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Dive into the research topics where David Rivest-Hénault is active.

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Featured researches published by David Rivest-Hénault.


International Journal of Radiation Oncology Biology Physics | 2015

Automatic Substitute Computed Tomography Generation and Contouring for Magnetic Resonance Imaging (MRI)-Alone External Beam Radiation Therapy From Standard MRI Sequences

Jason Dowling; Jidi Sun; Peter Pichler; David Rivest-Hénault; Soumya Ghose; Haylea Richardson; Chris Wratten; Jarad Martin; Jameen Arm; Leah Best; Shekhar S. Chandra; Jurgen Fripp; F. W. Menk; Peter B. Greer

PURPOSE To validate automatic substitute computed tomography CT (sCT) scans generated from standard T2-weighted (T2w) magnetic resonance (MR) pelvic scans for MR-Sim prostate treatment planning. PATIENTS AND METHODS A Siemens Skyra 3T MR imaging (MRI) scanner with laser bridge, flat couch, and pelvic coil mounts was used to scan 39 patients scheduled for external beam radiation therapy for localized prostate cancer. For sCT generation a whole-pelvis MRI scan (1.6 mm 3-dimensional isotropic T2w SPACE [Sampling Perfection with Application optimized Contrasts using different flip angle Evolution] sequence) was acquired. Three additional small field of view scans were acquired: T2w, T2*w, and T1w flip angle 80° for gold fiducials. Patients received a routine planning CT scan. Manual contouring of the prostate, rectum, bladder, and bones was performed independently on the CT and MR scans. Three experienced observers contoured each organ on MRI, allowing interobserver quantification. To generate a training database, each patient CT scan was coregistered to their whole-pelvis T2w using symmetric rigid registration and structure-guided deformable registration. A new multi-atlas local weighted voting method was used to generate automatic contours and sCT results. RESULTS The mean error in Hounsfield units between the sCT and corresponding patient CT (within the body contour) was 0.6 ± 14.7 (mean ± 1 SD), with a mean absolute error of 40.5 ± 8.2 Hounsfield units. Automatic contouring results were very close to the expert interobserver level (Dice similarity coefficient): prostate 0.80 ± 0.08, bladder 0.86 ± 0.12, rectum 0.84 ± 0.06, bones 0.91 ± 0.03, and body 1.00 ± 0.003. The change in monitor units between the sCT-based plans relative to the gold standard CT plan for the same dose prescription was found to be 0.3% ± 0.8%. The 3-dimensional γ pass rate was 1.00 ± 0.00 (2 mm/2%). CONCLUSIONS The MR-Sim setup and automatic sCT generation methods using standard MR sequences generates realistic contours and electron densities for prostate cancer radiation therapy dose planning and digitally reconstructed radiograph generation.


Medical Physics | 2015

Continuous table acquisition MRI for radiotherapy treatment planning: distortion assessment with a new extended 3D volumetric phantom

Amy Walker; Gary P Liney; Lois C Holloway; Jason Dowling; David Rivest-Hénault; Peter E Metcalfe

PURPOSE Accurate geometry is required for radiotherapy treatment planning (RTP). When considering the use of magnetic resonance imaging (MRI) for RTP, geometric distortions observed in the acquired images should be considered. While scanner technology and vendor supplied correction algorithms provide some correction, large distortions are still present in images, even when considering considerably smaller scan lengths than those typically acquired with CT in conventional RTP. This study investigates MRI acquisition with a moving table compared with static scans for potential geometric benefits for RTP. METHODS A full field of view (FOV) phantom (diameter 500 mm; length 513 mm) was developed for measuring geometric distortions in MR images over volumes pertinent to RTP. The phantom consisted of layers of refined plastic within which vitamin E capsules were inserted. The phantom was scanned on CT to provide the geometric gold standard and on MRI, with differences in capsule location determining the distortion. MRI images were acquired with two techniques. For the first method, standard static table acquisitions were considered. Both 2D and 3D acquisition techniques were investigated. With the second technique, images were acquired with a moving table. The same sequence was acquired with a static table and then with table speeds of 1.1 mm/s and 2 mm/s. All of the MR images acquired were registered to the CT dataset using a deformable B-spline registration with the resulting deformation fields providing the distortion information for each acquisition. RESULTS MR images acquired with the moving table enabled imaging of the whole phantom length while images acquired with a static table were only able to image 50%-70% of the phantom length of 513 mm. Maximum distortion values were reduced across a larger volume when imaging with a moving table. Increased table speed resulted in a larger contribution of distortion from gradient nonlinearities in the through-plane direction and an increased blurring of capsule images, resulting in an apparent capsule volume increase by up to 170% in extreme axial FOV regions. Blurring increased with table speed and in the central regions of the phantom, geometric distortion was less for static table acquisitions compared to a table speed of 2 mm/s over the same volume. Overall, the best geometric accuracy was achieved with a table speed of 1.1 mm/s. CONCLUSIONS The phantom designed enables full FOV imaging for distortion assessment for the purposes of RTP. MRI acquisition with a moving table extends the imaging volume in the z direction with reduced distortions which could be useful particularly if considering MR-only planning. If utilizing MR images to provide additional soft tissue information to the planning CT, standard acquisition sequences over a smaller volume would avoid introducing additional blurring or distortions from the through-plane table movement.


