognosis

Gliomas,the most prevalent primary brain tumors,require accurate segmentation for diagnosis and risk assess-ment.In this paper,we develop a novel deep learning-based method,the Dynamic Hierarchical Attention for Improved Segmentation and Survival Prognosis(DHA-ISSP)model.The DHA-ISSP model combines a three-band 3D convolutional neural network(CNN)U-Net architecture with dynamic hierarchical attention mechanisms,enabling precise tumor segmentation and survival prediction.The DHA-ISSP model captures fine-grained details and contextual information by leveraging attention mechanisms at multiple levels,enhancing segmentation accuracy.By achieving remarkable results,our approach surpasses 369 competing teams in the 2020 Multimodal Brain Tumor Segmentation Challenge.With a Dice similarity coefficient of 0.89 and a Hausdorff distance of 4.8 mm,the DHA-ISSP model demonstrates its effectiveness in accurately segmenting brain tumors.We also extract radio mic characteristics from the segmented tumor areas using the DHA-ISSP model.By applying cross-validation of decision trees to the selected features,we identify crucial predictors for glioma survival,enabling personalized treatment strategies.Utilizing the DHA-ISSP model and the desired features,we assess patients’overall survival and categorize survivors into short,mid,in addition to long survivors.The proposed work achieved impressive performance metrics,including the highest accuracy of 0.91,precision of 0.84,recall of 0.92,F1 score of 0.88,specificity of 0.94,sensitivity of 0.92,area under the curve(AUC)value of 0.96,and the lowest mean absolute error value of 0.09 and mean squared error value of 0.18.These results clearly demonstrate the superiority of the proposed system in accurately segmenting brain tumors and predicting survival outcomes,highlighting its significant merit and potential for clinical applications.

The differential effects of integrase strand transfer inhibitors and efavirenz on neuropsychiatric conditions and brain imaging in HIV-positive men who have sex with men

Integrase strand transfer inhibitors(INSTIs)have emerged as the first‐line choice for treating human immunodeficiency virus(HIV)infection due to their superior efficacy and safety.However,the impact of INSTIs on the development of neuropsychiatric conditions in people living with HIV(PLWH)is not fully understood due to limited data.In this study,we conducted a cross‐sectional examination of PLWH receiving antiretroviral therapy,with a specific focus on HIV‐positive men who have sex with men(MSM)on INSTI‐based regimens(n=61)and efavirenz(EFV)‐based regimens(n=28).Participants underwent comprehensive neuropsychiatric evaluations and multimodal magnetic resonance imaging(MRI)scans,including T1‐weighted images and resting‐state functional MRI.Compared to the EFV group,the INSTI group exhibited primarily reduced gray matter volume(GMV)in the right superior parietal gyrus,higher regional homogeneity(ReHo)in the left postcentral gyrus,lower ReHo in the right orbital part of the inferior frontal gyrus,and increased voxel‐wise functional connectivity for the seed region in the left inferior temporal gyrus with clusters in the right cuneus.Furthermore,the analysis revealed a main effect of antiretroviral drugs on GMV changes,but no main effect of neuropsychiatric disorders or their interaction.The repeated analysis of participants who did not switch regimens confirmed the GMV changes in the INSTI group,validating the initial findings.Our study demonstrated gray matter atrophy and functional brain changes in PLWH on INSTI‐based regimens compared to those on EFV‐based regimens.These neuroimaging results provide valuable insights into the characteristics of brain network modifications in PLWH receiving INSTI‐based regimens。