Combined brain language connectivity and intraoperative neurophysiologic techniques in awake craniotomy for eloquent-area brain tumor resection

Speech processing can be disturbed by primary brain tumors (PBT). Improvement of presurgical planning techniques decrease neurological morbidity associated to tumor resection during awake craniotomy. The aims of this work were: 1. To perform Diffusion Kurtosis Imaging based tractography (DKI-tract) in the detection of brain tracts involved in language; 2. To investigate which factors contribute to functional magnetic resonance imaging (fMRI) maps in predicting eloquent language regional reorganization; 3. To determine the technical aspects of accelerometric (ACC) recording of speech during surgery. DKI-tracts were streamlined using a 1.5T magnetic resonance scanner. Number of tracts and fiber pathways were compared between DKI and standard Diffusion Tensor Imaging (DTI) in healthy subjects (HS) and PBT patients. fMRI data were acquired using task-specific and resting-state paradigms during language and motor tasks. After testing intraoperative fMRI’s influence on direct cortical stimulation (DCS) number of stimuli, graph-theory measures were extracted and analyzed. Regarding speech recording, ACC signals were recorded after evaluating neck positions and filter bandwidths. To test this method, language disturbances were recorded in patients with dysphonia and after applying DCS in the inferior frontal gyrus. In contrast, HS reaction time was recorded during speech execution. DKI-tract showed increased number of arcuate fascicle tracts in PBT patients. Lower spurious tracts were identified with DKI-tract. Intraoperative fMRI and DCS showed similar stimuli in comparison with DCS alone. Increased local centrality accompanied language ipsilateral and contralateral reorganization. ACC recordings showed minor artifact contamination when placed at the suprasternal notch using a 20-200 Hz filter bandwidth. Patients with dysphonia showed decreased amplitude and frequency in comparison with HS. ACC detected an additional 11% disturbances after DCS, and a shortening of latency within the presence of a loud stimuli during speech execution. This work improved current knowledge on presurgical planning techniques based on brain structural and functional neuroimaging connectivity, and speech recordingA função linguística do ser humano pode ser afetada pela presença de tumores cerebrais (TC) A melhoria de técnicas de planeamento pré-cirurgico diminui a morbilidade neurológica iatrogénica associada ao seu tratamento cirúrgico. O objetivo deste trabalho é: 1. Testar a fiabilidade da tractografia estimada por difusor de kurtose (tract-DKI), dos feixes cerebrais envolvidos na linguagem 2. Identificar os fatores que contribuem para o mapeamento linguagem por ressonância magnética funcional (RMf) na predição da neuroplasticidade. 3. Identificar aspetos técnicos do registo da linguagem por accelerometria (ACC). A DKI-tract foi estimada após realização de RM cerebral com 1.5T. O número e percurso das fibras foi avaliado. A RMf foi adquirida durante realização de tarefas linguísticas, motoras, e em repouso. Foi testada influência dos mapas de ativação calculados por RMf, no número de estímulos realizados durante a estimulação direta cortical (EDC) intraoperatória. Medidas de conectividade foram extraídas de regiões cerebrais. A posição e filtragem de sinal ACC foram estudadas após vocalização de palavras. O sinal ACC obtido em voluntários foi comparado com doentes disfónicos, após estimulação do giro inferior frontal, e após a adição de um estímulo sonoro perturbador durante vocalização. A tract-DKI estimou um elevado número de fascículos do feixe arcuato com menos falsos negativos. Os mapas linguísticos de RMf intraoperatória, não influenciou a EDC. Medidas de centralidade aumentaram após neuroplasticidade ipsilateral e contralateral. A posição supraesternal e a filtragem de sinal ACC entre 20-200Hz demonstrou menor ruido de contaminação. Este método identificou diminuição de frequência e amplitude em doentes com disfonia, 11% de erros linguísticos adicionais após estimulação e diminuição do tempo de latência quando presente o sinal sonoro perturbador. Este trabalho promoveu a utilização de novas técnicas no planeamento pré-cirúrgico do doente com tumor cerebral e alterações da linguagem através do estudo de conectividade estrutural, funcional e registo da linguagem

Models and Analysis of Vocal Emissions for Biomedical Applications

The MAVEBA Workshop proceedings, held on a biannual basis, collect the scientific papers presented both as oral and poster contributions, during the conference. The main subjects are: development of theoretical and mechanical models as an aid to the study of main phonatory dysfunctions, as well as the biomedical engineering methods for the analysis of voice signals and images, as a support to clinical diagnosis and classification of vocal pathologies

Models and Analysis of Vocal Emissions for Biomedical Applications

The Models and Analysis of Vocal Emissions with Biomedical Applications (MAVEBA) workshop came into being in 1999 from the particularly felt need of sharing know-how, objectives and results between areas that until then seemed quite distinct such as bioengineering, medicine and singing. MAVEBA deals with all aspects concerning the study of the human voice with applications ranging from the neonate to the adult and elderly. Over the years the initial issues have grown and spread also in other aspects of research such as occupational voice disorders, neurology, rehabilitation, image and video analysis. MAVEBA takes place every two years always in Firenze, Italy

