Automated shape-independent assessment of the spatial distribution of proton density fat fraction in vertebral bone marrow

IF 2.4 4区医学 Q2 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING Zeitschrift fur Medizinische Physik Pub Date : 2024-08-01 DOI:10.1016/j.zemedi.2022.12.004

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Abstract

This work proposes a method for automatic standardized assessment of bone marrow volume and spatial distribution of the proton density fat fraction (PDFF) in vertebral bodies. Intra- and interindividual variability in size and shape of vertebral bodies is a challenge for comparable interindividual evaluation and monitoring of changes in the composition and distribution of bone marrow due to aging and/or intervention. Based on deep learning image segmentation, bone marrow PDFF of single vertebral bodies is mapped to a cylindrical template and corrected for the inclination with respect to the horizontal plane. The proposed technique was applied and tested in a cohort of 60 healthy (30 males, 30 females) individuals. Obtained bone marrow volumes and mean PDFF values are comparable to former manual and (semi-)automatic approaches. Moreover, the proposed method allows shape-independent characterization of the spatial PDFF distribution inside vertebral bodies.

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与形状无关的椎骨骨髓质子密度脂肪部分空间分布自动评估。

这项研究提出了一种自动标准化评估椎体中骨髓体积和质子密度脂肪分数（PDFF）空间分布的方法。椎体的大小和形状在个体内和个体间存在差异，这对可比的个体间评估和监测因老化和/或干预引起的骨髓组成和分布变化是一个挑战。基于深度学习图像分割，单个椎体的骨髓PDFF被映射到一个圆柱模板上，并校正了相对于水平面的倾斜度。所提出的技术在 60 名健康人（30 名男性，30 名女性）中进行了应用和测试。获得的骨髓体积和平均 PDFF 值与以前的手动和（半）自动方法相当。此外，所提出的方法还能不受形状影响地描述椎体内部的空间 PDFF 分布。

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来源期刊

Zeitschrift fur Medizinische Physik 医学-核医学

CiteScore

3.70

自引率

10.00%

发文量

审稿时长

65 days

期刊介绍： Zeitschrift fur Medizinische Physik (Journal of Medical Physics) is an official organ of the German and Austrian Society of Medical Physic and the Swiss Society of Radiobiology and Medical Physics.The Journal is a platform for basic research and practical applications of physical procedures in medical diagnostics and therapy. The articles are reviewed following international standards of peer reviewing. Focuses of the articles are: -Biophysical methods in radiation therapy and nuclear medicine -Dosimetry and radiation protection -Radiological diagnostics and quality assurance -Modern imaging techniques, such as computed tomography, magnetic resonance imaging, positron emission tomography -Ultrasonography diagnostics, application of laser and UV rays -Electronic processing of biosignals -Artificial intelligence and machine learning in medical physics In the Journal, the latest scientific insights find their expression in the form of original articles, reviews, technical communications, and information for the clinical practice.

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