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Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the BRATS challenge

arXiv

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arXiv 2018年

作者： Bakas, Spyridon Reyes, Mauricio Jakab, Andras Bauer, Stefan Rempfler, Markus Crimi, Alessandro Shinohara, Russell Takeshi Berger, Christoph Ha, Sung Min Rozycki, Martin Prastawa, Marcel Alberts, Esther Lipkova, Jana Freymann, John Kirby, Justin Bilello, Michel Fathallah-Shaykh, Hassan M. Wiest, Roland Kirschke, Jan Wiestler, Benedikt Colen, Rivka Kotrotsou, Aikaterini Lamontagne, Pamela Marcus, Daniel Milchenko, Mikhail Nazeri, Arash Weber, Marc-Andr Mahajan, Abhishek Baid, Ujjwal Gerstner, Elizabeth Kwon, Dongjin Acharya, Gagan Agarwal, Manu Alam, Mahbubul Albiol, Alberto Albiol, Antonio Albiol, Francisco J. Alex, Varghese Allinson, Nigel Amorim, Pedro H.A. Amrutkar, Abhijit Anand, Ganesh Andermatt, Simon Arbel, Tal Arbelaez, Pablo Avery, Aaron Azmat, Muneeza Pranjal, B. Bai, Wenjia Banerjee, Subhashis Barth, Bill Batchelder, Thomas Batmanghelich, Kayhan Battistella, Enzo Beers, Andrew Belyaev, Mikhail Bendszus, Martin Benson, Eze Bernal, Jose Bharath, Halandur Nagaraja Biros, George Bisdas, Sotirios Brown, James Cabezas, Mariano Cao, Shilei Cardoso, Jorge M. Carver, Eric N. Casamitjana, Adri Castillo, Laura Silvana Cat, Marcel Cattin, Philippe Cérigues, Albert Chagas, Vinicius S. Chandra, Siddhartha Chang, Yi-Ju Chang, Shiyu Chang, Ken Chazalon, Joseph Chen, Shengcong Chen, Wei Chen, Jefferson W. Chen, Zhaolin Cheng, Kun Choudhury, Ahana Roy Chylla, Roger Clrigues, Albert Colleman, Steven Colmeiro, Ramiro German Rodriguez Combalia, Marc Costa, Anthony Cui, Xiaomeng Dai, Zhenzhen Dai, Lutao Daza, Laura Alexandra Deutsch, Eric Ding, Changxing Dong, Chao Dong, Shidu Dudzik, Wojciech Eaton-Rosen, Zach Egan, Gary Escudero, Guilherme Estienne, Tho Everson, Richard Fabrizio, Jonathan Fan, Yong Fang, Longwei Feng, Xue Ferrante, Enzo Fidon, Lucas Fischer, Martin French, Andrew P. Fridman, Naomi Fu, Huan Fuentes, David Gao, Yaozong Gates, Evan Gering, David Gholami, Amir Gierke, Willi Glocker, Ben Gong, Mingming Gonzlez-Vill, Sandra Grosges, T. Guan, Yuanfang Guo, Sheng Gupta, Sudeep Han, Woo-Sup Han, Il Song Harmuth, Ko Center for Biomedical Image Computing and Analytics University of Pennsylvania PhiladelphiaPA United States Department of Radiology Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Department of Pathology and Laboratory Medicine Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Institute for Surgical Technology and Biomechanics University of Bern Bern Switzerland Center for MR-Research University Children's Hospital Zurich Zurich Switzerland Support Centre for Advanced Neuroimaging Inselspital Institute for Diagnostic and Interventional Neuroradiology Bern University Hospital Bern Switzerland University Hospital of Zurich Zurich Switzerland Center for Clinical Epidemiology and Biostatistics University of Pennsylvania Philadelphia United States Image-Based Biomedical Modeling Group Technical University of Munich Munich Germany Icahn School of Medicine Mount Sinai Health System New YorkNY United States Leidos Biomedical Research Inc. Frederick National Laboratory for Cancer Research FrederickMD21701 United States Cancer Imaging Program National Cancer Institute National Institutes of Health BethesdaMD20814 United States Department of Neurology University of Alabama at Birmingham BirminghamAL United States Department of Diagnostic Radiology University of Texas MD Anderson Cancer Center HoustonTX United States Department of Psychology Washington University St. LouisMO United States Neuroimaging Informatics and Analysis Center Washington University St. LouisMO United States Department of Radiology Washington University St. LouisMO United States Institute of Diagnostic and Interventional Radiology Pediatric Radiology and Neuroradiology University Medical Center Rostock Ernst-Heydemann-Str. 6 Rostock18057 Germany Tata Memorial Centre Homi Bhabha National Institute Mumbai India Shri Guru Gobind Singhji Institute of Engineering and Technology Nanded India NVIDIA Santa Clara

