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Histopathological validation of semi-automated myocardial scar quantification techniques for dark-blood late gadolinium enhancement magnetic resonance imaging.
Nies, Hedwig M J M; Gommers, Suzanne; Bijvoet, Geertruida P; Heckman, Luuk I B; Prinzen, Frits W; Vogel, Gaston; Van De Heyning, Caroline M; Chiribiri, Amedeo; Wildberger, Joachim E; Mihl, Casper; Holtackers, Robert J.
Affiliation
  • Nies HMJM; Cardiovascular Research Institute Maastricht (CARIM), Maastricht University, Maastricht, The Netherlands.
  • Gommers S; Department of Radiology & Nuclear Medicine, Maastricht University Medical Centre, PO Box 5800, AZ 6202, Maastricht, The Netherlands.
  • Bijvoet GP; Department of Radiology & Nuclear Medicine, Maastricht University Medical Centre, PO Box 5800, AZ 6202, Maastricht, The Netherlands.
  • Heckman LIB; Cardiovascular Research Institute Maastricht (CARIM), Maastricht University, Maastricht, The Netherlands.
  • Prinzen FW; Department of Cardiology, Maastricht University Medical Centre, Maastricht, The Netherlands.
  • Vogel G; Department of Physiology, Maastricht University, Maastricht, The Netherlands.
  • Van De Heyning CM; Cardiovascular Research Institute Maastricht (CARIM), Maastricht University, Maastricht, The Netherlands.
  • Chiribiri A; Department of Physiology, Maastricht University, Maastricht, The Netherlands.
  • Wildberger JE; Pie Medical Imaging, Maastricht, The Netherlands.
  • Mihl C; Department of Cardiology, Antwerp University Hospital and GENCOR, University of Antwerp, Antwerp, Belgium.
  • Holtackers RJ; School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK.
Eur Heart J Cardiovasc Imaging ; 24(3): 364-372, 2023 02 17.
Article in En | MEDLINE | ID: mdl-35723673
ABSTRACT

AIMS:

To evaluate the performance of various semi-automated techniques for quantification of myocardial infarct size on both conventional bright-blood and novel dark-blood late gadolinium enhancement (LGE) images using histopathology as reference standard. METHODS AND

RESULTS:

In 13 Yorkshire pigs, reperfused myocardial infarction was experimentally induced. At 7 weeks post-infarction, both bright-blood and dark-blood LGE imaging were performed on a 1.5 T magnetic resonance scanner. Following magnetic resonance imaging (MRI), the animals were sacrificed, and histopathology was obtained. The percentage of infarcted myocardium was assessed per slice using various semi-automated scar quantification techniques, including the signal threshold vs. reference mean (STRM, using 3 to 8 SDs as threshold) and full-width at half-maximum (FWHM) methods, as well as manual contouring, for both LGE methods. Infarct size obtained by histopathology was used as reference. In total, 24 paired LGE MRI slices and histopathology samples were available for analysis. For both bright-blood and dark-blood LGE, the STRM method with a threshold of 5 SDs led to the best agreement to histopathology without significant bias (-0.23%, 95% CI [-2.99, 2.52%], P = 0.862 and -0.20%, 95% CI [-2.12, 1.72%], P = 0.831, respectively). Manual contouring significantly underestimated infarct size on bright-blood LGE (-1.57%, 95% CI [-2.96, -0.18%], P = 0.029), while manual contouring on dark-blood LGE outperformed semi-automated quantification and demonstrated the most accurate quantification in this study (-0.03%, 95% CI [-0.22, 0.16%], P = 0.760).

CONCLUSION:

The signal threshold vs. reference mean method with a threshold of 5 SDs demonstrated the most accurate semi-automated quantification of infarcted myocardium, without significant bias compared to histopathology, for both conventional bright-blood and novel dark-blood LGE.
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Full text: 1 Database: MEDLINE Main subject: Cicatrix / Myocardial Infarction Limits: Animals Language: En Journal: Eur Heart J Cardiovasc Imaging Year: 2023 Type: Article Affiliation country: Netherlands

Full text: 1 Database: MEDLINE Main subject: Cicatrix / Myocardial Infarction Limits: Animals Language: En Journal: Eur Heart J Cardiovasc Imaging Year: 2023 Type: Article Affiliation country: Netherlands