Optimizing the accuracy of cortical volumetric analysis in traumatic brain injury
Bram R. Diamond,
Christine L. Mac Donald,
Aina Frau-Pascual,
Samuel B. Snider,
Bruce Fischl,
Kristen Dams-O'Connor,
Brian L. Edlow
Affiliations
Bram R. Diamond
Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA; Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA
Christine L. Mac Donald
Department of Neurological Surgery, University of Washington, Seattle, WA
Aina Frau-Pascual
Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA; Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA
Samuel B. Snider
Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA
Bruce Fischl
Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA; Harvard-MIT Health Sciences and Technology, Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA
Kristen Dams-O'Connor
Department of Rehabilitation and Human Performance, Icahn School of Medicine at Mount Sinai, New York, NY; Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY; Corresponding author: Kristen Dams-O'Connor.
Brian L. Edlow
Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA; Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA
ABSTRACT: Cortical volumetric analysis is widely used to study the anatomic basis of neurological deficits in patients with traumatic brain injury (TBI). However, patients with TBI-related lesions are often excluded from MRI analyses because cortical lesions may compromise the accuracy of reconstructed surfaces upon which volumetric measurements are based. We developed a FreeSurfer-based lesion correction method and tested its impact on cortical volume measures in 87 patients with chronic moderate-to-severe TBI. We reconstructed cortical surfaces from T1-weighted MRI scans, then manually labeled and removed vertices on the cortical surfaces where lesions caused inaccuracies. Next, we measured the surface area of lesion overlap with seven canonical brain networks and the percent volume of each network affected by lesions. • The lesion correction method revealed that cortical lesions in patients with TBI are preferentially located in the limbic and default mode networks (95.7% each), with the limbic network also having the largest average surface area (4.4+/−3.7%) and percent volume affected by lesions (12.7+/−9.7%). • The method has the potential to improve the accuracy of cortical volumetric measurements and permit inclusion of patients with lesioned brains in MRI analyses. • The method also provides new opportunities to elucidate network-based mechanisms of neurological deficits in patients with TBI.
