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Fuzzy logic image analysis techniques were used to analyze three shades of blue (lavender blue, light blue, and dark blue) in dermoscopic images for melanoma detection. A logistic regression model provided up to 82.7% accuracy for melanoma discrimination for 866 images. With a support vector machines (SVM) classifier, lower accuracy was obtained for individual shades (79.9–80.1%) compared with up to 81.4% accuracy with multiple shades. All fuzzy blue logic alpha cuts scored higher than the crisp case. Fuzzy logic techniques applied to multiple shades of blue can assist in melanoma detection. These vector-based fuzzy logic techniques can be extended to other image analysis problems involving multiple colors or color shades.

Background Blue-gray ovoids (B-GOs), a critical dermoscopic structure for basal cell carcinoma (BCC), offer an opportunity for automatic detection of BCC. Due to variation in size and color, B-GOs can be easily mistaken for similar structures in benign lesions. Analysis of these structures could afford accurate characterization and automatic recognition of B-GOs, furthering the goal of automatic BCC detection. This study utilizes a novel segmentation method to discriminate B-GOs from their benign mimics. Methods Contact dermoscopy images of 68 confirmed BCCs with B-GOs were obtained. Another set of 131 contact dermoscopic images of benign lesions possessing B-GO mimics provided a benign competitive set. A total of 22 B-GO features were analyzed for all structures: 21 color features and one size feature. Regarding segmentation, this study utilized a novel sector-based, non-recursive segmentation method to expand the masks applied to the B-GOs and mimicking structures. Results Logistic regression analysis determined that blue chromaticity was the best feature for discriminating true B-GOs in BCC from benign, mimicking structures. Discrimination of malignant structures was optimal when the final B-GO border was approximated by a best-fit ellipse. Using this optimal configuration, logistic regression analysis discriminated the expanded and fitted malignant structures from similar benign structures with a classification rate as high as 96.5%. Conclusions Experimental results show that color features allow accurate expansion and localization of structures from seed areas. Modeling these structures as ellipses allows high discrimination of B-GOs in BCCs from similar structures in benign images.

Background—Basal cell carcinoma (BCC) is the most commonly diagnosed cancer in the United States. In this research, we examine four different feature categories used for diagnostic decisions, including patient personal profile (patient age, gender, etc.), general exam (lesion size and location), common dermoscopic (blue-gray ovoids, leaf-structure dirt trails, etc.), and specific dermoscopic lesion (white/pink areas, semitranslucency, etc.). Specific dermoscopic features are more restricted versions of the common dermoscopic features. Methods—Combinations of the four feature categories are analyzed over a data set of 700 lesions, with 350 BCCs and 350 benign lesions, for lesion discrimination using neural networkbased techniques, including Evolving Artificial Neural Networks and Evolving Artificial Neural Network Ensembles. Results—Experiment results based on ten-fold cross validation for training and testing the different neural network-based techniques yielded an area under the receiver operating characteristic curve as high as 0.981 when all features were combined. The common dermoscopic lesion features generally yielded higher discrimination results than other individual feature categories. Conclusions—Experimental results show that combining clinical and image information provides enhanced lesion discrimination capability over either information source separately. This research highlights the potential of data fusion as a model for the diagnostic process.

Background Pink blush is a common feature in basal cell carcinoma (BCC). A related feature, semitranslucency, appears as smooth pink or orange regions resembling skin color. We introduce an automatic method for detection of these features based on smoothness and brightness. We also introduce a neighborhood correction method for texture area correction. Methods Smoothness and brightness were analyzed over four bands: luminance, red, green, and blue, then merged using variance-based dynamic thresholding. Dermoscopic images of 100 biopsy-proven BCCs and 254 competitive benign mimics were used to train the algorithm. Sixteen color and texture features were extracted from the automatically detected areas. The confusion matrix for the algorithm showed 15 classification errors in the training set for the 354 images: three errors in the BCC set and 12 errors in the benign set. Results Logistic regression analysis on a separate 1024-image test set was able to achieve good separation of BCC from benign lesions with an area under the receiver operating characteristic curve (ROC) of 0.878 and 0.877 using manually-created and automatically-generated BCC border masks, respectively. Conclusion This pilot study indicates that automatic detection of semitranslucent and pink blush areas in BCC is feasible using colors and first-order texture statistics.

