Sensors and imaging for wound healing : a review

Wound healing involves a complex series of biochemical events and has traditionally been managed with 'low tech' dressings and bandages. The concept that diagnostic and theranostic sensors can complement wound management is rapidly growing in popularity as there is tremendous potential to apply this technology to both acute and chronic wounds. Benefits in sensing the wound environment include reduction of hospitalization time, prevention of amputations and better understanding of the processes which impair healing. This review discusses the state-of-the-art in detection of markers associated with wound healing and infection, utilizing devices imbedded within dressings or as point-of-care techniques to allow for continual or rapid wound assessment and monitoring. Approaches include using biological or chemical sensors of wound exudates and volatiles to directly or indirectly detect bacteria, monitor pH, temperature, oxygen and enzymes. Spectroscopic and imaging techniques are also reviewed as advanced wound monitoring techniques. The review concludes with a discussion of the limitations of and future directions for this field.

Anomalous event detection using a semi-two dimensional hidden Markov model

The rapid increase in the deployment of CCTV systems has led to a greater demand for algorithms that are able to process incoming video feeds. These algorithms are designed to extract information of interest for human operators. During the past several years, there has been a large effort to detect abnormal activities through computer vision techniques. Typically, the problem is formulated as a novelty detection task where the system is trained on normal data and is required to detect events which do not fit the learned `normal' model. Many researchers have tried various sets of features to train different learning models to detect abnormal behaviour in video footage. In this work we propose using a Semi-2D Hidden Markov Model (HMM) to model the normal activities of people. The outliers of the model with insufficient likelihood are identified as abnormal activities. Our Semi-2D HMM is designed to model both the temporal and spatial causalities of the crowd behaviour by assuming the current state of the Hidden Markov Model depends not only on the previous state in the temporal direction, but also on the previous states of the adjacent spatial locations. Two different HMMs are trained to model both the vertical and horizontal spatial causal information. Location features, flow features and optical flow textures are used as the features for the model. The proposed approach is evaluated using the publicly available UCSD datasets and we demonstrate improved performance compared to other state of the art methods.

A 3D virtual medical imaging suite : bridging the academic-clinical training boundary

Aims The Medical Imaging Training Immersive Environment (MITIE) system is a recently developed virtual reality (VR) platform that allows students to practice a range of medical imaging techniques. The aim of this pilot study was to harvest user feedback about the educational value of the application and inform future pedagogical development. This presentation explores the use of this technology for skills training and blurring the boundaries between academic learning and clinical skills training. Background MITIE is a 3D VR environment that allows students to manipulate a patient and radiographic equipment in order to produce a VR-generated image for comparison with a gold standard. As with VR initiatives in other health disciplines (1-6) the software mimics clinical practice as much as possible and uses 3D technology to enhance immersion and realism. The software was developed by the Medical Imaging Course Team at a provider University with funding from a Health Workforce Australia “Simulated Learning Environments” grant. Methods Over 80 students undertaking the Bachelor of Medical Imaging Course were randomised to receive practical experience with either MITIE or radiographic equipment in the medical radiation laboratory. Student feedback about the educational value of the software was collected and performance with an assessed setup was measured for both groups for comparison. Ethical approval for the project was provided by the university ethics panel. Results This presentation provides qualitative analysis of student perceptions relating to satisfaction, usability and educational value as well as comparative quantitative performance data. Students reported high levels of satisfaction and both feedback and assessment results confirmed the application’s significance as a pre-clinical training tool. There was a clear emerging theme that MITIE could be a useful learning tool that students could access to consolidate their clinical learning, either during their academic timetables or their clinical placement. Conclusion Student feedback and performance data indicate that MITIE has a valuable role to play in the clinical skills training for medical imaging students both in the academic and the clinical environment. Future work will establish a framework for an appropriate supporting pedagogy that can cross the boundary between the two environments. This project was possible due to funding made available by Health Workforce Australia.

