Autocontouring a transformative leap in radiotherapy

Dr Aminudin Rahman Mohd Mydin, a consultant clinical oncologist, talks about the role of artificial intelligence (AI) in oncology and the advent of auto-contouring via the application of AI in radiotherapy.

Radiotherapy is a a pivotal cancer treatment. It employs radiation in the form of photon beams, gamma rays, and X-rays to eliminate cancer cells.  Its primary advantage lies in its localized targeting, minimizing collateral damage to surrounding body areas and reducing potential side effects compared to broader cancer treatments.

The significance of contouring in radiotherapy
Challenges arise when cancer sites are too close to critical organs, for instance, the heart in cases of breast cancer, is termed as an ‘organ at risk’ (OAR). Oncologists traditionally invest substantial time in identifying, delineating, and mapping OARs, primary and secondary tumor sites, and cancer-affected lymph nodes. This process is known as contouring and is vital for shielding OARs and reducing or preventing damage to adjacent cells. However, it is labor-intensive and requires precision.

Auto-contouring solutions are diverse and tailored to oncologists’ varying requirements. Some are integrated directly into CT scanners, offering AI-generated outlines for oncologists’ refinement. Others focus on OAR auto-contouring or provide comprehensive workstations with combined auto-contouring, simulation, and image assessment capabilities.


Advantages of auto-contouring

Precision and safety
The deep learning algorithms of AI are the backbone auto-contouring, enhancing its precision and accuracy through continuous learning from cancer cases. This results in high-quality contours aligning with international medical standards, devoid of human error. Thus, auto-contouring ensures precise tumor boundary demarcation and meticulous radiation dosage control, substantially reducing healthy tissue and organ damage risk during treatment.

Efficiency
Auto-contouring’s automation dramatically shortens contouring time, with studies indicating potential time savings of up to 80 percent. This efficiency allows oncologists to manage more patients and allocate additional time to other critical aspects of patient care. Patients benefit too, as quicker, more precise contouring can significantly decrease the number of required radiotherapy sessions.

Auto-contouring is gaining traction as the results of a survey by The Royal College of Radiologists from the UK, published in 2023, found that 78 percent of clinical oncologists felt that the use of AI will have a positive impact on radiotherapy and 60 percent felt that AI would save time in radiotherapy planning. [Clin Oncol (R Coll Radiol) 2023;35:219–226]

Despite the positive reception among healthcare professionals (HCPs), auto-contouring in radiotherapy is still in its early stages of adoption. This calls for enhanced support, guidance, and educational resources for both HCPs and the public regarding this technology.