The Impact Of Ai On Medical Imaging - The Sum Exceeds The Parts
Dr. Arjun Kalyanpur, Founder CEO & Chief Radiologist, Teleradiology Solutions, 0
Patient safety and well-being are no longer solely the responsibility of doctors or healthcare practitioners. Information technology plays a significant role in this sphere. Accurate information truly saves lives, however, the interpretation of this information by the physician is critical to delivering value. The effective management of such human and computer interactions is therefore paramount and presents the entrepreneurial opportunity of the future. As Peter Thiel says in his book Zero to One, ‘the most valuable businesses of coming decades will be built by entrepreneurs who seek to empower people( in this case,read physicians) rather than to make them obsolete’. This statement is very relevant to the healthcare ecosystem. In recent times with emerging information technologies, healthcare has emerged as one of the most dynamic industries to benefit from the information technology revolution, witnessing an ever-changing landscape filled with advances. As an integral part of healthcare, radiology too is undergoing the same transformation. In layman’s terms, radiology is responsible for generating medical imaging. Besides the routine X-ray, radiology also helps to view abnormalities within the patient’s body through imaging procedures, which include CT scans, angiography, MRI, and PET imaging. Through this technology, doctors can view the internal anatomy of the patient for accurate diagnosis. Imaging also enables doctors to detect a disease in its early stage and helps the patient to get access to early treatment that prevents it from progressing to an advanced stage where the treatment is less effective and the outcomes are grave. Medical imaging, in essence, is critical in saving lives. However, the essence of the effective deployment of AI in imaging lies in ensuring that it functions in synergy with the interpreting radiologist.
AI in Medicine & Radiology
As in any other field, artificial intelligence holds significant potential to revolutionize healthcare in many aspects. It is a valuable tool that offers vast potential to the healthcare industry when combined with the human expertise of radiologists and clinicians. All the way from bridging the gap between the demands of ever-mounting, extremely complex data and the correspondingly insufficient number of radiologists, to simplifying data interpretation through sophisticated AI algorithms, it widely improves the diagnostic process, thereby enhancing patient safety.
Let’s explore some AI trends that focus on how radiology plays a role in the digital shift of healthcare and how humans and technology can come together to add value to patient care.
AI as an Alert Mechanism
AI for radiology may be viewed as an expert assistant, who sifts through the images and highlights areas of concern, prioritizing urgent cases so that the radiologist can adjust workflows to match patient needs. Undoubtedly there is hype around AI radiology today that it is soon going to replace radiologists in healthcare, however, this is not true. The human touch is critical in both the final analysis and patient care, and cannot be replaced. One benefit that AI affords is the capability to provide alerts in critical scenarios wherein it provides an important triage tool (similar to the fire alarm that alerts us to a critical event,. In such a situation, AI provides a valuable alert mechanism to radiologists to ensure
AI as an expert assistant The foremost pressing challenge in radiology today is the exponential growth of data, with a corresponding equal shortage of medical staff. AI assists radiologists by helping with the detection and quantification of abnormalities to make better-informed clinical decisions and add value along the patient journey. AI-powered solutions assist radiologists and healthcare practitioners in making the right decision for every patient.
AI for radiology may be viewed as an expert assistant, who sifts through the images and highlights areas of concern by prioritizing urgent cases so that the radiologist can adjust workflows to match patient needs
Intelligent Imaging that bridges medical specialities
AI plays a crucial role in generating accurate data and faster image interpretation, thereby creating actionable insights. This digital shift helps radiologists achieve reproducible results more efficiently by analysing the imaging data and providing output that includes identification of the disease, measurement of its extent and even detection of its complications. Using a revolutionary new approach called radiomics, it allows for the correlation of the imaging information with tissue pathology and genetic data to provide an ultra accurate interpretation of the imaging findings. No denying the fact that this all has been made possible due to the invasion of AI in radiology which launches a new era of intelligent imaging that works with radiologists to efficiently operate modalities.
Machine learning has been constantly contributing toward improving patient care and radiology is no exception. It has the potential to improve different steps of the radiology workflow including order scheduling and triage, clinical decision support systems, detection and interpretation of findings, post processing and dose estimation, sequence optimization and reducing examination time, examination quality control, radiology reporting, and many more.Along with a shortage of radiologists, the radiology and imaging departments worldwide face additional pressure like increasing workload. Digital solutions enable data driven decisions along the entire patient pathway which can simplify operations and create smart workflows to help reduce the workload and accelerate workforce productivity. In parallel, such solutions can and will improve the quality of life of radiologists by reducing their workload and addressing the impending issue of radiologist burnout.
At the end of the day, AI is the ultimate solution for not only the healthcare sector in general but also for individual medical specialties, radiology being one of the primary beneficiaries. Therefore, rather than radiologists feeling excluded or threatened by machine intelligence, they should adopt it, learn it, and promote it. After all, this is all about improving patientcare and patient outcomes, as well as benefiting their own lifestyle.
Dr.Arjun Kalyanpur, Founder CEO & Chief Radiologist, Teleradiology Solutions
Dr. Arjun founded Teleradiology Solutions in 2002 to address the critical issue of global radiologist shortages using technology innovation. Dr. Kalyanpur's passion and commitment to radiology has inspired him to run Radguru.net, an e-Learning portal on radiology. He is an active contributor to the scientific literature, has edited a radiology textbook and also serves as a reviewer for several radiology journals.