Judy Burleson

CT
6 tips for joining a CT lung cancer screening registry
Imaging facilities across the U.S. are beginning to provide CT lung cancer screening -- and they are getting Medicare payment for it as well. But to get paid, you have to participate in a CT lung cancer registry. In this article, Judy Burleson of the American College of Radiology offers six tips for getting started.
April 16, 2017
2016 12 21 15 11 05 414 Lung Cancer 400
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Two representative cases demonstrate the performance of PlaqueSegNet for coronary plaque segmentation. (A–D) Coronary CT angiography (CCTA) and intravascular US (IVUS) images in a 65-year-old male patient with chest pain for two months show plaque. (A) Cross-sectional IVUS image shows a lipid-rich plaque (hypoechoic, arrows). (B) Axial and (C) cross-sectional CCTA images show the same plaque (low-attenuation area, yellow line and arrows) in the proximal left anterior descending artery. (D) PlaqueSegNet segmentation of the noncalcified plaque (yellow shading) and coronary lumen (green shading) in the cross-sectional image. (E–G) CCTA images in a 57-year old female patient with chest pain for three months show multiple plaques. (E) Volume-rendered CCTA image of the coronary tree shows PlaqueSegNet plaque segmentation (yellow) in the right and left coronary arteries. (F, G) PlaqueSegNet segmentation delineates a mixed plaque (yellow shading) and coronary lumen (green shading) in the left main artery and proximal-to-mid left anterior descending artery.
CT
AI plus CCTA cuts plaque analysis time, predicts cardiac event risk
A deep-learning model quantifies coronary plaque volume from coronary CT angiography (CCTA) images.
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A 65-y-old man with HCC and liver cirrhosis confirmed by MRI. Ga-68 FAPI-46 PET/CT demonstrates increased focal uptake (SUVmax, 13.26, and TBRmax, 2.89) in liver, whereas F-18 FDG-PET/CT scans showed non–F-18 FDG-avid lesion (SUVmax, 3.24, and TBRmax, 1.43), indicated by solid arrows. Additionally, histologically proven adenocarcinoma in colon transversum was identified as pathologic with Ga-68 FAPI-46 alone (dashed arrows).
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AI plus CCTA cuts plaque analysis time, predicts cardiac event risk
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Two representative cases demonstrate the performance of PlaqueSegNet for coronary plaque segmentation. (A–D) Coronary CT angiography (CCTA) and intravascular US (IVUS) images in a 65-year-old male patient with chest pain for two months show plaque. (A) Cross-sectional IVUS image shows a lipid-rich plaque (hypoechoic, arrows). (B) Axial and (C) cross-sectional CCTA images show the same plaque (low-attenuation area, yellow line and arrows) in the proximal left anterior descending artery. (D) PlaqueSegNet segmentation of the noncalcified plaque (yellow shading) and coronary lumen (green shading) in the cross-sectional image. (E–G) CCTA images in a 57-year old female patient with chest pain for three months show multiple plaques. (E) Volume-rendered CCTA image of the coronary tree shows PlaqueSegNet plaque segmentation (yellow) in the right and left coronary arteries. (F, G) PlaqueSegNet segmentation delineates a mixed plaque (yellow shading) and coronary lumen (green shading) in the left main artery and proximal-to-mid left anterior descending artery.
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