An Optimized Method for Skin Cancer Diagnosis Using Modified Thermal Exchange Optimization Algorithm.

Skin cancer is the most common cancer of the body. It is estimated that more than one million people worldwide develop skin cancer each year. Early detection of this cancer has a high effect on the disease treatment. In this paper, a new optimal and automatic pipeline approach has been proposed for the diagnosis of this disease from dermoscopy images. The proposed method includes a noise reduction process before processing for eliminating the noises. Then, the Otsu method as one of the widely used thresholding method is used to characterize the region of interest. Afterward, 20 different features are extracted from the image. To reduce the method complexity, a new modified version of the Thermal Exchange Optimization Algorithm is performed to the features. This improves the method precision and consistency. To validate the proposed method's efficiency, it is implemented to the American Cancer Society database, its results are compared with some state-of-the-art methods, and the final results showed the superiority of the proposed method against the others.

Ultra high-frequency ultrasound with seventy-MHz transducer in hair disorders: Development of a novel noninvasive diagnostic methodology.

BACKGROUND: Ultra high-frequency ultrasound (uHFUS) is a recently developed diagnostic technology. Despite its potential usefulness, no study has assessed its advantage in diagnosis and evaluation of hair disorders in comparison with other diagnostic methods. OBJECTIVES: To assess the practicability of uHFUS in diagnosing hair disorders and propose a diagnostic methodology. METHODS: Ultrasonographic images of scalp and forehead from patients with hair disorders (n = 103) and healthy controls (n = 40) were obtained by uHFUS and analyzed by both descriptive and numerical parameters. Furthermore, the data were compared with trichoscopic and histopathological findings. RESULTS: The pattern of inflammation and fibrosis, hair cycle abnormality, and the findings in subcutis were detected by uHFUS. Significant differences were noted in the numerical parameters associated with the number of hair shafts and follicles, hair diameters and their diversity, and dermal echogenicity in both cicatricial and non-cicatricial hair disorders. Findings in uHFUS were associated with those observed in trichoscopy and scalp biopsy but uHFUS was able to detect pathological findings associated with hair cycle, inflammation, fibrosis, and subcutaneous abnormalities, which are hardly assessable by trichoscopy. CONCLUSION: The findings of this study highlighted usefulness of uHFUS in diagnosing hair disorders, while overcoming the weaknesses and limitations of other diagnostic tools.

Diagnostic tools used for melanoma: A survey of Australian general practitioners and dermatologists.

BACKGROUND/OBJECTIVE: Diagnostic tools such as dermoscopy, sequential digital dermoscopy imaging (SDDI), total body photography (TBP) and automated diagnostic tools are available to assist in early melanoma diagnosis. The use, accessibility and barriers of dermoscopy have been well studied; however, there are few similar studies regarding SDDI, TBP and automated diagnostic tools. We aim to understand the use of these diagnostic aids amongst Australian general practitioners (GPs) and dermatologists. METHODS: Between June 2019 and January 2020, GPs and dermatologists across Australia were invited to participate in an online survey. Surveys were distributed through GP and dermatology organisations. RESULTS: A total of 227 survey responses were received, 175 from GPs and 52 from dermatologists. Amongst GPs, 44.6% worked in a skin cancer clinic. Dermoscopy was used at least occasionally by 98.9% of all GPs. SDDI was used by 93.6% of skin cancer GPs, 80.8% of dermatologists and 45.3% of generalist GPs. TBP was used or recommended by 77.1% of generalist GPs, 82.3% of skin cancer GPs and 86.5% of dermatologists. The most common barriers to the use of TBP were cost, limited accessibility, poor patient compliance, and time required for both patients and doctors. Very few clinicians reported using automated diagnostic tools. There was an interest in future diagnostic aids for melanoma in 88% of GPs and dermatologists. CONCLUSION: Dermoscopy, SDDI and TBP were commonly used by responding Australian skin cancer GPs and dermatologists in this survey. Automated diagnostic tools were not reported to be used routinely. Several barriers were identified for use of TBP.

Incorporation of dermoscopy improves inter-observer agreement among dermatopathologists in histologic assessment of melanocytic neoplasms.

