Development of an Atlas-Based Segmentation of Cranial Nerves Using Shape-Aware Discrete Deformable Models for Neurosurgical Planning and Simulation

Twelve pairs of cranial nerves arise from the brain or brainstem and control our sensory functions such as vision, hearing, smell and taste as well as several motor functions to the head and neck including facial expressions and eye movement. Often, these cranial nerves are difficult to detect in MRI data, and thus represent problems in neurosurgery planning and simulation, due to their thin anatomical structure, in the face of low imaging resolution as well as image artifacts. As a result, they may be at risk in neurosurgical procedures around the skull base, which might have dire consequences such as the loss of eyesight or hearing and facial paralysis. Consequently, it is of great importance to clearly delineate cranial nerves in medical images for avoidance in the planning of neurosurgical procedures and for targeting in the treatment of cranial nerve disorders. In this research, we propose to develop a digital atlas methodology that will be used to segment the cranial nerves from patient image data. The atlas will be created from high-resolution MRI data based on a discrete deformable contour model called 1-Simplex mesh. Each of the cranial nerves will be modeled using its centerline and radius information where the centerline is estimated in a semi-automatic approach by finding a shortest path between two user-defined end points. The cranial nerve atlas is then made more robust by integrating a Statistical Shape Model so that the atlas can identify and segment nerves from images characterized by artifacts or low resolution. To the best of our knowledge, no such digital atlas methodology exists for segmenting nerves cranial nerves from MRI data. Therefore, our proposed system has important benefits to the neurosurgical community

Deformable Contour Models for Digitizing a Printed Brainstem Atlas

The brainstem is a part of the brain that is connected to the cerebrum and the spinal cord. Ten out of twelve pairs of cranial nerves emerge from the brainstem. The cranial nerves transmit information between the brain and various parts of the body. Due to its anatomical and physiological relevance, a descriptive digital brainstem is important for neurosurgery planning and simulation. For both of these neurosurgical applications, the complexity of the brainstem requires a digital atlas approach to segmentation that maps intensities to tissues rather than less descriptive voxel or surface-based approaches. However, a descriptive brainstem atlas with adequate details for neurosurgery planning and simulation has not been developed to date. Fortunately, various textbooks contain 2D representations of the brainstem at various longitudinal coordinates. The aim of this thesis is to describe a minimally supervised method to segment sketches coinciding with slices of the brainstem featuring labeled contours. This thesis also describes a deformable contour model approach, emphasizing a 1-simplex framework, to reconstruct a 3D volume from 2D slices

Multi-Material Mesh Representation of Anatomical Structures for Deep Brain Stimulation Planning

The Dual Contouring algorithm (DC) is a grid-based process used to generate surface meshes from volumetric data. However, DC is unable to guarantee 2-manifold and watertight meshes due to the fact that it produces only one vertex for each grid cube. We present a modified Dual Contouring algorithm that is capable of overcoming this limitation. The proposed method decomposes an ambiguous grid cube into a set of tetrahedral cells and uses novel polygon generation rules that produce 2-manifold and watertight surface meshes with good-quality triangles. These meshes, being watertight and 2-manifold, are geometrically correct, and therefore can be used to initialize tetrahedral meshes. The 2-manifold DC method has been extended into the multi-material domain. Due to its multi-material nature, multi-material surface meshes will contain non-manifold elements along material interfaces or shared boundaries. The proposed multi-material DC algorithm can (1) generate multi-material surface meshes where each material sub-mesh is a 2-manifold and watertight mesh, (2) preserve the non-manifold elements along the material interfaces, and (3) ensure that the material interface or shared boundary between materials is consistent. The proposed method is used to generate multi-material surface meshes of deep brain anatomical structures from a digital atlas of the basal ganglia and thalamus. Although deep brain anatomical structures can be labeled as functionally separate, they are in fact continuous tracts of soft tissue in close proximity to each other. The multi-material meshes generated by the proposed DC algorithm can accurately represent the closely-packed deep brain structures as a single mesh consisting of multiple material sub-meshes. Each sub-mesh represents a distinct functional structure of the brain. Printed and/or digital atlases are important tools for medical research and surgical intervention. While these atlases can provide guidance in identifying anatomical structures, they do not take into account the wide variations in the shape and size of anatomical structures that occur from patient to patient. Accurate, patient-specific representations are especially important for surgical interventions like deep brain stimulation, where even small inaccuracies can result in dangerous complications. The last part of this research effort extends the discrete deformable 2-simplex mesh into the multi-material domain where geometry-based internal forces and image-based external forces are used in the deformation process. This multi-material deformable framework is used to segment anatomical structures of the deep brain region from Magnetic Resonance (MR) data

Construction of Physics-based brain atlas and its application

Ph.DDOCTOR OF PHILOSOPH

Proceedings, MSVSCC 2018

Proceedings of the 12th Annual Modeling, Simulation & Visualization Student Capstone Conference held on April 19, 2018 at VMASC in Suffolk, Virginia. 155 pp

