AutoVOI: real‐time automatic prescription of volume‐of‐interest for single voxel spectroscopy

• Published in: Magnetic resonance in medicine Vol. 80; no. 5; pp. 1787 - 1798
• Main Authors: Park, Young Woo, Deelchand, Dinesh K., Joers, James M., Hanna, Brian, Berrington, Adam, Gillen, Joseph S., Kantarci, Kejal, Soher, Brian J., Barker, Peter B., Park, HyunWook, Öz, Gülin, Lenglet, Christophe
• Format: Journal Article
• Language: English
• Published: United States Wiley Subscription Services, Inc 01.11.2018
• Subjects: Automation; Brain; Brain stem; Cerebellum; Cerebrospinal fluid; Cerebrum; Computation; Consistency; Dependence; generalized dice coefficient; Hand tools; MRS; Pipelines; Placement; prescription; registration; Spectroscopy; Spectrum analysis; Substantia alba; Substantia grisea; generalized dice coefficient; registration; automation; prescription; MRS
• ISSN: 0740-3194; 1522-2594; 1522-2594
• DOI: 10.1002/mrm.27203

Purpose To develop a fast and automated volume‐of‐interest (VOI) prescription pipeline (AutoVOI) for single‐voxel MRS that removes the need for manual VOI placement, allows flexible VOI planning in any brain region, and enables high inter‐ and intra‐subject consistency of VOI prescription. Methods AutoVOI was designed to transfer pre‐defined VOIs from an atlas to the 3D anatomical data of the subject during the scan. The AutoVOI pipeline was optimized for consistency in VOI placement (precision), enhanced coverage of the targeted tissue (accuracy), and fast computation speed. The tool was evaluated against manual VOI placement using existing T1‐weighted data sets and corresponding VOI prescriptions. Finally, it was implemented on 2 scanner platforms to acquire MRS data from clinically relevant VOIs that span the cerebrum, cerebellum, and the brainstem. Results The AutoVOI pipeline includes skull stripping, non‐linear registration of the atlas to the subject's brain, and computation of the VOI coordinates and angulations using a minimum oriented bounding box algorithm. When compared against manual prescription, AutoVOI showed higher intra‐ and inter‐subject spatial consistency, as quantified by generalized Dice coefficients (GDC), lower intra‐ and inter‐subject variability in tissue composition (gray matter, white matter, and cerebrospinal fluid) and higher or equal accuracy, as quantified by GDC of prescribed VOI with targeted tissues. High quality spectra were obtained on Siemens and Philips 3T systems from 6 automatically prescribed VOIs by the tool. Conclusion Robust automatic VOI prescription is feasible and can help facilitate clinical adoption of MRS by avoiding operator dependence of manual selection.