Multilayered non-invasive temperature estimation from backscattered ultrasound

Roughly one in four breast cancer survivors report some degree of arm oedema. Lymphoedema is a build-up of excess lymph fluids in the tissues. Persistent lymphoedema leads to pain, diminished limb function, increased risk of infection, soft tissue fibrosis, and severe cases can be grossly disfiguring. From a mechanics perspective, the lymphoedemous tissue may be thought of as a two phase composite, consisting of both fluid and solid phases. Here we discuss the use of composites mixture theory to model the mechanics of lymphoedemous tissues. By treating the tissue as a fluid-solid composite, rules-of-mixtures may be used to estimate the effective moduli in terms of the properties of the individual components and their respective volume fractions in these two states.

Open source data sensing software for ultrasonic non-invasive temperature estimation

In this paper, an open source solution for measurement of temperature and ultrasonic signals (RF-lines) is proposed. This software is an alternative to the expensive commercial data acquisition software, enabling the user to tune applications to particular acquisition architectures. The collected ultrasonic and temperature signals were used for non-invasive temperature estimation using neural networks. The existence of precise temperature estimators is an essential point aiming at the secure and effective applica tion of thermal therapies in humans. If such estimators exist then effective controllers could be developed for the therapeutic instrumentation. In previous works the time-shift between RF-lines echoes were extracted, and used for creation of neural networks estimators. The obtained estimators successfully represent the temperature in the time-space domain, achieving a maximum absolute error inferior to the threshold value defined for hyperthermia/diathermia applications.

A soft-computing approach for non-invasive temperature estimation

The domain of thermal therapies applications can be improved with the development of accurate non-invasive timespatial temperature models. These models should represent the non-linear tissue thermal behaviour and be capable of tracking temperature at both time-instant and spatial position. If such estimators exist then efficient controllers for the therapeutic instrumentation could be developed, and the desired safety and effectiveness reached.

Using non-invasive techniques to examine black bear (Ursus americanus) abundance in the North Cascades Ecosystem, Washington State

Thesis (Master's)--University of Washington, 2013

Non-Invasive Human Brain Stimulation in Cognitive Neuroscience: A Primer

The use of non-invasive brain stimulation is widespread in studies of human cognitive neuroscience. This has led to some genuine advances in understanding perception and cognition, and has raised some hopes of applying the knowledge in clinical contexts. There are now several forms of stimulation, the ability to combine these with other methods, and ethical questions that are special to brain stimulation. In this Primer, we aim to give the users of these methods a starting point and perspective from which to view the key questions and usefulness of the different forms of non-invasive brain stimulation. We have done so by taking a critical view of recent highlights in the literature, selected case studies to illustrate the elements necessary and sufficient for good experiments, and pointed to questions and findings that can only be addressed using interference methods

Non-invasive measurement of trigeminal nerve somatosensory evoked potentials

Whiplash injuries are common yet enigmatic to substantiate clinically. Trigeminal somatosensory evoked potentials (TSEPs) were posited as an indicator of trigeminal nerve conduction damage resulting from whiplash. Alternating polarity square-wave current stimuli were applied transcutaneously in the facial region. 379 recorded pilot trials from 27 participants (8 male and 19 female) were utilized to develop a non-invasive recording capability for TSEPs. Stimulus intensity and artifact, cortical recording sites, stimulation electrode design and placement were explored. Statistically significant differences in amplitude of TSEP waveform components at 13, 19 and 27 ms between uninjured and whiplashed participants were noted. Increased stimulus intensity in whiplashed participants was observed to increase TSEP amplitude. The present methodology and hardware are discussed and directions for future advancement of the current process are outlined.

