Suitability of frequency modulated thermal wave imaging for skin cancer detection—A theoretical prediction

Portable, handheld, and affordable blood perfusion imager for screening of subsurface cancer in resource-limited settings

Existing procedures of screening subsurface cancers are either prohibitively resource-intensive and expensive or are unable to provide direct quantitative estimates of the relevant physiological parameters for accurate classification accommodating interpatient variabilities and overlapping clinical manifestations. Here, we introduce a handheld and inexpensive blood perfusion imager that provides a noninvasive in situ screening approach for distinguishing precancer, cancer, and normal scenarios by precise quantitative estimation of the localized blood circulation in the tissue over an unrestricted region of interest without any unwarranted noise in the data, augmented by machine learning–based classification. Clinical trials in minimally resourced settings have established the efficacy of the method in differentiating cancerous and precancerous stages of suspected oral abnormalities, as verified by gold-standard biopsy reports.

Precise information on localized variations in blood circulation holds the key for noninvasive diagnostics and therapeutic assessment of various forms of cancer. While thermal imaging by itself may provide significant insights on the combined implications of the relevant physiological parameters, viz. local blood perfusion and metabolic balance due to active tumors as well as the ambient conditions, knowledge of the tissue surface temperature alone may be somewhat inadequate in distinguishing between some ambiguous manifestations of precancer and cancerous lesions, resulting in compromise of the selectivity in detection. This, along with the lack of availability of a user-friendly and inexpensive portable device for thermal-image acquisition, blood perfusion mapping, and data integration acts as a deterrent against the emergence of an inexpensive, contact-free, and accurate in situ screening and diagnostic approach for cancer detection and management. Circumventing these constraints, here we report a portable noninvasive blood perfusion imager augmented with machine learning–based quantitative analytics for screening precancerous and cancerous traits in oral lesions, by probing the localized alterations in microcirculation. With a proven overall sensitivity >96.66% and specificity of 100% as compared to gold-standard biopsy-based tests, the method successfully classified oral cancer and precancer in a resource-limited clinical setting in a double-blinded patient trial and exhibited favorable predictive capabilities considering other complementary modes of medical image analysis as well. The method holds further potential to achieve contrast-free, accurate, and low-cost diagnosis of abnormal microvascular physiology and other clinically vulnerable conditions, when interpreted along with complementary clinically evidenced decision-making perspectives.

Near-infrared heating of skin to delineate non-melanoma skin cancer lesions: A pilot study

BACKGROUND

Surgical excision is a mainstay of treatment for non-melanoma skin cancer (NMSC); improving margin delineation can reduce the need for further monitoring/treatment. The objective of this pilot study was to determine if near-infrared radiation (NIR) application to skin causes visible changes in normal and NMSC skin, to help delineate margins.

MATERIALS/METHODS

Eleven biopsy-proven NMSC lesions were included. The skin was then heated under a 175W NIR heating bulb; margins were traced onto acetate film before and after heating. Lesions were then randomly assigned to excision based on pre- or post-heating margins. Composite images were generated by overlaying the heat and no-heat lesion contours. All specimens were sent for histopathology.

RESULTS

The range of closest margins in the control group was 2.0-3.0 mm with a median of 2.0 mm; the range in the intervention group was 4.0-9.0 mm with a median of 5.0 mm. Composite images showed larger heat contours when the initial lesion was larger. There was a statistically significant difference between the two groups. Overall, NIR light caused visible hyperaemia to skin, and more intense erythema to malignant skin lesions.

CONCLUSION

Near-infrared light may have use in an outpatient setting for skin cancer delineation, possibly reducing the rate of positive margins.

Numerical modelling of skin tumour tissue with temperature-dependent properties for dynamic thermography

Dynamic thermography has been clinically proven to be a valuable diagnostic technique for skin tumour detection as well as for other medical applications, and shows many advantages over static thermography. Numerical modelling of heat transfer phenomena in biological tissue during dynamic thermography can aid the technique by improving process parameters or by estimating unknown tissue parameters based on measurement data. This paper presents a new non-linear numerical model of multilayer skin tissue containing a skin tumour together with thermoregulation response of the tissue during the cooling-rewarming process of dynamic thermography. The thermoregulation response is modelled by temperature-dependent blood perfusion rate and metabolic heat generation. The aim is to describe bioheat transfer more realistically. The model is based on the Pennes bioheat equation and solved numerically using a subdomain BEM approach treating the problem as axisymmetrical. The paper includes computational tests for Clark II and Clark IV tumours, comparing the models using constant and temperature-dependent properties which showed noticeable differences and highlighted the importance of using a local thermoregulation model. Results also show the advantage of using dynamic thermography for skin tumour screening and detection at an early stage. One of the contributions of this paper is a complete sensitivity analysis of 56 model parameters based on the gradient of the surface temperature difference between tumour and healthy skin. The analysis shows that size of the tumour, blood perfusion rate, thermoregulation coefficient of the tumour, body core temperature and density and specific heat of the skin layers in which the tumour is embedded are important for modelling the problem, and so have to be determined more accurately to reflect realistic skin response of the investigated tissue, while metabolic heat generation and its thermoregulation are not.

