Dynamic Thermal Imaging for Intraoperative Monitoring of Neuronal Activity and Cortical Perfusion

Neurosurgery is a demanding medical discipline that requires a complex interplay of several neuroimaging techniques. This allows structural as well as functional information to be recovered and then visualized to the surgeon. In the case of tumor resections this approach allows more fine-grained differentiation of healthy and pathological tissue which positively influences the postoperative outcome as well as the patient's quality of life. In this work, we will discuss several approaches to establish thermal imaging as a novel neuroimaging technique to primarily visualize neural activity and perfusion state in case of ischaemic stroke. Both applications require novel methods for data-preprocessing, visualization, pattern recognition as well as regression analysis of intraoperative thermal imaging. Online multimodal integration of preoperative and intraoperative data is accomplished by a 2D-3D image registration and image fusion framework with an average accuracy of 2.46 mm. In navigated surgeries, the proposed framework generally provides all necessary tools to project intraoperative 2D imaging data onto preoperative 3D volumetric datasets like 3D MR or CT imaging. Additionally, a fast machine learning framework for the recognition of cortical NaCl rinsings will be discussed throughout this thesis. Hereby, the standardized quantification of tissue perfusion by means of an approximated heating model can be achieved. Classifying the parameters of these models yields a map of connected areas, for which we have shown that these areas correlate with the demarcation caused by an ischaemic stroke segmented in postoperative CT datasets. Finally, a semiparametric regression model has been developed for intraoperative neural activity monitoring of the somatosensory cortex by somatosensory evoked potentials. These results were correlated with neural activity of optical imaging. We found that thermal imaging yields comparable results, yet doesn't share the limitations of optical imaging. In this thesis we would like to emphasize that thermal imaging depicts a novel and valid tool for both intraoperative functional and structural neuroimaging

Infrared Thermography for the Assessment of Lumbar Sympathetic Blocks in Patients with Complex Regional Pain Syndrome

