Journal article
Deep learning from atrioventricular plane displacement in patients with Takotsubo syndrome: lighting up the black-box
European heart journal. Digital health, Vol.5(2), pp.134-143
03/18/2024
DOI: 10.1093/ehjdh/ztad077
PMCID: PMC10944681
PMID: 38505490
Abstract
Abstract Aims The spatiotemporal deep convolutional neural network (DCNN) helps reduce echocardiographic readers’ erroneous ‘judgement calls’ on Takotsubo syndrome (TTS). The aim of this study was to improve the interpretability of the spatiotemporal DCNN to discover latent imaging features associated with causative TTS pathophysiology. Methods and results We applied gradient-weighted class activation mapping analysis to visualize an established spatiotemporal DCNN based on the echocardiographic videos to differentiate TTS (150 patients) from anterior wall ST-segment elevation myocardial infarction (STEMI, 150 patients). Forty-eight human expert readers interpreted the same echocardiographic videos and prioritized the regions of interest on myocardium for the differentiation. Based on visualization results, we completed optical flow measurement, myocardial strain, and Doppler/tissue Doppler echocardiography studies to investigate regional myocardial temporal dynamics and diastology. While human readers’ visualization predominantly focused on the apex of the heart in TTS patients, the DCNN temporal arm’s saliency visualization was attentive on the base of the heart, particularly at the atrioventricular (AV) plane. Compared with STEMI patients, TTS patients consistently showed weaker peak longitudinal displacement (in pixels) in the basal inferoseptal (systolic: 2.15 ± 1.41 vs. 3.10 ± 1.66, P < 0.001; diastolic: 2.36 ± 1.71 vs. 2.97 ± 1.69, P = 0.004) and basal anterolateral (systolic: 2.70 ± 1.96 vs. 3.44 ± 2.13, P = 0.003; diastolic: 2.73 ± 1.70 vs. 3.45 ± 2.20, P = 0.002) segments, and worse longitudinal myocardial strain in the basal inferoseptal (−8.5 ± 3.8% vs. −9.9 ± 4.1%, P = 0.013) and basal anterolateral (−8.6 ± 4.2% vs. −10.4 ± 4.1%, P = 0.006) segments. Meanwhile, TTS patients showed worse diastolic mechanics than STEMI patients (Eʹ/septal: 5.1 ± 1.2 cm/s vs. 6.3 ± 1.5 cm/s, P < 0.001; Sʹ/septal: 5.8 ± 1.3 cm/s vs. 6.8 ± 1.4 cm/s, P < 0.001; Eʹ/lateral: 6.0 ± 1.4 cm/s vs. 7.9 ± 1.6 cm/s, P < 0.001; Sʹ/lateral: 6.3 ± 1.4 cm/s vs. 7.3 ± 1.5 cm/s, P < 0.001; E/Eʹ: 15.5 ± 5.6 vs. 12.5 ± 3.5, P < 0.001). Conclusion The spatiotemporal DCNN saliency visualization helps identify the pattern of myocardial temporal dynamics and navigates the quantification of regional myocardial mechanics. Reduced AV plane displacement in TTS patients likely correlates with impaired diastolic mechanics.
Details
- Title: Subtitle
- Deep learning from atrioventricular plane displacement in patients with Takotsubo syndrome: lighting up the black-box
- Creators
- Fahim Zaman - University of IowaNicholas Isom - University of IowaAmanda Chang - University of IowaYi Grace Wang - California State University, Dominguez HillsAhmed Abdelhamid - University of IowaArooj KhanMajesh Makan - Washington University in St. LouisMahmoud Abdelghany - Cleveland ClinicXiaodong Wu - University of IowaKan Liu - University of Iowa
- Resource Type
- Journal article
- Publication Details
- European heart journal. Digital health, Vol.5(2), pp.134-143
- DOI
- 10.1093/ehjdh/ztad077
- PMID
- 38505490
- PMCID
- PMC10944681
- NLM abbreviation
- Eur Heart J Digit Health
- ISSN
- 2634-3916
- eISSN
- 2634-3916
- Grant note
- name: Obermann Center for Advanced Studies Interdisciplinary Research; DOI: 10.13039/100007930, name: Institute for Clinical and Translational Science
- Language
- English
- Electronic publication date
- 12/06/2023
- Date published
- 03/18/2024
- Academic Unit
- Electrical and Computer Engineering; Iowa Technology Institute; Cardiovascular Medicine; Radiation Oncology; The Iowa Institute for Biomedical Imaging; Internal Medicine
- Record Identifier
- 9984539526302771
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