Amparo L Figueroa1, Amr Abdelbaky1, Quynh A Truong2, Erin Corsini1, Megan H MacNabb1, Zachary R Lavender1, Meredith A Lawler1, Steven K Grinspoon3, Thomas J Brady1, Khurram Nasir4, Udo Hoffmann1, Ahmed Tawakol5. 1. Cardiac MR PET CT Program, Department of Imaging and Division of Cardiology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts. 2. Cardiac MR PET CT Program, Department of Imaging and Division of Cardiology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts; Division of Cardiology, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts. 3. Program in Nutritional Metabolism, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts. 4. Center for Prevention and Wellness Research, Baptist Health South Florida, Department of Medicine, Herbert Wertheim College of Medicine, Department of Epidemiology, Robert Stempel College of Public Health, Florida International University, Miami, Florida; Ciccarone Center for Preventive Cardiology, Johns Hopkins University, Baltimore, Maryland. 5. Cardiac MR PET CT Program, Department of Imaging and Division of Cardiology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts; Division of Cardiology, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts. Electronic address: atawakol@partners.org.
Abstract
OBJECTIVES: This study sought to determine whether arterial inflammation measured by (18)F-fluorodeoxyglucose positron emission tomography ((18)F-FDG-PET) improves prediction of cardiovascular disease (CVD) beyond traditional risk factors. BACKGROUND: It is unknown whether arterial (18)F-FDG uptake measured with routine PET imaging provides incremental value for predicting CVD events beyond Framingham risk score (FRS). METHODS: We consecutively identified 513 individuals from 6,088 patients who underwent (18)F-FDG-PET and computed tomography (CT) imaging at Massachusetts General Hospital between 2005 and 2008 and who met additional inclusion criteria: ≥30 years of age, no prior CVD, and free of cancer. CVD events were independently adjudicated, while blinded to clinical data, using medical records to determine incident stroke, transient ischemic attack, acute coronary syndrome, revascularization, new-onset angina, peripheral arterial disease, heart failure, or CVD death. FDG uptake was measured in the ascending aorta (as target-to-background-ratio [TBR]), while blinded to clinical data. RESULTS: During follow-up (median 4.2 years), 44 participants developed CVD (2 per 100 person-years at risk). TBR strongly predicted subsequent CVD independent of traditional risk factors (hazard ratio: 4.71; 95% confidence interval [CI]: 1.98 to 11.2; p < 0.001) and (hazard ratio: 4.13; 95% CI: 1.59 to 10.76; p = 0.004) after further adjustment for coronary calcium score. Addition of arterial PET measurement to FRS scores improved the C-statistic (mean ± standard error 0.62 ± 0.03 vs. 0.66 ± 0.03). Further, incorporation of TBR into a model with FRS variables resulted in an integrated discrimination of 5% (95% CI: 0.36 to 9.87). Net reclassification improvements were 27.48% (95% CI: 16.27 to 39.92) and 22.3% (95% CI: 11.54 to 35.42) for the 10% and 6% intermediate-risk cut points, respectively. Moreover, TBR was inversely associated with the timing of CVD (beta -0.096; p < 0.0001). CONCLUSIONS: Arterial FDG uptake, measured from routinely obtained PET/CT images, substantially improved incident CVD prediction beyond FRS among individuals undergoing cancer surveillance and provided information on the potential timing of such events.
OBJECTIVES: This study sought to determine whether arterial inflammation measured by (18)F-fluorodeoxyglucose positron emission tomography ((18)F-FDG-PET) improves prediction of cardiovascular disease (CVD) beyond traditional risk factors. BACKGROUND: It is unknown whether arterial (18)F-FDG uptake measured with routine PET imaging provides incremental value for predicting CVD events beyond Framingham risk score (FRS). METHODS: We consecutively identified 513 individuals from 6,088 patients who underwent (18)F-FDG-PET and computed tomography (CT) imaging at Massachusetts General Hospital between 2005 and 2008 and who met additional inclusion criteria: ≥30 years of age, no prior CVD, and free of cancer. CVD events were independently adjudicated, while blinded to clinical data, using medical records to determine incident stroke, transient ischemic attack, acute coronary syndrome, revascularization, new-onset angina, peripheral arterial disease, heart failure, or CVD death. FDG uptake was measured in the ascending aorta (as target-to-background-ratio [TBR]), while blinded to clinical data. RESULTS: During follow-up (median 4.2 years), 44 participants developed CVD (2 per 100 person-years at risk). TBR strongly predicted subsequent CVD independent of traditional risk factors (hazard ratio: 4.71; 95% confidence interval [CI]: 1.98 to 11.2; p < 0.001) and (hazard ratio: 4.13; 95% CI: 1.59 to 10.76; p = 0.004) after further adjustment for coronary calcium score. Addition of arterial PET measurement to FRS scores improved the C-statistic (mean ± standard error 0.62 ± 0.03 vs. 0.66 ± 0.03). Further, incorporation of TBR into a model with FRS variables resulted in an integrated discrimination of 5% (95% CI: 0.36 to 9.87). Net reclassification improvements were 27.48% (95% CI: 16.27 to 39.92) and 22.3% (95% CI: 11.54 to 35.42) for the 10% and 6% intermediate-risk cut points, respectively. Moreover, TBR was inversely associated with the timing of CVD (beta -0.096; p < 0.0001). CONCLUSIONS: Arterial FDG uptake, measured from routinely obtained PET/CT images, substantially improved incident CVD prediction beyond FRS among individuals undergoing cancer surveillance and provided information on the potential timing of such events.
Authors: Markella V Zanni; Mabel Toribio; Gregory K Robbins; Tricia H Burdo; Michael T Lu; Amorina E Ishai; Meghan N Feldpausch; Amanda Martin; Kathy Melbourne; Virginia A Triant; Sujit Suchindran; Hang Lee; Udo Hoffmann; Kenneth C Williams; Ahmed Tawakol; Steven K Grinspoon Journal: JAMA Cardiol Date: 2016-07-01 Impact factor: 14.676
Authors: Lotte C A Stiekema; Erik S G Stroes; Simone L Verweij; Helina Kassahun; Lisa Chen; Scott M Wasserman; Marc S Sabatine; Venkatesh Mani; Zahi A Fayad Journal: Eur Heart J Date: 2019-09-01 Impact factor: 29.983
Authors: Amit K Dey; Aditya A Joshi; Abhishek Chaturvedi; Joseph B Lerman; Tsion M Aberra; Justin A Rodante; Heather L Teague; Charlotte L Harrington; Joshua P Rivers; Jonathan H Chung; Mohammad Tarek Kabbany; Balaji Natarajan; Joanna I Silverman; Qimin Ng; Gregory E Sanda; Alexander V Sorokin; Yvonne Baumer; Emily Gerson; Ronald B Prussick; Alison Ehrlich; Lawrence J Green; Benjamin N Lockshin; Mark A Ahlman; Martin P Playford; Joel M Gelfand; Nehal N Mehta Journal: JAMA Cardiol Date: 2017-09-01 Impact factor: 14.676