[ES] El síndrome de dolor regional complejo (SDRC) es un trastorno de dolor crónico debilitante que suele afectar a una extremidad, y se caracteriza por su compleja e incomprendida fisiopatología subyacente, lo que supone un reto para su diagnóstico y tratamiento. Para evitar el deterioro de la calidad de vida de los pacientes, la consecución de un diagnóstico y tratamiento tempranos marca un punto de inflexión. Entre los diferentes tratamientos, los bloqueos simpáticos lumbares (BSLs) tienen como objetivo aliviar el dolor y reducir algunos signos simpáticos de la afección. Este procedimiento intervencionista se lleva a cabo inyectando anestesia local alrededor de los ganglios simpáticos y, hasta ahora, se realiza frecuentemente bajo el control de diferentes técnicas de imagen, como los ultrasonidos o la fluoroscopia. Dado que la termografía infrarroja (TIR) ha demostrado ser una herramienta eficaz para evaluar la temperatura de la piel, y teniendo en cuenta el efecto vasodilatador que presentan los anestésicos locales inyectados, se ha considerado el uso de la IRT para la evaluación de los BSLs. El objetivo de esta tesis es, estudiar la capacidad de la TIR como una técnica complementaria para la evaluación de la eficacia en la ejecución de los BSLs. Para cumplir este objetivo, se han realizado tres estudios implementando la TIR en pacientes diagnosticados de SDRC de miembros inferiores sometidos a BSLs. El primer estudio se centra en la viabilidad de la TIR como herramienta complementaria para la evaluación de la eficacia ejecución de los BSLs. Cuando se realizan los BSLs, la colocación correcta de la aguja es crítica para llevar realizar el procedimiento técnicamente correcto y, en consecuencia, para lograr los resultados clínicos deseados. Para verificar la posición de la aguja, tradicionalmente se han utilizado técnicas de imagen, sin embargo, los BSLs bajo control fluoroscópico no siempre aseguran su exacta ejecución. Por este motivo, se han aprovechado las alteraciones térmicas inducidas por los anestésicos locales y se han evaluado mediante la TIR. Así, cuando en las imágenes infrarrojas se observaron cambios térmicos en la planta del pie afectado tras la inyección de lidocaína, se consideró que el BSL era exitoso. El segundo estudio trata del análisis cuantitativo de los datos térmicos recogidos en el entorno clínico a partir de diferentes parámetros basados en las temperaturas extraídas de ambos pies. Según los resultados, para predecir adecuadamente los BSLs exitosos, se deberían analizar las temperaturas de las plantas de los pies durante los primeros cuatro minutos tras la inyección del anestésico local. Así, la aplicación de la TIR en el entorno clínico podría ser de gran ayuda para evaluar la eficacia de ejecución de los BSLs mediante la evaluación de las temperaturas de los pies en tiempo real. Por último, el tercer estudio aborda el análisis cuantitativo mediante la implementación de herramientas de machine learning (ML) para evaluar su capacidad de clasificar automáticamente los BSLs. En este estudio se han utilizado una serie de características térmicas extraídas de las imágenes infrarrojas para evaluar cuatro algoritmos de ML para tres momentos diferentes después del instante de referencia (inyección de lidocaína). Los resultados indican que los cuatro modelos evaluados presentan buenos rendimientos para clasificar automáticamente los BSLs entre exitosos y fallidos. Por lo tanto, la combinación de parámetros térmicos junto con de clasificación ML muestra ser eficaz para la clasificación automática de los procedimientos de BSLs. En conclusión, el uso de la TIR como técnica complementaria en la práctica clínica diaria para la evaluación de los BSLs ha demostrado ser totalmente eficaz. Dado que es un método objetivo y relativamente sencillo de implementar, puede permitir que los médicos especialistas en dolor identifiquen los bloqueos realizados fallidos y, en consecuencia, puedan revertir esta situación.[CA] La síndrome de dolor regional complex (SDRC) és un trastorn de dolor crònic debilitant que sol afectar una extremitat, i es caracteritza per la seua complexa i incompresa fisiopatologia subjacent, la qual cosa suposa un repte per al seu diagnòstic i tractament. Per a evitar la deterioració de la qualitat de vida dels pacients, la consecució d'un diagnòstic i tractament primerencs marca un punt d'inflexió. Entre els diferents tractaments , els bloquejos simpàtics lumbars (BSLs) tenen com a objectiu alleujar el dolor i reduir alguns signes simpàtics de l'afecció. Aquest procediment intervencionista es duu a terme injectant anestèsia local al voltant dels ganglis simpàtics i, fins ara, es realitza freqüentment sota el control de diferents tècniques d'imatge, com els ultrasons o la fluoroscopia. Atés que la termografia infraroja (TIR) ha demostrat ser una eina eficaç per a avaluar la temperatura de la pell, i tenint en compte l'efecte vasodilatador que presenten els anestèsics locals injectats, s'ha considerat l'ús de la TIR per a l'avaluació dels BSLs. L'objectiu d'aquesta tesi és, estudiar la capacitat de la TIR com una tècnica complementària per a l'avaluació de l'eficàcia en l'execució dels BSLs. Per a complir aquest objectiu, s'han realitzat tres estudis implementant la TIR en pacients diagnosticats de SDRC de membres inferiors sotmesos a BSLs. El primer estudi avalua la viabilitat de la TIR com a eina complementària per a l'analisi de l'eficàcia en l'execució dels BSLs. Quan es realitzen els BSLs, la col·locació correcta de l'agulla és crítica per a dur a terme el procediment tècnicament correcte i, en conseqüència, per a aconseguir els resultats clínics desitjats. Per a verificar la posició de l'agulla, tradicionalment s'han utilitzat tècniques d'imatge, no obstant això, els BSLs baix control fluoroscòpic no sempre asseguren la seua exacta