Imaging the Brain and Criminal Mind

Sep 20th, 2013
Kansas City, MO
US
https://store2.aheconline.com/
This one-of-a-kind course will begin with an introduction into the evolution of neuroimaging and psychiatry to set the stage for modern imaging methods.
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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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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
By Kate Madden Yee
A deep-learning model quantifies coronary plaque volume from coronary CT angiography (CCTA) images.
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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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The finding is from a prospective head-to-head comparison among 59 patients with suspicious lesions.
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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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