AJR Podcasts

Full article: https://www.ajronline.org/doi/10.2214/AJR.23.29826

Hong Linda Li, MD discusses a new article that examines the need for a comprehensive approach that integrates clinical, radiological, and histopathological data for accurate diagnosis and management of adrenal masses.

Full article: https://www.ajronline.org/doi/10.2214/AJR.23.29769

In this podcast, Bahram Mohajer, MD, MPH introduces a study on AI's role in assessing endotracheal tube positions on chest radiographs. The study demonstrates high sensitivity and specificity in identifying tube presence and positioning, especially in critical cases. The AI system's potential to expedite detection and reduce delays in repositioning is highlighted. While the study's strengths include a large sample size and multi-institutional data, the author acknowledges limitations such as the retrospective design and lack of clinical outcome data. The podcast concludes by emphasizing the promising impact of AI on radiologists' efficiency and patient safety, with the need for further validation and integration into diverse healthcare settings.

Full article: https://ajronline.org/doi/10.2214/AJR.23.29984

Robbie Hill, MD discusses an article in which the authors derive an optimal size threshold for determining retropharyngeal lymph node involvement in nasopharyngeal carcinoma (NPC) based on outcome predictions. The authors show that the optimally derived threshold of 6mm provides better outcome predictions and may lead to improved treatment decision-making for patients with NPC.

Full article: https://www.ajronline.org/doi/10.2214/AJR.23.29964

Xiao Xiao Tong, MD discusses an original research article that focuses on the pathological correlation of MRI scoring systems. The upgrade and downgrade rates from targeted biopsy to radical prostatectomy were not significantly different between patients whose MRI examinations were clinically interpreted using PI-RADS v2.0 or v2.1. Additional and alternative biopsy techniques with different accuracy rates should be considered in future research to implement the correlation between imaging findings and histology.

Full article: https://www.ajronline.org/doi/10.2214/AJR.23.29950

In this episode, Alessandro Micelli, MD discusses an article detailing the advantages that photon-counting detector (PCD) CT can give in the setting of lumbar spine CT, specifically in terms of better CNR and lower radiation dose exposure. This original research study represents first steps in the PCD CT era and will be useful to guide future studies to establish a standard protocol for specific indications of lumbar spine examinations.

Full article: https://www.ajronline.org/doi/10.2214/AJR.23.29670

Sid Dogra, MD discusses an AJR article in which the authors show that retained biopsy site markers following resection of breast lesions increases risk of residual malignancy, particularly in patients whose initial pathology suggested malignancy. Radiologists can improve patient care by more explicitly noting missing biopsy site markers and recommending early postoperative mammogram on initial intraoperative specimen radiographs.

Full article: https://www.ajronline.org/doi/10.2214/AJR.23.29655

Shruti Kumar, MD discusses an AJR study that compares the performance of mammography alone, standalone artificial intelligence (AI), ultrasound alone, and a combination of these methods in a sample of 1,325 women. The study suggests that adding AI to mammography and ultrasound does not provide significant benefit in cancer detection rates in patients with dense breasts. However, the study's limitations, including single-institution data and specific AI platform, must be considered before generalizing the results.

Full article: https://www.ajronline.org/doi/10.2214/ajr.23.29570

Childhood obesity is a growing epidemic globally. Precisely quantifying abdominal fat distribution on MRI could be valuable for research and clinical care, but manual segmentation is extremely tedious. Farzaneh Ghazi Sherbaf, MD discusses a recent study in which the authors developed and validated an AI method to automatically segment subcutaneous and visceral abdominal fat on MRI in adolescents. The work has implications for making obesity research and care more effective through automated, personalized abdominal fat mapping.

Full article: https://www.ajronline.org/doi/abs/10.2214/AJR.23.29607

When grading hepatic steatosis on MRI, we generally assume that chemical-shift images are needed. Robert Smalley, MD takes a look at a recent AJR article that proposes a simpler way using in-and-opposed-phase images. How good is it, and is it ready for clinical adoption?

Full article: https://www.ajronline.org/doi/10.2214/ajr.23.29674

Peter Gunderman, MD discusses a recent study that finds artificial intelligence can accurately predict the pathology of pure ground glass nodules, at least in the subset of nodules representing variants of adenocarcinoma.