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Isotropic 3 D cardiac cine MRI allows efficient sparse segmentation strategies based on 3 D surface reconstruction
Author(s) -
Odille Freddy,
Bustin Aurélien,
Liu Shufang,
Chen Bailiang,
Vuissoz PierreAndré,
Felblinger Jacques,
Bonnemains Laurent
Publication year - 2018
Publication title -
magnetic resonance in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.696
H-Index - 225
eISSN - 1522-2594
pISSN - 0740-3194
DOI - 10.1002/mrm.26923
Subject(s) - segmentation , artificial intelligence , isotropy , computer science , computer vision , pattern recognition (psychology) , mathematics , physics , optics
Purpose Segmentation of cardiac cine MRI data is routinely used for the volumetric analysis of cardiac function. Conventionally, 2D contours are drawn on short‐axis (SAX) image stacks with relatively thick slices (typically 8 mm). Here, an acquisition/reconstruction strategy is used for obtaining isotropic 3D cine datasets; reformatted slices are then used to optimize the manual segmentation workflow. Methods Isotropic 3D cine datasets were obtained from multiple 2D cine stacks (acquired during free‐breathing in SAX and long‐axis (LAX) orientations) using nonrigid motion correction (cine‐GRICS method) and super‐resolution. Several manual segmentation strategies were then compared, including conventional SAX segmentation, LAX segmentation in three views only, and combinations of SAX and LAX slices. An implicit B‐spline surface reconstruction algorithm is proposed to reconstruct the left ventricular cavity surface from the sparse set of 2D contours. Results All tested sparse segmentation strategies were in good agreement, with Dice scores above 0.9 despite using fewer slices (3–6 sparse slices instead of 8–10 contiguous SAX slices). When compared to independent phase‐contrast flow measurements, stroke volumes computed from four or six sparse slices had slightly higher precision than conventional SAX segmentation (error standard deviation of 5.4 mL against 6.1 mL) at the cost of slightly lower accuracy (bias of −1.2 mL against 0.2 mL). Functional parameters also showed a trend to improved precision, including end‐diastolic volumes, end‐systolic volumes, and ejection fractions). Conclusion The postprocessing workflow of 3D isotropic cardiac imaging strategies can be optimized using sparse segmentation and 3D surface reconstruction. Magn Reson Med 79:2665–2675, 2018. © 2017 International Society for Magnetic Resonance in Medicine.