Magnetic nanoparticle hyperthermia enhances radiation therapy: A study in mouse models of human prostate cancer.

PURPOSE: We aimed to characterise magnetic nanoparticle hyperthermia (mNPH) with radiation therapy (RT) for prostate cancer. METHODS: Human prostate cancer subcutaneous tumours, PC3 and LAPC-4, were grown in nude male mice. When tumours measured 150 mm3 magnetic iron oxide nanoparticles (MIONPs) were injected into tumours to a target dose of 5.5 mg Fe/cm3 tumour, and treated 24 h later by exposure to alternating magnetic field (AMF). Mice were randomly assigned to one of four cohorts to characterise (1) intratumour MIONP distribution, (2) effects of variable thermal dose mNPH (fixed AMF peak amplitude 24 kA/m at 160 ± 5 kHz) with/without RT (5 Gy), (3) effects of RT (RT5: 5 Gy; RT8: 8 Gy), and (4) fixed thermal dose mNPH (43 °C for 20 min) with/without RT (5 Gy). MIONP concentration and distribution were assessed following sacrifice and tissue harvest using inductively coupled plasma mass spectrometry (ICP-MS) and Prussian blue staining, respectively. Tumour growth was monitored and compared among treated groups. RESULTS: LAPC-4 tumours retained higher MIONP concentration and more uniform distribution than did PC3 tumours. AMF power modulation provided similar thermal dose for mNPH and combination therapy groups (CEM43: LAPC-4: 33.6 ± 3.4 versus 25.9 ± 0.8, and PC3: 27.19 ± 0.7 versus 27.50 ± 0.6), thereby overcoming limitations of MIONP distribution and yielding statistically significant tumour growth delay. CONCLUSION: PC3 and LAPC-4 tumours represent two biological models that demonstrate different patterns of nanoparticle retention and distribution, offering a model to make comparisons of these effects for mNPH. Modulating power for mNPH offers potential to overcome limitations of MIONP distribution to enhance mNPH.

Motion tracking in infrared imaging for quantitative medical diagnostic applications.

In medical applications, infrared (IR) thermography is used to detect and examine the thermal signature of skin abnormalities by quantitatively analyzing skin temperature in steady state conditions or its evolution over time, captured in an image sequence. However, during the image acquisition period, the involuntary movements of the patient are unavoidable, and such movements will undermine the accuracy of temperature measurement for any particular location on the skin. In this study, a tracking approach using a template-based algorithm is proposed, to follow the involuntary motion of the subject in the IR image sequence. The motion tacking will allow to associate a temperature evolution to each spatial location on the body while the body moves relative to the image frame. The affine transformation model is adopted to estimate the motion parameters of the template image. The Lucas-Kanade algorithm is applied to search for the optimized parameters of the affine transformation. A weighting mask is incorporated into the algorithm to ensure its tracking robustness. To evaluate the feasibility of the tracking approach, two sets of IR image sequences with random in-plane motion were tested in our experiments. A steady-state (no heating or cooling) IR image sequence in which the skin temperature is in equilibrium with the environment was considered first. The thermal recovery IR image sequence, acquired when the skin is recovering from 60-s cooling, was the second case analyzed. By proper selection of the template image along with template update, satisfactory tracking results were obtained for both IR image sequences. The achieved tracking accuracies are promising in terms of satisfying the demands imposed by clinical applications of IR thermography.

Possibilities and limitations of the ART-Sample algorithm for reconstruction of 3D temperature fields and the influence of opaque obstacles.

The need for the measurement of complex, unsteady, three-dimensional (3D) temperature distributions arises in a variety of engineering applications, and tomographic techniques are applied to accomplish this goal. Holographic interferometry (HI), one of the optical methods used for visualizing temperature fields, combined with tomographic reconstruction techniques requires multi-directional interferometric data to recover the 3D information. However, the presence of opaque obstacles (such as solid objects in the flow field and heaters) in the measurement volume, prevents the probing light beams from traversing the entire measurement volume. As a consequence, information on the average value of the field variable will be lost in regions located in the shade of the obstacle. The capability of the ART-Sample tomographic reconstruction method to recover 3D temperature distributions both in unobstructed temperature fields and in the presence of opaque obstacles is discussed in this paper. A computer code for tomographic reconstruction of 3D temperature fields from 2D projections was developed. In the paper, the reconstruction accuracy is discussed quantitatively both without and with obstacles in the measurement volume for a set of phantom functions mimicking realistic temperature distributions. The reconstruction performance is optimized while minimizing the number of irradiation directions (experimental hardware requirements) and computational effort. For the smooth temperature field both with and without obstacles, the reconstructions produced by this algorithm are good, both visually and using quantitative criteria. The results suggest that the location and the size of the obstacle and the number of viewing directions will affect the reconstruction of the temperature field. When the best performance parameters of the ART-Sample algorithm identified in this paper are used to reconstruct the 3D temperature field, the 3D reconstructions with and without obstacle are both excellent, and the obstacle has little influence on the reconstruction. The results indicate that the ART-Sample algorithm can successfully recover instantaneous 3D temperature distributions in the presence of opaque obstacles with only 4 viewing directions.

