The use of artificial intelligence (AI) is transforming care for breast cancer, which has the highest incidence rate and the second-highest mortality among all cancers. As such, early detection is a vital first step in breast cancer management, as routine screening tests increase the probability of successful treatment.
A report published in Cureus explored how AI can provide innovations in imaging, digital pathology, diagnosis, and treatment of breast cancer, along with shortcomings such as false negative results.
Early detection begins with mammograms. These—alongside other types of breast imaging scans—can notice even the most subtle abnormalities that can be difficult for human radiologists to pick up on, i.e., early-stage tumors or microcalcifications, according to the study. Another concern, the frequency of false-negative findings, which can occur when cancer is present but not necessarily diagnosed, can be lowered with the use of this technology. By regularly scanning radiographs for possible signs of cancer with the use of computer-aided detection (CAD) systems that automatically point to pathological spots on medical images, AI can improve the likelihood of detecting tumors in their early stages, according to the investigators.
When it comes to pathological diagnosis, digital pathology photographs of breast tissue slides can be efficiently reviewed by AI systems. They allow pathologists to diagnose cancer by recognizing anomalies, cellular structures, and malignant areas, taking the issue of human error out of the equation and allowing pathologists to utilize that time to accomplish other tasks.
Counting the number of mitotic figures that are in found in tissue samples, which the authors of the analysis consider to be an essential part of assessing breast cancer’s aggressiveness, can also be accomplished with AI.
As patients know, it’s standard practice for healthcare providers to ask for one’s medical history and any symptoms in order to help diagnose the issue. With AI, a person’s risk factors, including age, genetics, family history, and medical history, can be taken into account by AI models. In this case, software would explore genetic data, including BRCA1 and BRCA2 mutations, which can enable the development of screening and preventative programs. AI-driven risk assessment models could potentially suggest more frequent evaluation or further imaging for people that are at higher risk; this type of proactive approach can contribute to early diagnosis.
AI is also able to support the growth of efficient databases housing electronic medical records (EMRs) along with patient outcomes and treatment strategies. AI can identify trends and connections that can predict how new patients might respond to therapies; with current patients, by reviewing diagnostic images (MRI, CT, or PET scans), it is able to determine how a tumor’s shape, size, and density have evolved throughout the treatment process, which the authors said is a measuring stick to assess how well a tumor is responding to treatment.
However, for all of the positives presented by AI, there are also caveats. Being that it is powered by patient data, it is imperative to guard patient privacy by verifying that information security measures are laid out to protect against any data breaches. Patients will also need to give their consent for this data sharing. Transparency is key when thinking about the impact of AI on diagnosis, treatment, and data use, according to the study.
As a result, conclude the authors, “artificial intelligence has revolutionized breast cancer management by enhancing early detection, diagnostic precision, risk assessment, personalized treatments, and predictive analytics. These advancements have improved patient care, reduced treatment side effects, and fostered patient-centered decision-making.” Nonetheless, they write, “it is crucial to strike a balance between clinical autonomy and AI’s function. The final word in treatment selection should rest with clinicians, with AI acting as a useful guidance and assistance tool.”
Singh A, Paruthy SB, Belsariya V, Chandra J N, Singh SK, Manivasagam SS, Choudhary S, Kumar MA, Khera D, Kuraria V. Revolutionizing Breast Healthcare: Harnessing the Role of Artificial Intelligence. Cureus. 2023 Dec 8;15(12):e50203. doi: 10.7759/cureus.50203. PMID: 38192969; PMCID: PMC10772314.