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MRI-based radiomics models for noninvasive evaluation of lymphovascular space invasion in cervical cancer: a systematic review and meta-analysis.
Zhang, H; Teng, C; Yao, Y; Bian, W; Chen, J; Liu, H; Wang, Z.
Afiliação
  • Zhang H; Department of Radiology, Jiaxing Maternity and Child Health Care Hospital, Jiaxing, Zhejiang 314000, China.
  • Teng C; Department of Radiology, Wenzhou Central Hospital, Wenzhou, Zhejiang 325000, China.
  • Yao Y; Department of Radiology, Jiaxing Maternity and Child Health Care Hospital, Jiaxing, Zhejiang 314000, China. Electronic address: hinadayao11@163.com.
  • Bian W; Department of Radiology, Jiaxing Maternity and Child Health Care Hospital, Jiaxing, Zhejiang 314000, China.
  • Chen J; Department of Radiology, Jiaxing Maternity and Child Health Care Hospital, Jiaxing, Zhejiang 314000, China.
  • Liu H; Department of Radiology, Jiaxing Maternity and Child Health Care Hospital, Jiaxing, Zhejiang 314000, China.
  • Wang Z; Department of Radiology, Jiaxing Maternity and Child Health Care Hospital, Jiaxing, Zhejiang 314000, China.
Clin Radiol ; 2024 Aug 07.
Article em En | MEDLINE | ID: mdl-39183137
ABSTRACT

AIM:

Aimed to evaluate the diagnostic performance of preoperative MRI-based radiomic models for noninvasive prediction of lymphovascular space invasion (LVSI) in patients with cervical cancer (CC). MATERIALS AND

METHODS:

A systematic search of the PubMed, Embase, Web of Science, and Cochrane databases was conducted up to December 21, 2023. The quality of the studies was assessed utilizing the Radiomics Quality Score (RQS) system and the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool. Pooled estimates of sensitivity, specificity, diagnostic odds ratio (DOR), and area under the curve (AUC) of the summary receiver operating characteristic curve (SROC) were computed. The clinical utility was evaluated using the Fagan nomogram. Heterogeneity was investigated and subgroup analyses were conducted.

RESULTS:

Eleven studies were included, with nine studies reporting independent validation sets. In the training sets, the pooled sensitivity, specificity, DOR, and AUC of SROC were 0.81 (95% CI 0.75-0.85), 0.78 (95% CI 0.73-0.83), 15 (95% CI 11-20), and 0.86 (95% CI 0.79-0.92), respectively. For the validation sets, the overall sensitivity, specificity, DOR, and AUC of SROC were 0.79 (95% CI 0.73-0.84), 0.73 (95% CI 0.67-0.78), 10 (95% CI 7-15), and 0.83 (95% CI 0.71-0.91), respectively. The Fagan nomogram indicated good clinical utility. Subgroup analysis revealed that multi-sequence MRI-based models exhibited superior diagnostic performance compared to single-sequence MRI-based models in validation sets.

CONCLUSION:

This meta-analysis highlights the potential diagnostic efficacy of MRI-based radiomic models for predicting LVSI in CC. Nevertheless, large-sample, multicenter studies are still warranted, and improvements in the standardization of radiomics methodology are necessary.

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Clin Radiol Ano de publicação: 2024 Tipo de documento: Article País de afiliação: China

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Clin Radiol Ano de publicação: 2024 Tipo de documento: Article País de afiliação: China