Xujiao Chen1, Yuxue Dang1, Hong Hu1, Shaowei Ma2, Yue Ma1, Kunhua Wang3, Ting Liu4, Xiaomei Lu5, Yang Hou1. 1. Radiology Department, Shengjing Hospital of China Medical University, Shenyang, China. 2. Department of Cardiology, Shengjing Hospital of China Medical University, Shenyang, China. 3. Radiology Department, People's Hospital of Liaoning Province, Shenyang, China. 4. Radiology Department, the First Affiliated Hospital of China Medical University, Shenyang, China. 5. CT Clinical Science, Philips Healthcare, Shenyang, China.
Abstract
BACKGROUND: The pericoronary fat attenuation index (FAI) derived from conventional polychromatic computed tomography (CT) can capture the presence of coronary inflammation. However, conventional polychromatic CT has limitations in material component differentiation, and spectral CT could have a better ability to discriminate tissue characteristics. Hence, this study sought to assess pericoronary adipose tissue (PCAT) attenuation using spectral CT and explore its association with atherosclerotic plaque characteristics. METHODS: We enrolled 104 patients with coronary atherosclerosis who met the inclusion criteria and underwent coronary CT angiography with dual-layer spectral detector computed tomography (SDCT). Plaque anatomical characteristics were measured, and the PCAT attenuation was assessed by polychromatic images (CTpoly), virtual mono-energetic images at 40 keV (CT40 keV), the slope of spectral attenuation curve (λHU), and the effective atomic number (Zeff). The association of PCAT attenuation indicators with the presence of high-risk plaques was analyzed, along with the indicators' ability to identify high-risk plaques. RESULTS: PCAT attenuation indicators around high-risk plaques were higher than those around non-high-risk plaques, especially CT40 keV [-153.76±24.97 (non-high-risk plaque) vs. -119.87±22.74 (high-risk plaque), P<0.001]. CT40 keV was a predictive factor of high-risk plaques, and high CT40 keV (≥-120.60 HU) could assist in the identification of high-risk plaques, with an area under the curve of 0.883 (95% CI: 0.83-0.94, P<0.05). CONCLUSIONS: PCAT surrounding high-risk plaques showed higher attenuation; a finding that has been associated with coronary artery inflammation. The metrics derived from SDCT, especially CT40 keV, showed higher discriminatory power for detecting changes in PCAT attenuation than polychromatic CT. PCAT attenuation assessed by CT40 keV may provide a novel imaging marker of plaque vulnerability. 2021 Quantitative Imaging in Medicine and Surgery. All rights reserved.
BACKGROUND: The pericoronary fat attenuation index (FAI) derived from conventional polychromatic computed tomography (CT) can capture the presence of coronary inflammation. However, conventional polychromatic CT has limitations in material component differentiation, and spectral CT could have a better ability to discriminate tissue characteristics. Hence, this study sought to assess pericoronary adipose tissue (PCAT) attenuation using spectral CT and explore its association with atherosclerotic plaque characteristics. METHODS: We enrolled 104 patients with coronary atherosclerosis who met the inclusion criteria and underwent coronary CT angiography with dual-layer spectral detector computed tomography (SDCT). Plaque anatomical characteristics were measured, and the PCAT attenuation was assessed by polychromatic images (CTpoly), virtual mono-energetic images at 40 keV (CT40 keV), the slope of spectral attenuation curve (λHU), and the effective atomic number (Zeff). The association of PCAT attenuation indicators with the presence of high-risk plaques was analyzed, along with the indicators' ability to identify high-risk plaques. RESULTS: PCAT attenuation indicators around high-risk plaques were higher than those around non-high-risk plaques, especially CT40 keV [-153.76±24.97 (non-high-risk plaque) vs. -119.87±22.74 (high-risk plaque), P<0.001]. CT40 keV was a predictive factor of high-risk plaques, and high CT40 keV (≥-120.60 HU) could assist in the identification of high-risk plaques, with an area under the curve of 0.883 (95% CI: 0.83-0.94, P<0.05). CONCLUSIONS: PCAT surrounding high-risk plaques showed higher attenuation; a finding that has been associated with coronary artery inflammation. The metrics derived from SDCT, especially CT40 keV, showed higher discriminatory power for detecting changes in PCAT attenuation than polychromatic CT. PCAT attenuation assessed by CT40 keV may provide a novel imaging marker of plaque vulnerability. 2021 Quantitative Imaging in Medicine and Surgery. All rights reserved.
Authors: Balaji Tamarappoo; Damini Dey; Haim Shmilovich; Ryo Nakazato; Heidi Gransar; Victor Y Cheng; John D Friedman; Sean W Hayes; Louise E J Thomson; Piotr J Slomka; Alan Rozanski; Daniel S Berman Journal: JACC Cardiovasc Imaging Date: 2010-11
Authors: Markus Goeller; Stephan Achenbach; Sebastien Cadet; Alan C Kwan; Frederic Commandeur; Piotr J Slomka; Heidi Gransar; Moritz H Albrecht; Balaji K Tamarappoo; Daniel S Berman; Mohamed Marwan; Damini Dey Journal: JAMA Cardiol Date: 2018-09-01 Impact factor: 14.676
Authors: Michael T Lu; Jakob Park; Khristine Ghemigian; Thomas Mayrhofer; Stefan B Puchner; Ting Liu; Jerome L Fleg; James E Udelson; Quynh A Truong; Maros Ferencik; Udo Hoffmann Journal: Atherosclerosis Date: 2016-05-20 Impact factor: 5.162
Authors: Sebastian Ehn; Thorsten Sellerer; Daniela Muenzel; Alexander A Fingerle; Felix Kopp; Manuela Duda; Kai Mei; Bernhard Renger; Julia Herzen; Julia Dangelmaier; Benedikt J Schwaiger; Andreas Sauter; Isabelle Riederer; Martin Renz; Rickmer Braren; Ernst J Rummeny; Franz Pfeiffer; Peter B Noël Journal: J Appl Clin Med Phys Date: 2017-12-20 Impact factor: 2.102
Authors: Evangelos K Oikonomou; Mohamed Marwan; Milind Y Desai; Jennifer Mancio; Alaa Alashi; Erika Hutt Centeno; Sheena Thomas; Laura Herdman; Christos P Kotanidis; Katharine E Thomas; Brian P Griffin; Scott D Flamm; Alexios S Antonopoulos; Cheerag Shirodaria; Nikant Sabharwal; John Deanfield; Stefan Neubauer; Jemma C Hopewell; Keith M Channon; Stephan Achenbach; Charalambos Antoniades Journal: Lancet Date: 2018-08-28 Impact factor: 79.321