Yin and Yang of skin microbiota in "swimmer acne".

Cutibacterium acnes (C. acnes) is an organism implicated in the pathogenesis of acne. Despite regular immersion in antimicrobial chlorine, adolescent swimmers suffer from acne and tend to be resistant to standard therapies.

Effects of swimming on facial sebum in adolescents.

Swimmers often complain of dry skin, consistent with decreased skin sebum levels, and yet may also have acne, which is commonly related to elevated sebum levels. Sixteen adolescent swimmers with and without acne were enrolled to examine two markers of facial sebum levels before and after 1 hour of swimming. Swimmers with acne did not have significant decreases in their sebum levels or shine measurements after swimming, whereas swimmers without acne did.

Parametric Acne Severity (PAS) Score and Lesion Counts From Multi-Modality Facial Image Analysis Correlates Strongly with Investigator Assessment.

Variability in acne lesion counting and assessing global severity necessitates large sample sizes that increase trial costs. Lack of standardized measures for these outcomes precludes the conduct of meta-analyses needed to compare efficacy of acne treatments. The goal of this study was to evaluate objective measures of lesion counts and global severity using analysis of multimodal photography.

Quantitative measurement of skin surface oiliness and shine using differential polarized images.

Excess amounts of skin surface oil can lead to adverse psychological consequences. Grease-spot photometry-based techniques measure sebum production rate. However, besides being tedious, these measurements are influenced by contact area, applied pressure, and time of application.

Measuring acne using Coproporphyrin III, Protoporphyrin IX, and lesion-specific inflammation: an exploratory study.

Propionibacterium acnes: (P. acnes) produce Porphyrins; however, fluorescence measurement of Porphyrins from Ultraviolet-A (UVA) images has failed to establish a correlation. Acne clinical research and imaging has ignored the spectral excitation-emission characteristics and the exact pattern of the Porphyrins synthesized by P.

Auto-classification of acne lesions using multimodal imaging.

Differentiating inflammatory and non-inflammatory acne lesions and obtaining lesion counts is pivotal part of acne evaluation. Manual lesion counting has reliably demonstrated the clinical efficacy of anti-acne products for decades. However, maintaining assessment consistency within and across acne trials is an important consideration since lesion counting can be subjective to the individual evaluators, and the technique has not been rigorously standardized.

In vivo fluorescence lifetime tomography.

Local molecular and physiological processes can be imaged in vivo through perturbations in the fluorescence lifetime (FLT) of optical imaging agents. In addition to providing functional information, FLT methods can quantify specific molecular events and multiplex diagnostic and prognostic information. We have developed a fluorescence lifetime diffuse optical tomography (DOT) system for in vivo preclinical imaging.

Quantitative diffuse optical tomography for small animals using an ultrafast gated image intensifier.

The quantitative accuracy of fluorescence and bioluminescence imaging of small animals can be improved by knowledge of the in situ optical properties of each animal. Obtaining in situ optical property maps is challenging, however, due to short propagation distances, requirements for high dynamic range, and the need for dense spatial, temporal, and spectral sampling. Using an ultrafast gated image intensifier and a pulsed laser source, we have developed a small animal diffuse optical tomography system with multiple synthetic modulation frequencies up to >1 GHz.

Quantitative small animal fluorescence tomography using an ultrafast gated image intensifier.

Optical approaches to small animal in vivo molecular imaging provide high sensitivity, stable non-radioactive probes, and an extensive array of functional reporting strategies. However, quantitative whole body assays remain illusive. The quantitative accuracy of optical imaging is affected by the depth of the buried target and the heterogeneity of tissue optical properties.

Multi-spectral imaging and analysis for classification of melanoma.

Wavelengths in the visible spectrum are selected for multi-spectral trans-illumination imaging of the skin lesions using the Nevoscope. The multi-spectral image data is analyzed using crisp and fuzzy partitioning techniques for classification of melanoma. It is shown that the multi-spectral images add the lesion depth and structural information to the superficial lesion characteristics obtained from the surface illumination images and hence, improve the sensitivity and specificity of melanoma diagnosis.

Monte Carlo simulation of light-tissue interaction: three-dimensional simulation for trans-illumination-based imaging of skin lesions.

Three-dimensional, voxel-based, and wavelength-dependent skin lesion models are developed and simulated using Monte Carlo techniques. The optical geometry of the Nevoscope with trans-illumination is used in the simulations for characterizing the lesion thickness. Based on the correlation analysis between the lesion thickness and the diffuse reflectance, optical wavelengths are selected for multispectral imaging of skin lesions using the Nevoscope.

Multi-spectral image analysis and classification of melanoma using fuzzy membership based partitions.

The sensitivity and specificity of melanoma diagnosis can be improved by adding the lesion depth and structure information obtained from the multi-spectral, trans-illumination images to the surface characteristic information obtained from the epi-illumination images. Wavelet transform based bi-modal channel energy features obtained from the images are used in the analysis. Methods using both crisp and fuzzy membership based partitioning of the feature space are evaluated.

Classification of melanoma using tree structured wavelet transforms.

This paper presents a wavelet transform based tree structure model developed and evaluated for the classification of skin lesion images into melanoma and dysplastic nevus. The tree structure model utilizes a semantic representation of the spatial-frequency information contained in the skin lesion images including textural information. Results show that the presented method is effective in discriminating melanoma from dysplastic nevus.