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AI autocontouring: Frequently asked questions

25 Aug 2021

What is AI auto-contouring? Do you have to train it? The questions you wanted to asked, but never did.

  1. FAQ: What is the organ at risk autocontouring?

Autocontouring automatically delineates organs at risk, taking away the manual need to draw around these organs. This task is a critical step in preparing a patient for radiation therapy to ensure that healthy organs surrounding the tumor are spared from radiation to improve patient outcomes. Two forms of autocontouring currently exist Atlas-based contours and Deep Learning, a form of AI.

  • Atlas-based autocontouring uses a combination of previously contoured anonymized patients, generally 20+. A matching algorithm selects the patient or contour most similar to today’s patient before deformable image registration is used to transfer the contours from the Atlas onto the patient.

  • Deep learning uses hundreds of anonymized past cases (carefully selected to ensure high-quality, consistent input data) to train an Artificial Intelligence, which learns how to predict the same structures onto new data. Deep learning contouring is a form of Artificial intelligence based on neural networks mimicking the human brain.

  • Today, Atlas technology is being replaced by superior AI-based Deep Learning technologies. Both solutions deliver autocontouring, but  Deep Learning technology is increasingly being shown to provide more usable clinical contours.   (See An evaluation of atlas selection methods for atlas-based automatic segmentation in radiotherapy. 2019, Schipaanboord B et al. for more information). The keystone to any good model is well-curated, robust data sets. Mirada now offers an AI library of contours covering the four anatomical regions, head and neck, thorax, prostate and breast.

Remember, not all algorithms are equal: rubbish data and training in equals rubbish out. If you’re looking at different vendors, see the data on their application first.

2. FAQ: How are AI autocontouring tools trained?

Mirada receives large anonymized clinical data sets of more than a hundred. Inhouse Dosimetrists then curate and consistently contour these. An algorithm is then trained to learn from this, forming the basis of Deep Learning models to be used in the AI library structure set and used in the clinics to contour new data. This technology is where the name DLCExpert originated. If you would like to see how your data looks and performs on DLCExpert, book a consultation.

3. FAQ: Will the software suit me immediately when I run cases in my clinic?

As the first clinical worldwide AI autocontouring provider, Mirada recognizes that all hospitals and Dosimetrists contour differently. This varied approach to contouring styles is reflected in the differing consensus guidelines and ESTRO and ASTRO guidelines. Mirada begins with these consensus guidelines. We encourage hospitals to see how your data looks and performs on DLCExpert, book a consultation.

4. FAQ: We use specific colors and naming conventions for our structures. Can we easily use those in your models?

The platform that DLC Expert is powered from can be easily configured to match your hospital preference. Mirada’s Clinical experts will help configure this for you.

5. FAQ: Is a Cloud solution is better than a traditional inhouse server solution?

Some companies claim that being on the cloud speeds processing of cases, yet like working from home, this depends on network speeds. If your network speed is relatively slow (most hospitals can be), the processing time won’t reflect what is advertised. Although it has some advantages, using a cloud feature reduces the need for some hardware and may present other issues and considerations: If on the cloud, where is your data being pushed to? Is a server somewhere remote? How secure is that server? Is there a contingency if, e.g. if there is an earthquake (e.g. as experienced in Christchurch New Zealand) or near a toilet where the pipes burst (a real example I experienced). Having the cases processed on–site gives you more control and oversight over your patient‘s data.  Related Links:

  • (Also read: AI autocontouring – Myth-Busting)

  • Purchasing AI autocontouring? Things to consider to avoid pitfalls

  • Book a demo to see DLCExpert on your data


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