Proposal of thermal imaging application in photodynamic therapy—Preliminary report

Combined Application of Dual-Wavelength Fluorescence Monitoring and Contactless Thermometry during Photodynamic Therapy of Basal Cell Skin Cancer

The aim of the study was to assess the capabilities of combined application of dual-wavelength fluorescence visualization and contactless skin thermometry during photodynamic therapy monitoring (PDT) of basal cell cancer.

Monitoring PDT effects in basal cell carcinoma treatment using thermal imaging

BACKGROUND

One of the most frequent type of malignant skin lesion (almost 95 percent of all skin tumours) is basal cell carcinoma (BCC). It is often treated by radiotherapy using ionizing radiation as well by photodynamic therapy (PDT) which is a selective method directed only on cancer cells and well tolerated by patients.

MATERIALS AND METHODS

Eight male patients of the Department and Clinic of Internal Diseases, Angiology and Physical Medicine in Bytom, Medical University of Silesia, in Katowice, Poland suffering from basal cell carcinoma were monitored by thermovision during the photodynamic therapy. All lesions were diagnosed as superficial were confirmed by histopathological examination.

RESULTS

The dynamics of changes observed in the isotherm area during the therapy can provide physicians with additional information. The significant increase of observed isotherm area in comparison to the lesion area diagnosed by a physician was confirmed, which may be connected with the increased metabolism processes occurring in the tissue surrounded the lesion.

CONCLUSION

The obtained results based on the temperature gradient changes in the lesion vicinity area may bring some new information describing the range of biochemical and physiological processes occurring during photodynamic therapy.

Infrared Thermal Imaging as a Method of Improving Skin Graft Qualification Procedure and Skin Graft Survivability

BACKGROUND

Appropriate wound classification (evaluation of skin damage depth) is a key element in the first days after the burn injury. In this study, we used a thermovision system to evaluate the degree of burn wound shortly after injury and the regenerative process of engraftment of autologous split-thickness skin grafts (STSGs). The results were referenced to wound assessment made by a physician.

METHODS

Twenty-one patients with STSGs were included in the study. The analysis of the dependence between the assessment of burn depth obtained with the use of numeric models (thermovision examination) and clinical assessment by physicians was conducted. Computed tomography angiography (CTA) was performed.

RESULTS

The study demonstrated that thermovision images allowed physicians a deeper assessment of burns. Decrease in the temperature difference was observed in subsequent measurements. Temperature increase during normal graft healing was observed. Graft vascularization was confirmed by CTA.

CONCLUSION

Thermovision may be useful in assessment of the clinical condition of burn wounds and monitoring of wound healing progress.

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.