News | Ultrasound Imaging | May 28, 2019

Improved Imaging for Prostate Cancer Could Lead to More Effective Treatment

Interdisciplinary project seeks to improve outcomes for high-risk prostate cancer patients

Improved Imaging for Prostate Cancer Could Lead to More Effective Treatment

The picture shows that time series signal is extracted from a series of ultrasound frames for classification. Each patch across a number of frames inside the prostate is classified into either cancerous or normal tissue. The image at the lower right corner shows the overall result for those frames. Image courtesy of Pingkun Yan and researchers from NIH, University of British Columbia and Queens University.

May 28, 2019 — Engineers at Rensselaer Polytechnic Institute are working to improve imaging methods in order to make medicine more precise and personalized. This work will be a critical component of a new interdisciplinary research project funded with $1.4 million from the National Institutes of Health (NIH) that seeks to improve radiation therapy for high-risk prostate cancer patients.

“In order to do precision medicine, you need to see better,” said Pingkun Yan, assistant professor of biomedical engineer at Rensselaer. “If you cannot see, you can’t do anything.”

Yan’s expertise in imaging will support researchers from University of Texas Southwestern, led by Jing Wang, associate professor of radiation oncology, who are currently conducting a clinical trial using an approach known as stereotactic body radiation therapy (SBRT), which delivers high doses of radiation directly to a tumor.

Multiple clinical trials have shown that high doses of radiation to prostate tumors can result in improved cancer outcomes, Yan said, but delivery of that radiation must be localized and precise to protect other healthy tissue nearby.

One of the challenges with SBRT is that the prostate can move and deform during delivery. To make sure the accurate dose is being given in the right location, a reliable and accurate tumor tracking method is needed. But traditional ultrasound technology is not sensitive enough to differentiate between the prostate tumor and healthy tissue.

That’s where Yan comes in. He and his team will develop an imaging method to help researchers distinguish between the healthy tissue and the tumor, so they can more accurately administer the radiation doses.

More specifically, Yan will integrate SBRT with a temporal enhanced ultrasound method (TeUS) that he previously developed through a collaboration with the University of British Columbia, Queens University and NIH. TeUS combines a series of ultrasound images, over time, so that researchers and doctors can visually separate the tumor from the healthy organ.

“The tumor and the healthy tissue move a little differently. By observing that area over time, we extract a difference,” he said.

Deep-learning techniques employed by Yan’s team will make this technique possible.

“We could obtain these images in the past, but didn’t have a good tool to analyze those images. With deep learning, with artificial intelligence, we are now able to decode the information and make it usable,” Yan said.

This research is a prime example of the work being done by Yan and other members of the Center for Biotechnology and Interdisciplinary Studies (CBIS) at Rensselaer. Yan is also part of a Cancer Research Group within the center.

Yan also recently received a Bench-to-Bedside award grant, also from NIH, to focus on improving cancer detection through ultrasound imaging. He hopes the results of these collaborative, interdisciplinary projects will improve treatment for all patients.

For more information: dial.rpi.edu

Related Content

This is a lung X-ray reviewed automatically by artificial intelligence (AI) to identify a collapsed lung (pneumothorax) in the color coded area. This AI app from Lunit is awaiting final FDA review and in planned to be integrated into several vendors' mobile digital radiography (DR) systems. Fujifilm showed this software integrated as a work-in-progress into its mobile X-ray system at RSNA 2019. GE Healthcare has its own version of this software for its mobile r=ray systems that gained FDA in 2019.   #RSNA #

This is a lung X-ray reviewed automatically by artificial intelligence (AI) to identify a collapsed lung (pneumothorax) in the color coded area. This AI app from Lunit is awaiting final FDA review and in planned to be integrated into several vendors' mobile digital radiography (DR) systems. Fujifilm showed this software integrated as a work-in-progress into its mobile X-ray system at RSNA 2019. GE Healthcare has its own version of this software for its mobile r=ray systems that gained FDA in 2019.

Feature | RSNA | January 20, 2020 | Dave Fornell, Editor
Here are images of some of the newest new medical imaging technologies displayed on the expo floor at the ...
Researchers at Karolinska Institutet in Sweden and Tampere University in Finland have developed a method based on artificial intelligence (AI) for histopathological diagnosis and grading of prostate cancer

From left: Peter Ström, Martin Eklund, Kimmo Kartasalo, Henrik Olsson och Lars Egevad, researchers at Karolinska Institutet in Sweden. Photo courtesy of Stefan Zimmerman

News | Prostate Cancer | January 20, 2020
January 20, 2020 — Researchers at Karolinska Institutet in Sweden and...
Videos | RSNA | January 13, 2020
ITN Editor Dave Fornell takes a tour of some of the most innovative new medical imaging technologies displayed on the
Trends in Overall Cancer Mortality Rates by Sex, United States, 1930 to 2017. Rates are age adjusted to the 2000 US standard population

Trends in Overall Cancer Mortality Rates by Sex, United States, 1930 to 2017. Rates are age adjusted to the 2000 US standard population. Chart courtesy of the American Cancer Society

News | Radiation Oncology | January 13, 2020
January 13, 2020 — The cancer death rate declined
Professor Samer Ezziddin, M.D., from Saarland University/Saarland University Hospital.

Professor Samer Ezziddin, M.D., from Saarland University/Saarland University Hospital. Image courtesy of Saarland University/Thorsten Mohr

 

News | Prostate Cancer | January 13, 2020
January 13, 2020 — When a non-scientist tries to imagine a scientist, the image that often arises is one of a somewha
Lung cancer patients who are inactive prior to chemoradiation are less likely to tolerate treatment and more likely to see their cancer return
News | Lung Cancer | January 08, 2020
January 8, 2020 — Numerous ...
Sponsored Content | Videos | Ultrasound Imaging | January 06, 2020
The Arietta 850SE provides facilities with numerous features and functionality to get the most out of a system.
Six of the top 20 radiotherapy stories in 2019 involved proton therapy. This includes two video inetrviews shot during a site visit to the Northwestern Medicine Proton Center in the Chicago suburb of Warrenville, Ill.

Six of the top 20 radiotherapy stories in 2019 involved proton therapy. This includes two video inetrviews shot during a site visit to the Northwestern Medicine Proton Center in the Chicago suburb of Warrenville, Ill.

Feature | Radiation Oncology | January 03, 2020 | Dave Fornell, Editor
January 3, 2020 — Here is the top 20 pieces of radiation oncology content on the Imaging Technology News (ITN) websit