“We can cultivate the hybrid IR [interventional radiology] clinician-scientist who not only executes patient care with precision but also propels innovation, contributes to global scientific leadership, and moulds the future of minimally invasive therapy.”
These are the words of Prithvijit Chakraborty (Apollo Multispeciality Hospitals, Kolkata, India) in a letter-to-the-editor recently published in the Journal of Clinical Interventional Radiology—the official journal of the Indian Society of Vascular and Interventional Radiology (ISVIR). The letter, cognisant of the rapid transformation of the specialty from a “procedure-based to knowledge-intensive discipline”, contends that Indian interventional radiologists are uniquely placed to emerge as leading clinician-scientists to drive the future of IR.
Characterised by its high case volumes and diverse disease patterns, Chakraborty emphasises the pressing need for IR clinicians in India—and globally—who are trained in simulation science, imaging physics expertise, translational vascular biology, biomaterial engineering, data science, and artificial intelligence (AI) literacy.
“Simulation-based skill development has become an indispensable component of IR education,” writes Chakraborty. “High-fidelity in vitro simulation enhances catheter–wire control, minimises complications, and accelerates learning curves, particularly in neurovascular and complex endovascular procedures.”
In his view, incorporating simulation and rehearsal of real cases as a mandatory rotation during advanced IR training—particularly for ruptured aneurysms, complex arteriovenous fistulas, and fenestrated anatomies— can “significantly enhance technical proficiency”. Even in small institutions, Chakraborty suggests that “simulation libraries” can file specific scenarios to help physicians prepare for adverse events.
Chakraborty states that advanced imaging physics and console literacy are strengths that are “underutilised” by interventional radiologists today. He highlights that modern angiographic systems offering customisable pulse-width modulator dynamic collimation, iterative reconstruction, and cone-beam computed tomography (CT) optimisation, should be included in training as “mandatory rather than aspirational” elements. In India, where equipment heterogeneity is “prevalent”, he writes that structured education on cross-platform console standardisation would improve uniformity in imaging quality.
In his letter he continues, describing animal models and translational IR science as the “cornerstone” of device development, embolic innovation and vascular biology research. “Regrettably”, however, he adds that a limited number of Indian IR training institutions possess routine access to preclinical laboratories. Offering a workaround for this, he outlines “shared preclinical research clusters” at regional veterinary universities.
“This would enable multiple hospitals to access swine animal vascular models, elastase aneurysm creation workshops, and basic biomaterial testing facilities. In the short term, protocol-driven training camps can expose trainees to endothelial response mechanisms, polymer kinetics, embolic-tissue interactions, and haemodynamic phenomena,” notes Chakraborty.
“AI is increasingly becoming an integral component of IR workflows”, Chakraborty continues, listing AI-assisted perfusion analytics, synthetic digital subtraction angiography (DSA), automated catheter navigation and real-time noise reduction as potential applications. Yet, to effectively utilise these tools, he states that physicians must possess a comprehensive understanding of algorithmic design, dataset bias, and performance metrics, to which he prescribes collaboration with academic engineering departments who can facilitate joint development of open-source training modules.
“India finds itself at a critical juncture,” Chakraborty writes. “To transcend merely high case volumes, the next paradigm shift in Indian IR training necessitates the integration of simulation science, imaging physics expertise, translational vascular biology, biomaterial engineering, data science, and AI literacy into the core curriculum.” Finalising his statements, he adds that, by embedding these parallel learning pathways in Indian IR training, the cultivation of hybrid clinician-scientists is achievable.
