SearcharxivSearch

arXiv subjects

Matthieu Chabanas

Publications and source records attributed to Matthieu Chabanas.

At least 19 recordsLinked to original sources

Marker-free deformable registration and fusion for augmented reality-guided positive margin localization during tumor resection surgery

Positive margins in head and neck oncologic surgery require mapping specimen-side pathology findings to the patient resection bed. This is challenging because pathologists identify the positive margin on slices of the resected, deformed specimen, while surgeons must relocate the corresponding site on the resection bed using only verbal descriptions and no visual guidance. We present a marker-free augmented reality (AR) workflow for mapping a margin label from a three-dimensional specimen scan to the resection bed. The method combines contour-constrained deformation, residual alignment to a depth scan, surface-based fusion to a head-mounted display, and target projection onto the reconstructed bed. Bead-suture correspondences estimate specimen deformation, whereas patient-to-display fusion does not require external fiducial markers. Following formative experiments, five residents and surgeons performed cadaveric cheek and scalp re-resection tasks under verbal guidance, verbal guidance with specimen examination, and AR guidance. Deformation target errors were $7.63 \pm 3.74$ mm for the cheek and $3.72 \pm 1.02$ mm for the scalp; residual specimen-to-bed distances were $2.43 \pm 2.15$ mm and $2.19 \pm 1.06$ mm, respectively. Fusion error did not differ significantly between marker-free and marker-based methods on either cadaver; overall marker-free fusion error was $2.15 \pm 0.87$ mm. End-to-end margin localization error decreased from $21.40 \pm 3.84$ mm with verbal guidance and $16.09 \pm 4.30$ mm with specimen examination to $6.19 \pm 1.79$ mm with AR guidance ($p < 0.001$). Online fusion required $5.23 \pm 0.34$ s. These results demonstrate effective marker-free AR guidance for positive-margin localization and support more precise tumor resection.

cs.CV

Contour-Constrained Deformable Registration with Parameter Characterization for Head and Neck Surgical Guidance

With 890,000 annual new cases globally, head and neck squamous cell carcinoma has one of the highest recurrence rates among solid malignancies. Although frozen section analysis is the standard of care for intraoperative margin assessment, accurately relocating detected positive margins on the resection bed remains challenging due to imprecise alignment between resected specimens and their resection bed, compounded by post-resection mucosal tissue shrinkage. We present a biomechanics-driven deformable registration framework that corrects post-resection tissue deformation to provide intraoperative guidance. Our approach registers 3D specimen meshes to intraoperative resection bed point clouds using a deformable registration approach based on regularized Kelvinlet basis functions. The registration matches surface point clouds, fiducial landmarks, and boundary contour constraints that directly penalize perpendicular distance-to-agreement between specimen and resection bed boundaries. Across nine specimens from skin, buccal mucosa, and tongue sites, the overall mean target registration error was $11.11 \pm 4.07$ mm using rigid registration, which decreased to $8.20 \pm 2.68$ mm (26.19\% reduction) using deformable registration without contour constraint. The proposed contour-constrained deformable registration further reduced the error to $5.62 \pm 2.28$ mm, a 49.41\% reduction relative to rigid registration. We observed the largest reduction in the most clinically challenging tongue specimens. We also performed a systematic two-stage parameter search to characterize the relative importance of surface alignment, fiducial correspondences, contour constraint, and strain energy regularization. This search revealed that contour weighting dominates registration accuracy for tissue types with large lateral deformation, while the algorithm operates over a broad range of parameter combinations.

eess.IV

All-in-One Augmented Reality Guided Head and Neck Tumor Resection

Positive margins are common in head and neck squamous cell carcinoma, yet intraoperative re-resection is often imprecise because margin locations are typically communicated verbally from pathology. We present an all-in-one augmented reality (AR) system that relocalizes positive margins from a resected specimen to the resection bed and visualizes them in situ using HoloLens 2 depth sensing and fully automated markerless surface registration. In a silicone phantom study with six medical trainees, markerless registration achieved target registration errors comparable to a marker-based baseline (median 1.8 mm vs. 1.7 mm; maximum < 4 mm). In a margin relocalization task, AR guidance reduced error from verbal guidance (median 14.2 mm) to a few millimeters (median 3.2 mm), with all AR localizations within 5 mm error. These results support the feasibility of markerless AR margin guidance for more precise intraoperative re-excision.

cs.CV

Automated Assessment of Kidney Ureteroscopy Exploration for Training

Purpose: Kidney ureteroscopic navigation is challenging with a steep learning curve. However, current clinical training has major deficiencies, as it requires one-on-one feedback from experts and occurs in the operating room (OR). Therefore, there is a need for a phantom training system with automated feedback to greatly \revision{expand} training opportunities. Methods: We propose a novel, purely ureteroscope video-based scope localization framework that automatically identifies calyces missed by the trainee in a phantom kidney exploration. We use a slow, thorough, prior exploration video of the kidney to generate a reference reconstruction. Then, this reference reconstruction can be used to localize any exploration video of the same phantom. Results: In 15 exploration videos, a total of 69 out of 74 calyces were correctly classified. We achieve < 4mm camera pose localization error. Given the reference reconstruction, the system takes 10 minutes to generate the results for a typical exploration (1-2 minute long). Conclusion: We demonstrate a novel camera localization framework that can provide accurate and automatic feedback for kidney phantom explorations. We show its ability as a valid tool that enables out-of-OR training without requiring supervision from an expert.