Heat transfer model for deep tissue injury: a step towards an early thermographic diagnostic capability.

BACKGROUND: Deep tissue injury (DTI) is a class of serious lesions which develop in the deep tissue layers as a result of sustained tissue loading or pressure-induced ischemic injury. DTI lesions often do not become visible on the skin surface until the injury reaches an advanced stage, making their early detection a challenging task. THEORY: Early diagnosis leading to early treatment mitigates the progression of the lesion and remains one of the priorities in clinical care. The aim of the study is to relate changes in tissue temperature with key physiological changes occurring at the tissue level to develop criteria for the detection of incipient DTIs. METHOD: Skin surface temperature distributions of the damaged tissue were analyzed using a multilayer tissue model. Thermal response of the skin surface to a cooling stress, was computed for deep tissue inflammation and deep tissue ischemia, and then compared with computed skin temperature of healthy tissue. RESULTS: For a deep lesion situated in muscle and fat layers, measurable skin temperature differences were observed within the first five minutes of thermal recovery period including temperature increases between 0.25 °C to 0.9 °C during inflammation and temperature decreases between -0.2 °C to -0.5 °C during ischemia. CONCLUSIONS: The computational thermal models can explain previously published thermographic findings related to DTIs and pressure ulcers. It is concluded that infrared thermography can be used as an objective, non-invasive and quantitative means of early DTI diagnosis. VIRTUAL SLIDES: The virtual slides for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/1461254346108378.

The role of dynamic infrared imaging in melanoma diagnosis.

Melanoma incidence and the lifetime risk are increasing at an alarming rate in the United States and worldwide. In order to improve survival rates, the goal is to detect melanoma at an early stage of the disease. Accurate, sensitive and reliable quantitative diagnostic tools can reduce the number of unnecessary biopsies, the associated morbidity as well as the costs of care in addition to improving survival rates. The recently introduced quantitative dynamic infrared imaging system QUAINT measures differences in the infrared emission between healthy tissue and the lesion during the thermal recovery process after the removal of a cooling stress. Results from a clinical study suggest that the temperature of cancerous lesions is higher during the first 45-60 seconds of thermal recovery than the temperature of benign pigmented lesions. This small temperature difference can be measured by modern infrared cameras and serve as an indicator for melanoma in modern quantitative melanoma detectors.

Involuntary motion tracking for medical dynamic infrared thermography using a template-based algorithm.

In medical applications, Dynamic Infrared (IR) Thermography is used to detect the temporal variation of the skin temperature. Dynamic Infrared Imaging first introduces a thermal challenge such as cooling on the human skin, and then a sequence of hundreds of consecutive frames is acquired after the removal of the thermal challenge. As a result, by analyzing the temporal variation of the skin temperature over the image sequence, the thermal signature of skin abnormality can be examined. However, during the acquisition of dynamic IR imaging, the involuntary movements of patients are unavoidable, and such movements will undermine the accuracy of diagnosis. In this study, based on the template-based algorithm, a tracking approach is proposed to compensate the motion artifact. The affine warping model is adopted to estimate the motion parameter of the image template, and then the Lucas-Kanade algorithm is applied to search for the optimized parameters of the warping function. In addition, the weighting mask is also incorporated in the computation to ensure the robustness of the algorithm. To evaluate the performance of the approach, two sets of IR image sequences of a subject's hand are analyzed: the steady-state image sequence, in which the skin temperature is in equilibrium with the environment, and the thermal recovery image sequence, which is acquired after cooling is applied on the skin for 60 seconds. By selecting the target region in the first frame as the template, satisfactory tracking results were obtained in both experimental trials, and the robustness of the approach can be effectively ensured in the recovery trial.

SIMULATION OF DISCRETE BLOOD VESSEL EFFECTS ON THE THERMAL SIGNATURE OF A MELANOMA LESION.

The effect of the underlying blood vessel on the transient thermal response of the skin surface with and without a melanoma lesion is studied. A 3D computational model of the layers of the skin tissue with cancerous lesion was developed in COMSOL software package. Heat transfer in the skin layers and the lesion is governed by the Pennes bio-heat equation, while the blood vessel is modeled as fully developed pipe flow with constant heat transfer coefficient. The effect of various pertinent parameters, such as diameter of the blood vessel, lateral location of the blood vessel relative to the lesion, flow velocity of the blood, on the skin surface temperature distribution, have been studied in the paper. The results show significant influence of the underlying blood vessel on the temperature of the skin surface and lesion as well as on the surrounding healthy tissue. Thus, a need for development of evaluation criteria for detection of malignant lesions in the presence of blood vessels is is discussed.

