Post-Processing and Workflow
Géraldine Montier, MD
MD
Centre Hospitalier Universitaire de Bordeaux, France
Géraldine Montier, MD
MD
Centre Hospitalier Universitaire de Bordeaux, France
Jean-David Maes, MD
MD
Centre Hospitalier Universitaire de Bordeaux, France
Pauline Gut, MSc
MSc
University Hospital (CHUV) and University of Lausanne (UNIL), Switzerland
Thibault Boullé, MD
MD
Centre Hospitalier Universitaire de Bordeaux, France
Victor de Villedon de Naide, MSc
MSc
IHU LIRYC, Electrophysiology and Heart Modeling Institute, Université de Bordeaux – INSERM U1045, France
Indra Ribal, MSc
MSc
IHU Liryc, Université de Bordeaux, France
Michel Montaudon, MD, PhD
PROF/PhD
Hôpital Cardiologique du Haut-Lévêque, CHU de Bordeaux
Pessac, Aquitaine, France
Gäel Dournes, MD, PhD
PROF/PhD
Hôpital Cardiologique du Haut-Lévêque, CHU de Bordeaux, France
François Laurent, MD, PhD
PROF/PhD
Hôpital Cardiologique du Haut-Lévêque, CHU de Bordeaux
Pessac, Aquitaine, France
Soumaya Sridi, MD
MD
Centre Hospitalier Universitaire de Bordeaux, France
Pierre Jaïs, MD, PhD
PROF/PhD
Hôpital Cardiologique du Haut-Lévêque, CHU de Bordeaux
Bordeaux, Aquitaine, France
Matthias Stuber, PhD
Professor
University Hospital (CHUV) and University of Lausanne (UNIL)
Lausanne, Switzerland
Hubert Cochet, MD, PhD
PROF/PhD
Centre Hospitalier Universitaire de Bordeaux
Pessac, Aquitaine, France
Aurélien Bustin, PhD
Junior Professor
IHU LIRYC
Bordeaux, Aquitaine, France
Bright-blood late gadolinium enhancement (LGE) imaging is considered the gold standard for the assessment of myocardial viability1. However, infarct transmurality measurements and visualization highly depend on the accurate delineation of the endocardial border of the infarct and are often hampered by low scar-to-blood contrast2,3. Bright- and black-blood LGE imaging technologies have recently enabled more accurate scar detection and localization and have shown promising results for scar quantification4. However, the best segmentation method for scar quantification using such imaging techniques is currently unknown.
Our aim was therefore to compare several myocardial scar quantification techniques for joint bright- and black-blood LGE imaging in patients with ischemic heart disease.
Methods:
Acquisition: 23 patients (7 females, 60±10 years) with known ischemic heart disease underwent CMR at 1.5-T (Siemens, MAGNETOM Aera) as part of clinical care. Two full stacks of left ventricular (LV) short-axis 2D slices were collected in random order and during multiple breath-holds using both conventional phase-sensitive inversion recovery LGE5 and the recently developed joint bright- and black-blood SPOT technology4 10 min after the administration of gadoteric acid.
Analysis: LV endocardial and epicardial contours were manually outlined on each bright-blood slice using CVI42 (Circle, Calgary). Epicardial fat and papillary muscles were excluded from the LV wall. Contours were propagated to each black-blood SPOT image and infarct size was quantified using manual (reference) and semi-automated techniques (full width half maximum [FWHM] and n-SD, n from 1 to 20). Two regions of interest were drawn around normal (for n-SD techniques) and hyperintense myocardium (for FWHM). Total infarct mass and percent of infarcted myocardium were extracted in all patients. Pearson correlation, linear regression, and Bland-Altman analyses were performed to show agreements between the manual and semi-automated segmentation techniques.
Results:
The 12-SD segmentation provided the lowest absolute difference in scar mass (0.4±3.6g, Fig1) compared with the reference manual segmentation. There was an excellent correlation between manual and 12-SD segmentation for scar mass (23.10±11.98g vs. 23.49±12.6g, R=0.96, P< 0.001) and scar percentage (20.35±10.43% vs. 20.52±9.65%, R=0.96, P< 0.001). Bland-Altman analysis of scar mass comparing manual with 12-SD segmentation showed excellent agreement with a non-significant bias of 0.39 g (95% confidence interval [CI]: -6.6 to 7.4, P=0.60); likewise for percentage scar tissue with a non-significant bias of 0.17% (95% CI: -5.8 to 6.2, P=0.79). Fig 2 compares the manual and 12-SD LGE segmentations in 4 patients with chronic myocardial infarction.
Conclusion:
The 12-SD technique may serve as the most accurate approach for the analysis and quantification of infarct size on joint bright- and black-blood LGE images in patients with ischemic heart disease.