BACKGROUND/PURPOSE Computer-aided diagnosis of skin cancer requires accurate lesion segmentation, which must overcome noise such as hair, skin color variations, and ambient light variability. METHODS A biologically inspired geodesic active contour (GAC) technique is used for lesion segmentation. The algorithm presented here employs automatic contour initialization close to the actual lesion boundary, overcoming the 'sticking' at minimum local energy spots caused by noise artifacts such as hair. The border is significantly smoothed to mimic natural lesions. In addition, features that mimic biological parameters include spectral image subtraction and removal of peninsulas and inlets. Multiple boundary choices borders are created by parameter options used at different steps. These choices can allow future improvement over the basic default border. RESULTS The basic GAC algorithm was tested on 100 images (30 melanomas and 70 benign lesions), yielding a median XOR border error of 6.7%, comparable to the median inter-dermatologist XOR border error (7.4%), and lower than the gradient vector flow snake median XOR error of 14.2% on the same image set. On a difficult low-contrast border set of 1238 images, which included 350 non-melanocytic lesions, a median XOR error of 23.9% is obtained. CONCLUSION GAC techniques show promise in attaining the goal of automatic skin lesion segmentation.

Importance Bites from the brown recluse spider (BRS) can cause extreme pain. We propose cytokine release as a cause of the discomfort and a central mechanism through glial cell upregulation to explain measured pain levels and time course. Observations Twenty-three BRS bites were scored at a probable or documented level clinically, and an enzyme-linked immunosorbent assay was used to confirm the presence of BRS venom. The mean (SD) pain level in these cases 24 hours after the spider bite was severe: 6.74 (2.75) on a scale of 0 to 10. Narcotics may be needed to provide relief in some cases. The difference in pain level by anatomic region was not significant. Escalation observed in 22 of 23 cases, increasing from low/none to extreme within 24 hours, is consistent with a cytokine pain pattern, in which pain increases concomitantly with a temporal increase of inflammatory cytokines. Conclusions and Relevance These findings in BRS bites support the hypothesis of cytokine release in inflammatory pain. A larger series is needed to confirm the findings reported here. The extreme pain from many BRS bites motivates us to find better prevention and treatment techniques.

This is the first part of a two-part article on personal details revealed by the hand examination. Daily activities revealed by hand examination are the focus of Part 1, while personal details including nutrition and psychological assessment are presented in Part 2. These clues enable the examiner to discern hobbies, vocation, sporting activities, dietary information, and psychosocial information of the patient. We describe signs that may aid the clinician in determining these activities, enabling us to provide better patient care by establishing good patient rapport. Part 1, presented here, focuses on detection of visible traces on the hands of sporting activities, hobbies, and vocation. The patient through long familiarity may be oblivious to these features or may find them too insignificant to mention, yet they can provide meaningful social details for the physician.

Objective. To describe children’s consumption of sugar-sweetened beverages (SSBs) and 100% fruit juice (FJ), and identify factors that may reduce excessive consumption. Design. A total of 830 parents of young children completed a 36-item questionnaire at the pediatricians’ office. Results. Children consumed soda (62.2%), other SSBs (61.6%), and FJ (88.2%): 26.9% exceeded the American Academy of Pediatrics’ recommended daily FJ intake. 157 (18.9%) children consumed excessive calories (>200 kcal/d) from beverages (median = 292.2 kcal/d, range 203.8-2177.0 kcal/d). Risk factors for excessive calorie consumption from beverages were exceeding recommendations for FJ (odds ratio [OR] = 119.7, 95% confidence interval [CI] = 52.2-274.7), being 7 to 12 years old (OR = 4.3, 95%CI = 1.9-9.9), and having Medicaid insurance (OR = 2.6, 95%CI = 1.1-6.0). Parents would likely reduce beverage consumption if recommended by the physician (65.6%). Conclusions. About 1 in 5 children consumes excessive calories from soda, other SSBs and FJ, with FJ the major contributor.

