Dataset Information

Validation of brain-derived signals in near-infrared spectroscopy through multivoxel analysis of concurrent functional magnetic resonance imaging.

ABSTRACT: Near-infrared spectroscopy (NIRS) is a convenient and safe brain-mapping tool. However, its inevitable confounding with hemodynamic responses outside the brain, especially in the frontotemporal head, has questioned its validity. Some researchers attempted to validate NIRS signals through concurrent measurements with functional magnetic resonance imaging (fMRI), but, counterintuitively, NIRS signals rarely correlate with local fMRI signals in NIRS channels, although both mapping techniques should measure the same hemoglobin concentration. Here, we tested a novel hypothesis that different voxels within the scalp and the brain tissues might have substantially different hemoglobin absorption rates of near-infrared light, which might differentially contribute to NIRS signals across channels. Therefore, we newly applied a multivariate approach, a partial least squares regression, to explain NIRS signals with multivoxel information from fMRI within the brain and soft tissues in the head. We concurrently obtained fMRI and NIRS signals in 9 healthy human subjects engaging in an n-back task. The multivariate fMRI model was quite successfully able to predict the NIRS signals by cross-validation (interclass correlation coefficient = ∼0.85). This result confirmed that fMRI and NIRS surely measure the same hemoglobin concentration. Additional application of Monte-Carlo permutation tests confirmed that the model surely reflects temporal and spatial hemodynamic information, not random noise. After this thorough validation, we calculated the ratios of the contributions of the brain and soft-tissue hemodynamics to the NIRS signals, and found that the contribution ratios were quite different across different NIRS channels in reality, presumably because of the structural complexity of the frontotemporal regions. Hum Brain Mapp 38:5274-5291, 2017. © 2017 Wiley Periodicals, Inc.

SUBMITTER: Moriguchi Y

PROVIDER: S-EPMC6866983 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Medulloblastoma (MB) is the most common malignant brain tumor occurring in childhood and rarely found in adult. Based on transcriptome profile MB are currently classified into four major molecular groups reflecting a considerable biological heterogeneity: WNT-activated, SHH-activated, group 3 and group 4. Recently, DNA methylation profiling allowed the identification of additional subgroups within the four major molecular groups associated with different clinic-pathological and molecular features. Isocitrate Dehydrogenase-1 (IDH1) mutations have been described in several tumours, including gliomas, while in MB are exceptionally reported and not routinely investigated. By mean of magnetic resonance spectroscopy (MRS) we unequivocally assessed the presence the oncometabolite D-2-Hydroxyglutarate (2HG), a marker of IDH1 and IDH2 mutation, in a case of adult MB. Immunophenotypical work-up and methylation profiling assigned the diagnosis of MB, subclass SHH-A, and molecular testing revealed the presence of the non-canonical somatic IDH1(p.R132C) mutation and an additional GNAS mutation, also exceptionally described in MB. To our knowledge this is the first reported case of MB harboring both mutations together. Of note, tumour exhibited a heterogeneous phenotype with a tumour component displaying glial differentiation, with robust GFAP expression, and a component with conventional MB features and selective presence of GNAS mutation, suggesting coexistence of two different major tumour clones. These findings draw attention to the need of a deeper genetic characterization of MB in order to get insights into their biology and improve stratification and clinical management of the patients. Moreover, reported data underling the importance of performing MRS for the identification of IDH mutations in non-glial tumours. The use of throughput molecular profiling analysis and advanced medical imaging technology will certainly increase the frequency with which rare tumour entities will be identified. Whether they have any particular therapeutic implications or prognostic relevance requires further investigations.

Dataset Information

Validation of brain-derived signals in near-infrared spectroscopy through multivoxel analysis of concurrent functional magnetic resonance imaging.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets