CT Colonography & Tumor Differentiation; COVID-19 & Leukoencephalopathy; MRI, the Angiography Suite, and Acute Ischemic Stroke; Plus, DBT, African American Women, & Decreased Access
Welcome to Diagnostic Imaging’s Weekly Scan. I’m senior editor, Whitney Palmer.
Before we get to our featured interview with Linda Blount, MPH, president and chief executive officer for Black Women’s Health Imperative about the inequities of access to digital breast tomosynthesis, here are the top stories of the week.
Adding a radiomics-based machine learning algorithm to CT colonography allows for the differentiation between benign and pre-cancerous polyps picked up on colorectal cancer screening. To date, radiologists have not been able to make that determination using CT colonography, but thanks to work from German researchers, it is possible to do so with high sensitivity and specificity. They built a machine algorithm that uses radiomics to extract quantitative image features that predict whether a polyp will develop into cancer. They trained the algorithm on 169 CT segmentations from 107 colorectal polyps from 63 patients and tested it on 118 segmentations from 77 polyps from 59 patients. Using random forest analysis, they determined their algorithm could accurately differentiate benign and pre-malignant polyps with 82-percent sensitivity and 85-percent specificity with an area under the curve of 0.91. Ultimately, the team said, incorporating a machine learning-derived algorithm into CT colonography can make it an even better colorectal cancer screening tool.
New brain MRI images have shown that COVID-19 can create leukoencephalopathy, a rare condition that affects white brain matter. Currently, the industry does not have defining criteria for COVID-19 disseminated leukoencephalopathy (CRDL), so researchers from the University of Pennsylvania investigated whether identifying signs was possible, and they published their findings in the American Journal of Roentgenology. After examining 2,820 COVID-19-positive patients who were hospitalized between March 2020 and June 2020, they determined 59 patients underwent brain MRI. Those scans revealed six patients (10.2 percent) had findings that suggested CRDL, such as extensive confluent or multifocal white matter lesions, micro-hemorrhages, diffusion restriction, and enhancement. Other patients also had evidence of multiple sclerosis and small vessel ischemic disease white matter lesions; acute, subacute, and chronic infarcts; abnormal basal ganglia signal from hypoxemia; and micro-hemorrhage associated with acute, subacute, and chronic infarcts. The team did note that their findings could overlap with findings for other conditions, but they maintained that radiologists must remain alert to potential presentations of CRDL.
While CT is typically used in the angiography suite, new research published in Radiology shows that using MRI instead can help providers determine whether to continue to thrombectomy, the place stents, or to administer anti-thrombotic medications with patients who have suffered acute ischemic stroke. In a retrospective study of patients who received endovascular intervention for acute ischemic stroke between July 2019 and May 2020, a team from the University of California at San Francisco determined that of 47 patients who underwent stroke intervention, 12 had X-ray angiography with MRI. Based on their analysis, including MRI directly impacted treatment decision for all 12, including whether to proceed with mechanical thrombectomy, to place intracranial stents, or whether to administer antithrombotic medication. But, while these advancements show promise, other experts said that streamlining workflow to reduce transfer time between the angiography unit and the MRI is critical because, with stroke, “time in brain.”
And, finally, this week, Diagnostic Imaging spoke with Linda Blount, MPH, president and chief executive officer for Black Women’s Health Imperative about recent research that reveals black women do not have equal access to digital breast tomosynthesis despite better cancer detection and lower recall rates associated with the screening. She discussed what these inequities mean for this patient group and what can be done to alleviate the disparities. Here’s what she had to say.
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Can Radiomics Bolster Low-Dose CT Prognostic Assessment for High-Risk Lung Adenocarcinoma?
December 16th 2024A CT-based radiomic model offered over 10 percent higher specificity and positive predictive value for high-risk lung adenocarcinoma in comparison to a radiographic model, according to external validation testing in a recent study.
Study Shows Merits of CTA-Derived Quantitative Flow Ratio in Predicting MACE
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