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Lu H, Li J. MRI-informed machine learning-driven brain age models for classifying mild cognitive impairment converters. J Cent Nerv Syst Dis 2024; 16:11795735241266556. [PMID: 39049837 PMCID: PMC11268046 DOI: 10.1177/11795735241266556] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2024] [Accepted: 06/02/2024] [Indexed: 07/27/2024] Open
Abstract
BACKGROUND Brain age model, including estimated brain age and brain-predicted age difference (brain-PAD), has shown great potentials for serving as imaging markers for monitoring normal ageing, as well as for identifying the individuals in the pre-diagnostic phase of neurodegenerative diseases. PURPOSE This study aimed to investigate the brain age models in normal ageing and mild cognitive impairments (MCI) converters and their values in classifying MCI conversion. METHODS Pre-trained brain age model was constructed using the structural magnetic resonance imaging (MRI) data from the Cambridge Centre for Ageing and Neuroscience (Cam-CAN) project (N = 609). The tested brain age model was built using the baseline, 1-year and 3-year follow-up MRI data from normal ageing (NA) adults (n = 32) and MCI converters (n = 22) drew from the Open Access Series of Imaging Studies (OASIS-2). The quantitative measures of morphometry included total intracranial volume (TIV), gray matter volume (GMV) and cortical thickness. Brain age models were calculated based on the individual's morphometric features using the support vector machine (SVM) algorithm. RESULTS With comparable chronological age, MCI converters showed significant increased TIV-based (Baseline: P = 0.021; 1-year follow-up: P = 0.037; 3-year follow-up: P = 0.001) and left GMV-based brain age than NA adults at all time points. Higher brain-PAD scores were associated with worse global cognition. Acceptable classification performance of TIV-based (AUC = 0.698) and left GMV-based brain age (AUC = 0.703) was found, which could differentiate the MCI converters from NA adults at the baseline. CONCLUSIONS This is the first demonstration that MRI-informed brain age models exhibit feature-specific patterns. The greater GMV-based brain age observed in MCI converters may provide new evidence for identifying the individuals at the early stage of neurodegeneration. Our findings added value to existing quantitative imaging markers and might help to improve disease monitoring and accelerate personalized treatments in clinical practice.
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Affiliation(s)
- Hanna Lu
- Department of Psychiatry, The Chinese University of Hong Kong, Hong Kong, China
- Department of Neurology, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Jing Li
- Department of Psychiatry, The Chinese University of Hong Kong, Hong Kong, China
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Lu H, Li J, Chan SSM, Ma SL, Mok VCT, Shi L, Mak ADP, Lam LCW. Predictive values of pre-treatment brain age models to rTMS effects in neurocognitive disorder with depression: Secondary analysis of a randomised sham-controlled clinical trial. DIALOGUES IN CLINICAL NEUROSCIENCE 2024; 26:38-52. [PMID: 38963341 PMCID: PMC11225634 DOI: 10.1080/19585969.2024.2373075] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/18/2024] [Accepted: 06/21/2024] [Indexed: 07/05/2024]
Abstract
INTRODUCTION One major challenge in developing personalised repetitive transcranial magnetic stimulation (rTMS) is that the treatment responses exhibited high inter-individual variations. Brain morphometry might contribute to these variations. This study sought to determine whether individual's brain morphometry could predict the rTMS responders and remitters. METHODS This was a secondary analysis of data from a randomised clinical trial that included fifty-five patients over the age of 60 with both comorbid depression and neurocognitive disorder. Based on magnetic resonance imaging scans, estimated brain age was calculated with morphometric features using a support vector machine. Brain-predicted age difference (brain-PAD) was computed as the difference between brain age and chronological age. RESULTS The rTMS responders and remitters had younger brain age. Every additional year of brain-PAD decreased the odds of relieving depressive symptoms by ∼25.7% in responders (Odd ratio [OR] = 0.743, p = .045) and by ∼39.5% in remitters (OR = 0.605, p = .022) in active rTMS group. Using brain-PAD score as a feature, responder-nonresponder classification accuracies of 85% (3rd week) and 84% (12th week), respectively were achieved. CONCLUSION In elderly patients, younger brain age appears to be associated with better treatment responses to active rTMS. Pre-treatment brain age models informed by morphometry might be used as an indicator to stratify suitable patients for rTMS treatment. TRIAL REGISTRATION ClinicalTrials.gov Identifier: ChiCTR-IOR-16008191.
