CASE STUDY / AUTOCONTOUR

AI Contouring Delivers Time Savings Across the Board for AdventHealth

 

Prior to the introduction of AI segmentation, AdventHealth experimented with several previous iterations of autosegmentation tools, none of which consistently delivered accurate or clinically useful results. As medical physicist Adi Robinson points out, “Time savings in the contouring stage means nothing if you spend more time fixing the contours or otherwise adjusting them to your needs.”

Thanks to the adaptability of Radformation solutions, AdventHealth has unified its expansive team, standardizing procedures for dosimetrists, physicists, and physicians alike. This cohesive approach ensures consistent and accurate contours for each patient in a fraction of the time.

To quantify the time savings in real terms, the team reviewed a cohort of 97 patient plans over a diverse range of disease sites and anatomical regions. The study included contributions from six different dosimetrists ranging in experience from 3-25 years, ensuring a thorough evaluation that accounted for any variations in contouring speed.

Download the case study to see their results.

“I was surprised by AutoContour. It saves significantly more time than I expected…AutoContour simplifies our work because it adds all of the structures so we don’t have to manually add them prior to contouring. I appreciate that the software handles structures we encounter less frequently—and are therefore a bit of a challenge to master— such as hippocampus, macula and brachial plexus.”

 

— Elena Rubin, Medical Dosimetrist at AdventHealth

 
 
 

Drastically Reduced Contouring Time

 

 
 
 

High-Quality Contours

 

 
 
 

Standardization of Structures