Topological localization using optical flow descriptors

We propose a topological localization method based on optical flow information. We analyse the statistical characteristics of the optical flow signal and demonstrate that the flow vectors can be used to identify and describe key locations in the environment. The key locations (nodes) correspond to significant scene changes and depth discontinuities. Since optical flow vectors contain position, magnitude and angle information, for each node, we extract low and high order statistical moments of the vectors and use them as descriptors for that node. Once a database of nodes and their corresponding optical flow features is created, the robot can perform topological localization by using the Mahalanobis distance between the current frame and the database. This is supported by field trials, which illustrate the repeatability of the proposed method for detecting and describing key locations in indoor and outdoor environments in challenging and diverse lighting conditions.

Functional brain maps of Tower of London performance : a positron emission tomography and functional magnetic resonance imaging study

Regional cerebral blood flow (rCBF) and blood oxygenation level-dependent (BOLD) contrasts represent different physiological measures of brain activation. The present study aimed to compare two functional brain imaging techniques (functional magnetic resonance imaging versus [15O] positron emission tomography) when using Tower of London (TOL) problems as the activation task. A categorical analysis (task versus baseline) revealed a significant BOLD increase bilaterally for the dorsolateral prefrontal and inferior parietal cortex and for the cerebellum. A parametric haemodynamic response model (or regression analysis) confirmed a task-difficulty-dependent increase of BOLD and rCBF for the cerebellum and the left dorsolateral prefrontal cortex. In line with previous studies, a task-difficulty-dependent increase of left-hemispheric rCBF was also detected for the premotor cortex, cingulate, precuneus, and globus pallidus. These results imply consistency across the two neuroimaging modalities, particularly for the assessment of prefrontal brain function when using a parametric TOL adaptation.

Investigation of fiducial marker and soft-tissue image guidance techniques in prostate radiation therapy

This thesis examines and compares imaging methods used during the radiotherapy treatment of prostate cancer. The studies found that radiation therapists were able to localise and target the prostate consistently with planar imaging techniques and that the use of small gold markers in the prostate reduced the variation in prostate localisation when using volumetric imaging. It was concluded that larger safety margins are required when using volumetric imaging without gold markers.

Imaging tumour distribution of a polymeric drug delivery platformin vivoby PET-MRI

Background Over the past decade, molecular imaging has played a key role in the progression of drug delivery platforms from concept to commercialisation. Of the molecular imaging techniques commonly utilised, positron emission tomography (PET) can yield a breadth of information not easily accessible by other methodologies and when combined with other complementary imaging modalities, is a powerful tool for pre- and clinical development of therapeutics. However, very little research has focussed on the information available from complimentary imaging modalities. This paper reports on the data-rich methodologies of contrast enhanced PET/CT and PET/MRI for probing efficacy of polymer drug delivery platforms. Results The information available from an ExiTron nano 6000 contrast enhanced PET/CT and a gadolinium (Gd) enhanced PET/MRI image of a 64Cu labeled HBP in the same mouse was qualitatively compared. Conclusions Gd contrast enhanced PET/MRI offers a powerful methodology for investigating the distribution of polymer drug delivery platforms in vivo and throughout a tumour volume. Furthermore, information about depth of penetration away from primary blood vessels can be gleaned, potentially leading to development of more efficacious delivery vehicles for clinical use.

Synthesis of a multimodal molecular imaging probe based on a hyperbranched polymer architecture

