Global motion detection and censoring in high-density diffuse optical tomography.

Autor: Sherafati A; Department of Physics, Washington University in St. Louis, St. Louis, Missouri, USA., Snyder AZ; Department of Radiology, Washington University School of Medicine in St, St. Louis, Missouri, USA.; Department of Neurology, Washington University in St. Louis, St. Louis, Missouri, USA., Eggebrecht AT; Department of Radiology, Washington University School of Medicine in St, St. Louis, Missouri, USA.; Department of Biomedical Engineering, Washington University School in St. Louis, St. Louis, Missouri, USA.; Division of Biology and Biomedical Sciences, Washington University School of Medicine in St. Louis, St. Louis, Missouri, USA., Bergonzi KM; L3Harris, 400 Initiative Dr, Rochester, New York, 14624, USA., Burns-Yocum TM; Department of Psychological and Brain Sciences, Indiana University, Bloomington, Indiana, USA., Lugar HM; Department of Psychiatry, Washington University School of Medicine in St. Louis, St. Louis, Missouri, USA., Ferradal SL; Department Of Intelligent Systems Engineering, Indiana University, Bloomington, Indiana, USA., Robichaux-Viehoever A; Department of Neurology, Washington University in St. Louis, St. Louis, Missouri, USA., Smyser CD; Department of Radiology, Washington University School of Medicine in St, St. Louis, Missouri, USA.; Department of Neurology, Washington University in St. Louis, St. Louis, Missouri, USA.; Department of Pediatrics, Washington University in St. Louis, St. Louis, Missouri, USA., Palanca BJ; Department of Anesthesiology, Washington University School of Medicine in St. Louis, St. Louis, Missouri, USA., Hershey T; Department of Radiology, Washington University School of Medicine in St, St. Louis, Missouri, USA.; Department of Psychological and Brain Sciences, Indiana University, Bloomington, Indiana, USA., Culver JP; Department of Physics, Washington University in St. Louis, St. Louis, Missouri, USA.; Department of Radiology, Washington University School of Medicine in St, St. Louis, Missouri, USA.; Department of Biomedical Engineering, Washington University School in St. Louis, St. Louis, Missouri, USA.; Division of Biology and Biomedical Sciences, Washington University School of Medicine in St. Louis, St. Louis, Missouri, USA.
Jazyk: angličtina
Zdroj: Human brain mapping [Hum Brain Mapp] 2020 Oct 01; Vol. 41 (14), pp. 4093-4112. Date of Electronic Publication: 2020 Jul 10.
DOI: 10.1002/hbm.25111
Abstrakt: Motion-induced artifacts can significantly corrupt optical neuroimaging, as in most neuroimaging modalities. For high-density diffuse optical tomography (HD-DOT) with hundreds to thousands of source-detector pair measurements, motion detection methods are underdeveloped relative to both functional magnetic resonance imaging (fMRI) and standard functional near-infrared spectroscopy (fNIRS). This limitation restricts the application of HD-DOT in many challenging imaging situations and subject populations (e.g., bedside monitoring and children). Here, we evaluated a new motion detection method for multi-channel optical imaging systems that leverages spatial patterns across measurement channels. Specifically, we introduced a global variance of temporal derivatives (GVTD) metric as a motion detection index. We showed that GVTD strongly correlates with external measures of motion and has high sensitivity and specificity to instructed motion-with an area under the receiver operator characteristic curve of 0.88, calculated based on five different types of instructed motion. Additionally, we showed that applying GVTD-based motion censoring on both hearing words task and resting state HD-DOT data with natural head motion results in an improved spatial similarity to fMRI mapping. We then compared the GVTD similarity scores with several commonly used motion correction methods described in the fNIRS literature, including correlation-based signal improvement (CBSI), temporal derivative distribution repair (TDDR), wavelet filtering, and targeted principal component analysis (tPCA). We find that GVTD motion censoring on HD-DOT data outperforms other methods and results in spatial maps more similar to those of matched fMRI data.
(© 2020 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)
Databáze: MEDLINE
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