ADC, D, f dataset calculated through the simplified IVIM model, with MGMT promoter methylation, age, and ECOG, in 38 patients with wildtype IDH glioblastoma

Pejman Jabehdar Maralani; Sten Myrehaug; Hatef Mehrabian; Aimee KM Chan; Max Wintermark; Chris Heyn; John Conklin; Benjamin M. Ellingson; Saba Rahimi; Angus Z Lau; Chia-Lin Tseng; Hany Soliman; Jay Detsky; Shadi Daghighi; Julia Keith; David G. Munoz; Sunit Das; Eshetu G. Atenafu; Nir Lipsman; James Perry; Greg Stanisz; Arjun Sahgal

Data in Brief (Apr 2021)

ADC, D, f dataset calculated through the simplified IVIM model, with MGMT promoter methylation, age, and ECOG, in 38 patients with wildtype IDH glioblastoma

Pejman Jabehdar Maralani,
Sten Myrehaug,
Hatef Mehrabian,
Aimee KM Chan,
Max Wintermark,
Chris Heyn,
John Conklin,
Benjamin M. Ellingson,
Saba Rahimi,
Angus Z Lau,
Chia-Lin Tseng,
Hany Soliman,
Jay Detsky,
Shadi Daghighi,
Julia Keith,
David G. Munoz,
Sunit Das,
Eshetu G. Atenafu,
Nir Lipsman,
James Perry,
Greg Stanisz,
Arjun Sahgal

Affiliations

Pejman Jabehdar Maralani: Department of Medical Imaging, Sunnybrook Health Sciences Center, University of Toronto, Toronto, ON, Canada; Corresponding author.
Sten Myrehaug: Department of Radiation Oncology, Sunnybrook Health Sciences Center, University of Toronto, Toronto, ON, Canada
Hatef Mehrabian: Department of Radiation Oncology, Sunnybrook Health Sciences Center, University of Toronto, Toronto, ON, Canada
Aimee KM Chan: Department of Medical Imaging, Sunnybrook Health Sciences Center, University of Toronto, Toronto, ON, Canada
Max Wintermark: Department of Radiology, Stanford University, Stanford, CA, United States
Chris Heyn: Department of Medical Imaging, Sunnybrook Health Sciences Center, University of Toronto, Toronto, ON, Canada
John Conklin: Department of Radiology, Massachusetts General Hospital, Boston, MA, United States
Benjamin M. Ellingson: Department of Radiological Sciences and Psychiatry, University of California Los Angeles, Los Angeles, CA, United States
Saba Rahimi: Department of Biomedical Engineering, University of Toronto, Toronto, ON, Canada
Angus Z Lau: Department of Medical Biophysics, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
Chia-Lin Tseng: Department of Radiation Oncology, Sunnybrook Health Sciences Center, University of Toronto, Toronto, ON, Canada
Hany Soliman: Department of Radiation Oncology, Sunnybrook Health Sciences Center, University of Toronto, Toronto, ON, Canada
Jay Detsky: Department of Radiation Oncology, Sunnybrook Health Sciences Center, University of Toronto, Toronto, ON, Canada
Shadi Daghighi: Department of Medical Imaging, Sunnybrook Health Sciences Center, University of Toronto, Toronto, ON, Canada
Julia Keith: Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada
David G. Munoz: Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada
Sunit Das: Department of Surgery, Division of Neurosurgery, University of Toronto, Toronto, ON, Canada
Eshetu G. Atenafu: Department of Biostatistics, University Health Network, Toronto, ON, Canada
Nir Lipsman: Department of Surgery, Division of Neurosurgery, University of Toronto, Toronto, ON, Canada
James Perry: Department of Medicine, Division of Neurology, University of Toronto, Toronto, ON, Canada
Greg Stanisz: Department of Medical Biophysics, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
Arjun Sahgal: Department of Radiation Oncology, Sunnybrook Health Sciences Center, University of Toronto, Toronto, ON, Canada

Journal volume & issue: Vol. 35
p. 106950

Abstract

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Patients undergoing standard chemoradiation post-resection had MRIs at radiation planning and fractions 10 and 20 of chemoradiation. MRIs were 1.5T and 3D T2-FLAIR, pre- and post-contrast 3D T1-weighted (T1) and echo planar DWI with three b-values (0, 500, and 1000s/mm2) were acquired. T2-FLAIR was coregistered to T1C images. Non-overlapping T1 contrast-enhancing (T1C) and nonenhancing T2-FLAIR hyperintense regions were segmented, with necrotic/cystic regions, the surgical cavity, and large vessels excluded. The simplified IVIM model was used to calculate voxelwise diffusion coefficient (D) and perfusion fraction (f) maps; ADC was calculated using the natural logarithm of b = 1000 over b = 0 images. T1C and T2-FLAIR segmentations were brought into this space, and medians calculated. MGMT promoter methylation status (MGMTPMS), age at diagnosis, and Eastern Cooperative Oncology Group (ECOG) performance status were extracted from electronic medical records. The data were presented, analyzed, and described in the article, “Intravoxel incoherent motion (IVIM) modeling of diffusion MRI during chemoradiation predicts therapeutic response in IDH wildtype Glioblastoma”, published in Radiotherapy and Oncology [1].

Published in Data in Brief

ISSN: 2352-3409 (Online)
Publisher: Elsevier
Country of publisher: United States
LCC subjects: Medicine: Medicine (General): Computer applications to medicine. Medical informatics; Science: Science (General)
Website: http://www.journals.elsevier.com/data-in-brief/

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