A shortage of radiologists and increasing demand for medical imaging has led to a notable rise in teleradiology demand across Germany and Austria, with the number of hospitals leveraging these services doubling between 2018 and 2023 (1). With projections indicating continued growth in teleradiology demand, there’s growing interest in how artificial intelligence (AI) could enhance quality and efficiency, benefiting both patients and teleradiologists.
Reif & Möller, Germany’s largest teleradiology network and also the first one in Germany to routinely use AI since 2022 is shedding light into these questions. At this year’s European Congress of Radiology (ECR) in Vienna, Reif & Möller’s CEO, Dr. med. Torsten Möller, unveiled the results of two recent studies, revealing demonstrable benefits of AI to quality of care, and staff satisfaction.
Reif & Möller started their AI journey two years ago, by partnering with the leading clinical AI provider, Aidoc. They integrated a suite of Aidoc’s AI solutions (2) into their existing workflow, which served to automatically notify teleradiologists of suspected positive cases of acute pathologies in patient CT scans, including intracranial haemorrhage (ICH).
Their first study aimed to determine whether AI can help to improve quality in teleradiological reporting. A study of 2,707 patient CT scans were analysed from 140 hospitals across Germany and Austria using Aidoc’s ICH AI solution, with the results compared to those of radiologists that did not have access to AI. Out of the cohort, 189 scans were flagged as suspected positives by the AI, and were confirmed by the radiologists.
However, there were discrepancies where the AI flagged suspected positives that were not initially described by the radiologists. Upon re-reading, an additional 5% of positive cases were surfaced that were initially unreported by radiologists working without the support of AI and an additional 4% were classified as inconclusive, but with a side note of the importance of AI alerting on these cases.
The results of this study clearly show the potential for AI in helping to increase quality in radiological reporting, particularly in the environment of teleradiology where teleradiologists are consistently faced with high volumes of cases (3).
In Reif and Möller’s second study, two surveys were conducted, 5 and 18 months after the initial AI deployment, to measure teleradiologists’ satisfaction when using Aidoc’s AI. The survey captured results from teleradiologists who had substantial experience with the AI solution, using it to analyse tens of thousands of patient scans from over 130 hospitals in Germany and Austria, encountering numerous suspected positive cases along the way.
The survey results clearly revealed a strong and growing satisfaction among radiologists using AI, indicating a tangible positive impact on their professional experience. These findings underscore the significant role of AI in enhancing teleradiologists’ confidence in their roles.
At the end of his presentation at ECR, Dr. Möller predicted a future where radiologists would be mandated to use AI. However, he emphasised that AI alone is not a substitute for the radiologist, rather radiologist plus AI is the future. As teleradiology navigates a future of ever-increasing demand on its services, one thing is abundantly clear: the future of teleradiology is AI-driven.
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