Abstract

BackgroundTakotsubo syndrome (TTS) is often associated with symptoms of heart failure (HF) during the acute phase of the disease. 3-dimensional optical coherence tomography (OCT) may be used to assess the extent of angiographically silent underlying coronary artery disease (CAD). This study aims to use an artificial intelligence algorithm to analyze OCT findings and to determine whether the presence of pre-existing CAD predisposes TTS patients to present HF at admission. MethodsThis is an observational and retrospective study that enrolled TTS patients who underwent coronary angiography and OCT examination of left anterior descending (LAD) coronary artery. Plaque characterization was automatically analyzed via an artificial intelligence model from OCT images. An angiography-derived index of microcirculatory resistance (IMRangio) using the optic flow ratio (OFR) was calculated to assess its correlation with plaque volumes. ResultsThirty-seven patients were included (94.6 % women) with a median age of 82.0 years. Ten patients (27 %) showed some degree of HF at admission. Sixty-seven coronary non-obstructive plaques were analyzed. Tissue compositional analysis showed that patients with HF had an increased overall plaque volume (79.0 mm3 vs 28.6 mm3; p = 0.011) and longer plaque lesion length (12.8 mm vs 7.2 mm; p = 0.006). Patients with HF also showed an increased percentage of lipidic and calcified plaque tissue (26.4 % vs 13.4 %; p = 0.019 and 4.5 % vs 0.0 %; p = 0.001, respectively). A moderate positive correlation was found between global overall plaque volume and IMRangio. ConclusionIncreased overall plaque volume was associated with the development of HF during the acute phase of TTS, suggesting that the presence of angiographically silent underlying CAD may play a prognostic role in these patients.

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