Hepatic tumor diagnosis by analysing dense transport fields in contrast-enhanced ultrasound

International audienceDynamic contrast agent enhanced ultrasound (DCEUS) is considered as a safe, noninvasive, accurate, and economic tool for analysing blood perfusion of various organs [1]. Gas-filled mi-crobubble contrast agents are used as intravascular flow tracers. In this study, a new methodology is proposed to quantify the divergence (i.e sources, sinks), curl (i.e sheering) and amplitude in the apparent microbubble transports during the bolus arrival. The efficiency of proposed methodology is evaluated in-vivo, for the classification of focal nodular hyperplasia (FNH) and inflammatory hepatic adenomas (I-HCA)

A framework for continuous target tracking during MR-guided high intensity focused ultrasound thermal ablations in the abdomen

Scatterplot showing percentage changes in stroke volume index (ΔSVI, %) and functional hemodynamic markers, Stroke Volume Variation (SVV, %) Pulse Pressure Variation (PPV, %), with the three tested tidal volumes (V T ), 6, 12 and 18 ml/kg during intra-abdominal hypertension. Solid line shows regression line between variables. (PDF 56 kb

Integration of operator-validated contours in deformable image registration for dose accumulation in radiotherapy

BACKGROUND AND PURPOSE: Deformable image registration (DIR) is a core element of adaptive radiotherapy workflows, integrating daily contour propagation and/or dose accumulation in their design. Propagated contours are usually manually validated and may be edited, thereby locally invalidating the registration result. This means the registration cannot be used for dose accumulation. In this study we proposed and evaluated a novel multi-modal DIR algorithm that incorporated contour information to guide the registration. This integrates operator-validated contours with the estimated deformation vector field and warped dose. MATERIALS AND METHODS: The proposed algorithm consisted of both a normalized gradient field-based data-fidelity term on the images and an optical flow data-fidelity term on the contours. The Helmholtz-Hodge decomposition was incorporated to ensure anatomically plausible deformations. The algorithm was validated for same- and cross-contrast Magnetic Resonance (MR) image registrations, Computed Tomography (CT) registrations, and CT-to-MR registrations for different anatomies, all based on challenging clinical situations. The contour-correspondence, anatomical fidelity, registration error, and dose warping error were evaluated. RESULTS: The proposed contour-guided algorithm considerably and significantly increased contour overlap, decreasing the mean distance to agreement by a factor of 1.3 to 13.7, compared to the best algorithm without contour-guidance. Importantly, the registration error and dose warping error decreased significantly, by a factor of 1.2 to 2.0. CONCLUSIONS: Our contour-guided algorithm ensured that the deformation vector field and warped quantitative information were consistent with the operator-validated contours. This provides a feasible semi-automatic strategy for spatially correct warping of quantitative information even in difficult and artefacted cases

Hepatic tumor diagnosis by analysing dense transport fields in contrast-enhanced ultrasound

International audienceDynamic contrast agent enhanced ultrasound (DCEUS) is considered as a safe, noninvasive, accurate, and economic tool for analysing blood perfusion of various organs [1]. Gas-filled mi-crobubble contrast agents are used as intravascular flow tracers. In this study, a new methodology is proposed to quantify the divergence (i.e sources, sinks), curl (i.e sheering) and amplitude in the apparent microbubble transports during the bolus arrival. The efficiency of proposed methodology is evaluated in-vivo, for the classification of focal nodular hyperplasia (FNH) and inflammatory hepatic adenomas (I-HCA)

A framework for continuous target tracking during MR-guided high intensity focused ultrasound thermal ablations in the abdomen

International audienceBackground: During lengthy magnetic resonance-guided high intensity focused ultrasound (MRg-HIFU) thermal ablations in abdominal organs, the therapeutic work-flow is frequently hampered by various types of physiological motion occurring at different time-scales. If left un-addressed this can lead to an incomplete therapy and/or to tissue damage of organs-at-risk. While previous studies focus on correction schemes for displacements occurring at a particular time-scale within the work-flow of an MRg-HIFU therapy, in the current work we propose a motion correction strategy encompassing the entire work-flow.Methods: The proposed motion compensation framework consists of several linked components, each being adapted to motion occurring at a particular time-scale. While respiration was addressed through a fast correction scheme, long term organ drifts were compensated using a strategy operating on time-scales of several minutes. The framework relies on a periodic examination of the treated area via MR scans which are then registered to a reference scan acquired at the beginning of the therapy. The resulting displacements were used for both on-the-fly re-optimization of the interventional plan and to ensure the spatial fidelity between the different steps of the therapeutic work-flow. The approach was validated in three complementary studies: an experiment conducted on a phantom undergoing a known motion pattern, a study performed on the abdomen of 10 healthy volunteers and during 3 in-vivo MRg-HIFU ablations on porcine liver.Results: Results have shown that, during lengthy MRg-HIFU thermal therapies, the human liver and kidney can manifest displacements that exceed acceptable therapeutic margins. Also, it was demonstrated that the proposed framework is capable of providing motion estimates with sub-voxel precision and accuracy. Finally, the 3 successful animal studies demonstrate the compatibility of the proposed approach with the work-flow of an MRg-HIFU intervention under clinical conditions.Conclusions: In the current study we proposed an image-based motion compensation framework dedicated to MRg-HIFU thermal ablations in the abdomen, providing the possibility to re-optimize the therapy plan on-the-fly with the patient on the interventional table. Moreover, we have demonstrated that even under clinical conditions, the proposed approach is fully capable of continuously ensuring the spatial fidelity between the different phases of the therapeutic work-flow

Anatomically-adaptive multi-modal image registration for image-guided external-beam radiotherapy

Image-guided radiotherapy (IGRT) allows observation of the location and shape of the tumor and organs-at-risk (OAR) over the course of a radiation cancer treatment. Such information may in turn be used for reducing geometric uncertainties during therapeutic planning, dose delivery and response assessment. However, given the multiple imaging modalities and/or contrasts potentially included within the imaging protocol over the course of the treatment, the current manual approach to determining tissue displacement may become time-consuming and error prone. In this context, variational multi-modal deformable image registration (DIR) algorithms allow automatic estimation of tumor and OAR deformations across the acquired images. In addition, they require short computational times and a low number of input parameters, which is particularly beneficial for online adaptive applications, which require on-the-fly adaptions with the patient on the treatment table. However, the majority of such DIR algorithms assume that all structures across the entire field-of-view (FOV) undergo a similar deformation pattern. Given that various anatomical structures may behave considerably different, this may lead to the estimation of anatomically implausible deformations at some locations, thus limiting their validity. Therefore, in this paper we propose an anatomically-adaptive variational multi-modal DIR algorithm, which employs a regionalized registration model in accordance with the local underlying anatomy. The algorithm was compared against two existing methods which employ global assumptions on the estimated deformations patterns. Compared to the existing approaches, the proposed method has demonstrated an improved anatomical plausibility of the estimated deformations over the entire FOV as well as displaying overall higher accuracy. Moreover, despite the more complex registration model, the proposed approach is very fast and thus suitable for online scenarios. Therefore, future adaptive IGRT workflows may benefit from an anatomically-adaptive registration model for precise contour propagation and dose accumulation, in areas showcasing considerable variations in anatomical properties