Gliomas are the most common primary brain malignancies, with different degrees of aggressiveness, variable prognosis and various heterogeneous histologic sub-regions, i.e., peritumoral edematous/invaded tissue, necrotic core, active and non-enhancing core. This intrinsic heterogeneity is also portrayed in their radio-phenotype, as their sub-regions are depicted by varying intensity profiles disseminated across multi-parametric magnetic resonance imaging (mpMRI) scans, reflecting varying biological properties. Their heterogeneous shape, extent, and location are some of the factors that make these tumors difficult to resect, and in some cases inoperable. The amount of resected tumor is a factor also considered in longitudinal scans, when evaluating the apparent tumor for potential diagnosis of progression. Furthermore, there is mounting evidence that accurate segmentation of the various tumor sub-regions can offer the basis for quantitative image analysis towards prediction of patient overall survival. This study assesses the state-of-the-art machine learning (ML) methods used for brain tumor image analysis in mpMRI scans, during the last seven instances of the International Brain Tumor Segmentation (BraTS) challenge, i.e., 2012-2018. Specifically, we focus on i) evaluating segmentations of the various glioma sub-regions in pre-operative mpMRI scans, ii) assessing potential tumor progression by virtue of longitudinal growth of tumor sub-regions, beyond use of the RECIST/RANO criteria, and iii) predicting the overall survival from pre-operative mpMRI scans of patients that underwent gross total resection. Finally, we investigate the challenge of identifying the best ML algorithms for each of these tasks, considering that apart from being diverse on each instance of the challenge, the multi-institutional mpMRI BraTS dataset has also been a continuously evolving/growing dataset. Copyright © 2018, The Authors. All rights reserved.

关键词： Tumors

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26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3 Antwerp, Belgium. 15-20 July 2017 Abstracts

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BMC NEUROSCIENCE 2017年第SUPPL 1期18卷 95-176页

作者： [Anonymous] Department of Neuroscience Yale University New Haven CT 06520 USA Department Physiology & Pharmacology SUNY Downstate Brooklyn NY 11203 USA NYU School of Engineering 6 MetroTech Center Brooklyn NY 11201 USA Departament de Matemàtica Aplicada Universitat Politècnica de Catalunya Barcelona 08028 Spain Institut de Neurobiologie de la Méditerrannée (INMED) INSERM UMR901 Aix-Marseille Univ Marseille France Center of Neural Science New York University New York NY USA Aix-Marseille Univ INSERM INS Inst Neurosci Syst Marseille France Laboratoire de Physique Théorique et Modélisation CNRS UMR 8089 Université de Cergy-Pontoise 95300 Cergy-Pontoise Cedex France Department of Mathematics and Computer Science ENSAT Abdelmalek Essaadi’s University Tangier Morocco Laboratory of Natural Computation Department of Information and Electrical Engineering and Applied Mathematics University of Salerno 84084 Fisciano SA Italy Department of Medicine University of Salerno 84083 Lancusi SA Italy Dipartimento di Fisica Università degli Studi Aldo Moro Bari and INFN Sezione Di Bari Italy Data Analysis Department Ghent University Ghent Belgium Coma Science Group University of Liège Liège Belgium Cruces Hospital and Ikerbasque Research Center Bilbao Spain BIOtech Department of Industrial Engineering University of Trento and IRCS-PAT FBK 38010 Trento Italy Department of Data Analysis Ghent University Ghent 9000 Belgium The Wellcome Trust Centre for Neuroimaging University College London London WC1N 3BG UK Department of Electronic Engineering NED University of Engineering and Technology Karachi Pakistan Blue Brain Project École Polytechnique Fédérale de Lausanne Lausanne Switzerland Departement of Mathematics Swansea University Swansea Wales UK Laboratory for Topology and Neuroscience at the Brain Mind Institute École polytechnique fédérale de Lausanne Lausanne Switzerland Institute of Mathematics University of Aberdeen Aberdeen Scotland UK Department of Integrativ

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The Liver Tumor Segmentation Benchmark (LiTS)

arXiv

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arXiv 2019年

作者： Bilic, Patrick Christ, Patrick Li, Hongwei Bran Vorontsov, Eugene Ben-Cohen, Avi Kaissis, Georgios Szeskin, Adi Jacobs, Colin Mamani, Gabriel Efrain Humpire Chartrand, Gabriel Lohöfer, Fabian Holch, Julian Walter Sommer, Wieland Hofmann, Felix Hostettler, Alexandre Lev-Cohain, Naama Drozdzal, Michal Amitai, Michal Marianne Vivanti, Refael Sosna, Jacob Ezhov, Ivan Sekuboyina, Anjany Navarro, Fernando Kofler, Florian Paetzold, Johannes C. Shit, Suprosanna Hu, Xiaobin Lipková, Jana Rempfler, Markus Piraud, Marie Kirschke, Jan Wiestler, Benedikt Zhang, Zhiheng Hülsemeyer, Christian Beetz, Marcel Ettlinger, Florian Antonelli, Michela Bae, Woong Bellver, Míriam Bi, Lei Chen, Hao Chlebus, Grzegorz Dam, Erik B. Dou, Qi Fu, Chi-Wing Georgescu, Bogdan Giró-I-Nieto, Xavier Gruen, Felix Han, Xu Heng, Pheng-Ann Hesser, Jürgen Moltz, Jan Hendrik Igel, Christian Isensee, Fabian Jäger, Paul Jia, Fucang Kaluva, Krishna Chaitanya Khened, Mahendra Kim, Ildoo Kim, Jae-Hun Kim, Sungwoong Kohl, Simon Konopczynski, Tomasz Kori, Avinash Krishnamurthi, Ganapathy Li, Fan Li, Hongchao Li, Junbo Li, Xiaomeng Lowengrub, John Ma, Jun Maier-Hein, Klaus Maninis, Kevis-Kokitsi Meine, Hans Merhof, Dorit Pai, Akshay Perslev, Mathias Petersen, Jens Pont-Tuset, Jordi Qi, Jin Qi, Xiaojuan Rippel, Oliver Roth, Karsten Sarasua, Ignacio Schenk, Andrea Shen, Zengming Torres, Jordi Wachinger, Christian Wang, Chunliang Weninger, Leon Wu, Jianrong Xu, Daguang Yang, Xiaoping Yu, Simon Chun-Ho Yuan, Yading Yue, Miao Zhang, Liping Cardoso, Jorge Bakas, Spyridon Braren, Rickmer Heinemann, Volker Pal, Christopher Tang, An Kadoury, Samuel Soler, Luc van Ginneken, Bram Greenspan, Hayit Joskowicz, Leo Menze, Bjoern Department of Informatics Technical University of Munich Germany Department of Quantitative Biomedicine University of Zurich Switzerland Ecole Polytechnique de Montréal Canada Department of Medical Imaging Radboud University Medical Center Nijmegen Netherlands Department of Biomedical Engineering Tel-Aviv University Israel Germany Pattern Analysis and Learning Group Department of Radiation Oncology Heidelberg University Hospital Heidelberg Germany Philips Research China Philips China Innovation Campus Shanghai China School of Biomedical Engineering & Imaging Sciences King0s College London London United Kingdom Institute for AI in Medicine Technical University of Munich Germany Department of Computer Science Guangdong University of Foreign Studies China Institute for diagnostic and interventional radiology Klinikum rechts der Isar Technical University of Munich Germany Institute for Diagnostic and Interventional Neuroradiology Klinikum Rechts der Isar Technical University of Munich Germany Department of Hepatobiliary Surgery The Affiliated Drum Tower Hospital Nanjing University Medical School China Department of Computing Imperial College London London United Kingdom Institute for Tissue Engineering and Regenerative Medicine Helmholtz Zentrum München Neuherberg Germany Brigham and Women's Hospital Harvard Medical School United States School of Computer Science and Engineering The Hebrew University of Jerusalem Israel University of Pennsylvania PA United States Pte. Ltd. Singapore Medical Imaging and Reconstruction Lab Department of Engineering Design Indian Institute of Technology Madras India Sensetime Shanghai China Department of Radiology Perelman School of Medicine University of Pennsylvania United States Department of Pathology and Laboratory Medicine Perelman School of Medicine University of Pennsylvania PA United States Co. Ltd China MontréalQC Canada Department of Radiology Radiation Oncology and Nuclear Medicine University of Montréal

In this work, we report the set-up and results of the Liver Tumor Segmentation Benchmark (LiTS), which was organized in conjunction with the IEEE International Symposium on Biomedical Imaging (ISBI) 2017 and the International Conferences on Medical Image Computing and Computer-Assisted Intervention (MICCAI) 2017 and 2018. The image dataset is diverse and contains primary and secondary tumors with varied sizes and appearances with various lesion-to-background levels (hyper-/hypo-dense), created in collaboration with seven hospitals and research institutions. Seventy-five submitted liver and liver tumor segmentation algorithms were trained on a set of 131 computed tomography (CT) volumes and were tested on 70 unseen test images acquired from different patients. We found that not a single algorithm performed best for both liver and liver tumors in the three events. The best liver segmentation algorithm achieved a Dice score of 0.963, whereas, for tumor segmentation, the best algorithms achieved Dices scores of 0.674 (ISBI 2017), 0.702 (MICCAI 2017), and 0.739 (MICCAI 2018). Retrospectively, we performed additional analysis on liver tumor detection and revealed that not all top-performing segmentation algorithms worked well for tumor detection. The best liver tumor detection method achieved a lesion-wise recall of 0.458 (ISBI 2017), 0.515 (MICCAI 2017), and 0.554 (MICCAI 2018), indicating the need for further research. LiTS remains an active benchmark and resource for research, e.g., contributing the liver-related segmentation tasks in http://***/. In addition, both data and online evaluation are accessible via ***. © 2019, CC BY-NC-ND.

关键词： Deep learning

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Correction to: 2021 Taxonomic update of phylum Negarnaviricota (Riboviria: Orthornavirae), including the large orders Bunyavirales and Mononegavirales

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Archives of virology 2021年第12期166卷 3567-3579页

