The Promise of Semantic Segmentation in Detecting Actinic Keratosis Using Clinical Photography in the Wild.

AK is a common precancerous skin condition that requires effective detection and treatment monitoring. To improve the monitoring of the AK burden in clinical settings with enhanced automation and precision, the present study evaluates the application of semantic segmentation based on the U-Net architecture (i.e., AKU-Net). AKU-Net employs transfer learning to compensate for the relatively small dataset of annotated images and integrates a recurrent process based on convLSTM to exploit contextual information and address the challenges related to the low contrast and ambiguous boundaries of AK-affected skin regions. We used an annotated dataset of 569 clinical photographs from 115 patients with actinic keratosis to train and evaluate the model. From each photograph, patches of 512 × 512 pixels were extracted using translation lesion boxes that encompassed lesions in different positions and captured different contexts of perilesional skin. In total, 16,488 translation-augmented crops were used for training the model, and 403 lesion center crops were used for testing. To demonstrate the improvements in AK detection, AKU-Net was compared with plain U-Net and U-Net++ architectures. The experimental results highlighted the effectiveness of AKU-Net, improving upon both automation and precision over existing approaches, paving the way for more effective and reliable evaluation of actinic keratosis in clinical settings.

Image Perceptual Similarity Metrics for the Assessment of Basal Cell Carcinoma.

Efficient management of basal cell carcinomas (BCC) requires reliable assessments of both tumors and post-treatment scars. We aimed to estimate image similarity metrics that account for BCC's perceptual color and texture deviation from perilesional skin. In total, 176 clinical photographs of BCC were assessed by six physicians using a visual deviation scale. Internal consistency and inter-rater agreement were estimated using Cronbach's α, weighted Gwet's AC2, and quadratic Cohen's kappa. The mean visual scores were used to validate a range of similarity metrics employing different color spaces, distances, and image embeddings from a pre-trained VGG16 neural network. The calculated similarities were transformed into discrete values using ordinal logistic regression models. The Bray-Curtis distance in the YIQ color model and rectified embeddings from the 'fc6' layer minimized the mean squared error and demonstrated strong performance in representing perceptual similarities. Box plot analysis and the Wilcoxon rank-sum test were used to visualize and compare the levels of agreement, conducted on a random validation round between the two groups: 'Human-System' and 'Human-Human.' The proposed metrics were comparable in terms of internal consistency and agreement with human raters. The findings suggest that the proposed metrics offer a robust and cost-effective approach to monitoring BCC treatment outcomes in clinical settings.

Methylprednisolone Plus Low-Dose Methotrexate for Bullous Pemphigoid-A Single Center Retrospective Analysis.

Monomodal systemic glucocorticoids remain the mainstay of treatment for bullous pemphigoid (BP). In this retrospective, single-arm study, we evaluated the feasibility (efficacy and tolerability) of the combination of methylprednisolone and low-dose (up to 12.5 mg/week) methotrexate (MP + MTX) for BP. At week 12, 53/55 (96.4%) patients initiated on MP + MTX during a five-year period (potential follow up time: ≥4 years) remained on treatment. At this time-point, BP remission was achieved in all compliant patients (including n = 24 cases of dipeptidyl peptidase-4 inhibitors-associated BP; 12-week remission rate: 100% [95% CI: 91.9-100.0%]; mean time to remission: 29.5 days, SEM: 2.3 days) at a mean cumulative MP dose to disease control of 678.4 mg (SEM = 49.4 mg). Eight patients relapsed during follow up (10.81 [95% CI: 5.16-21.72] relapses/100 person years, py), and seven manifested a severe adverse event (6.80 [95% CI: 3.00-14.28] severe adverse events/100 py); however, 73.4% (±7.9%) had suffered neither a relapse nor a SAE at the three-years follow up. Continuing low dose MP intake (≤8 mg/day) beyond week 12 in combination with MTX minimized the risk of a feasibility limiting event (p = 0.013). Conclusively, the combination of methylprednisolone with methotrexate is a promising, safe, and efficient modality for BP patients, which enables rapid glucocorticoid tapering.