Molecular imaging is utilised in modern medicine to aid in the diagnosis and treatment of disease by allowing its spatiotemporal state to be examined in vivo. This study focuses on the development of novel multimodal molecular imaging agents based on hyperbranched polymers that combine the complementary capabilities of optical fluorescence imaging and positron emission tomography-computed tomography (PET/CT) into one construct. RAFT-mediated polymerisation was used to prepare two hydrophilic hyperbranched polymers that were differentiated by their size and level of branching. The multiple functional end-groups facilitated covalent attachment of both near infrared fluorescent dyes for optical imaging, as well as a copper chelator allowing binding of 64Cu as a PET radio nuclei. In vivo multimodal imaging of mice using PET/CT and planar optical imaging was first used to assess the biodistribution of the polymeric materials and it was shown that the larger and more branched polymer had a significantly longer circulation time. The larger constructs were also shown to exhibit enhanced accumulation in solid tumours in a murine B16 melanoma model. Importantly, it was demonstrated that the PET modality gave rise to high sensitivity immediately after injection of the agent, while the optical modality facilitated extended longitudinal studies, thus highlighting how the complementary capabilities of the molecular imaging agents can be useful for studying various diseases, including cancer.

Noninvasive imaging of atheromatous carotid plaques

Atherothrombosis is a systemic disease of the arterial wall that affects the carotid, coronary, and peripheral vascular beds, and the aorta. This condition is associated with complications such as stroke, myocardial infarction, and peripheral vascular disease, which usually result from unstable atheromatous plaques. The study of atheromatous plaques can provide useful information about the natural history and progression of the disease, and aid in the selection of appropriate treatment. Plaque imaging can be crucial in achieving this goal. In this Review, we focus on the various noninvasive imaging techniques that are being used for morphological and functional assessment of carotid atheromatous plaques in the clinical setting.

Microsurgical Aneurysm Model in Rats and Mice: Development of Endovascular Treatment and Optimization of Magnetic Resonance Imaging

The rupture of a cerebral artery aneurysm causes a devastating subarachnoid hemorrhage (SAH), with a mortality of almost 50% during the first month. Each year, 8-11/100 000 people suffer from aneurysmal SAH in Western countries, but the number is twice as high in Finland and Japan. The disease is most common among those of working age, the mean age at rupture being 50-55 years. Unruptured cerebral aneurysms are found in 2-6% of the population, but knowledge about the true risk of rupture is limited. The vast majority of aneurysms should be considered rupture-prone, and treatment for these patients is warranted. Both unruptured and ruptured aneurysms can be treated by either microsurgical clipping or endovascular embolization. In a standard microsurgical procedure, the neck of the aneurysm is closed by a metal clip, sealing off the aneurysm from the circulation. Endovascular embolization is performed by packing the aneurysm from the inside of the vessel lumen with detachable platinum coils. Coiling is associated with slightly lower morbidity and mortality than microsurgery, but the long-term results of microsurgically treated aneurysms are better. Endovascular treatment methods are constantly being developed further in order to achieve better long-term results. New coils and novel embolic agents need to be tested in a variety of animal models before they can be used in humans. In this study, we developed an experimental rat aneurysm model and showed its suitability for testing endovascular devices. We optimized noninvasive MRI sequences at 4.7 Tesla for follow-up of coiled experimental aneurysms and for volumetric measurement of aneurysm neck remnants. We used this model to compare platinum coils with polyglycolic-polylactic acid (PGLA) -coated coils, and showed the benefits of the latter in this model. The experimental aneurysm model and the imaging methods also gave insight into the mechanisms involved in aneurysm formation, and the model can be used in the development of novel imaging techniques. This model is affordable, easily reproducible, reliable, and suitable for MRI follow-up. It is also suitable for endovascular treatment, and it evades spontaneous occlusion.

Kirjallisuuskatsaus: Eturauhassyövän androgeeniresponsiiviset in vivo -mallit; Kokeellinen osa: Bioluminesenssiin perustuvan ortotooppisen eturauhassyöpämallin optimointi

