Purpose

To evaluate the performance of texture-based biomarkers by radiomic analysis using magnetic resonance imaging (MRI) of patients with sacroiliitis secondary to spondyloarthritis (SpA). Relevance: The determination of sacroiliac joints inflammatory activity supports the drug management in these diseases.

Methods

Sacroiliac joints (SIJ) MRI examinations of 47 patients were evaluated. Thirty-seven patients had SpA diagnoses (27 axial SpA and ten peripheral SpA) which was established previously after clinical and laboratory follow-up. To perform the analysis, the SIJ MRI was first segmented and warped. Second, radiomics biomarkers were extracted from the warped MRI images for associative analysis with sacroiliitis and the SpA subtypes. Finally, statistical and machine learning methods were applied to assess the associations of the radiomics texture-based biomarkers with clinical outcomes.

Results

All diagnostic performances obtained with individual or combined biomarkers reached areas under the receiver operating characteristic curves ≥ 0.80 regarding SpA related sacroiliitis and and SpA subtypes classification. Radiomics texture-based analysis showed significant differences between the positive and negative SpA groups and differentiated the axial and peripheral subtypes (P < 0.001). In addition, the radiomics analysis was also able to correctly identify the disease even in the absence of active inflammation.

Conclusion

We concluded that the application of the radiomic approach constitutes a potential noninvasive tool to aid the diagnosis of sacroiliitis and for SpA subclassifications based on MRI of sacroiliac joints.

中文翻译：

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基于MRI的sa关节炎和脊椎关节炎的放射学生物标记物的研究。

目的

通过磁共振分析（MRI）对继发于脊椎关节炎（SpA）的cro关节炎患者进行放射分析，以评估基于纹理的生物标志物的性能。相关性：sa关节炎性活性的测定支持这些疾病中的药物管理。

方法

评估了47例关节（SIJ）MRI检查。三十七名患者进行了SpA诊断（27例轴向SpA和10例外周SpA），这是在临床和实验室随访之后确定的。为了进行分析，首先对SIJ MRI进行了分割和变形。其次，从变形的MRI图像中提取放射性标记物生物标志物，用于与sa关节炎和SpA亚型进行关联分析。最后，统计学和机器学习方法被应用于评估基于放射线纹理的生物标志物与临床结果的关联。

结果

关于SpA相关sa关节炎和SpA亚型分类，使用单个或组合生物标记物获得的所有诊断性能均达到接收器工作特性曲线下≥0.80的区域。放射学基于纹理的分析显示，正负SpA组之间存在显着差异，并且区分了轴向亚型和外周亚型（P  <0.001）。此外，即使在没有活动性炎症的情况下，放射学分析也能够正确识别疾病。

结论

我们得出的结论是，放射学方法的应用构成了一种潜在的非侵入性工具，可帮助the关节炎的诊断和基于sa关节MRI的SpA分类。