Prediction of prognosis in patients with tetralogy of Fallot based on deep learning imaging analysis. Issue 13 (11th March 2020)

• Record Type: Journal Article
• Authors: Diller, Gerhard Paul; Orwat, Stefan; Vahle, Julius; Bauer, Ulrike M M; Urban, Aleksandra; Sarikouch, Samir; Berger, Felix; Beerbaum, Philipp; Baumgartner, Helmut
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W. E. author non-byline.; Gillor Alex author non-byline.; Niehues Tim author non-byline.; Terhoeven Peter author non-byline.; Leidig Steffen author non-byline.; Dähnert Ingo author non-byline.; Kinzel Peter author non-byline.; Kostelka Martin author non-byline.; Kändler Liane author non-byline.; Bethge Martin author non-byline.; Köster Stefan author non-byline.; Schröder Christoph author non-byline.; Karstedt Jens author non-byline.; Seitz Uwe author non-byline.; Kampmann Christoph author non-byline.; Vahl Christian-Friedrich author non-byline.; Stahl Frank author non-byline.; Abedini Mojtaba author non-byline.; Müller-Scholden Joachim author non-byline.; Ewert Peter author non-byline.; Hager Alfred author non-byline.; Kaemmerer Harald author non-byline.; Nagdyman Nicole author non-byline.; Schoetzau Jörg author non-byline.; Tutarel Oktay author non-byline.; Lange Rüdiger author non-byline.; Hörer Jürgen author non-byline.; Haas Nikolaus A. author non-byline.; Rosenthal Lale author non-byline.; Hauser Michael author non-byline.; Roithmaier Alexander author non-byline.; Kehl Hans-Gerd author non-byline.; Malec Edward author non-byline.; Baumgartner Helmut author non-byline.; Diller Gerhard author non-byline.; Bahle Roswitha author non-byline.; Hofner Gerald author non-byline.; Zink Stefan author non-byline.; Reif Roland author non-byline.; Singer Helmut author non-byline.; Parlasca Christoph author non-byline.; Freund Matthias W. author non-byline.; Schumacher Michael author non-byline.; Dewald Oliver author non-byline.; Darrelmann Christine author non-byline.; Motz Reinald author non-byline.; Willmann Olaf author non-byline.; Schmiedl Norbert author non-byline.; Quick Peter author non-byline.; Hillebrand Dirk author non-byline.; Eiselt Stephan Michele author non-byline.; Nekarda Torsten author non-byline.; Eberhard Michael author non-byline.; Baier Georg author non-byline.; Uhlemann Frank author non-byline.; Tzanavaros Ioannis author non-byline.; Beyer Alexander author non-byline.; Binz Gudrun author non-byline.; Hess Steffen author non-byline.; Teufel Thomas author non-byline.; Handke Ronald-Peter author non-byline.; Hofbeck Michael author non-byline.; Kaulitz Renate author non-byline.; Sieverding Ludger author non-byline.; Schlensak Christian author non-byline.; Apitz Christian author non-byline.; Kaestner Michael author non-byline.; Kupferschmid Christoph author non-byline.; Holtvogt Jürgen author non-byline.; Wippermann Carl-Friedrich author non-byline.; Heusch Andreas author non-byline.; Wirbelauer Johannes author non-byline.; Brosi Wolfgang author non-byline.;
• Is Part Of: Heart. Volume 106:Issue 13(2020)
• Page Start: 1007
• Page End: 1014
• Publication Date: 2020-03-11
• Subjects: congenital heart disease -- tetralogy of Fallot -- cardiac magnetic resonance (CMR) imaging -- advanced cardiac imaging; Heart -- Diseases -- Treatment -- Periodicals; Cardiology -- Periodicals; 616.12
• DOI: 10.1136/heartjnl-2019-315962
• Languages: English
• ISSNs: 1355-6037

Abstract

Abstract : Objective: To assess the utility of machine learning algorithms for automatically estimating prognosis in patients with repaired tetralogy of Fallot (ToF) using cardiac magnetic resonance (CMR). Methods: We included 372 patients with ToF who had undergone CMR imaging as part of a nationwide prospective study. Cine loops were retrieved and subjected to automatic deep learning (DL)-based image analysis, trained on independent, local CMR data, to derive measures of cardiac dimensions and function. This information was combined with established clinical parameters and ECG markers of prognosis. Results: Over a median follow-up period of 10 years, 23 patients experienced an endpoint of death/aborted cardiac arrest or documented ventricular tachycardia (defined as >3 documented consecutive ventricular beats). On univariate Cox analysis, various DL parameters, including right atrial median area (HR 1.11/cm², p=0.003) and right ventricular long-axis strain (HR 0.80/%, p=0.009) emerged as significant predictors of outcome. DL parameters were related to adverse outcome independently of left and right ventricular ejection fraction and peak oxygen uptake (p<0.05 for all). A composite score of enlarged right atrial area and depressed right ventricular longitudinal function identified a ToF subgroup at significantly increased risk of adverse outcome (HR 2.1/unit, p=0.007). Conclusions: We present data on the utility of machine learning algorithms trained on external imaging datasets to automatically estimate prognosis in patients with ToF. Due to the automated analysis process these two-dimensional-based algorithms may serve as surrogates for labour-intensive manually attained imaging parameters in patients with ToF.