Jeff Hall

In a new podcast episode, Joseph Cavallo, MD, MBA, offered his perspective on AI integration, potential efficiency gains, navigating post-deployment monitoring and how to incorporate AI literacy into radiology resident training.

The FFR-IQ software recently demonstrated a 92.2 percent sensitivity for non-invasive estimation of fractional flow reserve (FFRC) based on coronary CT angiography (CCTA) scans.

A Kaiser score > 5 with breast MRI demonstrated a 97 percent sensitivity and 87.9 percent specificity for predicting malignancy in patients with BI-RADS 0 or 4 presentations on mammography and breast ultrasound, according to a new study.

In a recent interview, Francesco Giganti, MD, PhD, discussed findings from a recent multicenter study demonstrating the ability of an AI software to provide significant clarity to initial PI-RADS 3 assessments on MRI and facilitate a nearly 19 percent reduction in unnecessary prostate biopsies.

The NEXT-Cue AI software, which incorporates analysis of brain MRI scans, reportedly facilitates prognostic assessments of potential progression from mild cognitive impairment (MCI) to Alzheimer’s disease within five years.

In a new podcast episode, Amir Iravani, MD, FRACP, discusses emerging dosimetry data from the COMPETE trial for 177Lu-edotreotide and how it may help facilitate more personalized treatment for patients with gastroenteropancreatic neuroendocrine tumors (GEP-NETs).

In a recent interview, Phillip Koo, MD, discussed emerging trends with AI, theranostics and empowered patients, and how these developments may lead to challenges and potential opportunities for radiologists and nuclear medicine physicians.

Catch up on the top radiology content of the past week.

Assessing breast MRI scans, pathology and clinical data, the AI-powered TumorSight Risk software reportedly provides five- and 10-year risk for breast cancer recurrence for women with HR+, HER2-negative stage I-IIIA breast cancer.

Tightness of the high-convexity sulci (THC) on brain MRI was associated with nearly threefold higher odds of cognitive decline over five to seven years of follow-up, according to a new prospective study involving over 2,100 community-dwelling senior citizens.

An AI model for prostate MRI offered an 89 percent AUC for prostate cancer detection in external validation testing, according to a newly published international multicenter study.

In a recent episode of our Molecular Imaging in Focus series, Jack Andrews, MD, discussed pertinent findings from a recent intra-patient comparative study of PSMA PET agents in men with recurrent prostate cancer presented at the recent ASTRO conference.

The use of adjunctive CT bone reading software in women with breast cancer detected between 8 to 22 percent more metastatic lesions for reviewing radiologists and reduced CT interpretation time by 50 percent or more, according to a new study.

Catch up on the top radiology content of the past week.

In the third of a three-part podcast episode, Wendie Berg, MD, PhD, FACR, FSBI, Manisha Bahl, MD, and Amy Patel, MD discuss recent developments with autonomous AI in breast imaging and share their perspective on the overall potential of AI to help mitigate the radiologist shortage.

In a recent interview, Amir Iravani, MD, FRACP, discussed the radiotherapeutic agent 177Lu-edotreotide and new dosimetry data from the COMPETE trial that was recently presented at the ASTRO conference.

The cloud-based NextMR platform reportedly provides automated 3D bone images of conventional spine MRI images in less than 60 seconds.

Incorporation of pseudocapsule presence into a modified Clear Cell Likelihood Score (m-ccLS) was associated with a greater than 11 percent higher AUC in differentiating benign and malignant renal masses on mpMRI, according to a new study.

For patients with hepatocellular carcinoma (HCC), perfusion beyond tumor margin on contrast-enhanced ultrasound that exceeds gray-scale ultrasound tumor measurement by 5 mm is associated with a 76 percent higher risk of worse recurrence-free survival, according to newly published research.

The AI-powered SwiftSight Body Composition software reportedly provides automated quantification of muscle and adipose tissue after a brief MRI scan.

In the second of a three-part podcast episode, Wendie Berg, MD, PhD, FACR, FSBI, Manisha Bahl, MD, and Amy Patel, MD discuss how to handle disagreements with adjunctive AI in breast imaging, whether to include AI assessments in PACS, and whether patients should pay for the use of adjunctive AI.

Catch up on the top radiology content of the past week.

Magnetic resonance imaging offered a 29 percent higher sensitivity than CT for differentiating liver metastases, but CT provided 12 percent higher sensitivity than MRI for assessing vascular invasion, according to a new 40-study meta-analysis.

In a recent interview with Diagnostic Imaging, Joseph Cavallo, MD, MBA, offered insights on post-deployment monitoring with AI, the potential for improved workflow efficiency and the ongoing challenge of balancing essential clinical skills and AI literacy in the training of radiology residents and fellows.

In the first of a three-part podcast episode, Wendie Berg, MD, PhD, FACR, FSBI, Manisha Bahl, MD, and Amy Patel, MD share insights on the utility of AI in breast imaging with respect to potential advantages, current concerns and future directions.

The BiPASS program, which combines 68Ga PSMA PET imaging with prostate MRI prior to the use of prostate biopsy, is slated to be evaluated in an impending phase 3 trial.

For patients with localized prostate cancer, stereotactic body radiotherapy (SBRT) offered comparable freedom from biochemical/clinical failure at eight years and nearly 40 percent lower urinary incontinence in comparison to radical prostatectomy, according to research presented at the ASTRO conference.

For patients with small cell lung cancer (SCLC), there was a 40 percent improvement in cognitive failure-free survival (CFFS) with brain MRI alone in comparison to the combination of brain MRI and prophylactic cranial irradiation (PCI), according to research presented at the ASTRO conference.

Catch up on the top radiology content of the past week.

In a recent interview, Shadpour Demehri, MD, discussed new research examining connections between deep learning assessment of bone mineral density on chest CT, brain MRI data and the potential for enhanced risk stratification in patients with diabetes.