Deformable Multi-material 2-Simplex Surface Mesh for Intraoperative MRI-Ready Surgery Planning and Simulation, with Deep-Brain Stimulation Applications

Rashid, Tanweer; Sultana, Sharmin; Fischer, Gregory S.; Pilitsis, Julie G.; Audette, Michel

doi:10.1007/978-3-319-67552-7_12

Cited by 3 publications

(2 citation statements)

References 6 publications

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“…35 In conjunction with this MRI-compatible DBS robotic assistant, the first author has sought to develop a deformable multi-surface model of a digital deep brain atlas, 36 which is conducive to fast updates in conjunction with intraoperative MR imaging. 37 The efficiency of the MRI reconstruction itself must also be an important consideration. Huang et al have proposed fast reconstruction of multi-contrast MR images from partially sampled signals in k-space.…”

Section: Coping With Soft-tissue Motion Through Intraoperative Imagingmentioning

confidence: 99%

<p>Robotically Steered Needles: A Survey of Neurosurgical Applications and Technical Innovations</p>

Audette¹,

Bordas²,

Blatt³

2020

RSRR

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This paper surveys both the clinical applications and main technical innovations related to steered needles, with an emphasis on neurosurgery. Technical innovations generally center on curvilinear robots that can adopt a complex path that circumvents critical structures and eloquent brain tissue. These advances include several needle-steering approaches, which consist of tip-based, lengthwise, base motion-driven, and tissue-centered steering strategies. This paper also describes foundational mathematical models for steering, where potential fields, nonholonomic bicycle-like models, spring models, and stochastic approaches are cited. In addition, practical path planning systems are also addressed, where we cite uncertainty modeling in path planning, intraoperative soft tissue shift estimation through imaging scans acquired during the procedure, and simulation-based prediction. Neurosurgical scenarios tend to emphasize straight needles so far, and span deep-brain stimulation (DBS), stereoelectroencephalography (SEEG), intracerebral drug delivery (IDD), stereotactic brain biopsy (SBB), stereotactic needle aspiration for hematoma, cysts and abscesses, and brachytherapy as well as thermal ablation of brain tumors and seizure-generating regions. We emphasize therapeutic considerations and complications that have been documented in conjunction with these applications.

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Section: Coping With Soft-tissue Motion Through Intraoperative Imagingmentioning

confidence: 99%

<p>Robotically Steered Needles: A Survey of Neurosurgical Applications and Technical Innovations</p>

Audette¹,

Bordas²,

Blatt³

2020

RSRR

View full text Add to dashboard Cite

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“…Such a conversion of a CAD model is surprisingly absent in literature and permits the use of the CAD drawing as a foundation for a deformable multi-surface model-based segmentation, particularly for musculoskeletal applications where ligamentous models are essential: orthopedics, obstetrics, etc. Extending the single-surface deformable model to include multiple anatomical boundaries is possible through Rashid's multi-surface methodology that emphasizes shared boundaries based on multi-material surface extraction (Rashid et al, 2017). This approach produces models of weight-bearing anatomy which maintain flush surfaces as needed.…”

Section: Converting Generic Anatomical Modelsmentioning

confidence: 99%

"""Surgical Gps"" Proof of Concept for Scoliosis Surgery"

Tapp

Audette

2020

Spring Simulation Conference (SpringSim 2020)

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Scoliotic deformities may be addressed with either anterior or posterior approaches for scoliosis correction procedures. While typically quite invasive, the impact of these operations may be reduced through the use of computer-assisted surgery. A combination of physician-designated anatomical landmarks and surgical ontologies allows for real-time intraoperative guidance during computer-assisted surgical interventions. Predetermined landmarks are labeled on an identical patient model, which seeks to encompass vertebrae, intervertebral disks, ligaments, and other soft tissues. The inclusion of this anatomy permits the consideration of hypothetical forces that are previously not well characterized in a patient-specific manner. Updated ontologies then suggest procedural directions throughout the surgical corridor, observing the positioning of both the physician and the anatomical landmarks of interest at the present moment. Merging patient-specific models, physician-designated landmarks, and ontologies to produce real-time recommendations magnifies the successful outcome of scoliosis correction through enhanced pre-surgical planning, reduced invasiveness, and shorted recovery time.

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Towards a Deformable Multi-surface Approach to Ligamentous Spine Models for Predictive Simulation-Based Scoliosis Surgery Planning

Audette

Schmid

Goodmurphy

et al. 2019

Lecture Notes in Computer Science

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Scoliosis correction surgery is typically a highly invasive procedure that involves either an anterior or posterior release, which respectively entail the resection of ligaments and bone facets from the front or back of the spine, in order to make it sufficiently compliant to enable the correction of the deformity. In light of progress in other areas of surgery in minimally invasive therapies, orthopedic surgeons have begun envisioning computer simulation-assisted planning that could answer unprecedented what-if questions. This paper presents preliminary steps taken towards finite elements simulation-based surgery planning that will provide answers as to how much anterior or posterior release is truly necessary, provided we also establish the amplitude of surgical forces involved in corrective surgery. This question motivates us to pursue a medical image-based anatomical modeling pipeline that can support personalized finite elements simulation, based on models of the spine that not only feature vertebrae and intervertebral discs (IVDs), but also descriptive ligament models. This paper suggests a way of proceeding, based on the application of deformable multi-surface Simplex model to a CAD-based representation of the spine that makes explicit all spinal ligaments, along with vertebrae and IVDs. It presents a preliminary model-based segmentation study whereby Simplex meshes of CAD vertebrae are registered to the subject's corresponding vertebrae in CT data, which then drives ligament and IVD model registration by aggregation of neighboring vertebral transformations. This framework also anticipates foreseen improvements in MR imaging that could achieve better contrasts in ligamentous tissues in the future.

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Deformable Multi-material 2-Simplex Surface Mesh for Intraoperative MRI-Ready Surgery Planning and Simulation, with Deep-Brain Stimulation Applications

Cited by 3 publications

References 6 publications

<p>Robotically Steered Needles: A Survey of Neurosurgical Applications and Technical Innovations</p>

<p>Robotically Steered Needles: A Survey of Neurosurgical Applications and Technical Innovations</p>

"""Surgical Gps"" Proof of Concept for Scoliosis Surgery"

Towards a Deformable Multi-surface Approach to Ligamentous Spine Models for Predictive Simulation-Based Scoliosis Surgery Planning

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