Dissecting abdominal aortic aneurysm in Angiotensin II-infused mice: the importance of imaging

INTRODUCTION Since the initial publication in 2000, Angiotensin II-infused mice have become one of the most popular models to study abdominal aortic aneurysm in a pre-clinical setting. We recently used phase contrast X-ray based computed tomography to demonstrate that these animals develop an apparent luminal dilatation and an intramural hematoma, both related to mural ruptures in the tunica media in the vicinity of suprarenal side branches. AIMS The aim of this narrative review was to provide an extensive overview of small animal applicable techniques that have provided relevant insight into the pathogenesis and morphology of dissecting AAA in mice, and to relate findings from these techniques to each other and to our recent PCXTM-based results. Combining insights from recent and consolidated publications we aimed to enhance our understanding of dissecting AAA morphology and anatomy. RESULTS AND CONCLUSION We analyzed in vivo and ex vivo images of aortas obtained from macroscopic anatomy, histology, high-frequency ultrasound, contrast-enhanced micro-CT, micro-MRI and PCXTM. We demonstrate how in almost all publications the aorta has been subdivided into a part in which an intact lumen lies adjacent to a remodeled wall/hematoma, and a part in which elastic lamellae are ruptured and the lumen appears to be dilated. We show how the novel paradigm fits within the existing one, and how 3D images can explain and connect previously published 2D structures. We conclude that PCXTM-based findings are in line with previous results, and all evidence points towards the fact that dissecting AAAs in Angiotensin II-infused mice are actually caused by ruptures of the tunica media in the immediate vicinity of small side branches.

Intravital and whole-organ imaging reveals capture of melanoma-derived antigen by lymph node subcapsular macrophages leading to widespread deposition on follicular dendritic cells.

Aberrant antigens expressed by tumor cells, such as in melanoma, are often associated with humoral immune responses, which may in turn influence tumor progression. Despite recent data showing the central role of adaptive immune responses on cancer spread or control, it remains poorly understood where and how tumor-derived antigen (TDA) induces a humoral immune response in tumor-bearing hosts. Based on our observation of TDA accumulation in B cell areas of lymph nodes (LNs) from melanoma patients, we developed a pre-metastatic B16.F10 melanoma model expressing a fluorescent fusion protein, tandem dimer tomato, as a surrogate TDA. Using intravital two-photon microscopy (2PM) and whole-mount 3D LN imaging of tumor-draining LNs in immunocompetent mice, we report an unexpectedly widespread accumulation of TDA on follicular dendritic cells (FDCs), which were dynamically scanned by circulating B cells. Furthermore, 2PM imaging identified macrophages located in the subcapsular sinus of tumor-draining LNs to capture subcellular TDA-containing particles arriving in afferent lymph. As a consequence, depletion of macrophages or genetic ablation of B cells and FDCs resulted in dramatically reduced TDA capture in tumor-draining LNs. In sum, we identified a major pathway for the induction of humoral responses in a melanoma model, which may be exploitable to manipulate anti-TDA antibody production during cancer immunotherapy.

Nasolabial symmetry and esthetics in cleft lip and palate: analysis of 3D facial images

OBJECTIVES To determine the relationship between nasolabial symmetry and esthetics in subjects with orofacial clefts. MATERIAL AND METHODS Eighty-four subjects (mean age 10 years, standard deviation 1.5) with various types of nonsyndromic clefts were included: 11 had unilateral cleft lip (UCL); 30 had unilateral cleft lip and alveolus (UCLA); and 43 had unilateral cleft lip, alveolus, and palate (UCLAP). A 3D stereophotogrammetric image of the face was taken for each subject. Symmetry and esthetics were evaluated on cropped 3D facial images. The degree of asymmetry of the nasolabial area was calculated based on all 3D data points using a surface registration algorithm. Esthetic ratings of various elements of nasal morphology were performed by eight lay raters on a 100 mm visual analog scale. Statistical analysis included ANOVA tests and regression models. RESULTS Nasolabial asymmetry increased with growing severity of the cleft (p = 0.029). Overall, nasolabial appearance was affected by nasolabial asymmetry; subjects with more nasolabial asymmetry were judged as having a less esthetically pleasing nasolabial area (p < 0.001). However, the relationship between nasolabial symmetry and esthetics was relatively weak in subjects with UCLAP, in whom only vermilion border esthetics was associated with asymmetry. CONCLUSIONS Nasolabial symmetry assessed with 3D facial imaging can be used as an objective measure of treatment outcome in subjects with less severe cleft deformity. In subjects with more severe cleft types, other factors may play a decisive role. CLINICAL SIGNIFICANCE Assessment of nasolabial symmetry is a useful measure of treatment success in less severe cleft types.