Medical Image Analysis | 2015

Robust inverse-consistent affine CT-MR registration in MRI-assisted and MRI-alone prostate radiation therapy

David Rivest-Hénault; Nicholas Dowson; Peter B. Greer; Jurgen Fripp; Jason Dowling

BACKGROUND CT-MR registration is a critical component of many radiation oncology protocols. In prostate external beam radiation therapy, it allows the propagation of MR-derived contours to reference CT images at the planning stage, and it enables dose mapping during dosimetry studies. The use of carefully registered CT-MR atlases allows the estimation of patient specific electron density maps from MRI scans, enabling MRI-alone radiation therapy planning and treatment adaptation. In all cases, the precision and accuracy achieved by registration influences the quality of the entire process. PROBLEM Most current registration algorithms do not robustly generalize and lack inverse-consistency, increasing the risk of human error and acting as a source of bias in studies where information is propagated in a particular direction, e.g. CT to MR or vice versa. In MRI-based treatment planning where both CT and MR scans serve as spatial references, inverse-consistency is critical, if under-acknowledged. PURPOSE A robust, inverse-consistent, rigid/affine registration algorithm that is well suited to CT-MR alignment in prostate radiation therapy is presented. METHOD The presented method is based on a robust block-matching optimization process that utilises a half-way space definition to maintain inverse-consistency. Inverse-consistency substantially reduces the influence of the order of input images, simplifying analysis, and increasing robustness. An open source implementation is available online at http://aehrc.github.io/Mirorr/. RESULTS Experimental results on a challenging 35 CT-MR pelvis dataset demonstrate that the proposed method is more accurate than other popular registration packages and is at least as accurate as the state of the art, while being more robust and having an order of magnitude higher inverse-consistency than competing approaches. CONCLUSION The presented results demonstrate that the proposed registration algorithm is readily applicable to prostate radiation therapy planning.


Physics in Medicine and Biology | 2015

MRI simulation: end-to-end testing for prostate radiation therapy using geometric pelvic MRI phantoms.

Jidi Sun; Jason Dowling; Peter Pichler; F. W. Menk; David Rivest-Hénault; Jonathan Lambert; Joel Parker; Jameen Arm; Leah Best; Jarad Martin; James W. Denham; Peter B. Greer

To clinically implement MRI simulation or MRI-alone treatment planning requires comprehensive end-to-end testing to ensure an accurate process. The purpose of this study was to design and build a geometric phantom simulating a human male pelvis that is suitable for both CT and MRI scanning and use it to test geometric and dosimetric aspects of MRI simulation including treatment planning and digitally reconstructed radiograph (DRR) generation.A liquid filled pelvic shaped phantom with simulated pelvic organs was scanned in a 3T MRI simulator with dedicated radiotherapy couch-top, laser bridge and pelvic coil mounts. A second phantom with the same external shape but with an internal distortion grid was used to quantify the distortion of the MR image. Both phantoms were also CT scanned as the gold-standard for both geometry and dosimetry. Deformable image registration was used to quantify the MR distortion. Dose comparison was made using a seven-field IMRT plan developed on the CT scan with the fluences copied to the MR image and recalculated using bulk electron densities. Without correction the maximum distortion of the MR compared with the CT scan was 7.5 mm across the pelvis, while this was reduced to 2.6 and 1.7 mm by the vendors 2D and 3D correction algorithms, respectively. Within the locations of the internal organs of interest, the distortion was <1.5 and <1 mm with 2D and 3D correction algorithms, respectively. The dose at the prostate isocentre calculated on CT and MRI images differed by 0.01% (1.1 cGy). Positioning shifts were within 1 mm when setup was performed using MRI generated DRRs compared to setup using CT DRRs.The MRI pelvic phantom allows end-to-end testing of the MRI simulation workflow with comparison to the gold-standard CT based process. MRI simulation was found to be geometrically accurate with organ dimensions, dose distributions and DRR based setup within acceptable limits compared to CT.


