Surviving Your First Radiology Call Shift
Everything you need to know before your first overnight call shift — from search patterns to the cases that matter most.
What to Expect
Your first call shift will feel overwhelming. That's normal. You'll be responsible for reading emergency studies — CTs, X-rays, ultrasounds — and communicating findings to the ED, surgery, and medicine teams.
The good news: most of what you'll see falls into a predictable set of patterns.
Building a Search Pattern
A search pattern is a systematic approach to reading a scan so you don't miss findings. For CT Abdomen/Pelvis, this means checking every organ in a consistent order. For CT Head, it means evaluating blood, midline shift, ventricles, and bone in sequence.
The key is consistency — same pattern, every scan, every time.
The Cases You Need to Know
It's a LOT… but you don't need to know everything on day one. Go through these courses and focus on the essential pathologies, including:
How to Use Downtime
Call shifts and rotation days can sometimes have quiet periods. Use them to scroll through cases on our platform. These are higher-yield than the cases you'll randomly come across on rotation. Every case has incremental learning value.
When to Call Your Attending
When in doubt, call. No attending will fault you for waking them up when you need support. The AI Attending can help you practice case interpretation before call, so you arrive with more confidence.
Tools That Help
Platforms like Navigating Radiology let you practice on real DICOM cases with a Fullscreen PACS viewer that simulates the workplace, building the exact skills you'll use on service. The on-call prep courses are specifically designed to cover the patterns you'll encounter most frequently.
Dr. Rajesh Bhayana
Assistant Professor of Radiology, University of Toronto
Dr. Rajesh Bhayana is a practising abdominal radiologist at Toronto General Hospital and Princess Margaret Cancer Centre, an Assistant Professor at the University of Toronto, and the AI & IT Lead at University Medical Imaging Toronto (UMIT). He completed his Diagnostic Radiology residency at the University of Toronto, where he served as Chief Resident, followed by an Abdominal Imaging Fellowship at Massachusetts General Hospital / Harvard Medical School. He is one of the most published voices internationally on the use of large language models (LLMs) in radiology, including the landmark 2023 Radiology studies evaluating ChatGPT on radiology board-style exams, and the state-of-the-art review Primer on LLMs for Radiologists. He is the founder of Navigating Radiology.
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