Non-rigid Free-Form 2D-3D Registration Using Statistical Deformation Model

This paper presents a non-rigid free-from 2D-3D registration approach using statistical deformation model (SDM). In our approach the SDM is first constructed from a set of training data using a non-rigid registration algorithm based on b-spline free-form deformation to encode a priori information about the underlying anatomy. A novel intensity-based non-rigid 2D-3D registration algorithm is then presented to iteratively fit the 3D b-spline-based SDM to the 2D X-ray images of an unseen subject, which requires a computationally expensive inversion of the instantiated deformation in each iteration. In this paper, we propose to solve this challenge with a fast B-spline pseudo-inversion algorithm that is implemented on graphics processing unit (GPU). Experiments conducted on C-arm and X-ray images of cadaveric femurs demonstrate the efficacy of the present approach.

Computer-Assisted Orthopedic Surgery: Current State and Future Perspective

Introduced about two decades ago, computer-assisted orthopedic surgery (CAOS) has emerged as a new and independent area, due to the importance of treatment of musculoskeletal diseases in orthopedics and traumatology, increasing availability of different imaging modalities, and advances in analytics and navigation tools. The aim of this paper is to present the basic elements of CAOS devices and to review state-of-the-art examples of different imaging modalities used to create the virtual representations, of different position tracking devices for navigation systems, of different surgical robots, of different methods for registration and referencing, and of CAOS modules that have been realized for different surgical procedures. Future perspectives will also be outlined.

Computer-assisted virtual autopsy using surgical navigation techniques

UNLABELLED OBJECTIVE; Virtual autopsy methods, such as postmortem CT and MRI, are increasingly being used in forensic medicine. Forensic investigators with little to no training in diagnostic radiology and medical laypeople such as state's attorneys often find it difficult to understand the anatomic orientation of axial postmortem CT images. We present a computer-assisted system that permits postmortem CT datasets to be quickly and intuitively resliced in real time at the body to narrow the gap between radiologic imaging and autopsy. CONCLUSION Our system is a potentially valuable tool for planning autopsies, showing findings to medical laypeople, and teaching CT anatomy, thus further closing the gap between radiology and forensic pathology.

Computer Assisted Diagnosis and Treatment Planning of Femoroacetabular Impingement (FAI)

Femoroacetabular impingement (FAI) is a dynamic conflict of the hip defined by a pathological, early abutment of the proximal femur onto the acetabulum or pelvis. In the past two decades, FAI has received increasing focus in both research and clinical practice as a cause of hip pain and prearthrotic deformity. Anatomical abnormalities such as an aspherical femoral head (cam-type FAI), a focal or general overgrowth of the acetabulum (pincer-type FAI), a high riding greater or lesser trochanter (extra-articular FAI), or abnormal torsion of the femur have been identified as underlying pathomorphologies. Open and arthroscopic treatment options are available to correct the deformity and to allow impingement-free range of motion. In routine practice, diagnosis and treatment planning of FAI is based on clinical examination and conventional imaging modalities such as standard radiography, magnetic resonance arthrography (MRA), and computed tomography (CT). Modern software tools allow three-dimensional analysis of the hip joint by extracting pelvic landmarks from two-dimensional antero-posterior pelvic radiographs. An object-oriented cross-platform program (Hip2Norm) has been developed and validated to standardize pelvic rotation and tilt on conventional AP pelvis radiographs. It has been shown that Hip2Norm is an accurate, consistent, reliable and reproducible tool for the correction of selected hip parameters on conventional radiographs. In contrast to conventional imaging modalities, which provide only static visualization, novel computer assisted tools have been developed to allow the dynamic analysis of FAI pathomechanics. In this context, a validated, CT-based software package (HipMotion) has been introduced. HipMotion is based on polygonal three-dimensional models of the patient’s pelvis and femur. The software includes simulation methods for range of motion, collision detection and accurate mapping of impingement areas. A preoperative treatment plan can be created by performing a virtual resection of any mapped impingement zones both on the femoral head-neck junction, as well as the acetabular rim using the same three-dimensional models. The following book chapter provides a summarized description of current computer-assisted tools for the diagnosis and treatment planning of FAI highlighting the possibility for both static and dynamic evaluation, reliability and reproducibility, and its applicability to routine clinical use.

