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Basal Cell Carcinoma: Using AI to Improve Tumor Excision and Patient Results

By: Celeste L. Dixon
Posted: Wednesday, March 27, 2024

An artificial intelligence (AI) platform, based in part on the successful methods used to excise basal cell carcinoma with Mohs micrographic surgery (MMS), has the potential to enhance intraoperative margin assessment to improve the odds of complete excision in other solid cancers, particularly skin cancers. Such complete excision, either for definitive treatment or before adjuvant therapy, increases the chance of better patient outcomes, according to Joshua J. Levy, PhD, of Cedars-Sinai Medical Center, Los Angeles, and colleagues, who described their work in npj Precision Oncology.

This deep learning–based platform, or digital assessment tool, performs automated tissue measurements, which should improve laboratory workflow through efficient grossing and inking recommendations, thus reducing tissue preprocessing and histologic assessment time. Better mapping and orientation of tumor to the surgical specimen are also involved, the team explained. Ultimately, use of the software would mean an expert pathologist would not have to be in physical proximity to the operating suite.

Currently, “real-time assessment in many tumor types is constrained by tissue size, complexity, and specimen processing/assessment time during general anesthesia,” Dr. Levy and co-investigators observed. These factors contribute to “surgical laboratory efficiency bottlenecks,” they continued. “Intraoperative and postoperative radial sectioning, the most common form of margin assessment, can lead to incomplete excision and increase the risk of recurrence and repeat procedures.”

Their single-center study involved specimens from 194 patients undergoing basal cell carcinoma tumor excision with MMS. Tissue samples from 16 patients were used for tissue-grossing algorithms; tissue specimens from the remaining 178 were used for histologic assessment and tumor-mapping algorithms.

The team would like to facilitate the use of the complete, real-time margin analysis that is the hallmark of MMS in a wider range of surgical contexts, while acknowledging that it cannot replace all resection protocols. “Additionally, [the platform] can be used to support the current standard of care, rather than replacing it entirely, by providing more accurate and efficient margin assessment,” they noted.

Disclosure: The study authors reported no conflicts of interest.

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