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特发性炎性肌病患者大腿肌肉定量 MRI 测量与组织病理学的相关性分析。

Correlation analysis of quantitative MRI measurements of thigh muscles with histopathology in patients with idiopathic inflammatory myopathy.

机构信息

Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.

Department of Neurology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.

出版信息

Eur Radiol Exp. 2023 Aug 17;7(1):51. doi: 10.1186/s41747-023-00350-z.

Abstract

OBJECTIVES

To validate the correlation between histopathological findings and quantitative magnetic resonance imaging (qMRI) fat fraction (FF) and water T2 mapping in patients with idiopathic inflammatory myopathy (IIM).

METHODS

The study included 13 patients with histopathologically confirmed IIM who underwent dedicated thigh qMRI scanning within 1 month before open muscle biopsy. For the biopsied muscles, FF derived from the iterative decomposition of water and fat with echo asymmetry and least-squares estimation quantitation (IDEAL-IQ) and T2 time from T2 mapping with chemical shift selective fat saturation were measured using a machine learning software. Individual histochemical and immunohistochemical slides were evaluated using a 5-point Likert score. Inter-reader agreement and the correlation between qMRI markers and histopathological scores were analyzed.

RESULTS

Readers showed good to perfect agreement in qMRI measurements and most histopathological scores. FF of the biopsied muscles was positively correlated with the amount of fat in histopathological slides (p = 0.031). Prolonged T2 time was associated with the degree of variation in myofiber size, inflammatory cell infiltration, and amount of connective tissues (p ≤ 0.008 for all).

CONCLUSIONS

Using the machine learning-based muscle segmentation method, a positive correlation was confirmed between qMRI biomarkers and histopathological findings of patients with IIM. This finding provides a basis for using qMRI as a non-invasive tool in the diagnostic workflow of IIM.

RELEVANCE STATEMENT

By using ML-based muscle segmentation, a correlation between qMRI biomarkers and histopathology was found in patients with IIM: qMRI is a potential non-invasive tool in this clinical setting.

KEY POINTS

• Quantitative magnetic resonance imaging measurements using machine learning-based muscle segmentation have good consistency and reproductivity. • Fat fraction of idiopathic inflammatory myopathy (IIM) correlated with the amount of fat at histopathology. • Prolonged T2 time was associated with muscle inflammation in IIM.

摘要

目的

验证特发性炎性肌病(IIM)患者的组织病理学发现与定量磁共振成像(qMRI)脂肪分数(FF)和水 T2 映射之间的相关性。

方法

该研究纳入了 13 名经组织病理学证实为 IIM 的患者,他们在开放肌肉活检前 1 个月内接受了专门的大腿 qMRI 扫描。对于活检肌肉,使用机器学习软件测量来自水和脂肪的迭代分解与回波不对称和最小二乘估计定量(IDEAL-IQ)的 FF 和 T2 时间从具有化学位移选择性脂肪饱和的 T2 映射。使用 5 分李克特评分评估个体组织化学和免疫组织化学幻灯片。分析 qMRI 标志物与组织病理学评分之间的读者间一致性和相关性。

结果

读者在 qMRI 测量和大多数组织病理学评分中表现出良好到极好的一致性。活检肌肉的 FF 与组织病理学切片中的脂肪量呈正相关(p = 0.031)。T2 时间延长与肌纤维大小变化程度、炎症细胞浸润和结缔组织量相关(p ≤ 0.008 均)。

结论

使用基于机器学习的肌肉分割方法,确认了 IIM 患者的 qMRI 生物标志物与组织病理学发现之间存在正相关。这一发现为将 qMRI 作为 IIM 诊断工作流程中的一种非侵入性工具提供了依据。

相关性陈述

通过使用基于机器学习的肌肉分割,在 IIM 患者中发现了 qMRI 生物标志物与组织病理学之间的相关性:qMRI 是这种临床情况下的一种潜在的非侵入性工具。

关键点

• 使用基于机器学习的肌肉分割的定量磁共振成像测量具有良好的一致性和可重复性。• IIM 的脂肪分数与组织病理学中的脂肪量相关。• T2 时间延长与 IIM 中的肌肉炎症相关。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/60be/10435435/9f258aa3d253/41747_2023_350_Fig1_HTML.jpg

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