Application of a burn scar assessment tool for the evaluation of visual scarring following immunocryosurgery for facial basal cell carcinoma

Background: The therapeutic interventions for basal cell carcinoma (BCC) impact facial cosmesis. Objectives: Our aim was to assess the aesthetic burden of facial BCC treatment by evaluating the extent of the tumour site visually based on clinical images before and after immunocryosurgery; a minimally invasive combination treatment of topical imiquimod and cryosurgery. Materials & Methods: A three-item (texture, height, colour) burn scar scale was independently applied by four physicians (two dermatologists and two plastic surgeons) on archival semi-standardized clinical images of facial BCC before and one year after immunocryosurgery. The score assessments were compared using non-parametric statistical tests; internal consistency (reliability) and inter-rater agreement were assessed using Cronbach's α and Gwet's AC2, respectively. Results: Images (before and one year after treatment) of 27 BCCs from 26 patients (15 males) were analysed. The reliability was good (α>0.80) for all items before surgery and for colour after surgery. The inter-rater agreement was acceptable (AC2>0.70) for all items except for height pre-treatment (AC2 = 0.482). Based on averaging of all raters, cosmesis improved significantly after treatment at all tumour sites (p<0.001, Wilcoxon signed ranks test). The main limitations of the study are the inclusion of cases from a single centre and its retrospective nature. Conclusion: The evaluated burn scar scale can be reliably used to compare the extent of the BCC site visually before therapy and after resultant scars have formed. In this way, the impact of therapeutic interventions on cosmesis (from tumour to scar) can be evaluated, particularly for less aggressive facial skin tumours, such as most BCC.

Characterizing Malignant Melanoma Clinically Resembling Seborrheic Keratosis Using Deep Knowledge Transfer.

Malignant melanomas resembling seborrheic keratosis (SK-like MMs) are atypical, challenging to diagnose melanoma cases that carry the risk of delayed diagnosis and inadequate treatment. On the other hand, SK may mimic melanoma, producing a 'false positive' with unnecessary lesion excisions. The present study proposes a computer-based approach using dermoscopy images for the characterization of SΚ-like MMs. Dermoscopic images were retrieved from the International Skin Imaging Collaboration archive. Exploiting image embeddings from pretrained convolutional network VGG16, we trained a support vector machine (SVM) classification model on a data set of 667 images. SVM optimal hyperparameter selection was carried out using the Bayesian optimization method. The classifier was tested on an independent data set of 311 images with atypical appearance: MMs had an absence of pigmented network and had an existence of milia-like cysts. SK lacked milia-like cysts and had a pigmented network. Atypical MMs were characterized with a sensitivity and specificity of 78.6% and 84.5%, respectively. The advent of deep learning in image recognition has attracted the interest of computer science towards improved skin lesion diagnosis. Open-source, public access archives of skin images empower further the implementation and validation of computer-based systems that might contribute significantly to complex clinical diagnostic problems such as the characterization of SK-like MMs.

A Guttate Psoriasis That Tends to Spare Three Tattoos: A Macrophage Liaison.

Induction of new psoriasis sites was reported in only a small amount of psoriasis patients undergoing tattooing, despite the intuitive belief that tattoo trauma might awaken the disease due to the isomorphic phenomenon of Koebner. In this case report, we discuss a patient who presented with a remarkable sparing of his three tattoo sites during a guttate psoriasis flare-up that was unrelated to tattooing. The spatial concordance of tattoo and psoriasis lesions was analyzed on clinical pictures of tattoo sites taken during the psoriasis episode. For the quantification of the spatial distribution of the psoriasis lesions, Voronoi diagrams were generated, and coefficients of variation and the two-sample t-test were employed to compare the distributions of Voronoi patch sizes in different settings. Compared to skin areas without tattoos, a tattoo introduced a higher variation in the sizes of the Voronoi patches centered around psoriasis lesions. Based on our findings, we would like to discuss the possible role of macrophages as the key cellular link in the complex pathophysiologic relationship between tattooing/tattoo and psoriasis. Taking into account the relationship of autophagy and psoriasis lesions, we propose the hypothesis that tattoos represent a "psoriasis-hostile" tissue environment pertained by a population of LAP active M2-polarized macrophages. Further clinical studies of the relationship of psoriasis lesions to the tattooed skin are needed and may provide important insights into the role of macrophages in the pathogenesis of psoriasis.

Advanced keratinocyte skin cancer is a tumor with considerable disease burden and aggressiveness.

In a 2013 study published in this Journal, Dacosta Byfield et al. used MediCare data to extract reliable estimations of the incidence (I = 6.16) and prevalence (P = 10.31) rates of advanced keratinocyte skin cancer (aKSC) per 100,000 US population. These data unmask a considerable disease burden of aKSC (tumor stages ≥ 3) compared to the corresponding projected SEER predictions in 2019 of all invasive cases (tumor stages ≥ 1). According to its incidence, aKSC ranks 19th out of 29 major SEER registered neoplasms and has an average disease duration of 1.67 years, which is the second shortest disease duration next only to pancreatic carcinoma. Furthermore, in support of the high disease aggressiveness of aKSC and using a calibration approach, we calculated a mortality estimate of 4.64 per 100,000 and a 5-year survival rate of 21.8% for this tumor, which corresponds to positions of 13th and 5th out of 29 cancers among the SEER tracked malignancies, respectively. Taken together, these data indicate a considerable disease burden and biologic aggressiveness of aKSC.