RETICULAR PSEUDODRUSEN ON INFRARED IMAGING ARE TOPOGRAPHICALLY DISTINCT FROM SUBRETINAL DRUSENOID DEPOSITS ON EN FACE OPTICAL COHERENCE TOMOGRAPHY.

PURPOSE: To evaluate the quantitative and topographic relationship between reticular pseudodrusen (RPD) on infrared reflectance (IR) and subretinal drusenoid deposits (SDD) on en face volumetric spectral domain optical coherence tomography. METHODS: Reticular pseudodrusen were marked on IR images by a masked observer. Subretinal drusenoid deposits were visualized on en face sections of spectral domain optical coherence tomography below the external limiting membrane and identified by a semiautomated technique. Control RPD lesions were generated in a random distribution for each IR image. Binary maps of control and experimental RPD and SDD were merged and analyzed in terms of topographic localization and quantitative drusen load comparison. RESULTS: A total of 54 eyes of 41 patients diagnosed with RPD were included in this study. The average number of RPD lesions on IR images was 320 ± 44.62 compared with 127 ± 26.02 SDD lesions on en face (P < 0.001). The majority of RPD lesions did not overlap with SDD lesions and were located >30 μm away (92%). The percentage of total SDD lesions overlapping RPD was 2.91 ± 0.87% compared with 1.73 ± 0.68% overlapping control RPD lesions (P < 0.05). The percentage of total SDD lesions between 1 and 3 pixels of the nearest RPD lesion was 5.08 ± 1.40% compared with 3.33 ± 1.07% between 1 and 3 pixels of the nearest control RPD lesion (P < 0.05). CONCLUSION: This study identified significantly more RPD lesions on IR compared with SDD lesions on en face spectral domain optical coherence tomography and found that a large majority of SDD (>90% of lesions) were >30 μm away from the nearest RPD. Together, our findings indicate that RPD and SDD are two entities that are only occasionally topographically associated, suggesting that at some stage in their development, they may be pathologically related.

Comparison of Routine Brain Imaging at 3 T and 7 T.

OBJECTIVE The aim of this study was to compare quantitative and semiquantitative parameters (signal-to-noise ratio [SNR], contrast-to-noise ratio [CNR], image quality, diagnostic confidence) from a standard brain magnetic resonance imaging examination encompassing common neurological disorders such as demyelinating disease, gliomas, cerebrovascular disease, and epilepsy, with comparable sequence protocols and acquisition times at 3 T and at 7 T. MATERIALS AND METHODS Ten healthy volunteers and 4 subgroups of 40 patients in total underwent comparable magnetic resonance protocols with standard diffusion-weighted imaging, 2D and 3D turbo spin echo, 2D and 3D gradient echo and susceptibility-weighted imaging of the brain (10 sequences) at 3 T and 7 T. The subgroups comprised patients with either lesional (n = 5) or nonlesional (n = 4) epilepsy, intracerebral tumors (n = 11), demyelinating disease (n = 11) (relapsing-remitting multiple sclerosis [MS, n = 9], secondary progressive MS [n = 1], demyelinating disease not further specified [n = 1]), or chronic cerebrovascular disorders [n = 9]). For quantitative analysis, SNR and CNR were determined. For a semiquantitative assessment of the diagnostic confidence, a 10-point scale diagnostic confidence score (DCS) was applied. Two experienced radiologists with additional qualification in neuroradiology independently assessed, blinded to the field strength, 3 pathology-specific imaging criteria in each of the 4 disease groups and rated their diagnostic confidence. The overall image quality was semiquantitatively assessed using a 4-point scale taking into account whether diagnostic decision making was hampered by artifacts or not. RESULTS Without correction for spatial resolution, SNR was higher at 3 T except in the T2 SPACE 3D, DWI single shot, and DIR SPACE 3D sequences. The SNR corrected by the ratio of 3 T/7 T voxel sizes was higher at 7 T than at 3 T in 10 of 11 sequences (all except for T1 MP2RAGE 3D).In CNR, there was a wide variation between sequences and patient cohorts, but average CNR values were broadly similar at 3 T and 7 T.DCS values for all 4 pathologic entities were higher at 7 T than at 3 T. The DCS was significantly higher at 7 T for diagnosis and exclusion of cortical lesions in vascular disease. A tendency to higher DCS at 7 T for cortical lesions in MS was observed, and for the depiction of a central vein and iron deposits within MS lesions. Despite motion artifacts, DCS values were higher at 7 T for the diagnosis and exclusion of hippocampal sclerosis in mesial temporal lobe epilepsy (improved detection of the hippocampal subunits). Interrater agreement was 69.7% at 3 T and 93.3% at 7 T. There was no significant difference in the overall image quality score between 3 T and 7 T taking into account whether diagnostic decision making was hampered by artifacts or not. CONCLUSIONS Ultra-high-field magnetic resonance imaging at 7 T compared with 3 T yielded an improved diagnostic confidence in the most frequently encountered neurologic disorders. Higher spatial resolution and contrast were identified as the main contributory factors.