Histopathologic assessment of melanocytic neoplasms is the current gold standard of diagnosis. However, there are well recognized limitations including inter-observer diagnostic discordance. This study aimed to determine if integrating dermoscopy with histopathology of melanocytic neoplasms impacts diagnosis and improves inter-observer agreement. We conducted a prospective cohort study in a pigmented lesion clinic. Consecutive melanocytic lesions were identified for biopsy based on atypical gross or dermoscopic features. Standardized immunohistochemistry and levels were ordered on each specimen. The cases were randomized. Three dermatopathologists blinded to the clinical impression assessed each lesion. The cases were then re-randomized and re-assessed with addition of gross clinical and dermoscopic images. Inter-rater reliability (IRR) using Fleiss' kappa statistic revealed an increase from 0.447 without to 0.496 with dermoscopy amongst all dermatopathologists. The kappa increased from 0.495 before to 0.511 with dermoscopy in separating high-grade atypia or melanoma from moderate atypia or less. In 16 of 136 cases, at least 2 of 3 dermatopathologists favored a diagnosis of melanoma only after dermoscopy. In total, the consensus grade of atypia changed in 24.3% (33/ 136) of cases thereby representing changes to excisional margins and patient follow up. This study is limited by the cohort size. Dermoscopy significantly impacts diagnosis and improves identification of early melanomas in high risk populations and improves inter-observer agreement.

Optical imaging guided- 'precision' biopsy of skin tumors: a novel approach for targeted sampling and histopathologic correlation.

Dermoscopy and reflectance confocal microscopy (RCM) are two noninvasive, optical imaging tools used to facilitate clinical diagnosis. A biopsy technique that produces exact correlation with optical imaging features is not previously reported. To evaluate the applications of a novel feature-focused 'precision biopsy' technique that correlates clinical-dermoscopy-RCM findings with histopathology. This was a prospective case-series performed during August 2017 and June 2019 at a tertiary care cancer. We included consecutive patients requiring a precise dermoscopy-RCM-histopathologic correlation. We performed prebiopsy dermoscopy and both wide probe and handheld RCM of suspicious lesions. Features of interest were isolated with the aid of paper rings and a 2 mm punch biopsy was performed in the dermoscopy- or RCM-highlighted area. Tissue was processed either en face or with vertical sections. One-to-one correlation with histopathology was obtained. Twenty-three patients with 24 lesions were included in the study. The mean age was 64.6 years (range 22-91 years); there were 16 (69.6%) males, 14 (58.3%) lesions biopsied were on head and neck region. We achieved tissue-conservation diagnosis in 100% (24/24), 13 (54.2%) were clinically equivocal lesions, six (25%) were selected for 'feature correlation' of structures on dermoscopy or RCM, and five (20.8%) for 'correlation of new/unknown' RCM features seen on follow-up. The precision biopsy technique described herein is a novel method that facilitates direct histopathological correlation of dermoscopy and RCM features. With the aids of optical imaging devices, accurate diagnosis may be achieved by minimally invasive tissue extraction.

In vivo imaging characterization of basal cell carcinoma and cutaneous response to high-dose ionizing radiation therapy: A prospective study of reflectance confocal microscopy, dermoscopy, and ultrasonography.

BACKGROUND: Radiation therapy (RT) is a treatment option for select skin cancers. The histologic effects of RT on normal skin or skin cancers are not well characterized. Dermoscopy, high-frequency ultrasonography (HFUS), and reflectance confocal microscopy (RCM) are noninvasive imaging modalities that may help characterize RT response. OBJECTIVES: To describe changes in the tumor and surrounding skin of patients with basal cell carcinoma (BCC) treated with RT. METHODS: The study was conducted between 2014 and 2018. Patients with biopsy-proven BCCs were treated with 42 Gy in 6 fractions using a commercially available brachytherapy device. Dermoscopy, HFUS, and RCM were performed before treatment and at 6 weeks, 3 months, and 12 months after RT. RESULTS: A total of 137 imaging assessments (RCM + dermoscopy + HFUS) were performed in 12 patients. BCC-specific features were present in 81.8%, 91%, and 17% of patients imaged with dermoscopy, RCM, and HFUS at baseline, respectively, before treatment. After treatment, the resolution of these features was noted in 33.4%, 91.7%, and 100% of patients imaged with the respective modalities. No recurrences were seen after a mean of 31.7 months of follow-up. LIMITATIONS: Small sample size and no histopathologic correlation. CONCLUSION: Dermoscopy and HFUS were not as reliable as RCM at characterizing BCC RT response.

Dermoscopic Findings in the Presurgical Evaluation of Basal Cell Carcinoma. A Prospective Study.

