Molecular phenotyping by gene expression profiling is common in contemporary cancer research and in molecular diagnostics. However, molecular profiling remains costly and resource intense to implement, and is just starting to be introduced into clinical diagnostics. Molecular changes, including genetic alterations and gene expression changes, occuring in tumors cause morphological changes in tissue, which can be observed on the microscopic level. The relationship between morphological patterns and some of the molecular phenotypes can be exploited to predict molecular phenotypes directly from routine haematoxylin and eosin (H&E) stained whole slide images (WSIs) using deep convolutional neural networks (CNNs). In this study, we propose a new, computationally efficient approach for disease specific modelling of relationships between morphology and gene expression, and we conducted the first transcriptome-wide analysis in prostate cancer, using CNNs to predict bulk RNA-sequencing estimates from WSIs of H&E stained tissue. The work is based on the TCGA PRAD study and includes both WSIs and RNA-seq data for 370 patients. Out of 15586 protein coding and sufficiently frequently expressed transcripts, 6618 had predicted expression significantly associated with RNA-seq estimates (FDR-adjusted p-value < 1*10-4) in a cross-validation. 5419 (81.9%) of these were subsequently validated in a held-out test set. We also demonstrate the ability to predict a prostate cancer specific cell cycle progression score directly from WSIs. These findings suggest that contemporary computer vision models offer an inexpensive and scalable solution for prediction of gene expression phenotypes directly from WSIs, providing opportunity for cost-effective large-scale research studies and molecular diagnostics.
SIGMMA: Hierarchical Graph-Based Multi-Scale Multi-modal Contrastive Alignment of Histopathology Image and Spatial Transcriptome
Wellcome Sanger Institute（沃森桑格研究所）；Cambridge Centre for AI in Medicine（剑桥人工智能医学中心）；Institute of AI for Health（人工智能与健康研究所）；Cambridge Stem Cell Institute（剑桥干细胞研究所）
Weakly Supervised Spatial Grounding for Discriminative Attention-Based Ultrasound-Histopathology Alignment in Prostate Cancer Grading
University of British Columbia（不列颠哥伦比亚大学）；Vector Institute（向量研究所）；Ordensklinikum Linz（林茨教团医院）；University of Alberta（阿尔伯塔大学）；Exact Imaging（Exact Imaging公司）
Pathologist Attention-Aligned Report Generation for Prostate Histopathology
Department of Computer Science, Stony Brook University（纽约州立大学石溪分校计算机科学系）；Department of Biomedical Informatics, Stony Brook University（纽约州立大学石溪分校生物医学信息学系）；Université Paris-Saclay, CentraleSupélec, Gustave Roussy, INSERM, IHU PRISM, Cancer Data Science Unit（巴黎萨克雷大学、中央理工高等电力学院、古斯塔夫·鲁西研究所、法国国家健康与医学研究院、PRISM综合大学医院、癌症数据科学单元）；Université Paris-Saclay, CentraleSupélec, MICS Laboratory（巴黎萨克雷大学、中央理工高等电力学院、MICS实验室）；Department of Pathology and Laboratory Medicine, Northwell Health Laboratories（诺斯韦尔健康实验室病理与检验医学部）；Department of Pathology, University of Utah School of Medicine（犹他大学医学院病理系）；Department of Psychology, Stony Brook University（纽约州立大学石溪分校心理学系）
Classification of Gleason Grading in Prostate Cancer Histopathology Images Using Deep Learning Techniques: YOLO, Vision Transformers, and Vision Mamba
School of Computer Engineering, Iran University of Science and Technology（伊朗科学技术大学计算机工程学院）；School of Electrical Engineering, Iran University of Science and Technology（伊朗科学技术大学电气工程学院）；School of Electrical Engineering, Shahrood Branch, Islamic Azad University（伊斯兰阿扎德大学沙赫鲁德分校电气工程学院）；Medical Sciences and Technologies Department, Science and Research Branch, Islamic Azad University（伊斯兰阿扎德大学科学研究分支医学科学与技术部门）
Large scale digital prostate pathology image analysis combining feature extraction and deep neural network
Stony Brook University（石溪大学）；Brigham and Women's Hospital（布莱根妇女医院）；Harvard Medical School（哈佛医学院）；Dana-Farber Cancer Institute（丹娜-法伯癌症研究所）；Fraunhofer Institute for Medical Image Computing MEVIS（弗劳恩霍夫医学图像计算研究所）；University of Bremen（不来梅大学）