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Affiliation(s)
- Hanna Lu
- Department of Psychiatry, The Chinese University of Hong Kong, Hong Kong SAR, China
- The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Jing Li
- Department of Psychiatry, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Sandra Sau Man Chan
- Department of Psychiatry, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Suk Ling Ma
- Department of Psychiatry, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Vincent Chung Tong Mok
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Lin Shi
- Department of Imaging and Interventional Radiology, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Arthur Dun-Ping Mak
- Department of Psychiatry, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Linda Chiu Wa Lam
- Department of Psychiatry, The Chinese University of Hong Kong, Hong Kong SAR, China
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Burmistrov DE, Gudkov SV, Franceschi C, Vedunova MV. Sex as a Determinant of Age-Related Changes in the Brain. Int J Mol Sci 2024; 25:7122. [PMID: 39000227 PMCID: PMC11241365 DOI: 10.3390/ijms25137122] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2024] [Revised: 06/25/2024] [Accepted: 06/26/2024] [Indexed: 07/16/2024] Open
Abstract
The notion of notable anatomical, biochemical, and behavioral distinctions within male and female brains has been a contentious topic of interest within the scientific community over several decades. Advancements in neuroimaging and molecular biological techniques have increasingly elucidated common mechanisms characterizing brain aging while also revealing disparities between sexes in these processes. Variations in cognitive functions; susceptibility to and progression of neurodegenerative conditions, notably Alzheimer's and Parkinson's diseases; and notable disparities in life expectancy between sexes, underscore the significance of evaluating aging within the framework of gender differences. This comprehensive review surveys contemporary literature on the restructuring of brain structures and fundamental processes unfolding in the aging brain at cellular and molecular levels, with a focus on gender distinctions. Additionally, the review delves into age-related cognitive alterations, exploring factors influencing the acceleration or deceleration of aging, with particular attention to estrogen's hormonal support of the central nervous system.
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Affiliation(s)
- Dmitriy E. Burmistrov
- Prokhorov General Physics Institute of the Russian Academy of Sciences, 38 Vavilova St., 119991 Moscow, Russia;
| | - Sergey V. Gudkov
- Prokhorov General Physics Institute of the Russian Academy of Sciences, 38 Vavilova St., 119991 Moscow, Russia;
- Institute of Biology and Biomedicine, Lobachevsky State University of Nizhny Novgorod, 23 Gagarin Ave., 603022 Nizhny Novgorod, Russia
| | - Claudio Franceschi
- Institute of Biology and Biomedicine, Lobachevsky State University of Nizhny Novgorod, 23 Gagarin Ave., 603022 Nizhny Novgorod, Russia
| | - Maria V. Vedunova
- Institute of Biology and Biomedicine, Lobachevsky State University of Nizhny Novgorod, 23 Gagarin Ave., 603022 Nizhny Novgorod, Russia
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Díaz Beltrán L, Madan CR, Finke C, Krohn S, Di Ieva A, Esteban FJ. Fractal Dimension Analysis in Neurological Disorders: An Overview. ADVANCES IN NEUROBIOLOGY 2024; 36:313-328. [PMID: 38468040 DOI: 10.1007/978-3-031-47606-8_16] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/13/2024]
Abstract
Fractal analysis has emerged as a powerful tool for characterizing irregular and complex patterns found in the nervous system. This characterization is typically applied by estimating the fractal dimension (FD), a scalar index that describes the topological complexity of the irregular components of the nervous system, both at the macroscopic and microscopic levels, that may be viewed as geometric fractals. Moreover, temporal properties of neurophysiological signals can also be interpreted as dynamic fractals. Given its sensitivity for detecting changes in brain morphology, FD has been explored as a clinically relevant marker of brain damage in several neuropsychiatric conditions as well as in normal and pathological cerebral aging. In this sense, evidence is accumulating for decreases in FD in Alzheimer's disease, frontotemporal dementia, Parkinson's disease, multiple sclerosis, and many other neurological disorders. In addition, it is becoming increasingly clear that fractal analysis in the field of clinical neurology opens the possibility of detecting structural alterations in the early stages of the disease, which highlights FD as a potential diagnostic and prognostic tool in clinical practice.