eess.IV

RESECT-SEG: Open access annotations of intra-operative brain tumor ultrasound images

Purpose: Registration and segmentation of magnetic resonance (MR) and ultrasound (US) images play an essential role in surgical planning and resection of brain tumors. However, validating these techniques is challenging due to the scarcity of publicly accessible sources with high-quality ground truth information. To this end, we propose a unique annotation dataset of tumor tissues and resection cavities from the previously published RESECT dataset (Xiao et al. 2017) to encourage a more rigorous assessments of image processing techniques. Acquisition and validation methods: The RESECT database consists of MR and intraoperative US (iUS) images of 23 patients who underwent resection surgeries. The proposed dataset contains tumor tissues and resection cavity annotations of the iUS images. The quality of annotations were validated by two highly experienced neurosurgeons through several assessment criteria. Data format and availability: Annotations of tumor tissues and resection cavities are provided in 3D NIFTI formats. Both sets of annotations are accessible online in the \url{https://osf.io/6y4db}. Discussion and potential applications: The proposed database includes tumor tissue and resection cavity annotations from real-world clinical ultrasound brain images to evaluate segmentation and registration methods. These labels could also be used to train deep learning approaches. Eventually, this dataset should further improve the quality of image guidance in neurosurgery.

physics.med-ph

Measurement and Analysis of Lobar Lung Deformation After a Change of Patient Position During Video-Assisted Thoracoscopic Surgery

Video-assisted thoracoscopic surgery (VATS) is a minimally invasive surgical technique for the diagnosis and treatment of early-stage lung cancer. During VATS, large lung deformation occurs as a result of a change of patient position and a pneumothorax (lung deflation), which hinders the intraoperative localization of pulmonary nodules. Modeling lung deformation during VATS for surgical navigation is desirable, but the mechanisms causing such deformation are yet not well-understood. In this study, we estimate, quantify and analyze the lung deformation occurring after a change of patient position during VATS. We used deformable image registration to estimate the lung deformation between a preoperative CT (in supine position) and an intraoperative CBCT (in lateral decubitus position) of six VATS clinical cases. We accounted for sliding motion between lobes and against the thoracic wall and obtained consistently low average target registration errors (under 1 mm). We observed large lung displacement (up to 40 mm); considerable sliding motion between lobes and against the thoracic wall (up to 30 mm); and localized volume changes indicating deformation. These findings demonstrate the complexity of the change of patient position phenomenon, which should necessarily be taken into account to model lung deformation for intraoperative guidance during VATS.

physics.med-ph

Evaluation of MRI to ultrasound registration methods for brain shift correction: The CuRIOUS2018 Challenge

In brain tumor surgery, the quality and safety of the procedure can be impacted by intra-operative tissue deformation, called brain shift. Brain shift can move the surgical targets and other vital structures such as blood vessels, thus invalidating the pre-surgical plan. Intra-operative ultrasound (iUS) is a convenient and cost-effective imaging tool to track brain shift and tumor resection. Accurate image registration techniques that update pre-surgical MRI based on iUS are crucial but challenging. The MICCAI Challenge 2018 for Correction of Brain shift with Intra-Operative UltraSound (CuRIOUS2018) provided a public platform to benchmark MRI-iUS registration algorithms on newly released clinical datasets. In this work, we present the data, setup, evaluation, and results of CuRIOUS 2018, which received 6 fully automated algorithms from leading academic and industrial research groups. All algorithms were first trained with the public RESECT database, and then ranked based on test dataset of 10 additional cases with identical data curation and annotation protocols as the RESECT database. The article compares the results of all participating teams and discusses the insights gained from the challenge, as well as future work.

eess.IV

A biomechanical model of the face including muscles for the prediction of deformations during speech production

A 3D biomechanical finite element model of the face is presented. Muscles are represented by piece-wise uniaxial tension cable elements linking the insertion points. Such insertion points are specific entities differing from nodes of the finite element mesh, which makes possible to change either the mesh or the muscle implementation totally independently of each other. Lip/teeth and upper lip/lower lip contacts are also modeled. Simulations of smiling and of an Orbicularis Oris activation are presented and interpreted. The importance of a proper account of contacts and of an accurate anatomical description is shown

physics.med-ph

Computer aided planning and navigation for orbito-zygomatic reconstruction

This paper suggests a full protocol of Computer Aided Surgery as previously recommended in literature addressing the challenging task of primary or secondary reconstruction of orbito-zygomatic dislocation. First, on a specifically developed planning software, the best zygoma reduction and orbital boundaries reconstruction to achieve skeletal symmetry are determined. This treatment plan is then transferred to the 3D Navigation Systems within the operating room. After patient's anatomy registration to his preoperative CT scan data, the navigation system allows zygomatic guiding to its planned reduced location and bone orbital volume restoration control. The feasibility of this technique was checked in 3 patients with major orbito-zygomatic deformities. Preliminary clinical results are presented.