Segmentation Strategies in Deep Learning for Prostate Cancer Diagnosis: A Comparative Study of Mamba, SAM, and YOLO
School of Electrical Engineering, Iran University of Science and Technology（伊朗科学技术大学电气工程学院）；School of Computer Engineering, Iran University of Science and Technology（伊朗科学技术大学计算机工程学院）；School of Electrical Engineering, Shahrood Branch, Islamic Azad University（伊斯兰阿扎德大学沙赫鲁德分校电气工程学院）；Medical Sciences and Technologies Department, Science and Research Branch, Islamic Azad University（伊斯兰阿扎德大学科学研究分支医学与技术系）；Biomedical Engineering Department, School of Electrical Engineering, Iran University of Science and Technology（伊朗科学技术大学电气工程学院生物医学工程系）
Maximizing T2-Only Prostate Cancer Localization from Expected Diffusion Weighted Imaging
UCL Hawkes Institute and the Department of Medical Physics and Biomedical Engineering, University College London（伦敦大学学院霍克斯研究所与医学物理与生物医学工程系）；Centre for Bioengineering, School of Engineering and Materials Science and Digital Environment Research Institute, Queen Mary University of London（伦敦玛丽女王大学工程与材料科学学院生物工程中心与数字环境研究所）；Centre for Medical Imaging, University College London（伦敦大学学院医学影像中心）；Division of Surgery & Interventional Science, University College London（伦敦大学学院外科与介入科学部）；Urological Research Network（泌尿研究网络）
Histopathological Spectrum-Guided Prostate Stratification via Segmentation-Assisted Diagnostic Transformer
College of Artificial Intelligence, Nankai University（南开大学人工智能学院）；Tianjin First Central Hospital（天津市第一中心医院）；School of Electronics and Information Engineering, Tiangong University（天津工业大学电子与信息工程学院）；School of Artificial Intelligence, Hebei University of Technology（河北工业大学人工智能学院）；North China Digital Health Technology Co., Ltd.（华北数字健康科技有限公司）；School of Computing and Information Systems, Singapore Management University（新加坡管理大学计算与信息系统学院）
Equivariant Imaging Biomarkers for Robust Unsupervised Segmentation of Histopathology
Department of Biomedical Engineering, Yale University（生物医学工程系，耶鲁大学）；Department of Radiology & Biomedical Imaging, Yale University（放射科与生物医学成像系，耶鲁大学）；Department of Urology, Yale University（泌尿外科系，耶鲁大学）；Medical Scientist Training Program, Yale University（医学科学家培训计划，耶鲁大学）
The PAR dataset: Prostate biopsy whole slide images from an underrepresented Middle Eastern population
Koya University（科亚大学）；Karolinska Institutet（卡罗林斯卡学院）；Hawler Medical University（哈勒医科大学）；PAR Private Hospital（PAR私立医院）；University of Sulaimani（苏莱曼尼亚大学）；Stavanger University Hospital（斯塔万格大学医院）；University of Stavanger（斯塔万格大学）；ELLIS Institute Finland（芬兰ELLIS研究所）；University of Turku（图尔库大学）
PAST: A multimodal single-cell foundation model for histopathology and spatial transcriptomics in cancer
King Abdullah University of Science and Technology (KAUST)（阿卜杜拉国王科技大学）；Shanghai Academy of Artificial Intelligence for Science（上海科学智能研究院）；Fudan University（复旦大学）；Zhongshan Hospital, Fudan University（复旦大学附属中山医院）
One Model to Magnify Them All: Efficient Scale-Invariant Histopathology via Conditional Normalization and Continuous Magnification Training
Sano Centre for Computational Medicine（萨诺计算医学中心）；AGH University of Krakow（克拉科夫AGH大学）；Institute of Informatics, HES-SO Valais-Wallis（瓦莱州瓦利斯高等专业学院信息学研究所）；Faculty of Medicine, University of Geneva (UNIGE)（日内瓦大学医学院）
Validation of Diagnostic Artificial Intelligence Models for Prostate Pathology in a Middle Eastern Cohort
Koya University（科亚大学）；Karolinska Institutet（卡罗林斯卡学院）；Hawler Medical University（霍勒医科大学）；PAR Private Hospital（PAR私立医院）；University of Sulaimani（苏莱曼尼大学）；Stavanger University Hospital（斯塔万格大学医院）；University of Stavanger（斯塔万格大学）
Extracting and analyzing 3D histomorphometric features related to perineural and lymphovascular invasion in prostate cancer
Stanford University（斯坦福大学）；University of Washington（华盛顿大学）；University of Chicago（芝加哥大学）；University of California, Berkeley（加州大学伯克利分校）；Public Health Agency of Catalonia（加泰罗尼亚公共卫生局）；Georgia Institute of Technology（佐治亚理工学院）；Emory University（埃默里大学）；Atlanta VA Medical Center（亚特兰大退伍军人事务医疗中心）；University of Pennsylvania（宾夕法尼亚大学）
