The white matter query language: a novel approach for describing human white matter anatomy

• Published in: Brain Structure and Function Vol. 221; no. 9; pp. 4705 - 4721
• Main Authors: Wassermann, Demian, Makris, Nikos, Rathi, Yogesh, Shenton, Martha, Kikinis, Ron, Kubicki, Marek, Westin, Carl-Fredrik
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.12.2016; Springer Nature B.V; Springer Verlag
• Subjects: Adult; Algorithms; Anatomy & physiology; Atlases as Topic; Biomedical and Life Sciences; Biomedicine; Brain; Brain - anatomy & histology; Brain - pathology; Cell Biology; Cognitive science; Computer Science; Databases, Factual; Diffusion Magnetic Resonance Imaging; Female; Human health and pathology; Humans; Image Processing, Computer-Assisted - methods; Information Storage and Retrieval - methods; Life Sciences; Male; Medical Imaging; Methods Paper; Natural Language Processing; Neural Pathways - anatomy & histology; Neurology; Neuroscience; Neurosciences; NMR; Nuclear magnetic resonance; Reproducibility of Results; Schizophrenia - pathology; Software; Tissues and Organs; User-Computer Interface; White Matter - anatomy & histology; White Matter - pathology; Diffusion MRI; White matter fascicles; Computational neuroanatomy; Automatic classification of white matter tracts; Tractography; diffusion MRI; white matter; tractography; neuroanatomy
• ISSN: 1863-2653; 1863-2661; 1863-2661; 0340-2061
• DOI: 10.1007/s00429-015-1179-4

We have developed a novel method to describe human white matter anatomy using an approach that is both intuitive and simple to use, and which automatically extracts white matter tracts from diffusion MRI volumes. Further, our method simplifies the quantification and statistical analysis of white matter tracts on large diffusion MRI databases. This work reflects the careful syntactical definition of major white matter fiber tracts in the human brain based on a neuroanatomist’s expert knowledge. The framework is based on a novel query language with a near-to-English textual syntax. This query language makes it possible to construct a dictionary of anatomical definitions that describe white matter tracts. The definitions include adjacent gray and white matter regions, and rules for spatial relations. This novel method makes it possible to automatically label white matter anatomy across subjects. After describing this method, we provide an example of its implementation where we encode anatomical knowledge in human white matter for ten association and 15 projection tracts per hemisphere, along with seven commissural tracts. Importantly, this novel method is comparable in accuracy to manual labeling. Finally, we present results applying this method to create a white matter atlas from 77 healthy subjects, and we use this atlas in a small proof-of-concept study to detect changes in association tracts that characterize schizophrenia.