Low-energy energetic neutral atom imaging of Io plasma and neutral tori

Io's plasma and neutral tori play significant roles in the Jovian magnetosphere. We present feasibility studies of measuring low-energy energetic neutral atoms (LENAs) generated from the Io tori. We calculate the LENA flux between 10 eV and 3 keV. The energy range includes the corotational plasma flow energy. The expected differential flux at Ganymede distance is typically 10(3)-10(5) cm(-2) s(-1) sr(-1) eV(-1) near the energy of the corotation. It is above the detection level of the planned LENA sensor that is to be flown to the Jupiter system with integration times of 0.01-1 s. The flux has strong asymmetry with respective to the Io phase. The observations will exhibit periodicities, which can be attributed to the Jovian magnetosphere rotation and the rotation of Io around Jupiter. The energy spectra will exhibit dispersion signatures, because of the non-negligible flight time of the LENAs from Io to the satellite. In 2030, the Jupiter exploration mission JUICE will conduct a LENA measurement with a LENA instrument, the Jovian Neutrals Analyzer (JNA). From the LENA observations collected by JNA, we will be able to derive characteristic quantities, such as the density, velocity, velocity distribution function, and composition of plasma-torus particles. We also discuss the possible physics to be explored by JNA in addition to the constraints for operating the sensor and analyzing the obtained dataset. (C) 2015 Elsevier Ltd. All rights reserved.

Computer vision profiling of neurite outgrowth dynamics reveals spatiotemporal modularity of Rho GTPase signaling

Rho guanosine triphosphatases (GTPases) control the cytoskeletal dynamics that power neurite outgrowth. This process consists of dynamic neurite initiation, elongation, retraction, and branching cycles that are likely to be regulated by specific spatiotemporal signaling networks, which cannot be resolved with static, steady-state assays. We present NeuriteTracker, a computer-vision approach to automatically segment and track neuronal morphodynamics in time-lapse datasets. Feature extraction then quantifies dynamic neurite outgrowth phenotypes. We identify a set of stereotypic neurite outgrowth morphodynamic behaviors in a cultured neuronal cell system. Systematic RNA interference perturbation of a Rho GTPase interactome consisting of 219 proteins reveals a limited set of morphodynamic phenotypes. As proof of concept, we show that loss of function of two distinct RhoA-specific GTPase-activating proteins (GAPs) leads to opposite neurite outgrowth phenotypes. Imaging of RhoA activation dynamics indicates that both GAPs regulate different spatiotemporal Rho GTPase pools, with distinct functions. Our results provide a starting point to dissect spatiotemporal Rho GTPase signaling networks that regulate neurite outgrowth.

Development of a 3D Game Engine

This paper presents the development history and specification of a 3D game engine titled "Spark Engine". The term "engine" is used to describe a complex graphics software suite that streamlines application development and provides efficient rendering functionality. A game engine specifically provides tools to simplify game development. Spark Engine is fully shader driven and is built on top of Microsoft's XNA Framework. It is a reusable and flexible platform that can be used to build any type of graphics application ranging from gaming to simulation. The engine was released as open source software under the New BSD License with an interest in furthering its development.

