Suppr超能文献

基于MRI的影像组学列线图用于眼眶附件淋巴瘤与特发性眼眶炎症的术前鉴别诊断

MRI-Based Radiomics Nomogram for Preoperative Differentiation Between Ocular Adnexal Lymphoma and Idiopathic Orbital Inflammation.

作者信息

Yang Lijuan, Zhang Huachen, Xie Xiaoyang, Jiang Shijie, Zhang Hui, Cao Xin, Hou Yuqing, He Xiaowei, Wang Junming, Zhang Tao, Zhao Fengjun

机构信息

Department of Radiology, Xi'an People's Hospital (Xi'an Fourth Hospital), Xi'an, Shaanxi, China.

Xi'an Key Lab of Radiomics and Intelligent Perception, School of Information Science and Technology, Northwest University, Xi'an, Shaanxi, China.

出版信息

J Magn Reson Imaging. 2023 May;57(5):1594-1604. doi: 10.1002/jmri.28404. Epub 2022 Aug 20.

Abstract

BACKGROUND

Ocular adnexal lymphoma (OAL) and idiopathic orbital inflammation (IOI) are malignant and benign lesions for which radiotherapy and corticosteroids are indicated, but similar clinical manifestations make their differentiation difficult.

PURPOSE

To develop and validate an MRI-based radiomics nomogram for individual diagnosis of OAL vs. IOI.

STUDY TYPE

Retrospective.

POPULATION

A total of 103 patients (46.6% female) with mean age of 56.4 ± 16.3 years having OAL (n = 58) or IOI (n = 45) were divided into an independent training (n = 82) and a testing dataset (n = 21).

FIELD STRENGTH/SEQUENCE: A 3-T, precontrast T1-weighted imaging (T1WI), T2-weighted imaging (T2WI), and postcontrast T1WI (T1 + C).

ASSESSMENT

Radiomics features were extracted and selected from segmented tumors and peritumoral regions in MRI before-and-after filtering. These features, alone or combined with clinical characteristics, were used to construct a radiomics or joint signature to differentiate OAL from IOI, respectively. A joint nomogram was built to show the impact of the radiomics signature and clinical characteristics on individual risk of developing OAL.

STATISTICAL TESTS

Area under the curve (AUC) and accuracy (ACC) were used for performance evaluation. Mann-Whitney U and Chi-square tests were used to analyze continuous and categorical variables. Decision curve analysis, kappa statistics, DeLong and Hosmer-Lemeshow tests were also conducted. P < 0.05 was considered statistically significant.

RESULTS

The joint signature achieved an AUC of 0.833 (95% confidence interval [CI]: 0.806-0.870), slightly better than the radiomics signature with an AUC of 0.806 (95% CI: 0.767-0.838) (P = 0.778). The joint and radiomics signatures were comparable to experienced radiologists referencing to clinical characteristics (ACC = 0.810 vs. 0.796-0.806, P > 0.05) or not (AUC = 0.806 vs. 0.753-0.791, P > 0.05), respectively. The joint nomogram gained more net benefits than the radiomics nomogram, despite both showing good calibration and discriminatory efficiency (P > 0.05).

DATA CONCLUSION

The developed radiomics-based analysis might help to improve the diagnostic performance and reveal the association between radiomics features and individual risk of developing OAL.

EVIDENCE LEVEL

3 TECHNICAL EFFICACY: 3.

摘要

背景

眼附属器淋巴瘤(OAL)和特发性眼眶炎症(IOI)分别为恶性和良性病变,放疗和皮质类固醇激素是针对这两种疾病的治疗手段,但二者相似的临床表现使其鉴别诊断存在困难。

目的

开发并验证一种基于MRI的影像组学列线图,用于OAL与IOI的个体诊断。

研究类型

回顾性研究。

研究对象

共纳入103例患者(女性占46.6%),平均年龄56.4±16.3岁,其中OAL患者58例,IOI患者45例。这些患者被分为独立的训练数据集(n=82)和测试数据集(n=21)。

场强/序列:3-T,平扫T1加权成像(T1WI)、T2加权成像(T2WI)及增强后T1WI(T1+C)。

评估

在MRI图像上对肿瘤及瘤周区域进行分割,经滤波前后提取并选择影像组学特征。这些特征单独或联合临床特征,分别构建影像组学或联合特征用于区分OAL和IOI。构建联合列线图以显示影像组学特征和临床特征对个体发生OAL风险的影响。

统计学检验

采用曲线下面积(AUC)和准确率(ACC)进行性能评估。采用Mann-Whitney U检验和卡方检验分析连续变量和分类变量。还进行决策曲线分析、kappa统计、DeLong检验和Hosmer-Lemeshow检验。P<0.05认为具有统计学意义。

结果

联合特征的AUC为0.833(95%置信区间[CI]:0.806-0.870),略优于影像组学特征的AUC(0.806,95%CI:0.767-0.838)(P=0.778)。联合特征和影像组学特征在参考临床特征(ACC=0.810 vs. 0.796-0.806,P>0.05)或不参考临床特征(AUC=0.806 vs. 0.753-0.791,P>0.05)时,与经验丰富放射科医生的诊断效能相当。联合列线图比影像组学列线图获得了更多的净效益,尽管二者均显示出良好的校准度和鉴别效能(P>0.05)。

数据结论

所开发的基于影像组学的分析方法可能有助于提高诊断性能,并揭示影像组学特征与个体发生OAL风险之间的关联。

证据水平

3级 技术效能:3级

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验