Novel MRI Technologies for Structural and Functional Imaging of Tissues with Ultra-short T₂ Values

Conventional MRI has several limitations such as long scan durations, motion artifacts, very loud acoustic noise, signal loss due to short relaxation times, and RF induced heating of electrically conducting objects. The goals of this work are to evaluate and improve the state-of-the-art methods for MRI of tissue with short T₂, to prove the feasibility of in vivo Concurrent Excitation and Acquisition, and to introduce simultaneous electroglottography measurement during functional lung MRI

Laryngeal preneoplastic lesions and cancer: challenging diagnosis. Qualitative literature review and meta-analysis

Background: The treatment of laryngeal cancer and its precursor lesions has a great impact on important laryngeal basic functions, thus, early detection and preoperative assessment are important for a curative and function-preserving therapy. Furthermore, delayed diagnosis, leads to loco-regional failure and a high incidence of second primary tumor, reasons for poor outcome. In this setting, there are two basic clinical problems in the management of premalignant and malignant laryngeal lesions. First, small and thin lesions are difficult to evaluate by the histopathologic examination and initial biopsies are often not sufficient for a conclusive diagnosis. Second, margins of the specimens from surgical excisions are difficult to evaluate due to tissue damage from the device, leaving us in doubt whether the excision is radical or not. From these observations, it is obvious that an instrument offering the possibility to detect pre-cancerous-early cancerous lesions, and satellite foci or second primaries would be the key to improving the survival rate in head and neck cancer. But, despite the high number of more advanced diagnostic techniques and methods, unfortunately, it is not uncommon for different clinicians to use different nomenclature or to identify different stage for the same laryngeal lesion. Object. Different modalities of diagnostic techniques of laryngeal lesions exist. Rather than difference between benign and obvious malignant diseases, more difficult is to detect the presence of precancerous epithelial alterations. Not all tests achieve the same diagnostic accuracy and that all tests must be considered against a gold standard, hence this meta-analysis of literature aimed to synthesise the validity of each single diagnostic technique in identifying and staging laryngeal diseases. Methods: A systematic review of literature was led searching for articles mentioning the following terms including their various combinations to maximize the yield: larynx, laryngeal cancer, white light (WL) endoscopy, contact endoscopy (CE), stroboscopy, autofluorescence (AF), ultrasound (US), narrow band imaging (NBI), computers assail tomography (CAT), magnetic resonance imaging (MRI), positron emission tomography (PET). A quantitative analysis was carried on for paper published after 2005 onward, reporting a minumun series of 10 patients each study, declaring sensitivity and specificity of each diagnostic system. Results: The search identified 7215 publications, of which 3616 published after 2005, with a final results of a total of 214 articles stratified and included by our selection criteria. 58 out of 214 articles were selected for quantitative synthesis. 35 out of 58 studies had a quality score of ≥ 6 (good), 15 presented a score between 4 and 5 (fair), the remaining 8 had a score between 2 and 3 (poor). While objections can be raised about the pooling of different diagnostic procedures under the same group and the high level of heterogeneity in the meta-analyses, the inclusion of over 2500 patients makes the results fairly robust. Conclusions: A comprehensive overview of the most recent advances in laryngeal imaging technology combined with all of the information needed to interpret findings and successfully manage patients with voice disorders can be found herein. With these data, clinicians can risk-stratify patients and select proper examination modalities in order to provide appropriate care. Moreover, study limitations, together with possible clinical and research implications have been counted, as well

Recent Advances in Signal Processing

The signal processing task is a very critical issue in the majority of new technological inventions and challenges in a variety of applications in both science and engineering fields. Classical signal processing techniques have largely worked with mathematical models that are linear, local, stationary, and Gaussian. They have always favored closed-form tractability over real-world accuracy. These constraints were imposed by the lack of powerful computing tools. During the last few decades, signal processing theories, developments, and applications have matured rapidly and now include tools from many areas of mathematics, computer science, physics, and engineering. This book is targeted primarily toward both students and researchers who want to be exposed to a wide variety of signal processing techniques and algorithms. It includes 27 chapters that can be categorized into five different areas depending on the application at hand. These five categories are ordered to address image processing, speech processing, communication systems, time-series analysis, and educational packages respectively. The book has the advantage of providing a collection of applications that are completely independent and self-contained; thus, the interested reader can choose any chapter and skip to another without losing continuity

Adaptive threshold optimisation for colour-based lip segmentation in automatic lip-reading systems