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Affiliation(s)
- Leticia Díaz Beltrán
- Department of Medical Oncology, Clinical Research Unit, University Hospital of Jaén, Jaén, Spain
| | | | - Carsten Finke
- Department of Neurology, Charité-Universitätsmedizin, Berlin, Germany
| | - Stephan Krohn
- Department of Neurology, Charité-Universitätsmedizin, Berlin, Germany
| | - Antonio Di Ieva
- Computational NeuroSurgery (CNS) Lab, Faculty of Medicine, Health and Human Sciences, Macquarie Medical School, Macquarie University, Sydney, NSW, Australia
| | - Francisco J Esteban
- Systems Biology Unit, Department of Experimental Biology, University of Jaén, Jaén, Spain.
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Lu H, Li J, Yang NS, Lam LCW, Ma SL, Wing YK, Zhang L. Using gamma-band transcranial alternating current stimulation (tACS) to improve sleep quality and cognition in patients with mild neurocognitive disorders due to Alzheimer's disease: A study protocol for a randomized controlled trial. PLoS One 2023; 18:e0289591. [PMID: 37540692 PMCID: PMC10403094 DOI: 10.1371/journal.pone.0289591] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Accepted: 07/21/2023] [Indexed: 08/06/2023] Open
Abstract
BACKGROUND Sleep disturbances are highly prevalent in patients with age-related neurodegenerative diseases, which severely affect cognition and even lead to accumulated β-amyloid. Encouraging results from recent studies on transcranial direct current stimulation (tDCS) showed moderate positive effects on sleep quality in preclinical Alzheimer's disease (AD). Compared to tDCS, transcranial alternating current stimulation (tACS) enables the entrainment of neuronal activity with optimized focality through injecting electric current with a specific frequency and has significant enhancement effects on slow wave activities. METHODS AND DESIGN This is a randomized, double-blind, sham-controlled clinical trial comparing 40 Hz tACS with tDCS in mild neurocognitive disorders due to AD with sleep disturbances. Magnetic resonance imaging (MRI) data is used to construct personalized realistic head model. Treatment outcomes, including sleep quality, cognitive performance and saliva Aβ levels will be conducted at baseline, 4th week, 8th week, 12th week and 24th week. CONCLUSIONS It is expected that the repeated gamma-band tACS will show significant improvements in sleep quality and cognitive functions compared to tDCS and sham tDCS. The findings will provide high-level evidence and guide further advanced studies in the field of neurodegenerative diseases and sleep medicine. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT05544201.
