Researchers Use Breast MRI Technique Without Contrast To Detect Cancer.

Tuesday, February 20, 2018

Aunt Minnie (2/20, Forrest) reports that German researchers have developed a breast MRI technique that greatly reduces false-positive findings and increases the detection of breast cancer – without the need for a gadolinium-based contrast agent, according to a study published online February 20 in Radiology. “[The] model ... reduces false-positive results by 70% in lesions classified as BI-RADS 4 or 5 at screening mammography while retaining sensitivity greater than 98%,” wrote the researchers, adding, “Since malignant lesions disrupt the tissue structures at this level, diffusion kurtosis might serve as a relevant marker of changes.”

Diagnostic Digital Breast Tomosynthesis May Reduce Rate Of False Positive Exams, Research Suggests.

Thursday, February 15, 2018

DOT Med News (2/15, Dubinsky) reports that “the use of diagnostic digital breast tomosynthesis (DBT) significantly reduces the rate of false positive exams.” The research is scheduled to be presented at the American Roentgen Ray Society annual meeting.

Women Who Get MRI Screening Tests For Breast Cancer May Get More Biopsies That Detect Fewer Cancers, Study Suggests.

Thursday, February 15, 2018

Reuters (2/15, Rapaport) reports that research suggests “women who get magnetic resonance imaging (MRI) screening tests for breast cancer are more likely to get invasive surgical biopsies to look for tumors than women who just get screening mammograms.” The study also indicated that “regardless of previous breast cancer history, when women get MRIs, fewer of the biopsies that follow result in a cancer diagnosis compared to when women had just a mammogram.” The findings were published in JAMA Internal Medicine.

Deep-Learning Can Provide Fully-Automated Analysis Of Breast Density.

Friday, February 9, 2018

Aunt Minnie (2/9, Ridley) reports that a new study published online on January 24, 2018, in Medical Physics presents a deep-learning algorithm that can provide a fully-automated analysis of breast density on screening mammography exams, including density estimates that correlate well with assessments provided by radiologists. Researchers from the University of Pittsburgh Medical Center trained a deep-learning algorithm “to segment dense fibroglandular tissue on mammograms.” In testing, “the algorithm’s calculation of breast percent density (PD) correlated well with radiologists’ classifications of breast density using BI-RADS, and it also outperformed an existing breast density estimation algorithm, according to the authors.”

False-Positive Stereotactic Vacuum-Assisted Breast Biopsies May Not Negatively Impact A Patient’s Future Screening Mammography Adherence, Research Suggests.

Friday, February 9, 2018

The Radiology Business Journal (2/9, Walter) reported that “false-positive stereotactic vacuum-assisted breast biopsies (SVABs) do not negatively affect a patient’s future screening mammography adherence.” The findings were published in the Journal of the American College of Radiology.