Study Examines Impact of Deep Learning on Fast MRI Protocols for Knee Pain
Ten-minute and five-minute knee MRI exams with compressed sequences facilitated by deep learning offered nearly equivalent sensitivity and specificity as an 18-minute conventional MRI knee exam, according to research presented recently at the RSNA conference.
Can AI Enhance PET/MRI Assessment for Extraprostatic Tumor Extension in Patients with PCa?
The use of an adjunctive machine learning model led to 17 and 21 percent improvements in the AUC and sensitivity rate, respectively, for PET/MRI in diagnosing extraprostatic tumor extension in patients with primary prostate cancer.
Can Radiomics Bolster Low-Dose CT Prognostic Assessment for High-Risk Lung Adenocarcinoma?
A 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.
Addressing Cybersecurity Issues in Radiology
In a recent interview at the RSNA conference, Raj Chopra, MD shared his insights on the continued rise of cyberattacks, the impact of these attacks in radiology and keys to prevention and effectively responding to such events.
Mammography Study Suggests DBT-Based AI May Help Reduce Disparities with Breast Cancer Screening
New research suggests that AI-powered assessment of digital breast tomosynthesis (DBT) for short-term breast cancer risk may help address racial disparities with detection and shortcomings of traditional mammography in women with dense breasts.
Can AI Facilitate Single-Phase CT Acquisition for COPD Diagnosis and Staging?
The authors of a new study found that deep learning assessment of single-phase CT scans provides comparable within-one stage accuracies to multiphase CT for detecting and staging chronic obstructive pulmonary disease (COPD).
Study Shows Merits of CTA-Derived Quantitative Flow Ratio in Predicting MACE
For patients with suspected or known coronary artery disease (CAD) without percutaneous coronary intervention (PCI), researchers found that those with a normal CTA-derived quantitative flow ratio (CT-QFR) had a 22 percent higher MACE-free survival rate.
Can MRI-Based AI Bolster Biopsy Decision-Making in PI-RADS 3 Cases?
In patients with PI-RADS 3 lesion assessments, the combination of AI and prostate-specific antigen density (PSAD) level achieved a 78 percent sensitivity and 93 percent negative predictive value for clinically significant prostate cancer (csPCa), according to research presented at the Radiological Society of North American (RSNA) conference.
Assessing MACE Risk in Women: Can an Emerging Model with SPECT MPI Imaging Have an Impact?
In research involving over 2,200 women who had SPECT MPI exams, researchers found that those who had a high score with the COronary Risk Score in WOmen (CORSWO) model had a greater than fourfold higher risk of major adverse coronary events (MACE).
Can an Emerging AI Software for DBT Help Reduce Disparities in Breast Cancer Screening?
In a recent interview, Sarah Friedewald, MD, discussed new study findings for an adjunctive AI software for digital breast tomosynthesis (DBT) that revealed nearly equivalent sensitivity and specificity rates for breast cancer across a diverse cohort.
In a multicenter study involving over 747,000 women who had mammography screening, those who paid for AI-enhanced screening had a 21 percent higher recall rate and a 15 percent higher positive predictive value (PPV) for breast cancer, according to research presented at the Radiological Society of North America (RSNA) conference.
Skeletal Muscle Loss and Dementia: What Emerging MRI Research Reveals
In a recent interview at the RSNA conference, Shadpour Demehri, MD and Kamyar Moradi, MD discussed new brain MRI research findings that demonstrated a link between increased dementia risk and sarcopenia with the temporalis muscle.