Creation of a novel trigeminal tractography atlas for automated trigeminal nerve identification
Fan Zhang,
Guoqiang Xie,
Laura Leung,
Michael A. Mooney,
Lorenz Epprecht,
Isaiah Norton,
Yogesh Rathi,
Ron Kikinis,
Ossama Al-Mefty,
Nikos Makris,
Alexandra J. Golby,
Lauren J. O’Donnell
Affiliations
Fan Zhang
Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, USA; Corresponding author.
Guoqiang Xie
Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, USA; Department of Neurosurgery, Nuclear Industry 215 Hospital of Shaanxi Province, Xianyang, China
Laura Leung
Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, USA; Department of Neurosurgery, Brigham and Women’s Hospital, Harvard Medical School, Boston, USA; Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong, China
Michael A. Mooney
Department of Neurosurgery, Brigham and Women’s Hospital, Harvard Medical School, Boston, USA
Lorenz Epprecht
Department of Otolaryngology, Head and Neck Surgery, University Hospital Zurich, Zurich, Switzerland
Isaiah Norton
Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, USA
Yogesh Rathi
Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, USA; Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, USA
Ron Kikinis
Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, USA
Ossama Al-Mefty
Department of Neurosurgery, Brigham and Women’s Hospital, Harvard Medical School, Boston, USA
Nikos Makris
Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, USA; Departments of Psychiatry, Neurology and Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, USA
Alexandra J. Golby
Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, USA; Department of Neurosurgery, Brigham and Women’s Hospital, Harvard Medical School, Boston, USA
Lauren J. O’Donnell
Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, USA
Diffusion MRI (dMRI) tractography has been successfully used to study the trigeminal nerves (TGNs) in many clinical and research applications. Currently, identification of the TGN in tractography data requires expert nerve selection using manually drawn regions of interest (ROIs), which is prone to inter-observer variability, time-consuming and carries high clinical and labor costs. To overcome these issues, we propose to create a novel anatomically curated TGN tractography atlas that enables automated identification of the TGN from dMRI tractography. In this paper, we first illustrate the creation of a trigeminal tractography atlas. Leveraging a well-established computational pipeline and expert neuroanatomical knowledge, we generate a data-driven TGN fiber clustering atlas using tractography data from 50 subjects from the Human Connectome Project. Then, we demonstrate the application of the proposed atlas for automated TGN identification in new subjects, without relying on expert ROI placement. Quantitative and visual experiments are performed with comparison to expert TGN identification using dMRI data from two different acquisition sites. We show highly comparable results between the automatically and manually identified TGNs in terms of spatial overlap and visualization, while our proposed method has several advantages. First, our method performs automated TGN identification, and thus it provides an efficient tool to reduce expert labor costs and inter-operator bias relative to expert manual selection. Second, our method is robust to potential imaging artifacts and/or noise that can prevent successful manual ROI placement for TGN selection and hence yields a higher successful TGN identification rate.
