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  • 1
    Online Resource
    Online Resource
    A Brain Morphometry Study with Across-Site Harmonization Using a ComBat-Generalized Additive Model in Children and Adolescents
    MDPI AG ; 2023
    In:  Diagnostics Vol. 13, No. 17 ( 2023-08-27), p. 2774-
    Details
    In: Diagnostics, MDPI AG, Vol. 13, No. 17 ( 2023-08-27), p. 2774-
    Abstract: Regional anatomical structures of the brain are intimately connected to functions corresponding to specific regions and the temporospatial pattern of genetic expression and their functions from the fetal period to old age. Therefore, quantitative brain morphometry has often been employed in neuroscience investigations, while controlling for the scanner effect of the scanner is a critical issue for ensuring accuracy in brain morphometric studies of rare orphan diseases due to the lack of normal reference values available for multicenter studies. This study aimed to provide across-site normal reference values of global and regional brain volumes for each sex and age group in children and adolescents. We collected magnetic resonance imaging (MRI) examinations of 846 neurotypical participants aged 6.0–17.9 years (339 male and 507 female participants) from 5 institutions comprising healthy volunteers or neurotypical patients without neurological disorders, neuropsychological disorders, or epilepsy. Regional-based analysis using the CIVET 2.1.0. pipeline provided regional brain volumes, and the measurements were across-site combined using ComBat-GAM harmonization. The normal reference values of global and regional brain volumes and lateral indices in our study could be helpful for evaluating the characteristics of the brain morphology of each individual in a clinical setting and investigating the brain morphology of ultra-rare diseases.
    Type of Medium: Online Resource
    ISSN: 2075-4418
    URL: Article
    DOI: 10.3390/diagnostics13172774
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2662336-5
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  • 2
    Online Resource
    Online Resource
    Harmonized Z-Scores Calculated from a Large-Scale Normal MRI Database to Evaluate Brain Atrophy in Neurodegenerative Disorders
    MDPI AG ; 2022
    In:  Journal of Personalized Medicine Vol. 12, No. 10 ( 2022-09-21), p. 1555-
    Details
    In: Journal of Personalized Medicine, MDPI AG, Vol. 12, No. 10 ( 2022-09-21), p. 1555-
    Abstract: Alzheimer’s disease (AD), the most common type of dementia in elderly individuals, slowly and progressively diminishes the cognitive function. Mild cognitive impairment (MCI) is also a significant risk factor for the onset of AD. Magnetic resonance imaging (MRI) is widely used for the detection and understanding of the natural progression of AD and other neurodegenerative disorders. For proper assessment of these diseases, a reliable database of images from cognitively healthy participants is important. However, differences in magnetic field strength or the sex and age of participants between a normal database and an evaluation data set can affect the accuracy of the detection and evaluation of neurodegenerative disorders. We developed a brain segmentation procedure, based on 30 Japanese brain atlases, and suggest a harmonized Z-score to correct the differences in field strength and sex and age from a large data set (1235 cognitively healthy participants), including 1.5 T and 3 T T1-weighted brain images. We evaluated our harmonized Z-score for AD discriminative power and classification accuracy between stable MCI and progressive MCI. Our procedure can perform brain segmentation in approximately 30 min. The harmonized Z-score of the hippocampus achieved high accuracy (AUC = 0.96) for AD detection and moderate accuracy (AUC = 0.70) to classify stable or progressive MCI. These results show that our method can detect AD with high accuracy and high generalization capability. Moreover, it may discriminate between stable and progressive MCI. Our study has some limitations: the age groups in the 1.5 T data set and 3 T data set are significantly different. In this study, we focused on AD, which is primarily a disease of elderly patients. For other diseases in different age groups, the harmonized Z-score needs to be recalculated using different data sets.
    Type of Medium: Online Resource
    ISSN: 2075-4426
    URL: Article
    DOI: 10.3390/jpm12101555
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2662248-8
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  • 3
    Online Resource
    Online Resource
    Age and Sex-Related Effects on Single-Subject Gray Matter Networks in Healthy Participants
    MDPI AG ; 2023
    In:  Journal of Personalized Medicine Vol. 13, No. 3 ( 2023-02-26), p. 419-
    Details
    In: Journal of Personalized Medicine, MDPI AG, Vol. 13, No. 3 ( 2023-02-26), p. 419-
    Abstract: Recent developments in image analysis have enabled an individual’s brain network to be evaluated and brain age to be predicted from gray matter images. Our study aimed to investigate the effects of age and sex on single-subject gray matter networks using a large sample of healthy participants. We recruited 812 healthy individuals (59.3 ± 14.0 years, 407 females, and 405 males) who underwent three-dimensional T1-weighted magnetic resonance imaging. Similarity-based gray matter networks were constructed, and the following network properties were calculated: normalized clustering, normalized path length, and small-world coefficients. The predicted brain age was computed using a support-vector regression model. We evaluated the network alterations related to age and sex. Additionally, we examined the correlations between the network properties and predicted brain age and compared them with the correlations between the network properties and chronological age. The brain network retained efficient small-world properties regardless of age; however, reduced small-world properties were observed with advancing age. Although women exhibited higher network properties than men and similar age-related network declines as men in the subjects aged 〈 70 years, faster age-related network declines were observed in women, leading to no differences in sex among the participants aged ≥ 70 years. Brain age correlated well with network properties compared to chronological age in participants aged ≥ 70 years. Although the brain network retained small-world properties, it moved towards randomized networks with aging. Faster age-related network disruptions in women were observed than in men among the elderly. Our findings provide new insights into network alterations underlying aging.
    Type of Medium: Online Resource
    ISSN: 2075-4426
    URL: Article
    DOI: 10.3390/jpm13030419
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2662248-8
    Location Call Number Limitation Availability
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