作者： Jens H Kuhn Scott Adkins Bernard R Agwanda Rim Al Kubrusli Sergey V Alkhovsky Gaya K Amarasinghe Tatjana Avšič-Županc María A Ayllón Justin Bahl Anne Balkema-Buschmann Matthew J Ballinger Christopher F Basler Sina Bavari Martin Beer Nicolas Bejerman Andrew J Bennett Dennis A Bente Éric Bergeron Brian H Bird Carol D Blair Kim R Blasdell Dag-Ragnar Blystad Jamie Bojko Wayne B Borth Steven Bradfute Rachel Breyta Thomas Briese Paul A Brown Judith K Brown Ursula J Buchholz Michael J Buchmeier Alexander Bukreyev Felicity Burt Carmen Büttner Charles H Calisher Mengji Cao Inmaculada Casas Kartik Chandran Rémi N Charrel Qi Cheng Yuya Chiaki Marco Chiapello Il-Ryong Choi Marina Ciuffo J Christopher S Clegg Ian Crozier Elena Dal Bó Juan Carlos de la Torre Xavier de Lamballerie Rik L de Swart Humberto Debat Nolwenn M Dheilly Emiliano Di Cicco Nicholas Di Paola Francesco Di Serio Ralf G Dietzgen Michele Digiaro Olga Dolnik Michael A Drebot J Felix Drexler William G Dundon W Paul Duprex Ralf Dürrwald John M Dye Andrew J Easton Hideki Ebihara Toufic Elbeaino Koray Ergünay Hugh W Ferguson Anthony R Fooks Marco Forgia Pierre B H Formenty Jana Fránová Juliana Freitas-Astúa Jingjing Fu Stephanie Fürl Selma Gago-Zachert George Fú Gāo María Laura García Adolfo García-Sastre Aura R Garrison Thomas Gaskin Jean-Paul J Gonzalez Anthony Griffiths Tony L Goldberg Martin H Groschup Stephan Günther Roy A Hall John Hammond Tong Han Jussi Hepojoki Roger Hewson Jiang Hong Ni Hong Seiji Hongo Masayuki Horie John S Hu Tao Hu Holly R Hughes Florian Hüttner Timothy H Hyndman M Ilyas Risto Jalkanen Dàohóng Jiāng Gilda B Jonson Sandra Junglen Fujio Kadono Karia H Kaukinen Michael Kawate Boris Klempa Jonas Klingström Gary Kobinger Igor Koloniuk Hideki Kondō Eugene V Koonin Mart Krupovic Kenji Kubota Gael Kurath Lies Laenen Amy J Lambert Stanley L Langevin Benhur Lee Elliot J Lefkowitz Eric M Leroy Shaorong Li Longhui Li Jiànróng Lǐ Huazhen Liu Igor S Lukashevich Piet Maes William Marciel de Souza Marco Marklewitz Sergio H Marshall Shin-Yi L Marzano Se Integrated Research Facility at Fort Detrick National Institute of Allergy and Infectious Diseases National Institutes of Health Frederick MD USA. kuhnjens@mail.nih.gov. United States Department of Agriculture Agricultural Research Service US Horticultural Research Laboratory Fort Pierce FL USA. Zoology Department National Museums of Kenya Nairobi Kenya. Jomo Kenyatta University of Agriculture & Technology Nairobi Kenya. Division Phytomedicine Faculty of Life Sciences Humboldt-Universität zu Berlin Berlin Germany. D.I. Ivanovsky Institute of Virology of N.F. Gamaleya National Center on Epidemiology and Microbiology of Ministry of Health of Russian Federation Moscow Russia. Department of Pathology and Immunology Washington University School of Medicine St. Louis MO USA. Faculty of Medicine University of Ljubljana Ljubljana Slovenia. Centro de Biotecnología y Genómica de Plantas Universidad Politécnica de Madrid-Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria Campus de Montegancedo Pozuelo de Alarcón Madrid Spain. Departamento de Biotecnología-Biología Vegetal Escuela Técnica Superior de Ingeniería Agronómica Alimentaria y de Biosistemas Universidad Politécnica de Madrid Madrid Spain. Center for Ecology of Infectious Diseases Department of Infectious Diseases Department of Epidemiology and Biostatistics Insitute of Bioinformatics University of Georgia Athens GA USA. Institute of Novel and Emerging Infectious Diseases Friedrich-Loeffler-Institut Federal Research Institute for Animal Health Greifswald-Insel Riems Germany. Department of Biological Sciences Mississippi State University Mississippi State MS USA. Center for Microbial Pathogenesis Institute for Biomedical Sciences Georgia State University Atlanta GA USA. Edge BioInnovation Consulting and Mgt Frederick MD USA. Institute of Diagnostic Virology Friedrich-Loeffler-Institut Greifswald-Insel Riems Germany. UFyMA INTA-CONICET Cordoba Argentina. Genomics and Bioinformatics D

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Global, regional, and national burden of diabetes from 1990 to 2021, with projections of prevalence to 2050: a systematic analysis for the Global Burden of Disease Study 2021

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The Lancet 2023年第10397期402卷 203-234页

