Use of Pretreatment Multiparametric MRI to Predict Tumor Regression Pattern to Neoadjuvant Chemotherapy in Breast Cancer.
Acad Radiol
; 30 Suppl 2: S62-S70, 2023 09.
Article
en En
| MEDLINE
| ID: mdl-37019697
ABSTRACT
RATIONALE AND OBJECTIVES:
To develop an easy-to-use model by combining pretreatment MRI and clinicopathologic features for early prediction of tumor regression pattern to neoadjuvant chemotherapy (NAC) in breast cancer. MATERIALS ANDMETHODS:
We retrospectively analyzed 420 patients who received NAC and underwent definitive surgery in our hospital from February 2012 to August 2020. Pathologic findings of surgical specimens were used as the gold standard to classify tumor regression patterns into concentric and non-concentric shrinkage. Morphologic and kinetic MRI features were both analyzed. Univariable and multivariable analyses were performed to select the key clinicopathologic and MRI features for pretreatment prediction of regression pattern. Logistic regression and six machine learning methods were used to construct prediction models, and their performance were evaluated with receiver operating characteristic curve.RESULTS:
Two clinicopathologic variables and three MRI features were selected as independent predictors to construct prediction models. The apparent area under the curve (AUC) of seven prediction models were in the range of 0.669-0.740. The logistic regression model yielded an AUC of 0.708 (95% confidence interval [CI] 0.658-0.759), and the decision tree model achieved the highest AUC of 0.740 (95% CI 0.691-0.787). For internal validation, the optimism-corrected AUCs of seven models were in the range of 0.592-0.684. There was no significant difference between the AUCs of the logistic regression model and that of each machine learning model.CONCLUSION:
Prediction models combining pretreatment MRI and clinicopathologic features are useful for predicting tumor regression pattern in breast cancer, which can assist to select patients who can benefit from NAC for de-escalation of breast surgery and modify treatment strategy.Palabras clave
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Neoplasias de la Mama
/
Imágenes de Resonancia Magnética Multiparamétrica
Tipo de estudio:
Observational_studies
/
Prognostic_studies
/
Risk_factors_studies
Límite:
Female
/
Humans
Idioma:
En
Revista:
Acad Radiol
Asunto de la revista:
RADIOLOGIA
Año:
2023
Tipo del documento:
Article