Background. In dermoscopic images, multiple shades of pink have been described in melanoma without specifying location of these areas within the lesion.Objective. The purpose of this study was to determine the statistics for the presence of centrally and peripherally located pink melanoma and benign melanocytic lesions.Methods. Three observers, untrained in dermoscopy, each retrospectively analyzed 1290 dermoscopic images (296 melanomas (170in situand 126 invasive), 994 benign melanocytic nevi) and assessed the presence of any shade of pink in the center and periphery of the lesion.Results. Pink was located in the peripheral region in 14.5% of melanomas and 6.3% of benign melanocytic lesions, yielding an odds ratio of 2.51 (95% CI: 1.7–3.8,P<0.0001). Central pink was located in 12.8% of melanomas and 21.8% of benign lesions, yielding an odds ratio of 0.462 (95% CI: 0.67,P=0.204). Pink in melanomain situtended to be present throughout the lesion (68% of pink lesions). Pink in invasive melanoma was present in 17% of cases, often presenting as a pink rim.Conclusions. The presence of pink in the periphery or rim of a dermoscopic melanocytic lesion image provides an indication of malignancy. We offer the “pink rim sign” as a clue to the dermoscopic diagnosis of invasive melanoma.

We report an atypical course of a likely brown recluse spider bite in a 79-year-old male. The Rader scale and Loxosceles reclusa venom detection by ELISA provide supporting evidence for a loxoscelism diagnosis. Obtundation and myocardial infarction occurred following a drop in hemoglobin to 6.5g/dL. The rapid loss of blood volume was considered a significant etiologic factor for both the obtundation and myocardial infarction. The neurological symptoms reversed rapidly after packed red blood cell transfusion.

Blue-gray ovoids (B-GOs) are critical dermoscopic structures in basal cell carcinomas (BCCs) that pose a challenge for automatic detection. Due to variation in size and color, B-GOs can be easily mistaken for similar structures in benign lesions. Analysis of these structures could help further accomplish the goal of automatic BCC detection. This study introduces an efficient sector-based method for segmenting B-GOs. Four modifications of conventional region-growing techniques are presented: (i) employing a seed area rather than a seed point, (ii) utilizing fixed control limits determined from the seed area to eliminate re-calculations of previously-added regions, (iii) determining region growing criteria using logistic regression, and (iv) area analysis and expansion by sectors. Contact dermoscopy images of 68 confirmed BCCs having B-GOs were obtained. A total of 24 color features were analyzed for all B-GO seed areas. Logistic regression analysis determined blue chromaticity, followed by red variance, were the best features for discriminating B-GO edges from surrounding areas. Segmentation of malignant structures obtained an average Pratt's figure of merit of 0.397. The techniques presented here provide a non-recursive, sector-based, region-growing method applicable to any colored structure appearing in digital images. Further research using these techniques could lead to automatic detection of B-GOs in BCCs.

Black-spot poison ivy is an uncommon presentation of poison ivy (Toxicodendron) allergic contact dermatitis. A 78-year-old sought evaluation of a black spot present on her right hand amid pruritic vesicles. The presentation of a black spot on the skin in a clinical context suggesting poison ivy is indicative of black-spot poison ivy. Dermoscopy revealed a jagged, centrally homogeneous, dark brown lesion with a red rim. A skin sample was obtained and compared against a poison ivy standard using ultra-fast liquid chromatography-tandem mass spectrometry (UFLC-MS/MS). This finding confirmed the presence of multiple urushiol congeners in the skin sample. Black-spot poison ivy may be added to the list of diagnoses that show a specific dermoscopic pattern.

