Decoding MRI-informed brain age using mutual information.

IF 4.1 2区医学 Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING Insights into Imaging Pub Date : 2024-08-26 DOI:10.1186/s13244-024-01791-9

Jing Li, Linda Chiu Wa Lam, Hanna Lu

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Abstract

Objective: We aimed to develop a standardized method to investigate the relationship between estimated brain age and regional morphometric features, meeting the criteria for simplicity, generalization, and intuitive interpretability.

Methods: We utilized T1-weighted magnetic resonance imaging (MRI) data from the Cambridge Centre for Ageing and Neuroscience project (N = 609) and employed a support vector regression method to train a brain age model. The pre-trained brain age model was applied to the dataset of the brain development project (N = 547). Kraskov (KSG) estimator was used to compute the mutual information (MI) value between brain age and regional morphometric features, including gray matter volume (GMV), white matter volume (WMV), cerebrospinal fluid (CSF) volume, and cortical thickness (CT).

Results: Among four types of brain features, GMV had the highest MI value (8.71), peaking in the pre-central gyrus (0.69). CSF volume was ranked second (7.76), with the highest MI value in the cingulate (0.87). CT was ranked third (6.22), with the highest MI value in superior temporal gyrus (0.53). WMV had the lowest MI value (4.59), with the insula showing the highest MI value (0.53). For brain parenchyma, the volume of the superior frontal gyrus exhibited the highest MI value (0.80).

Conclusion: This is the first demonstration that MI value between estimated brain age and morphometric features may serve as a benchmark for assessing the regional contributions to estimated brain age. Our findings highlighted that both GMV and CSF are the key features that determined the estimated brain age, which may add value to existing computational models of brain age.

Critical relevance statement: Mutual information (MI) analysis reveals gray matter volume (GMV) and cerebrospinal fluid (CSF) volume as pivotal in computing individuals' brain age.

Key points: Mutual information (MI) interprets estimated brain age with morphometric features. Gray matter volume in the pre-central gyrus has the highest MI value for estimated brain age. Cerebrospinal fluid volume in the cingulate has the highest MI value. Regarding brain parenchymal volume, the superior frontal gyrus has the highest MI value. The value of mutual information underscores the key brain regions related to brain age.

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利用互信息解码磁共振成像显示的大脑年龄

目的：我们旨在开发一种标准化方法，用于研究估计脑年龄与区域形态特征之间的关系：我们旨在开发一种标准化方法来研究估计脑年龄与区域形态特征之间的关系，该方法应符合简便性、通用性和直观可解释性的标准：我们利用剑桥老龄化与神经科学中心项目（N = 609）的 T1 加权磁共振成像（MRI）数据，采用支持向量回归法训练脑年龄模型。预先训练好的脑年龄模型被应用于大脑发育项目的数据集（N = 547）。使用Kraskov（KSG）估计器计算脑年龄与灰质体积（GMV）、白质体积（WMV）、脑脊液体积（CSF）和皮质厚度（CT）等区域形态特征之间的互信息（MI）值：在四种大脑特征中，灰质体积的 MI 值最高（8.71），在中央前回达到峰值（0.69）。脑脊液体积排名第二（7.76），扣带回的 MI 值最高（0.87）。CT 排名第三（6.22），颞上回的 MI 值最高（0.53）。WMV的MI值最低（4.59），岛叶的MI值最高（0.53）。就大脑实质而言，额上回的体积显示出最高的 MI 值（0.80）：这是首次证明估计脑年龄与形态特征之间的 MI 值可作为评估区域对估计脑年龄贡献的基准。我们的研究结果突出表明，GMV 和 CSF 是决定估计脑年龄的关键特征，这可能会增加现有脑年龄计算模型的价值：互信息（MI）分析揭示了灰质体积（GMV）和脑脊液（CSF）体积在计算个人脑年龄中的关键作用：要点：互信息（MI）通过形态特征来解释估计的脑年龄。中央前回的灰质体积对估计脑年龄的互信息值最高。扣带回的脑脊液体积具有最高的 MI 值。在脑实质体积方面，额上回的 MI 值最高。互信息值强调了与脑年龄相关的关键脑区。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Insights into Imaging Medicine-Radiology, Nuclear Medicine and Imaging

CiteScore

7.30

自引率

4.30%

发文量

182

审稿时长

13 weeks

期刊介绍： Insights into Imaging (I³) is a peer-reviewed open access journal published under the brand SpringerOpen. All content published in the journal is freely available online to anyone, anywhere! I³ continuously updates scientific knowledge and progress in best-practice standards in radiology through the publication of original articles and state-of-the-art reviews and opinions, along with recommendations and statements from the leading radiological societies in Europe. Founded by the European Society of Radiology (ESR), I³ creates a platform for educational material, guidelines and recommendations, and a forum for topics of controversy. A balanced combination of review articles, original papers, short communications from European radiological congresses and information on society matters makes I³ an indispensable source for current information in this field. I³ is owned by the ESR, however authors retain copyright to their article according to the Creative Commons Attribution License (see Copyright and License Agreement). All articles can be read, redistributed and reused for free, as long as the author of the original work is cited properly. The open access fees (article-processing charges) for this journal are kindly sponsored by ESR for all Members. The journal went open access in 2012, which means that all articles published since then are freely available online.