Analysis of thyroid thermographic images for detection of thyroid tumor: An experimental-numerical study

Thermography is a developing and noninvasive medical imaging technique that can be used for diagnosis of body disorders based on temperature deviation from normal body temperature. This research investigates the feasibility of thermography method in conjunction with artificial neural networks (ANNs) for detection of thyroid tumors. For this purpose, first, a 3-D model of the healthy human neck is constructed based on patient-specific computed tomography (CT) images. This model is used for analyzing bio-heat transfer in the human neck. The healthy thyroid gland is considered as a heat source and generates heat according to its temporal temperature. Finite element results verify the thermography potential for detection of thyroid gland location and estimation of its butterfly shape on the neck thermogram. The numerical analysis is carried out on 35 models with varying thermo-physical parameters of the healthy thyroid gland, including heat generation and blood perfusion. The acquired thermograms are used to develop an ANN for correlating the thermo-physical parameters of the gland and temperature profile on the neck surface. In the next stage, dynamic thermal images are captured from 10 healthy and three cancerous human cases. The experimental thermal images are analyzed by the developed ANN and the corresponding thermo-physical parameters are obtained. Results show that the estimated heat generation values for the healthy cases are about 3000 Wm3 while it increases to more than 12 000 Wm3 for the cases with tumors. This significant variation confirms the potential of dynamic thermography in diagnosis of thyroid tumors.

Distinguishing melanocytic nevi from melanomas using static and dynamic infrared thermal imaging

BACKGROUND

The incidence rates of melanoma have risen to worrying levels over the last decade. Delayed diagnosis, due to faults on the detection stage, indicates the necessity of new aiding diagnosis techniques. Since metabolic activity is highly connected to neoplasia formation, a detection technique that focuses its results on vascular responses, as Infrared thermal (IRT), seems to be a viable option.

MATERIALS AND METHODS

Static and dynamic (cooling) thermal images of melanoma and melanocytic nevi lesions were collected and analysed to retrieve thermal parameters characteristic of this skin lesion types. The steady-state and dynamic variables were tested separately with different machine learning classifiers to verify whether the distinction of melanoma and nevi lesions was achievable.

RESULTS

The differentiation of both types of skin tumours was doable, achieving an accuracy of 84.2% and a sensitivity of 91.3% with the implementation of a learner based on support vector machines and an input vector composed by static variables.

CONCLUSION

The use of IRT for skin tumour classification is achievable, but some improvement is needed to raise the metrics of sensitivity and specificity. For future work, it is recommended the study of dynamic parameters for the classification of other types of skin neoplasia.

Dedicated tool to assess the impact of a rhetorical task on human body temperature

INTRODUCTION

Functional infrared thermal imaging is a method widely used in medicine, including analysis of the mechanisms related to the effect of emotions on physiological processes. The article shows how the body temperature may change during stress associated with performing a rhetorical task and proposes new parameters useful for dynamic thermal imaging measurements MATERIALS AND METHODS: 29 healthy male subjects were examined. They were given a rhetorical task that induced stress. Analysis and processing of collected body temperature data in a spatial resolution of 256×512pixels and a temperature resolution of 0.1°C enabled to show the dynamics of temperature changes. This analysis was preceded by dedicated image analysis and processing methods RESULTS: The presented dedicated algorithm for image analysis and processing allows for fully automated, reproducible and quantitative assessment of temperature changes and time constants in a sequence of thermal images of the patient. When performing the rhetorical task, the temperature rose by 0.47±0.19°C in 72.41% of the subjects, including 20.69% in whom the temperature decreased by 0.49±0.14°C after 237±141s. For 20.69% of the subjects only a drop in temperature was registered. For the remaining 6.89% of the cases, no temperature changes were registered CONCLUSIONS: The performance of the rhetorical task by the subjects causes body temperature changes. The ambiguous temperature response to the given stress factor indicates the complex mechanisms responsible for regulating stressful situations. Stress associated with the examination itself induces body temperature changes. These changes should always be taken into account in the analysis of infrared data.

Thermography-based blood flow imaging in human skin of the hands and feet: a spectral filtering approach

The determination of the relationship between skin blood flow and skin temperature dynamics is the main problem in thermography-based blood flow imaging. Oscillations in skin blood flow are the source of thermal waves propagating from micro-vessels toward the skin's surface, as assumed in this study. This hypothesis allows us to use equations for the attenuation and dispersion of thermal waves for converting the temperature signal into the blood flow signal, and vice versa. We developed a spectral filtering approach (SFA), which is a new technique for thermography-based blood flow imaging. In contrast to other processing techniques, the SFA implies calculations in the spectral domain rather than in the time domain. Therefore, it eliminates the need to solve differential equations. The developed technique was verified within 0.005-0.1 Hz, including the endothelial, neurogenic and myogenic frequency bands of blood flow oscillations. The algorithm for an inverse conversion of the blood flow signal into the skin temperature signal is addressed. The examples of blood flow imaging of hands during cuff occlusion and feet during heating of the back are illustrated. The processing of infrared (IR) thermograms using the SFA allowed us to restore the blood flow signals and achieve correlations of about 0.8 with a waveform of a photoplethysmographic signal. The prospective applications of the thermography-based blood flow imaging technique include non-contact monitoring of the blood supply during engraftment of skin flaps and burns healing, as well the use of contact temperature sensors to monitor low-frequency oscillations of peripheral blood flow.

Finite element modeling of haptic thermography: A novel approach for brain tumor detection during minimally invasive neurosurgery

Intraoperative Thermal Imaging (ITI) is a novel neuroimaging method that can potentially locate tissue abnormalities and hence improves surgeon's diagnostic ability. In the present study, thermography technique coupled with artificial tactile sensing method called "haptic thermography" is utilized to investigate the presence of an abnormal object as a tumor with an elevated temperature relative to the normal tissue in the brain. The brain tissue is characterized as a hyper-viscoelastic material to be descriptive of mechanical behavior of the brain tissue during tactile palpation. Based on a finite element approach, Magnetic Resonance Imaging (MRI) data of a patient diagnosed to have a brain tumor is utilized to simulate and analyze the capability of haptic thermography in detection and localization of brain tumor. Steady-state thermal results prove that temperature distribution is an appropriate outcome of haptic thermography for the superficial tumors while heat flux distribution can be used as an extra thermal result for deeply located tumors.