EXPLORING BREAST CANCER RESPONSE PREDICTION TO NEOADJUVANT SYSTEMIC THERAPY USING MRI-BASED RADIOMICS: A SYSTEMATIC REVIEW

Authors

  • Derajat Fauzan Nardian Faculty of Medicine, Sebelas Maret University, Indonesia Author

DOI:

https://doi.org/10.53555/nnmhs.v9i5.1666

Keywords:

Breast cancer, MRI-based radiomics, Neoadjuvant, Systemic therapy

Abstract

Breast cancer affects more than one out of every ten persons diagnosed with cancer each year, making it the most common type of cancer in women. It is the second most common cause of cancer-related death among females worldwide. The milk-producing glands are placed in front of the chest wall, according to breast anatomy. Breast cancer progression is almost often missed. The majority of people find out they have the illness through a normal test. Others may present with an unintentional breast lump, a change in the shape or size of their breasts, or a discharge from their nips. When compared to adjuvant chemotherapy, NST allows for in vivo tumor response, tumor size reduction (allowing for breast-conserving therapy where mastectomy was recommended), and pathologic complete response (pCR). Breast cancer tumor response to NST can be predicted using imaging modalities. Breast magnetic resonance imaging (MRI) is the most effective imaging modality for evaluating tumors and predicting response. Its precision in evaluating and forecasting tumor response to NST is insufficient to change clinical treatment. NST tumor response cannot be predicted using pretreatment MRI. As a result, breast MRI accuracy must be continuously enhanced. Despite large methodological heterogeneity in each step of the radiomics workflow, studies focusing on MRI-based radiomics for tumor response prediction to NST in breast cancer patients yielded promising results.

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Published

2023-05-08

How to Cite

Nardian, D. F. (2023). EXPLORING BREAST CANCER RESPONSE PREDICTION TO NEOADJUVANT SYSTEMIC THERAPY USING MRI-BASED RADIOMICS: A SYSTEMATIC REVIEW. Journal of Advanced Research in Medical and Health Science (ISSN 2208-2425), 9(5), 27-32. https://doi.org/10.53555/nnmhs.v9i5.1666

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