A lock-in thermal imaging setup for dermatological applications

Lateral heat flux reduction using a lock-in thermography compensation method

The naturally diffusive heat flow in solids often results in differences in surface temperatures. Active thermography (AT) exploits such differences to gain information on the internal structure, morphology, or geometry of technical components or biological specimens. In contrast to sound or light waves, thermal waves are lossy; consequently, it is difficult to interpret measured 2D temperature fields. Most AT evaluation methods are based on 1D approaches, and measured 3D heat fluxes are frequently not considered, which is why edges, small features, or gradients are often blurred. Herein, we present a method for reducing the local temperature gradients at feature areas and minimizing the induced lateral heat flux in optical lock-in thermography (LT) measurements through spatial- and temporal-structured heating. The vanishing lateral gradients convert the problem into a 1D problem, which can be adequately solved by the LT approach. The proposed compensation method can bypass the blind frequency of LT and make the inspection largely independent of the excitation frequency. Furthermore, the edge sharpness and separability of features are improved, ultimately improving the feature-detection efficiency.

Skin Cancer Detection Using Infrared Thermography: Measurement Setup, Procedure and Equipment

Infrared thermography technology has improved dramatically in recent years and is gaining renewed interest in the medical community for applications in skin tissue identification applications. However, there is still a need for an optimized measurement setup and protocol to obtain the most appropriate images for decision making and further processing. Nowadays, various cooling methods, measurement setups and cameras are used, but a general optimized cooling and measurement protocol has not been defined yet. In this literature review, an overview of different measurement setups, thermal excitation techniques and infrared camera equipment is given. It is possible to improve thermal images of skin lesions by choosing an appropriate cooling method, infrared camera and optimized measurement setup.

Dynamic thermal imaging for pigmented basal cell carcinoma and seborrheic keratosis

BACKGROUND

Clinical differentiation between pigmented basal cell carcinoma (BCC) and seborrheic keratosis (SK) can sometimes be difficult. Noninvasive diagnostic technologies, such as thermal imaging, can be helpful in these situations. This study explored the use of dynamic thermal imaging (DTI), which records thermal images after the application of external thermal stimuli (heat or cold) for the differential diagnosis of pigmented BCC and SK.

MATERIALS AND METHODS

Twenty-two patients with pigmented BCC and 15 patients with SK participated in this study. Dynamic thermal images of lesions (pigmented BCC or SK) and control sites (contralateral normal skin) were recorded after the heat and cold stimuli. Temperature changes in the region of interest (ROI) are plotted as a thermal response graph. After fitting an exponential equation to each thermal response graph, the rate constants were compared between groups (pigmented BCC versus control, SK versus control).

RESULTS

The thermal response graphs revealed that the average temperature of pigmented BCC showed faster thermal recovery to baseline than the control site. There was a significant difference in the rate constants of the fitted exponential equations between the pigmented BCCs and the control sites (p<.001). However, we did not find a significantly different thermal recovery pattern between SK lesions and control sites.

CONCLUSIONS

DTI can be used as a diagnostic tool for distinguishing pigmented BCC from SK by comparing thermal recovery patterns between target lesions (pigmented BCC or SK) and the control site.

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.

Application of dynamic thermal imaging in a photocarcinogenesis mouse model

INTRODUCTION

In clinical practice and experimental settings, cutaneous premalignant and malignant lesions are commonly diagnosed by histopathological biopsy. However, this technique is invasive and results in functional or cosmetic defects. Dynamic thermal imaging is a non-invasive technique that quantifies the infra-red (IR) radiation emitted by a subject after the introduction of external thermal stimuli (such as heat or cold).

METHODS

Forty hairless albino (Crl:SKH1-hr) mice were randomised to the control group or the experimental group. The experimental group was regularly irradiated with artificial ultraviolet. Clinical photographs, immunohistochemical staining and dynamic thermal imaging results of both groups were obtained.

RESULTS

As photocarcinogenesis proceeded, faster thermal recovery to basal temperature after heat stimuli was significant on dynamic thermal imaging. With histopathological correlations, it was possible to differentiate normal, premalignant and malignant cutaneous lesions according to thermal imaging results. CD 31 staining analysis showed that increased vasculature was the key change responsible for different thermal imaging results among photocarcinogenesis steps.

CONCLUSIONS

Dynamic thermal imaging is useful to differentiate normal, premalignant and malignant cutaneous lesions. Increased vasculature is the key change responsible for different thermal imaging results.