Literature DB >> 34185678

NCI Imaging Data Commons.

Andrey Fedorov1, William J R Longabaugh2, David Pot3, David A Clunie4, Steve Pieper5, Hugo J W L Aerts6,7,8, André Homeyer9, Rob Lewis10, Afshin Akbarzadeh11, Dennis Bontempi6, William Clifford2, Markus D Herrmann12, Henning Höfener9, Igor Octaviano10, Chad Osborne3, Suzanne Paquette2, James Petts13, Davide Punzo10, Madelyn Reyes3, Daniela P Schacherer9, Mi Tian2, George White2, Erik Ziegler10, Ilya Shmulevich2, Todd Pihl14, Ulrike Wagner14, Keyvan Farahani15, Ron Kikinis11.   

Abstract

The National Cancer Institute (NCI) Cancer Research Data Commons (CRDC) aims to establish a national cloud-based data science infrastructure. Imaging Data Commons (IDC) is a new component of CRDC supported by the Cancer Moonshot. The goal of IDC is to enable a broad spectrum of cancer researchers, with and without imaging expertise, to easily access and explore the value of deidentified imaging data and to support integrated analyses with nonimaging data. We achieve this goal by colocating versatile imaging collections with cloud-based computing resources and data exploration, visualization, and analysis tools. The IDC pilot was released in October 2020 and is being continuously populated with radiology and histopathology collections. IDC provides access to curated imaging collections, accompanied by documentation, a user forum, and a growing number of analysis use cases that aim to demonstrate the value of a data commons framework applied to cancer imaging research. SIGNIFICANCE: This study introduces NCI Imaging Data Commons, a new repository of the NCI Cancer Research Data Commons, which will support cancer imaging research on the cloud. ©2021 The Authors; Published by the American Association for Cancer Research.

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Year:  2021        PMID: 34185678      PMCID: PMC8373794          DOI: 10.1158/0008-5472.CAN-21-0950

Source DB:  PubMed          Journal:  Cancer Res        ISSN: 0008-5472            Impact factor:   12.701


  20 in total

Review 1.  Future cancer research priorities in the USA: a Lancet Oncology Commission.

Authors:  Elizabeth M Jaffee; Chi Van Dang; David B Agus; Brian M Alexander; Kenneth C Anderson; Alan Ashworth; Anna D Barker; Roshan Bastani; Sangeeta Bhatia; Jeffrey A Bluestone; Otis Brawley; Atul J Butte; Daniel G Coit; Nancy E Davidson; Mark Davis; Ronald A DePinho; Robert B Diasio; Giulio Draetta; A Lindsay Frazier; Andrew Futreal; Sam S Gambhir; Patricia A Ganz; Levi Garraway; Stanton Gerson; Sumit Gupta; James Heath; Ruth I Hoffman; Cliff Hudis; Chanita Hughes-Halbert; Ramy Ibrahim; Hossein Jadvar; Brian Kavanagh; Rick Kittles; Quynh-Thu Le; Scott M Lippman; David Mankoff; Elaine R Mardis; Deborah K Mayer; Kelly McMasters; Neal J Meropol; Beverly Mitchell; Peter Naredi; Dean Ornish; Timothy M Pawlik; Jeffrey Peppercorn; Martin G Pomper; Derek Raghavan; Christine Ritchie; Sally W Schwarz; Richard Sullivan; Richard Wahl; Jedd D Wolchok; Sandra L Wong; Alfred Yung
Journal:  Lancet Oncol       Date:  2017-10-31       Impact factor: 41.316

2.  A Case for Data Commons: Toward Data Science as a Service.

Authors:  Robert L Grossman; Allison Heath; Mark Murphy; Maria Patterson; Walt Wells
Journal:  Comput Sci Eng       Date:  2016-08-24       Impact factor: 2.080

3.  The Cancer Genomics Cloud: Collaborative, Reproducible, and Democratized-A New Paradigm in Large-Scale Computational Research.

Authors:  Jessica W Lau; Erik Lehnert; Anurag Sethi; Raunaq Malhotra; Gaurav Kaushik; Zeynep Onder; Nick Groves-Kirkby; Aleksandar Mihajlovic; Jack DiGiovanna; Mladen Srdic; Dragan Bajcic; Jelena Radenkovic; Vladimir Mladenovic; Damir Krstanovic; Vladan Arsenijevic; Djordje Klisic; Milan Mitrovic; Igor Bogicevic; Deniz Kural; Brandi Davis-Dusenbery
Journal:  Cancer Res       Date:  2017-11-01       Impact factor: 12.701

Review 4.  The NCI Genomic Data Commons as an engine for precision medicine.

Authors:  Mark A Jensen; Vincent Ferretti; Robert L Grossman; Louis M Staudt
Journal:  Blood       Date:  2017-06-09       Impact factor: 22.113

5.  BRIDG: a domain information model for translational and clinical protocol-driven research.

Authors:  Lauren B Becnel; Smita Hastak; Wendy Ver Hoef; Robert P Milius; MaryAnn Slack; Diane Wold; Michael L Glickman; Boris Brodsky; Charles Jaffe; Rebecca Kush; Edward Helton
Journal:  J Am Med Inform Assoc       Date:  2017-09-01       Impact factor: 4.497

6.  Open Health Imaging Foundation Viewer: An Extensible Open-Source Framework for Building Web-Based Imaging Applications to Support Cancer Research.