Variation of cultured skin microbiota in mothers and their infants during the first year postpartum.

BACKGROUND/OBJECTIVES: The establishment of newborn skin flora depends on the ongoing skin maturation and the existence of potential microbial colonizers within the environment of the infant during a period of intense mother-infant physical interaction. This longitudinal study assessed culturable skin bacteria in the mother-infant dyad during the first year of life. METHODS: A total of 17 mother-infant dyads were swabbed within 24 hours postpartum and at 3, 6, 9, and 12 months. Skin swabbing was performed on two anatomical areas per individual (mothers: chest-abdomen; infants: forehead-buttocks) and were incubated in five different solid culture media to optimize yield. Isolated bacterial species were identified to genus or species level using the API system (BioMeriéux, Marcy l'Etoile, France). RESULTS: A total of 444 microbial strains were isolated belonging to 22 genera: 6 "frequent" (isolated from > 5% samples: S aureus, Proteus, Klebsiella, Pseudomonas, Enterobacter, and Enterococcus) and 16 "infrequent." Isolated genera per individual peaked at 6 months postpartum for mothers and infants (P < 0.05). Enterobacter, Enterococcus, Klebsiella, and Pseudomonas isolation rates varied significantly as a function of sampling time contrary to the rather constant isolation rates of Proteus and S aureus. The rates of concordant isolation of the same microbial species within the mother-infant dyad tended to drop from birth to the end of the first year postpartum. CONCLUSIONS: Distinct variations in the isolation rates of skin commensals from specific anatomical sites of the mother-infant dyad indicate bidirectional microbial transmission. Increasing skin flora individuality of the growing infant was recorded, manifested by declining rates of concordant isolation of the same microbial species from mother and her infant.

Late fusion of deep and shallow features to improve discrimination of actinic keratosis from normal skin using clinical photography.

BACKGROUND: Actinic keratosis (AK) is a common premalignant skin lesion that can potentially progress to squamous cell carcinoma. Appropriate long-term management of AK requires close patient monitoring in addition to therapeutic interventions. Computer-aided diagnostic systems based on clinical photography might evolve in the future into valuable adjuncts to AK patient management. The present study proposes a late fusion approach of color-texture features (shallow features) and deep features extracted from pre-trained convolutional neural networks (CNN) to boost AK detection accuracy on clinical photographs. MATERIALS AND METHODS: System uses a sliding rectangular window of 50 × 50 pixels and a classifier that assigns the window region to either the AK or the healthy skin class. 6010 and 13 915 cropped regions of interest (ROI) of 50 × 50 pixels of AK and healthy skin, respectively, from 22 patients were used for system implementation. Different support vector machine (SVM) classifiers employing shallow or deep features and their late fusion using the max rule at decision level were compared with the McNemar test and Yule's Q-statistic. RESULTS: Support vector machine classifiers based on deep and shallow features exhibited overall competitive performances with complementary improvements in detection accuracy. Late fusion yielded significant improvement (6%) in both sensitivity (87%) and specificity (86%) compared to single classifier performance. CONCLUSION: The parallel improvement of sensitivity and specificity is encouraging, demonstrating the potential use of our system in evaluating AK burden. The latter might be of value in future clinical studies for the comparison of field-directed treatment interventions.

Brain activation during repeated imagining of chocolate consumption: a functional magnetic resonance imaging study.

OBJECTIVE: To assess brain activation during mental visualization of eating chocolate. DESIGN: Twenty-one subjects were included. FMRI was acquired with a single-shot, multislice, gradient echo-planar sequence, while subjects were performing two specific imaginary tasks. RESULTS: Activation of motor-associated brain areas was observed during both mental visualization tasks. Increased activation of the right dorsolateral prefrontal cortex, the thalamus, the postcentral gyrus and the left anterior cingulate cortex, and the precuneus was observed during imagining eating chocolate. CONCLUSIONS: Repeated imagination of chocolate consumption results in activation of brain areas associated with hedonic effects of food and satiety and inhibition of orexigenic areas.