Towards Explainable End-to-End Prostate Cancer Relapse Prediction from H&E Images Combining Self-Attention Multiple Instance Learning with a Recurrent Neural Network
University Medical Center Hamburg-Eppendorf（汉堡-埃彭多夫大学医学中心）；Universität Hamburg（汉堡大学）
AI-assisted prostate cancer detection and localisation on biparametric MR by classifying radiologist-positives
Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London（医学图像计算中心，医学物理与生物医学工程系，伦敦大学学院）；Div of Surgery & Interventional Sci, University College London（外科与介入科学部，伦敦大学学院）；School of Computer Science and Engineering, University of Westminster（计算机科学与工程学院，威斯敏斯特大学）
CHIMERA Challenge: Biochemical Recurrence Prediction in Prostate Cancer Patients using multimodal datasets
Radboud University Medical Center（拉德堡德大学医学中心）；Canisius Wilhelmina Hospital（卡尼修斯威廉明娜医院）；Oncode Institute（Oncode研究所）；Erasmus University Medical Center（伊拉斯姆斯大学医学中心）；Bydgoszcz University of Science and Technology（比得哥什科技大学）；Yerevan State Medical University（埃里温国立医科大学）；IMP Diagnostics（IMP诊断公司）
Stain Based Contrastive Co-training for Histopathological Image Analysis
University of Utah（犹他大学）；Scientific Computing and Imaging Institute, University of Utah（犹他大学科学计算与成像研究所）；Huntsman Cancer Institute, University of Utah（犹他大学亨茨曼癌症研究所）
Controllable Diffusion-Based Lesion Inpainting for Scalable Histopathology Data Augmentation
Department of Diagnostic Radiology, Li Ka Shing Faculty of Medicine, The University of Hong Kong（香港大学李嘉诚医学院诊断放射学系）；Department of Pathology, Li Ka Shing Faculty of Medicine, The University of Hong Kong（香港大学李嘉诚医学院病理学系）；Department of Anatomical and Cellular Pathology, Prince of Wales Hospital, The Chinese University of Hong Kong（香港中文大学威尔斯亲王医院解剖及细胞病理学系）；Department of Infectious Diseases and Public Health, Jockey Club College of Veterinary Medicine and Life Sciences, City University of Hong Kong（香港城市大学赛马会动物医学及生命科学院传染病及公共卫生学系）；CityU Veterinary Diagnostic Laboratory Co., Ltd., City University of Hong Kong（香港城市大学城市大学兽医诊断实验室有限公司）
Pan-Cancer Diagnostic Consensus Through Searching Archival Histopathology Images Using Artificial Intelligence
Huron Digital Pathology（休伦数字病理学公司）；University of Waterloo（滑铁卢大学）；Vector Institute（矢量研究所）；McMaster University（麦克马斯特大学）；University of Pittsburgh Medical Center（匹兹堡大学医学中心）
Pathomic Fusion: An Integrated Framework for Fusing Histopathology and Genomic Features for Cancer Diagnosis and Prognosis
Broad Institute of Harvard and MIT（哈佛大学与麻省理工学院博德研究所）；Dana-Farber Cancer Institute（丹娜法伯癌症研究院）；Department of Biomedical Informatics, Harvard Medical School（哈佛医学院生物医学信息学系）
Scaling Artificial Intelligence for Prostate Cancer Detection on MRI towards Organized Screening and Primary Diagnosis in a Global, Multiethnic Population (Study Protocol)
DeepGleason: a System for Automated Gleason Grading of Prostate Cancer using Deep Neural Networks
University of Augsburg（奥格斯堡大学）；University Hospital Augsburg（奥格斯堡大学医院）；BioM Biotech Cluster Development GmbH（BioM生物技术集群发展有限公司）；Bavarian Cancer Research Center (BZKF)（巴伐利亚癌症研究中心）
H&E-adversarial network: a convolutional neural network to learn stain-invariant features through Hematoxylin & Eosin regression
Institute of Information Systems, HES-SO (University of Applied Sciences and Arts Western Switzerland)（瑞士西部应用科学与艺术大学 信息系统研究所）；Department of Computer Science, University of Geneva（日内瓦大学 计算机科学系）；Department of Neurosciences, University of Padua（帕多瓦大学 神经科学系）；Inselspital, Bern Hospital（伯尔尼大学医院）；Medical Faculty, University of Geneva（日内瓦大学 医学院）
DISC: Latent Diffusion Models with Self-Distillation from Separated Conditions for Prostate Cancer Grading
Scientific Computing and Imaging Institute, University of Utah（犹他大学科学计算与成像研究所）；The Catholic University of Korea College of Medicine（韩国天主教大学医学院）；Case Western Reserve University（凯斯西储大学）；Huntsman Cancer Institute, University of Utah Health（犹他大学健康亨茨曼癌症研究所）；University of Utah（犹他大学）