Authors:  Erik Ziegler; Trinity Urban; Danny Brown; James Petts; Steve D Pieper; Rob Lewis; Chris Hafey; Gordon J Harris
Journal:  JCO Clin Cancer Inform       Date:  2020-04

7.  Deep learning for lung cancer prognostication: A retrospective multi-cohort radiomics study.

Authors:  Ahmed Hosny; Chintan Parmar; Thibaud P Coroller; Patrick Grossmann; Roman Zeleznik; Avnish Kumar; Johan Bussink; Robert J Gillies; Raymond H Mak; Hugo J W L Aerts
Journal:  PLoS Med       Date:  2018-11-30       Impact factor: 11.069

Review 8.  The Human Tumor Atlas Network: Charting Tumor Transitions across Space and Time at Single-Cell Resolution.

Authors:  Orit Rozenblatt-Rosen; Aviv Regev; Philipp Oberdoerffer; Tal Nawy; Anna Hupalowska; Jennifer E Rood; Orr Ashenberg; Ethan Cerami; Robert J Coffey; Emek Demir; Li Ding; Edward D Esplin; James M Ford; Jeremy Goecks; Sharmistha Ghosh; Joe W Gray; Justin Guinney; Sean E Hanlon; Shannon K Hughes; E Shelley Hwang; Christine A Iacobuzio-Donahue; Judit Jané-Valbuena; Bruce E Johnson; Ken S Lau; Tracy Lively; Sarah A Mazzilli; Dana Pe'er; Sandro Santagata; Alex K Shalek; Denis Schapiro; Michael P Snyder; Peter K Sorger; Avrum E Spira; Sudhir Srivastava; Kai Tan; Robert B West; Elizabeth H Williams
Journal:  Cell       Date:  2020-04-16       Impact factor: 66.850

9.  The FAIR Guiding Principles for scientific data management and stewardship.

Authors:  Mark D Wilkinson; Michel Dumontier; I Jsbrand Jan Aalbersberg; Gabrielle Appleton; Myles Axton; Arie Baak; Niklas Blomberg; Jan-Willem Boiten; Luiz Bonino da Silva Santos; Philip E Bourne; Jildau Bouwman; Anthony J Brookes; Tim Clark; Mercè Crosas; Ingrid Dillo; Olivier Dumon; Scott Edmunds; Chris T Evelo; Richard Finkers; Alejandra Gonzalez-Beltran; Alasdair J G Gray; Paul Groth; Carole Goble; Jeffrey S Grethe; Jaap Heringa; Peter A C 't Hoen; Rob Hooft; Tobias Kuhn; Ruben Kok; Joost Kok; Scott J Lusher; Maryann E Martone; Albert Mons; Abel L Packer; Bengt Persson; Philippe Rocca-Serra; Marco Roos; Rene van Schaik; Susanna-Assunta Sansone; Erik Schultes; Thierry Sengstag; Ted Slater; George Strawn; Morris A Swertz; Mark Thompson; Johan van der Lei; Erik van Mulligen; Jan Velterop; Andra Waagmeester; Peter Wittenburg; Katherine Wolstencroft; Jun Zhao; Barend Mons
Journal:  Sci Data       Date:  2016-03-15       Impact factor: 6.444

10.  Quantitative Imaging Informatics for Cancer Research.

Authors:  Andrey Fedorov; Reinhard Beichel; Jayashree Kalpathy-Cramer; David Clunie; Michael Onken; Jörg Riesmeier; Christian Herz; Christian Bauer; Andrew Beers; Jean-Christophe Fillion-Robin; Andras Lasso; Csaba Pinter; Steve Pieper; Marco Nolden; Klaus Maier-Hein; Markus D Herrmann; Joel Saltz; Fred Prior; Fiona Fennessy; John Buatti; Ron Kikinis
Journal:  JCO Clin Cancer Inform       Date:  2020-05
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  3 in total

Review 1.  Artificial Intelligence for Radiation Oncology Applications Using Public Datasets.

Authors:  Kareem A Wahid; Enrico Glerean; Jaakko Sahlsten; Joel Jaskari; Kimmo Kaski; Mohamed A Naser; Renjie He; Abdallah S R Mohamed; Clifton D Fuller
Journal:  Semin Radiat Oncol       Date:  2022-10       Impact factor: 5.421

Review 2.  Big data in basic and translational cancer research.

Authors:  Peng Jiang; Sanju Sinha; Kenneth Aldape; Sridhar Hannenhalli; Cenk Sahinalp; Eytan Ruppin
Journal:  Nat Rev Cancer       Date:  2022-09-05       Impact factor: 69.800

3.  Cloud-enabled Biodepot workflow builder integrates image processing using Fiji with reproducible data analysis using Jupyter notebooks.

Authors:  Ling-Hong Hung; Evan Straw; Shishir Reddy; Robert Schmitz; Zachary Colburn; Ka Yee Yeung
Journal:  Sci Rep       Date:  2022-09-02       Impact factor: 4.996

  3 in total

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