execució. Per aquest motiu, s'han aprofitat les alteracions tèrmiques induïdes pels anestèsics locals i s'han avaluat mitjançant la TIR. Així, quan en les imatges infraroges es van observar canvis tèrmics en la planta del peu afectat després de la injecció de lidocaIna, es va considerar que el BSL era exitós. El segon estudi tracta de l'anàlisi quantitativa de les dades tèrmiques recollides en l'entorn clínic a partir de diferents paràmetres basats en les temperatures extretes d'ambdós peus. Segons els resultats, per a predir adequadament l'execució exitosa d'un BSL, s'haurien d'analitzar les temperatures de les plantes dels peus durant els primers quatre minuts després de la injecció de l'anestèsic local. Així, l'implementació de la TIR en l'entorn clínic podria ser de gran ajuda per a avaluar l'eficàcia d'execució dels BSLs mitjançant l'avaluació de les temperatures dels peus en temps real. El tercer estudi aborda l'anàlisi quantitativa mitjançant la implementació d'eines machine learning (ML) per a avaluar la seua capacitat de classificar automàticament els BSLs. En aquest estudi s'han utilitzat una sèrie de característiques tèrmiques extretes de les imatges infraroges per a avaluar quatre algorismes de ML per a tres moments diferents després de l'instant de referència (injecció de lidocaïna). Els resultats indiquen que els quatre models avaluats presenten bons rendiments per a classificar automàticament els BSLs en exitosos i fallits. Per tant, la combinació de paràmetres tèrmics juntament amb models de classificació ML mostra ser eficaç per a la classificació automàtica dels procediments de BSLs. En conclusió, l'ús de la TIR com a tècnica complementària en la pràctica clínica diària per a l'avaluació dels BSLs ha demostrat ser totalment eficaç. Atés que és un mètode objectiu i relativament senzill d'implementar, pot ajudar els metges especialistes en dolor a identificar els bloquejos realitzats fallits i, en conseqüència, puguen revertir aquesta situació.[EN] Complex regional pain syndrome (CRPS) is a debilitating chronic pain condition that usually affects one limb, and it is characterized by its misunderstood underlying pathophysiology, resulting in both challenging diagnosis and treatment. To avoid the patients' impairment quality of life, the achievement of both an early diagnosis and treatment marks a turning point. Among the different treatment approaches, lumbar sympathetic blocks (LSBs) are addressed to alleviate the pain and reduce some sympathetic signs of the condition. This interventional procedure is performed by injecting local anaesthetic around the sympathetic ganglia and, until now, it has been performed under different imaging techniques, including the ultrasound or the fluoroscopy approaches. Since infrared thermography (IRT) has proven to be a powerful tool to evaluate skin temperatures and taking into account the vasodilatory effects of the local anaesthetics injected in the LSB, the use of IRT has been considered for the LSBs assessment. Therefore, the purpose of this thesis is to evaluate the capability of IRT as a complementary assessment technique for the LSBs procedures performance. To fulfil this aim, three studies have been conducted implementing the IRT in patients diagnosed with lower limbs CRPS undergoing LSBs. The first study focuses on the feasibility of IRT as a complementary assessment tool for LSBs performance, that is, for the confirmation of the proper needle position. When LSBs are performed, the correct needle placement is critical to carry out the procedure technically correct and, consequently, to achieve the desired clinical outcomes. To verify the needle placement position, imaging techniques have traditionally been used, however, LSBs under radioscopic guidance do not always ensure an exact performance. For this reason, the thermal alterations induced by the local anaesthetics, have been exploited and assessed by means of IRT. Thus, the LSB procedure was considered successfully performed when thermal changes within the affected plantar foot were observed in the infrared images after the lidocaine injection. The second study deals with the quantitative analysis of the thermal data collected in the clinical setting through the evaluation of different temperature-based parameters extracted from both feet. According to the results, the proper LSB success prediction could be achieved in the first four minutes after the block through the evaluation of the feet skin temperatures. Therefore, the implementation of IRT in the clinical setting might be of great help in assessing the LSBs performance by evaluating the plantar feet temperatures in real time. Finally, the third study addresses the quantitative analysis by implementing machine learning (ML) tools to assess their capability to automatically classify LSBs. In this study, a set of thermal features retrieved from the infrared images have been used to evaluate four ML algorithms for three different moments after the baseline time (lidocaine injection). The results indicate that all four models evaluated present good performance metrics to automatically classify LSBs into successful and failed. Therefore, combining infrared features with ML classification models shows to be effective for the LSBs procedures automatic classification. In conclusion, the use of IRT as a complementary technique in daily clinical practice for LSBs assessment has been evidenced entirely effective. Since IRT is an objective method and it is not very demanding to perform, it is of great help for pain physicians to identify failed procedures, and consequently, it allow them to reverse this situation.Cañada Soriano, M. (2022). Infrared Thermography for the Assessment of Lumbar Sympathetic Blocks in Patients with Complex Regional Pain Syndrome [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/181699TESI

