New Delhi: Dr Arjun Kalyanpurchief radiologist and founding CEO, Teleradiology Solutions in interaction with ETHealthworld’s Prathiba Raju clarified the shortage of subspecialty radiologists and how the sophistication of new imaging technologies can close this gap.
The pandemic has increased the use of digitization. Can you tell us how this has translated into increased use of teleradiology?
During the pandemic, hospitals faced sudden spikes in emergency admissions related to COVID and its complications. At the same time, there was a shortage of personnel related to the doctors themselves who were unwell and in quarantine. In such an environment, the ability to have a cohort of radiologists working from home benefited hospitals by giving them immediate access to backup and support from off-site radiologists, as well as radiologists who were able to remain productive while working safely and securely. isolated. from home. Post-COVID, many radiologists now prefer to work from home, which has increased the impact and utilization of teleradiology.
How is the rise of NCDs affecting the radiology industry? What is the shortage of subspecialty radiologists focusing particularly on neuroimaging, oncoimaging and cardiovascular imaging in India? Can technology play a role in filling these gaps?
The rise of NCDs, namely heart disease, cancer, and stroke require more frequent imaging, as patients with these conditions require imaging at multiple time points, including at regular screening, screening, presentation, and follow-up. Furthermore, the imaging data sets for these studies are large. for example, a CT angiography performed to detect or quantify stroke risk may consist of up to 2,000 images for review by the radiologist. All of this results in more data for the radiologist to interpret, resulting in increased radiologist workload, stress, and ultimately burnout, which is now a well-described clinical entity.
In addition, the sophistication of new imaging technologies and the clinical subtleties involved in its interpretation requires a category of subspecialty radiologists who are trained in and appreciate the nuances of the subspecialty. While general radiologists remain relevant and important in today’s world, radiology has become so complex and varied that there is a growing need for subspecialists. For example, the anatomy of the heart, as well as the diseases that affect it, are very different from those of the brain, requiring specialized training and a focus on imaging just as in clinical medicine. Therefore, a subspecialty in radiology is needed. Since radiologists in India today are in short supply with only 20,000 or more for a population of 1.4 billion (a grossly inadequate ratio of 1:100,000), subspecialist radiologists who form a further fraction of this number have even greater scarcity. Technology in the form of teleradiology can play an important role in increasing access for subspecialty radiologists by providing them with images rather than vice versa.
How can teleradiology enable rural populations to access high-quality radiology services? What kind of difference are you seeing at ground level? How are digital and portable radiology equipment transforming rural primary care? Can you give some examples?
In our organization’s experience, both rural and urban populations, predominantly the former, can benefit from teleradiology. This depends on the clinical scenario. For over 15 years, we have provided free reporting services to the Ramakrishna Mission Hospital in Itanagar, Arunachal Pradesh, which cares for a poor tribal population in remote North East India. This involved interpreting high-level CT and MRI scans (the team has been funded by the GOI, but there is a shortage of radiologists in Arunachal Pradesh to report on these studies).
Over a period of five years, we have reported more than 100,000 x-rays for the Tripura Ministry of Health which serves more than 20 community health centers and district and subdivision hospitals. In this way, access to high-quality radiological interpretation was provided to a remote tribal community, far removed from India’s centers of excellence. The impact of these services is also related to the reduced need to transport patients to cities and level II metropolitan areas solely for radiological diagnosis. The use of digital equipment is transformative in terms of enabling telemedicine/teleradiology options to solve diagnostic challenges. In Tripura, several of the centers we were looking to serve were using old analogue X-ray equipment, which is considered largely obsolete in many parts of the world. Using a low-cost technological innovation, we created a process by which these images could be digitized and allowed to be uploaded to our cloud-based teleradiology server.
Portable X-ray equipment also has the potential to improve diagnostics in rural areas, particularly from a screening perspective. Mobile X-rays can also similarly transform TB detection.
How do you see the Chat GPT technology? Do you think it can have an impact on the radiological spectrum? What are some of your potential use cases both in the short and long term?
This is an exciting new technology that I think has the potential to offer some value in the radiology reporting space. The literature has shown its value in terms of simplifying reports in a language that the patient can understand. As we know, radiology reports contain technical language that patients may not be able to understand, and ChatGPT can help translate it into simpler terms that are understandable to the general public. It has also been found useful in developing imaging protocols and summarizing clinical information, as well as in the translation of reports.
In terms of actual reporting, we have found that while ChatGPT offers basic value, there are significant gaps in its production that would need to be addressed before sustained clinical value can be delivered. For example, the report may address one abnormality in detail but completely ignore others, which is a challenge or risk, as it may result in misleading information being reported. Therefore, this will require further development and research.
Among medical subspecialties, radiologists rank high in stress management. Do you think smart workflow solutions and next-generation technology can help radiologists manage the burnout crisis?
Yes, although radiologists may not deal with life-threatening situations as trauma surgeons or cardiologists do, there is stress in the emergency radiology environment related to increased workload with concurrent expectation to produce a quality report in a very short time. frame. Ultimately, radiology reports save lives by detecting ruptured aneurysms, strokes, clots in the lungs, aortic ruptures, ulcer perforation, etc. burnout of the radiologist, resulting in a loss of productivity of the radiologist.
Having a technological solution that simplifies the workflow is a powerful solution. Our technological platform RadSPADesigned as a spa for radiologists, it was essentially developed to ensure easy access to clinical data and current and past images, making the role of a radiologist much more relevant while providing a convenient environment in which that the radiologist can navigate through the reports. process with the minimum of mouse clicks, ergonomically. Adding artificial intelligence (AI) to this workflow produces a simultaneous benefit of quality and productivity.
What niche is your technology solution and is it helping in the detection of complications such as cancer, stroke and intracranial hemorrhage? How is your clinical research division helping the pharmaceutical and biotech segments in clinical trials and drug discovery, as well as AI validation programs?
We have developed AI algorithms in the area of detecting stroke, head injury and breast cancer. Strokes and head injuries are very common in the Indian environment. Our neural assist algorithm focuses on the detection and quantification of bleeding within the brain seen in the context of acute stroke and head injury, both of which are extremely common conditions in India. In both conditions, the most important diagnostic decision is whether or not there is internal bleeding in the brain, on the basis of which treatment is decided. The neural assist algorithm helps detect such bleeding and alerts the radiologist to its presence, based on which the priority of the scan can be informed. It also measures the size of the hemorrhage and detects life-threatening complications, such as swelling in the brain.
Breast cancer is the most common cancer in Indian women today. For there to be an impact at the public health level, massive screening programs using mammography are needed. Our MammoAssist breast cancer detection algorithm analyzes mammographic images to detect early signs of breast cancer and develop a risk score for breast cancer evaluation. This allows the reporting radiologist to be more efficient in reporting such cases within the framework of a comprehensive screening program.
Our clinical research division Image Core Lab supports pharmaceutical and biotechnology companies in the analysis of image scans that allow to determine the efficacy of treatments against cancer that are in development in clinical trials, as well as for cardiovascular and neurological diseases. and other conditions. This provides benefits to customers in the form of reduced drug discovery time and also ensures that standardized imaging protocols are met for regulatory compliance.
