Jeff Hall

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.

A deep learning model developed for predicting BI-RADS assessments from dynamic contrast-enhanced (DCE) breast MRI had over a 14 percent lower AUC than radiologist evaluation in external validation testing.

Offering telescoping and high-flow configurations, the TriNav Advance device reportedly provides interventional radiologists with improved access to small distal vessels during liver embolization procedures.

The CARE Chest X-Ray (CXR) Triage software reportedly bolsters consistent flagging of suspicious chest X-rays for lung collapse and pneumomediastinum across reviewing readers of different experience levels.

In a study involving over 700 participants who had chest CT and brain MRI, those with diabetes and lower vertebral bone mineral density (vBMD) had a nearly five percent faster total accumulation of white matter hyperintensity (WMH) in comparison to those without diabetes.

Indicated for the treatment of foregut, midgut and hindgut neuroendocrine tumors, the radiopharmaceutical Bravnetsa is reportedly bioequivalent and therapeutically equivalent to the previously FDA-approved Lutathera.

Newly cleared findings for the adjunctive AI platform a2z-Abdo-Triage include acute appendicitis, renal traumatic injury, ureteral stone and retroperitoneal hematoma.

In multivariable external testing, tumor structure habitat phenotypes from pre-treatment MRI revealed more than a doubling of recurrence risk for women with stage 2 and stage 3 breast cancer.

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

Reportedly one of the first FDA-cleared chest X-ray AI software platforms derived from a foundation model, the Chest Xray software facilitates detection and localization of lung nodules, pneumothorax, mediastinal abnormalities and other thoracic abnormalities.

Incorporating structural MRI to improve PET imaging resolution, the MICSI-PET software also offers automated Centiloid quantification from amyloid PET scans.

For patients with intermediate-risk prostate cancer, those with lower apparent diffusion coefficient (ADC) values on pre-treatment DWI MRI had a fourfold higher prevalence of distant metastasis in a study with a 10.3-year median follow-up.

In the second of a two-part podcast episode, Lauren Nicola, MD, Christoph Wald, MD, PhD, MBA, and Peter Shen discuss challenges with evaluating value and ROI for AI software, the physician time required to do so, and possible solutions to facilitate improved clarity and consistency with AI reimbursement.

In a study involving over 2,800 people who had brain MRI scans, researchers found that people in the most disadvantaged neighborhoods had 37 percent higher white matter hyperintensity volume (WMHV) on average in comparison to people in the least disadvantaged areas.