Elodie Roullot

Fully automated segmentation of the left ventricle applied to cine MR images: Description and results on a database of 45 Subjects

A fully automated segmentation method of the left ventricle from short-axis cardiac MR images is proposed and evaluated. The segmentation is based on morphological filtering and gradient vector flow snake for which an automatic setting of parameters has already been proposed. The present work focuses on the automatic detection of a region of interest (ROI) surrounding the left ventricle, prior to the segmentation step. The whole process was applied to the MICCAI 2009 Left Ventricle Challenge database containing 45 subjects (9 healthy subjects and 36 with pathology). The automatic detection of the ROI was judged accurate in 86% of the cases. It failed in 2% of the slices and provided an overestimation in 9% of the slices. Furthermore, the endocardial segmentation was accurate in 80% of the slices and the epicardial was judged satisfactory in 71% of the slices. This fully automated procedure can thus be used as a first step in a user controlled approach, in order to reduce the total number of interactions.

Improved Estimation of Cardiac Function Parameters Using a Combination of Independent Automated Segmentation Results in Cardiovascular Magnetic Resonance Imaging.

This work aimed at combining different segmentation approaches to produce a robust and accurate segmentation result. Three to five segmentation results of the left ventricle were combined using the STAPLE algorithm and the reliability of the resulting segmentation was evaluated in comparison with the result of each individual segmentation method. This comparison was performed using a supervised approach based on a reference method. Then, we used an unsupervised statistical evaluation, the extended Regression Without Truth (eRWT) that ranks different methods according to their accuracy in estimating a specific biomarker in a population. The segmentation accuracy was evaluated by estimating six cardiac function parameters resulting from the left ventricle contour delineation using a public cardiac cine MRI database. Eight different segmentation methods, including three expert delineations and five automated methods, were considered, and sixteen combinations of the automated methods using STAPLE were investigated. The supervised and unsupervised evaluations demonstrated that in most cases, STAPLE results provided better estimates than individual automated segmentation methods. Overall, combining different automated segmentation methods improved the reliability of the segmentation result compared to that obtained using an individual method and could achieve the accuracy of an expert.

Methodology for Jointly Assessing Myocardial Infarct Extent and Regional Contraction in 3-D CMRI

Automated extraction of quantitative parameters from cardiac magnetic resonance images is crucial for the management of patients with myocardial infarct. This paper proposes a postprocessing procedure to jointly analyze Cine and delayed-enhanced (DE) acquisitions, in order to provide an automatic quantification of myocardial contraction and enhancement parameters and a study of their relationship. For that purpose, the following processes are performed: 1) DE/Cine temporal synchronization and 3-D scan alignment, 2) 3-D DE/Cine rigid registration in a region about the heart, 3) myocardium segmentation on Cine-MRI and superimposition of the epicardial and endocardial contours on the DE images, 4) quantification of the myocardial infarct extent (MIE), 5) study of the regional contractile function using a new index, the amplitude to time ratio (ATR). The whole procedure was applied to ten patients with clinically proven myocardial infarction. The comparison between the MIE and the visually assessed regional function scores demonstrated that the MIE is highly related to the severity of the wall motion abnormality. In addition, it was shown that the newly developed regional myocardial contraction parameter (ATR) decreases significantly in delayed enhanced regions. This largely automated approach enables the combined study of regional MIE and left ventricular function.

A new strategy to improve coregistration of spect and MR images in patients with high grade glioma

This paper proposes a new strategy to optimize the coregistration of Technetium-99m Sestamibi SPECT and MRI data in case of patients with high grade glioma. It consists in a personalized approach which selects, for each data set, the best registration method among several ones. To achieve this selection, a quantitative dedicated evaluation criterion based on the average intensities within specific anatomical structures corresponding to physiological areas of uptake of Sestamibi was defined. The strategy was applied to sixty-two data sets using nine registration methods based on mutual information and chamfer distance registration approaches, with different settings. It was implemented within the Anatomist/Brainvisa environment, using its basic registration functions. The visual evaluation by experts indicated that this strategy provides 60% good quality registrations, and 26% intermediate quality ones. Compared to the single use of the best global registration method, the number of registrations of good quality was multiplied by 1.4 when using the data specific strategy.

An efficient strategy based on an individualized selection of registration methods. Application to the coregistration of MR and SPECT images in neuro-oncology.

An efficient registration strategy is described that aims to help solve delicate medical imaging registration problems. It consists of running several registration methods for each dataset and selecting the best one for each specific dataset, according to an evaluation criterion. Finally, the quality of the registration results, obtained with the best method, is visually scored by an expert as excellent, correct or poor. The strategy was applied to coregister Technetium-99m Sestamibi SPECT and MRI data in the framework of a follow-up protocol in patients with high grade gliomas receiving antiangiogenic therapy. To adapt the strategy to this clinical context, a robust semi-automatic evaluation criterion based on the physiological uptake of the Sestamibi tracer was defined. A panel of eighteen multimodal registration algorithms issued from BrainVisa, SPM or AIR software environments was systematically applied to the clinical database composed of sixty-two datasets. According to the expert visual validation, this new strategy provides 85% excellent registrations, 12% correct ones and only 3% poor ones. These results compare favorably to the ones obtained by the globally most efficient registration method over the whole database, for which only 61% of excellent registration results have been reported. Thus the registration strategy in its current implementation proves to be suitable for clinical application.

Comparison of different segmentation approaches without using gold standard. Application to the estimation of the left ventricle ejection fraction from cardiac cine MRI sequences

A statistical method is proposed to compare several estimates of a relevant clinical parameter when no gold standard is available. The method is illustrated by considering the left ventricle ejection fraction derived from cardiac magnetic resonance images and computed using seven approaches with different degrees of automation. The proposed method did not use any a priori regarding with the reliability of each method and its degree of automation. The results showed that the most accurate estimates of the ejection fraction were obtained using manual segmentations, followed by the semiautomatic methods, while the methods with the least user input yielded the least accurate ejection fraction estimates. These results were consistent with the expected performance of the estimation methods, suggesting that the proposed statistical approach might be helpful to assess the performance of estimation methods on clinical data for which no gold standard is available.

A Framework using multimodal imaging for longitudinal monitoring of patients in neuro-oncology. Application to a SPECT/MRI study

This paper proposes a framework to assess the potential value of 99mTc Sestamibi SPECT in addition to Gadolinium-enhanced MRI for the monitoring of patients with high grade gliomas under antiangiogenic treatment. It includes: 1) multimodal and monomodal high precision registration steps achieved thanks to a registration strategy which selects the best method among several ones for each dataset, 2) tumor segmentation steps dedicated to each modality and 3) a tumor comparison step which consists in the computation of some global (volume, intensity) and local (matching and mismatching) quantitative indices to analyze the tumor using different imaging modalities and at different times during the treatment. Each step is checked via 2D and 3D visualization. This framework was applied to a database of fifteen patients. For all patients, except one, the tumor volumes decrease globally and locally. Furthermore, a high correlation (r=0.77) was observed between MRI and Sestamibi tumor volumes. Finally, local indices show some possible mismatches between MRI Gadolinium uptake and Sestamibi uptake, which need to be further investigated.