Key Takeaways
- Artificial intelligence helps radiologists analyze medical images faster while improving efficiency and consistency.
- AI enhances, rather than replaces, the expertise of radiologists by serving as a clinical decision-support tool.
- Advanced algorithms can detect subtle abnormalities, track disease progression, and improve diagnostic accuracy.
- AI supports earlier intervention in conditions such as stroke, cancer, Alzheimer’s disease, and multiple sclerosis.
- As AI adoption grows, radiology is becoming more efficient, helping address increasing imaging demands and clinician shortages.
Damon Deteso, M.D., is a diagnostic radiologist who has practiced with Millennium Medical Imaging in Saratoga Springs, New York, since 2004. He brings extensive expertise across computed tomography, magnetic resonance imaging, ultrasound, X-ray, and nuclear medicine, and holds staff positions at five local hospitals, including Saratoga Hospital. Damon Deteso also spent three years as a medical advisor with Imagen Technologies and remains active in professional development through organizations such as the American Society of Head & Neck Radiology.
His clinical background makes him well positioned to discuss how artificial intelligence tools are transforming radiology – not by replacing radiologists, but by expanding their capacity to analyze scans faster, detect findings earlier, and deliver more consistent, accurate results.
In recent years, artificial intelligence (AI) has impacted virtually every industry, including modern medicine. Few medical fields have taken to the adoption of AI tools as readily as radiology. AI requires large sets of data to improve and refine operations, and radiology is the most data-rich subspecialty, making the two a natural fit. AI has already reduced workloads for radiologists and helped facilities mitigate the effects of the nationwide clinician shortage.
Medical imaging is a critically important segment of America’s healthcare industry, typically serving as the first step toward detecting and diagnosing a disease. Doctors use medical imaging technology to identify small tumors, document the first signs of Alzheimer’s disease, assess broken bones, and for many additional purposes. However, interpreting medical imaging scans is a time-consuming, technically challenging process.
Fortunately, advanced computer algorithms have enabled AI tools to help radiologists in several ways, resulting in more accurate and precise scan analysis at greater speeds. AI essentially functions as a radiology assistant capable of spotting extremely subtle changes in vital parts of the body, carefully measuring and tracking tumor growth, disease progression, and other bodily changes over time, as well as standardizing radiology reports.
Expediting scans is perhaps the greatest advantage offered by AI tools. In many cases, AI allows doctors to analyze imaging scans 75 percent faster, to say nothing of the improved image quality. Speed is particularly important when it comes to the time patients must spend in MRI machines, as roughly one-third of patients experience claustrophobia or severe anxiety while inside MRI scanners. Patients benefit from reduced stress and increased comfort, while radiologists enjoy enhanced image quality that translates to more accurate analyses.
While speed and patient comfort are important, nothing is more crucial than accurate results. AI tools not only improve the precision of scan results but assist medical professionals in prioritizing cases with critical findings and beginning the treatment process as soon as possible. For instance, AI tools can quickly identify a stroke on a CT scan and alert doctors immediately, resulting in timely intervention, less time spent in hospital for patients, and improved treatment outcomes.
AI tools have also helped healthcare professionals dealing with Alzheimer’s disease. The latest tools quantify brain changes associated with Alzheimer’s symptoms, from brain shrinkage to abnormal protein buildups. This allows medical teams to develop a patient-management plan early in the progress of the disease, which helps patients retain a higher quality of life.
When it comes to multiple sclerosis, AI improves doctors’ ability to identify and track the development of plaques that form on the brain over time, ultimately leading to this autoimmune disease. Radiologists can train AI to automatically measure the size of existing plaques and notify doctors in real time about the appearance of new plaques. As AI provides more information, doctors can adjust treatment accordingly.
Finally, AI tools have helped radiologists with cancer detection. For many cancers, early detection is critical to successful treatment and disease management. AI combines pattern recognition technology with a doctor’s clinical experience to identify cancer at the earliest possible stage, in addition to measuring tumors, aiding with biopsies, and gauging a patient’s response to treatment. It must be noted that AI serves to empower radiologists, not replace them. AI tools cannot be effective without the insight of a skilled and knowledgeable medical professional.
FAQs
How is AI being used in radiology today?
AI is used to assist radiologists with image analysis, detecting abnormalities, measuring disease progression, prioritizing urgent cases, and improving reporting consistency. These capabilities help streamline workflows and allow radiologists to focus more attention on complex diagnostic decisions.
Does AI replace radiologists?
No. AI serves as a support tool that enhances efficiency and accuracy, while radiologists provide the clinical judgment, interpretation, and decision-making that AI cannot replicate. The most effective outcomes occur when AI technology and physician expertise work together.
What are the benefits of AI for patients?
Patients may benefit from faster scan analysis, shorter imaging times, earlier detection of diseases, quicker treatment decisions, and improved diagnostic accuracy. These improvements can contribute to a more efficient healthcare experience and better overall outcomes.
Can AI help detect serious diseases earlier?
Yes. AI has demonstrated value in identifying early signs of conditions such as stroke, cancer, Alzheimer’s disease, and multiple sclerosis, helping clinicians intervene sooner. Earlier detection often expands treatment options and can improve long-term prognosis.
Why is radiology well suited for AI adoption?
Radiology generates large volumes of digital imaging data, providing the extensive datasets AI systems need to learn patterns, improve performance, and support diagnostic workflows. This data-rich environment makes radiology one of the most promising specialties for continued AI innovation.
About Damon Deteso
Damon Deteso, M.D., is a diagnostic radiologist who has practiced with Millennium Medical Imaging in Saratoga Springs, New York, since 2004. He has broad expertise across computed tomography, MRI, ultrasound, X-ray, and nuclear medicine, and holds staff positions at five local hospitals, including Saratoga Hospital. He also served three years as a medical advisor with Imagen Technologies and remains active in radiology professional development, including with the American Society of Head & Neck Radiology.