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Affiliation(s)
- Hanna Lu
- Department of Psychiatry, The Chinese University of Hong Kong, Hong Kong SAR, China
- The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Jing Li
- Department of Psychiatry, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Natalie Shu Yang
- Department of Psychiatry, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Linda Chiu Wa Lam
- Department of Psychiatry, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Suk Ling Ma
- Department of Psychiatry, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Yun Kwok Wing
- Department of Psychiatry, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Li Zhang
- Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Hong Kong SAR, China
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Nazlee N, Waiter GD, Sandu A. Age-associated sex and asymmetry differentiation in hemispheric and lobar cortical ribbon complexity across adulthood: A UK Biobank imaging study. Hum Brain Mapp 2023; 44:49-65. [PMID: 36574599 PMCID: PMC9783444 DOI: 10.1002/hbm.26076] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2021] [Revised: 07/28/2022] [Accepted: 08/21/2022] [Indexed: 02/01/2023] Open
Abstract
Cortical morphology changes with ageing and age-related neurodegenerative diseases. Previous studies suggest that the age effect is more pronounced in the frontal lobe. However, our knowledge of structural complexity changes in male and female brains is still limited. We measured cortical ribbon complexity through fractal dimension (FD) analysis at the hemisphere and lobe level in 7010 individuals from the UK Biobank imaging cohort to study age-related sex differences (3332 males, age ranged 45-79 years). FD decreases significantly with age and sexual dimorphism exists. With correction for brain size, females showed higher complexity in the left hemisphere and left and right parietal lobes whereas males showed higher complexity in the right temporal and left and right occipital lobes. A nonlinear age effect was observed in the left and right frontal, and right temporal lobes. Differential patterns of age effects were observed in both sexes with relatively more age-affected regions in males. Significantly higher rightward asymmetries at hemisphere, frontal, parietal, and occipital lobe level and higher leftward asymmetry in temporal lobe were observed. There was no age-by-sex-by asymmetry interaction in any region. When controlling for brain size, the leftward hemispheric, and temporal lobe asymmetry decreased with age. Males had significantly lower asymmetry between hemispheres and higher asymmetry in the parietal and occipital lobes than females. This work provides distinct patterns of age-related sex and asymmetry differences that can aid in the future development of sex-specific models of the normal brain to ascribe cognitive functional significance of these patterns in ageing.
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Affiliation(s)
- Nafeesa Nazlee
- Aberdeen Biomedical Imaging CentreUniversity of AberdeenAberdeenScotland
| | - Gordon D. Waiter
- Aberdeen Biomedical Imaging CentreUniversity of AberdeenAberdeenScotland
| | - Anca‐Larisa Sandu
- Aberdeen Biomedical Imaging CentreUniversity of AberdeenAberdeenScotland
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Lu H, Chan SSM, Ma S, Lin C, Mok VCT, Shi L, Wang D, Mak AD, Lam LCW. Clinical and radiomic features for predicting the treatment response of repetitive transcranial magnetic stimulation in major neurocognitive disorder: Results from a randomized controlled trial. Hum Brain Mapp 2022; 43:5579-5592. [PMID: 35912517 PMCID: PMC9704797 DOI: 10.1002/hbm.26032] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2022] [Revised: 06/15/2022] [Accepted: 07/18/2022] [Indexed: 01/15/2023] Open
Abstract
Image-guided repetitive transcranial magnetic stimulation (rTMS) has shown clinical effectiveness in senior adults with co-occurring depression and cognitive impairment, yet the imaging markers for predicting the treatment response are less investigated. In this clinical trial, we examined the efficacy and sustainability of 10 Hz rTMS for the treatment of depression and cognitive impairment in major neurocognitive disorder (NCD) patients and tested the predictive values of imaging-informed radiomic features in response to rTMS treatment. Fifty-five major NCD patients with depression were randomly assigned to receive a 3-week rTMS treatment of either active 10 Hz rTMS (n = 27) or sham rTMS (n = 28). Left dorsolateral prefrontal cortex (DLPFC) was the predefined treatment target. Based on individual structural magnetic resonance imaging scans, surface-based analysis was conducted to quantitatively measure the baseline radiomic features of left DLPFC. Severity of depression, global cognition and the serum brain-derived neurotrophic factor (BDNF) level were evaluated at baseline, 3-, 6- and 12-week follow-ups. Logistic regression analysis revealed that advanced age, higher baseline cognition and randomized group were associated with the remission of depression. Increased cortical thickness and gyrification in left DLPFC were the significant predictors of clinical remission and cognitive enhancement. A 3-week course of 10 Hz rTMS is an effective adjuvant treatment for rapid ameliorating depressive symptoms and enhancing cognitive function. Pre-treatment radiomic features of the stimulation target can predict the response to rTMS treatment in major NCD. Cortical thickness and folding of treatment target may serve as imaging markers to detect the responders. ChiCTR-IOR-16008191, registered on March 30, 2016.
