title: A new automatic algorithm for quantification of myocardial infarction imaged by late gadolinium enhancement cardiovascular magnetic resonance: experimental validation and comparison to expert delineations in multi-center, multi-vendor patient data.
abstract: Late gadolinium enhancement (LGE) cardiovascular magnetic resonance (CMR) using magnitude inversion recovery (IR) or phase sensitive inversion recovery (PSIR) has become clinical standard for assessment of myocardial infarction (MI). However, there is no clinical standard for quantification of MI even though multiple methods have been proposed. Simple thresholds have yielded varying results and advanced algorithms have only been validated in single center studies. Therefore, the aim of this study was to develop an automatic algorithm for MI quantification in IR and PSIR LGE images and to validate the new algorithm experimentally and compare it to expert delineations in multi-center, multi-vendor patient data.
  
  
  
  The new automatic algorithm, EWA (Expectation Maximization, weighted intensity, a priori information), was implemented using an intensity threshold by Expectation Maximization (EM) and a weighted summation to account for partial volume effects. The EWA algorithm was validated in-vivo against triphenyltetrazolium-chloride (TTC) staining (n = 7 pigs with paired IR and PSIR images) and against ex-vivo high resolution T1-weighted images (n = 23 IR and n = 13 PSIR images). The EWA algorithm was also compared to expert delineation in 124 patients from multi-center, multi-vendor clinical trials 2-6 days following first time ST-elevation myocardial infarction (STEMI) treated with percutaneous coronary intervention (PCI) (n = 124 IR and n = 49 PSIR images).
  
  
  
  Infarct size by the EWA algorithm in vivo in pigs showed a bias to ex-vivo TTC of -1 ± 4%LVM (R = 0.84) in IR and -2 ± 3%LVM (R = 0.92) in PSIR images and a bias to ex-vivo T1-weighted images of 0 ± 4%LVM (R = 0.94) in IR and 0 ± 5%LVM (R = 0.79) in PSIR images. In multi-center patient studies, infarct size by the EWA algorithm showed a bias to expert delineation of -2 ± 6 %LVM (R = 0.81) in IR images (n = 124) and 0 ± 5%LVM (R = 0.89) in PSIR images (n = 49).
  
  
  
  The EWA algorithm was validated experimentally and in patient data with a low bias in both IR and PSIR LGE images. Thus, the use of EM and a weighted intensity as in the EWA algorithm, may serve as a clinical standard for the quantification of myocardial infarction in LGE CMR images.
  
  
  
  CHILL-MI: NCT01379261 .
  
  
  
  NCT01374321 .
authors.affiliation: Department of Clinical Sciences Lund, Clinical Physiology, Lund University, Skåne University Hospital, Lund, Sweden.
authors.forename: Henrik
authors.initials: H
authors.lastname: Engblom
authors.affiliation: Department of Clinical Sciences Lund, Clinical Physiology, Lund University, Skåne University Hospital, Lund, Sweden.|Department of Biomedical Engineering, Faculty of Engineering, Lund University, Lund, Sweden.
authors.forename: Jane
authors.initials: J
authors.lastname: Tufvesson
authors.affiliation: Department of Clinical Sciences Lund, Clinical Physiology, Lund University, Skåne University Hospital, Lund, Sweden.
authors.forename: Robert
authors.initials: R
authors.lastname: Jablonowski
authors.affiliation: Department of Clinical Sciences Lund, Clinical Physiology, Lund University, Skåne University Hospital, Lund, Sweden.
authors.forename: Marcus
authors.initials: M
authors.lastname: Carlsson
authors.affiliation: Department of Clinical Sciences Lund, Clinical Physiology, Lund University, Skåne University Hospital, Lund, Sweden.|Laboratory of Medical Informatics, School of Medicine, Aristotle University of Thessaloniki, Thessaloniki, Greece.
authors.forename: Anthony H
authors.initials: AH
authors.lastname: Aletras
authors.affiliation: Section for Interventional Cardiology, Department of Cardiology, Division of Cardiovascular and Pulmonary Diseases, Oslo University Hospital, Ullevaal, Oslo, Norway.
authors.forename: Pavel
authors.initials: P
authors.lastname: Hoffmann
authors.affiliation: Aix-Marseille University, UMR 7339 CRMBM, Marseille, France.|Department of Radiology, La Timone University Hospital, Marseille, France.
authors.forename: Alexis
authors.initials: A
authors.lastname: Jacquier
authors.affiliation: Aix-Marseille University, UMR 7339 CRMBM, Marseille, France.
authors.forename: Frank
authors.initials: F
authors.lastname: Kober
authors.affiliation: Department of Cardiology, Medical University of Innsbruck, Innsbruck, Austria.
authors.forename: Bernhard
authors.initials: B
authors.lastname: Metzler
authors.affiliation: Department of Cardiology, Lund University, Lund, Sweden.
authors.forename: David
authors.initials: D
authors.lastname: Erlinge
authors.affiliation: Department of Cardiology B, Oslo University Hospital Ullevål and Faculty of Medicine, University of Oslo, Oslo, Norway.
authors.forename: Dan
authors.initials: D
authors.lastname: Atar
authors.affiliation: Department of Clinical Sciences Lund, Clinical Physiology, Lund University, Skåne University Hospital, Lund, Sweden.
authors.forename: Håkan
authors.initials: H
authors.lastname: Arheden
authors.affiliation: Department of Clinical Sciences Lund, Clinical Physiology, Lund University, Skåne University Hospital, Lund, Sweden. einar.heiberg@med.lu.se.|Department of Biomedical Engineering, Faculty of Engineering, Lund University, Lund, Sweden. einar.heiberg@med.lu.se.|Department of Clinical Physiology and Nuclear Medicine, Skåne University Hospital, SE-221 85, Lund, Sweden. einar.heiberg@med.lu.se.
authors.forename: Einar
authors.initials: E
authors.lastname: Heiberg
mesh_terms: D000465:Algorithms; D000818:Animals; D001331:Automation; D002986:Clinical Trials as Topic; D003132:Commerce; D003287:Contrast Media / Q000008:administration & dosage*; D004195:Disease Models, Animal; D005682:Gadolinium / Q000008:administration & dosage*; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D009206:Myocardium / Q000473:pathology*; D062645:Percutaneous Coronary Intervention; D011237:Predictive Value of Tests; D015203:Reproducibility of Results; D000072657:ST Elevation Myocardial Infarction / Q000000981:diagnostic imaging* / Q000473:pathology / Q000628:therapy; D034421:Sus scrofa; D016896:Treatment Outcome
chemical_list: D003287:Contrast Media; D005682:Gadolinium
keywords: Automatic quantification algorithm; Expectation maximization; Experimental validation; LGE CMR; Multi-center patient data