CT-based radiomics for predicting lymph node metastasis in esophageal cancer: a systematic review and meta-analysis
ObjectiveWe 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).MethodsThe present study conducted a comprehensive search by accessing the following databases: PubMed,...
| Main Authors: | , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2024-03-01
|
| Series: | Frontiers in Oncology |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fonc.2024.1267596/full |
| _version_ | 1827312176840310784 |
|---|---|
| author | Liangsen Liu Liangsen Liu Hai Liao Yang Zhao Jiayu Yin Jiayu Yin Chen Wang Lixia Duan Peihan Xie Wupeng Wei Meihai Xu Danke Su |
| author_facet | Liangsen Liu Liangsen Liu Hai Liao Yang Zhao Jiayu Yin Jiayu Yin Chen Wang Lixia Duan Peihan Xie Wupeng Wei Meihai Xu Danke Su |
| author_sort | Liangsen Liu |
| collection | DOAJ |
| description | ObjectiveWe 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).MethodsThe 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).ResultsThe 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.ConclusionThe 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 RegistrationOpen Science Framework platform at https://osf.io/5zcnd. |
| first_indexed | 2024-04-24T21:38:34Z |
| format | Article |
| id | doaj.art-a4494dad276b496fb124744e4e44000d |
| institution | Directory Open Access Journal |
| issn | 2234-943X |
| language | English |
| last_indexed | 2024-04-24T21:38:34Z |
| publishDate | 2024-03-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Oncology |
| spelling | doaj.art-a4494dad276b496fb124744e4e44000d2024-03-21T13:30:15ZengFrontiers Media S.A.Frontiers in Oncology2234-943X2024-03-011410.3389/fonc.2024.12675961267596CT-based radiomics for predicting lymph node metastasis in esophageal cancer: a systematic review and meta-analysisLiangsen Liu0Liangsen Liu1Hai Liao2Yang Zhao3Jiayu Yin4Jiayu Yin5Chen Wang6Lixia Duan7Peihan Xie8Wupeng Wei9Meihai Xu10Danke Su11Department of Medical Imaging Center, Guangxi Medical University Cancer Hospital, Nanning, ChinaDepartment of Nuclear Medicine, The Fifth Affiliated Hospital of Guangxi Medical University, Nanning, ChinaDepartment of Medical Imaging Center, Guangxi Medical University Cancer Hospital, Nanning, ChinaDepartment of Medical Imaging Center, Guangxi Medical University Cancer Hospital, Nanning, ChinaDepartment of Medical Imaging Center, Guangxi Medical University Cancer Hospital, Nanning, ChinaDepartment of Radiology, The Fifth Affiliated Hospital of Guangxi Medical University, Nanning, ChinaDepartment of Medical Imaging Center, Guangxi Medical University Cancer Hospital, Nanning, ChinaDepartment of Medical Imaging Center, Guangxi Medical University Cancer Hospital, Nanning, ChinaDepartment of Medical Imaging Center, Guangxi Medical University Cancer Hospital, Nanning, ChinaDepartment of Radiology, The Second Affiliated Hospital of Guangxi Medical University, Nanning, ChinaDepartment of Radiology, The Fifth Affiliated Hospital of Guangxi Medical University, Nanning, ChinaDepartment of Medical Imaging Center, Guangxi Medical University Cancer Hospital, Nanning, ChinaObjectiveWe 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).MethodsThe 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).ResultsThe 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.ConclusionThe 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 RegistrationOpen Science Framework platform at https://osf.io/5zcnd.https://www.frontiersin.org/articles/10.3389/fonc.2024.1267596/fullesophageal cancerlymph node metastasiscomputerized tomographyradiomicsdiagnosismeta-analysis |
| spellingShingle | Liangsen Liu Liangsen Liu Hai Liao Yang Zhao Jiayu Yin Jiayu Yin Chen Wang Lixia Duan Peihan Xie Wupeng Wei Meihai Xu Danke Su CT-based radiomics for predicting lymph node metastasis in esophageal cancer: a systematic review and meta-analysis Frontiers in Oncology esophageal cancer lymph node metastasis computerized tomography radiomics diagnosis meta-analysis |
| title | CT-based radiomics for predicting lymph node metastasis in esophageal cancer: a systematic review and meta-analysis |
| title_full | CT-based radiomics for predicting lymph node metastasis in esophageal cancer: a systematic review and meta-analysis |
| title_fullStr | CT-based radiomics for predicting lymph node metastasis in esophageal cancer: a systematic review and meta-analysis |
| title_full_unstemmed | CT-based radiomics for predicting lymph node metastasis in esophageal cancer: a systematic review and meta-analysis |
| title_short | CT-based radiomics for predicting lymph node metastasis in esophageal cancer: a systematic review and meta-analysis |
| title_sort | ct based radiomics for predicting lymph node metastasis in esophageal cancer a systematic review and meta analysis |
| topic | esophageal cancer lymph node metastasis computerized tomography radiomics diagnosis meta-analysis |
| url | https://www.frontiersin.org/articles/10.3389/fonc.2024.1267596/full |
| work_keys_str_mv | AT liangsenliu ctbasedradiomicsforpredictinglymphnodemetastasisinesophagealcancerasystematicreviewandmetaanalysis AT liangsenliu ctbasedradiomicsforpredictinglymphnodemetastasisinesophagealcancerasystematicreviewandmetaanalysis AT hailiao ctbasedradiomicsforpredictinglymphnodemetastasisinesophagealcancerasystematicreviewandmetaanalysis AT yangzhao ctbasedradiomicsforpredictinglymphnodemetastasisinesophagealcancerasystematicreviewandmetaanalysis AT jiayuyin ctbasedradiomicsforpredictinglymphnodemetastasisinesophagealcancerasystematicreviewandmetaanalysis AT jiayuyin ctbasedradiomicsforpredictinglymphnodemetastasisinesophagealcancerasystematicreviewandmetaanalysis AT chenwang ctbasedradiomicsforpredictinglymphnodemetastasisinesophagealcancerasystematicreviewandmetaanalysis AT lixiaduan ctbasedradiomicsforpredictinglymphnodemetastasisinesophagealcancerasystematicreviewandmetaanalysis AT peihanxie ctbasedradiomicsforpredictinglymphnodemetastasisinesophagealcancerasystematicreviewandmetaanalysis AT wupengwei ctbasedradiomicsforpredictinglymphnodemetastasisinesophagealcancerasystematicreviewandmetaanalysis AT meihaixu ctbasedradiomicsforpredictinglymphnodemetastasisinesophagealcancerasystematicreviewandmetaanalysis AT dankesu ctbasedradiomicsforpredictinglymphnodemetastasisinesophagealcancerasystematicreviewandmetaanalysis |