New Delhi: Dr Arjun Kalyanpur, Chief Radiologist and Founder CEO, Teleradiology Solutions spoke to ETHealthworld’s Prathiba Raju on the shortage of subspecialist radiologists and how the sophistication of the new imaging technologies can bridge this gap.
The pandemic has increased the utilisation of digitisation. Can you tell us how this has translated into greater utilisation of teleradiology?
During the pandemic, hospitals were faced with sudden spikes in emergency admissions related to COVID and its complications. In parallel, there were staffing shortages related to physicians themselves being unwell and in quarantine. In such an environment, the ability to have a cohort of radiologists working from home benefited the hospitals by providing them with immediate access to radiologist backup and support from offsite, as well as the radiologists who were able to remain productive while working safely and in isolation from home. After COVID, many radiologists are now preferring to work from home which has increased the impact and utilisation of teleradiology.
How increasing NCDs are impacting the radiology industry? What is the shortage of subspecialty radiologists particularly focusing on neuroimaging, oncoimaging and cardiovascular imaging in India? can technology play a role in filling these gaps?
The increase in NCDs, namely heart disease, cancer and stroke is necessitating more frequent imaging, as patients with these conditions require imaging at multiple time points, including at screening, detection, presentation and for regular follow-up. Also, the imaging datasets for these studies are large. For example, a CT angiogram performed to detect or quantify the risk for stroke may consist of up to 2000 images for the radiologist to review. All of this results in more data for the radiologist to interpret, the result of which is increased radiologist workload, stress and eventually burnout, which is now a well-described clinical entity.
Also, the sophistication of the new imaging technologies and the clinical subtleties involved in their interpretation necessitates a category of subspecialist radiologists who are trained in and appreciate the nuances of the subspecialty. While general radiologists are still relevant and important in today’s world, radiology has become so complex and varied that there is an increasing need for subspecialists. For example, the anatomy of the heart as well as the diseases that affect it are very different from the brain, requiring specialized training and focus in imaging just as in clinical medicine. Therefore subspecialization in radiology is needed. Given that radiologists in India, today are in short supply with only 20,000 or so 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 are in even greater shortage. Technology in the form of teleradiology can play an important role in increasing the access of subspecialist radiologists by bringing images to them instead of vice versa.
How teleradiology can enable rural populations to access high-quality radiology services, what kind of difference you are seeing at the 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 now we have been providing reporting pro bono services to the Ramakrishna Mission Hospital in Itanagar, Arunachal Pradesh, which serves a poor tribal population in the remote northeast of India. This involved interpretation of high-end CT and MRI scans ( the equipment has been funded by GOI, but there is a shortage of radiologists on site in Arunachal Pradesh to report these studies).
Over a five-year period, we have reported over 100,000 x-rays for the MOH Tripura serving over 20 community health centres and district and subdivisional hospitals. In this manner access to high-quality radiology interpretation was provided to a remote tribal community, far removed from India’s centres of excellence. The impact of such services also is related to the decreased need for transporting patients to tier II cities and metros purely for radiologic diagnosis. The use of digital equipment is transformational in terms of enabling telemedicine/teleradiology options for solving diagnostic challenges. In Tripura a number of the centres we sought to provide services to used the old analogue x-ray equipment, which is considered largely obsolete in many parts of the world. Using a low-cost technology innovation, we created a process by which these images could be digitized allowing them to be uploaded to our cloud-based teleradiology server.
Portable X-ray equipment also has the potential to further diagnostics in rural areas, particularly from a screening perspective. Mobile, X-rays can also similarly transform TB screening.
How do you view Chat GPT technology? Do you think it can have an impact on the radiology spectrum? What are some of its potential use cases in both the short- and long-term?
This is an interesting new technology that I believe has the potential to deliver some value in the radiology reporting space. The literature has shown its value in terms of simplifying reports into a language which a patient can understand. As we know, radiology reports contain technical language that patients may not be able to understand, and ChatGPT can help translate this into simpler terms that are understandable by the general public. It has also been found helpful in developing imaging protocols and summarizing clinical information as well as in report translation.
In terms of actual report generation, we have observed that while ChatGPT does deliver some basic value, there are significant lacunae in its output, 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 communicated. This will therefore require further development and investigation.
Among the medical subspecialties, radiologists rank high in dealing with stress. Do you think smart workflow solutions and next-gen technology can help radiologists to handle the burn-out crisis?
Yes, while radiologists may not deal with life-and death-situations in the manner of trauma surgeons or cardiologists, there is stress in the emergency radiology environment related to increasing workloads with the simultaneous expectation of producing a quality report in an ultra-short time frame. Ultimately radiology reports save lives, by detecting ruptured aneurysms, strokes, clots in the lungs, aortic ruptures, ulcer perforation etc. The resulting pressure to diagnose accurately and consistently, in the setting of high volume, can produce stress for radiologists and predispose them to radiologist burnout, resulting in a loss of radiologist productivity.
Having a technology solution that simplifies workflow is a potent solution. Our technology platform RadSPA, designed as a Spa for radiologists essentially is developed to ensure easy access to clinical data and current as well as prior images which makes the role of a radiologist so much more relevant, while providing an environment of convenience which the radiologist can navigate through the reporting process with the minimum of mouse clicks, ergonomically. Adding Artificial Intelligence (AI) into this workflow produces a simultaneous quality and productivity benefit.
How niche is your technology solution and is it helping in the detection of complications like cancer, stroke, and intracranial haemorrhage? How is your clinical research division helping the pharma and biotech segments in clinical trials and drug discovery, as well as AI validation programs?
We have developed AI algorithms in the space of stroke, head injury, and breast cancer detection. Stroke and head injury are both very common in the Indian setting. Our neural assist algorithm focuses on the detection and quantification of bleeding within the brain seen in the setting of acute stroke and head injury, both of which are extremely common conditions in India. In both these conditions, the most important diagnostic decision is whether or not there is internal bleeding in the brain, based on which the treatment is decided. The neural assist algorithm helps detect such bleeding and alert the radiologist about their presence, based on which the scan can be reported on priority. It also measures the size of the bleed and detects life-threatening complications such as swelling in the brain.
Breast cancer is the commonest cancer in Indian women today. For there to be an impact at a public health level, mass screening programs using mammography are needed. Our breast cancer detection algorithm MammoAssist analyses mammographic images to detect early signs of breast cancer and develop a risk score for breast cancer assessment. This allows the reporting radiologist to be more efficient in the reporting of such cases in the setting of a large screening program.
Our clinical research division Image Core Lab supports pharma and biotech companies in the analysis of imaging scans that allow for determining the efficacy of cancer treatments that are under development in clinical trials, as well as for cardiovascular and neurologic diseases and other conditions. This provides benefits to clients in the form of a reduction in drug discovery time and also ensures that standardized imaging protocols are adhered to for regulatory compliance.
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