A Case Series of Bowen's Disease Treated with the Combination of Cryosurgery and Ingenol Mebutate and Followed Up with Optical Coherence Tomography.

Bowen's disease (BD) is a relatively rare in situ squamous cell carcinoma (SCC) with a limited potential of becoming invasive. Ingenol mebutate (IM) was relatively successful for the treatment of BD lesions in small case series. Optical coherence tomography (OCT) is a promising method for the diagnosis of cutaneous keratinocytic carcinomas, including BD. Herein we report the treatment of BD with the combination of cryosurgery and IM and the application of OCT imagining in treatment monitoring. Patients treated within a period of 12 months are retrospectively compiled. Treatment consisted of a mild cryosurgery session (liquid N2, open spray, and 2 freeze-thaw cycles of 15 sec each) of a field including the BD lesion and a 0.5cm rim and IM application for 4 consecutive days starting at the cryosurgery day. Four patients (3 females; average age: 76.5 years) with 4 lesions (20-70mm maximal diameter; average 36.2mm) were included. Healing was excellent and no relapse was observed at 12 months' follow-up. Baseline OCT revealed a disarranged, thickened epidermis, while a normally layered epidermis overlying a hyperreflective dermis was present after treatment. Conclusively, the combination of cryosurgery followed by IM is a feasible, effective treatment for BD that should be evaluated in further studies.

Automatic discrimination of actinic keratoses from clinical photographs.

BACKGROUND AND OBJECTIVE: Actinic keratoses (AK) are common premalignant skin lesions that can progress to invasive skin squamous cell carcinoma (sSCC). The subtle accumulation of multiple AK in aging individuals increases the risk of sSCC development, and this underscores the need for efficient treatment and patient follow-up. Our objectives were to develop a method based on color texture analysis of standard clinical photographs for the discrimination of AK from healthy skin and subsequently to test the developed approach in the quantification of field-directed treatment interventions. METHODS: AK and healthy skin in clinical photographs of 22 patients were demarcated by experts and regions of interest (ROIs) of 50 × 50 pixels were cropped. The data set comprised 6010 and 13915 ROIs from AK and healthy skin, respectively. Color texture features were extracted using local binary patterns (LBP) or texton frequency histograms and evaluated employing a support vector machine (SVM) classifier. Classifier evaluation was performed using a leave-one-patient-out scheme in RGB, YIQ and CIE-Lab color spaces. The best configuration of the SVM model was tested using 157 AK and 216 healthy skin rectangular regions of arbitrary size. AK treatment outcome was evaluated in an additional group of eight patients with 32 skin lesions. RESULTS: The best configuration of the discrimination model was achieved by employing LBP color texture descriptors estimated from the Y and I components of the YIQ color space. The sensitivity and specificity of the SVM model were 80.1% and 81.1% at ROI level and 89.8% and 91.7% at region level, respectively. Based on the classifier results the quantitative AK reduction was 83.6%. CONCLUSIONS: It is important that patients with AK seek evaluation for treatment to reduce the risk of disease progression. Efficient patient follow-up and treatment evaluation require cost-effective and easy to use approaches. The proposed SVM discrimination model based on LBP color texture analysis renders clinical photography a practical, widely available and cost-effective tool for the evaluation of AK burden and treatment efficacy.

Evaluation of vermillion border descriptors and relevance vector machines discrimination model for making probabilistic predictions of solar cheilosis on digital lip photographs.

INTRODUCTION: Solar cheilosis (SC), a common precancer of the lower lip with a high potential to progress to invasive squamous cell carcinoma, presents with characteristic morphological vermillion-skin border alterations, like the border retraction. AIM: To determine robust macro-morphological descriptors of the vermillion border from non-standardized digital photographs and to exploit a probabilistic model for SC recognition in real clinical environments. METHODS: Lip borders of 150 individuals (75 SC patients, 75 non-SC controls) were quantified on the basis of the extent of vermillion retraction and the degree of border irregularity employing fractal features and type-P Fourier descriptors. Eight lip border quantifiers were evaluated in terms of their reliability and reproducibility. The probabilistic 'diagnostic' model was implemented using the relevance vector machine (RVM) algorithm. RESULTS: Picture acquisition contributes substantially to overall variability of lip border images; however, for the different lip descriptors 33% to 65% of border morphological variability is due to differences among individuals. Different camera operators or the use of cameras with different specifications did not affect significantly the extracted lip features. The proposed RVM probabilistic model yielded a high sensitivity and specificity of 94.6% and 96%, respectively. CONCLUSION: We explored the use of digital photography within the clinical routine setting to validate a probabilistic model for the assessment of lip conditions like SC. The proposed method opens new perspectives toward a cost effective, non-invasive monitoring of SC to support large scale epidemiological and interventional studies in different clinical environments.

