BACKGROUND: Advanced imaging methods have the potential to serve as quantitative biomarkers in neuro-oncology research. However, a lack of standardization of image acquisition, processing, and analysis limits their application in clinical research. Standardization of these methods and an organized archival platform are required to better validate and apply these markers in research settings and, ultimately, in clinical practice. OBJECTIVE: The primary objective of the Comprehensive Neuro-oncology Data Repository (CONDR) is to develop a data set for assessing and validating advanced imaging methods in patients diagnosed with brain tumors. As a secondary objective, informatics resources will be developed to facilitate the integrated collection, processing, and analysis of imaging, tissue, and clinical data in multicenter clinical trials. Finally, CONDR data and informatics resources will be shared with the research community for further analysis. METHODS: CONDR will enroll 200 patients diagnosed with primary brain tumors. Clinical, imaging, and tissue-based data are obtained from patients serially, beginning with diagnosis and continuing over the course of their treatment. The CONDR imaging protocol includes structural and functional sequences, including diffusion- and perfusion-weighted imaging. All data are managed within an XNAT-based informatics platform. Imaging markers are assessed by correlating image and spatially aligned pathological markers and a variety of clinical markers. EXPECTED OUTCOMES: CONDR will generate data for developing and validating imaging markers of primary brain tumors, including multispectral and probabilistic maps. DISCUSSION: CONDR implements a novel, open-research model that will provide the research community with both open-access data and open-source informatics resources.
BACKGROUND: Advanced imaging methods have the potential to serve as quantitative biomarkers in neuro-oncology research. However, a lack of standardization of image acquisition, processing, and analysis limits their application in clinical research. Standardization of these methods and an organized archival platform are required to better validate and apply these markers in research settings and, ultimately, in clinical practice. OBJECTIVE: The primary objective of the Comprehensive Neuro-oncology Data Repository (CONDR) is to develop a data set for assessing and validating advanced imaging methods in patients diagnosed with brain tumors. As a secondary objective, informatics resources will be developed to facilitate the integrated collection, processing, and analysis of imaging, tissue, and clinical data in multicenter clinical trials. Finally, CONDR data and informatics resources will be shared with the research community for further analysis. METHODS: CONDR will enroll 200 patients diagnosed with primary brain tumors. Clinical, imaging, and tissue-based data are obtained from patients serially, beginning with diagnosis and continuing over the course of their treatment. The CONDR imaging protocol includes structural and functional sequences, including diffusion- and perfusion-weighted imaging. All data are managed within an XNAT-based informatics platform. Imaging markers are assessed by correlating image and spatially aligned pathological markers and a variety of clinical markers. EXPECTED OUTCOMES: CONDR will generate data for developing and validating imaging markers of primary brain tumors, including multispectral and probabilistic maps. DISCUSSION: CONDR implements a novel, open-research model that will provide the research community with both open-access data and open-source informatics resources.
Authors: Benjamin M Ellingson; Timothy F Cloughesy; Taryar Zaw; Albert Lai; Phioanh L Nghiemphu; Robert Harris; Shadi Lalezari; Naveed Wagle; Kourosh M Naeini; Jose Carrillo; Linda M Liau; Whitney B Pope Journal: Neuro Oncol Date: 2012-01-22 Impact factor: 12.300
Authors: A Vidiri; C M Carapella; A Pace; A Mirri; A Fabi; M Carosi; D Giannarelli; A Pompili; B Jandolo; E Occhipinti; S Di Giovanni; M Crecco Journal: J Exp Clin Cancer Res Date: 2006-06
Authors: K K Kwong; D A Chesler; R M Weisskoff; K M Donahue; T L Davis; L Ostergaard; T A Campbell; B R Rosen Journal: Magn Reson Med Date: 1995-12 Impact factor: 4.668
Authors: Mikhail Milchenko; Abraham Z Snyder; Pamela LaMontagne; Joshua S Shimony; Tammie L Benzinger; Sarah Jost Fouke; Daniel S Marcus Journal: Neuroinformatics Date: 2016-07
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Authors: Andrei G Vlassenko; Jonathan McConathy; Lars E Couture; Yi Su; Parinaz Massoumzadeh; Hayden S Leeds; Michael R Chicoine; David D Tran; Jiayi Huang; Sonika Dahiya; Daniel S Marcus; Sarah Jost Fouke; Keith M Rich; Marcus E Raichle; Tammie L S Benzinger Journal: Dis Markers Date: 2015-09-03 Impact factor: 3.434
Authors: Qing Wang; Gloria J Guzmán Pérez-Carrillo; Maria Rosana Ponisio; Pamela LaMontagne; Sonika Dahiya; Daniel S Marcus; Mikhail Milchenko; Joshua Shimony; Jingxia Liu; Gengsheng Chen; Amber Salter; Parinaz Massoumzadeh; Michelle M Miller-Thomas; Keith M Rich; Jonathan McConathy; Tammie L S Benzinger; Yong Wang Journal: PLoS One Date: 2019-11-14 Impact factor: 3.240