Advanced X-Ray Imaging Technique for Detecting Breast Cancer Could Also Diagnose COVID-19
By HospiMedica International staff writers Posted on 19 Feb 2021 |
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An advanced X-ray imaging method that aims to improve the detection and diagnosis of breast cancer could also be applied to detect COVID-19 and track the progress of lung inflammation, from mild symptoms to severe illness.
The non-invasive technology being developed by a team of researchers at UMass Lowell (Lowell, MA, USA) uses dyes, called contrast agents, that are specifically designed to recognize molecularly breast cancer cells and bind to them. The dyes will amplify the X-ray signal for tumors when imaged with a special, state-of-the-art computed tomography (CT) scanner, called “photon-counting spectral CT.”
Unlike images from conventional CT scanners, the multicolor, 3D X-ray images generated by spectral CT can help visualize tissue composition in the body based on the density and the atomic number of chemical elements found in those tissues. However, the widely used iodine-based contrast agents approved by the US Food and Drug Administration allow only for fast screening lasting several minutes before they are excreted from the body, while other metal-based contrast media reported in preclinical studies lack the ability to specifically target cancer cells.
“In our approach, we are designing metal-based nanomaterial contrast agents that could stay in the body for a prolonged period due to their high specificity for tumors,” said Manos Gkikas, Chemistry Asst. Prof. at UMass Lowell who is leading the team. “They can accumulate at the cancer site, based on what breast cancer cells produce or feed from, and enhance the CT signal to better visualize the tumor.”
“The resulting data can then be amplified even further using image reconstruction algorithms and machine learning, enabling us to track a tumor’s progression in primary breast cancer,” added Prof. Hengyong Yu of the Department of Electrical and Computer Engineering at UMass Lowell.
According to Gkikas, if the technology is successful, it could be expanded later to detect secondary metastatic cancers - those that usually emerge 4 to 10 years after treatment of the primary cancers and have spread to other tissues and organs. It could even be used to improve early diagnosis of other diseases. “We believe our methodology can provide significant improvement in detecting breast cancer, arthritis and other diseases, including COVID-19,” said Gkikas who has been awarded a grant to apply the imaging technique to detect COVID-19 and track the progress of lung inflammation, from mild symptoms to severe illness.
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UMass Lowell
The non-invasive technology being developed by a team of researchers at UMass Lowell (Lowell, MA, USA) uses dyes, called contrast agents, that are specifically designed to recognize molecularly breast cancer cells and bind to them. The dyes will amplify the X-ray signal for tumors when imaged with a special, state-of-the-art computed tomography (CT) scanner, called “photon-counting spectral CT.”
Unlike images from conventional CT scanners, the multicolor, 3D X-ray images generated by spectral CT can help visualize tissue composition in the body based on the density and the atomic number of chemical elements found in those tissues. However, the widely used iodine-based contrast agents approved by the US Food and Drug Administration allow only for fast screening lasting several minutes before they are excreted from the body, while other metal-based contrast media reported in preclinical studies lack the ability to specifically target cancer cells.
“In our approach, we are designing metal-based nanomaterial contrast agents that could stay in the body for a prolonged period due to their high specificity for tumors,” said Manos Gkikas, Chemistry Asst. Prof. at UMass Lowell who is leading the team. “They can accumulate at the cancer site, based on what breast cancer cells produce or feed from, and enhance the CT signal to better visualize the tumor.”
“The resulting data can then be amplified even further using image reconstruction algorithms and machine learning, enabling us to track a tumor’s progression in primary breast cancer,” added Prof. Hengyong Yu of the Department of Electrical and Computer Engineering at UMass Lowell.
According to Gkikas, if the technology is successful, it could be expanded later to detect secondary metastatic cancers - those that usually emerge 4 to 10 years after treatment of the primary cancers and have spread to other tissues and organs. It could even be used to improve early diagnosis of other diseases. “We believe our methodology can provide significant improvement in detecting breast cancer, arthritis and other diseases, including COVID-19,” said Gkikas who has been awarded a grant to apply the imaging technique to detect COVID-19 and track the progress of lung inflammation, from mild symptoms to severe illness.
Related Links:
UMass Lowell
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