Optimizing Breast Reconstruction With AI Molds

Breast reconstruction with custom molds aims to enhance patient recovery, reduce procedure costs, and improve psychosocial outcomes.

In the United States, one in every eight women will be diagnosed with breast cancer in their lifetime, and more than 40% of those who undergo surgery will need breast reconstruction. Breast reconstruction can help women cope with the changes in their appearance following mastectomy, and it’s an important part of their quality of life.

A research team led by University of Houston professor Fatima Merchant, who chairs the engineering technology department, is developing custom molds for breast cancer patients undergoing reconstructive surgery after cancer treatment().

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With a $2.7 million grant from the National Institutes of Health, the goal of the research is to

Improve the quality and efficiency of breast reconstruction

Reduce hospital stays

Support patients’ psychosocial adjustment to survivorship

“While a few studies have demonstrated the feasibility of using patient-specific molds to shape tissue into a breast form, a critical barrier to progress in the field is that no one has rigorously evaluated their impact. In contrast, our study includes a randomized controlled clinical trial for evaluation.”

Barriers in Breast Reconstruction

During the commonly performed autologous reconstruction, the surgeon uses skin, fat, blood vessels, and muscle from another part of the patient’s body to rebuild the breast. This method is widely recognized as effective, with long-term advantages over other techniques.

However, autologous reconstruction procedures are complex, lengthy operations requiring substantial skill and experience. Plus, a revision procedure is typically required to adequately restore the patient’s bodily form; in some cases, multiple revisions are needed.

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Advantages of New Breast Molds

In practice, the new algorithm-driven breast molds should reduce the cost of reconstruction and the pain and risk associated with reconstruction by reducing the number of procedures a patient undergoes.

Prior work investigated simple molds that merely copied the preoperative shape and size of the patient’s breasts, or a mirrored version of the contralateral breast in the case of unilateral breast reconstruction. But many patients desire or require a different breast form after mastectomy so simply copying the preoperative breast form is inadequate.

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“Our approach in developing the clinical decision-support algorithms is informed by our experience in image perception, machine learning, image processing, and shape modeling, and conducting a thorough evaluation in a randomized controlled clinical trial,” said Merchant.

Reference:

Next-Level Breast Reconstruction After Cancer- (https:uh.edu/news-events/stories/2024/august/08272024-merchant-breast-reconstruction-nih-grant.php)

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Source-Eurekalert