作者： Ong, Kanyin Liane Stafford, Lauryn K. McLaughlin, Susan A. Boyko, Edward J. Vollset, Stein Emil Smith, Amanda E. Dalton, Bronte E. Duprey, Joe Cruz, Jessica A. Hagins, Hailey Lindstedt, Paulina A. Aali, Amirali Abate, Yohannes Habtegiorgis Abate, Melsew Dagne Abbasian, Mohammadreza Abbasi-Kangevari, Zeinab Abbasi-Kangevari, Mohsen ElHafeez, Samar Abd Abd-Rabu, Rami Abdulah, Deldar Morad Abdullah, Abu Yousuf Md Abedi, Vida Abidi, Hassan Aboagye, Richard Gyan Abolhassani, Hassan Abu-Gharbieh, Eman Abu-Zaid, Ahmed Adane, Tigist Demssew Adane, Denberu Eshetie Addo, Isaac Yeboah Adegboye, Oyelola A. Adekanmbi, Victor Adepoju, Abiola Victor Adnani, Qorinah Estiningtyas Sakilah Afolabi, Rotimi Felix Agarwal, Gina Aghdam, Zahra Babaei Agudelo-Botero, Marcela Arriagada, Constanza Elizabeth Aguilera Agyemang-Duah, Williams Ahinkorah, Bright Opoku Ahmad, Danish Ahmad, Rizwan Ahmad, Sajjad Ahmad, Aqeel Ahmadi, Ali Ahmadi, Keivan Ahmed, Ali Ahmed, Luai A. Ahmed, Syed Anees Ajami, Marjan Akinyemi, Rufus Olusola Al Hamad, Hanadi Al Hasan, Syed Mahfuz AL-Ahdal, Tareq Mohammed Ali Alalwan, Tariq A. Al-Aly, Ziyad AlBataineh, Mohammad T. Alcalde-Rabanal, Jacqueline Elizabeth Alemi, Sharifullah Ali, Hassam Alinia, Tahereh Aljunid, Syed Mohamed Almustanyir, Sami Al-Raddadi, Rajaa M. Alvis-Guzman, Nelson Amare, Firehiwot Ameyaw, Edward Kwabena Amiri, Sohrab Amusa, Ganiyu Adeniyi Andrei, Catalina Liliana Anjana, Ranjit Mohan Ansar, Adnan Ansari, Golnoosh Ansari-Moghaddam, Alireza Anyasodor, Anayochukwu Edward Arabloo, Jalal Aravkin, Aleksandr Y. Areda, Demelash Arifin, Hidayat Arkew, Mesay Armocida, Benedetta Arnlov, Johan Artamonov, Anton A. Arulappan, Judie Aruleba, Raphael Taiwo Arumugam, Ashokan Aryan, Zahra Asemu, Mulu Tiruneh Asghari-Jafarabadi, Mohammad Askari, Elaheh Asmelash, Daniel Astell-Burt, Thomas Athar, Mohammad Athari, Seyyed Shamsadin Atout, Maha Moh'd Wahbi Avila-Burgos, Leticia Awaisu, Ahmed Azadnajafabad, Sina Darshan, B.B. Babamohamadi, Hassan Badar, Muhammad Badawi, Alaa Badiye, Ashish D. Baghcheghi, Nayereh Baghe Institute for Health Metrics and Evaluation School of Medicine General Medicine Service Department of Veterans Affairs Seattle WA United States Department of Health Metrics Sciences School of Medicine Faculty of Medicine France Department of Clinical Governance and Quality Improvement Aleta Wondo Hospital Aleta Wondo Ethiopia Department of Nursing Woldia University Woldia Ethiopia Department of Nursing Department of Orthopedic Surgery Orthopaedic Surgery Social Determinants of Health Research Center Non-communicable Diseases Research Center Epidemiology Department Evidence-Based Practice Center Community and Maternity Nursing Unit University of Duhok Duhok Iraq School of Planning Faculty of Environment Department of Public Health Sciences Penn State College of Medicine Pennsylvania State University Hershey PA United States Biocomplexity Institute Virginia Tech Blacksburg VA United States College of Medicine Department of Public Health Laboratory Technology Sciences Department Department of Family and Community Health University of Health and Allied Sciences Ho Ghana Research Center for Immunodeficiencies Department of Biosciences and Nutrition Karolinska University Hospital Huddinge Sweden Clinical Sciences Department Department of Surgery Department of Surgery Department of Obstetrics & Gynecology College of Graduate Health Sciences University of Tennessee Memphis TN United States Department of Obstetrics & Gynecology Department of Clinical and Psychosocial Epidemiology Department of Anesthesia and Critical Care Centre for Social Research in Health Quality and Systems Performance Unit Cancer Institute NSW Sydney NSW Australia Department of Public Health and Tropical Medicine HIV and Infectious Diseases Department Jhpiego Abuja Nigeria Adolescent Research and Care Department Adolescent Friendly Research Initiative and Care Ado Ekiti Nigeria Department of Epidemiology Department of Epidemiology and Medical Statistics Department of Family Medicine McMaster University

Background: Diabetes is one of the leading causes of death and disability worldwide, and affects people regardless of country, age group, or sex. Using the most recent evidentiary and analytical framework from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD), we produced location-specific, age-specific, and sex-specific estimates of diabetes prevalence and burden from 1990 to 2021, the proportion of type 1 and type 2 diabetes in 2021, the proportion of the type 2 diabetes burden attributable to selected risk factors, and projections of diabetes prevalence through 2050. Methods: Estimates of diabetes prevalence and burden were computed in 204 countries and territories, across 25 age groups, for males and females separately and combined;these estimates comprised lost years of healthy life, measured in disability-adjusted life-years (DALYs;defined as the sum of years of life lost [YLLs] and years lived with disability [YLDs]). We used the Cause of Death Ensemble model (CODEm) approach to estimate deaths due to diabetes, incorporating 25 666 location-years of data from vital registration and verbal autopsy reports in separate total (including both type 1 and type 2 diabetes) and type-specific models. Other forms of diabetes, including gestational and monogenic diabetes, were not explicitly modelled. Total and type 1 diabetes prevalence was estimated by use of a Bayesian meta-regression modelling tool, DisMod-MR 2.1, to analyse 1527 location-years of data from the scientific literature, survey microdata, and insurance claims;type 2 diabetes estimates were computed by subtracting type 1 diabetes from total estimates. Mortality and prevalence estimates, along with standard life expectancy and disability weights, were used to calculate YLLs, YLDs, and DALYs. When appropriate, we extrapolated estimates to a hypothetical population with a standardised age structure to allow comparison in populations with different age structures. We used the comparative r

