UNLABELLED: Ruptured coronary atherosclerotic plaques commonly cause acute myocardial infarction. It has recently been shown that active microcalcification in the coronary arteries, one of the features that characterizes vulnerable plaques at risk of rupture, can be imaged using (18)F-NaF PET. We aimed to determine whether a motion correction technique applied to gated (18)F-NaF PET images could enhance image quality and improve uptake estimates. METHODS: Seventeen patients with myocardial infarction (n = 7) or stable angina (n = 10) underwent (18)F-NaF PET and prospective coronary CT angiography. PET data were reconstructed in 4 different ways: the first was 1 gated bin (end-diastolic phase with 25% of the counts), the second was 4 gated bins (consecutive 25% segments), the third was 10 gated bins (consecutive 10% segments), and the fourth was ungated. Subsequently, with data from either 4 or 10 bins, gated PET images were registered using a local, nonlinear motion correction method guided by the extracted coronary arteries from CT angiography. Global noise levels and target-to-background ratios (TBR) defined on manually delineated coronary plaque lesions were compared to assess image quality and uptake estimates. RESULTS: Compared with the reference standard of using only 1 bin of PET data, motion correction using 10 bins of PET data reduced image noise by 46% (P < 0.0001). TBR in positive lesions for 10-bin motion-corrected data was 11% higher than for 1-bin data (1.98 [interquartile range, 1.70-2.37] vs. 1.78 [1.58-2.16], P = 0.0027) and 33% higher than for ungated data (1.98 [1.70-2.37] vs. 1.49 [1.39-1.88], P < 0.0001). CONCLUSION: Motion correction of gated (18)F-NaF PET/coronary CT angiography is feasible, reduces image noise, and increases TBR. This improvement may allow more reliable identification of vulnerable coronary artery plaques using (18)F-NaF PET.
UNLABELLED: Ruptured coronary atherosclerotic plaques commonly cause acute myocardial infarction. It has recently been shown that active microcalcification in the coronary arteries, one of the features that characterizes vulnerable plaques at risk of rupture, can be imaged using (18)F-NaF PET. We aimed to determine whether a motion correction technique applied to gated (18)F-NaF PET images could enhance image quality and improve uptake estimates. METHODS: Seventeen patients with myocardial infarction (n = 7) or stable angina (n = 10) underwent (18)F-NaF PET and prospective coronary CT angiography. PET data were reconstructed in 4 different ways: the first was 1 gated bin (end-diastolic phase with 25% of the counts), the second was 4 gated bins (consecutive 25% segments), the third was 10 gated bins (consecutive 10% segments), and the fourth was ungated. Subsequently, with data from either 4 or 10 bins, gated PET images were registered using a local, nonlinear motion correction method guided by the extracted coronary arteries from CT angiography. Global noise levels and target-to-background ratios (TBR) defined on manually delineated coronary plaque lesions were compared to assess image quality and uptake estimates. RESULTS: Compared with the reference standard of using only 1 bin of PET data, motion correction using 10 bins of PET data reduced image noise by 46% (P < 0.0001). TBR in positive lesions for 10-bin motion-corrected data was 11% higher than for 1-bin data (1.98 [interquartile range, 1.70-2.37] vs. 1.78 [1.58-2.16], P = 0.0027) and 33% higher than for ungated data (1.98 [1.70-2.37] vs. 1.49 [1.39-1.88], P < 0.0001). CONCLUSION: Motion correction of gated (18)F-NaF PET/coronary CT angiography is feasible, reduces image noise, and increases TBR. This improvement may allow more reliable identification of vulnerable coronary artery plaques using (18)F-NaF PET.
Authors: Jacek Kwiecinski; Daniel S Berman; Sang-Eun Lee; Damini Dey; Sebastien Cadet; Martin L Lassen; Guido Germano; Maurits A Jansen; Marc R Dweck; David E Newby; Hyuk-Jae Chang; Mijin Yun; Piotr J Slomka Journal: J Nucl Med Date: 2018-09-13 Impact factor: 10.057
Authors: Stephanie Marchesseau; Aruni Seneviratna; A Therese Sjöholm; Daphne Liang Qin; Jamie X M Ho; Derek J Hausenloy; David W Townsend; A Mark Richards; John J Totman; Mark Y Y Chan Journal: J Nucl Cardiol Date: 2017-05-12 Impact factor: 5.952
Authors: Philip M Robson; Marc R Dweck; Maria Giovanna Trivieri; Ronan Abgral; Nicolas A Karakatsanis; Johanna Contreras; Umesh Gidwani; Jagat P Narula; Valentin Fuster; Jason C Kovacic; Zahi A Fayad Journal: JACC Cardiovasc Imaging Date: 2017-01-18
Authors: Martin Lyngby Lassen; Jacek Kwiecinski; Sebastien Cadet; Damini Dey; Chengjia Wang; Marc R Dweck; Daniel S Berman; Guido Germano; David E Newby; Piotr J Slomka Journal: J Nucl Med Date: 2018-11-15 Impact factor: 10.057
Authors: Tao Sun; Yoann Petibon; Paul K Han; Chao Ma; Sally J W Kim; Nathaniel M Alpert; Georges El Fakhri; Jinsong Ouyang Journal: Med Phys Date: 2019-10-08 Impact factor: 4.071