BACKGROUND: Surgery is the best treatment for basal cell carcinoma (BCC); however, incomplete excisions are possible. OBJECTIVE: Assessment of the accurateness of dermoscopy and clinical evaluation in the detection of borders of BCC and description of dermoscopic findings in clinically healthy tissue surrounding BCC. MATERIALS AND METHODS: Eighty-eight lesions with clinical dermoscopic diagnosis of BCC were examined clinically and dermoscopically, to delineate the correct site of surgical incision, demarcating the respective margins with colred dermographic pencils. Specific dermoscopic features were searched in the skin adjacent to the demarcated clinical margin. RESULTS: In 29 of 88 lesions, clinical and dermoscopic margins of the tumor coincided. In the remaining 59 (67%), 10 (16.9%) presented, in the lesion area identified under dermoscopy, classical criteria for BCC and 57 (96.6%) nonclassical criteria. Differences between clinical and dermoscopic margins were significantly more frequent in superficial BCCs (p = .006). The frequency was not significantly different (p = .85) in relation to body sites. CONCLUSION: Dermoscopy improves the identification of margins for surgical excision in BCC. The observation of nontraditional dermoscopic criteria of BCC, mainly pink-white areas and short telangiectasias in the area between clinically and dermoscopically detected margins, helps to define the actual tumoral margins and to achieve a really radical excision.

Dark pigmented lesions: Diagnostic accuracy of dermoscopy and reflectance confocal microscopy in a tertiary referral center for skin cancer diagnosis.

BACKGROUND: There is lack of studies on the diagnostic accuracy of dermoscopy and reflectance confocal microscopy (RCM) for dark pigmented lesions. OBJECTIVE: To assess the diagnostic accuracy of dermoscopy plus confocal microscopy for melanoma diagnosis of dark pigmented lesions in real life. METHODS: Prospective analysis of difficult dark lesions with clinical/dermoscopic suspicion of melanoma referred for RCM for further analysis. The outcome could be excision or dermoscopic digital follow-up. RESULTS: We included 370 clinically dark lesions from 350 patients (median age, 45 y). Because of the clinical/dermoscopic/RCM approach, we saved 129 of 213 unnecessary biopsies (specificity of 60.6%), with a sensitivity of 98.1% (154/157). The number needed to excise with the addition of RCM was 1.5 for melanoma diagnosis. LIMITATIONS: Single institution based; Italian population only. CONCLUSIONS: This study showed that RCM coupled with dermoscopy increases the specificity for diagnosing melanoma, and it helps correctly identify benign lesions. Our findings provide the basis for subsequent prospective studies on melanocytic neoplasms belonging to patients in different countries.

Segmentation of Intensity-Corrupted Medical Images Using Adaptive Weight-Based Hybrid Active Contours.

Segmentation accuracy is an important criterion for evaluating the performance of segmentation techniques used to extract objects of interest from images, such as the active contour model. However, segmentation accuracy can be affected by image artifacts such as intensity inhomogeneity, which makes it difficult to extract objects with inhomogeneous intensities. To address this issue, this paper proposes a hybrid region-based active contour model for the segmentation of inhomogeneous images. The proposed hybrid energy functional combines local and global intensity functions; an incorporated weight function is parameterized based on local image contrast. The inclusion of this weight function smoothens the contours at different intensity level boundaries, thereby yielding improved segmentation. The weight function suppresses false contour evolution and also regularizes object boundaries. Compared with other state-of-the-art methods, the proposed approach achieves superior results over synthetic and real images. Based on a quantitative analysis over the mini-MIAS and PH2 databases, the superiority of the proposed model in terms of segmentation accuracy, as compared with the ground truths, was confirmed. Furthermore, when using the proposed model, the processing time for image segmentation is lower than those when using other methods.

Trichoscopy of Alopecia Areata: Hair Loss Feature Extraction and Computation Using Grid Line Selection and Eigenvalue.

Recently, the hair loss population, alopecia areata patients, is increasing due to various unconfirmed reasons such as environmental pollution and irregular eating habits. In this paper, we introduce an algorithm for preventing hair loss and scalp self-diagnosis by extracting HLF (hair loss feature) based on the scalp image using a microscope that can be mounted on a smart device. We extract the HLF by combining a scalp image taken from the microscope using grid line selection and eigenvalue. First, we preprocess the photographed scalp images using image processing to adjust the contrast of microscopy input and minimize the light reflection. Second, HLF is extracted through each distinct algorithm to determine the progress degree of hair loss based on the preprocessed scalp image. We define HLF as the number of hair, hair follicles, and thickness of hair that integrate broken hairs, short vellus hairs, and tapering hairs.

Inequalities in the patterns of dermoscopy use and training across Europe: conclusions of the Eurodermoscopy pan-European survey.