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Global investments in pandemic preparedness and COVID-19: development assistance and domestic spending on health between 1990 and 2026

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The Lancet Global Health 2023年第3期11卷 e385-e413页

作者： Micah, Angela E. Bhangdia, Kayleigh Cogswell, Ian E. Lasher, Dylan Lidral-Porter, Brendan Maddison, Emilie R. Nguyen, Trang Nhu Ngoc Patel, Nishali Pedroza, Paola Solorio, Juan Stutzman, Hayley Tsakalos, Golsum Wang, Yifeng Warriner, Wesley Zhao, Yingxi Zlavog, Bianca S. Abbafati, Cristiana Abbas, Jaffar Abbasi-Kangevari, Mohsen Abbasi-Kangevari, Zeinab Abdelmasseh, Michael Abdulah, Deldar Morad Abedi, Aidin Abegaz, Kedir Hussein Abhilash, E.S. Aboagye, Richard Gyan Abolhassani, Hassan Abrigo, Michael R.M. Abubaker Ali, Hiwa Abu-Gharbieh, Eman Adem, Mohammed Hussien Afzal, Muhammad Sohail Ahmadi, Ali Ahmed, Haroon Ahmed Rashid, Tarik Aji, Budi Akbarialiabad, Hossein Akelew, Yibeltal Al Hamad, Hanadi Alam, Khurshid Alanezi, Fahad Mashhour Alanzi, Turki M. Al-Hanawi, Mohammed Khaled Alhassan, Robert Kaba Aljunid, Syed Mohamed Almustanyir, Sami Al-Raddadi, Rajaa M. Alvis-Guzman, Nelson Alvis-Zakzuk, Nelson J. Amare, Azmeraw T. Ameyaw, Edward Kwabena Amini-Rarani, Mostafa Amu, Hubert Ancuceanu, Robert Andrei, Tudorel Anwar, Sumadi Lukman Appiah, Francis Aqeel, Muhammad Arabloo, Jalal Arab-Zozani, Morteza Aravkin, Aleksandr Y. Aremu, Olatunde Aruleba, Raphael Taiwo Athari, Seyyed Shamsadin Avila-Burgos, Leticia Ayanore, Martin Amogre Azari, Samad Baig, Atif Amin Bantie, Abere Tilahun Barrow, Amadou Baskaran, Pritish Basu, Sanjay Batiha, Abdul-Monim Mohammad Baune, Bernhard T. Berezvai, Zombor Bhardwaj, Nikha Bhardwaj, Pankaj Bhaskar, Sonu Boachie, Micheal Kofi Bodolica, Virginia Botelho, João Silva Botelho Braithwaite, Dejana Breitborde, Nicholas J.K. Busse, Reinhard Cahuana-Hurtado, Lucero Catalá-López, Ferrán Chansa, Collins Charan, Jaykaran Chattu, Vijay Kumar Chen, Simiao Chukwu, Isaac Sunday Dadras, Omid Dandona, Lalit Dandona, Rakhi Dargahi, Abdollah Debela, Sisay Abebe Denova-Gutiérrez, Edgar Desye, Belay Dharmaratne, Samath Dhamminda Diao, Nancy Doan, Linh Phuong Dodangeh, Milad dos Santos, Wendel Mombaque Doshmangir, Leila Dube, John Eini, Ebrahim El Sayed Zaki, Maysaa El Tantawi, Maha Enyew, Daniel Berhanie Institute for Health Metrics and Evaluation University of Washington Seattle WA United States Department of Applied Mathematics University of Washington Seattle WA United States Department of Health Metrics Sciences School of Medicine University of Washington Seattle WA United States Nuffield Department of Medicine University of Oxford Oxford United Kingdom Department of Juridical and Economic Studies La Sapienza University Rome Italy Antai College of Economics Shanghai Jiao Tong University Shanghai China Non-communicable Diseases Research Center Tehran University of Medical Sciences Tehran Iran Research Center for Immunodeficiencies Tehran University of Medical Sciences Tehran Iran Multiple Sclerosis Research Center Tehran University of Medical Sciences Tehran Iran Children’s Medical Center Tehran University of Medical Sciences Tehran Iran Department of Epidemiology and Biostatistics Tehran University of Medical Sciences Tehran Iran Tehran Heart Center Tehran University of Medical Sciences Tehran Iran Faculty of Medicine Tehran University of Medical Sciences Tehran Iran National Institute for Health Research Tehran University of Medical Sciences Tehran Iran Department of Pharmacology Tehran University of Medical Sciences Tehran Iran Department of Cardiology Tehran University of Medical Sciences Tehran Iran Sina Trauma and Surgery Research Center Tehran University of Medical Sciences Tehran Iran Digestive Diseases Research Institute Tehran University of Medical Sciences Tehran Iran Department of Neurology Tehran University of Medical Sciences Tehran Iran Social Determinants of Health Research Center Shahid Beheshti University of Medical Sciences Tehran Iran Department of Epidemiology Shahid Beheshti University of Medical Sciences Tehran Iran Department of Health Economics and Statistics Shahid Beheshti University of Medical Sciences Tehran Iran Department of Neurosurgery Shahid Beheshti University of Medical Sciences Tehran Iran Ophthalmic R

