Future of Medical Imaging

Radiology currently faces major challenges. It grapples with rising demand due to an aging global population – by 2050, those over 60 will make up for 22% of the world, doubling 2015’s figures, while the number of radiologists grows slowly[1]. In addition, the impact of COVID, with increasing workloads and growing burnout rates, puts further pressure on the field and contributes to a decline in the number of aspiring healthcare professionals.
In this context, the imaging IT industry must prove capable of alleviating radiologists’ workload, to in turn improve the quality of care. We will look at prevailing industry trends and focus on artificial intelligence’s potential in revolutionising medical imaging.

Riding the Cloud Wave

There was palpable enthusiasm around the Cloud at RSNA, and it is no passing trend. As vendors refine their Cloud offers, Signify Research’s “RSNA 2021 Post-Show Trends” report shows a swift shift to Cloud solutions in imaging IT, to overcome “the limitations of on-premise deployment”[1] highlighted by the pandemic.
“Why the Cloud?”, you may think. First, it is budget-friendly – healthcare organisations tailor storage to their needs without investing in superfluous hardware. It also gives 24/7 data protection guarantees. The Cloud, however, is also about enhancing patient care: radiologists collaborate beyond the walls of their departments and organisations, ensuring get unparalleled care. What is more, they can work from anywhere, be it at home, at a café or at the beach. Jennifer Kemp, MD, Vice-Chair of Quality and Operations at Colorado University, Denver, is spot on: “We need to get creative with job opportunities to keep people engaged. When we advertise our open positions as hybrid, we garner more applicants. There’s no reason why some reading cannot be done at home”[2]. It is clear that combining the Cloud with hybrid work is the right strategy to make radiology resonate with the next-gen workforce.


“Two sides of the Cloud coin: Cybersecurity and Evolving Business Models”

The growing popularity of the Cloud in healthcare comes with rising cybersecurity concerns and shifting business strategies. Healthcare facilities house vast quantities of data and increasingly share this data beyond their own walls, meaning they have become favourite cyberattack targets. The HIPAA Journal reported a 74% rise in weekly attacks on the sector in 2022, making healthcare the third most targeted industry globally[3]. Imaging IT players face the essential responsibility to protect and preserve the data, ensuring its integrity and safeguarding patients’ confidentiality. Meanwhile, regarding the business model, Signify Research notes the increasing relevance of ‘as-a-Service’ imaging models. This approach not only promises flexibility in deployment – on-site, Cloud, or hybrid – but also scalable, predictable costs for healthcare organisations.


Smarter Workflows and the Rise of AI

Radiology is changing fast: merging image systems and medical records gives professionals a one-stop shop to view patient data, saving time and avoiding the pitfalls of juggling multiple systems. With routine, tedious tasks like tagging automated, radiologists can focus on the more complex cases, provide more accurate diagnoses and make more informed decisions regarding patient treatment. This fosters a simplified, more dynamic work environment for radiologists, but also elevates the quality of care for patients.
The 2023 European Congress of Radiology shed light on the expanding role of AI – from acquiring to reconstructing and post-processing images[4]. As AI makes its way, the future of radiology looks more promising than ever.


Redefining Radiology: Is AI the Next Big Leap?

RSNA 2021 showed AI was taking centre stage, with Signify Research noting imaging IT providers showcasing their latest, seamlessly integrated AI features.
Now, AI is potentially redefining radiology. A recent study demonstrated ChatGPT’s ability to draft imaging reports about different cases of distal radial fractures. Despite reservations on the reports’ conciseness and ChatGPT’s understanding of specific terminology, ChatGPT’s performance was deemed satisfactory. Wolfram A. Bosbach, MD, PhD, from the University Hospital of Bern and one of the study’s authors, says: “Text drafting tools might well support work of radiologists in the future. They would allow a radiologist to focus time on the observation of image details and patient pathology. ChatGPT can be considered a substantial step forward towards that aim” [5].
Radiologists liberated from the constraints of repetitive tasks and routine reporting, concentrating on cases and enhancing patient care: could AI be guiding us into a new era of medical imaging?


“Unlocking the Power of AI in Imaging: A Glimpse into Tomorrow’s Radiology”

Generative image AI can transform the face of medical imaging, with three main applications: generative adversarial networks (GAN), variational autoencoders and autoencoders[6].

Looking at GANs, picture this: two networks in a friendly duel. One creates synthetic images while the other learns to distinguish the genuine from the fake. The potential? Enhanced image segmentation, allowing for precise studies of specific tissues. What is more, GANs can ‘de-noise’ images, and even fabricate realistic images for training and research purposes.

Autoencoders, on the other hand, learn to generate realistic images based on real ones. Variational autoencoders go further, encoding and decoding images. These prove useful for segmenting images, and when trained to understand images, can detect anomalies and fast-track diagnostic procedures.

AI is not a mere aid here: it is truly redefining radiology.


Radiology Redefined: Elevating Care, for Providers and Patients Alike

 As we look at current transformations in radiology, it becomes clear that the integration of state-of-the-art tools and the role of AI are reshaping the field. Radiologists are freed from routine, tedious tasks, and can dive deeper into complex cases, delivering diagnoses with unmatched precision, providing an unparalleled quality of care. Innovating means constantly pushing boundaries, for the benefit of professionals and patients alike. And this is only the beginning.

[1] Henderson, M. (2022, May 10). Radiology Facing a Global Shortage. https://www.rsna.org/news/2022/may/Global-Radiologist-Shortage

[2] Thompson, A., & Holloway, S. (2021). RSNA 2021 Post-Show Trends (p.43). Signify Research.

[3] Henderson, M. (2022, May 10). Radiology Facing a Global Shortage. https://www.rsna.org/news/2022/may/Global-Radiologist-Shortage

[4] Alder, S. (2023, January 10). Global Healthcare Cyberattacks Increased by 74% in 2022. HIPAA Journal. Global Healthcare Cyberattacks Increased by 74% in 2022 (hipaajournal.com)

[5] Fornell, D. (2023, April 7). Key trends in radiology at the European Congress of Radiology 2023 meeting Key trends in radiology at the European Congress of Radiology 2023 meeting (radiologybusiness.com)

[6]HealthManagement.org. (n.d.). ChatGPT to Generate Highly Rated Radiology Repots. HealthManagement. Retrieved September 1, 2023, from ChatGPT to Generate Highly Rated Radiology Reports – HealthManagement.org

[7] Munuerra del Cerro, J., & Valls Esteve, A. (2023). How Imaging Generative AI Will Transform the Medical Radiological Practice. HealthManagement.org23(2), pp. 128–137. https://healthmanagement.org/c/healthmanagement/issuearticle/how-imaging-generative-ai-will-transform-the-medical-radiological-practice

[8] Book, C. (2023, July 12). AI Essentials in Radiology: Experts Weigh In. itonline.com. AI Essentials in Radiology: Experts Weigh In | Imaging Technology News (itnonline.com)

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