American Institute of Ultrasound in Medicine (AIUM) Annual Convention

Mar 20th, 2020Mar 24th, 2020
New York City, NY
US
http://www.aium.org
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Group mean C-11 PBR28 SUVR maps of females with ASD (top) and female controls (middle). Statistical map from voxelwise comparison of C-11 PBR28 SUVR between groups, controlled for age and TSPO genotype, shows elevated regional TSPO levels relative to whole brain mean in the midcingulate cortex and splenium of the corpus callosum in ASD (N = 12) compared with controls (N = 10) (Z > 2.3, pcluster) (bottom). TSPO = translocator protein, ASD = autism spectrum disorder, CON = control, SUVR = standardized uptake value ratio, N = number. Image and caption courtesy of Neuropsychopharmacology.
PET/MRI reveals sex differences in patients with autism
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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.
AI proposed to help radiologists detect child abuse injuries
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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 (TSPO).
April 18, 2024
Group mean C-11 PBR28 SUVR maps of females with ASD (top) and female controls (middle). Statistical map from voxelwise comparison of C-11 PBR28 SUVR between groups, controlled for age and TSPO genotype, shows elevated regional TSPO levels relative to whole brain mean in the midcingulate cortex and splenium of the corpus callosum in ASD (N = 12) compared with controls (N = 10) (Z > 2.3, pcluster) (bottom). TSPO = translocator protein, ASD = autism spectrum disorder, CON = control, SUVR = standardized uptake value ratio, N = number. Image and caption courtesy of Neuropsychopharmacology.
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.
April 18, 2024
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Pisano speaks with AuntMinnie.com on new ARPA-H leadership role
By Amerigo Allegretto
Etta Pisano, MD, spoke with AuntMinnie.com on leading the Advancing Clinical Trials Readiness initiative, part of ARPA-H.
April 18, 2024
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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.
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POCUS used widely in lung ultrasound applications
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Some of the top domains for users of point-of-care ultrasound (POCUS) incorporate the technology for lung ultrasound applications.
April 17, 2024
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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.
FAPI-PET shows promise in patients with lung cancer
By Will Morton
FAPI-PET imaging could emerge as a new tool for assessing patients with single pulmonary tumors, especially in those with negative results on other scans.
April 15, 2024
F-18 FDG and Ga-68 FAPI-46 images of a 51-year-old woman with adenocarcinoma with lepidic growth pattern in right upper lobe. (A) Maximum-intensity-projection PET images. The lesion had F-18 FDG uptake below blood pool level but was strongly Ga-68 FAPI-46-positive. CT-guided biopsy led to pathologic diagnosis of adenocarcinoma, and the patient was treated by stereotactic body radiation therapy because of functional inoperability. Image courtesy of the Journal of Nuclear Medicine.
IMV: Nuclear medicine procedure volumes decrease
By Davin Korstjens
Total nuclear medicine patient study volumes decreased between 2021 and 2023, according to a newly published IMV 2024 Nuclear Medicine Market Outlook Report.
April 15, 2024
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Can brain MRI for emergency imaging of dizziness be more effective?
By Kate Madden Yee
Predictors for acute conditions such as stroke could make brain MRI more effective in patients who present in the emergency department with dizziness or vertigo, according to recent research.
April 15, 2024
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