The substantial tumor contrast witnessed in 3D optical images of human breast cancer owes its visibility to the use of novel fluorescent probes. One day these probes might serve as diagnostic aids on par with those used in PET and MRI, according to researchers at the University of Pennsylvania who produced the 3D images using a technique called fluorescence diffuse optical tomography (FDOT).
The substantial tumor contrast witnessed in 3D optical images of human breast cancer owes its visibility to the use of novel fluorescent probes. One day these probes might serve as diagnostic aids on par with those used in PET and MRI, according to researchers at the University of Pennsylvania who produced the 3D images using a technique called fluorescence diffuse optical tomography (FDOT).
"Successful FDOT represents a critical first step toward application of molecular imaging probes, such as dyes and molecular beacons that bind to tumor-specific receptors in deep tissue," said Arjun Yodh, a professor in the departments of radiation oncology and physics and astronomy at the University of Pennsylvania.
The key is the use of fluorophore molecules, which absorb light of one color and then emit the light as a different color. Because these molecules are very sensitive to their local environment, their use in FDOT holds the potential to provide information about tumor physiology, including tissue oxygen, tissue pH, and tissue calcium concentration levels, according to Yodh.
"The potential uses of optical fluorophores bear close resemblance to the use of contrast agents in PET and MRI," he said.
The intravenous addition of an exogenous molecular agent, indocyanine green (ICG), was used to enhance tumor contrast. The vasculature of tumors delays ICG washout from the body and thereby elevates its concentration in tumors relative to normal tissue. University of Pennsylvania researchers plan to improve the instrument in order to assess the flourophore lifetime, which will provide richer information about tumor physiology.
The images are the first clinical shots of human tissue by the researchers, whose previous development of the technique focused on animals. Tumor-to-normal-tissue contrast based on FDOT with the fluorophore indocyanine green was two- to fourfold higher than contrast based on endogenous contrasts, such as hemoglobin, and scattering parameters obtained with traditional diffuse optical tomography.
As the development of molecularly targeted exogenous fluorophores continues, research will help pave the way for optics-based diagnostic tools that will provide improved sensitivity and specificity between healthy and normal tissues, Yodh said.
Could a Deep Learning Model for Mammography Improve Prediction of DCIS and Invasive Breast Cancer?
April 15th 2024Artificial intelligence (AI) assessment of mammography images may significantly enhance the prediction of invasive breast cancer and ductal carcinoma in situ (DCIS) in women with breast cancer, according to new research presented at the Society for Breast Imaging (SBI) conference.
Mammography-Based AI Abnormality Scoring May Improve Prediction of Invasive Upgrade of DCIS
April 9th 2024Emerging research suggests that an artificial intelligence (AI) score of 75 or greater for mammography abnormalities more than doubles the likelihood of invasive upgrade of ductal carcinoma in situ (DCIS) diagnosed with percutaneous biopsy.
Mammography Study: AI Improves Breast Cancer Detection and Reduces Reading Time with DBT
April 3rd 2024An emerging artificial intelligence (AI) model demonstrated more than 12 percent higher specificity and reduced image reading time by nearly six seconds in comparison to unassisted radiologist interpretation of digital breast tomosynthesis (DBT) images.