Black-spot poison ivy is an uncommon presentation of poison ivy (Toxicodendron) allergic contact dermatitis. A 78-year-old sought evaluation of a black spot present on her right hand amid pruritic vesicles. The presentation of a black spot on the skin in a clinical context suggesting poison ivy is indicative of black-spot poison ivy. Dermoscopy revealed a jagged, centrally homogeneous, dark brown lesion with a red rim. A skin sample was obtained and compared against a poison ivy standard using ultra-fast liquid chromatography-tandem mass spectrometry (UFLC-MS/MS). This finding confirmed the presence of multiple urushiol congeners in the skin sample. Black-spot poison ivy may be added to the list of diagnoses that show a specific dermoscopic pattern.

Photosensitivity to sitagliptin, a dipeptidyl peptidase-4 (DPP-4) inhibitor, is reported. No previous reports of photosensitivity to any DPP-4 inhibitors are known. Physical examination of the patient revealed edematous plaques confined to sun-exposed areas of the skin. An unusual finding in this case was the spongy sensation upon palpation of the plaques. Histopathology revealed parakeratosis and abundant eosinophils, supporting the clinical impression of cutaneous drug sensitivity. The eruption finally cleared, approximately two years after onset.

Photosensitivity to sitagliptin, a dipeptidyl peptidase-4 (DPP-4) inhibitor, is reported. No previous reports of photosensitivity to any DPP-4 inhibitors are known. Physical examination of the patient revealed edematous plaques confined to sun-exposed areas of the skin. An unusual finding in this case was the spongy sensation upon palpation of the plaques. Histopathology revealed parakeratosis and abundant eosinophils, supporting the clinical impression of cutaneous drug sensitivity. The eruption finally cleared, approximately two years after onset.

A significant seasonal correlation was recently shown for brown recluse spider activity. Vetter (2011) observed brown recluse spiders were submitted by the general public predominantly during April–October. For patients with suspected brown recluse spider bites (BRSB), we have observed the same seasonality. Among 45 cases with features consistent of a BRSB, 43 (95.6%) occurred during April–October. Both the Vetter study and our study serve to demonstrate seasonal activity for brown recluse spiders.

Scale-crust, also termed ''keratin crust'', appears as yellowish-to-tan scale on the skin's surface. It is caused by hyperkeratosis and parakeratosis in inflamed areas of squamous cell carcinoma in situ (SCCIS, Bowen's disease) and is a critical dermoscopy feature for detecting this skin cancer. In contrast, scale appears as a white-to-ivory detaching layer of the skin, without crust, and is most commonly seen in benign lesions such as seborrheic keratoses (SK). Distinguishing scale-crust from ordinary scale in digital dermoscopy images holds promise for early SCCIS detection and differentiation from SK. Reported here are image analysis techniques that best characterize scale-crust in SCCIS and scale in SK, thereby allowing accurate separation of these two dermoscopic features. Classification using a logistic regression operating on color features extracted from these digital dermoscopy structures can reliably separate SCCIS from SK.

To the Editor The study by Wolf et al1 highlights the low accuracy of smartphone applications for melanoma self-detection, and correctly concludes that these applications could harm patients by delaying melanoma treatment through incorrect diagnosis. The article also found 98% sensitivity with 30.4% specificity for pigmented lesion evaluation by store-and-forward teledermatology. We question whether the teledermatology results can be reproduced in a real-world setting.

Acanthosis nigricans (AN) is so closely linked with insulin resistance (IR) that it has been called a clinical surrogate for laboratory-determined hyperinsulinemia.1 The presence of AN can therefore indicate patients with IR, allowing implementation of interventions that may prevent progression to type 2 diabetes mellitus.2 We report 30 patients who presented with elevated body mass index (BMI, calculated as weight in kilograms divided by height in meters squared) to correlate IR with different AN physical findings.