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Paper Details

Multicenter imaging outcomes study of The Cancer Genome Atlas glioblastoma patient cohort: imaging predictors of overall and progression-free survival.
Neuro Oncol
67
2015
Cancer Genome, GBM, glioblastoma, patient, patients, tumor
Author NameAffiliation
Adam E FlandersUniversity of Texas MD Anderson Cancer Center, University of Pittsburgh Medical Center, Thomas Jefferson University Hospital, Clinical Monitoring Research Program (CMRP), Frederick National Laboratory for Cancer Research, Inc., Stanford University, University of Texas Health Sciences Center, University of California San Diego, St Jude Children's Research Hospital, Tennessee (S.N.H.) Clinical Monitoring Research Program, Emory University School of Medicine, Baylor College of Medicine
Adam E FlandersUniversity of Texas MD Anderson Cancer Center, University of Pittsburgh Medical Center, Thomas Jefferson University Hospital, Clinical Monitoring Research Program (CMRP), Frederick National Laboratory for Cancer Research, Inc., Stanford University, University of Texas Health Sciences Center, University of California San Diego, St Jude Children's Research Hospital, Tennessee (S.N.H.) Clinical Monitoring Research Program, Emory University School of Medicine, Baylor College of Medicine
Max WintermarkUniversity of Texas MD Anderson Cancer Center, University of Pittsburgh Medical Center, Thomas Jefferson University Hospital, Clinical Monitoring Research Program (CMRP), Frederick National Laboratory for Cancer Research, Inc., Stanford University, University of Texas Health Sciences Center, University of California San Diego, St Jude Children's Research Hospital, Tennessee (S.N.H.) Clinical Monitoring Research Program, Emory University School of Medicine, Baylor College of Medicine
Daniel L RubinUniversity of Texas MD Anderson Cancer Center, University of Pittsburgh Medical Center, Thomas Jefferson University Hospital, Clinical Monitoring Research Program (CMRP), Frederick National Laboratory for Cancer Research, Inc., Stanford University, University of Texas Health Sciences Center, University of California San Diego, St Jude Children's Research Hospital, Tennessee (S.N.H.) Clinical Monitoring Research Program, Emory University School of Medicine, Baylor College of Medicine
Daniel L RubinUniversity of Texas MD Anderson Cancer Center, University of Pittsburgh Medical Center, Thomas Jefferson University Hospital, Clinical Monitoring Research Program (CMRP), Frederick National Laboratory for Cancer Research, Inc., Stanford University, University of Texas Health Sciences Center, University of California San Diego, St Jude Children's Research Hospital, Tennessee (S.N.H.) Clinical Monitoring Research Program, Emory University School of Medicine, Baylor College of Medicine
John FreymannUniversity of Texas MD Anderson Cancer Center, University of Pittsburgh Medical Center, Thomas Jefferson University Hospital, Clinical Monitoring Research Program (CMRP), Frederick National Laboratory for Cancer Research, Inc., Stanford University, University of Texas Health Sciences Center, University of California San Diego, St Jude Children's Research Hospital, Tennessee (S.N.H.) Clinical Monitoring Research Program, Emory University School of Medicine, Baylor College of Medicine
Rivka R ColenUniversity of Texas MD Anderson Cancer Center, University of Pittsburgh Medical Center, Thomas Jefferson University Hospital, Clinical Monitoring Research Program (CMRP), Frederick National Laboratory for Cancer Research, Inc., Stanford University, University of Texas Health Sciences Center, University of California San Diego, St Jude Children's Research Hospital, Tennessee (S.N.H.) Clinical Monitoring Research Program, Emory University School of Medicine, Baylor College of Medicine
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Datasets

Dataset
Description
Source Link
The Cancer Imaging ArchiveTCIA is a service which de-identifies and publishes medical image datasets to study cancer. The data are organized as ⿿Collections⿝, typically subjects related by a common disease (e.g. lung cancer), image modality (MRI, CT, etc) or research focus. DICOM is the primary file format used by TCIA for radiology image storage. Supporting data related to the images such as patient outcomes, treatment details, genomics, pathology, and image analyses are also provided when available.Link
The Cancer Imaging ArchiveTCIA is a service which de-identifies and publishes medical image datasets to study cancer. The data are organized as ⿿Collections⿝, typically subjects related by a common disease (e.g. lung cancer), image modality (MRI, CT, etc) or research focus. DICOM is the primary file format used by TCIA for radiology image storage. Supporting data related to the images such as patient outcomes, treatment details, genomics, pathology, and image analyses are also provided when available.Link
The Cancer Imaging ArchiveTCIA is a service which de-identifies and publishes medical image datasets to study cancer. The data are organized as ⿿Collections⿝, typically subjects related by a common disease (e.g. lung cancer), image modality (MRI, CT, etc) or research focus. DICOM is the primary file format used by TCIA for radiology image storage. Supporting data related to the images such as patient outcomes, treatment details, genomics, pathology, and image analyses are also provided when available.Link
The Cancer Imaging ArchiveTCIA is a service which de-identifies and publishes medical image datasets to study cancer. The data are organized as ⿿Collections⿝, typically subjects related by a common disease (e.g. lung cancer), image modality (MRI, CT, etc) or research focus. DICOM is the primary file format used by TCIA for radiology image storage. Supporting data related to the images such as patient outcomes, treatment details, genomics, pathology, and image analyses are also provided when available.Link
