Affiliation:
1. Department of Scientific Research and Academic Cancer Hospital of China Medical University, Liaoning Cancer Hospital and Institute Shenyang China
2. Department of Biomedical Engineering China Medical University Shenyang China
3. Department of Radiology Cancer Hospital of China Medical University, Liaoning Cancer Hospital and Institute Shenyang China
4. Department of Radiology Shengjing Hospital of China Medical University Shenyang China
Abstract
BackgroundRadiomics has been applied for assessing lymphovascular invasion (LVI) in patients with breast cancer. However, associations between features from peritumoral regions and the LVI status were not investigated.PurposeTo investigate the value of intra‐ and peritumoral radiomics for assessing LVI, and to develop a nomogram to assist in making treatment decisions.Study TypeRetrospective.PopulationThree hundred and sixteen patients were enrolled from two centers and divided into training (N = 165), internal validation (N = 83), and external validation (N = 68) cohorts.Field Strength/Sequence1.5 T and 3.0 T/dynamic contrast‐enhanced (DCE) and diffusion‐weighted imaging (DWI).AssessmentRadiomics features were extracted and selected based on intra‐ and peritumoral breast regions in two magnetic resonance imaging (MRI) sequences to create the multiparametric MRI combined radiomics signature (RS‐DCE plus DWI). The clinical model was built with MRI‐axillary lymph nodes (MRI ALN), MRI‐reported peritumoral edema (MPE), and apparent diffusion coefficient (ADC). The nomogram was constructed with RS‐DCE plus DWI, MRI ALN, MPE, and ADC.Statistical TestsIntra‐ and interclass correlation coefficient analysis, Mann–Whitney U test, and least absolute shrinkage and selection operator regression were used for feature selection. Receiver operating characteristic and decision curve analyses were applied to compare performance of the RS‐DCE plus DWI, clinical model, and nomogram.ResultsA total of 10 features were found to be associated with LVI, 3 from intra‐ and 7 from peritumoral areas. The nomogram showed good performance in the training (AUCs, nomogram vs. clinical model vs. RS‐DCE plus DWI, 0.884 vs. 0.695 vs. 0.870), internal validation (AUCs, nomogram vs. clinical model vs. RS‐DCE plus DWI, 0.813 vs. 0.695 vs. 0.794), and external validation (AUCs, nomogram vs. clinical model vs. RS‐DCE plus DWI, 0.862 vs. 0.601 vs. 0.849) cohorts.Data ConclusionThe constructed preoperative nomogram might effectively assess LVI.Level of Evidence3Technical EfficacyStage 2
Funder
Natural Science Foundation of Liaoning Province
Subject
Radiology, Nuclear Medicine and imaging