Thermal signature of melanoma and non-melanoma skin cancers

González, Francisco; Castillo-Martínez, Claudio; Valdés‐Rodríguez, Rodrigo; Kolosovas-Machuca, Eleazar Samuel; Villela-Segura, Uriel; Moncada, Benjamín

doi:10.21611/qirt.2012.276

Cited by 11 publications

(11 citation statements)

References 13 publications

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“…Angiogenesis is the physiological process by which new blood vessels form from existing vessels to provide the necessary extra energy [45][46][47]. In conjunction with the increased energy requirements, melanoma skin lesions are thought to have a higher (∆ 2-4 K) temperature than the surrounding healthy skin [27,[48][49][50]. Therefore, IR imaging for melanoma skin lesions is based on the detection of new blood vessels and chemical changes associated with a tumour development and growth [42,51].…”

Section: Skin Cancer and Infrared Thermographymentioning

confidence: 99%

“…Other skin tumor types, such as basal cell carcinoma may form an encapsulating layer of involved cells which acts like a thermal insulator, resulting in a delayed thermoregulatory process [27,52]. Similarly, González et al [50] studied the vascularity of different skin lesions (melanoma and non-melanoma) and discovered that each cancer type has its own thermal signature.…”

Section: Skin Cancer and Infrared Thermographymentioning

confidence: 99%

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

Verstockt

Verspeek

Thiessen

et al. 2022

Sensors

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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.

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Section: Skin Cancer and Infrared Thermographymentioning

confidence: 99%

Section: Skin Cancer and Infrared Thermographymentioning

confidence: 99%

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

Verstockt

Verspeek

Thiessen

et al. 2022

Sensors

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“…Thermal imaging (66)(67)(68)(69)(70)(71)(72)(73)(74)(75)(76)(77) is the leading technique investigated in literature. Thermal cameras were used to obtain skin lesion features at steady-state (71,74,77) and in dynamic thermal conditions (66)(67)(68)(69)(70)(72)(73)(74)(75)(76)(77). In steady-state studies, thermal images were used to obtain temperature features of the investigated lesion, such as, pixels temperature profiles (74) and temperature difference between several type of lesions and the healthy surrounding skin (71).…”

Section: Thermal Measurementsmentioning

confidence: 99%

“…Thermal cameras were used to obtain skin lesion features at steady-state (71,74,77) and in dynamic thermal conditions (66)(67)(68)(69)(70)(72)(73)(74)(75)(76)(77). In steady-state studies, thermal images were used to obtain temperature features of the investigated lesion, such as, pixels temperature profiles (74) and temperature difference between several type of lesions and the healthy surrounding skin (71). Some authors suggested that the application of a cooling stress is essential to highlight malignancy: indeed, the thermal recovery of the lesion over time differs between malignant and benign tissues.…”

Section: Thermal Measurementsmentioning

confidence: 99%

Comparative Analysis of Diagnostic Techniques for Melanoma Detection: A Systematic Review of Diagnostic Test Accuracy Studies and Meta-Analysis

et al. 2021

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Melanoma has the highest mortality rate among skin cancers, and early-diagnosis is essential to maximize survival rate. The current procedure for melanoma diagnosis is based on dermoscopy, i.e., a qualitative visual inspection of lesions with intrinsic limited diagnostic reliability and reproducibility. Other non-invasive diagnostic techniques may represent valuable solutions to retrieve additional objective information of a lesion. This review aims to compare the diagnostic performance of non-invasive techniques, alternative to dermoscopy, for melanoma detection in clinical settings. A systematic review of the available literature was performed using PubMed, Scopus and Google scholar databases (2010-September 2020). All human, in-vivo, non-invasive studies using techniques, alternative to dermoscopy, for melanoma diagnosis were included with no restriction on the recruited population. The reference standard was histology but dermoscopy was accepted only in case of benign lesions. Attributes of the analyzed studies were compared, and the quality was evaluated using CASP Checklist. For studies in which the investigated technique was implemented as a diagnostic tool (DTA studies), the QUADAS-2 tool was applied. For DTA studies that implemented a melanoma vs. other skin lesions classification task, a meta-analysis was performed reporting the SROC curves. Sixty-two references were included in the review, of which thirty-eight were analyzed using QUADAS-2. Study designs were: clinical trials (13), retrospective studies (10), prospective studies (8), pilot studies (10), multitiered study (1); the remain studies were proof of concept or had undefined study type. Studies were divided in categories based on the physical principle employed by each diagnostic technique. Twenty-nine out of thirty-eight DTA studies were included in the meta-analysis. Heterogeneity of studies' types, testing strategy, and diagnostic task limited the systematic comparison of the techniques. Based on the SROC curves, spectroscopy achieved the best performance in terms of sensitivity (93%, 95% CI 92.8–93.2%) and specificity (85.2%, 95%CI 84.9–85.5%), even though there was high concern regarding robustness of metrics. Reflectance-confocal-microscopy, instead, demonstrated higher robustness and a good diagnostic performance (sensitivity 88.2%, 80.3–93.1%; specificity 65.2%, 55–74.2%). Best practice recommendations were proposed to reduce bias in future DTA studies. Particular attention should be dedicated to widen the use of alternative techniques to conventional dermoscopy.

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“…They tested their setup in 37 patients, achieving better results than using conventional diagnostic techniques [34]. Similarly, González et al [35] studied the vascularity of skin lesions and concluded that there is a characteristic thermal signature associated with each type of cancer. In previous work [36], [37], we presented a set of algorithms to detect cancerous skin lesions using the TRCs of the suspicious lesion and its surrounding tissue, measured after cooling.…”

Section: Introductionmentioning

confidence: 99%

An Instrument for Accurate and Non-Invasive Screening of Skin Cancer Based on Multimodal Imaging

et al. 2019

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We present an instrument based on commodity embedded hardware, that implements an automatic procedure for early skin-cancer screening using dynamic thermal imaging. The procedure leverages image segmentation in the visible range and real-time multimodal registration to compute the temperature recovery curve (TRC) of suspicious skin lesions using thermal infrared video. The instrument implements two algorithms that infer the malignancy of the lesion from the computed TRCs. The first algorithm assumes that the TRCs are deterministic and infers the malignancy from the distance between the TRC of the suspicious lesion and its surrounding skin, which is assumed to be healthy tissue. The second algorithm models the TRC of the lesion as a random process and uses detection theory to statistically infer its malignancy from the eigenfunctions and corresponding eigenvalues of its covariance function. We built a prototype of the instrument using a Raspberry Pi 3 model B+ board, which acquires a visible-range image of the lesion at the beginning of the procedure and performs image segmentation in 62ms. Operating on a 400 × 400-pixel region-of-interest within the infrared video, the board performs frame-by-frame multimodal image registration and generates the TRCs in real time at more than 37 frames per second, thus eliminating the need to store video data for off-line processing. The statistical detection algorithm, which yields the best results, runs in 1.07s at the end of the procedure, and achieves a sensitivity of 98% and a specificity of 95% on a dataset of 116 volunteer subjects.

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Thermal signature of melanoma and non-melanoma skin cancers

Cited by 11 publications

References 13 publications

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

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

Comparative Analysis of Diagnostic Techniques for Melanoma Detection: A Systematic Review of Diagnostic Test Accuracy Studies and Meta-Analysis

An Instrument for Accurate and Non-Invasive Screening of Skin Cancer Based on Multimodal Imaging

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