Hippocampal atrophy and cognitive function in transient ischemic attack and minor stroke patients over three years

Barber, Philip A.; Nestor, Sean M.; Wang, Meng; Wu, Pauline; Ursenbach, Jake; Munir, Amlish; Gupta, Ritu; Tariq, Sah Sana; Smith, Eric E.; Frayne, Richard; Black, Sandra E.; Sajobi, Tolupe; Coutts, Shelagh B.

doi:10.1016/j.cccb.2021.100019

Cited by 4 publications

(4 citation statements)

References 19 publications

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“…HA has a variety of pathologies, such as β-amyloid deposition, α-synuclein protein deposition [31,32], and vascular brain injuries [8,9]. In our study, even though the cut-offs for the MTA score excluded maximally HA caused by degenerative diseases [15], we still found 3 dementia CSVD patients were diagnosed as AD, which con rmed further the results of the 1362 autopsy pathology study, they suggest that the majority of patients with AD have mixed dementia, with both classic AD neurodegenerative pathology as well as cerebrovascular pathology [35].…”

Section: Discussionmentioning

confidence: 99%

“…No statistical differences were found among the three models. Given the highest AUC value in the T2-FLAIR model, converting the rad-score into binary T2-FLAIR (No, Yes) revealed a correlation between a 'Yes' response and dementia (OR = 13.21, 95% CI 3.487−59.922, p < 0.001) after adjusting for risk factors.Conclusion: Radiomic analysis of the hippocampus in T2-FLAIR images can effectively identify dementia in CSVD patients with normal age-related HA.Hippocampal atrophy (HA) has been associated with dementia in AD [4,5], PD [6,7], and post-stroke [8,9]. However, little is known about its association with CSVD, despite atrophy being recognized as a neuroimaging manifestation of CSVD [10].…”

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confidence: 99%

“…Hippocampal atrophy (HA) has been associated with dementia in AD [4,5], PD [6,7], and post-stroke [8,9]. However, little is known about its association with CSVD, despite atrophy being recognized as a neuroimaging manifestation of CSVD [10].…”

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confidence: 99%

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Radiomics Models Identifying Dementia in Patients with Normal Age-Related Hippocampal Atrophy: A study based on Machine Learning

Yang,

Huang,

Luo

et al. 2024

Preprint

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Background: Our study aimed to employ a machine learning models based on radiomics for automated dementia identification in cerebral small vessel disease (CSVD) patients with normal age-related hippocampal atrophy (HA). Methods: CSVD patients were divided randomly into training and validation sets in a 6:4 ratio. Bilateral hippocampus segmented based on T2 and FLAIR were used for radiomics. Dementia radiomics models (T2 model, T2FLAIR model, T2-T2FLAIR model) were developed in the training sets and was further verified in the validation sets. The rad_score from the best models, along with clinical factors, was integrated to construct clinic-radiomics models for dementia through multifactor logistic regression analysis. Results: 116 CSVD patients were recruited, 30 patients were dementia and 86 patients were non-dementia. In predicting dementia in the training and validation sets, the area under curves (AUC) were 0.811 and 0.779 for the T2 model, 0.807 and 0.755 for the T2FLAIR model, and 0.864 and 0.801 for the T2-T2FLAIR model. In the overall 116 patients, the AUCs were 0.801 for of the T2 model, 0.783 for the T2FLAIR model, and 0.840 for the T2FLAIR model. No statistical differences were found among the three models. Given the highest AUC value in the T2-FLAIR model, converting the rad-score into binary T2-FLAIR (No, Yes) revealed a correlation between a 'Yes' response and dementia (OR = 13.21, 95% CI 3.487−59.922, p < 0.001) after adjusting for risk factors. Conclusion: Radiomic analysis of the hippocampus in T2-FLAIR images can effectively identify dementia in CSVD patients with normal age-related HA.

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Section: Discussionmentioning

confidence: 99%

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confidence: 99%

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Radiomics Models Identifying Dementia in Patients with Normal Age-Related Hippocampal Atrophy: A study based on Machine Learning

Yang,

Huang,

Luo

et al. 2024

Preprint

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“…Both diastolic blood pressure and white matter disease severity were correlated with the atrophy rate in TIA patients. In a study of TIA/minor stroke patients from the Extended-CATCH (CT and MRI in the Triage of TIA and minor Cerebrovascular events to identify high-risk patients) study compared to healthy controls from the Alzheimer's Disease Neuroimaging Initiative (ADNI), patients with TIA/minor stroke demonstrated a higher hippocampal atrophy rate than controls over a 3-year interval [91]. The annual percentage change of the left hippocampal volume was 2.5% (78 mm 3 per year) for TIA/minor stroke patients compared to 0.9% (29 mm 3 per year) for controls; the annual percentage change of the right hippocampal volume was 2.5% (80 mm 3 per year) for TIA/stroke patients compared to 0.5% (17 mm 3 per year) for controls.…”