Segmentation approaches for diabetic foot disorders

Thermography enables non-invasive, accessible, and easily repeated foot temperature measurements for diabetic patients, promoting early detection and regular monitoring protocols, that limit the incidence of disabling conditions associated with diabetic foot disorders. The establishment of this application into standard diabetic care protocols requires to overcome technical issues, particularly the foot sole segmentation. In this work we implemented and evaluated several segmentation approaches which include conventional and Deep Learning methods. Multimodal images, constituted by registered visual-light, infrared and depth images, were acquired for 37 healthy subjects. The segmentation methods explored were based on both visual-light as well as infrared images, and optimization was achieved using the spatial information provided by the depth images. Furthermore, a ground truth was established from the manual segmentation performed by two independent researchers. Overall, the performance level of all the implemented approaches was satisfactory. Although the best performance, in terms of spatial overlap, accuracy, and precision, was found for the Skin and U-Net approaches optimized by the spatial information. However, the robustness of the U-Net approach is preferred.This research was funded by the IACTEC Technological Training program, grant number TF INNOVA 2016–2021. This work was completed while Abián Hernández was beneficiary of a pre-doctoral grant given by the “Agencia Canaria de Investigacion, Innovacion y Sociedad de la Información (ACIISI)” of the “Consejería de Economía, Industria, Comercio y Conocimiento” of the “Gobierno de Canarias”, which is partly financed by the European Social Fund (FSE) (POC 2014–2020, Eje 3 Tema Prioritario 74 (85%))

Laser stimulated dynamic thermal imaging system for tumor detection

Laser stimulated dynamic thermal imaging system for tumor detectionby Hongyu Meng Doctor of Philosophy in Biomedical Engineering Washington University in St. Louis, 2021 Professor Samuel Achilefu, Chair Recent advances in infrared sensor technology have enabled the rapid application of thermal imaging in materials science, security and medicine. Relying on the infrared characteristics of living systems, thermal imaging has been used to generate individual heat maps, detect inflammation and tumor. As an imaging system, thermal imaging has the advantages of portability, real-time, non-invasive, and non-contact. But the low specificity of thermal imaging hinders its wide clinical application. Unfortunately, label-free DTI is less able to fully capture thermal tissue heterogeneity in high resolution due partly to how thermal stimulation is applied. Current DTI methods apply thermal stimulation to a large area of tissue, which obscures the detection of the unique thermal characteristics of a small area in the thermally disturbed area. Super-resolution DTI grating can improve the spatial resolution, but the system setup is complex. For biological samples, the use of exogenous contrast agents can enhance contrast, but contrast agents increase regulatory hurdles in clinical trials. In this work, we have developed a focused dynamic laser stimulation imaging (FDTI) system to overcome these limitations. The system, which has high resolution, high speed and large field of view uses a short wavelength laser to stimulate small tissue area and a thermal camera to acquire data. We captured thermal images and videos, extracted features, and built classifiers to distinguish tumors from normal tissues. Data analysis showed that FDTI method achieved high accuracy (classifier surpassed 90%) with spatial resolution attaining 1 mm, which surpasses conventional thermal imaging and DTI. We next explored the ability of FDTI to detect early-stage tumors by scanning multiple areas that exhibited normal thermal images with conventional thermal imaging. A bioluminescence imaging (BLI) system was then used to locate the tumor, which was co-registered to the FDTI images to determine the position of the laser spot. By extracting features from the collected thermal images and videos and constructing the classifier, the FDTI system achieved an accuracy greater than 80% in detecting early tumors in different mouse tumor models. Subsequently, the FDTI system was optimized to improve its acquisition speed, automation and robustness. First, we analyzed the influencing factors of imaging and proposed new system hardware designs to improve the data acquisition speed. Then, to shorten the acquisition time from the software level, we tested and analyzed the performance of features at different stages during the acquisition process. We also designed and tested registration markers, including registration results of different features, feature robustness under interference, marker detection from the background, and marker performance in motion correction to improve the degree of automation of the system. Furthermore, we tested the performance of thermal imaging applications in other research fields, including brain tumor detection, nerve damage assessment, and whether temperature changes correlate with stroke. These results show that FDTI is a promising technique for enhancing contrast, improving spatial resolution, determining underlying tumor heterogeneity, and detecting tumors at stages when conventional thermal imaging is ineffective. This work lays a strong foundation for diverse applications and clinical translation of FDTI to address unmet needs of current thermal imaging technologies