Bioengineering Analysis of Traumatic Brain Injury

Traumatic brain injury (TBI) is a serious health concern affecting over a million people in the UK. Brain shift and herniation, which are closely related to severe disability or death, are important signs of abnormally elevated intracranial pressure (ICP) or space-occupying intracranial mass after trauma. This research aims to use medical image computing and biomechanical modelling techniques to characterise the specific deformation field of brain tissues under various TBI scenarios and strengthen the biomechanical understanding across the full spectrum of TBI. Medical image computing provides the research with a solid clinical grounding. To better interpret the neuro-images, three computational tools have been developed, including a CT preprocessing pipeline, an automatic mid-sagittal plane detector and an automatic brain extractor. Using these tools, a novel concept of midplane shift (MPS) is developed to quantitatively evaluate the brain herniation condition across the mid-sagittal plane. In the meantime, a lesion heatmap is generated to quantify the asymmetric haematoma volumes across the mid-sagittal plane. The MPS heatmaps generated for 33 TBI patients with heterogeneous brain pathologies demonstrate highly similar shift patterns. Together with the lesion heatmap, a brain deformation mechanism has been presented: the brain will not deform randomly in response to trauma, instead, it will only deform in a regulated mechanism so that the deformation is directed and restricted to the soft ventricular region, thanks to the anatomic structures of the head such as the falx. The MPS heatmap, the lesion heatmap, together with the novel CT parameters derived from them, provide a rich abundance of information on intracranial brain herniation, for a more complete overview of TBI from medical images. Biomechanical modelling, being one of the most important tools in trauma biomechanics, has been used to quantitatively simulate the brain shift and herniation condition caused by various intracranial lesions and increasing ICP. Preliminary finite element models reconstructed from the Virtual Human Project have demonstrated some limitations. To resolve the observed deficiencies, an advanced high-fidelity patient-specific FE brain model is constructed and explicitly assessed to optimise its injury simulation performance with the help of the developed medical image computing tools. During simulation, the patient-specific traumatic injuries have been reconstructed by imposing both the primary lesion and the secondary injury. The primary lesion simulation is achieved mechanically by ``indenting" a rigid lesion surface simulating the shape of the haematoma to the brain model. While the secondary swelling is modelled with a thermal-expansion-based method to simulate the bulging brain. Using this approach, the observed brain herniation can be decomposed into a deformation due to pure mass effect of space-occupying primary lesion and a shift as a result of secondary swelling. The head injuries of six different TBI patients have been reconstructed and simulated using the prescribed method. The realistic case study suggested that the subdural haematoma patients, as compared to the epidural haematoma patients, were exposed to more significant secondary swelling, which agrees well with the historical clinical findings. In addition to the realistic TBI case studies, an idealised traumatic lesion simulation is performed to investigate the role of lesion morphology and the lesion locations of onsets, in brain herniations during TBI. It is suggested by the idealised TBI cases that the brain is more sensitive to lesion that is more concentrated spatially, if lesion volumes and lesion locations were exactly the same. Moreover, in terms of lesion locations, lesions that strikes on the temporal region and the anterior region are more likely to lead to greater brain deformation, if other lesion morphologies were equal and no secondary swelling considered. Ultimately, the developed tools are expected to help clinicians better understand and predict the brain behaviour after the onset of TBI and during subsequent injury evolution.WD Armstrong Trus

Medical Robotics

The first generation of surgical robots are already being installed in a number of operating rooms around the world. Robotics is being introduced to medicine because it allows for unprecedented control and precision of surgical instruments in minimally invasive procedures. So far, robots have been used to position an endoscope, perform gallbladder surgery and correct gastroesophogeal reflux and heartburn. The ultimate goal of the robotic surgery field is to design a robot that can be used to perform closed-chest, beating-heart surgery. The use of robotics in surgery will expand over the next decades without any doubt. Minimally Invasive Surgery (MIS) is a revolutionary approach in surgery. In MIS, the operation is performed with instruments and viewing equipment inserted into the body through small incisions created by the surgeon, in contrast to open surgery with large incisions. This minimizes surgical trauma and damage to healthy tissue, resulting in shorter patient recovery time. The aim of this book is to provide an overview of the state-of-art, to present new ideas, original results and practical experiences in this expanding area. Nevertheless, many chapters in the book concern advanced research on this growing area. The book provides critical analysis of clinical trials, assessment of the benefits and risks of the application of these technologies. This book is certainly a small sample of the research activity on Medical Robotics going on around the globe as you read it, but it surely covers a good deal of what has been done in the field recently, and as such it works as a valuable source for researchers interested in the involved subjects, whether they are currently “medical roboticists” or not

Brain and Human Body Modeling

This open access book describes modern applications of computational human modeling with specific emphasis in the areas of neurology and neuroelectromagnetics, depression and cancer treatments, radio-frequency studies and wireless communications. Special consideration is also given to the use of human modeling to the computational assessment of relevant regulatory and safety requirements. Readers working on applications that may expose human subjects to electromagnetic radiation will benefit from this book’s coverage of the latest developments in computational modelling and human phantom development to assess a given technology’s safety and efficacy in a timely manner. Describes construction and application of computational human models including anatomically detailed and subject specific models; Explains new practices in computational human modeling for neuroelectromagnetics, electromagnetic safety, and exposure evaluations; Includes a survey of modern applications for which computational human models are critical; Describes cellular-level interactions between the human body and electromagnetic fields

Brain and Human Body Modeling

This open access book describes modern applications of computational human modeling with specific emphasis in the areas of neurology and neuroelectromagnetics, depression and cancer treatments, radio-frequency studies and wireless communications. Special consideration is also given to the use of human modeling to the computational assessment of relevant regulatory and safety requirements. Readers working on applications that may expose human subjects to electromagnetic radiation will benefit from this book’s coverage of the latest developments in computational modelling and human phantom development to assess a given technology’s safety and efficacy in a timely manner. Describes construction and application of computational human models including anatomically detailed and subject specific models; Explains new practices in computational human modeling for neuroelectromagnetics, electromagnetic safety, and exposure evaluations; Includes a survey of modern applications for which computational human models are critical; Describes cellular-level interactions between the human body and electromagnetic fields