Book ChapterDOI
Radiomics Based Analysis of Breast Tumors in DCE-MRI due to Neoadjuvant Treatment Therapy
Priscilla Dinkar Moyya,Mythili Asaithambi,Anandh Kilpattu Ramaniharan +2 more
- pp 2197-2204
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TLDR
In this article, Radiomic analysis was performed on 20 studies of 10 patients using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) for early prediction of breast cancer.Abstract:
Breast cancer is the utmost frequent cancer amid women. The efficiency of cancer treatments on tumor development is carried out using a most sensitive method dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). Neoadjuvant chemotherapy (NAC) treatment is widely used in patients for early prediction of breast cancer. The development of extraction of high throughput of features is referred to radiomics. The purpose of this study is to determine the capability of radiomic features in the breast region respond to the treatment. Radiomic analysis was performed on 20 studies of 10 patients using DCE-MRI. A total of 94 three-dimensional radiomic features were extracted and examined statistically. Results explain that the five features 90 and 99 percentile of histogram intensity, mean 3D, variance 3D, and short-run emphasis are significant with p-value from 0.0025 to 0.0694. Hence, these radiomic features are potency to identify the ambivert changes in the breast region during the follow-ups.read more
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Journal ArticleDOI
Prediction of the Pathological Response to Neoadjuvant Chemotherapy in Breast Cancer Patients With MRI-Radiomics: A Systematic Review and Meta-analysis.
Filippo Pesapane,Giorgio Maria Agazzi,Anna Rotili,Federica Ferrari,A. Cardillo,Silvia Penco,Valeria Dominelli,O. D'ecclesiis,Silvano Vignati,Sara Raimondi,Anna Bozzini,Sara Pizzamiglio,Giuseppe Petralia,Luca Nicosia,Enrico Cassano +14 more
TL;DR: A systematic review and a meta-analysis of studies using MRI-radiomics for predicting the pathological complete response in breast cancer patients undergoing neoadjuvant therapy , and evaluated their methodological quality using the radiomics quality score (RQS) as mentioned in this paper .
References
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