评估用于快速准确测量人体成分的全自动计算机断层扫描图像分割方法。

IF 3.2 3区医学 Q2 NUTRITION & DIETETICS

Nutrition Pub Date : 2024-10-05 DOI:10.1016/j.nut.2024.112592

Michelle V. Dietz M.D., PhD , Karteek Popuri Ph.D. , Lars Janssen B.Sc. , Mushfiqus Salehin B.Sc. , Da Ma Ph.D. , Vincent Tze Yang Chow B.Sc. , Hyunwoo Lee Ph.D. , Cornelis Verhoef M.D., Ph.D. , Eva V.E. Madsen M.D., Ph.D. , Mirza F. Beg Ph.D. , Jeroen L.A. van Vugt M.D., Ph.D.

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引用次数: 0

摘要

介绍：身体成分评估可用于评估患者的营养状况，从而预测临床结果。为了方便临床实践中进行可靠、省时的身体成分测量，人们开发了全自动计算机断层扫描分割方法。本研究旨在评估数据分析辅助套件在独立数据集中的自动分割效果：2014年至2019年期间，对165名接受细胞减灭术和腹腔内热化疗的患者进行了术前计算机断层扫描图像。在第三腰椎处对骨骼肌质量（SMM）、内脏脂肪组织（VAT）、皮下脂肪组织（SAT）和肌肉内脂肪组织（IMAT）进行手动和自动测量。使用 Jaccard 指数和类内相关系数评估了自动测量的分割准确性：结果：与人工分析相比，自动分割提供了准确的测量结果，SMM 的 Jaccard 评分系数为 94.9，VAT 为 98.4，SAT 为 99.1，IMAT 为 79.4。类内相关系数从 0.98 到 1.00 不等。与人工分析相比，自动测量平均高估了 SMM 和 SAT 面积，平均差异（±2 个标准差）分别为 1.10（-1.91 至 4.11）和 1.61（-2.26 至 5.48）。对于 VAT 和 IMAT，自动测量平均低估了面积，平均差异分别为-1.24（-3.35 至 0.87）和-0.93（-5.20 至 3.35）：结论：市面上销售的数据分析辅助套件在第三腰椎水平的身体成分测量结果与人工测量结果相似。该软件可提供准确、省时的身体成分测量结果，这对于在临床实践中应用非常必要。

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Evaluation of a fully automated computed tomography image segmentation method for fast and accurate body composition measurements

Introduction

Body composition evaluation can be used to assess patients’ nutritional status to predict clinical outcomes. To facilitate reliable and time-efficient body composition measurements eligible for clinical practice, fully automated computed tomography segmentation methods were developed. The aim of this study was to evaluate automated segmentation by Data Analysis Facilitation Suite in an independent dataset.

Materials and methods

Preoperative computed tomography images were used of 165 patients undergoing cytoreductive surgery with hyperthermic intraperitoneal chemotherapy from 2014 to 2019. Manual and automated measurements of skeletal muscle mass (SMM), visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT), and intramuscular adipose tissue (IMAT) were performed at the third lumbar vertebra. Segmentation accuracy of automated measurements was assessed using the Jaccard index and intra-class correlation coefficients.

Results

Automatic segmentation provided accurate measurements compared to manual analysis, resulting in Jaccard score coefficients of 94.9 for SMM, 98.4 for VAT, 99.1 for SAT, and 79.4 for IMAT. Intra-class correlation coefficients ranged from 0.98 to 1.00. Automated measurements on average overestimated SMM and SAT areas compared to manual analysis, with mean differences (±2 standard deviations) of 1.10 (–1.91 to 4.11) and 1.61 (–2.26 to 5.48) respectively. For VAT and IMAT, automated measurements on average underestimated the areas with mean differences of –1.24 (–3.35 to 0.87) and –0.93 (–5.20 to 3.35), respectively.

Conclusions

Commercially available Data Analysis Facilitation Suite provides similar results compared to manual measurements of body composition at the level of third lumbar vertebra. This software provides accurate and time-efficient body composition measurements, which is necessary for implementation in clinical practice.

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来源期刊

Nutrition 医学-营养学

CiteScore

7.80

自引率

2.30%

发文量

300

审稿时长

60 days

期刊介绍： Nutrition has an open access mirror journal Nutrition: X, sharing the same aims and scope, editorial team, submission system and rigorous peer review. Founded by Michael M. Meguid in the early 1980''s, Nutrition presents advances in nutrition research and science, informs its readers on new and advancing technologies and data in clinical nutrition practice, encourages the application of outcomes research and meta-analyses to problems in patient-related nutrition; and seeks to help clarify and set the research, policy and practice agenda for nutrition science to enhance human well-being in the years ahead.