This study compares different methods for diagnosing breast cancer, focusing on their sensitivity, specificity, and clinical usefulness. Using the PICO framework, we reviewed key studies published from 2002 to 2024, sourced from databases like PubMed, Scopus, and Google Scholar. In total, we analysed 8 studies, covering a range of diagnostic techniques. These methods include traditional approaches like Core Needle Biopsy (CNB) and Fine Needle Aspiration (FNA), as well as more advanced methods such as Abbreviated MRI (ABB-MRI), image segmentation algorithms, Raman and infrared spectroscopy, blood-based proteomics, and cytometric testing. The findings showed that CNB had the highest diagnostic performance overall. However, ABB-MRI and some molecular techniques offered strong non-invasive alternatives. Computational tools, while promising, still need more validation for widespread use. In conclusion, no single diagnostic method stood out as the best for all cases. Instead, a combination of different approaches, tailored to each patient’s specific situation, seems to be the most accurate and efficient strategy for detecting breast cancer.

Breast cancer, diagnosis, sensitivity, specificity, core needle biopsy, MRI, spectroscopy, proteomics, image segmentation, SCM test.

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