title: Noninvasive hemodynamic assessment, treatment outcome prediction and follow-up of aortic coarctation from MR imaging.
abstract: OBJECTIVE
  Coarctation of the aorta (CoA) is a congenital heart disease characterized by an abnormal narrowing of the proximal descending aorta. Severity of this pathology is quantified by the blood pressure drop (△P) across the stenotic coarctation lesion. In order to evaluate the physiological significance of the preoperative coarctation and to assess the postoperative results, the hemodynamic analysis is routinely performed by measuring the △P across the coarctation site via invasive cardiac catheterization. The focus of this work is to present an alternative, noninvasive measurement of blood pressure drop △P through the introduction of a fast, image-based workflow for personalized computational modeling of the CoA hemodynamics.
  
  
  METHODS
  The authors propose an end-to-end system comprised of shape and computational models, their personalization setup using MR imaging, and a fast, noninvasive method based on computational fluid dynamics (CFD) to estimate the pre- and postoperative hemodynamics for coarctation patients. A virtual treatment method is investigated to assess the predictive power of our approach.
  
  
  RESULTS
  Automatic thoracic aorta segmentation was applied on a population of 212 3D MR volumes, with mean symmetric point-to-mesh error of 3.00 ± 1.58 mm and average computation time of 8 s. Through quantitative evaluation of 6 CoA patients, good agreement between computed blood pressure drop and catheter measurements is shown: average differences are 2.38 ± 0.82 mm Hg (pre-), 1.10 ± 0.63 mm Hg (postoperative), and 4.99 ± 3.00 mm Hg (virtual stenting), respectively.
  
  
  CONCLUSIONS
  The complete workflow is realized in a fast, mostly-automated system that is integrable in the clinical setting. To the best of our knowledge, this is the first time that three different settings (preoperative--severity assessment, poststenting--follow-up, and virtual stenting--treatment outcome prediction) of CoA are investigated on multiple subjects. We believe that in future-given wider clinical validation-our noninvasive in-silico method could replace invasive pressure catheterization for CoA.
authors.affiliation: Siemens AG, Imaging and Computer Vision, San-Carlos-Strasse 7, 91058 Erlangen, Germany and Technical University of Munich, Boltzmannstrasse 3, Munich 85748, Germany.
authors.forename: Kristóf
authors.initials: K
authors.lastname: Ralovich
authors.affiliation: Siemens S.r.l., Imaging and Computer Vision, B-dul Eroilor nr. 5, 500007 Brasov, Romania and Transilvania University of Brasov, B-dul Eroilor nr. 29, 500036 Brasov, Romania.
authors.forename: Lucian
authors.initials: L
authors.lastname: Itu
authors.affiliation: Siemens AG, Imaging and Computer Vision, San-Carlos-Strasse 7, 91058 Erlangen, Germany and Pattern Recognition Lab, Friedrich-Alexander University Erlangen-Nuremberg, Martensstrasse 3, 91058 Erlangen, Germany.
authors.forename: Dime
authors.initials: D
authors.lastname: Vitanovski
authors.affiliation: Siemens Corporation, Imaging and Computer Vision, 755 College Road East, Princeton, New Jersey 08540.
authors.forename: Puneet
authors.initials: P
authors.lastname: Sharma
authors.affiliation: Siemens Corporation, Imaging and Computer Vision, 755 College Road East, Princeton, New Jersey 08540.
authors.forename: Razvan
authors.initials: R
authors.lastname: Ionasec
authors.affiliation: Siemens Corporation, Imaging and Computer Vision, 755 College Road East, Princeton, New Jersey 08540.
authors.forename: Viorel
authors.initials: V
authors.lastname: Mihalef
authors.affiliation: Siemens AG, Imaging and Computer Vision, San-Carlos-Strasse 7, 91058 Erlangen, Germany.
authors.forename: Waldemar
authors.initials: W
authors.lastname: Krawtschuk
authors.affiliation: Siemens Corporation, Imaging and Computer Vision, 755 College Road East, Princeton, New Jersey 08540.
authors.forename: Yefeng
authors.initials: Y
authors.lastname: Zheng
authors.affiliation: The Johns Hopkins Hospital, 600 North Wolfe Street, Baltimore, Maryland 21287.
authors.forename: Allen
authors.initials: A
authors.lastname: Everett
authors.affiliation: Ospedale Pediatrico Bambino Gesù, Piazza Sant'Onofrio 4, 00165 Rome, Italy.
authors.forename: Giacomo
authors.initials: G
authors.lastname: Pongiglione
authors.affiliation: Ospedale Pediatrico Bambino Gesù, Piazza Sant'Onofrio 4, 00165 Rome, Italy.
authors.forename: Benedetta
authors.initials: B
authors.lastname: Leonardi
authors.affiliation: The Johns Hopkins Hospital, 600 North Wolfe Street, Baltimore, Maryland 21287.
authors.forename: Richard
authors.initials: R
authors.lastname: Ringel
authors.affiliation: Technical University of Munich, Boltzmannstrasse 3, Munich 85748, Germany.
authors.forename: Nassir
authors.initials: N
authors.lastname: Navab
authors.affiliation: Siemens AG, Imaging and Computer Vision, San-Carlos-Strasse 7, 91058 Erlangen, Germany.
authors.forename: Tobias
authors.initials: T
authors.lastname: Heimann
authors.affiliation: Siemens Corporation, Imaging and Computer Vision, 755 College Road East, Princeton, New Jersey 08540.
authors.forename: Dorin
authors.initials: D
authors.lastname: Comaniciu
mesh_terms: D001011:Aorta / Q000473:pathology / Q000503:physiopathology / Q000601:surgery; D001017:Aortic Coarctation / Q000175:diagnosis / Q000473:pathology* / Q000503:physiopathology* / Q000601:surgery; D001794:Blood Pressure; D003198:Computer Simulation; D005500:Follow-Up Studies; D006439:Hemodynamics; D006801:Humans; D021621:Imaging, Three-Dimensional / Q000379:methods; D018810:Magnetic Resonance Angiography / Q000379:methods; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008955:Models, Cardiovascular; D010363:Pattern Recognition, Automated; D057285:Precision Medicine / Q000379:methods*; D011379:Prognosis; D015607:Stents; D013997:Time Factors; D016896:Treatment Outcome