红外光谱可区分软骨损伤模型:对软骨完整性评估的启示

IF 3 2区 医学 Q3 ENGINEERING, BIOMEDICAL
Fatemeh Shahini, Soroush Oskouei, Ervin Nippolainen, Ali Mohammadi, Jaakko K. Sarin, Nikae C. R. te Moller, Harold Brommer, Rubina Shaikh, Rami K. Korhonen, P. René van Weeren, Juha Töyräs, Isaac O. Afara
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引用次数: 0

摘要

为了提高临床诊断鉴别不同来源的关节软骨损伤的能力,本研究探讨了中红外(MIR)光谱在检测两种损伤类型导致的关节软骨结构、成分和功能变化方面的灵敏度。研究人员使用钝器和锐器在九头健康的成年雌性设得兰小马(年龄 = 6.8 ± 2.6 岁;4-13 岁之间)的第三腕骨桡侧(腕中关节)和中间腕骨(桡腕关节)的交感神经上通过关节切开术开了三条沟(两条平行于掌背方向,一条平行于内外侧方向)。缺陷被随机分配到两个关节中的每一个。小马经过3周的箱式休息,然后进行8周的跑步机训练和26周的自由牧场运动,最后安乐死以收集骨软骨样本。骨软骨样本经过生物力学压痕测试,然后进行近红外光谱评估。随后进行数字密度测定,以估算组织中的蛋白多糖(PG)含量。随后,开发了机器学习模型对样本进行分类,以便根据近红外光谱按损伤类型估算样本的生物力学特性和蛋白多糖含量。结果表明,近红外光谱能够区分健康和受伤的 AC(91%)以及不同类型的损伤(88%)。该方法还能以相对较低的误差(厚度 = 12.7% mm,平衡模量 = 10.7% MPa,瞬时模量 = 11.8% MPa)估算出 AC 的属性。这些研究结果证明了近红外光谱法作为一种评估因损伤导致的 AC 完整性变化的工具的潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Infrared Spectroscopy Can Differentiate Between Cartilage Injury Models: Implication for Assessment of Cartilage Integrity

Infrared Spectroscopy Can Differentiate Between Cartilage Injury Models: Implication for Assessment of Cartilage Integrity

In order to improve the ability of clinical diagnosis to differentiate articular cartilage (AC) injury of different origins, this study explores the sensitivity of mid-infrared (MIR) spectroscopy for detecting structural, compositional, and functional changes in AC resulting from two injury types. Three grooves (two in parallel in the palmar-dorsal direction and one in the mediolateral direction) were made via arthrotomy in the AC of the radial facet of the third carpal bone (middle carpal joint) and of the intermediate carpal bone (the radiocarpal joint) of nine healthy adult female Shetland ponies (age = 6.8 ± 2.6 years; range 4–13 years) using blunt and sharp tools. The defects were randomly assigned to each of the two joints. Ponies underwent a 3-week box rest followed by 8 weeks of treadmill training and 26 weeks of free pasture exercise before being euthanized for osteochondral sample collection. The osteochondral samples underwent biomechanical indentation testing, followed by MIR spectroscopic assessment. Digital densitometry was conducted afterward to estimate the tissue's proteoglycan (PG) content. Subsequently, machine learning models were developed to classify the samples to estimate their biomechanical properties and PG content based on the MIR spectra according to injury type. Results show that MIR is able to discriminate healthy from injured AC (91%) and between injury types (88%). The method can also estimate AC properties with relatively low error (thickness = 12.7% mm, equilibrium modulus = 10.7% MPa, instantaneous modulus = 11.8% MPa). These findings demonstrate the potential of MIR spectroscopy as a tool for assessment of AC integrity changes that result from injury.

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来源期刊
Annals of Biomedical Engineering
Annals of Biomedical Engineering 工程技术-工程:生物医学
CiteScore
7.50
自引率
15.80%
发文量
212
审稿时长
3 months
期刊介绍: Annals of Biomedical Engineering is an official journal of the Biomedical Engineering Society, publishing original articles in the major fields of bioengineering and biomedical engineering. The Annals is an interdisciplinary and international journal with the aim to highlight integrated approaches to the solutions of biological and biomedical problems.
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