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Affiliation(s)
- Hanna Lu
- Department of PsychiatryThe Chinese University of Hong KongHong Kong SARChina,The Affiliated Brain Hospital of Guangzhou Medical UniversityGuangzhouChina
| | - Sandra Sau Man Chan
- Department of PsychiatryThe Chinese University of Hong KongHong Kong SARChina
| | - Sukling Ma
- Department of PsychiatryThe Chinese University of Hong KongHong Kong SARChina
| | - Cuichan Lin
- Department of PsychiatryThe Chinese University of Hong KongHong Kong SARChina
| | - Vincent Chung Tong Mok
- Department of Medicine and TherapeuticsThe Chinese University of Hong KongHong Kong SARChina
| | - Lin Shi
- Department of Imaging and Interventional RadiologyThe Chinese University of Hong KongHong Kong SARChina
| | - Defeng Wang
- Department of Imaging and Interventional RadiologyThe Chinese University of Hong KongHong Kong SARChina
| | - Arthur Dun‐Ping Mak
- Department of PsychiatryThe Chinese University of Hong KongHong Kong SARChina
| | - Linda Chiu Wa Lam
- Department of PsychiatryThe Chinese University of Hong KongHong Kong SARChina
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8
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Meregalli V, Alberti F, Madan CR, Meneguzzo P, Miola A, Trevisan N, Sambataro F, Favaro A, Collantoni E. Cortical Complexity Estimation Using Fractal Dimension: A Systematic Review of the Literature on Clinical and Nonclinical Samples. Eur J Neurosci 2022; 55:1547-1583. [PMID: 35229388 PMCID: PMC9313853 DOI: 10.1111/ejn.15631] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2021] [Revised: 01/27/2022] [Accepted: 02/20/2022] [Indexed: 12/04/2022]
Abstract
Fractal geometry has recently been proposed as a useful tool for characterizing the complexity of the brain cortex, which is likely to derive from the recurrence of sulci–gyri convolution patterns. The index used to describe the cortical complexity is called fractal dimensional (FD) and was employed by different research exploring the neurobiological correlates of distinct pathological and nonpathological conditions. This review aims to describe the literature on the application of this index, summarize the heterogeneities between studies and inform future research on this topic. Sixty‐two studies were included in the systematic review. The main research lines concern neurodevelopment, aging and the neurobiology of specific psychiatric and neurological disorders. Overall, the included papers indicate that cortical complexity is likely to reduce during aging and in various pathological processes affecting the brain. Nevertheless, the high heterogeneity between studies strongly prevents the possibility of drawing conclusions. Further research considering this index besides other morphological values is needed to better clarify the role of FD in characterizing the cortical structure. Fractal dimension (FD) is a useful tool for the assessment of cortical complexity. In healthy controls, FD is associated with development, aging and cognition. Alterations in FD have been observed in different neurological and psychiatric disorders.
