Highlights The Brain/MINDS beyond project plans to collect multi-site/scanner brain MRI data. Prospective harmonization of MRI was achieved by standardizing scanning protocols. The preliminary data showed moderate reliability of brain connectome data. Completing traveling subject plan will allow robust statistical harmonization. Scanning protocols are publicly available and data will also be shared by 2024.
Magnetic field inhomogeneities cause geometric distortions of echo planar images used for functional magnetic resonance imaging (fMRI). To reduce this problem, distortion correction (DC) with field map is widely used for both task and resting-state fMRI (rs-fMRI). Although DC with field map has been reported to improve the quality of task fMRI, little is known about its effects on rs-fMRI. Here, we tested the influence of field-map DC on rs-fMRI results using two rs-fMRI datasets derived from 40 healthy subjects: one with DC (DC+) and the other without correction (DC−). Independent component analysis followed by the dual regression approach was used for evaluation of resting-state functional connectivity networks (RSN). We also obtained the ratio of low-frequency to high-frequency signal power (0.01–0.1 Hz and above 0.1 Hz, respectively; LFHF ratio) to assess the quality of rs-fMRI signals. For comparison of RSN between DC+ and DC− datasets, the default mode network showed more robust functional connectivity in the DC+ dataset than the DC− dataset. Basal ganglia RSN showed some decreases in functional connectivity primarily in white matter, indicating imperfect registration/normalization without DC. Supplementary seed-based and simulation analyses supported the utility of DC. Furthermore, we found a higher LFHF ratio after field map correction in the anterior cingulate cortex, posterior cingulate cortex, ventral striatum, and cerebellum. In conclusion, field map DC improved detection of functional connectivity derived from low-frequency rs-fMRI signals. We encourage researchers to include a DC step in the preprocessing pipeline of rs-fMRI analysis.
[Purpose] Multidisciplinary treatments are recommended for treatment of chronic low back pain. The aim of this study was to show the associations among multidisciplinary treatment outcomes, pretreatment psychological factors, self-reported pain levels, and history of pain in chronic low back pain patients. [Subjects and Methods] A total of 221 chronic low back pain patients were chosen for the study. The pretreatment scores for the 10-cm Visual Analogue Scale, Hospital Anxiety and Depression Scale, Pain Catastrophizing Scale, Short-Form McGill Pain Questionnaire, Pain Disability Assessment Scale, pain drawings, and history of pain were collected. The patients were divided into two treatment outcome groups a year later: a good outcome group and a poor outcome group. [Results] One-hundred eighteen patients were allocated to the good outcome group. The scores for the Visual Analogue Scale, Pain Disability Assessment Scale, and affective subscale of the Short-Form McGill Pain Questionnaire and number of nonorganic pain drawings in the good outcome group were significantly lower than those in the poor outcome group. Duration of pain in the good outcome group was significantly shorter than in the poor outcome group. [Conclusion] These findings help better predict the efficacy of multidisciplinary treatments in chronic low back pain patients.
63Psychiatric and neurological disorders are afflictions of the brain that can affect individuals 64 throughout their lifespan. Many brain magnetic resonance imaging (MRI) studies have been 65 conducted; however, imaging-based diagnostic and therapeutic biomarkers are not yet well 66 established. The Brain/MINDS Beyond human brain MRI project (FY2018 ~ FY2023) is a 67 multi-site harmonization study aiming to establish clinically-relevant imaging biomarkers using 68 multiple high-performance scanners, standardized multi-modal imaging, and a study design that 69 includes traveling subjects. This project began with 13 clinical research sites that collect MRI 70 data on psychiatric and neurological disorders across the lifespan and three research sites that 71 design and develop measurement procedures, neuroimaging protocols, data storage and sharing, 72 and analysis tools. Brain images obtained with the Harmonization protocol (HARP) are 73 preprocessed and analyzed using approaches developed by the Human Connectome Project, 74 generating preliminary cortical structure, function, and connectivity measures that are 75 comparable across scanners. The use of 'travelling subjects', in which study participants travel to 76 multiple sites to undergo scanning with standardized neuroimaging techniques, enable us to 77 minimize the measurement bias between scanners and protocols and to increase the sensitivity 78 and specificity of case-control studies. All the imaging and demographic and clinical data are 79shared between the participating sites and will be made publicly available in 2024. To the best of 80 our knowledge, this is the first multi-site human brain MRI project to explore multiple 81 psychiatric and neurological disorders across the lifespan. The Brain/MINDS Beyond human 82 brain MRI project will help to identify the common and disease-specific pathophysiology 83 features of brain diseases and develop imaging biomarkers for clinical practice. 84 4 Keywords 85 Multi-site Study; HCP-style Brain Imaging; Psychiatric Disorders; Neurological Disorders; 86 Harmonization Protocol; Traveling Subjects 87 5 Text 88 Abbreviations 89 DALYs, disability-adjusted life years 90 MRI, magnetic resonance imaging 91 HCP, Human Connectome Project 92 ABCD, Adolescent Brain Cognitive Development 93 BPD, bipolar disorder 94 MDD, major depressive disorder 95 DecNef, Decoded Neurofeedback 96 ASD, autism spectrum disorder 97 ADNI, Alzheimer's Disease Neuroimaging Initiative 98 AD, Alzheimer's disease 99 MCI, mild cognitive impairment 100 PPMI, Parkinson's Progression Markers Initiative 101 PD, Parkinson's disease 102 T1w, T1-weighted 103 T2w, T2-weighted 104 rsfMRI, resting state functional MRI
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