Emerging technologies for the detection of melanoma: achieving better outcomes.

Every year around 2.5-3 million skin lesions are biopsied in the US, and a fraction of these - between 50,000 and 100,000 - are diagnosed as melanoma. Diagnostic instruments that allow early detection of melanoma are the key to improving survival rates and reducing the number of unnecessary biopsies, the associated morbidity, and the costs of care. Advances in technology over the past 2 decades have enabled the development of new, sophisticated test methods, which are currently undergoing laboratory and small-scale clinical testing. This review highlights and compares some of the emerging technologies that hold the promise of melanoma diagnosis at an early stage of the disease. The needs for detection at different levels (patient, primary care, specialized care) are discussed, and three broad classes of instruments are identified that are capable of satisfying these needs. Technical and clinical requirements on the diagnostic instruments are introduced to aid the comparison and evaluation of new technologies. White- and polarized-light imaging, spatial and spectroscopic multispectral methods, quantitative thermographic imaging, confocal microscopy, Optical Coherence Tomography (OCT), and Terahertz (THZ) imaging methods are highlighted in light of the criteria identified in the review. Based on the properties, possibilities, and limitations of individual methods, those best suited for a particular setting are identified. Challenges faced in development and wide-scale application of novel technologies are addressed.

HEAT TRANSFER MODEL AND QUANTITATIVE ANALYSIS OF DEEP TISSUE INJURY.

Deep tissue injuries (DTI) are serious lesions which may develop in deep tissue layers as a result of sustained tissue loading or ischemic injury. These lesions may not become visible on the skin surface until the injury reaches an advanced stage making their early detection a challenging task. Early diagnosis leading to early treatment mitigates the progression of lesion and remains one of the priorities in management. The aim of this study is to examine skin surface temperature distributions of damaged tissue and develop criteria for the detection of incipient DTI. A multilayer quantitative heat transfer model of the skin tissue was developed using finite element based software COMSOL Multiphysics. Thermal response of the skin surface was computed during deep tissue inflammation and deep tissue ischemia and then compared with that of healthy tissue. In the presence of a DTI, an increase of about 0.5°C in skin surface temperatures was noticed during initial phase of deep tissue inflammation, which was followed by a surface temperature decrease of about 0.2°C corresponding to persistent deep tissue ischemia. These temperature differences are large enough to be detected by thermographic imaging. This study, therefore, also enhances the understanding of the previously detected thermographic quantitative changes associated with DTI.

Thermal analysis of cancerous breast model.

Breast cancer is one of the most common and dangerous cancers. Subsurface breast cancer lesions generate more heat and have increased blood supply when compared to healthy tissue, and this temperature rise is mirrored in the skin surface temperature. The rise in temperature on the skin surface, caused by the cancerous lesion, can be measured noninvasively using infrared thermography, which can be used as a diagnostic tool to detect the presence of a lesion. However, its diagnostic ability is limited when image interpretation relies on qualitative principles. In this study, we present a quantitative thermal analysis of breast cancer using a 3D computational model of the breast. The COMSOL FEM software was used to carry out the analysis. The effect of various parameters (tumor size, location, metabolic heat generation and blood perfusion rate) on the surface temperature distribution (which can be measured with infrared thermography) has been analyzed. Key defining features of the surface temperature profile have been identified, which can be used to estimate the size and location of the tumor based on (measured) surface temperature data. In addition, we employed a dynamic cooling process, to analyze surface temperature distributions during cooling and thermal recovery as a function of time. In this study, the effect of the cooling temperature on the enhancement of the temperature differences between normal tissue and cancerous lesions is evaluated. This study demonstrates that a quantification of temperature distributions by computational modeling, combined with thermographic imaging and dynamic cooling can be an important tool in the early detection of breast cancer.

CURVATURE EFFECT QUANTIFICATION FOR IN-VIVO IR THERMOGRAPHY.