An exploratory study for the discovery of non-invasive hepatocellular carcinoma biomarkers among high-risk hepatitis C virus infected patients

Hepatocellular Carcinoma (HCC) is a major healthcare problem, representing the third most common cause of cancer-related mortality worldwide. Chronic infections with Hepatitis B virus (HBV) and/or Hepatitis C virus (HCV) are the major risk factors for the development of HCC. The incidence of HBV -associated HCC is in decline as a result of an effective HBV vaccine; however, since an equally effective HCV vaccine has not yet been developed, there are 130 million HCV infected patients worldwide who are at a high-risk for developing HCC. Because reliable parameters and/or tools for the early detection of HCC among high-risk individuals are severely lacking, HCC patients are always diagnosed at a late stage where surgical solutions or effective treatment are not possible. Using urine as a non-invasive sample source, two different approaches (proteomic-based and genomic-based approaches) were pursued with the common goal of discovering potential biomarker candidates for the early detection of HCC among high-risk chronic HCV infected patients. Urine was collected from 106 HCV infected Egyptian patients, 32 of whom had already developed HCC and 74 patients who were diagnosed as HCC-free at the time of initial sample collection. In addition to these patients, urine samples were also collected from 12 healthy control individuals. Total urinary proteins, Trans-renal nucleic acid (Tr-NA) and microRNA (miRNA) were isolated from urine using novel methodologies and silicon carbide-loaded spin columns. In the first, "proteomic-based", approach, liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) was used to identify potential candidates from pooled urine samples. This was followed by validating relative expression levels of proteins present in urine among all the patients using quantitative real time-PCR (qRT-PCR). This approach revealed that significant over-expression of three proteins: DJ-1, Chromatin Assembly Factor-1 (CAF-1) and 11 Moemen Abdalla HCC Biomarkers Heat Shock Protein 60 (HSP60), were characteristic events among HCC-post HCV infected patients. As a single-based HCC biomarker, CAF-1 over-expression identified HCC among HCV infected patients with a specificity of 90%, sensitivity of 66% and with an overall diagnostic accuracy of 78%. Moreover, the CAF-lIHSP60 tandem identified HCC among HCV infected patients with a specificity of 92%, sensitivity of 61 % and with an overall diagnostic accuracy of 77%. In the second genomic-based approach, two different approaches were processed. The first approach was the miRNA-based approach. The expression levels of miRNAs isolated from urine were studied using the Illumina MicroRNA Expression Profiling Assay. This was followed by qRT-PCR-based validation of deregulated expression of identified miRNA candidates among all the patients. This approach shed the light on the deregulated expression of a number of miRNAs, which may have a role in either the development of HCC among HCV infected patients (i.e. miR-640, miR-765, miR-200a, miR-521 and miR-520) or may allow for a better understanding of the viral-host interaction (miR-152, miR-486, miR-219, miR452, miR-425, miR-154 and miR-31). Moreover, the deregulated expression of both miR-618 and miR-650 appeared to be a common event among HCC-post HCV infected patients. The results of the search for putative targets of these two miRNA suggested that miR-618 may be a potent oncogene, as it targets the tumor-suppressor gene Low density lipoprotein-related protein 12 (LPR12), while miR-650 may be a potent tumor-suppressor gene, as it is supposed to downregulate the TNF receptor-associated factor-4 (TRAF4) oncogene. The specificity of miR-618 and miR-650 deregulated expression patterns for the early detection of HCC among HCV infected patients was 68% and 58%, respectively, whereas the sensitivity was 64% and 72%, respectively. When the deregulated expression of both miRNAs was combined as a tandem biomarker, the specificity and the sensitivity were 75% and 58% respectively. 111 Moemen Abdalla HCC Biomarkers In the second, "Trans-renal nucleic acid-based", approach, the urinary apoptotic nucleic acid (uaNA) levels of 70ng/mL or more were found to be a good predictor of HCC among chronic HCV infected patients. The specificity and the sensitivity of this diagnostic approach were 76% and 86%, respectively, with an overall diagnostic value of 81 %. The uaNA levels positively correlated to HCC disease progression as monitored by epigenetic changes of a panel of eight tumor-suppressor genes (TSGs) using methylation-sensitive PCR. Moreover, the pairing of high uaNA levels (:::: 70 ng/mL) and CAF-1 over-expreSSIOn produced a highly specific (l 00%) multiple-based HCC biomarker with an acceptable sensitivity of 64%, and with a diagnostic accuracy of 82%. In comparison to the previous pairing, the uaNA levels (:::: 70 ng/mL) in tandem with HSP60 over-expression was less specific (89%) but highly sensitive (72%), resulting in a diagnostic accuracy of 64%. The specificities of miR-650 deregulated expression in combination with either high uaNA content or HSP 60 over-expression were 82% and 79%, respectively, whereas, the sensitivities of these combinations were 64% and 58%, respectively. The potential biomarkers identified in this study compare favorably with the diagnostic accuracy of the a-fetoprotein levels test, which has a specificity of 75%, sensitivity of 68% and an overall diagnostic accuracy of 70%. Here we present an intriguing study which shows the significance of using urine as a noninvasive sample source for the identification of promising HCC biomarkers. We have also introduced new techniques for the isolation of different urinary macromolecules, especially miRNA, from urine. Furthermore, we strongly recommend the potential biomarkers indentified in this study as focal points of any future research on HCC diagnosis. A larger testing pool will determine if their use is practical for mass population screening. This explorative study identified potential targets that merit further investigation for the development of diagnostically accurate biomarkers isolated from 1-2 mL urine samples that were acquired in a non-invasive manner.

