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 diseases such as stroke, cancer, Alzheimer’s disease and multiple sclerosis.
- As AI adoption grows, radiology becomes more efficient, helping to address the growing demand for imaging and shortage of clinicians.
Damon DetesoMD, is a diagnostic radiologist who has practiced at Millennium Medical Imaging in Saratoga Springs, New York, since 2004. He brings extensive expertise in computed tomography, magnetic resonance imaging, ultrasound, x-ray and nuclear medicine, and holds positions at five local hospitals, including Saratoga Hospital. Damon Deteso also spent three years as a medical advisor at Imagen Technologies and remains active in professional development with organizations such as the American Society of Head & Neck Radiology.
His clinical experience makes him well-positioned to discuss how artificial intelligence tools are transforming radiology – not by replacing radiologists, but by expanding their ability to analyze exams faster, detect results earlier, and provide more consistent and accurate results.
In recent years, artificial intelligence (AI) had an impact virtually all industries, including modern medicine. Few medical fields have adopted AI tools as readily as radiology. AI requires large data sets to improve and refine operations, and radiology is the most data-rich subspecialty, making the two naturally complement each other. AI has already reduced radiologists’ workload and helped institutions mitigate the effects of the national clinician shortage.
Medical imaging is a critically important segment in the U.S. healthcare industry, typically serving as the first step toward detecting and diagnosing disease. Doctors use medical imaging technology to identify small tumors, document early signs of Alzheimer’s disease, evaluate fractures and for many other purposes. However, the interpretation of medical imaging images is a time-consuming and technically difficult process.
Fortunately, advanced computer algorithms have allowed AI tools to assist radiologists in several ways, resulting in more precise and accurate scans at higher speeds. AI essentially functions as a radiology assistant that can detect extremely subtle changes in vital parts of the body, carefully measure and track tumor growth, disease progression, and other bodily changes over time, as well as standardize radiology reports.
Speeding up analytics is perhaps the biggest benefit offered by AI tools. In many cases, AI allows doctors to analyze images 75% faster, not to mention improving image quality. Speed is particularly important when it comes to the amount of time patients must spend in MRI machines, as approximately one-third of patients experience claustrophobia, or severe anxiety, while inside an MRI machine. Patients benefit from reduced stress and increased comfort, while radiologists benefit from improved image quality that results in more accurate scans.
While speed and patient comfort are important, nothing is more crucial than accurate results. AI tools not only improve the accuracy of analysis results but help healthcare professionals prioritize cases with critical findings and begin the treatment process as soon as possible. For example, AI tools can quickly identify a stroke on a CT scan and immediately alert doctors, leading to rapid intervention, reduced time spent in the hospital for patients, and better 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 accumulation. This allows medical teams to develop a patient care plan early in the course of the disease, which helps patients maintain a better quality of life.
When it comes to multiple sclerosis, AI is improving 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 when new plaques appear. As AI provides more information, doctors can adjust treatment accordingly.
Finally, AI tools have helped radiologists detect cancer. 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 as early as possible, in addition to measuring tumors, facilitating biopsies and assessing a patient’s response to treatment. It should be noted that AI serves to empower radiologists, not replace them. AI tools cannot be effective without the advice of a competent and knowledgeable healthcare professional.
FAQs
How is AI used in radiology today?
AI is used to help radiologists analyze images, detect abnormalities, measure disease progression, prioritize urgent cases, and improve reporting consistency. These features help streamline workflows and allow radiologists to focus more on complex diagnostic decisions.
Is AI replacing radiologists?
AI serves as an assistive tool that improves efficiency and accuracy, while radiologists provide the clinical judgment, interpretation and decision-making that AI cannot replicate. The most effective results occur when AI technology and physician expertise work together.
What are the benefits of AI for patients?
Patients can benefit from faster analysis, shorter imaging times, earlier disease detection, faster 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 illnesses earlier?
Yes. AI has demonstrated its utility in identifying early signs of diseases such as stroke, cancer, Alzheimer’s disease and multiple sclerosis, helping clinicians intervene earlier. Early 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 data sets that 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, MD, is a diagnostic radiologist who has practiced at Millennium Medical Imaging in Saratoga Springs, New York, since 2004. He has extensive expertise in CT, MRI, ultrasound, X-ray and nuclear medicine, and holds positions at five local hospitals, including Saratoga Hospital. He also worked for three years as a medical advisor at Imagen Technologies and remains active in radiology professional development, including with the American Society of Head & Neck Radiology.