Computer Simulation of Crowd Dynamics and Destructive Crowd Behavior

The social processes that lead to destructive behavior in celebratory crowds can be studied through an agent-based computer simulation. Riots are an increasingly common outcome of sports celebrations, and pose the potential for harm to participants, bystanders, property, and the reputation of the groups with whom participants are associated. Rioting cannot necessarily be attributed to the negative emotions of individuals, such as anger, rage, frustration and despair. For instance, the celebratory behavior (e.g., chanting, cheering, singing) during UConn’s “Spring Weekend” and after the 2004 NCAA Championships resulted in several small fires and overturned cars. Further, not every individual in the area of a riot engages in violence, and those who do, do not do so continuously. Instead, small groups carry out the majority of violent acts in relatively short-lived episodes. Agent-based computer simulations are an ideal method for modeling complex group-level social phenomena, such as celebratory gatherings and riots, which emerge from the interaction of relatively “simple” individuals. By making simple assumptions about individuals’ decision-making and behaviors and allowing actors to affect one another, behavioral patterns emerge that cannot be predicted by the characteristics of individuals. The computer simulation developed here models celebratory riot behavior by repeatedly evaluating a single algorithm for each individual, the inputs of which are affected by the characteristics of nearby actors. Specifically, the simulation assumes that (a) actors possess 1 of 5 distinct social identities (group memberships), (b) actors will congregate with actors who possess the same identity, (c) the degree of social cohesion generated in the social context determines the stability of relationships within groups, and (d) actors’ level of aggression is affected by the aggression of other group members. Not only does this simulation provide a systematic investigation of the effects of the initial distribution of aggression, social identification, and cohesiveness on riot outcomes, but also an analytic tool others may use to investigate, visualize and predict how various individual characteristics affect emergent crowd behavior.

NOVEL PHANTOMS AND POST-PROCESSING FOR DIFFUSION SPECTRUM IMAGING

High Angular Resolution Diffusion Imaging (HARDI) techniques, including Diffusion Spectrum Imaging (DSI), have been proposed to resolve crossing and other complex fiber architecture in the human brain white matter. In these methods, directional information of diffusion is inferred from the peaks in the orientation distribution function (ODF). Extensive studies using histology on macaque brain, cat cerebellum, rat hippocampus and optic tracts, and bovine tongue are qualitatively in agreement with the DSI-derived ODFs and tractography. However, there are only two studies in the literature which validated the DSI results using physical phantoms and both these studies were not performed on a clinical MRI scanner. Also, the limited studies which optimized DSI in a clinical setting, did not involve a comparison against physical phantoms. Finally, there is lack of consensus on the necessary pre- and post-processing steps in DSI; and ground truth diffusion fiber phantoms are not yet standardized. Therefore, the aims of this dissertation were to design and construct novel diffusion phantoms, employ post-processing techniques in order to systematically validate and optimize (DSI)-derived fiber ODFs in the crossing regions on a clinical 3T MR scanner, and develop user-friendly software for DSI data reconstruction and analysis. Phantoms with a fixed crossing fiber configuration of two crossing fibers at 90° and 45° respectively along with a phantom with three crossing fibers at 60°, using novel hollow plastic capillaries and novel placeholders, were constructed. T2-weighted MRI results on these phantoms demonstrated high SNR, homogeneous signal, and absence of air bubbles. Also, a technique to deconvolve the response function of an individual peak from the overall ODF was implemented, in addition to other DSI post-processing steps. This technique greatly improved the angular resolution of the otherwise unresolvable peaks in a crossing fiber ODF. The effects of DSI acquisition parameters and SNR on the resultant angular accuracy of DSI on the clinical scanner were studied and quantified using the developed phantoms. With a high angular direction sampling and reasonable levels of SNR, quantification of a crossing region in the 90°, 45° and 60° phantoms resulted in a successful detection of angular information with mean ± SD of 86.93°±2.65°, 44.61°±1.6° and 60.03°±2.21° respectively, while simultaneously enhancing the ODFs in regions containing single fibers. For the applicability of these validated methodologies in DSI, improvement in ODFs and fiber tracking from known crossing fiber regions in normal human subjects were demonstrated; and an in-house software package in MATLAB which streamlines the data reconstruction and post-processing for DSI, with easy to use graphical user interface was developed. In conclusion, the phantoms developed in this dissertation offer a means of providing ground truth for validation of reconstruction and tractography algorithms of various diffusion models (including DSI). Also, the deconvolution methodology (when applied as an additional DSI post-processing step) significantly improved the angular accuracy of the ODFs obtained from DSI, and should be applicable to ODFs obtained from the other high angular resolution diffusion imaging techniques.