행동적 항상성 조절의 신경회로: 섭식 행동과 체온조절 행동 중심으로

학위논문(박사) -- 서울대학교대학원 : 자연과학대학 협동과정 뇌과학전공, 2022. 8. 김성연.Maintaining physiological conditions (e.g., nutrients, water, and body temperature) within a narrow range is a distinct quality of living organisms. Among them, animals utilize diverse behaviors to suffice materials in need to maintain internal stability, called homeostasis. As such, understanding the neural mechanisms for behavioral regulations of homeostatic conditions has been a key interest in neurobiology and physiology. However, despite the importance of this question, neural processes underlying some of the fundamental behaviors for maintaining organismal homeostasis are still elusive. In this dissertation, I describe the data revealing neural circuit mechanisms underlying two basic behaviors for regulating homeostasis: ingestive and thermoregulatory behaviors. Chapter one of this dissertation briefly overviews the origin of the homeostasis concept and provides a short historical perspective on studying neural processes for behavioral regulation of homeostasis. Chapter two describes a molecularly defined neural population in a hindbrain area called the parabrachial nucleus for monitoring and suppressing ingestion and demonstrates a gut-to-brain neural circuit spanning from the peripheral sensory ganglia to the hypothalamus for mechanosensory feedback control of ingestion. Chapter three describes a parabrachial-to-hypothalamic neural circuit for thermoregulatory behaviors and the neural coding of motivational aspects of thermal stimuli by a subpopulation of hypothalamic neurons. Chapter four describes a summary of the data presented in this dissertation and provides directions for further investigations. Together, this dissertation presents studies on understanding neural circuit mechanisms underlying fundamental behaviors for regulating crucial homeostatic conditions, including energy, fluid, and body temperature.영양분과 체온 등 체내 환경을 일정 수준으로 유지하는 성질인 항상성은 생명체의 중요한 특징이다. 여러 생물 종 중에서 특별히 동물들은 행동을 통해 자신의 필요를 채워 체내 항상성을 유지하는데, 따라서 항상성을 유지하기 위한 동물 행동을 매개하는 신경 기작을 이해하는 것은 신경생물학 및 생리학의 오랜 과제였다. 수십 년에 걸친 연구들로 많은 부분이 밝혀졌으나, 몇몇 근본적인 항상성 유지 행동을 매개하는 신경회로 기작은 여전히 알려지지 않고 있었다. 본 연구는 섭식 행동과 체온 유지 행동을 조절하는 데 관여하는 새로운 신경회로 기작을 밝힘으로써, 항상성 유지의 신경학적 원리에 대한 이해를 넓히는 것을 목표로 한다. 1장에서는 항상성 개념의 형성과 그 이후 이어진 항상성 조절 신경 기작에 관한 연구의 역사를 간략히 살펴보고자 한다. 2장에서는 소화관의 물리적 감각 신호를 이용하여 섭식을 모니터링하고 이에 따라 음식물의 섭취를 조절하는 후뇌부 신경세포 집단과, 그 집단을 중심으로 말초 신경절에서 시상하부까지 이어지는 장-뇌 신경회로에 관한 연구를 기술한다. 3장에서는 다양한 체온조절 행동에 필수적인 시상하부 신경 집단과 이를 중심으로 체온 조절 행동을 매개하는 신경회로 기작에 관한 연구를 기술한다. 4장에서는 본 논문에 기술된 연구 결과를 간략히 정리하고 그 의의에 관해 살펴본다. 본 연구들은 섭식 행동과 체온 조절 행동을 매개하는 신경회로 기작에 관한 새로운 이해를 더함으로써, 생명 유지에 필수적인 항상성 조절 행동의 신경학적 기반을 완전히 밝히는 데 기여할 것으로 기대한다.Chapter 1. Introduction 1 Chapter 2. A neural circuit mechanism for mechanosensory feedback control of ingestion 6 Chapter 3. A forebrain neural substrate for behavioral thermoregulation 80 Chapter 4. Conclusion 167 Bibliography 173 Abstract in Korean 186박

Video thermography: complex regional pain syndrome in the picture

In this thesis videothermography is developed and evaluated as a diagnostic and monitoring tool in Complex Regional Pain Syndrome type 1 (CRPS1). This work is conducted within four pre- set developmental phases: namely, the initial, potential, monitoring and diagnostic phases. Two main methods of measurement were developed and evaluated, namely: i) static videothermography: recording of a thermographic image of an extremity without application of any disturbing factors on temperature regulation and ii) dynamic videothermography: recordings of a sequence of thermographic images during application of various disturbing effects on temperature regulation of the human body. The recorded thermographic images were analysed by means of various mathematical methods and their additive value in the assessment of CRPS1 was studied