55M with treated lymphoma has spotty T1-hypo marrow on f/u MRI. Recurrence? Benign reconversion? Hedge or add value? Learn how to read bone marrow MRI like a pro in this new @Radiology_RSNA publication https://t.co/mnc2yBqmL5 #RadInTraining @RITEditor

🩻 Check out this article by @ahlawat_shivani and @LauraMFayad! A marrow-specific MRI protocol helps distinguish normal bone marrow and red marrow reconversion from disorders. #Radiology https://t.co/tCAHM2lYqs

Have you heard of Sybil, the deep learning model to predict lung cancer risk on CT? 🔮 A recent study in @radiology_RSNA tested the algorithm on an external cohort https://t.co/NP6AuBxNVa 👇Here is what the Authors found A #RadInTraining #Tweetorial🧵 @RITEditor #AI #lungcancer

🎙️ Don't miss out! @LindaChuMD and @siddograMD chat with Jessie Gommers & @IoannisNL about how AI is transforming radiologist performance and visual search in screening mammography. Tune in to the podcast now! 🎧

1/10 Can a radiology-trained LLM beat GPT-4o at writing impressions? Results of this 🧵 may surprise you! 👇 #RadInTraining #Tweetorial of a study just published in @radiology_rsna @RITEditor @VChernyakMD @DrLindaMoy https://t.co/TqXnG9s5jY

Chronological age is an imperfect measure of health. CT biomarkers—muscle, fat, bone, and vascular calcification—combined with AI can provide reproducible, explainable estimates of biological age, improving risk prediction and clinical decision making. https://t.co/VOOrkR6TSQ

The full August issue of #Radiology is now online! The cover features images from the article by Xiaoxu Guo, MD & Yuhan Zhou, MD. 🩻 Explore the issue here ⬇️ https://t.co/8roGZEKlgY

#RIAM (Radiology in a Minute)@radiology_rsna Intratumoral Microbiome–related MRI Model for Predicting Breast Cancer Shrinkage Pattern Following Neoadjuvant Therapy. https://t.co/OEogbacO4F @RITEditor @RadiologyEditor @VChernyakMD #RadInTraining

🧠Volumetric segmentation and quantitative evaluation of paraspinal muscles on preoperative MRI scans of brachial plexus injury patients accurately distinguished between severity levels of spinal root injuries, correlating with intraoperative findings.🔍 https://t.co/ZnoBk9Jq0I

Middle neck nodal metastases in Nasopharyngeal carcinoma (NPC): linked to worse outcomes? In 9795 N1-N2 patients, MRI-detected middle neck involvement independently predicted higher risk of distant metastasis and death. @radiology_rsna @RITEditor #RadInTraining #Tweetorial 🧵

1/10 ❓Can imaging-based paraspinal muscle volumes quantification on preop MRI classify normal, partial, or total avulsion traumatic brachial plexus injuries (TBPIs) to improve surgical planning? @Radiology_RSNA #RadInTraining @RITEditor 👉A Tweetorial on: https://t.co/jp7mSpAC2e

1/8 🧠 How do #AI models like GPT understand medical text? It’s not a guess – it’s patterns & context. Latest @radiology_rsna manuscript explains how transformers process words in clinical reports👇 https://t.co/AGfovnYCUZ  @RITEditor #RadInTraining #Tweetorial

8/8 🚨Read the full article in @radiology_rsna at https://t.co/AGfovnYCUZ #RadInTraining  @RITEditor  @VChernyakMD  @DrLindaMoy  @RadiologyEditor

1/ Can thermal ablation replace surgery in early-stage #BreastCancer? A new phase II trial in @radiology_rsna compares 3 percutaneous ablation techniques to identify the best candidate for a future phase III trial. @RITEditor @VChernyakMD 🔗

1/9 🔎 Ever had your paper questioned over sample size? Determining the right sample size is critical—not only for statistical rigor but also ethical integrity. Whatever project you are planning, here’s what researchers often overlook! #RadRes #RadInTraining @radiology_rsna

🚨 #Radiology in a Minute @radiology_rsna 🚨 Significance of cardiac chamber volume ratios in prediction and clinical risk stratification of adverse cardiac events - @malakhoballah et al https://t.co/7gdnsEtALS @RITEditor @RadiologyEditor @VChernyakMD #RadInTraining

Read this great summary of a new @radiology_rsna manuscript - great way that #AI can help with #mammogram workflow

🚨 #Tweetorial 1/6 Hot off the press @Radiology_rsna: "MRI Evaluation of Liver Fat & Iron After GLP-1R/GCGR Dual Agonist" Tackling metabolic dysfunction-associated steatotic liver disease (MASLD) with 9.4T MRI!  #Radiology #RSNA #RadInTraining

What factors affect PPV of MRI for #prostate #cancer? Take 2 min to listen to #RadInTraining #RIAM video summarizing the latest ⁦@radiology_rsna publication & then read more at https://t.co/b6ldnw2KnQ RIAM.PPV.Prostate.MRI-twitter.mp4

🚨 A new episode of the @radiology_rsna podcast is now available! 🚨@LindaChuMD is joined by Drs. Sivakumaran, Poston, and Dunham to explore dementia biomarkers, clinical utility, and patient-centered research. Sponsored by GE HealthCare.