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
4543 - Long-term real-world (RW) outcomes in patients with advanced melanoma (MEL) treated with ipilimumab (IPI) and non-IPI therapies: IMAGE study
Presenter: Stéphane Dalle
Session: Poster Display session 3
Resources:
Abstract
4523 - Prognostic Factors for efficacy of Ipilimumab used after AntiPD1 and/or BRAF+MEK inhibitors in Melanoma Patients: an Italian Melanoma Intergroup study
Presenter: Riccardo Marconcini
Session: Poster Display session 3
Resources:
Abstract
3632 - Rechallenge with combination ipilimumab and anti-PD-1 (IPI+PD1) in metastatic melanoma after acquired resistance to IPI+PD1 immunotherapy
Presenter: Adriana Hepner
Session: Poster Display session 3
Resources:
Abstract
3732 - Clinicopathologic characteristics of immune colitis in melanoma patients treated with combination ipilimumab and anti-PD1 (IPI+PD1) and PD1 monotherapy.
Presenter: Kazi Nahar
Session: Poster Display session 3
Resources:
Abstract
5005 - Real-world outcomes of ipilimumab plus nivolumab for advanced melanoma in the Netherlands
Presenter: Michiel van Zeijl
Session: Poster Display session 3
Resources:
Abstract
5524 - Utilization of Real-World Data to Assess the Effectiveness of Immune Checkpoint Inhibitors (ICIs) in Elderly Patients with Metastatic Melanoma
Presenter: D Scott Ernst
Session: Poster Display session 3
Resources:
Abstract
5884 - Tumor mutational burden and response to PD-1 inhibitors: an analysis of 89 cases of metastatic melanoma.
Presenter: Léa Dousset
Session: Poster Display session 3
Resources:
Abstract
3120 - Increase in S100B and LDH as early outcome predictors for non-responsiveness to anti-PD-1 monotherapy in advanced melanoma.
Presenter: Elisa Rozeman
Session: Poster Display session 3
Resources:
Abstract
2157 - Immune status defined by molecular information layers predicts response to pembrolizumab treatment in advanced melanoma
Presenter: Guillermo Prado-Vázquez
Session: Poster Display session 3
Resources:
Abstract
2553 - Interim analysis of a phase Ib study of cobimetinib plus atezolizumab in patients with advanced BRAFV600 wild type melanoma progressing on prior anti-PD-L1 therapy
Presenter: Shahneen Sandhu
Session: Poster Display session 3
Resources:
Abstract