Prediction of total and regional body composition from 3D body shape

IF 12.4 1区医学 Q1 HEALTH CARE SCIENCES & SERVICES

NPJ Digital Medicine Pub Date : 2024-10-23 DOI:10.1038/s41746-024-01289-0

Chexuan Qiao, Emanuella De Lucia Rolfe, Ethan Mak, Akash Sengupta, Richard Powell, Laura P. E. Watson, Steven B. Heymsfield, John A. Shepherd, Nicholas Wareham, Soren Brage, Roberto Cipolla

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Abstract

Accurate assessment of body composition is essential for evaluating the risk of chronic disease. 3D body shape, obtainable using smartphones, correlates strongly with body composition. We present a novel method that fits a 3D body mesh to a dual-energy X-ray absorptiometry (DXA) silhouette (emulating a single photograph) paired with anthropometric traits, and apply it to the multi-phase Fenland study comprising 12,435 adults. Using baseline data, we derive models predicting total and regional body composition metrics from these meshes. In Fenland follow-up data, all metrics were predicted with high correlations (r > 0.86). We also evaluate a smartphone app which reconstructs a 3D mesh from phone images to predict body composition metrics; this analysis also showed strong correlations (r > 0.84) for all metrics. The 3D body shape approach is a valid alternative to medical imaging that could offer accessible health parameters for monitoring the efficacy of lifestyle intervention programmes.

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根据三维体形预测身体总成分和区域成分

准确评估身体成分对评估慢性疾病风险至关重要。使用智能手机获得的三维体形与身体成分密切相关。我们提出了一种新方法，将三维人体网格与双能 X 射线吸收测量（DXA）轮廓（模拟单张照片）和人体测量特征相匹配，并将其应用于由 12,435 名成年人组成的多阶段芬兰研究。利用基线数据，我们从这些网格中推导出预测总体和区域身体成分指标的模型。在芬兰的后续数据中，所有指标的预测都具有很高的相关性（r > 0.86）。我们还对一款智能手机应用程序进行了评估，该应用程序可通过手机图像重建三维网格来预测身体成分指标；这项分析也显示所有指标都具有很强的相关性（r > 0.84）。三维体形方法是医学成像的有效替代方法，可以为监测生活方式干预计划的效果提供可获得的健康参数。

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来源期刊

NPJ Digital Medicine Multiple-

CiteScore

25.10

自引率

3.30%

发文量

170

审稿时长

15 weeks

期刊介绍： npj Digital Medicine is an online open-access journal that focuses on publishing peer-reviewed research in the field of digital medicine. The journal covers various aspects of digital medicine, including the application and implementation of digital and mobile technologies in clinical settings, virtual healthcare, and the use of artificial intelligence and informatics. The primary goal of the journal is to support innovation and the advancement of healthcare through the integration of new digital and mobile technologies. When determining if a manuscript is suitable for publication, the journal considers four important criteria: novelty, clinical relevance, scientific rigor, and digital innovation.