Dr. Ruud Pijnappel, PhD

Breast
6 vital steps to ensure success in breast screening
Screening for breast cancer works, but it requires a solid infrastructure, consisting of rigorous training and education, monitoring, auditing, and continuous adjustment, Dr. Ruud Pijnappel, PhD, from the Netherlands told delegates on the second day of the Total Radiology conference at Arab Health 2019.
January 29, 2019
2019 01 29 23 28 4154 Pijnappel Ruud 20190129234809
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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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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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