Validation of a method to compensate multicenter effects affecting CT radiomic features

International audienc

Local classification of microvascular function based on contrast-enhanced ultrasound data: a feasibility study

National audienceDynamic contrast-enhanced ultrasound can detect microvascular flow changes during tumor development and antiangiogenic therapy. However, the standard method for microvascular flow estimation in tumors is global and can lead to bias in flow estimations in heterogeneous tumors. A new method to segment tumors according to their vascularization was investigated. In addition, parameter normalization with respect to a highly vascularized region of reference was proposed to overcome inter-exam variability in parameters. Results demonstrate the potential to locally classify tumoral tissue using parameters that describes the arrival of an ultrasound contrast agent in the tumor

Usefulness of Tc-99m Sestamibi studies for monitoring response to therapy in patients with high grade gliomas: a preliminary study

Congrès sous l’égide de la Société Française de Génie Biologique et Médical (SFGBM).National audienceEarly and late Sestamibi studies were acquired in addition to conventional MRI protocol in 14 patients with high-grade gliomas to monitor an antiangiogenic treatment. Global and local indices were deduced from these SPECT studies and were compared with progression free survival (PFS) and overall survival (OS). Variations of intensity in late studies were not correlated with PFS, but were related to OS. This suggests the possible role of Sestamibi for monitoring response to treatment

How can we combat multicenter variability in MR radiomics? Validation of a correction procedure

International audienc

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

International audienceA 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

Improved estimation of the left ventricular ejection fraction using a combination of independent automated segmentation results in cardiovascular magnetic resonance imaging

—This work aimed at combining different segmenta-tion 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 focusing on the left ventricular ejection fraction (LVEF) estimate resulting from the LV contour delineation using a public cardiac cine MRI database. Eight different segmentation methods, including three expert delineations, were studied, and sixteen combinations of the five automated methods were investigated. The supervised and unsupervised evaluations demonstrated that in most cases, STAPLE results provided better estimates of the LVEF than individual automated segmentation methods. In addition, LVEF obtained with STAPLE were within inter-expert variability. Overall, combining different automated segmentation methods improved the reliability of the segmenta-tion result compared to that obtained using an individual metho

Detection of recurrent nerve paralysis: Development of a Computer Aided Diagnosis system

International audienceRecurrent nerve paralysis (RP) is one of the most frequent complications of thyroid surgery. It reduces vocal fold mobility. Nasal endoscopy, a mini-invasive procedure, is the reference procedure to detect RP, and is based on the examination of vocal fold mobility. A new approach based on laryngeal ultrasound acquisition and using a dedicated data analysis was designed to help with the automated detection of RP. One hundred and fifty subjects were enrolled for this feasibility study: 50 controls, 50 patients with RP and 50 patients without RP, according to nasal endoscopy. The ultrasound protocol was based on a ten seconds B-mode acquisition in an axial plane during normal breathing. Image processing included three steps: 1) the detection of two consecutive closing and opening images corresponding to extreme positions of vocal folds in the sequence of B-mode images; 2) the positioning of three landmarks and the robust tracking of these points using multi-pyramidal refined optical flow approaches; 3) the estimation of quantitative parameters indicating left and right fractions of mobility and motion symmetry. Results provided by the first two image processing steps were compared to those obtained by an expert. Motion symmetry and fraction of mobility indices were systematically computed using the automated procedures. Associated sensitivity and specificity values for detecting RP were then calculated. To optimize the performances of the system, a mixed CAD system, which integrates the automatic steps of image processing and a possible correction of its results by a trained operator was developed. Laryngeal ultrasound combined with appropriate image processing helped in the diagnosis of recurrent nerve paralysis and could be proposed as a first–line method

Consistency of aortic distensibility and pulse wave velocity estimates with respect to the Bramwell-Hill theoretical model: a cardiovascular magnetic resonance study

<p>Abstract</p> <p>Background</p> <p>Arterial stiffness is considered as an independent predictor of cardiovascular mortality, and is increasingly used in clinical practice. This study aimed at evaluating the consistency of the automated estimation of regional and local aortic stiffness indices from cardiovascular magnetic resonance (CMR) data.</p> <p>Results</p> <p>Forty-six healthy subjects underwent carotid-femoral pulse wave velocity measurements (<it>CF_PWV</it>) by applanation tonometry and CMR with steady-state free-precession and phase contrast acquisitions at the level of the aortic arch. These data were used for the automated evaluation of the aortic arch pulse wave velocity (<it>Arch_PWV</it>), and the ascending aorta distensibility (<it>AA_Distc, AA_Distb)</it>, which were estimated from ascending aorta strain (<it>AA_Strain</it>) combined with either carotid or brachial pulse pressure. The local ascending aorta pulse wave velocity <it>AA_PWVc </it>and <it>AA_PWVb </it>were estimated respectively from these carotid and brachial derived distensibility indices according to the Bramwell-Hill theoretical model, and were compared with the <it>Arch_PWV</it>. In addition, a reproducibility analysis of <it>AA_PWV </it>measurement and its comparison with the standard <it>CF_PWV </it>was performed. Characterization according to the Bramwell-Hill equation resulted in good correlations between <it>Arch_PWV </it>and both local distensibility indices <it>AA_Distc </it>(r = 0.71, p < 0.001) and <it>AA_Distb </it>(r = 0.60, p < 0.001); and between <it>Arch_PWV </it>and both theoretical local indices <it>AA_PWVc </it>(r = 0.78, p < 0.001) and <it>AA_PWVb </it>(r = 0.78, p < 0.001). Furthermore, the <it>Arch_PWV </it>was well related to <it>CF_PWV </it>(r = 0.69, p < 0.001) and its estimation was highly reproducible (inter-operator variability: 7.1%).</p> <p>Conclusions</p> <p>The present work confirmed the consistency and robustness of the regional index <it>Arch_PWV </it>and the local indices <it>AA_Distc and AA_Distb </it>according to the theoretical model, as well as to the well established measurement of <it>CF_PWV</it>, demonstrating the relevance of the regional and local CMR indices.</p

Voxel-Based Statistical Analysis of 3D Immunostained Tissue Imaging

Recently developed techniques to visualize immunostained tissues in 3D and in large samples have expanded the scope of microscopic investigations at the level of the whole brain. Here, we propose to adapt voxel-based statistical analysis to 3D high-resolution images of the immunostained rodent brain. The proposed approach was first validated with a simulation dataset with known cluster locations. Then, it was applied to characterize the effect of ADAM30, a gene involved in the metabolism of the amyloid precursor protein, in a mouse model of Alzheimer's disease. This work introduces voxel-based analysis of 3D immunostained microscopic brain images and, therefore, opens the door to localized whole-brain exploratory investigation of pathological markers and cellular alterations