July 16, 2009 - Principal investigator, radiologist Dr. Alexander Poellinger, and his team of researchers at the Charité, Medical University in Berlin, Germany, will use fluorescent dye to demonstrate an enhancement of the sensitivity and the specificity of diffuse optical tomography in a new a breast cancer imaging study. Imaging Diagnostic Systems Inc., a laser breast imaging systems company, launched the breast cancer imaging study to examine the potential role of its model 1020 CTLM laser breast imaging system as an enhanced breast cancer-screening tool when used in combination with the fluorescent dye, Indocyanine Green (ICG). “In other studies, optical imaging using fluorescent dyes have shown great promise to detect and differentiate malignancies. By using a fluorescent dye in a clinical breast cancer study, we hope to demonstrate an enhancement of the sensitivity and the specificity of diffuse optical tomography. For this purpose we will use a modified CTLM breast scanner that is capable of acquiring both absorption and fluorescence images," said Dr. Alexander Poellinger. The ICG fluorescent dye has a distribution pattern in the human body similar to that of extracellular MRI and CT contrast agents and it is already approved for other medical applications. The IDSI model 1020 CTLM scanner that will be used in the study has been specially modified to be able to both excite the ICG dye and image its fluorescence in breast tissue. Following injection of ICG into the patient, the scanner produces 3D images of the localized concentration of the dye. These images are expected to show increased extravazation and accumulation of the dye in malignant tissue. IDSI users have performed over 15,000 CT Laser Mammography (CTLM) clinical cases worldwide. For more information: www.imds.com
Laser Breast Imaging Study Uses Fluorescent Dye
Fatty tissue and breast density may be considered in the context of many factors that affect the occurrence and detection of breast cancer. Permission to publish provided by DenseBreast-info.org
A smart algorithm has been trained on a neural network to recognize the appearance of breast cancer in MR images. The algorithm, described at the SBI/ACR Breast Imaging Symposium, used “Deep Learning,“ a form of machine learning, which is a type of artificial intelligence. Graphic courtesy of Sarah Eskreis-Winkler, M.D.