The Cancer Imaging ArchiveTCIA is a service which de-identifies and publishes medical image datasets to study cancer. The data are organized as ⿿Collections⿝, typically subjects related by a common disease (e.g. lung cancer), image modality (MRI, CT, etc) or research focus. DICOM is the primary file format used by TCIA for radiology image storage. Supporting data related to the images such as patient outcomes, treatment details, genomics, pathology, and image analyses are also provided when available.Link
The Cancer Imaging ArchiveTCIA is a service which de-identifies and publishes medical image datasets to study cancer. The data are organized as ⿿Collections⿝, typically subjects related by a common disease (e.g. lung cancer), image modality (MRI, CT, etc) or research focus. DICOM is the primary file format used by TCIA for radiology image storage. Supporting data related to the images such as patient outcomes, treatment details, genomics, pathology, and image analyses are also provided when available.Link
The Cancer Imaging ArchiveTCIA is a service which de-identifies and publishes medical image datasets to study cancer. The data are organized as ⿿Collections⿝, typically subjects related by a common disease (e.g. lung cancer), image modality (MRI, CT, etc) or research focus. DICOM is the primary file format used by TCIA for radiology image storage. Supporting data related to the images such as patient outcomes, treatment details, genomics, pathology, and image analyses are also provided when available.Link
The Cancer Imaging ArchiveTCIA is a service which de-identifies and publishes medical image datasets to study cancer. The data are organized as ⿿Collections⿝, typically subjects related by a common disease (e.g. lung cancer), image modality (MRI, CT, etc) or research focus. DICOM is the primary file format used by TCIA for radiology image storage. Supporting data related to the images such as patient outcomes, treatment details, genomics, pathology, and image analyses are also provided when available.Link
The Cancer Imaging ArchiveTCIA is a service which de-identifies and publishes medical image datasets to study cancer. The data are organized as ⿿Collections⿝, typically subjects related by a common disease (e.g. lung cancer), image modality (MRI, CT, etc) or research focus. DICOM is the primary file format used by TCIA for radiology image storage. Supporting data related to the images such as patient outcomes, treatment details, genomics, pathology, and image analyses are also provided when available.Link
The Cancer Imaging ArchiveTCIA is a service which de-identifies and publishes medical image datasets to study cancer. The data are organized as ⿿Collections⿝, typically subjects related by a common disease (e.g. lung cancer), image modality (MRI, CT, etc) or research focus. DICOM is the primary file format used by TCIA for radiology image storage. Supporting data related to the images such as patient outcomes, treatment details, genomics, pathology, and image analyses are also provided when available.Link
The Cancer Imaging ArchiveTCIA is a service which de-identifies and publishes medical image datasets to study cancer. The data are organized as ⿿Collections⿝, typically subjects related by a common disease (e.g. lung cancer), image modality (MRI, CT, etc) or research focus. DICOM is the primary file format used by TCIA for radiology image storage. Supporting data related to the images such as patient outcomes, treatment details, genomics, pathology, and image analyses are also provided when available.Link
The Cancer Imaging ArchiveTCIA is a service which de-identifies and publishes medical image datasets to study cancer. The data are organized as ⿿Collections⿝, typically subjects related by a common disease (e.g. lung cancer), image modality (MRI, CT, etc) or research focus. DICOM is the primary file format used by TCIA for radiology image storage. Supporting data related to the images such as patient outcomes, treatment details, genomics, pathology, and image analyses are also provided when available.Link
The Cancer Imaging ArchiveTCIA is a service which de-identifies and publishes medical image datasets to study cancer. The data are organized as ⿿Collections⿝, typically subjects related by a common disease (e.g. lung cancer), image modality (MRI, CT, etc) or research focus. DICOM is the primary file format used by TCIA for radiology image storage. Supporting data related to the images such as patient outcomes, treatment details, genomics, pathology, and image analyses are also provided when available.Link
The Cancer Imaging ArchiveTCIA is a service which de-identifies and publishes medical image datasets to study cancer. The data are organized as ⿿Collections⿝, typically subjects related by a common disease (e.g. lung cancer), image modality (MRI, CT, etc) or research focus. DICOM is the primary file format used by TCIA for radiology image storage. Supporting data related to the images such as patient outcomes, treatment details, genomics, pathology, and image analyses are also provided when available.Link
The Cancer Imaging ArchiveTCIA is a service which de-identifies and publishes medical image datasets to study cancer. The data are organized as ⿿Collections⿝, typically subjects related by a common disease (e.g. lung cancer), image modality (MRI, CT, etc) or research focus. DICOM is the primary file format used by TCIA for radiology image storage. Supporting data related to the images such as patient outcomes, treatment details, genomics, pathology, and image analyses are also provided when available.Link
Release 1.2