International Journal of Cardiology: Heart & Vasculature (Aug 2023)

Usefulness of automatic assessment for longitudinal strain to diagnose wild-type transthyretin amyloid cardiomyopathy

  • Hiroki Usuku,
  • Eiichiro Yamamoto,
  • Daisuke Sueta,
  • Kanako Imamura,
  • Fumi Oike,
  • Kyohei Marume,
  • Masanobu Ishii,
  • Shinsuke Hanatani,
  • Yuichiro Arima,
  • Seiji Takashio,
  • Seitaro Oda,
  • Hiroaki Kawano,
  • Mitsuharu Ueda,
  • Hirotaka Matsui,
  • Kenichi Tsujita

Journal volume & issue
Vol. 47
p. 101227

Abstract

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Background: Left ventricular (LV) apical sparing by transthoracic echocardiography (TTE) has not been widely accepted to diagnose transthyretin amyloid cardiomyopathy (ATTR-CM), because it is time consuming and requires a level of expertise. We hypothesized that automatic assessment may be the solution for these problems. Methods-and-Results: We enrolled 63 patients aged ≥70 years who underwent 99mTc-labeled pyrophosphate (99mTc-PYP) scintigraphy on suspicion of ATTR-CM and performed TTE by EPIQ7G, and had enough information for two-dimensional speckle tracking echocardiography at Kumamoto University Hospital from January 2016 to December 2019. LV apical sparing was described as a high relative apical longitudinal strain (LS) index (RapLSI). Measurement of LS was repeated using the same apical images with three different measurement packages as follows: (1) full-automatic assessment, (2) semi-automatic assessment, and (3) manual assessment. The calculation time for full-automatic assessment (14.7 ± 1.4 sec/patient) and semi-automatic assessment (66.7 ± 14.4 sec/patient) were significantly shorter than that for manual assessment (171.2 ± 59.7 sec/patient) (p < 0.01 for both). Receiver operating characteristic curve analysis showed that the area under curve of the RapLSI evaluated by full-automatic assessment for predicting ATTR-CM was 0.70 (best cut-off point; 1.14 [sensitivity 63%, specificity 81%]), by semi-automatic assessment was 0.85 (best cut-off point; 1.00 [sensitivity, 66%; specificity, 100%]) and by manual assessment was 0.83 (best cut-off point; 0.97 [sensitivity, 72%; specificity, 97%]). Conclusion: There was no significant difference between the diagnostic accuracy of RapLSI estimated by semi-automatic assessment and that estimated by manual assessment. Semi-automatically assessed RapLSI is useful to diagnose ATTR-CM in terms of rapidity and diagnostic accuracy.

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