CPT code X237T issued for Unfold AI in prostate cancer


The CPT code will be effective beginning July 1, 2024.

The American Medical Association (AMA) has granted Unfold AI, an artificial intelligence (AI)-based mapping tool for prostate cancer, the category III Current Procedural Terminology (CPT) code X237T, Avenda Health, the developer of the tool, announced in a news release.1

Unfold AI (formerly iQuest) was granted FDA 510(k) clearance in December 2022.

Unfold AI (formerly iQuest) was granted FDA 510(k) clearance in December 2022.

According to the release, the new code is for “Non-invasive prostate cancer estimation map, derived from augmentative analysis of image-guided fusion biopsy and pathology, including visualization of margin volume and location, with margin determination and physician interpretation and report.”1

The approved CPT code is part of a set of codes that will be published to the AMA CPT website on January 1, 2024, and will be effective beginning July 1, 2024.

COO and co-founder of Avenda Health Brittany Berry-Pusey, PhD, said in the news release, "This recognition by the CPT Editorial Panel is a testament to our dedication to providing cutting-edge solutions in the field of cancer diagnosis and treatment. The new CPT code solidifies our position as a frontrunner in revolutionizing cancer care and our commitment to making our technology accessible to all patients."

The company noted that they plan to expand access of the tool to major teaching hospitals and urology practices nationwide.

Additional data on Unfold AI

Unfold AI (formerly iQuest) was granted FDA 510(k) clearance in December 2022.2

Recent data on the tool were published earlier this year in European Urology Open Science, showing superior efficacy of Unfold AI in determining cancer risk over the current standard of care.

Specifically, the AI-based tool, which incorporates biomarker, biopsy, and image features, demonstrated an 80% rate of complete encapsulation of clinically significant prostate cancer, compared with 56% with conventional margins.Further, in almost half of cases assessed, Unfold AI uncovered clinically significant disease beyond that with conventional margin boundaries.3,4

For the study, investigators retrospectively assessed independent data on 50 patients with prostate cancer who had undergone radical prostatectomy. AI margins with Unfold AI were compared with conventional MRI regions of interest (ROIs), 10-mm regions around ROIs, and hemigland margins.

The mean sensitivity of Unfold AI for cancer-bearing voxels (97%) was higher than that for conventional ROIs (37%; P < .001), 10-mm ROI margins (93%; P = .24), and hemigland margins (94%; P < .001).

The authors concluded, “The AI model was accurate and effective in an independent test set. This approach could improve and standardize treatment margin definition, potentially reducing cancer recurrence rates.”3


1. Avenda Health’s revolutionary AI mapping tool for prostate cancer achieves landmark category III CPT code designation. News release. Avenda Health. November 1, 2023. Accessed November 8, 2023. https://www.prnewswire.com/news-releases/avenda-healths-revolutionary-ai-mapping-tool-for-prostate-cancer-achieves-landmark-category-iii-cpt-code-designation-301973699.html

2. First AI-powered precision oncology platform for prostate cancer care, iQuest, receives FDA clearance. News release. Avenda Health. December 7, 2022. Accessed November 8, 2023. https://www.prnewswire.com/news-releases/first-ai-powered-precision-oncology-platform-for-prostate-cancer-care-iquesttm-receives-fda-clearance-301696475.html

3. Priester A, Fan RE, Shubert J, et al. Prediction and mapping of intraprostatic tumor extent with artificial intelligence. Eur Urol Open Sci. 2023;54:20-27. doi:10.1016/j.euros.2023.05.018

4. New Stanford research study provides further evidence for personalized prostate cancer mapping using machine learning. News release. Avenda Health. June 15, 2023. Accessed November 8, 2023. https://www.prnewswire.com/news-releases/new-stanford-research-study-provides-further-evidence-for-personalized-prostate-cancer-mapping-using-machine-learning-301852037.html

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