Anton Orlichenko, Kuan-Jui Su, Hui Shen, Hong-Wen Deng, Yu-Ping Wang
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We also compare the ability of Power264 and UKB-provided, independent component analysis (ICA)-based FC to determine which of a longitudinal scan pair is older. Finally, we investigate cross-sectional FC changes as well as differences due to differing scanner tasks in the UKB, Philadelphia Neurodevelopmental Cohort, and Alzheimer's Disease Neuroimaging Initiative datasets.</p><p><strong>Results: </strong>We find a 6.8% average increase in somatomotor network (SMT)-visual network (VIS) connectivity from younger to older scans (corrected <math><mrow><mi>p</mi><mo><</mo><msup><mn>10</mn><mrow><mo>-</mo><mn>15</mn></mrow></msup></mrow></math>) that occurs in male, female, older subject (<math><mrow><mo>></mo><mn>65</mn></mrow></math> years old), and younger subject (<math><mrow><mo><</mo><mn>55</mn></mrow></math> years old) groups. Among all internetwork connections, the average SMT-VIS connectivity is the best predictor of relative scan age. Using the full FC and a training set of 2000 subjects, one is able to predict which scan is older 82.5% of the time using either the full Power264 FC or the UKB-provided ICA-based FC.</p><p><strong>Conclusions: </strong>We conclude that SMT-VIS connectivity increases with age in the UKB longitudinal cohort and that resting state FC increases with age in the UKB cross-sectional cohort.</p>","PeriodicalId":47707,"journal":{"name":"Journal of Medical Imaging","volume":null,"pages":null},"PeriodicalIF":1.9000,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11009525/pdf/","citationCount":"0","resultStr":"{\"title\":\"Somatomotor-visual resting state functional connectivity increases after 2 years in the UK Biobank longitudinal cohort.\",\"authors\":\"Anton Orlichenko, Kuan-Jui Su, Hui Shen, Hong-Wen Deng, Yu-Ping Wang\",\"doi\":\"10.1117/1.JMI.11.2.024010\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Purpose: </strong>Functional magnetic resonance imaging (fMRI) and functional connectivity (FC) have been used to follow aging in both children and older adults. Robust changes have been observed in children, in which high connectivity among all brain regions changes to a more modular structure with maturation. We examine FC changes in older adults after 2 years of aging in the UK Biobank (UKB) longitudinal cohort.</p><p><strong>Approach: </strong>We process fMRI connectivity data using the Power264 atlas and then test whether the average internetwork FC changes in the 2722-subject longitudinal cohort are statistically significant using a Bonferroni-corrected <math><mrow><mi>t</mi></mrow></math>-test. We also compare the ability of Power264 and UKB-provided, independent component analysis (ICA)-based FC to determine which of a longitudinal scan pair is older. 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引用次数: 0
摘要
研究目的功能磁共振成像(fMRI)和功能连接(FC)已被用于跟踪儿童和老年人的衰老情况。在儿童中已观察到稳健的变化,其中所有脑区之间的高连通性随着成熟而转变为更模块化的结构。我们研究了英国生物库(UKB)纵向队列中老年人衰老 2 年后的 FC 变化:我们使用 Power264 图集处理 fMRI 连接数据,然后使用 Bonferroni 校正 t 检验 2722 个受试者纵向队列中的平均网络 FC 变化是否具有统计学意义。我们还比较了 Power264 和 UKB 提供的基于独立成分分析 (ICA) 的 FC 判断纵向扫描对中哪个年龄更大的能力。最后,我们研究了横断面FC变化以及UKB、费城神经发育队列和阿尔茨海默病神经影像倡议数据集中不同扫描任务导致的差异:我们发现,从年轻扫描到年长扫描(校正 p10-15),躯体运动网络(SMT)-视觉网络(VIS)连通性平均增加了 6.8%,分别出现在男性、女性、年长受试者(大于 65 岁)和年轻受试者(55 岁)组中。在所有网络连接中,平均 SMT-VIS 连接是预测相对扫描年龄的最佳指标。使用完整的 FC 和 2000 个受试者的训练集,无论是使用完整的 Power264 FC 还是 UKB 提供的基于 ICA 的 FC,都能在 82.5% 的情况下预测出哪个扫描的年龄更大:我们得出的结论是:在英国广播公司的纵向队列中,SMT-VIS 连接会随着年龄的增长而增加;在英国广播公司的横向队列中,静息状态 FC 会随着年龄的增长而增加。
Somatomotor-visual resting state functional connectivity increases after 2 years in the UK Biobank longitudinal cohort.
Purpose: Functional magnetic resonance imaging (fMRI) and functional connectivity (FC) have been used to follow aging in both children and older adults. Robust changes have been observed in children, in which high connectivity among all brain regions changes to a more modular structure with maturation. We examine FC changes in older adults after 2 years of aging in the UK Biobank (UKB) longitudinal cohort.
Approach: We process fMRI connectivity data using the Power264 atlas and then test whether the average internetwork FC changes in the 2722-subject longitudinal cohort are statistically significant using a Bonferroni-corrected -test. We also compare the ability of Power264 and UKB-provided, independent component analysis (ICA)-based FC to determine which of a longitudinal scan pair is older. Finally, we investigate cross-sectional FC changes as well as differences due to differing scanner tasks in the UKB, Philadelphia Neurodevelopmental Cohort, and Alzheimer's Disease Neuroimaging Initiative datasets.
Results: We find a 6.8% average increase in somatomotor network (SMT)-visual network (VIS) connectivity from younger to older scans (corrected ) that occurs in male, female, older subject ( years old), and younger subject ( years old) groups. Among all internetwork connections, the average SMT-VIS connectivity is the best predictor of relative scan age. Using the full FC and a training set of 2000 subjects, one is able to predict which scan is older 82.5% of the time using either the full Power264 FC or the UKB-provided ICA-based FC.
Conclusions: We conclude that SMT-VIS connectivity increases with age in the UKB longitudinal cohort and that resting state FC increases with age in the UKB cross-sectional cohort.
期刊介绍:
JMI covers fundamental and translational research, as well as applications, focused on medical imaging, which continue to yield physical and biomedical advancements in the early detection, diagnostics, and therapy of disease as well as in the understanding of normal. The scope of JMI includes: Imaging physics, Tomographic reconstruction algorithms (such as those in CT and MRI), Image processing and deep learning, Computer-aided diagnosis and quantitative image analysis, Visualization and modeling, Picture archiving and communications systems (PACS), Image perception and observer performance, Technology assessment, Ultrasonic imaging, Image-guided procedures, Digital pathology, Biomedical applications of biomedical imaging. JMI allows for the peer-reviewed communication and archiving of scientific developments, translational and clinical applications, reviews, and recommendations for the field.