A thesis submitted to the Faculty of Engineering and the Built Environment, University of the Witwatersrand, Johannesburg, in ful lment of the requirements for the degree of Doctor of Philosophy. Johannesburg, September 2016Having survived the ordeal of a laryngectomy, the patient must come to terms with the resulting loss of speech. With recent advances in portable computing power, automatic lip-reading (ALR) may become a viable approach to voice restoration. This thesis addresses the image processing aspect of ALR, and focuses three contributions to colour-based lip segmentation. The rst contribution concerns the colour transform to enhance the contrast between the lips and skin. This thesis presents the most comprehensive study to date by measuring the overlap between lip and skin histograms for 33 di erent colour transforms. The hue component of HSV obtains the lowest overlap of 6:15%, and results show that selecting the correct transform can increase the segmentation accuracy by up to three times. The second contribution is the development of a new lip segmentation algorithm that utilises the best colour transforms from the comparative study. The algorithm is tested on 895 images and achieves percentage overlap (OL) of 92:23% and segmentation error (SE) of 7:39 %. The third contribution focuses on the impact of the histogram threshold on the segmentation accuracy, and introduces a novel technique called Adaptive Threshold Optimisation (ATO) to select a better threshold value. The rst stage of ATO incorporates -SVR to train the lip shape model. ATO then uses feedback of shape information to validate and optimise the threshold. After applying ATO, the SE decreases from 7:65% to 6:50%, corresponding to an absolute improvement of 1:15 pp or relative improvement of 15:1%. While this thesis concerns lip segmentation in particular, ATO is a threshold selection technique that can be used in various segmentation applications.MT201

Models and Analysis of Vocal Emissions for Biomedical Applications

The International Workshop on Models and Analysis of Vocal Emissions for Biomedical Applications (MAVEBA) came into being in 1999 from the particularly felt need of sharing know-how, objectives and results between areas that until then seemed quite distinct such as bioengineering, medicine and singing. MAVEBA deals with all aspects concerning the study of the human voice with applications ranging from the neonate to the adult and elderly. Over the years the initial issues have grown and spread also in other aspects of research such as occupational voice disorders, neurology, rehabilitation, image and video analysis. MAVEBA takes place every two years always in Firenze, Italy. This edition celebrates twenty years of uninterrupted and succesfully research in the field of voice analysis

High-resolution full-vocal-tract dynamic speech magnetic resonance imaging

Dynamic magnetic resonance imaging (MRI) holds great promise for speech-related studies because of its potential to investigate velopharyngeal motion and physiological properties jointly in real time. However, many applications of dynamic speech MRI are limited by the technical trade-offs in imaging speed, spatial coverage, spatial resolution and clinical interpretation. In particular, high-resolution dynamic speech MRI with full-vocal-tract coverage and phonetically meaningful interpretation remains a challenging goal for many speech researchers. This dissertation develops novel model-based dynamic speech MRI approaches to enable high-resolution, full-vocal-tract 3D dynamic speech MRI with quantitative characterization of the articulatory motion. Our approaches include technical developments in imaging models, data acquisition strategies and image reconstruction methods: (a) high-spatiotemporal-resolution speech MRI from sparsely sampled data is achieved by employing a low-rank imaging model that leverages the spatiotemporal correlations in dynamic speech motion; (b) a self-navigated sampling strategy is developed and employed to acquire spatiotemporal data at high imaging speed, which collects high-nominal-frame-rate cone navigators and randomized Cartesian imaging data within a single TR; (c) quantitative interpretation of speech motion is enabled by introducing a deformation-based sparsity constraint that not only improves image reconstruction quality but also analyzes articulatory motion by a high-resolution deformation field; and (d) accurate assessment of subject-specific motion as opposed to generic motion pattern is realized by using a low-rank plus sparse imaging model jointly with a technique to construct high-quality spatiotemporal atlas. Regional sparse modeling is further introduced to assist effective motion analysis in the regions of interest. Our approaches are evaluated through both simulations on numerical phantoms and in vivo validation experiments across multiple subject groups. Both simulation and experimental results allow visualization of articulatory dynamics with a frame rate of 166 frames per second, a spatial resolution of 2.2 mm x 2.2 mm x 5.0 mm, and a spatial coverage of 280 mm x 280 mm x 40 mm covering the entire upper vocal tract across 8 mid-sagittal slices. Deformation fields yielded from our approaches share an identical spatiotemporal resolution that characterizes accurate soft-tissue motion. With a high-quality atlas, the low-rank and the sparse components are reconstructed to reveal both subject-specific motion and generic speech motion across a specific subject group. The effectiveness of our approaches is demonstrated through practical phonetics investigations that include (a) integrative imaging and acoustics analysis of velopharyngeal closure; (b) understanding the formation and variation in a variety of languages, American English, North Metropolitan French, Brazilian Portuguese and Levantine Arabic; and (c) analyzing motion variability of a particular subject with respect to a specific subject group. The capabilities of our method have the potential for precise assessment of the oropharyngeal dynamics and comprehensive evaluation of speech motion