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Differentiating T1a–T1b from T2 in gastric cancer lesions with three different measurement approaches based on contrast-enhanced T1W imaging at 3.0 T
- Source :
- BMC Medical Imaging, Vol 21, Iss 1, Pp 1-10 (2021)
- Publication Year :
- 2021
- Publisher :
- BMC, 2021.
-
Abstract
- Abstract Background To explore the diagnostic value of three different measurement approaches in differentiating T1a–T1b from T2 gastric cancer (GC) lesions. Methods A total of 95 consecutive patients with T1a–T2 stage of GC who performed preoperative MRI were retrospectively enrolled between January 2017 and November 2020. The parameters MRI T stage (subjective evaluation), thickness, maximum area and volume of the lesions were evaluated by two radiologists. Specific indicators including AUC, optimal cutoff, sensitivity, specificity, accuracy, positive likelihood ratio (PLR), negative likelihood ratio (NLR), positive predictive value (PPV) and negative predictive value (NPV) of MRI T stage, thickness, maximum area and volume for differentiating T1a–T1b from T2 stage lesions were calculated. The ROC curves were compared by the Delong test. Decision curve analysis (DCA) was used to evaluate the clinical benefit. Results The ROC curves for thickness (AUC = 0.926), maximum area (AUC = 0.902) and volume (AUC = 0.897) were all significantly better than those of the MRI T stage (AUC = 0.807) in differentiating T1a–T1b from T2 lesions, with p values of 0.004, 0.034 and 0.041, respectively. The values corresponding to the thickness (including AUC, sensitivity, specificity, accuracy, PPV, NPV, PLR and NLR) were all higher than those corresponding to the MRI T stage, maximum area and volume. The DCA curves indicated that the parameter thickness could provide the highest clinical benefit if the threshold probability was above 35%. Conclusions Thickness may provide an efficient approach to rapidly distinguish T1a–T1b from T2 stage GC lesions.
Details
- Language :
- English
- ISSN :
- 14712342
- Volume :
- 21
- Issue :
- 1
- Database :
- Directory of Open Access Journals
- Journal :
- BMC Medical Imaging
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.6fa3c5f3d604211b0398e40c15b574e
- Document Type :
- article
- Full Text :
- https://doi.org/10.1186/s12880-021-00672-7