Vincent Chan.
The topic of AI will once again be covered throughout the sessions and on display in the exhibitor hall at this year’s RSNA Scientific Assembly and Annual Meeting. The need for imaging modalities that enable earlier and more accurate diagnosis continues to drive AI applications in the medical imaging market.
In fact, the AI in medical imaging market size is witnessing phenomenal growth, which is expected to grow from $1.12 billion in 2022 to $27.52 billion by 2029, according to Maximize Market Research, a global healthcare market research company. As more transformational changes lie ahead, I would like to highlight three areas where AI is having a visible impact today.
Patient positioning
AI-based tools with varying degrees of automation and intelligence improve medical imaging workflows, including patient positioning. At RSNA 2023, look for AI-based systems that radiologists can use to make patient positioning faster, more accurate, and bring consistency to the process, all helping to improve image quality and to reduce the need for rework.
Positioning is a tedious step in the image capture process. Even the most experienced radiologists may fail to achieve correct positioning. Then, after placing the patient in the exact position, it is not uncommon for the patient to move in the time it takes for the radiologist to return to the console. Sometimes the slight change in position goes unnoticed, requiring a reshoot, adding even more time to the image capture process.
Today, sensors, cameras, and AI software all work together to automatically adjust the equipment for each patient and each exam, and alert the radiologist if the patient has moved so that corrective action can be taken. These intelligent capabilities allow the radiologist to correct positioning errors before imaging.
Image quality
AI and other algorithms also improve image quality, which helps improve diagnosis and treatment planning. One notable outcome of AI is advanced visualization techniques, also known as associated views, in which images are processed for a specific interpretation task. The algorithms use sophisticated image analysis, multi-frequency enhancements and grayscale transformations to accentuate interesting features such as edges, lines and fine textures. Examples of advanced visualization applications include helping to locate the ends of tubes and lines or improving the appearance of a pneumothorax or collapsed lung, thereby helping the physician see the area of interest.
Another advance in image processing rooted in AI balances noise and dose in images. These two factors are closely linked: the sharper the image, the more noise is accentuated, which is not a good result. At RSNA, attendees will experience AI technology that reduces image noise while retaining the finest spatial details. Significantly clearer images are produced and a better contrast-to-noise ratio is achieved over a wide exposure range. This technological advancement is particularly beneficial for the high-contrast detail needed for musculoskeletal (MSK) imaging. The ability to reduce radiation doses without loss of image quality also has considerable benefits in neonatal and pediatric imaging, where imaging at the lowest possible dose is essential.
Improve the patient experience
AI advances in patient positioning will have an additional important outcome: improved patient experience. Patients who undergo medical imaging are often worried, in pain, or both. Radiologists who spend less time positioning equipment are free to spend an extra moment or two reassuring patients. Additionally, a faster workflow gives patients added assurance that they are being cared for by a competent radiologist.
The other side of the human experience is that of radiologists. The systems and technology presented at RSNA will demonstrate how AI-based tools give them added confidence that they are capturing the best possible image and advancing patient care. Using AI in the medical imaging process also allows radiologists to focus on one of the most important aspects of their profession: interacting with patients.
Executives in industries other than healthcare routinely describe AI as being as important as the Industrial Revolution in terms of economic impact, productivity, innovation and overall impact on quality of life. In healthcare, it has the potential to improve diagnostic and treatment processes. As medical imaging providers continue to look to the future, RSNA participants can adopt existing AI radiology solutions that help improve clinical outcomes and enhance the imaging experience for patients and radiologists. ‘Today.
Vincent Chan is President and General Manager of Digital Radiography at Carestream.
The comments and observations expressed are those of the author and do not necessarily reflect the opinions of TanteMinnie.com.
