| Title: |
Prediction of prognosis in patients with tetralogy of Fallot based on deep learning imaging analysis |
| Authors: |
Diller, Gerhard Paul; Orwat, Stefan; Vahle, Julius; Bauer, Ulrike M M; Urban, Aleksandra; Sarikouch, Samir; Berger, Felix; Beerbaum, Philipp; Baumgartner, Helmut; German Competence Network for Congenital Heart Defects Investigators; Kerst, Gunter; Vazquez-Jimenez, jaime F; Vazquez-Jimenez, Dimitrios Gkalpakiotis; Schedifka, Andrea; Buheitel, Gernot; Streble, Joachim; Laser, Kai Thorsten; Sandica, Eugen; Trusen, Burkhard; Miera, Oliver; Ovroutski, Stanislav; Peters, Björn; Schmitt, Katharina; Schubert, Stephan; Photiadis, Joachim; Opgen-Rhein, Bernd; Weiss, Katja; Berns, Christoph; Blumenthal-Barby, Carl-Christian; Boeckel, Thomas; Haverkämper, Guido; Kästner, Andreas; Koch, Heike; Köpcke, Christian; Streichan, Frank; Timme, Jens; Franzbach, Birgit; Senft, Gabriela; Beyer, Frank; Winter, Klaus; Breuer, Johannes; Esmailzadeh, Bahman; Schneider, Martin; Asfour, Boulos; Bahlmann, Jens; Griese, Eberhard; Lê, Trong Phi; Hebe, Joachim; Nürnberg, Jan-Hendrik; Magsaam, Annette; Müller, Ronald; Potthoff, Ludger; Voigt, Renate; Krüger, Tim; Gerleve, Hubert; Kleideiter, Ulrich; Schneider-Kulla, Dirk; Krülls-Münch, Jürgen; Feil, Elmo; Menke, Thomas; Lehn, Martin; Heilmann, Antje; Tomczak, Helge; Krogmann, Otto N.; Tarusinov, Gleb; Scheid, Michael; Mayatepek, Ertan; Pillekamp, Frank; Lichtenberg, Artur; Terpeluk, Christiane; Kolterer, Bruno; Dittrich, Sven; Gundlach, Ulrike; Cesnjevar, Robert; Neudorf, Ulrich; Morf, Geert; Esmaeili, Anoosh; Backhoff, Stephan; Stiller, Brigitte; Beyersdorf, Friedhelm; Kroll, Johannes; Häffner, Nicole; Siaplaouras, Jannos; Masri-Zada, Antje; Jux, Christian; Böning, Andreas; Akintürk, Hakan; Paul, Thomas; Sigler, Matthias; Tirilomis, Theodor; Schürer, Gabriele; Hartmann, Johannes; Grabitz, Ralph; Liebaug, Uta; Rotzsch, Claudius; Kozlik-Feldmann, Rainer; Sachweh, Jörg; Riso, Arlindo; Renz, Stefan; Schemm, Andreas; Friedrich, Bernd; Schlobohm, Otmar; Böthig, Dietmar; Horke, Alexander; Bauersachs, Johann; Westhoff-Bleck, Mechthild; Gorenflo, Matthias; Karck, Matthias; Loukanov, Tsvetomir; Schrüfer, Hermann; Wilken, Martin; Abdul-Khaliq, Hashim; Rädle-Hurst, Tanja; Rentzsch, Axel; Schäfers, Hans-Joachim; Reichert, Hagen; Kriebel, Thomas; Boysen, Arnulf; Uebing, Anselm; Cremer, Joachim Thomas; Scheewe, Jens; Buchholz-Berdau, Regina; Möller, Peter; Ram, Wolfgang; Brockmeier, Konrad; Bennink, Gerardus B. W. E.; Gillor, Alex; Niehues, Tim; Terhoeven, Peter; Leidig, Steffen; Dähnert, Ingo; Kinzel, Peter; Kostelka, Martin; Kändler, Liane; Bethge, Martin; Köster, Stefan; Schröder, Christoph; Karstedt, Jens; Seitz, Uwe; Kampmann, Christoph; Vahl, Christian-Friedrich; Stahl, Frank; Abedini, Mojtaba; Müller-Scholden, Joachim; Ewert, Peter; Hager, Alfred; Kaemmerer, Harald; Nagdyman, Nicole; Schoetzau, Jörg; Tutarel, Oktay; Lange, Rüdiger; Hörer, Jürgen; Haas, Nikolaus A.; Rosenthal, Lale; Hauser, Michael; Roithmaier, Alexander; Kehl, Hans-Gerd; Malec, Edward; Diller, Gerhard; Bahle, Roswitha; Hofner, Gerald; Zink, Stefan; Reif, Roland; Singer, Helmut; Parlasca, Christoph; Freund, Matthias W.; Schumacher, Michael; Dewald, Oliver; Darrelmann, Christine; Motz, Reinald; Willmann, Olaf; Schmiedl, Norbert; Quick, Peter; Hillebrand, Dirk; Eiselt, Stephan Michele; Nekarda, Torsten; Eberhard, Michael; Baier, Georg; Uhlemann, Frank; Tzanavaros, Ioannis; Beyer, Alexander; Binz, Gudrun; Hess, Steffen; Teufel, Thomas; Handke, Ronald-Peter; Hofbeck, Michael; Kaulitz, Renate; Sieverding, Ludger; Schlensak, Christian; Apitz, Christian; Kaestner, Michael; Kupferschmid, Christoph; Holtvogt, Jürgen; Wippermann, Carl-Friedrich; Heusch, Andreas; Wirbelauer, Johannes; Brosi, Wolfgang |
| Publisher Information: |
BMJ Publishing Group Ltd |
| Publication Year: |
2020 |
| Collection: |
HighWire Press (Stanford University) |
| Subject Terms: |
Congenital heart disease |
| Description: |
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 |
| Document Type: |
text |
| File Description: |
text/html |
| Language: |
English |
| Relation: |
http://heart.bmj.com/cgi/content/short/106/13/1007; http://dx.doi.org/10.1136/heartjnl-2019-315962 |
| DOI: |
10.1136/heartjnl-2019-315962 |
| Availability: |
http://heart.bmj.com/cgi/content/short/106/13/1007; https://doi.org/10.1136/heartjnl-2019-315962 |
| Rights: |
Copyright (C) 2020, BMJ Publishing Group Ltd |
| Accession Number: |
edsbas.964CD26E |
| Database: |
BASE |