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:
A flurry of studies have been published in recent months about the efficacy and utilization of low-dose CT (LDCT) for lung cancer screening – these articles point to whether the exam actually works as proclaimed and how much impact it actually is having. The consensus is that the screening test is effective, but that there is still a lot of room for improvement in screening patients who could significantly benefit. This week, more data and guidance are coming. Keep your eyes open for an article in the coming days about who should be screened and when.
For more LDCT lung cancer screening coverage, click here.
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The value of MRI as a sensitive diagnostic tool is already widely known, and the modality continues to advance. This week, Editorial Board member Eliot Siegel, M.D., radiology professor and vice chair at the University of Maryland School of Medicine, takes a deep dive into what could be the next frontier for MRI – very low field strength. He explores the drivers behind the expansion of this advancement and what makes it effective. Look for his in-depth analysis later this week.
For more coverage of low-field strength MRI, click here.
Significant weight loss can be alarming for a patient, especially if it is unintended and the reason behind it is unclear. In an article published in Emergency Radiology, researchers reveal that CT can be useful in pinpointing the cause of an unexpected, rapid loss of pounds. A more detailed explanation of their findings will be published later this week.
For additional coverage on weight loss, 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.