DR To Meet DNA: The Future Of X-Ray
In the future, AI and machine learning will play an even larger role in augmenting the radiologist’s role in diagnosis with algorithms that go beyond pattern recognition and other basic forms of AI available today. These first steps in image analysis are important, however, as they are the groundwork for what will come over the next decade as artificial intelligence provides a different type of AI – Actionable Insights.
Greater advancements will occur as we realize the potential of precision medicine. Disparate data sets, including imaging, will be connected in a more intelligent manner. Analysis of anatomical and physiological data from X-rays will be augmented by AI that brings a patient’s genetic profile, familial history, risk factors and more into a comprehensive analysis, providing the radiologist with greater insights. As these intelligent analytics mature, it will be possible to compare the individual to the universe of patients with similar characteristics to provide more predictive and prescriptive personalized patient care. It’s where DR meets DNA. And it’s the future. Radiologists have the chance to be at the forefront of this transformation.
Think about the universe of possibilities to facilitate better decisions, sooner. The clinical benefit of directly visualizing physiological changes with low-cost and readily available X-ray. The potential cost savings made possible by these advancements through the reduced need for more advanced and costly imaging techniques. And, globally, enabling more advanced diagnostic capabilities in less advantaged regions of the world where X-ray is common but MRI, CT and nuclear medicine are not. The ability to achieve higher-quality individualized care, with greater access at a lower cost using DR, is in sight.
For nearly a century after Wilhelm Roentgen discovered electromagnetic radiation in 1895, X-ray remained relatively unchanged. Although the transition to digital images began with computed radiography (CR), it was the emergence of digital radiography (DR) that is expediting X-ray transformation. The future will bring continued enhancements, advanced capabilities such as AI and the ability to capture motion, addressing global healthcare issues and meeting the goals of higher quality care with greater access at a lower cost.
The digital X-ray is an essential primary diagnostic tool, widely available in developed nations. Access is increasing in underdeveloped countries, in part due to lower-cost DR equipment and the expansion of teleradiology. In the U.S., radiography accounts for 74 percent of all radiologic studies with over 36 million chest X-rays alone performed annually for diagnosis and patient management. A lot of information can be discerned from the static grayscale image. What if it were also possible to see even more? That ability is here today with even greater promise for the future to improve clinical outcomes, workflow and efficiency, and lower the cost of healthcare. Soon we will extract more data than previously thought possible from a radiograph. A conventional digital X-ray system will capture motion, allowing the clinician to observe the relationship of anatomical structures relative to physiological changes and time. With chest X-ray in motion we can visualize diaphragmatic, heart and lung motion during successive respiratory and cardiac cycles. It’s not fluoroscopy, but rapid sequential X-rays with advanced processing obtained at a low dose. By visualizing and quantifying these changes, clinicians can better assess functional limitations and monitor a patient’s progression. This capability has the potential to revolutionize our understanding of diseases and better manage patients based on their individual characteristics. It is not limited to chest X-rays but applicable to any anatomical area that can be imaged with radiography. There are an estimated 40 million spine and extremity X-rays each year as well. The potential benefit is enormous. X-ray in motion is the foundation upon which we will apply advanced analytics and artificial intelligence (AI) to provide a greater level of diagnostic information. It will be possible to visualize and quantify pulmonary function including ventilation and perfusion in the lung dynamically, allowing for greater diagnostic specificity.