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Digital archive of theses discussed at the University of Pisa

 

Thesis etd-10092022-195618


Thesis type
Tesi di specializzazione (4 anni)
Author
PERRI, MATTEO
URN
etd-10092022-195618
Thesis title
LGE-Dispersion mapping: a novel post-processing technique to assess risk of major arrhythmic events in patients with previous myocardial infarction and LVEF>35%
Department
PATOLOGIA CHIRURGICA, MEDICA, MOLECOLARE E DELL'AREA CRITICA
Course of study
MALATTIE DELL'APPARATO CARDIOVASCOLARE
Supervisors
relatore Prof. De Caterina, Raffaele
relatore Dott. Aquaro, Giovanni Donato
Keywords
  • cardiac magnetic resonance
  • myocardial infarction
  • late gadolinium enhancement
  • dispersion mapping
Graduation session start date
08/11/2022
Availability
None
Summary
BACKGROUND: Myocardial fibrosis is a major pathophysiologic determinant of arrhythmic propensity in both ischemic cardiomyopathy (ICM) and non-ICM (NICM). Recently a novel LGE image analysis method, named LGE-dispersion mapping was proposed as a new tool to predict arrhythmogenic in Hypertrophic cardiomyopathy (HCM). Here, we proposed this method to predict arrhythmogenic in the context of stable coronary heart disease after myocardial infarction with LVEF >35%.
METHODS: CMR was performed in 220 consecutive patients who had clinical evidence of an earlier MI (> 90 days prior) and LV EF > 35%. A parametric map was generated from each LGE image. A score from 0 to 8 was assigned at every pixel of these maps, indicating the number of the surrounding pixels having different quality (nonenhancement, mild-enhancement, or hyperenhancement) from the central pixel. The Global Dispersion Score (GDS) was calculated as the average score of all the pixels of the images.
RESULTS: During a clinical follow-up of 682 days (324 – 1327), 14 patients had events ( death for all causes, cardiac death, resuscitated cardiac arrest, and the proper ICD shock or anti-tachycardia pacing). GDS emerged as the only independent predictor of hard events. The Kaplan-Meier analysis showed that patients with GDS>0.5 had worse prognosis than those with lower GDS (Logrank p < 0.0001).
CONCLUSIONS: GDS is a new quantitative marker for the evaluation of heterogeneity and dispersion in myocardial fibrosis in the context of various forms of heart disease. For patients with a history of myocardial infarction at LVEF> 35%, GDS has a predictive role in identifying patients at higher risk for major cardiac events
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