physics.med-ph

Computer aided planning for orthognatic surgery

A computer aided maxillofacial sequence is presented, applied to orthognatic surgery. It consists of 5 main stages: data acquisition and integration, surgical planning, surgical simulation, and per operative assistance. The planning and simulation steps are then addressed in a way that is clinically relevant. First concepts toward a 3D cephalometry are presented for a morphological analysis, surgical planning, and bone and soft tissue simulation. The aesthetic surgical outcomes of bone repositioning are studied with a biomechanical Finite Element soft tissue model.

physics.med-ph

Evaluating soft tissue simulation in maxillofacial surgery using pre and post-operative CT scan

One of the most important issue in soft tissue modeling is to assess the quality of the simulations. A validation protocol is presented based on two CT scans of the patient acquired before and after cranio-maxillofacial surgery. The actual bones repositioning realized during the intervention are accurately measured and reproduced. A evaluation of the soft tissue deformation is then computed using a finite element model of the face. The simulations are therefore compared, qualitatively and quantitatively, with the actual outcome of the surgery. This protocol enable to rigorously evaluate different modeling methods, and to assess the clinical relevance of soft tissue simulation in maxillofacial surgery.

physics.med-ph

Computer-aided planning for zygomatic bone reconstruction in maxillofacial traumatology

An optimal planning procedure has been proposed to define the target position of the zygomatic bone following a fracture of the mid-face skeleton. The protocol has been successfully tested on healthy subjects, and ensures the global symmetry of the face could be obtained after the reconstruction surgery. Now that the planning procedure is available, the next step of this project will be to develop an intra-operative guiding system to help the surgeon to follow the planning. This procedure will mainly rely on the intra-operative registration of the zygomatic bone fragment, and the design of specific surgical ancillaries for cranio-maxillofacial surgery.

physics.med-ph

Biomechanics applied to computer-aided diagnosis: examples of orbital and maxillofacial surgeries

This paper introduces the methodology proposed by our group to model the biological soft tissues deformations and to couple these models with Computer-Assisted Surgical (CAS) applications. After designing CAS protocols that mainly focused on bony structures, the Computer Aided Medical Imaging group of Laboratory TIMC (CNRS, France) now tries to take into account the behaviour of soft tissues in the CAS context. For this, a methodology, originally published under the name of the Mesh-Matching method, has been proposed to elaborate patient specific models. Starting from an elaborate manually-built "generic" Finite Element (FE) model of a given anatomical structure, models adapted to the geometries of each new patient ("patient specific" FE models) are automatically generated through a non-linear elastic registration algorithm. This paper presents the general methodology of the Mesh-Matching method and illustrates this process with two clinical applications, namely the orbital and the maxillofacial computer-assisted surgeries.

physics.med-ph

Comparison of linear and non-linear soft tissue models with post-operative CT scan in maxillofacial surgery

A Finite Element model of the face soft tissue is proposed to simulate the morphological outcomes of maxillofacial surgery. Three modelling options are implemented: a linear elastic model with small and large deformation hypothesis, and an hyperelastic Mooney-Rivlin model. An evaluation procedure based on a qualitative and quantitative comparison of the simulations with a post-operative CT scan is detailed. It is then applied to one clinical case to evaluate the differences between the three models, and with the actual patient morphology. First results shows in particular that for a "simple" clinical procedure where stress is less than 20%, a linear model seams sufficient for a correct modelling.

physics.med-ph

Models for Planning and Simulation in Computer Assisted Orthognatic Surgery

Two aspects required to establish a planning in orthognatic surgery are addressed in this paper. First, a 3D cephalometric analysis, which is clini-cally essential for the therapeutic decision. Then, an original method to build a biomechanical model of patient face soft tissue, which provides evaluation of the aesthetic outcomes of an intervention. Both points are developed within a clinical application context for computer aided maxillofacial surgery.

physics.med-ph

A 3D Finite Element model of the face for simulation in plastic and maxillo-facial surgery

This paper introduces a new Finite Element biomechanical model of the human face, which has been developed to be integrated into a simulator for plastic and maxillo-facial surgery. The idea is to be able to predict, from an aesthetic and functional point of view, the deformations of a patient face, resulting from repositioning of the maxillary and mandibular bone structures. This work will complete the simulator for bone-repositioning diagnosis that has been developed by the laboratory. After a description of our research project context, each step of the modeling is precisely described: the continuous and elastic structure of the skin tissues, the orthotropic muscular fibers and their insertions points, and the functional model of force generation. First results of face deformations due to muscles activations are presented. They are qualitatively compared to the functional studies provided by the literature on face muscles roles and actions.

physics.med-ph