Eturauhassyöpä on yksi yleisimmistä syövistä länsimaissa. Eturauhassyöpä on yleensä hitaasti kehittyvä tauti. Edetessään se voi kuitenkin muuntua aggressiivisemmaksi ja aiheuttaa metastaaseja, jotka ovat pääasiallisena syynä taudin kuolleisuuteen. Androgeenit ovat merkittäviä tekijöitä eturauhassyövän patogeneesissä ja eturauhassyöpäkudos on useimmiten riippuvainen androgeeneista. Tämän vuoksi hoidon tavoitteena on estää niiden eritys kirurgisella tai kemiallisella kastraatiolla ja/tai estää androgeenien vaikutus antiandrogeeneilla. Eturauhassyöpää sekä sen hoitoon tarkoitettuja uusia lääkehoitomahdollisuuksia tutkitaan kiivaasti. Eturauhassyövän tutkimiseen on kehitetty lukematon määrä erilaisia in vivo -malleja. Koska eturauhassyöpä on yleensä androgeeneille herkkä, kuvaavat androgeeniresponsiiviset eläinmallit ihmisen tautia parhaiten. Eturauhassyövän mallintamiseen in vivo voidaan käyttää eri eläinlajeja, mutta hiiri on ylivoimaisesti käytetyin mallieläin. Immuunipuutteisiin hiiriin voidaan aiheuttaa kasvaimia inokuloimalla ihmisen kasvainsoluja tai osia ihmisen kasvaimista. Ortotooppisesti eturauhaseen inokuloitavat kasvainmallit mallintavat eturauhassyövässä esiintyvää syöpäsolujen ja stroomasolujen välistä epänormaalia vuorovaikutusta. Muuntogeeniset hiirimallit ovat yhä yleisempiä eturauhassyövän tutkimuksessa. Muuntogeenisilla malleilla voidaan mallintaa taudin kehittymistä ja sen etenemistä kokonaisuudessaan parhaiten. Eturauhasessa olevaa kasvainta ja sen kasvua on vaikea seurata ilman prostataspesifisen antigeenin (PSA) pitoisuuden mittausta tai erityisiä kuvantamistekniikoita. Tällaisia menetelmiä, kuten optista kuvantamista, käytetään yhä enemmän hyödyksi erilaisissa eturauhassyövän in vivo -malleissa. Tutkielman kokeellisen osan tavoitteena oli optimoida bioluminesenssiin perustuva optinen kuvantamismenetelmä androgeeniresponsiivisessa LNCaP-luc2-solulinjassa ortotooppisessa eturauhassyöpämallissa. Bioluminesenssikuvantaminen perustuu kasvainsolujen ilmentämän lusiferaasin katalysoimaan reaktioon, jossa entsyymin substraatti, lusiferiini, hapettuu ja tuottaa näkyvää valoa. Lisäksi tavoitteena oli tutkia lääkehoitojen ja kastraation vasteita mallissa. Bioluminesenssiin perustuvalla kuvantamisella oli mahdollista seurata eturauhaskasvainten kasvua noninvasiivisesti, reaaliaikaisesti ja toistuvasti. Bioluminesenssikuvantamisen avulla kasvainten kvantitointi oli nopeampaa kuin ultraäänikuvantamisen avulla, ja kasvainten kasvua oli myös mahdollista seurata useammin kuin seerumin PSA-mittausten avulla. Bioluminesenssikuvantamisen todettiin korreloivan paremmin PSA-pitoisuuden kanssa kuin kasvaimen todelliseen kokoon lopetushetkellä. Seerumin PSA-pitoisuus korreloi kuitenkin bioluminesenssimittausta paremmin eturauhaskasvaimen kokoon tässä kokeessa. Kasvainten oletettua suurempaa kokoa voidaan pitää todennäköisimpänä syynä sille, ettei lääkehoitojen tai kastraation todettu vaikuttavan kasvainten kasvuun bioluminesenssikuvantamisella mitattuna. Bioluminesenssikuvantaminen ei sovellu suurille eikä nekroottisille kasvaimille, sillä kuvantamismenetelmä toimii vain elävillä soluilla. Bioluminesenssikuvantamisen hyödyntämisen kannalta oleellista tässä mallissa on myös lusiferiini-injektion onnistuminen. Jatkotutkimuksia tarvitaan edelleen mallin validoimiseksi mm. lääkehoitojen vasteiden osoittamiseksi.