Background: The COVID-19 pandemic highlighted gaps in health surveillance systems, disease prevention, and treatment globally. Among the many factors that might have led to these gaps is the issue of the financing of national health systems, especially in low-income and middle-income countries (LMICs), as well as a robust global system for pandemic preparedness. We aimed to provide a comparative assessment of global health spending at the onset of the pandemic;characterise the amount of development assistance for pandemic preparedness and response disbursed in the first 2 years of the COVID-19 pandemic;and examine expectations for future health spending and put into context the expected need for investment in pandemic preparedness. Methods: In this analysis of global health spending between 1990 and 2021, and prediction from 2021 to 2026, we estimated four sources of health spending: development assistance for health (DAH), government spending, out-of-pocket spending, and prepaid private spending across 204 countries and territories. We used the Organisation for Economic Co-operation and Development (OECD)'s Creditor Reporting system (CRS) and the WHO Global Health Expenditure Database (GHED) to estimate spending. We estimated development assistance for general health, COVID-19 response, and pandemic preparedness and response using a keyword search. Health spending estimates were combined with estimates of resources needed for pandemic prevention and preparedness to analyse future health spending patterns, relative to need. Findings: In 2019, at the onset of the COVID-19 pandemic, US$9·2 trillion (95% uncertainty interval [UI] 9·1–9·3) was spent on health worldwide. We found great disparities in the amount of resources devoted to health, with high-income countries spending $7·3 trillion (95% UI 7·2–7·4) in 2019;293·7 times the $24·8 billion (95% UI 24·3–25·3) spent by low-income countries in 2019. That same year, $43·1 billion in development assistance was provided

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ESICM LIVES 2016: part one Milan, Italy. 1-5 October 2016 Abstracts

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INTENSIVE CARE MEDICINE EXPERIMENTAL 2016年第SUPPL 1期4卷 1-1页

作者： [Anonymous] Academic Medical Center University of Amsterdam Amsterdam Netherlands UMCU Utrecht Netherlands Autonomous University of Barcelona Barcelona Spain Hospital São Francisco Xavier Lisbon Portugal CHU Henri Mondor Medical ICU Créteil France Université de Paris Est-Créteil Groupe de Recherche Clinique CARMAS Créteil France Hôpital Tenon APHP Medical and Surgical ICU Paris France Université Paris Diderot Sorbonne Paris Cité UMR 1153 Paris France Interdepartmental Division of Critical Care University of Toronto Toronto Canada University Health Network University of Toronto Critical Care Medicine Toronto Canada University of Milan - Bicocca Health Sciences School of Medicine and Surgery Monza Italy St Michael’s Hospital University of Toronto Anesthesia Toronto Canada CHU d’Angers Medical ICU Angers France Interdepartmental Division of Critical Care University of Toronto Saint Michael’s Hospital and Keenan Research Centre Toronto Canada University of Birmingham Institute for Inflammation and Ageing Birmingham UK University of Sheffield Mathematics and Statistics Help Centre Sheffield UK Heart of England NHS Foundation Trust Intensive Care Medicine Birmingham UK Department of Surgery University Hospitals Birmingham NHS Trust Birmingham UK University Hospitals Birmingham NHS Trust Anaesthesia and Critical Care Medicine Birmingham UK Queen’s University of Belfast Wellcome-Wolfson Institute for Experimental Medicine Belfast UK Royal Victoria Hospital Intensive Care Medicine Belfast UK University of Warwick Warwick Clinical Trials Unit Coventry UK University of Bari ‘Aldo Moro’ Bari Italy Hospital Israelita Albert Einstein São Paulo Brazil Mayo Clinic Jacksonville USA Mahidol University Faculty of Tropical Medicine Bangkok Thailand University Medical Center Utrecht Intensive Care Utrecht Netherlands University Medical Center Utrecht Julius Center for Health Sciences and Primary Care Utrecht Netherlands Academic Medical Center University of Amste

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Genome-wide association study of lung adenocarcinoma in East Asia and comparison with a European population

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Nature communications 2023年第1期14卷 3043页

