Abstract 4035
Background
Breast cancer is one of the most common malignant disease for women. Mammography is the preferred method for breast cancer detection. The purpose is to investigate the feasibility and accuracy of texture features extracted from digital mammograms at predicting benign and malignant breast mass using Radiomics.
Methods
494 digital mammograms data who diagnosed as breast masses (Benign: 251 Malignant: 243) by mammography were enrolled. Enrol criteria: breast masses classified as BI-RADS 3, 4, and 5 and at last confirmed by histopathology. Lesion area was marked with a rectangular frame on the Cranio-Caudal (CC) and MedioLateral Oblique (MLO) images at the 5M workstation. The rectangular regions of interest (ROI) was segmented and 456 radiomics features were extracted from every ROI. Extracted features were dimensioned by Maximum Relevance Minimum Redundancy (MRMR) and Lasso algorithm. Post-dimension features were classified using Support Vector Machine (SVM). 70% of the data as a training set and the other 30% as a testing set. The reliability of the Classifier was evaluated by the 10-fold cross-validation. The classification accuracy was evaluated by the accuracy and sensitivity and AUC.
Results
Both the MRMR and Lasso screened 30 radiomics features respectively. 10-fold cross-validation showed that their accuracy were 88.70% and 86.71%, respectively. In testing sets, Through the MRMR algorithm, the classifier achieves an accuracy of 92.00% and a sensitivity of 91.10% and AUC of 95.10%. Through the lasso dimension reduction algorithm, the classifier achieves an accuracy of 83.26% and a sensitivity of 75.90% and AUC of 89.38%.
Conclusions
Radiomics texture features from digital mammograms may be used for benign and malignant prediction. This method offer better accuracy and sensitivity. It is expected to provide an auxiliary diagnosis for the imaging doctors.
Clinical trial identification
Editorial acknowledgement
Legal entity responsible for the study
The authors.
Funding
Has not received any funding.
Disclosure
All authors have declared no conflicts of interest.
Resources from the same session
1908 - Androgen Receptor (AR) Aberrations in Patients (Pts) With Metastatic Castration-Sensitive Prostate Cancer (mCSPC) Treated With Apalutamide (APA) Plus Androgen Deprivation Therapy (ADT) in TITAN
Presenter: Kim Chi
Session: Poster Display session 3
Resources:
Abstract
4058 - 68Ga-PSMA guided bone biopsies for molecular diagnostics in metastatic castration resistant prostate cancer patients
Presenter: Anouk de Jong
Session: Poster Display session 3
Resources:
Abstract
2226 - Spatial-Temporal Change in Quantitative Total Bone Imaging (QTBI) and Circulating Tumor Cells (CTCs) in Metastatic Castration-Resistant Prostate Cancer (mCRPC) Treated With Enzalutamide (ENZA)
Presenter: Glenn Liu
Session: Poster Display session 3
Resources:
Abstract
5795 - Efficacy of Enzalutamide in Hormone-sensitive Metastatic Prostate Cancer: Clinical Utility of 18F-Choline PET and Whole Body MRI.
Presenter: Susanne Osanto
Session: Poster Display session 3
Resources:
Abstract
899 - Urine extracellular vesicle GATA2 mRNA alone and in a multigene test predicts initial prostate biopsy result
Presenter: Jungreem Woo
Session: Poster Display session 3
Resources:
Abstract
3094 - Circulating tumor cell (CTC) genomic landscape in neuroendocrine prostate cancer (NEPC) by single cell copy number analysis
Presenter: Vincenza Conteduca
Session: Poster Display session 3
Resources:
Abstract
2527 - Circulating Tumor Cells (CTC) count and Prostate-Specific Antigen (PSA) response measures in metastatic Castration-Resistant Prostate Cancer (mCRPC) patients (pts) treated with Docetaxel (Doc)
Presenter: Rebeca Lozano Mejorada
Session: Poster Display session 3
Resources:
Abstract
6106 - Assessing the clinical relevance of drug–drug interactions (DDI) with darolutamide (DARO)
Presenter: Christian Zurth
Session: Poster Display session 3
Resources:
Abstract
2237 - KEYNOTE-921: phase 3 study of pembrolizumab (pembro) plus docetaxel and prednisone for enzalutamide (enza)- or abiraterone (abi)-pretreated patients (pts) with metastatic castration-resistant prostate cancer (mCRPC).
Presenter: Daniel Petrylak
Session: Poster Display session 3
Resources:
Abstract
2241 - KEYNOTE-641: Phase 3 Study of Pembrolizumab (pembro) Plus Enzalutamide for Metastatic Castration-Resistant Prostate Cancer (mCRPC)
Presenter: Julie Graff
Session: Poster Display session 3
Resources:
Abstract