Welcome to the Division of Radiology, Anaesthesia and Surgery (RAAS)
Deputy Head of Division: Associate Professor Aaron Quyn
The division encompasses a multidisciplinary group of clinical academics and associated teams spanning radiological, anaesthetic and surgical sciences.
Research is conducted in collaboration with Leeds Teaching Hospitals NHS Trust. In the surgical domain this is focused on transforming patient care through advanced technologies, robotic surgery, and clinical trials.
Key strengths
The development of next‑generation robotic instruments, machine‑learning tools that support real‑time clinical decision‑making, and virtual‑reality environments designed to improve technical skills and patient outcomes.
These innovations are already shaping practice in high‑impact areas such as colorectal and neurosurgery, reinforcing Leeds as a national leader in surgical innovation and translational research. Anaesthetic research interests span perioperative risk assessment, frailty, adverse drug reactions and malignant hyperthermia (MH).
The Malignant Hyperthermia Unit is the UK national centre for MH diagnostics with its world-leading multi-disciplinary research enabling rapid translation of genetic discovery into the clinical setting.
Clinically focused imaging research closely aligned with inter-disciplinary groups at the University (computer science; cancer; image guided radiotherapy; cardiovascular imaging) is conducted by the Academic Radiology Group. Key areas include advanced (quantitative) imaging analysis and AI techniques to improve prognostication, development and validation of pre-treatment imaging-derived risk stratification, improved response assessment and use of distributed learning across multiple centres to develop prognostic models for treatment outcomes.
There is a thriving integrated clinical-academic pathway within the division encompassing Academic Foundation posts, NIHR-funded Academic Clinical Fellowships, externally funded PhD fellowships, as well as allied health professionals with ring-fenced research time.
