Scholarlink

Aim <p>Alzheimer’s disease (AD) is a major cause of dementia, marked by cognitive decline and behavioral and psychological symptoms of dementia (BPSD). Early differentiation between AD, mild cognitive impairment (MCI), and healthy controls (HC) is essential for improving diagnostic accuracy and guiding effective treatment strategies.</p> Methods <p>This retrospective study included 120 participants divided into AD (<i>n</i> = 40), MCI (<i>n</i> = 40), and HC (<i>n</i> = 40) groups. Brain MRI data were analyzed using the AccuBrain system to quantify AD Resemblance Atrophy Index (AD-RAI), Quantitative Medial Temporal Atrophy (QMTA), hippocampal volume, and white matter hyperintensities. Correlation analyses were conducted between imaging biomarkers and cognitive function scores (Mini-Mental State Examination, MMSE; Neuropsychiatric Inventory, NPI). Receiver operating characteristic (ROC) curve analysis was used to evaluated the diagnostic performance of the biomarkers.</p> Results <p>AD patients had significantly higher AD-RAI (0.91 ± 0.25) and more pronounced hippocampal atrophy (0.36 ± 0.09) compared to MCI and HC (<i>P</i> &lt; 0.001). Correlation analyses showed that AD-RAI and QMTA were negatively correlated with MMSE scores (<i>r</i> = -0.718, <i>P</i> &lt; 0.001; <i>r</i> = -0.463, <i>P</i> &lt; 0.001), while hippocampal volume was positively correlated with MMSE (<i>r</i> = 0.408, <i>P</i> &lt; 0.001). ROC analysis revealed that AD-RAI had an AUC of 0.777 for distinguishing AD from MCI, while QMTA had an AUC of 0.938 for distinguishing AD from HC. BPSD patients exhibited higher AD-RAI (1.09 ± 0.18) and greater hippocampal atrophy, with ROC AUC &gt; 0.9 for distinguishing BPSD from non-BPSD patients.</p> Conclusion <p>The AccuBrain MRI system demonstrated high sensitivity and diagnostic value in distinguishing AD from MCI and HC, as well as in identifying patients with BPSD. Correlation and ROC analyses support the use of these imaging biomarkers for early diagnosis and personalized treatment strategies in AD.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Evaluation of AccuBrain-based MRI quantitative analysis in diagnosing Alzheimer’s disease and assessing behavioral and psychological symptoms of dementia

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年4月17日

查看全文
  • Huixian Lu,
  • Caixia Xu,
  • Jiaquan Liang

摘要

Aim

Alzheimer’s disease (AD) is a major cause of dementia, marked by cognitive decline and behavioral and psychological symptoms of dementia (BPSD). Early differentiation between AD, mild cognitive impairment (MCI), and healthy controls (HC) is essential for improving diagnostic accuracy and guiding effective treatment strategies.

Methods

This retrospective study included 120 participants divided into AD (n = 40), MCI (n = 40), and HC (n = 40) groups. Brain MRI data were analyzed using the AccuBrain system to quantify AD Resemblance Atrophy Index (AD-RAI), Quantitative Medial Temporal Atrophy (QMTA), hippocampal volume, and white matter hyperintensities. Correlation analyses were conducted between imaging biomarkers and cognitive function scores (Mini-Mental State Examination, MMSE; Neuropsychiatric Inventory, NPI). Receiver operating characteristic (ROC) curve analysis was used to evaluated the diagnostic performance of the biomarkers.

Results

AD patients had significantly higher AD-RAI (0.91 ± 0.25) and more pronounced hippocampal atrophy (0.36 ± 0.09) compared to MCI and HC (P < 0.001). Correlation analyses showed that AD-RAI and QMTA were negatively correlated with MMSE scores (r = -0.718, P < 0.001; r = -0.463, P < 0.001), while hippocampal volume was positively correlated with MMSE (r = 0.408, P < 0.001). ROC analysis revealed that AD-RAI had an AUC of 0.777 for distinguishing AD from MCI, while QMTA had an AUC of 0.938 for distinguishing AD from HC. BPSD patients exhibited higher AD-RAI (1.09 ± 0.18) and greater hippocampal atrophy, with ROC AUC > 0.9 for distinguishing BPSD from non-BPSD patients.

Conclusion

The AccuBrain MRI system demonstrated high sensitivity and diagnostic value in distinguishing AD from MCI and HC, as well as in identifying patients with BPSD. Correlation and ROC analyses support the use of these imaging biomarkers for early diagnosis and personalized treatment strategies in AD.