New imaging technology has been developed to determine better whether a rectal cancer patient is successfully treated with no residual cancers. Developed by scientists at Washington University in St. Louis, the technology combines photoacoustic microscopy, ultrasound, and deep learning.
Scientists believe that this technology could help physicians to determine a treated rectal tumor bed with residual cancers that need surgery or normalized rectal tissue without the need for surgery.
Rectal or Colorectal cancer is cancer that begins in the rectum. While some individuals can avoid surgery thanks to treatment, it’s challenging to tell whether cancer has been completely eradicated according to current technology.
Previously, Stage 2 and 3 rectal cancers have been treated with radiation and chemotherapy followed by surgical removal of the cancerous tissue. However, thanks to improvements in preoperative care, up to 35% of these individuals can completely eradicate their tumors using only radiation and chemotherapy.
In these patients, surgical resection has not demonstrated any benefit and entails substantial risks, including serious complications, a protracted recovery, and a decreased quality of life. Surgery is still the mainstay of care since it is difficult for surgeons to discern between a residual malignancy and scar tissue when using current imaging methods to evaluate whether the tumor has been removed.
Quing Zhu, a biomedical engineer at the McKelvey School of Engineering, said, “Improved imaging methods could resolve this problem and allow widespread adoption of nonoperative management called ‘watch and wait’ for hundreds of thousands of rectal cancer patients.”
“If successful, this technology will directly reduce the number of unnecessary surgeries for rectal cancer and improve the patient’s quality of life.”
To determine whether cancer has been completely eradicated from rectal tissue, researchers have created a co-registered acoustic resolution photoacoustic microscopy and ultrasound (AR-PAM/US) endoscopy prototype system and neural network classifiers. Her team put the device through its paces in a 2019–2021 feasibility study, and they discovered that it outperformed existing imaging techniques like MRI to detect residual tumors in treated rectal tissues.
With the additional money, the researchers will prospectively evaluate the technology’s capacity to enhance current imaging practices in a group of rectal cancer patients who are unsure whether they still have a tumor or scar tissue. The team will also keep tabs on a group of patients to see if the AR-PAM/US technology can gauge alterations in tumor vasculature and blood oxygen saturation and identify the tumor’s response to treatment.
A laser is used in photoacoustic imaging to stimulate the tissue. Due to tumor angiogenesis, the absorption of laser light results in the emission of sound waves that disclose characteristics of the tissue vasculature, a biomarker for malignant tissue. The novel probes being developed and improved by Zhu’s team utilize AR-PAM/US to evaluate the rectum after therapy effectively.
To aid surgeons in real-time diagnosis, Zhu and her team have created a unique pattern-recognition neural network that provides a quantitative interpretation of the AR-PAM and US pictures. In their earlier research, imaging and neural networks demonstrated how tumor beds in rectal tissue change from cancerous patterns to those typical of a healthy rectum, demonstrating a complete response to therapy.
They anticipate that their AR-PAM/US system and neural net classifiers will enable surgeons to examine the tumor’s microvessel network and gauge treatment response following only radiation and chemotherapy and that their studies will outperform current methods of care in predicting a patient’s response to treatment both after treatment and during the “watch-and-wait” period for up to two years after treatment.