Mathematical modelling of tumor growth is one of the most useful and inexpensive approaches to determine and predict the stage, size and progression of tumors in realistic geometries. Moreover, these models has been used to get an insight into cancer growth and invasion and in the analysis of tumor size and geometry for applications in cancer treatment and surgical planning. The present revision attempts to present a general perspective of the use of models based on reaction-diffusion equations not only for the description of tumor growth in gliomas, addressing for processes such as tumor heterogeneity, hypoxia, dormancy and necrosis, but also its potential use as a tool in designing optimized and patient specific therapies.
In Vivo Quantification of Glioma-Induced Solid Stress Using MR Elastography and Deformable Image Registration
Charité – Universitätsmedizin Berlin（柏林夏里特医科大学）；Berlin Institute of Health at Charité – Universitätsmedizin Berlin（柏林健康研究所（隶属于柏林夏里特医科大学））；Humboldt University, Berlin（柏林洪堡大学）；Physikalisch-Technische Bundesanstalt, Berlin（德国联邦物理技术研究院）；Technical University Berlin, Einstein Center Digital Future（柏林工业大学爱因斯坦数字中心）
Individualizing Glioma Radiotherapy Planning by Optimization of Data and Physics-Informed Discrete Loss
University of Zurich（苏黎世大学）；Technical University of Munich（慕尼黑工业大学）；Harvard University（哈佛大学）；ETH Zurich（苏黎世联邦理工学院）；Zuse Institute（祖斯研究所）；University of California, Irvine（加州大学尔湾分校）；TUM School of Medicine and Health（TUM医学院与健康学院）
Predicted disease compositions of human gliomas estimated from multiparametric MRI can predict endothelial proliferation, tumor grade, and overall survival
Indiana University School of Medicine（印第安纳大学医学院）；Purdue University（普渡大学）；Dayton Children’s Hospital（代顿儿童医院）
A Voxel-Wise Uncertainty-Guided Framework for Glioma Segmentation Using Spherical Projection-Based U-Net and Localized Refinement in Multi-Parametric MRI
MRI-based classification of IDH mutation and 1p/19q codeletion status of gliomas using a 2.5D hybrid multi-task convolutional neural network
Washington University in St. Louis（圣路易斯华盛顿大学）；Mallinckrodt Institute of Radiology（马林克罗特放射研究所）；Washington University School of Medicine（华盛顿大学医学院）；Institute for Informatics（信息学研究所）
异柠檬酸脱氢酶（IDH）突变和1 p/19 q共缺失状态是胶质瘤的重要预后标志。目前，它们是使用侵入性程序确定的。我们的目标是开发基于人工智能的方法来非侵入性地确定MRI中的这些分子改变。为此，2648例胶质瘤患者的术前MRI扫描（II-IV级）从华盛顿大学医学院收集（WUSM; n = 835）和公开可用的数据集，即脑肿瘤分割（BraTS; n = 378），LGG 1 p/19 q（n = 159），Ivy胶质母细胞瘤Atlas项目（Ivy GAP; n = 41）、癌症基因组图谱（TCGA; n = 461）和伊拉斯谟神经胶质瘤数据库（EGD; n = 774）。提出了一种2.5D混合卷积神经网络，通过利用来自MR扫描的成像特征和来自临床记录和肿瘤位置的先验知识特征，同时定位肿瘤并对其分子状态进行分类。模型在一个内部（TCGA）和两个外部（WUSM和EGD）测试集上进行了测试。对于IDH，表现最好的模型在内部、WUSM和EGD测试集上分别实现了0.925、0.874、0.933的受试者操作特征下的面积（AUROC）和0.899、0.702、0.853的精确-召回曲线下的面积（AUPRC）。对于1 p/19 q，最佳模型在这三个数据分割上分别实现了0.782，0.754，0.842的AUROC和0.588，0.713，0.782的AUPRC。该模型对未知数据的高准确性展示了其泛…
The Brain Tumor Segmentation (BraTS) Challenge 2023: Glioma Segmentation in Sub-Saharan Africa Patient Population (BraTS-Africa)
