Hot Topics in Radiology: Advanced Applications and Artificial Intelligence

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MR elastography effective for assessing liver stiffness in children
By Kate Madden Yee
MR elastography is an effective technique for noninvasive monitoring of liver stiffness -- a surrogate for fibrosis -- in children and young adults with autoimmune liver disease, researchers have reported.
April 19, 2024
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High breast density tied to impaired recurrence-free cancer survival
By Amerigo Allegretto
Recurrence-free breast cancer survival is less likely in women with high breast density compared with women with low density.
April 19, 2024
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Can ChatGPT ‘data mine’ patient reports for stroke registries?
By Will Morton
ChatGPT-4 appears useful for extracting details from reports on thrombectomy procedures in stroke patients, a labor-intensive and error-prone task currently performed by human readers.
April 19, 2024
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PET/MRI reveals sex differences in patients with autism
By Will Morton
PET/MRI shows that young women with autism spectrum disorder have increased brain metabolism associated with translocator protein.
April 18, 2024
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Radiologist consultation improves patients' LCS attitudes
By Kate Madden Yee
Consulting with a radiologist boosts patients' attitudes toward lung cancer screening (LCS) and their interest in quitting smoking, researchers have reported.
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Pisano speaks with AuntMinnie.com on new ARPA-H leadership role
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Etta Pisano, MD, spoke with AuntMinnie.com on leading the Advancing Clinical Trials Readiness initiative, part of ARPA-H.
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AI proposed to help radiologists detect child abuse injuries
By Will Morton
A team at Michigan State University has developed an AI model designed to detect rib fractures in children under 3 years old.
April 17, 2024
Test set images with ground truth (teal, red) and model predictions (green, yellow), with true positives (green), false positives (yellow), and false negatives (red). Predictions from the 6x-YOLOv5 ensemble trained on histogram equalized input images with a y = 0.2 avalanche scheme, achieving 0.536 precision, 0.795 recall, and 0.723 F2 score. Image and caption courtesy of Scientific Reports.
Tailored lung cancer screening model helps determine nodule follow-up
By Kate Madden Yee
A personalized lung cancer screening model used with patients with pulmonary nodules identified on low-dose CT helps clinicians determine how to follow up better than rule-based protocols, researchers have found.
April 17, 2024
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POCUS used widely in lung ultrasound applications
By Amerigo Allegretto
Some of the top domains for users of point-of-care ultrasound (POCUS) incorporate the technology for lung ultrasound applications.
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CT-based deep learning identifies patients at further lung cancer risk
By Kate Madden Yee
A CT-based deep learning model can identify individuals with clinical stage IA non-small cell lung cancer (NSCLC) at high risk of further disease, researchers have found.
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ChatGPT-4 matches radiologists in flagging errors on reports
By Will Morton
ChatGPT-4 matched radiologists when tasked with detecting errors in imaging reports, with the study suggesting the technology may be useful for improving reporting accuracy.
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Deep-learning model determines breast tumor staging
By Amerigo Allegretto
A deep-learning model based on mammographic images can determine tumor staging and sentinel lymph node metastasis in breast cancer patients.
April 16, 2024
Researchers explain the data preparation and structure of a proposed CNN-based deep learning model using mammography features to determine breast tumor staging. The image is available for use under a Creative Commons license: CC BY-NC-ND 4.0 DEED Attribution-NonCommercial-NoDerivs 4.0 International.
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