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Affiliation(s)
- Valentina Meregalli
- Department of Neurosciences, University of Padua, Padova, Italy.,Padua Neuroscience Center, University of Padua, Padova, Italy
| | | | | | - Paolo Meneguzzo
- Department of Neurosciences, University of Padua, Padova, Italy
| | - Alessandro Miola
- Department of Neurosciences, University of Padua, Padova, Italy.,Padua Neuroscience Center, University of Padua, Padova, Italy
| | - Nicolò Trevisan
- Department of Neurosciences, University of Padua, Padova, Italy.,Padua Neuroscience Center, University of Padua, Padova, Italy
| | - Fabio Sambataro
- Department of Neurosciences, University of Padua, Padova, Italy.,Padua Neuroscience Center, University of Padua, Padova, Italy
| | - Angela Favaro
- Department of Neurosciences, University of Padua, Padova, Italy.,Padua Neuroscience Center, University of Padua, Padova, Italy
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Lu H. MRI-Based Geometric Modeling for Personalized Transcranial Magnetic Stimulation in Age-Related Neurodegenerative Diseases. Front Neurosci 2021; 15:685424. [PMID: 34366775 PMCID: PMC8339904 DOI: 10.3389/fnins.2021.685424] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2021] [Accepted: 06/16/2021] [Indexed: 01/03/2023] Open
Affiliation(s)
- Hanna Lu
- Department of Psychiatry, The Chinese University of Hong Kong, Hong Kong, China.,Centre for Neuromodulation and Rehabilitation, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
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Lu H, Li J, Zhang L, Chan SSM, Lam LCW. Dynamic changes of region-specific cortical features and scalp-to-cortex distance: implications for transcranial current stimulation modeling. J Neuroeng Rehabil 2021; 18:2. [PMID: 33397402 PMCID: PMC7784346 DOI: 10.1186/s12984-020-00764-5] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2020] [Accepted: 09/22/2020] [Indexed: 02/02/2023] Open
Abstract
BACKGROUND Transcranial current stimulation in rehabilitation is a fast-growing field featured with computational and biophysical modeling. Cortical features and scalp-to-cortex distance (SCD) are key variables for determining the strength and distribution of the electric field, yet longitudinal studies able to capture these dynamic changes are missing. We sought to investigate and quantify the ageing effect on the morphometry and SCD of left primary motor cortex (M1) and dorsolateral prefrontal cortex (DLPFC) in normal ageing adults and mild cognitive impairment (MCI) converters. METHODS Baseline, 1-year and 3-year follow-up structural magnetic resonance imaging scans from normal ageing adults (n = 32), and MCI converters (n = 22) were drawn from the Open Access Series of Imaging Studies. We quantified the changes of the cortical features and SCDs of left M1 and DLPFC, including grey matter volume, white matter volume, cortical thickness, and folding. Head model was developed to simulate the impact of SCD on the electric field induced by transcranial current stimulation. RESULTS Pronounced ageing effect was found on the SCD of left DLPFC in MCI converters. The SCD change of left DLPFC from baseline to 3-year follow-up demonstrated better performance to discriminate MCI converters from normal ageing adults than the other morphometric measures. The strength of electric field was consequently decreased with SCD in MCI converters. CONCLUSION Ageing has a prominent, but differential effect on the region-specific SCD and cortical features in older adults with cognitive impairments. Our findings suggest that SCD, cortical thickness, and folding of the targeted regions could be used as valuable imaging markers when conducting transcranial brain stimulation in individuals with brain atrophy.
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Affiliation(s)
- Hanna Lu
- Department of Psychiatry, Multi-Centre, The Chinese University of Hong Kong, Tai Po Hospital, Hong Kong SAR, G/F China
- The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Jing Li
- Department of Psychiatry, Multi-Centre, The Chinese University of Hong Kong, Tai Po Hospital, Hong Kong SAR, G/F China
| | - Li Zhang
- Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Sandra Sau Man Chan
- Department of Psychiatry, Multi-Centre, The Chinese University of Hong Kong, Tai Po Hospital, Hong Kong SAR, G/F China
| | - Linda Chiu Wa Lam
- Department of Psychiatry, Multi-Centre, The Chinese University of Hong Kong, Tai Po Hospital, Hong Kong SAR, G/F China
| | - for the Open Access Series of Imaging Studies
- Department of Psychiatry, Multi-Centre, The Chinese University of Hong Kong, Tai Po Hospital, Hong Kong SAR, G/F China
- The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
- Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Hong Kong SAR, China
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