Left ventricular longitudinal strain analysis using cardiac computed tomography for the diagnosis of cardiac amyloidosis

Abstract Introduction Cardiac amyloidosis (CA) results in a restrictive cardiomyopathy caused by extracellular deposition of proteins in the myocardium, demanding early identification for effective management. Left ventricular (LV) strain, mainly evaluated by echocardiography or cardiac magnetic resonance, provides sensitive and specific indicators for detecting CA, particularly apical sparing. It represents a pattern where the longitudinal strain (LS) in the basal and middle segments of LV is more impaired compared to the apical segments.¹ Cardiac computed tomography (CT) is useful not only for coronary artery evaluation but also for myocardial assessment, including LV ejection fraction (LVEF). Advanced software made it possible to analyse LS on cardiac CT (Figures A,B). Hypothesis: LS analysis using four-dimensional cardiac CT is helpful for the differential diagnosis of LV hypertrophied myocardial diseases and for detecting CA. Methods We analyzed 60 patients with LV hypertrophied myocardial diseases who underwent cardiac CT using 256-detector row or 320-detector row CT since 2009. Twenty patients of them were diagnosed with CA ( 70 ± 10 years, 14 males), the other 20 patients were diagnosed with hypertrophic cardiomyopathy (HCM) ( 60 ± 14 years, 12 males), and the rest of the 20 patients were diagnosed with severe aortic valve stenosis (AS) ( 86 ± 6 years, nine males). We analyzed LV global LS (GLS) and segmental LS using specific software and four-dimensional CT data. We evaluated relative apical LS as the value dividing the average LS of apical segments by the sum of the average LS of basal segments and mid-ventricular segments (Figure C). If the value was ≥ 1, apical sparing was defined as present. We compared the LS data and the percentage of apical sparing among those three myocardial diseases. Results There was no significant difference in LVEF among the three groups (52 ± 14%, 55 ± 27%, and 50 ± 18%, respectively; P = 0.15). There was no significant difference in GLS among the three groups (-10.6 ± 3.6%, -10.2 ± 5.2%, and -11.6 ± 3.8%, respectively; P = 0.87). Apical sparing was observed in 13 cases (65%) of CA, which was significantly higher than 3 cases (15%) of HCM or 4 cases(20%) of AS (P = 0.0002). Conclusions LV strain analysis using cardiac CT is helpful for detecting apical sparing. Advanced image analysis software has enabled LV strain analysis by cardiac CT, which is useful for the differential diagnosis of CA among LV hypertrophied diseases.Figure A,B,C

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Journal
European Heart Journal
Published
2024-10-01
DOI
https://doi.org/10.1093/eurheartj/ehae666.193
Primary Topic
Cardiovascular Function and Risk Factors
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article
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article

Left ventricular longitudinal strain analysis using cardiac computed tomography for the diagnosis of cardiac amyloidosis

Hiroyuki Takaoka, Tomonori Kanaeda, Noriko Suzuki-Eguchi, Yoshio Kobayashi et al.
European Heart Journal
Cardiovascular Function and Risk Factors
article

Left ventricular longitudinal strain analysis using cardiac computed tomography for the diagnosis of cardiac amyloidosis

Hiroyuki Takaoka, Tomonori Kanaeda, Noriko Suzuki-Eguchi, Yoshio Kobayashi, Yoshihiko Nishikawa, Joji Ota, Kazuki Yoshida, Makiko Kinoshita, Katsuya Suzuki, S Aoki, Megumi Matsumoto, Satomi Yashima, Hidenao Sasaki
article en

Abstract

Abstract Introduction Cardiac amyloidosis (CA) results in a restrictive cardiomyopathy caused by extracellular deposition of proteins in the myocardium, demanding early identification for effective management. Left ventricular (LV) strain, mainly evaluated by echocardiography or cardiac magnetic resonance, provides sensitive and specific indicators for detecting CA, particularly apical sparing. It represents a pattern where the longitudinal strain (LS) in the basal and middle segments of LV is more impaired compared to the apical segments.¹ Cardiac computed tomography (CT) is useful not only for coronary artery evaluation but also for myocardial assessment, including LV ejection fraction (LVEF). Advanced software made it possible to analyse LS on cardiac CT (Figures A,B). Hypothesis: LS analysis using four-dimensional cardiac CT is helpful for the differential diagnosis of LV hypertrophied myocardial diseases and for detecting CA. Methods We analyzed 60 patients with LV hypertrophied myocardial diseases who underwent cardiac CT using 256-detector row or 320-detector row CT since 2009. Twenty patients of them were diagnosed with CA ( 70 ± 10 years, 14 males), the other 20 patients were diagnosed with hypertrophic cardiomyopathy (HCM) ( 60 ± 14 years, 12 males), and the rest of the 20 patients were diagnosed with severe aortic valve stenosis (AS) ( 86 ± 6 years, nine males). We analyzed LV global LS (GLS) and segmental LS using specific software and four-dimensional CT data. We evaluated relative apical LS as the value dividing the average LS of apical segments by the sum of the average LS of basal segments and mid-ventricular segments (Figure C). If the value was ≥ 1, apical sparing was defined as present. We compared the LS data and the percentage of apical sparing among those three myocardial diseases. Results There was no significant difference in LVEF among the three groups (52 ± 14%, 55 ± 27%, and 50 ± 18%, respectively; P = 0.15). There was no significant difference in GLS among the three groups (-10.6 ± 3.6%, -10.2 ± 5.2%, and -11.6 ± 3.8%, respectively; P = 0.87). Apical sparing was observed in 13 cases (65%) of CA, which was significantly higher than 3 cases (15%) of HCM or 4 cases(20%) of AS (P = 0.0002). Conclusions LV strain analysis using cardiac CT is helpful for detecting apical sparing. Advanced image analysis software has enabled LV strain analysis by cardiac CT, which is useful for the differential diagnosis of CA among LV hypertrophied diseases.Figure A,B,C

European Heart JournalVol. 45(Supplement_1)
Chiba University Hospital (JP), Teikyo University Chiba Medical Center (JP)
Openalex Percentile: Top 65%
Cardiovascular Function and Risk Factors
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