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:
The COVID-19 pandemic has made already difficult purchasing decisions even harder for many organizations. Is it possible for organizations to hit the sweet spot in investing in new technologies and controlling costs? This week, Guido Stoeckmann, regional sales manager for Dunlee, a medical imaging components manufacturer, offers guidance on how you can – and should – re-define your imaging technology investments. Look for his column later this week.
For more coverage based on industry expert insights and research, subscribe to the Diagnostic Imaging e-Newsletter here.
Recent conversations around low-dose CT screening for lung cancer have pointed out its low participation rates and discussed its efficacy. This week, however, in research presented at the 2021 World Conference on Lung Cancer, investigators from Taiwan are sharing their results on the performance of the screening in a never-smoker population. Look for our coverage of their encouraging results later this week.
For additional low-dose CT screening coverage, click here.
Treatments for prostate cancer, such as surgery or radiation therapy, are effective, but they often bring unwanted side effects. This week, in Radiology, investigators will share the outcomes of their work with a different technique that can be used to treat intermediate-risk prostate cancer. Keep your eyes open for details about their study.
For additional coverage of prostate cancer, click here.
Meta-Analysis Shows Merits of AI with CTA Detection of Coronary Artery Stenosis and Calcified Plaque
April 16th 2025Artificial intelligence demonstrated higher AUC, sensitivity, and specificity than radiologists for detecting coronary artery stenosis > 50 percent on computed tomography angiography (CTA), according to a new 17-study meta-analysis.
New bpMRI Study Suggests AI Offers Comparable Results to Radiologists for PCa Detection
April 15th 2025Demonstrating no significant difference with radiologist detection of clinically significant prostate cancer (csPCa), a biparametric MRI-based AI model provided an 88.4 percent sensitivity rate in a recent study.
Can CT-Based AI Radiomics Enhance Prediction of Recurrence-Free Survival for Non-Metastatic ccRCC?
April 14th 2025In comparison to a model based on clinicopathological risk factors, a CT radiomics-based machine learning model offered greater than a 10 percent higher AUC for predicting five-year recurrence-free survival in patients with non-metastatic clear cell renal cell carcinoma (ccRCC).