Infrared thermography: A non-invasive window into thermal physiology

Infrared thermography is a non-invasive technique that measures mid to long-wave infrared radiation emanating from all objects and converts this to temperature. As an imaging technique, the value of modern infrared thermography is its ability to produce a digitized image or high speed video rendering a thermal map of the scene in false colour. Since temperature is an important environmental parameter influencing animal physiology and metabolic heat production an energetically expensive process, measuring temperature and energy exchange in animals is critical to understanding physiology, especially under field conditions. As a non-contact approach, infrared thermography provides a non-invasive complement to physiological data gathering. One caveat, however, is that only surface temperatures are measured, which guides much research to those thermal events occurring at the skin and insulating regions of the body. As an imaging technique, infrared thermal imaging is also subject to certain uncertainties that require physical modeling, which is typically done via built-in software approaches. Infrared thermal imaging has enabled different insights into the comparative physiology of phenomena ranging from thermogenesis, peripheral blood flow adjustments, evaporative cooling, and to respiratory physiology. In this review, I provide background and guidelines for the use of thermal imaging, primarily aimed at field physiologists and biologists interested in thermal biology. I also discuss some of the better known approaches and discoveries revealed from using thermal imaging with the objective of encouraging more quantitative assessment.

Non-invasive investigation of the response to oxidative stress in living cardiomyocytes by studying mitochondrial NAD(P)H

Mémoire numérisé par la Division de la gestion de documents et des archives de l'Université de Montréal.