Section: Predictors and Mediators Of Cognitive Decline After Tiamentioning

confidence: 99%

The Cognitive Sequelae of Transient Ischemic Attacks—Recent Insights and Future Directions

Ganesh

Barber

2022

JCM

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There is now considerable evidence that Transient Ischemic Attack (TIA) carries important sequelae beyond the risk of recurrent stroke, particularly with respect to peri-event and post-event cognitive dysfunction and subsequent cognitive decline. The occurrence of a TIA could provide an important window in understanding the relationship of early mixed vascular-neurodegenerative cognitive decline, and by virtue of their clinical relevance as a “warning” event, TIAs could also furnish the opportunity to act preventatively not only for stroke prevention but also for dementia prevention. In this review, we discuss the current state of the literature regarding the cognitive sequelae associated with TIA, reviewing important challenges in the field. In particular, we discuss definitional and methodological challenges in the study of TIA-related cognitive impairment, confounding factors in the cognitive evaluation of these patients, and provide an overview of the evidence on both transient and long-term cognitive impairment after TIA. We compile recent insights from clinical studies regarding the predictors and mediators of cognitive decline in these patients and highlight important future directions for work in this area.

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Alterations of contralesional hippocampal subfield volumes and relations to cognitive functions in patients with unilateral stroke

Lu,

Xing,

et al. 2024

Brain and Behavior

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BackgroundThe volumes of the hippocampal subfields are related to poststroke cognitive dysfunctions. However, it remains unclear whether contralesional hippocampal subfield volume contributes to cognitive impairment. This study aimed to investigate the volumetric differences in the contralesional hippocampal subfields between patients with left and right hemisphere strokes (LHS/RHS). Additionally, correlations between contralesional hippocampal subfield volumes and clinical outcomes were explored.MethodsFourteen LHS (13 males, 52.57 ± 7.10 years), 13 RHS (11 males, 51.23 ± 15.23 years), and 18 healthy controls (11 males, 46.94 ± 12.74 years) were enrolled. Contralesional global and regional hippocampal volumes were obtained with T1‐weighted images. Correlations between contralesional hippocampal subfield volumes and clinical outcomes, including the Montreal Cognitive Assessment (MoCA) and Mini‐Mental State Examination (MMSE), were analyzed. Bonferroni correction was applied for multiple comparisons.ResultsSignificant reductions were found in contralesional hippocampal as a whole (adjusted p = .011) and its subfield volumes, including the hippocampal tail (adjusted p = .005), cornu ammonis 1 (CA1) (adjusted p = .002), molecular layer (ML) (adjusted p = .004), granule cell and ML of the dentate gyrus (GC‐ML‐DG) (adjusted p = .015), CA3 (adjusted p = .009), and CA4 (adjusted p = .014) in the RHS group compared to the LHS group. MoCA and MMSE had positive correlations with volumes of contralesional hippocampal tail (p = .015, r = .771; p = .017, r = .763) and fimbria (p = .020, r = .750; p = .019, r = .753) in the LHS group, and CA3 (p = .007, r = .857; p = .009, r = .838) in the RHS group, respectively.ConclusionUnilateral stroke caused volumetric differences in different hippocampal subfields contralesionally, which correlated to cognitive impairment. RHS leads to greater volumetric reduction in the whole contralesional hippocampus and specific subfields (hippocampal tail, CA1, ML, GC‐ML‐DG, CA3, and CA4) compared to LHS. These changes are correlated with cognitive impairments, potentially due to disrupted neural pathways and interhemispheric communication.

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Hippocampal atrophy and cognitive function in transient ischemic attack and minor stroke patients over three years

Cited by 4 publications

References 19 publications

Radiomics Models Identifying Dementia in Patients with Normal Age-Related Hippocampal Atrophy: A study based on Machine Learning

Radiomics Models Identifying Dementia in Patients with Normal Age-Related Hippocampal Atrophy: A study based on Machine Learning

The Cognitive Sequelae of Transient Ischemic Attacks—Recent Insights and Future Directions

Alterations of contralesional hippocampal subfield volumes and relations to cognitive functions in patients with unilateral stroke

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