Journal of Physics: Conference Series | 2014

Inverse-consistent rigid registration of CT and MR for MR-based planning and adaptive prostate radiation therapy

David Rivest-Hénault; Nicholas Dowson; Peter B. Greer; Jason Dowling

MRI-alone treatment planning and adaptive MRI-based prostate radiation therapy are two promising techniques that could significantly increase the accuracy of the curative dose delivery processes while reducing the total radiation dose. State-of-the-art methods rely on the registration of a patient MRI with a MR-CT atlas for the estimation of pseudo-CT [5]. This atlas itself is generally created by registering many CT and MRI pairs. Most registration methods are not symmetric, but the order of the images influences the result [8]. The computed transformation is therefore biased, introducing unwanted variability. This work examines how much a symmetric algorithm improves the registration. Methods: A robust symmetric registration algorithm is proposed that simultaneously optimises a half space transform and its inverse. During the registration process, the two input volumetric images are transformed to a common position in space, therefore minimising any computational bias. An asymmetrical implementation of the same algorithm was used for comparison purposes. Results: Whole pelvis MRI and CT scans from 15 prostate patients were registered, as in the creation of MR-CT atlases. In each case, two registrations were performed, with different input image orders, and the transformation error quantified. Mean residuals of 0.63±0.26 mm (translation) and (8.7±7.3) × 10−-3 rad (rotation) were found for the asymmetrical implementation with corresponding values of 0.038±0.039 mm and (1.6 ± 1.3) × 10−-3 rad for the proposed symmetric algorithm, a substantial improvement. Conclusions: The increased registration precision will enhance the generation of pseudo-CT from MRI for atlas based MR planning methods.


XVII International Conference on the Use of Computers in Radiation Therapy | 2014

Automatic Atlas Based Electron Density and Structure Contouring for MRI-based Prostate Radiation Therapy on the Cloud

Jason Dowling; N Burdett; Peter B. Greer; Jidi Sun; Joel Parker; Peter Pichler; Peter Stanwell; Shekhar S. Chandra; David Rivest-Hénault; Soumya Ghose; Olivier Salvado; Jurgen Fripp

Our group have been developing methods for MRI-alone prostate cancer radiation therapy treatment planning. To assist with clinical validation of the workflow we are investigating a cloud platform solution for research purposes. Benefits of cloud computing can include increased scalability, performance and extensibility while reducing total cost of ownership. In this paper we demonstrate the generation of DICOM-RT directories containing an automatic average atlas based electron density image and fast pelvic organ contouring from whole pelvis MR scans.


Journal of Applied Clinical Medical Physics | 2016

MRI geometric distortion: Impact on tangential whole-breast IMRT

Amy Walker; Peter E Metcalfe; Gary P Liney; Vikneswary Batumalai; Kylie L Dundas; Carri Glide-Hurst; Geoff Delaney; Miriam M Boxer; Mei Ling Yap; Jason Dowling; David Rivest-Hénault; Elise M. Pogson; Lois C Holloway

The purpose of this study was to determine the impact of magnetic resonance imaging (MRI) geometric distortions when using MRI for target delineation and planning for whole‐breast, intensity‐modulated radiotherapy (IMRT). Residual system distortions and combined systematic and patient‐induced distortions are considered. This retrospective study investigated 18 patients who underwent whole‐breast external beam radiotherapy, where both CT and MRIs were acquired for treatment planning. Distortion phantoms were imaged on two MRI systems, dedicated to radiotherapy planning (a wide, closed‐bore 3T and an open‐bore 1T). Patient scans were acquired on the 3T system. To simulate MRI‐based planning, distortion maps representing residual system distortions were generated via deformable registration between phantom CT and MRIs. Patient CT images and structures were altered to match the residual system distortion measured by the phantoms on each scanner. The patient CTs were also registered to the corresponding patient MRI scans, to assess patient and residual system effects. Tangential IMRT plans were generated and optimized on each resulting CT dataset, then propagated to the original patient CT space. The resulting dose distributions were then evaluated with respect to the standard clinically acceptable DVH and visual assessment criteria. Maximum residual systematic distortion was measured to be 7.9 mm (95%<4.7mm) and 11.9 mm (95%<4.6mm) for the 3T and 1T scanners, respectively, which did not result in clinically unacceptable plans. Eight of the plans accounting for patient and systematic distortions were deemed clinically unacceptable when assessed on the original CT. For these plans, the mean difference in PTV V95 (volume receiving 95% prescription dose) was 0.13±2.51% and −0.73±1.93% for right‐ and left‐sided patients, respectively. Residual system distortions alone had minimal impact on the dosimetry for the two scanners investigated. The combination of MRI systematic and patient‐related distortions can result in unacceptable dosimetry for whole‐breast IMRT, a potential issue when considering MRI‐only radiotherapy treatment planning. PACS number(s): 87.61.‐c, 87.57.cp, 87.57.nj, 87.55.D‐