Data-resolution based optimization of the data-collection strategy for near infrared diffuse optical tomography

Purpose: To optimize the data-collection strategy for diffuse optical tomography and to obtain a set of independent measurements among the total measurements using the model based data-resolution matrix characteristics. Methods: The data-resolution matrix is computed based on the sensitivity matrix and the regularization scheme used in the reconstruction procedure by matching the predicted data with the actual one. The diagonal values of data-resolution matrix show the importance of a particular measurement and the magnitude of off-diagonal entries shows the dependence among measurements. Based on the closeness of diagonal value magnitude to off-diagonal entries, the independent measurements choice is made. The reconstruction results obtained using all measurements were compared to the ones obtained using only independent measurements in both numerical and experimental phantom cases. The traditional singular value analysis was also performed to compare the results obtained using the proposed method. Results: The results indicate that choosing only independent measurements based on data-resolution matrix characteristics for the image reconstruction does not compromise the reconstructed image quality significantly, in turn reduces the data-collection time associated with the procedure. When the same number of measurements (equivalent to independent ones) are chosen at random, the reconstruction results were having poor quality with major boundary artifacts. The number of independent measurements obtained using data-resolution matrix analysis is much higher compared to that obtained using the singular value analysis. Conclusions: The data-resolution matrix analysis is able to provide the high level of optimization needed for effective data-collection in diffuse optical imaging. The analysis itself is independent of noise characteristics in the data, resulting in an universal framework to characterize and optimize a given data-collection strategy. (C) 2012 American Association of Physicists in Medicine. http://dx.doi.org/10.1118/1.4736820]

AN ITERATIVE ALGORITHM FOR PHASE RETRIEVAL WITH SPARSITY CONSTRAINTS: APPLICATION TO FREQUENCY DOMAIN OPTICAL COHERENCE TOMOGRAPHY

We address the problem of phase retrieval, which is frequently encountered in optical imaging. The measured quantity is the magnitude of the Fourier spectrum of a function (in optics, the function is also referred to as an object). The goal is to recover the object based on the magnitude measurements. In doing so, the standard assumptions are that the object is compactly supported and positive. In this paper, we consider objects that admit a sparse representation in some orthonormal basis. We develop a variant of the Fienup algorithm to incorporate the condition of sparsity and to successively estimate and refine the phase starting from the magnitude measurements. We show that the proposed iterative algorithm possesses Cauchy convergence properties. As far as the modality is concerned, we work with measurements obtained using a frequency-domain optical-coherence tomography experimental setup. The experimental results on real measured data show that the proposed technique exhibits good reconstruction performance even with fewer coefficients taken into account for reconstruction. It also suppresses the autocorrelation artifacts to a significant extent since it estimates the phase accurately.

Data-resolution based optimal choice of minimum required measurements for image-guided diffuse optical tomography

Image-guided diffuse optical tomography has the advantage of reducing the total number of optical parameters being reconstructed to the number of distinct tissue types identified by the traditional imaging modality, converting the optical image-reconstruction problem from underdetermined in nature to overdetermined. In such cases, the minimum required measurements might be far less compared to those of the traditional diffuse optical imaging. An approach to choose these optimally based on a data-resolution matrix is proposed, and it is shown that such a choice does not compromise the reconstruction performance. (C) 2013 Optical Society of America

Point Spread Function Engineering for Super-Resolution Single-Photon and Multiphoton Fluorescence Microscopy

Super-resolution imaging techniques are of paramount interest for applications in bioimaging and fluorescence microscopy. Recent advances in bioimaging demand application-tailored point spread functions. Here, we present some approaches for generating application-tailored point spread functions along with fast imaging capabilities. Aperture engineering techniques provide interesting solutions for obtaining desired system point spread functions. Specially designed spatial filters—realized by optical mask—are outlined both in a single-lens and 4Pi configuration. Applications include depth imaging, multifocal imaging, and super-resolution imaging. Such an approach is suitable for fruitful integration with most existing state-of-art imaging microscopy modalities.