Advances Of AI In Cancer Breast: Review

Maged Naser, Mohamed M. Nasr, Lamia H. Shehata

Abstract


The breast imaging landscape has changed dramatically since the introduction of mammography in the 1960s, led by ultrasound and biopsies in the 1990s. The advent of magnetic resonance imaging (MRI) in the 2000s added valuable features to advanced imaging. Multimodal and multiparametric imaging have established a central role in breast radiology and the management of breast problems. The transition from conventional radiology to digital radiology occurred in the late 20th and early 21st centuries, enabling advanced techniques such as digital breast tomosynthesis, contrast-enhanced mammography, and the introduction of artificial intelligence (AI). AI integration within breast radiology can improve diagnostic and surgical procedures. It includes computer-aided design (CAD) algorithms, surgical procedure support algorithms, and data processing algorithms. The CAD system, developed since the 1980s, improves cancer detection rates by fighting benign and malignant tumors. The role of radiologists will become that of clinical experts working with AI for effective patient care and the use of advanced multiparametric indicators in radiology. Wearable technologies, non-contrast MRI, and new modalities such as photoacoustic imaging can improve diagnostic imaging. Image-guided treatments, including cryotherapy and theranostics, are gaining ground. Theranostics, which combines treatment and diagnosis, offers the potential for precision medicine. AI, new treatments , and Advanced imaging will revolutionize breast radiology, providing more refined diagnosis and personalized treatment. Personalized monitoring, AI services and image-guided therapy will shape the future of breast radiology.

Keywords


Cognitive Function, Breast Imaging, Diagnostic Procedures, Diagnosis, Treatment, Radiology, Intervention.

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References


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DOI: http://dx.doi.org/10.52155/ijpsat.v48.1.6777

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