Search results for "Skin Cancer"
showing 10 items of 108 documents
Body mass index and baseline platelet count as predictive factors in Merkel cell carcinoma patients treated with avelumab
2023
BackgroundMerkel cell carcinoma (MCC) is a rare and aggressive skin cancer, associated with a worse prognosis. The Immune Checkpoint Inhibitors (ICIs) avelumab and pembrolizumab have been recently approved as first-line treatment in metastatic MCC (mMCC). The clinical observation of improved outcomes in obese patients following treatment with ICIs, known as the “obesity paradox”, has been studied across many types of tumors. Probably due to the rarity of this tumor, data on mMMC patients are lacking.Patients and methodsThis is an observational, hospital-based, study to investigate the role of Body Mass Index (BMI) as predictive biomarker of ICI response in mMCC patients treated with aveluma…
CCL27 Signaling in the Tumor Microenvironment
2021
Chemokines are a group of small proteins which play an important role in leukocyte migration and invasion. They are also involved in the cellular proliferation and migration of tumor cells.Chemokine CCL27 (cutaneous T cell-attracting chemokine, CTACK) is mainly expressed by keratinocytes of the normal epidermis. It is well known that this chemokine plays an important role in several inflammatory diseases of the skin, such as atopic dermatitis, contact dermatitis, and psoriasis. Moreover, several studies have shown an association between CCL27 expression and a variety of neoplasms including skin cancer.In this chapter, we address the role of chemokine CCL27 in the tumor microenvironment in t…
Classification of Melanoma Lesions Using Sparse Coded Features and Random Forests
2016
International audience; Malignant melanoma is the most dangerous type of skin cancer, yet it is the most treatable kind of cancer, conditioned by its early diagnosis which is a challenging task for clinicians and dermatologists. In this regard, CAD systems based on machine learning and image processing techniques are developed to differentiate melanoma lesions from benign and dysplastic nevi using dermoscopic images. Generally, these frameworks are composed of sequential processes: pre-processing, segmentation, and classification. This architecture faces mainly two challenges: (i) each process is complex with the need to tune a set of parameters, and is specific to a given dataset; (ii) the…
Multispectral integral imaging acquisition and processing using a monochrome camera and a liquid crystal tunable filter
2012
This paper presents an acquisition system and a procedure to capture 3D scenes in different spectral bands. The acquisition system is formed by a monochrome camera, and a Liquid Crystal Tunable Filter (LCTF) that allows to acquire images at different spectral bands in the [480, 680]nm wavelength interval. The Synthetic Aperture Integral Imaging acquisition technique is used to obtain the elemental images for each wavelength. These elemental images are used to computationally obtain the reconstruction planes of the 3D scene at different depth planes. The 3D profile of the acquired scene is also obtained using a minimization of the variance of the contribution of the elemental images at each …
Combined treatment of epidermodysplasia verruciformis with etretinate and α-interferon*
1992
Epidermodysplasia verruciformis (EV) is an uncommon cutaneous disease in which a focal and genetically determined immunological impairment is associated with chronic human papilloma virus (HPV) infection. In sun-exposed areas, when an oncogenic HPV type is the agent, skin cancer may occur. The treatment of EV is difficult and often unsatisfactory; etretinate has been reported in some instances as effective in improving lesions. We report a typical case of EV with pityriasis versicolor-like lesions on the trunk and many flat, erythematous wart-like lesions on the face, dorsal areas of the hands and legs. We performed a treatment with etretinate (1 mg/kg/day for 6 weeks) and subsequently with…
Optical design improvement for noncontact skin cancer diagnostic device
2018
Multispectral diffuse reflectance imaging and autofluorescence photo-bleaching imaging are methods that have been investigated for use in skin disorder diagnostics. In response to the ever-increasing incidence of skin cancer in light skinned populations a new device has been designed incorporating both of these methods. The aim of the study was to create a device that is most efficient in terms of hardware and software parameters for the screening of malignant and benign skin lesions. A set of 525 nm, 630 nm and 980 nm LEDs were used to illuminate the skin area at three wavelengths [1] and a set of 405 nm LEDs were used to induce the skin autofluorescence [2]. For a more homogenous illumina…
Robustness, Stability, and Fidelity of Explanations for a Deep Skin Cancer Classification Model
2022
Skin cancer is one of the most prevalent of all cancers. Because of its being widespread and externally observable, there is a potential that machine learning models integrated into artificial intelligence systems will allow self-screening and automatic analysis in the future. Especially, the recent success of various deep machine learning models shows promise that, in the future, patients could self-analyse their external signs of skin cancer by uploading pictures of these signs to an artificial intelligence system, which runs such a deep learning model and returns the classification results. However, both patients and dermatologists, who might use such a system to aid their work, need to …
Image quality enhancement for skin cancer optical diagnostics
2017
The research presents image quality analysis and enhancement proposals in biophotonic area. The sources of image problems are reviewed and analyzed. The problems with most impact in biophotonic area are analyzed in terms of specific biophotonic task – skin cancer diagnostics. The results point out that main problem for skin cancer analysis is the skin illumination problems. Since it is often not possible to prevent illumination problems, the paper proposes image post processing algorithm – low frequency filtering. Practical results show diagnostic results improvement after using proposed filter. Along that, filter do not reduces diagnostic results’ quality for images without illumination de…
Generating Hyperspectral Skin Cancer Imagery using Generative Adversarial Neural Network
2020
In this study we develop a proof of concept of using generative adversarial neural networks in hyperspectral skin cancer imagery production. Generative adversarial neural network is a neural network, where two neural networks compete. The generator tries to produce data that is similar to the measured data, and the discriminator tries to correctly classify the data as fake or real. This is a reinforcement learning model, where both models get reinforcement based on their performance. In the training of the discriminator we use data measured from skin cancer patients. The aim for the study is to develop a generator for augmenting hyperspectral skin cancer imagery. peerReviewed
Do nonmelanoma skin cancers develop from extra-cutaneous stem cells?
2008
A hypothesis is presented that nonmelanoma skin cancers can develop from extra-cutaneous stem cells, and not exclusively from skin keratinocytes. This idea is supported by recent findings regarding the initiation of cancers in the digestive tract, and by a cancer stem cell model of a neoplasia. It is known that multipotent adult progenitor cells can trans-differentiate into very diverse cellular lineages and can be recruited to areas of profound tissue injury. In these settings, they might also initiate malignant transformation. Some epidemiological data and recent findings regarding mechanisms of wound healing indicate that skin cancers could also originate from bone marrow-derived or othe…