作者： Jianxin Shi Kouya Shiraishi Jiyeon Choi Keitaro Matsuo Tzu-Yu Chen Juncheng Dai Rayjean J Hung Kexin Chen Xiao-Ou Shu Young Tae Kim Maria Teresa Landi Dongxin Lin Wei Zheng Zhihua Yin Baosen Zhou Bao Song Jiucun Wang Wei Jie Seow Lei Song I-Shou Chang Wei Hu Li-Hsin Chien Qiuyin Cai Yun-Chul Hong Hee Nam Kim Yi-Long Wu Maria Pik Wong Brian Douglas Richardson Karen M Funderburk Shilan Li Tongwu Zhang Charles Breeze Zhaoming Wang Batel Blechter Bryan A Bassig Jin Hee Kim Demetrius Albanes Jason Y Y Wong Min-Ho Shin Lap Ping Chung Yang Yang She-Juan An Hong Zheng Yasushi Yatabe Xu-Chao Zhang Young-Chul Kim Neil E Caporaso Jiang Chang James Chung Man Ho Michiaki Kubo Yataro Daigo Minsun Song Yukihide Momozawa Yoichiro Kamatani Masashi Kobayashi Kenichi Okubo Takayuki Honda Dean H Hosgood Hideo Kunitoh Harsh Patel Shun-Ichi Watanabe Yohei Miyagi Haruhiko Nakayama Shingo Matsumoto Hidehito Horinouchi Masahiro Tsuboi Ryuji Hamamoto Koichi Goto Yuichiro Ohe Atsushi Takahashi Akiteru Goto Yoshihiro Minamiya Megumi Hara Yuichiro Nishida Kenji Takeuchi Kenji Wakai Koichi Matsuda Yoshinori Murakami Kimihiro Shimizu Hiroyuki Suzuki Motonobu Saito Yoichi Ohtaki Kazumi Tanaka Tangchun Wu Fusheng Wei Hongji Dai Mitchell J Machiela Jian Su Yeul Hong Kim In-Jae Oh Victor Ho Fun Lee Gee-Chen Chang Ying-Huang Tsai Kuan-Yu Chen Ming-Shyan Huang Wu-Chou Su Yuh-Min Chen Adeline Seow Jae Yong Park Sun-Seog Kweon Kun-Chieh Chen Yu-Tang Gao Biyun Qian Chen Wu Daru Lu Jianjun Liu Ann G Schwartz Richard Houlston Margaret R Spitz Ivan P Gorlov Xifeng Wu Ping Yang Stephen Lam Adonina Tardon Chu Chen Stig E Bojesen Mattias Johansson Angela Risch Heike Bickeböller Bu-Tian Ji H-Erich Wichmann David C Christiani Gadi Rennert Susanne Arnold Paul Brennan James McKay John K Field Sanjay S Shete Loic Le Marchand Geoffrey Liu Angeline Andrew Lambertus A Kiemeney Shan Zienolddiny-Narui Kjell Grankvist Mikael Johansson Angela Cox Fiona Taylor Jian-Min Yuan Philip Lazarus Matthew B Schabath Melinda C Aldrich Hyo-Sung Jeon Shih Sheng Jiang Jae Sook Sung C Division of Cancer Epidemiology and Genetics National Cancer Institute Rockville MD USA. jianxin.shi@nih.gov. Division of Genome Biology National Cancer Research Institute Tokyo Japan. Division of Cancer Epidemiology and Genetics National Cancer Institute Rockville MD USA. Division of Cancer Epidemiology and Prevention Aichi Cancer Center Research Institute Nagoya Japan. Institute of Population Health Sciences National Health Research Institutes Zhunan Taiwan. Department of Epidemiology School of Public Health Nanjing Medical University Nanjing China. Jiangsu Key Lab of Cancer Biomarkers Prevention and Treatment Collaborative Innovation Center for Cancer Medicine Nanjing Medical University Nanjing China. Prosserman Centre for Population Health Research Lunenfeld-Tanenbaum Research Institute Sinai Health Toronto ON Canada. Department of Epidemiology and Biostatistics National Clinical Research Center for Cancer Key Laboratory of Molecular Cancer Epidemiology of Tianjin Tianjin Medical University Cancer Institute and Hospital Tianjin Medical University Tianjin China. Division of Epidemiology Department of Medicine Vanderbilt University Medical Center and Vanderbilt-Ingram Cancer Center Nashville TN USA. Cancer Research Institute Seoul National University College of Medicine Seoul Republic of Korea. Department of Etiology & Carcinogenesis and State Key Laboratory of Molecular Oncology Cancer Institute and Hospital Chinese Academy of Medical Sciences and Peking Union Medical College Beijing China. Department of Epidemiology School of Public Health China Medical University Shenyang China. Department of Clinical Epidemiology and Center of Evidence Based Medicine The First Hospital of China Medical University Shenyang China. Department of Oncology Shandong Cancer Hospital and Institute Shandong Academy of Medical Sciences Jinan China. Ministry of Education Key Laboratory of Contemporary Anthropology School of Life Sciences Fudan University Shanghai China. S

Lung adenocarcinoma is the most common type of lung cancer. Known risk variants explain only a small fraction of lung adenocarcinoma heritability. Here, we conducted a two-stage genome-wide association study of lung adenocarcinoma of East Asian ancestry (21,658 cases and 150,676 controls; 54.5% never-smokers) and identified 12 novel susceptibility variants, bringing the total number to 28 at 25 independent loci. Transcriptome-wide association analyses together with colocalization studies using a Taiwanese lung expression quantitative trait loci dataset (n = 115) identified novel candidate genes, including FADS1 at 11q12 and ELF5 at 11p13. In a multi-ancestry meta-analysis of East Asian and European studies, four loci were identified at 2p11, 4q32, 16q23, and 18q12. At the same time, most of our findings in East Asian populations showed no evidence of association in European populations. In our studies drawn from East Asian populations, a polygenic risk score based on the 25 loci had a stronger association in never-smokers vs. individuals with a history of smoking (P = 0.0058). These findings provide new insights into the etiology of lung adenocarcinoma in individuals from East Asian populations, which could be important in developing translational applications.

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