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Background Although many hair disorders can be readily diagnosed based on their clinical appearance, their progression and response to treatment are often difficult to monitor, particularly in quantitative terms. We introduce an innovative technique utilizing a smartphone and computerized image analysis to expeditiously and automatically measure and compute hair density and diameter in patients in real time. Methods A smartphone equipped with a dermatoscope lens wirelessly transmits trichoscopy images to a computer for image processing. A black-and-white binary mask image representing hair and skin is produced, and the hairs are thinned into single-pixel-thick fiber skeletons. Further analysis based on these fibers allows morphometric characteristics such as hair shaft number and diameters to be computed rapidly. The hair-bearing scalps of fifty participants were imaged to assess the precision of our automated smartphone-based device in comparison with a specialized trichometry device for hair shaft density and diameter measurement. The precision and operation time of our technique relative to manual trichometry, which is commonly used by hair disorder specialists, is determined. Results An equivalence test, based on two 1-sided t tests, demonstrates statistical equivalence in hair density and diameter values between this automated technique and manual trichometry within a 20% margin. On average, this technique actively required 24 seconds of the clinician's time whereas manual trichometry necessitated 9.2 minutes. Conclusion Automated smartphone-based trichometry is a rapid, precise, and clinically feasible technique which can significantly facilitate the assessment and monitoring of hair loss. Its use could be easily integrated into clinical practice to improve standard trichoscopy.

Background Basal cell carcinoma (BCC) is the most common skin cancer, which is highly damaging in its advanced stages. Computer-aided techniques provide a feasible option for early detection of BCC. However, automated BCC detection techniques immensely rely on handcrafting high-level precise features. Such features are not only computationally complex to design but can also represent a very limited aspect of the lesion characteristics. This paper proposes an automated BCC detection technique that directly learns the features from image data, eliminating the need for handcrafted feature design. Methods The proposed method is composed of 2 parts. First, an unsupervised feature learning framework is proposed which attempts to learn hidden characteristics of the data including vascular patterns directly from the images. This is done through the design of a sparse autoencoder (SAE). After the unsupervised learning, we treat each of the learned kernel weights of the SAE as a filter. Convolving each filter with the lesion image yields a feature map. Feature maps are condensed to reduce the dimensionality and are further integrated with patient profile information. The overall features are then fed into a softmax classifier for BCC classification. Results On a set of 1199 BCC images, the proposed framework achieved an area under the curve of 91.1%, while the visualization of learned features confirmed meaningful clinical interpretation of the features. Conclusion The proposed framework provides a non-invasive fast BCC detection tool that incorporates both dermoscopic lesional features and clinical patient information, without the need for complex handcrafted feature extraction.

Background/purpose: We present a method for calibrating low-cost digital dermoscopes that corrects for color and inconsistent lighting and also corrects for chromatic aberration. Chromatic aberration is a form of radial distortion that often occurs in inexpensive digital dermoscopes and creates red and blue halo-like effects on edges. Being radial in nature, distortions due to chromatic aberration are not constant across the image, but rather vary in both magnitude and direction. As a result, distortions are not only visually distracting but could also mislead automated characterization techniques. Methods: Two low-cost dermoscopes, based on different consumer-grade cameras, were tested. Color is corrected by imaging a reference and applying singular value decomposition to determine the transformation required to ensure accurate color reproduction. Lighting is corrected by imaging a uniform surface and creating lighting correction maps. Chromatic aberration is corrected using a secondorder radial distortion model. Results: Our results for color and lighting calibration are consistent with previously published results, while distortions due to chromatic aberration can be reduced by 42– 47% in the two systems considered. Conclusion: The disadvantages of inexpensive dermoscopy can be quickly substantially mitigated with a suitable calibration procedure.

A number of epidemiologic studies have suggested that exposure to polychlorinated biphenyls (PCB) and other organochlorine compounds (OCC) increase risk of cutaneous malignant melanoma (CMM). However, these studies have generally had no biologic measure of OCC exposure, and have been unable to control for sun exposure, the major known environmental risk factor for this disease. This preliminary study examined the relationship between OCC residues in plasma and risk of CMM adjusting for sun sensitivity and sun exposure. A case-control study of 80 CMM patients and 310 control subjects was conducted. Lifetime sun exposure information, along with data on pigmentation variables and sun sensitivity data was collected, along with a blood sample. Cases and controls were assayed for plasma levels of 14 PCB congeners and 11 organochlorine pesticide residues using gas chromatography. Strong associations were seen between risk of CMM and plasma levels of non-dioxin-like PCBs (Adjusted OR = 7.02; 95% CI: 2.30-21.43 for highest quartile) and several PCB congeners, organochlorine pesticides or metabolites. These associations persisted after control for sun sensitivity and sun exposure. Results from this investigation require independent confirmation in larger studies. However, they suggest that environmental factors other than UV radiation may play a role in genesis of CMM, and indicate that it may be productive to search for further agents which might increase risk.

Background: Our specific aim was to investigate whether the donation process hindered or ameliorated the bereavement process for organ donor families, specifically with regard to depression, post-traumatic stress and grief. Methods: Using the British Columbia Transplant Society (BCTS) database, we mailed packages to donor families who consented to and successfully proceeded to donate. Each package contained three standardized, validated questionnaires that included scales of depression, post-traumatic stress, and bereavement. We also included a newly designed questionnaire specific to the BCTS Donation Experience. Seventy-three completed packages were received and analyzed using multiple regression models. Our overall response rate was 46%. Results: The younger the deceased and the shorter the time elapsed since donation, the greater the strength of bereaved feelings reported by the donor families. If donor families felt there were negative aspects about the donation process, the more likely they were bothered by symptoms of post-traumatic stress. The more comforted donor families felt about donation, the less likely they were bothered by feelings of depression. Conclusions: Our data suggest that donation has a beneficial effect on the bereavement process.

Background/purpose: The Irregularity Index is a measure of border irregularity from pigmented skin lesion images. The measure attempts to quantify the degree of irregularity of the structural indentations and protrusions along a lesion border. A carefully designed study has shown that the parameters derived from the Irregularity Index were highly correlated with expert dermatologists’ notion of border shape. This paper investigates the predictive power of these parameters on a set of data with known histological diagnosis. Methods: A set of 188 pigmented skin lesions (30 malignant melanomas and 158 benign lesions) was selected for the study. Their images were segmented and their border shapes were analysed by the Irregularity Index, producing four border irregularity parameters. The predictive power of these four parameters was estimated by a series of statistical tests. Results: The mean values of the four border irregularity parameters were significantly different between the melanoma group and the benign lesion group. When using the four parameters to predict its disease status, the leave-oneout classification rate was 82.4%, and the area under the receiver operating characteristic curve was 0.77. A malignant melanoma was 8.9 times more likely to have an irregular border than a benign lesion. Conclusion: This study confirmed that border irregularity is an important clinical feature for the diagnosis of malignant melanoma. It also indicates that the computer-derived measures based on the Irregularity Index capture to certain extent the kind of irregularity which is exhibited by melanomas.