Resistant inflammatory breast lesions: can AI exclude malignancy?

Autor: Safaa Ibrahim Saif El-nasr, Norhan Mohamed Samy ElSayed, Eman Badawy, Sherif Nasser Taha, Rania Mohamed A. Hegazy
Jazyk: angličtina
Rok vydání: 2024
Předmět:
Zdroj: The Egyptian Journal of Radiology and Nuclear Medicine, Vol 55, Iss 1, Pp 1-11 (2024)
Druh dokumentu: article
ISSN: 2090-4762
DOI: 10.1186/s43055-024-01370-4
Popis: Abstract Background Numerous underlying causes can lead to inflammatory breast disorders. A wide range of non-specific symptoms may be presenting symptoms, which could cause a delay in diagnosis and thus improper therapy. Studies on artificial intelligence (AI) are rapidly developing and offer a wide range of possible uses in breast imaging. Artificial intelligence-based computer-assisted diagnosis (AI-CAD) holds promise in the field of mammography. It demonstrated diagnostic performances that are equivalent to or even better than those achieved by stand-alone methods. The current work aimed to identify whether AI can improve the performance of mammography in diagnosing inflammatory breast diseases and excluding the underlying malignancy in cases resistant to treatment that may reduce the need for interventional procedures such as biopsy. Methods Our study was a retrograde one done on 34 patients with pathologically proven inflammatory breast lesions. Results Suppurative breast lesions gave high false positive results. This was also the case with granulomatous mastitis; while simple inflammatory lesions gave true negative results on AI interrogation. Conclusions Artificial intelligence can be of great value in diagnosing simple inflammatory breast lesions thus following up on such lesions can usually be sufficient without asking for unneeded biopsies. On the other hand, our study showed that AI had high false positive results in suppurative lesions and granulomatous mastitis. Consequently, ultrasonography can be more reliable in their diagnosis.
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