CT-based radiomics for predicting lymph node metastasis in esophageal cancer: a systematic review and meta-analysis

Liangsen Liu; Hai Liao; Yang Zhao; Jiayu Yin; Chen Wang; Lixia Duan; Peihan Xie; Wupeng Wei; Meihai Xu; Danke Su

doi:10.3389/fonc.2024.1267596

CT-based radiomics for predicting lymph node metastasis in esophageal cancer: a systematic review and meta-analysis

Front Oncol. 2024 Mar 19:14:1267596. doi: 10.3389/fonc.2024.1267596. eCollection 2024.

Authors

Liangsen Liu^{1

2}, Hai Liao¹, Yang Zhao¹, Jiayu Yin^{1

3}, Chen Wang¹, Lixia Duan¹, Peihan Xie¹, Wupeng Wei⁴, Meihai Xu³, Danke Su¹

Affiliations

¹ Department of Medical Imaging Center, Guangxi Medical University Cancer Hospital, Nanning, China.
² Department of Nuclear Medicine, The Fifth Affiliated Hospital of Guangxi Medical University, Nanning, China.
³ Department of Radiology, The Fifth Affiliated Hospital of Guangxi Medical University, Nanning, China.
⁴ Department of Radiology, The Second Affiliated Hospital of Guangxi Medical University, Nanning, China.

Abstract

Objective: We aimed to evaluate the diagnostic effectiveness of computed tomography (CT)-based radiomics for predicting lymph node metastasis (LNM) in patients diagnosed with esophageal cancer (EC).

Methods: The present study conducted a comprehensive search by accessing the following databases: PubMed, Embase, Cochrane Library, and Web of Science, with the aim of identifying relevant studies published until July 10th, 2023. The diagnostic accuracy was summarized using the pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and area under the curve (AUC). The researchers utilized Spearman's correlation coefficient for assessing the threshold effect, besides performing meta-regression and subgroup analysis for the exploration of possible heterogeneity sources. The quality assessment was conducted using the Quality Assessment of Diagnostic Accuracy Studies-2 and the Radiomics Quality Score (RQS).

Results: The meta-analysis included six studies conducted from 2018 to 2022, with 483 patients enrolled and LNM rates ranging from 27.2% to 59.4%. The pooled sensitivity, specificity, PLR, NLR, DOR, and AUC, along with their corresponding 95% CI, were 0.73 (0.67, 0.79), 0.76 (0.69, 0.83), 3.1 (2.3, 4.2), 0.35 (0.28, 0.44), 9 (6, 14), and 0.78 (0.74, 0.81), respectively. The results demonstrated the absence of significant heterogeneity in sensitivity, while significant heterogeneity was observed in specificity; no threshold effect was detected. The observed heterogeneity in the specificity was attributed to the sample size and CT-scan phases (P < 0.05). The included studies exhibited suboptimal quality, with RQS ranging from 14 to 16 out of 36. However, most of the enrolled studies exhibited a low-risk bias and minimal concerns relating to applicability.

Conclusion: The present meta-analysis indicated that CT-based radiomics demonstrated a favorable diagnostic performance in predicting LNM in EC. Nevertheless, additional high-quality, large-scale, and multicenter trials are warranted to corroborate these findings.

Systematic review registration: Open Science Framework platform at https://osf.io/5zcnd.

Keywords: computerized tomography; diagnosis; esophageal cancer; lymph node metastasis; meta-analysis; radiomics.

Publication types

Systematic Review

Grants and funding

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This research was supported by the Guangxi Clinical Research Center for Medical Imaging Construction (Grant No. Guike AD20238096), Guangxi Key Clinical Specialty (Medical Imaging Department), Dominant Cultivation Discipline of Guangxi Medical University Cancer Hospital (Medical Imaging Department), and self-financing research of the Health Department of Guangxi Autonomous Region (Grant No. Z-A20231142).