PMID- 28353309
OWN - NLM
STAT- MEDLINE
DCOM- 20180404
LR  - 20180404
IS  - 1898-018X (Electronic)
IS  - 1898-018X (Linking)
VI  - 24
IP  - 3
DP  - 2017
TI  - Cardiac magnetic resonance imaging derived quantification of myocardial ischemia 
      and scar improves risk stratification and patient management in stable coronary 
      artery disease.
PG  - 293-304
LID - 10.5603/CJ.a2017.0036 [doi]
AB  - BACKGROUND: Quantification of myocardial ischemia and necrosis might ameliorate 
      prognostic models and lead to improved patient management. However, no 
      standardized consensus on how to assess and quantify these parameters has been 
      established. The aim of this study was to quantify these variables by cardiac 
      magnetic resonance imaging (CMR) and to establish possible incremental 
      implications in cardiovascular risk prediction. METHODS: This study is a 
      retrospective analysis of patients with known or suspected coronary artery 
      disease (CAD) referred for adenosine perfusion CMR was performed. Myocardial 
      ischemia and necrosis were assessed and quantified using an algorithm based on 
      standard first-pass perfusion imaging and late gadolinium enhancement (LGE). The 
      combined primary endpoint was defined as cardiac death, non-fatal myocardial 
      infarction, and stroke. RESULTS: 845 consecutive patients were enrolled into the 
      study. During the median follow-up of 3.64 [1.03; 10.46] years, 61 primary 
      endpoints occurred. Patients with primary endpoint showed larger extent of 
      ischemia (10.7 +/- 12.25% vs. 3.73 +/- 8.29%, p < 0.0001) and LGE (21.09 +/- 15.11% vs. 
      17.73 +/- 10.72%, p < 0.0001). A risk prediction model containing the extent of 
      ischemia and LGE proved to be superior in comparison to all other models (chi(2) 
      increase: from 39.678 to 56.676, integrated discrimination index: 0.3851, p = 
      0.0033, net reclassification index: 0.11516, p = 0.0071). The ben-eficial effect 
      of revascularization tended to be higher in patients with greater extents of 
      ischemia, though statistical significance was not reached. CONCLUSIONS: 
      Quantification of myocardial ischemia and LGE was shown to significantly improve 
      existing risk prediction models and might thus lead to an improvement in patient 
      management.
FAU - Buckert, Dominik
AU  - Buckert D
FAU - Cieslik, Maciej
AU  - Cieslik M
FAU - Tibi, Raid
AU  - Tibi R
FAU - Radermacher, Michael
AU  - Radermacher M
FAU - Rottbauer, Wolfgang
AU  - Rottbauer W
FAU - Bernhardt, Peter
AU  - Bernhardt P
AD  - Heart Clinic Ulm, Ulm, Germany, Germany. peter.bernhardt@herzklinik-ulm.de.
LA  - eng
PT  - Journal Article
DEP - 20170329
PL  - Poland
TA  - Cardiol J
JT  - Cardiology journal
JID - 101392712
SB  - IM
MH  - Adult
MH  - Aged
MH  - Coronary Artery Disease/complications/diagnosis/*therapy
MH  - Female
MH  - Follow-Up Studies
MH  - Germany
MH  - Humans
MH  - Incidence
MH  - Magnetic Resonance Imaging, Cine/*methods
MH  - Male
MH  - Middle Aged
MH  - Myocardial Infarction/*diagnosis/epidemiology/etiology
MH  - Myocardial Ischemia/*diagnosis/etiology/physiopathology
MH  - Myocardium/*pathology
MH  - Prognosis
MH  - Reproducibility of Results
MH  - Retrospective Studies
MH  - *Risk Assessment
MH  - Risk Factors
MH  - Severity of Illness Index
MH  - Stroke Volume
MH  - Time Factors
MH  - Ventricular Function, Left/*physiology
OTO - NOTNLM
OT  - cardiac magnetic resonance imaging
OT  - coronary artery disease
OT  - prognosis and outcomes
OT  - quantification of ischemia and necrosis
OT  - risk stratification
EDAT- 2017/03/30 06:00
MHDA- 2018/04/05 06:00
CRDT- 2017/03/30 06:00
PHST- 2016/08/23 00:00 [received]
PHST- 2017/02/24 00:00 [accepted]
PHST- 2017/03/27 00:00 [revised]
PHST- 2017/03/30 06:00 [pubmed]
PHST- 2018/04/05 06:00 [medline]
PHST- 2017/03/30 06:00 [entrez]
AID - VM/OJS/J/48524 [pii]
AID - 10.5603/CJ.a2017.0036 [doi]
PST - ppublish
SO  - Cardiol J. 2017;24(3):293-304. doi: 10.5603/CJ.a2017.0036. Epub 2017 Mar 29.