Surveillance non invasive de la réponse neuroimmunitaire fœtale à l’infection

Introduction. In utero, l’infection des membranes maternelles et fœtales, la chorioamniotite, passe souvent inaperçue et, en particulier lorsque associée à une acidémie, due à l’occlusion du cordon ombilical (OCO), comme il se produirait au cours du travail, peut entrainer des lésions cérébrales et avoir des répercussions neurologiques péri - et postnatales à long terme chez le fœtus. Il n'existe actuellement aucun moyen de détecter précocement ces conditions pathologiques in utéro afin de prévenir ou de limiter ces atteintes. Hypothèses. 1)l’électroencéphalogramme (EEG) fœtal obtenu du scalp fœtal pourrait servir d’outil auxiliaire à la surveillance électronique fœtale du rythme cardiaque fœtal (RCF) pour la détection précoce d'acidémie fœtale et d'agression neurologique; 2) la fréquence d’échantillonnage de l’ECG fœtal (ECGf) a un impact important sur le monitoring continu de la Variabilité du Rythme Cardiaque (VRCf) dans la prédiction de l’acidémie fœtale ; 3) les patrons de la corrélation de la VRCf aux cytokines pro-inflammatoires refléteront les états de réponses spontanées versus inflammatoires de la Voie Cholinergique Anti-inflammatoire (VCA); 4) grâce au développement d’un modèle de prédictions mathématiques, la prédiction du pH et de l’excès de base (EB) à la naissance sera possible avec seulement une heure de monitoring d’ECGf. Méthodes. Dans une série d’études fondamentales et cliniques, en utilisant respectivement le mouton et une cohorte de femmes en travail comme modèle expérimental et clinique , nous avons modélisé 1) une situation d’hypoxie cérébrale résultant de séquences d’occlusion du cordon ombilical de sévérité croissante jusqu’à atteindre un pH critique limite de 7.00 comme méthode expérimentale analogue au travail humain pour tester les première et deuxième hypothèses 2) un inflammation fœtale modérée en administrant le LPS à une autre cohorte animale pour vérifier la troisième hypothèse et 3) un modèle mathématique de prédictions à partir de paramètres et mesures validés cliniquement qui permettraient de déterminer les facteurs de prédiction d’une détresse fœtale pour tester la dernière hypothèse. Résultats. Les séries d’OCO répétitives se sont soldés par une acidose marquée (pH artériel 7.35±0.01 à 7.00±0.01), une diminution des amplitudes à l'électroencéphalogramme( EEG) synchronisé avec les décélérations du RCF induites par les OCO accompagnées d'une baisse pathologique de la pression artérielle (PA) et une augmentation marquée de VRCf avec hypoxie-acidémie aggravante à 1000 Hz, mais pas à 4 Hz, fréquence d’échantillonnage utilisée en clinique. L’administration du LPS entraîne une inflammation systémique chez le fœtus avec les IL-6 atteignant un pic 3 h après et des modifications de la VRCf retraçant précisément ce profil temporel des cytokines. En clinique, avec nos cohortes originale et de validation, un modèle statistique basée sur une matrice de 103 mesures de VRCf (R2 = 0,90, P < 0,001) permettent de prédire le pH mais pas l’EB, avec une heure d’enregistrement du RCF avant la poussée. Conclusions. La diminution de l'amplitude à l'EEG suggère un mécanisme d'arrêt adaptatif neuroprotecteur du cerveau et suggère que l'EEG fœtal puisse être un complément utile à la surveillance du RCF pendant le travail à haut risque chez la femme. La VRCf étant capable de détecter une hypoxie-acidémie aggravante tôt chez le fœtus à 1000Hz vs 4 Hz évoque qu’un mode d'acquisition d’ECG fœtal plus sensible pourrait constituer une solution. Des profils distinctifs de mesures de la VRCf, identifiés en corrélation avec les niveaux de l'inflammation, ouvre une nouvelle voie pour caractériser le profil inflammatoire de la réponse fœtale à l’infection. En clinique, un monitoring de chevet de prédiction du pH et EB à la naissance, à partir de mesures de VRCf permettrait des interprétations visuelles plus explicites pour des prises de décision plus exactes en obstétrique au cours du travail.

Non invasive classification system of scoliosis curve types using least-squares support vector machines

Objective To determine scoliosis curve types using non invasive surface acquisition, without prior knowledge from X-ray data. Methods Classification of scoliosis deformities according to curve type is used in the clinical management of scoliotic patients. In this work, we propose a robust system that can determine the scoliosis curve type from non invasive acquisition of the 3D back surface of the patients. The 3D image of the surface of the trunk is divided into patches and local geometric descriptors characterizing the back surface are computed from each patch and constitute the features. We reduce the dimensionality by using principal component analysis and retain 53 components using an overlap criterion combined with the total variance in the observed variables. In this work, a multi-class classifier is built with least-squares support vector machines (LS-SVM). The original LS-SVM formulation was modified by weighting the positive and negative samples differently and a new kernel was designed in order to achieve a robust classifier. The proposed system is validated using data from 165 patients with different scoliosis curve types. The results of our non invasive classification were compared with those obtained by an expert using X-ray images. Results The average rate of successful classification was computed using a leave-one-out cross-validation procedure. The overall accuracy of the system was 95%. As for the correct classification rates per class, we obtained 96%, 84% and 97% for the thoracic, double major and lumbar/thoracolumbar curve types, respectively. Conclusion This study shows that it is possible to find a relationship between the internal deformity and the back surface deformity in scoliosis with machine learning methods. The proposed system uses non invasive surface acquisition, which is safe for the patient as it involves no radiation. Also, the design of a specific kernel improved classification performance.