Workshop on Clinical Image-Based Procedures | 2013

Structure-Guided Nonrigid Registration of CT–MR Pelvis Scans with Large Deformations in MR-Based Image Guided Radiation Therapy

David Rivest-Hénault; Peter B. Greer; Jurgen Fripp; Jason Dowling

Multimodal registration of CT and MR scans is a required step in leading edge adaptive MR-based image guided radiation therapy protocols. Yet, anatomical changes limit the precision of the registration process and therefore that of the whole intervention. In prostate radiation therapy, the difference in bladder and rectum filling can significantly displace both the targeted area and the organs at risk. Here, we describe a method that integrates an image-based similarity criterion with the anatomical information from manual contours to guide the registration process toward an accurate solution. Whole pelvis CT and MR scans of 33 patients have been nonrigidly registered, and the proposed method leads to an average improvement of 0.17 DSC when compared to a baseline nonrigid registrations. The increased accuracy will thus enhance an MR-based prostate radiation therapy protocol.


International MICCAI Workshop on Medical Computer Vision | 2014

Fast Multiatlas Selection Using Composition of Transformations for Radiation Therapy Planning

David Rivest-Hénault; Soumya Ghose; Josien P. W. Pluim; Peter B. Greer; Jurgen Fripp; Jason Dowling

In radiation therapy, multiatlas segmentation is recognized as being accurate, but is generally not considered scalable since the highest accuracy is achieved only when using a large atlas database. The fundamental problem is to use such a large database, to accurately represent the population variability, while conserving a relatively small computational cost. A method based on the composition of transformations is proposed to address this issue. The main novelties and key contributions of this paper are the definition of a transitivity error function and the presentation of an image clustering scheme that is based solely on the computed registration transformations. Leave-one-out experiments conducted on a database of \(N=50\) MR prostate scans demonstrate that a reduction of \((N-1)=49\)x in the number of pre-alignment registrations, and of 3.2x in term of total registration effort, is possible without significant impact on segmentation quality.


Computer Methods and Programs in Biomedicine | 2018

A lightweight rapid application development framework for biomedical image analysis

Shekhar S. Chandra; Jason Dowling; Craig Engstrom; Ying Xia; Anthony Paproki; Ales Neubert; David Rivest-Hénault; Olivier Salvado; Stuart Crozier; Jurgen Fripp

Biomedical imaging analysis typically comprises a variety of complex tasks requiring sophisticated algorithms and visualising high dimensional data. The successful integration and deployment of the enabling software to clinical (research) partners, for rigorous evaluation and testing, is a crucial step to facilitate adoption of research innovations within medical settings. In this paper, we introduce the Simple Medical Imaging Library Interface (SMILI), an object oriented open-source framework with a compact suite of objects geared for rapid biomedical imaging (cross-platform) application development and deployment. SMILI supports the development of both command-line (shell and Python scripting) and graphical applications utilising the same set of processing algorithms. It provides a substantial subset of features when compared to more complex packages, yet it is small enough to ship with clinical applications with limited overhead and has a license suitable for commercial use. After describing where SMILI fits within the existing biomedical imaging software ecosystem, by comparing it to other state-of-the-art offerings, we demonstrate its capabilities in creating a clinical application for manual measurement of cam-type lesions of the femoral head-neck region for the investigation of femoro-acetabular impingement (FAI) from three dimensional (3D) magnetic resonance (MR) images of the hip. This application for the investigation of FAI proved to be convenient for radiological analyses and resulted in high intra (ICC=0.97) and inter-observer (ICC=0.95) reliabilities for measurement of α-angles of the femoral head-neck region. We believe that SMILI is particularly well suited for prototyping biomedical imaging applications requiring user interaction and/or visualisation of 3D mesh, scalar, vector or tensor data.

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Jason Dowling

Commonwealth Scientific and Industrial Research Organisation

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Jurgen Fripp

Commonwealth Scientific and Industrial Research Organisation

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Jidi Sun

University of Newcastle

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Soumya Ghose

Case Western Reserve University

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Jarad Martin

University of Newcastle

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Amy Walker

University of Wollongong

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