AI-Powered Imaging System Can Tell If a Patient Is Cancer-Free
A patient undergoes chemotherapy and radiation for rectal cancer. How do doctors know whether all the malignant tissue has been destroyed?
Washington University in St. Louis researchers have developed a way to answer this question, using an innovative combination of photoacoustic microscopy, ultrasound, and “deep learning” artificial intelligence neural networks.
This new system, called PAM/US, allows physicians to detect the presence of residual tumors within rectal tissue, even differentiating cancer cells from other tissue abnormalities such as scars.
“Our PAM/US system paired with the deep learning neural network has great potential to better identify patients suitable for nonoperative management and improve patient quality of life,” explained Quing Zhu, lead author of the study.
“If we can tell after radiation and chemotherapy which patients may have a good response with no residual tumors, the patient may be able to avoid surgery.” This is a huge leap forward in the standard of care for patients with non-metastatic rectal cancers, many of which need to undergo invasive follow-up procedures after cancer therapies.
In the study, Zhu and colleagues describe how the technique would be used in a clinical setting. A patient under…