Medical Artificial Intelligence Laboratory (MAI Lab)（医学人工智能实验室（MAI实验室））；Department of Radiation Biology, Radiotherapy and Radiodiagnosis, University of Lagos（拉各斯大学放射生物学、放射治疗与放射诊断系）；Department of Radiology, University of California, San Diego（加州大学圣地亚哥分校放射科）；Crestview Radiology Limited（Crestview放射科有限公司）；Lagos University Teaching Hospital（拉各斯大学教学医院）；Lagos State University Teaching Hospital, Ikeja, Lagos, Nigeria（拉各斯州大学教学医院，伊凯贾，拉各斯，尼日利亚）；NSIA-Kano Diagnostic Center, Kano Nigeria（NSIA-卡诺诊断中心，卡诺，尼日利亚）；Nnamdi Azikiwe University Teaching Hospital, Nnewi, Anambra State, Nigeria（恩内迪·阿齐基韦大学教学医院，恩韦伊，安纳博拉州，尼日利亚）；Federal Medical Centre, Abeokuta, Ogun State, Nigeria（阿博库塔联邦医疗中心，奥贡州，尼日利亚）；Federal Medical Centre, Umahia, Abia State, Nigeria（乌马希亚联邦医疗中心，阿比亚州，尼日利亚）；National Hospital Abuja, FCT, Nigeria（阿布贾国家医院，联邦首都区，尼日利亚）；Benue State University Teaching Hospital, Markurdi, Benue State, Nigeria（贝努埃州大学教学医院，马库尔迪，贝努埃州，尼日利亚）；Duke University Medical Center, Department of Radiology, USA（达特茅斯大学医学中心，放射科，美国）；University of California San Francisco, CA, USA（加州大学旧金山分校，CA，美国）；Yale University, New Haven, CT, USA（耶鲁大学，新 Haven，CT，美国）；Children's National Hospital, Washington DC, USA（儿童医院华盛顿特区，华盛顿特区，美国）；George Washington University, Washington DC, USA（乔治·华盛顿大学，华盛顿特区，美国）；Sage Bionetworks, USA（Sage生物网络，美国）；Department of Neuroradiology, Technical University of Munich, Munich, Germany（慕尼黑技术大学神经放射科系，慕尼黑，德国）；Helmholtz Research Center, Munich, Germany（海德堡研究中心，慕尼黑，德国）；Duke University Medical Center, Department of Radiation Oncology, USA（达特茅斯大学医学中心，放射肿瘤科，美国）；Children’s Hospital of Philadelphia, University of Pennsylvania, Philadelphia, PA, USA（费城儿童医院，宾夕法尼亚大学，费城，PA，美国）；Center for AI and Data Science for Integrated Diagnostics (AI2D) & Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA（人工智能与数据科学整合诊断中心（AI2D）及生物医学影像计算与分析中心（CBICA），宾夕法尼亚大学，费城，PA，美国）；Athinoula A Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, USA（Athinoula A Martinos生物医学影像中心，马萨诸塞总医院，波士顿，MA，美国）；University of Zurich, Switzerland（苏黎世大学，瑞士）；Cancer Imaging Program, National Cancer Institute, National Institutes of Health, Bethesda, MD 20814, USA（癌症成像计划，国家癌症研究所，国家卫生研究院，贝塞斯达，MD 20814，美国）；Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania, Philadelphia, USA（临床流行病学与生物统计学中心，宾夕法尼亚大学，费城，美国）；Department of Applied Mathematics and Computer Science, Technical University of Denmark, Denmark（应用数学与计算机科学系，丹麦技术大学，丹麦）；Mayo Clinic, MN, USA（梅奥诊所，MN，美国）；Precision FDA, U.S. Food and Drug Administration, Silver Spring, MD, USA（Precision FDA，美国食品药品监督管理局，Silver Spring，MD，美国）；Booz Allen Hamilton, McLean, VA, USA（Booz Allen Hamilton，麦肯，VA，美国）；Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA（放射科，佩尔曼医学院，宾夕法尼亚大学，费城，PA，美国）；Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA（病理学与实验室医学系，佩尔曼医学院，宾夕法尼亚大学，费城，PA，美国）；Center for Global Health, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA（全球健康中心，佩尔曼医学院，宾夕法尼亚大学，费城，宾夕法尼亚，美国）；Montreal Neurological Institute, McGill University, Montreal, Canada（蒙特利尔神经科学研究所，麦吉尔大学，蒙特利尔，加拿大）；Department of Medicine, University of Cape Town, South Africa（医学系，开普敦大学，南非）；Department of Radiation Medicine, University of Cape Town, South Africa（放射医学系，开普敦大学，南非）
Generative Style Transfer for MRI Image Segmentation: A Case of Glioma Segmentation in Sub-Saharan Africa
Institute of Mathematical Science, Strathmore University（斯特拉斯莫尔大学数学科学学院）；Faculty of Science and Engineering, University of Hull（赫尔大学科学与工程学院）；Technical University of Mombasa（蒙巴萨理工大学）；Lawson Health Research Institute（劳森健康研究所）；University of British Columbia（不列颠哥伦比亚大学）；University of Nairobi（内罗毕大学）；University of Cape Town（开普敦大学）；Montreal Neurological Institute, McGill University（麦吉尔大学蒙特利尔神经学研究所）；Brain Mind Institute, The Aga Khan University（阿迦汗大学脑与心智研究所）；Medical Physics Unit, McGill University（麦吉尔大学医学物理部门）
