基于影像组学的甲状腺乳头状癌淋巴结转移诊断效能的系统评价与 Meta 分析。

Radiomics diagnostic performance in predicting lymph node metastasis of papillary thyroid carcinoma: A systematic review and meta-analysis.

机构信息

Faculty of Medicine, Tabriz University of Medical Sciences, Tabriz, Iran.

出版信息

Eur J Radiol. 2023 Nov;168:111129. doi: 10.1016/j.ejrad.2023.111129. Epub 2023 Sep 30.

DOI:10.1016/j.ejrad.2023.111129

PMID:37820522

Abstract

PURPOSE

To evaluate the diagnostic performance of radiomics in lymph node metastasis (LNM) prediction in patients with papillary thyroid carcinoma (PTC) through a systematic review and meta-analysis.

METHOD

A literature search of PubMed, EMBASE, and Web of Science was conducted to find relevant studies published until February 18th, 2023. Studies that reported the accuracy of radiomics in different imaging modalities for LNM prediction in PTC patients were selected. The methodological quality of included studies was evaluated by radiomics quality score (RQS) and quality assessment of diagnostic accuracy studies (QUADAS-2) tools. General characteristics and radiomics accuracy were extracted. Overall sensitivity, specificity, and area under the curve (AUC) were calculated for diagnostic accuracy evaluation. Spearman correlation coefficient and subgroup analysis were performed for heterogeneity exploration.

RESULTS

In total, 25 studies were included, of which 22 studies provided adequate data for meta-analysis. We conducted two types of meta-analysis: one focused solely on radiomics features models and the other combined radiomics and non-radiomics features models in the analysis. The pooled sensitivity, specificity, and AUC of radiomics and combined models were 0.75 [0.68, 0.80] vs. 0.77 [0.74, 0.80], 0.77 [0.74, 0.81] vs. 0.83 [0.78, 0.87] and 0.80 [0.73, 0.85] vs 0.82 [0.75, 0.88], respectively. The analysis showed a high heterogeneity level among the included studies. There was no threshold effect. The subgroup analysis demonstrated that utilizing ultrasonography, 2D segmentation, central and lateral LNM detection, automatic segmentation, and PyRadiomics software could slightly improve diagnostic accuracy.

CONCLUSIONS

Our meta-analysis shows that the radiomics has the potential for pre-operative LNM prediction in PTC patients. Although methodological quality is sufficient but we still need more prospective studies with larger sample sizes from different centers.

摘要

目的

通过系统评价和荟萃分析评估放射组学在预测甲状腺乳头状癌（PTC）患者淋巴结转移（LNM）中的诊断性能。

方法

对 PubMed、EMBASE 和 Web of Science 进行文献检索，以查找截至 2023 年 2 月 18 日发表的相关研究。选择报告不同成像方式中放射组学用于预测 PTC 患者 LNM 准确性的研究。使用放射组学质量评分（RQS）和诊断准确性研究质量评估工具（QUADAS-2）评估纳入研究的方法学质量。提取一般特征和放射组学准确性。计算诊断准确性评估的总敏感性、特异性和曲线下面积（AUC）。进行 Spearman 相关系数和亚组分析以探索异质性。

结果

共纳入 25 项研究，其中 22 项研究提供了足够的数据进行荟萃分析。我们进行了两种类型的荟萃分析：一种仅关注放射组学特征模型，另一种则在分析中结合了放射组学和非放射组学特征模型。放射组学和联合模型的汇总敏感性、特异性和 AUC 分别为 0.75[0.68，0.80]与 0.77[0.74，0.80]、0.77[0.74，0.81]与 0.83[0.78，0.87]和 0.80[0.73，0.85]与 0.82[0.75，0.88]。研究之间存在高度异质性。不存在阈值效应。亚组分析表明，使用超声、2D 分割、中央和侧方 LNM 检测、自动分割和 PyRadiomics 软件可以略微提高诊断准确性。