Abstract #0566

Automated cervical spinal cord atrophy detection from conventional 3D T1w brain MRI

Jonathan A. Disselhorst^1,2,3, Michaela Andělová⁴, Veronica Ravano^1,2,3, Gian Franco Piredda^1,5,6, Tobias Kober^1,2,3, Manuela Vaněčková⁷, and Bénédicte Maréchal^1,2,3

¹Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland, ²Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland, ³LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland, ⁴Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital, Prague, Czech Republic, ⁵Human Neuroscience Platform, Fondation Campus Biotech Geneva, Geneva, Switzerland, ⁶CIBM-AIT, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland, ⁷Department of Radiology, First Faculty of Medicine, Charles University and General University Hospital, Prague, Czech Republic

Synopsis

Keywords: Spinal Cord, Segmentation, atrophyDetecting atrophy in the spinal cord (SC) is highly relevant in multiple sclerosis (MS) and other neuroinflammatory and neurodegenerative diseases. The most used method is measuring mean upper cervical cord area (MUCCA) from SC images. MRI of SC is time consuming and not always available. We recently developed a method to measure MUCCA directly from conventional T1w brain images. This work compares MUCCA estimates derived from MPRAGE and MP2RAGE sequences, determine reference ranges from 98 healthy subjects and show their value to detect atrophy in patients with progressive MS and neuromyelitis optica. We observe very high agreement between methods.

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