Here's what to expect this week on Diagnostic Imaging.
In this week’s preview, here are some highlights of what you can expect to see coming soon:
When it comes to COVID-19 detection, time is critical. This week, Diagnostic Imaging speaks with the leadership of RADLogics about their current artificial intelligence (AI) system that is designed to streamline workflow. CEO Moshe Becker shares not only the benefits of the system for radiologists, but also the impact on patient care. In addition, he also addresses what makes this AI system different from others in light of a new study that calls the efficacy and accuracy of COVID-19-related machine learning into questions. Look for the interview later this week.
For more COVID-19 AI coverage, click here.
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Recent research has shed a great deal of light on the role of the blood-brain barrier in brain aging diseases. This week, new investigative findings will be published about the impact of having a faulty blood brain barrier and how it might affect the brain. Look for details later this week.
For more coverage of the blood brain barrier, click here.
While tuberculosis is rare in the United States, that isn’t necessarily the case around the world. And, individuals who have active infections pose a dangerous risk to those around them. In a study to-be-published later this week, investigators take a deeper look at how the use of chest X-ray or chest CT allow for more timely screenings and diagnosis. Look for the story later this week.
For additional tuberculosis coverage, click here.
AI Algorithm Comparable to Radiologists in Differentiating Small Renal Masses on CT
May 14th 2024An emerging deep learning algorithm had a lower AUC and sensitivity than urological radiologists for differentiating between small renal masses on computed tomography (CT) scans but had a 21 percent higher sensitivity rate than non-urological radiologists, according to new research.
What a New Meta-Analysis Reveals About Fractional Flow Reserve Assessment with Computed Tomography
May 13th 2024While acknowledging variable accuracy overall with CT-derived fractional flow reserve (FFR-CT) values, researchers found that the accuracy rate increased to 90 percent for FFR-CT values greater > 0.90 and < 0.49.
ACR Collaborative Model Achieves 20 Percent Improvement in PI-QUAL Scores for Prostate MRI
May 9th 2024Using a learning network model to discuss challenges and share insights among radiology departments from five different organizations, researchers noted that 87 percent of audited prostate MRI exams had PI-QUAL scores > 4 at the conclusion of the collaborative program.
MRI-Based Deep Learning Algorithm Shows Comparable Detection of csPCa to Radiologists
May 8th 2024In a study involving over 1,000 visible prostate lesions on biparametric MRI, a deep learning algorithm detected 96 percent of clinically significant prostate cancer (csPCa) in comparison to a 98 percent detection rate for an expert genitourinary radiologist.