Mammography in 2022, from Computer-Aided Detection to Artificial Intelligence Applications

• Main Authors: Filippo Pesapane (Author), Chiara Trentin (Author), Marta Montesano (Author), Federica Ferrari (Author), Luca Nicosia (Author), Anna Rotili (Author), Silvia Penco (Author), Mariagiorgia Farina (Author), Irene Marinucci (Author), Francesca Abbate (Author), Lorenza Meneghetti (Author), Anna Bozzini (Author), Antuono Latronico (Author), Alessandro Liguori (Author), Giuseppe Carrafiello (Author), Enrico Cassano (Author)
• Format: Book
• Published: IMR Press, 2022-10-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.
• Notes: 0390-6663; 10.31083/j.ceog4911237
• Keywords: breast imaging; artificial intelligence; mammography; Gynecology and obstetrics; RG1-991
• Source: Clinical and Experimental Obstetrics & Gynecology, Vol 49, Iss 11, p 237 (2022)

Objective: During the last decades, advances in computing power, structured data, and algorithm development, developed a technology based on Artificial intelligence (AI) which is currently applied in medicine. Nowadays, the main use of AI in breast imaging is in decision support in mammography, where it facilitates human decision-making as opposed to replacing radiologists. In this paper, we analyze how AI is currently involved in radiological decision-making and how will change both interpretation efficacy and workflow efficiency in breast imaging. Mechanism: We performed a non-systematic review on Pubmed and Scopus and Web of Science electronic databases from January 2001 to January 2022, using the following keywords: artificial intelligence, machine and deep learning, breast imaging and mammography. Findings in Brief: Many retrospective studies showed that AI can match or even enhance performances of radiologists in mammography interpretation. However, to assess the real role of AI in clinical practice compelling evidence from accurate perspective studies in large cohorts is needed. Breast imaging must face with the exponential growth in imaging requests (and consequently higher costs) and a predicted reduced number of trained radiologists to read imaging and provide reports. To mitigate these urges, solution is being sought with increasing investments in the application of AI to improve the radiology workflow efficiency as well as patient outcomes. Conslusions: This paper show the background on the evolution and the application of AI in breast imaging in 2022, in addition to exploring advantages and limitations of this innovative technology, as well as ethical and legal issues that have been identified so far.