Perspective: Melanoma diagnosis and monitoring: Sunrise for melanoma therapy but early detection remains in the shade

Last revised 25 Jul 2016.Melanoma is one of the most dangerous forms of cancer. The five-year survival rate is 98% if it is detected early. However, this rate plummets to 63% for regional disease and 17% when tumors have metastasized, that is, spread to distant sites. Furthermore, the incidence of melanoma has been rising by about 3% per year, whereas the incidence of cancers that are more common is decreasing. A handful of targeted therapies have recently become available that have finally shown real promise for treatment, but for reasons that remain unclear only a fraction of patients respond long term. These drugs often increase survival by only a few months in metastatic patient groups before relapse occurs. More effective treatment may be possible if a diagnosis can be made when the tumor burden is still low. Here, an overview of the current state-of-the-art is provided along with an argument for newer technologies towards early point-of-care diagnosis of melanoma

Kinetics of 5-aminolevulinic acid-induced fluorescence in organ cultures of bronchial epithelium and tumor

Background: 5-Aminolevulinic acid (5-ALA)-induced protoporphyrin IX (PPIX) fluorescence improves the differentiation of tumor and normal tissue in the bladder, skin and brain. Objective: The kinetics of 5-ALA-induced protoporphyrin IX (PPIX) fluorescence in organ cultures of normal human bronchial epithelium and cocultures of bronchial epithelium and tumor have been studied. Methods: Cultured biopsies of bronchial epithelium were exposed for 5 or 15 min, or continuously to 5-ALA. PPIX fluorescence was quantified for up to 300 min by spectroscopy. Cocultures of normal bronchial epithelium and a non-small-cell lung cancer cell line (EPLC-32M1) were incubated with 5-ALA. Space-resolved fluorescence microscopy was used to quantify PPIX fluorescence kinetics in the tumor and normal epithelium. Results: In cultures of normal epithelium, PPIX fluorescence kinetics were shown to depend on the duration of exposure to 5-ALA. There was a trend to higher fluorescence intensities with longer exposure times. In cocultures of bronchial epithelium and tumor, increases of fluorescence intensity were significantly greater in the tumor. Best tumor/normal tissue fluorescence ratios were found between 110 and 160 min after exposure to 5-ALA. Conclusion: Data obtained in this coculture system of bronchial epithelium and tumor is valuable to optimize modalities of fluorescence bronchoscopy for the diagnosis of early bronchial carcinoma. Copyright (C) 2002 S. Karger AG, Basel

Smart embedded system for skin cancer classification

The very good results achieved with recent algorithms for image classification based on deep learning have enabled new applications in many domains. The medical field is one that can greatly benefit from these algorithms in order to help the medical professional elaborate on his/her diagnostic. In particular, portable devices for medical image classification are useful in scenarios where a full analysis system is not an option or is difficult to obtain. Algorithms based on deep learning models are computationally demanding; therefore, it is difficult to run them in low-cost devices with a low energy consumption and high efficiency. In this paper, a low-cost system is proposed to classify skin cancer images. Two approaches were followed to achieve a fast and accurate system. At the algorithmic level, a cascade inference technique was considered, where two models were used for inference. At the architectural level, the deep learning processing unit from Vitis-AI was considered in order to design very efficient accelerators in FPGA. The dual model was trained and implemented for skin cancer detection in a ZYNQ UltraScale+ MPSoC ZCU104 evaluation kit with a ZU7EV device. The core was integrated in a full system-on-chip solution and tested with the HAM10000 dataset. It achieves a performance of 13.5 FPS with an accuracy of 87%, with only 33k LUTs, 80 DSPs, 70 BRAMs and 1 URAM.info:eu-repo/semantics/publishedVersio

Multi-colour fluorescence imaging in connection with photodynamic therapy of delta-amino levulinic acid (ALA) sensitised skin malignancies

Abstract A system for multi-colour fluorescence imaging of tissue is described. The instrument is mainly developed for tissue diagnostics to identify and localise malignant tumours, but might also be useful for real-time monitoring of the therapeutic dose delivered during photodynamic therapy. In vivo examples from various malignant skin lesions following topical δ-amino levulinic acid (ALA) administration are presented. The diagnostic system utilises both characteristics of a fluorescent tumour marker, such as a porphyrin containing substance, and the native tissue autofluorescence to characterise the tissue. A dimensionless function of three or four simultaneously recorded fluorescence intensities is formed and an optimum-contrast image is calculated pixel-by-pixel