Spatial fuzzy c-means algorithm with adaptive fuzzy exponent selection for robust vermilion border detection in healthy and diseased lower lips.

INTRODUCTION: Accurate lip contour identification is demanding since variations in color, form and surface texture, even in normal lips, introduce artifacts in non-adapted segmentation algorithms. Herein, a method for vermilion border detection and quantification in healthy and diseased lower lips is presented. AIM: To quantify the morphological irregularities of lower lip border, to validate its discriminative power in solar cheilosis diagnosis and to provide supportive tools toward, cost effective, non invasive, disease monitoring. MATERIALS: Segmentation algorithm for lower lip border was based on spatial fuzzy c-means clustering algorithm with adaptive selection of fuzzy exponent m. Lip features measuring morphological lip border deviations were estimated. The method of lip border extraction and quantitative description was evaluated in a gold standard set of 25 young volunteers without onset of lip diseases. Quantitative descriptors were evaluated in terms of correct classification rates in differentiating 30 healthy control cases from 41 patients with solar cheilosis and were further applied to quantify the therapeutic outcome after immunocryosurgery in eight patients with solar cheilosis. RESULTS: Adaptive estimation of fuzzy exponent m substantially boosted the segmentation quality in gold standard cases yielding quite smooth lip contours and uniformly low values of lip irregularity features. Discriminant analysis highlighted the distance between the extracted and modeled vermilion border as a feature with excellent diagnostic accuracy (sensitivity and specificity 98% and 93% respectively). Results on patients with solar cheilosis followed up after treatment with immunocryosurgery showed that proposed quantitative lip marker was able to trace the improvement of disease after treatment. CONCLUSION: Correct lip border recognition is the prerequisite for extracting essential morphological descriptors from lips with epithelial diseases like solar cheilosis. In this paper we presented an efficient method for the automatic identification and quantitative description of lower lip vermilion border morphology in health and disease using digital photography and image analysis techniques.

Graphical tools for network meta-analysis in STATA.

Network meta-analysis synthesizes direct and indirect evidence in a network of trials that compare multiple interventions and has the potential to rank the competing treatments according to the studied outcome. Despite its usefulness network meta-analysis is often criticized for its complexity and for being accessible only to researchers with strong statistical and computational skills. The evaluation of the underlying model assumptions, the statistical technicalities and presentation of the results in a concise and understandable way are all challenging aspects in the network meta-analysis methodology. In this paper we aim to make the methodology accessible to non-statisticians by presenting and explaining a series of graphical tools via worked examples. To this end, we provide a set of STATA routines that can be easily employed to present the evidence base, evaluate the assumptions, fit the network meta-analysis model and interpret its results.

Gray Hausdorff distance measure for medical image comparison in dermatology: Evaluation of treatment effectiveness by image similarity.

INTRODUCTION: In clinical dermatology, the stabilization of the overall skin condition can be in many cases the earliest qualitative measure of the effectiveness of the therapeutic intervention. Subjective image comparisons, that offer empirical 'qualitative' judgments of degrees of image similarities, are traditionally employed by the involved physicians. OBJECTIVES: To quantify, by means of an image similarity metric, the degree of stabilization of an expanding skin disease, and to identify the situation of 'no further change' of the skin condition of the patient, providing thus the physician with an early, objective measure of the efficacy of the used therapy. METHODS: For treatment assessment, a variant of gray Hausdorff distance metric was employed to compare images of lesional skin segments of a patient, taken at different time points during a therapeutic course. Prior to image comparison, an effective preprocessing scheme was adapted to constrain wide pose and light variations. The proposed similarity algorithm was tested on raw clinical image data sets of patients diagnosed with toxic epidermal necrolysis, a life-threatening condition with rapid evolution. Fine tuning of algorithm's parameters was optimized using Precision-Recall curves. RESULTS: Proposed image comparison method resulted in a high-degree of image similarity (about 96%) between pictures taken at second and fifth day of hospitalization. Current similarity results substantiate a significant agreement between the computer-treatment assessment, by means of image comparison, and the corresponding clinical experts' review of skin condition. CONCLUSION: Objective evidence of 'no further change' situation may provide (a) intuitive clinical decision support to dermatologists in assessing aggressive skin conditions, where the timely evaluation of treatment response is of vital importance and (b) a versatile end-point measure for corresponding therapeutic clinical trials.