Statistical model based 3D shape prediction of postoperative trunks for non-invasive scoliosis surgery planning

One of the major concerns of scoliosis patients undergoing surgical treatment is the aesthetic aspect of the surgery outcome. It would be useful to predict the postoperative appearance of the patient trunk in the course of a surgery planning process in order to take into account the expectations of the patient. In this paper, we propose to use least squares support vector regression for the prediction of the postoperative trunk 3D shape after spine surgery for adolescent idiopathic scoliosis. Five dimensionality reduction techniques used in conjunction with the support vector machine are compared. The methods are evaluated in terms of their accuracy, based on the leave-one-out cross-validation performed on a database of 141 cases. The results indicate that the 3D shape predictions using a dimensionality reduction obtained by simultaneous decomposition of the predictors and response variables have the best accuracy.

Towards Non Invasive Diagnosis of Scoliosis Using Semi-supervised Learning Approach

In this paper, a new methodology for the prediction of scoliosis curve types from non invasive acquisitions of the back surface of the trunk is proposed. One hundred and fifty-nine scoliosis patients had their back surface acquired in 3D using an optical digitizer. Each surface is then characterized by 45 local measurements of the back surface rotation. Using a semi-supervised algorithm, the classifier is trained with only 32 labeled and 58 unlabeled data. Tested on 69 new samples, the classifier succeeded in classifying correctly 87.0% of the data. After reducing the number of labeled training samples to 12, the behavior of the resulting classifier tends to be similar to the reference case where the classifier is trained only with the maximum number of available labeled data. Moreover, the addition of unlabeled data guided the classifier towards more generalizable boundaries between the classes. Those results provide a proof of feasibility for using a semi-supervised learning algorithm to train a classifier for the prediction of a scoliosis curve type, when only a few training data are labeled. This constitutes a promising clinical finding since it will allow the diagnosis and the follow-up of scoliotic deformities without exposing the patient to X-ray radiations.

Non-invasive quantitative assessment of scoliosis spinal surgery outcome

Improving the appearance of the trunk is an important goal of scoliosis surgical treatment, mainly in patients' eyes. Unfortunately, existing methods for assessing postoperative trunk appearance are rather subjective as they rely on a qualitative evaluation of the trunk shape. In this paper, an objective method is proposed to quantify the changes in trunk shape after surgery. Using a non-invasive optical system, the whole trunk surface is acquired and reconstructed in 3D. Trunk shape is described by two functional measurements spanning the trunk length: the lateral deviation and the axial rotation. To measure the pre and postoperative differences, a correction rate is computed for both measurements. On a cohort of 36 scoliosis patients with the same spinal curve type who underwent the same surgical approach, surgery achieved a very good correction of the lateral trunk deviation (median correction of 76%) and a poor to moderate correction of the back axial rotation (median correction of 19%). These results demonstrate that after surgery, patients are still confronted with residual trunk deformity, mainly a persisting hump on the back. That can be explained by the fact that current scoliosis assessment and treatment planning are based solely on radiographic measures of the spinal deformity and do not take trunk deformity into consideration. It is believed that with our novel quantitative trunk shape descriptor, clinicians and surgeons can now objectively assess trunk deformity and postoperative shape and propose new treatment strategies that could better address patients' concern about their appearance. © (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.

Non-Invasive Prenatal Testing: Review of Ethical, Legal and Social Implications

Article