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
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].