Medical Infrared (IR) Imaging has become an important diagnostic tool over recent years. However, one underlying problem in medical diagnostics is associated with accurate quantification of body surface temperatures. This problem is caused by the artifacts induced by the curvature of objects, which leads to inaccurate temperature mapping and biased diagnostic results. Therefore, in our study, an experiment-based analysis is conducted to address the curvature effects toward the 3D temperature reconstruction of the IR thermography image. For quantification purposes, an isothermal copper plate with flat surface, and a cylindrical metal container filled with water are imaged. For the flat surface, the tilting angle measured from camera axis was varied incrementally from 0° to 60 °, such that the effects of surface viewing angle and travel distance on the measured temperature can be explored. On the cylindrical curved surface, the points viewed from 0° to 90° with respect to the camera axis are simultaneously imaged at different temperature levels. The experimental data obtained for the flat surface indicate that both viewing angle and distance effects become noticeable for angles over 40 °. The travel distance contributes a minor change when compared with viewing angle. The experimental results from the curved surface indicate that the curvature effect becomes pronounced when the viewing angle is larger than 60 °. The measurement error on the curved surface is compared with the simulation using the non-dielectric model, and the normalized temperature difference relative to 0° viewing angle was analyzed at six temperature levels. These results indicate that the linear formula associated with directional emissivity is a reasonable approximation for the measurement error, and the normalized error curves change consistently with viewing angle at various temperatures. Therefore, the analysis in this study implies that the directional emissivity based on the non-dielectric model can be applied for the calibration of measurement error. The normalized error curve serves as a consistent basis to correct the measurement error due to curvature artifacts.

Quantitative visualization and detection of skin cancer using dynamic thermal imaging.

In 2010 approximately 68,720 melanomas will be diagnosed in the US alone, with around 8,650 resulting in death. To date, the only effective treatment for melanoma remains surgical excision, therefore, the key to extended survival is early detection. Considering the large numbers of patients diagnosed every year and the limitations in accessing specialized care quickly, the development of objective in vivo diagnostic instruments to aid the diagnosis is essential. New techniques to detect skin cancer, especially non-invasive diagnostic tools, are being explored in numerous laboratories. Along with the surgical methods, techniques such as digital photography, dermoscopy, multispectral imaging systems (MelaFind), laser-based systems (confocal scanning laser microscopy, laser doppler perfusion imaging, optical coherence tomography), ultrasound, magnetic resonance imaging, are being tested. Each technique offers unique advantages and disadvantages, many of which pose a compromise between effectiveness and accuracy versus ease of use and cost considerations. Details about these techniques and comparisons are available in the literature. Infrared (IR) imaging was shown to be a useful method to diagnose the signs of certain diseases by measuring the local skin temperature. There is a large body of evidence showing that disease or deviation from normal functioning are accompanied by changes of the temperature of the body, which again affect the temperature of the skin. Accurate data about the temperature of the human body and skin can provide a wealth of information on the processes responsible for heat generation and thermoregulation, in particular the deviation from normal conditions, often caused by disease. However, IR imaging has not been widely recognized in medicine due to the premature use of the technology several decades ago, when temperature measurement accuracy and the spatial resolution were inadequate and sophisticated image processing tools were unavailable. This situation changed dramatically in the late 1990s-2000s. Advances in IR instrumentation, implementation of digital image processing algorithms and dynamic IR imaging, which enables scientists to analyze not only the spatial, but also the temporal thermal behavior of the skin, allowed breakthroughs in the field. In our research, we explore the feasibility of IR imaging, combined with theoretical and experimental studies, as a cost effective, non-invasive, in vivo optical measurement technique for tumor detection, with emphasis on the screening and early detection of melanoma. In this study, we show data obtained in a patient study in which patients that possess a pigmented lesion with a clinical indication for biopsy are selected for imaging. We compared the difference in thermal responses between healthy and malignant tissue and compared our data with biopsy results. We concluded that the increased metabolic activity of the melanoma lesion can be detected by dynamic infrared imaging.

Heat transfer and bubble detachment in subcooled pool boiling from a downward-facing microheater array in a nonuniform electric field.

The effects of a nonuniform electric field on vapor bubble detachment and heat transfer in subcooled pool boiling from a microheater array are investigated. The heater array faced downward to simulate a -1 g gravity condition and to eliminate the dominant masking effect of the buoyancy force. Experiments were conducted at different subcooling levels for various wall temperatures and electric field magnitudes. A dielectric fluid, FC-72, was used as the working fluid at ambient pressure. The array of 3 x 3 independently controlled microheaters was maintained at constant temperature and the rate of heat transfer from each heater was measured. Bubble images were recorded using a high-speed camera. The electric field was applied between the horizontal downward-facing microheater array, which was grounded, and a spherical, off-axis electrode beneath it. Boiling heat transfer results with and without the electric field are presented in this study. In the absence of the nonuniform electric field, compared to the same bulk fluid temperature and wall superheat settings in the +1 g situation, a much larger primary bubble was formed on the heater array, due to the coalescence of the secondary bubbles that nucleated on the heater array. The vapor bubble remained on the heater array surface and no bubble detachment was observed. With the nonuniform electric field applied, bubbles were lifted and sheared off from the heater array surface. The electric field was able to break up the primary bubble into several smaller bubbles--considerably greater heat transfer enhancement was measured than under similar conditions in +1 g.