Top Five Radiology Content of 2024
Touching on a variety of topics in radiology, here are the top five most well-viewed content from Diagnostic Imaging in 2024.
As we come to the end of 2024, we take a look back at some of the highest viewed content from Diagnostic Imaging of the past year with topics ranging from MRI-related claustrophobia and CMS coverage of computed tomography (CT) colonography to the use of PSMA PET/CT for oligometastatic prostate cancer and potential solutions to address radiology workforce issues. Review the slideshow below to see highlighted content from the past year.
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).
The Reading Room Podcast: Current Perspectives on the Updated Appropriate Use Criteria for Brain PET
March 18th 2025In a new podcast, Satoshi Minoshima, M.D., Ph.D., and James Williams, Ph.D., share their insights on the recently updated appropriate use criteria for amyloid PET and tau PET in patients with mild cognitive impairment.
Could Lymph Node Distribution Patterns on CT Improve Staging for Colon Cancer?
April 11th 2025For patients with microsatellite instability-high colon cancer, distribution-based clinical lymph node staging (dCN) with computed tomography (CT) offered nearly double the accuracy rate of clinical lymph node staging in a recent study.
Could Ultrafast MRI Enhance Detection of Malignant Foci for Breast Cancer?
April 10th 2025In a new study involving over 120 women, nearly two-thirds of whom had a family history of breast cancer, ultrafast MRI findings revealed a 5 percent increase in malignancy risk for each second increase in the difference between lesion and background parenchymal enhancement (BPE) time to enhancement (TTE).
Study Suggests AI Software May Offer Standalone Value for X-Ray Detection of Pediatric Fractures
April 9th 2025Artificial intelligence (AI) software demonstrated a 92 percent sensitivity for detecting fractures in a study involving over 1,600 X-rays from a tertiary pediatric emergency department.
