Noninvasive hemodynamic assessment, treatment outcome prediction and follow‐up of aortic coarctation from MR imaging. Issue 5 (10th April 2015)

• Record Type: Journal Article
• Authors: Ralovich, Kristóf; Itu, Lucian; Vitanovski, Dime; Sharma, Puneet; Ionasec, Razvan; Mihalef, Viorel; Krawtschuk, Waldemar; Zheng, Yefeng; Everett, Allen; Pongiglione, Giacomo; Leonardi, Benedetta; Ringel, Richard; Navab, Nassir; Heimann, Tobias; Comaniciu, Dorin
• Is Part Of: Medical physics. Volume 42:Issue 5(2015)
• Page Start: 2143
• Page End: 2156
• Publication Date: 2015-04-10
• Subjects: bioinformatics -- biomedical MRI -- blood flow measurement -- blood vessels -- cardiology -- computational fluid dynamics -- diseases -- image segmentation -- medical computing -- medical image processing -- patient care -- patient diagnosis -- surgery; Hemodynamics -- Magnetic resonance imaging -- Computer‐aided diagnosis -- Diseases; Measuring for diagnostic purposes; Identification of persons -- Measuring blood flow -- Involving electronic [emr] or nuclear [nmr] magnetic resonance, e.g. magnetic resonance imaging -- Surgical instruments, devices or methods, e.g. tourniquets -- Biological material, e.g. blood, urine; Haemocytometers -- Digital computing or data processing equipment or methods, specially adapted for specific applications -- Image data processing or generation, in general -- Knowledge representation; coarctation of aorta -- blood pressure drop -- MRI -- segmentation -- computational fluid dynamics (CFD); Medical physics -- Periodicals; Medical physics; Geneeskunde; Natuurkunde; Toepassingen; Biophysics; Periodicals; Periodicals; Electronic journals; 610.153
• DOI: 10.1118/1.4914856
• Languages: English
• ISSNs: 0094-2405

Abstract

Abstract : Purpose: 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.