BACKGROUND: Dermoscopy is a widely used technique, recommended in clinical practice guidelines worldwide for the early diagnosis of skin cancers. Intra-European disparities are reported for early detection and prognosis of skin cancers, however, no information exists about regional variation in patterns of dermoscopy use across Europe. OBJECTIVE: To evaluate the regional differences in patterns of dermoscopy use and training among European dermatologists. MATERIALS & METHODS: An online survey of European-registered dermatologists regarding dermoscopy training, practice and attitudes was established. Answers from Eastern (EE) versus Western European (WE) countries were compared and their correlation with their respective countries' gross domestic product/capita (GDPc) and total and government health expenditure/capita (THEc and GHEc) was analysed. RESULTS: We received 4,049 responses from 14 WE countries and 3,431 from 18 EE countries. A higher proportion of WE respondents reported dermoscopy use (98% vs. 77%, p<0.001) and training during residency (43% vs. 32%) or anytime (96.5% vs. 87.6%) (p<0.001) compared to EE respondents. The main obstacles in dermoscopy use were poor access to dermoscopy equipment in EE and a lack of confidence in one's skills in WE. GDPc, THEc and GHEc correlated with rate of dermoscopy use and dermoscopy training during residency (Spearman rho: 0.5-0.7, p<0.05), and inversely with availability of dermoscopy equipment. CONCLUSION: The rates and patterns of dermoscopy use vary significantly between Western and Eastern Europe, on a background of economic inequality. Regionally adapted interventions to increase access to dermoscopy equipment and training might enhance the use of this technique towards improving the early detection of skin cancers.

Number needed to biopsy ratio and diagnostic accuracy for melanoma detection.

BACKGROUND: The number needed to biopsy (NNB) ratio for melanoma diagnosis is calculated by dividing the total number of biopsies by the number of biopsied melanomas. It is the inverse of positive predictive value (PPV), which is calculated by dividing the number of biopsied melanomas by the total number of biopsies. NNB is increasingly used as a metric to compare the diagnostic accuracy of health care practitioners. OBJECTIVE: To investigate the association of NNB with the standard statistical measures of sensitivity and specificity. METHODS: We extracted published diagnostic accuracy data from 5 cross-sectional skin cancer reader studies (median [min-max] readers/study was 29 [8-511]). Because NNB is a ratio, we converted it to PPV. RESULTS: Four studies showed no association and 1 showed a negative association between PPV and sensitivity. All 5 studies showed a positive association between PPV and specificity. LIMITATIONS: Reader study data. CONCLUSIONS: An individual health care practitioner with a lower NNB is likely to have a higher specificity than one with a higher NNB, assuming they practice under similar conditions; no conclusions can be made about their relative sensitivities. We advocate for additional research to define quality metrics for melanoma detection and caution when interpreting NNB.

Vulval hidradenoma papilliferum: a clinical and dermoscopic study.

Hidradenoma papilliferum (HP) is a rare, slow-growing, benign adnexal tumour with apocrine differentiation. It usually affects the anogenital region in adult women and is clinically polymorphous, mimicking other benign or malignant neoformations. The dermoscopic features of vulval HP have not been reported yet. We report the clinical and dermoscopic features in a case series of histopathologically proven vulval HPs. Dermoscopy may be a useful tool for the diagnosis of vulval HP. To our knowledge, our paper represents the first report of dermoscopic findings in a series of vulval HPs in a multiracial population.

Computer algorithms show potential for improving dermatologists' accuracy to diagnose cutaneous melanoma: Results of the International Skin Imaging Collaboration 2017.

BACKGROUND: Computer vision has promise in image-based cutaneous melanoma diagnosis but clinical utility is uncertain. OBJECTIVE: To determine if computer algorithms from an international melanoma detection challenge can improve dermatologists' accuracy in diagnosing melanoma. METHODS: In this cross-sectional study, we used 150 dermoscopy images (50 melanomas, 50 nevi, 50 seborrheic keratoses) from the test dataset of a melanoma detection challenge, along with algorithm results from 23 teams. Eight dermatologists and 9 dermatology residents classified dermoscopic lesion images in an online reader study and provided their confidence level. RESULTS: The top-ranked computer algorithm had an area under the receiver operating characteristic curve of 0.87, which was higher than that of the dermatologists (0.74) and residents (0.66) (P < .001 for all comparisons). At the dermatologists' overall sensitivity in classification of 76.0%, the algorithm had a superior specificity (85.0% vs. 72.6%, P = .001). Imputation of computer algorithm classifications into dermatologist evaluations with low confidence ratings (26.6% of evaluations) increased dermatologist sensitivity from 76.0% to 80.8% and specificity from 72.6% to 72.8%. LIMITATIONS: Artificial study setting lacking the full spectrum of skin lesions as well as clinical metadata. CONCLUSION: Accumulating evidence suggests that deep neural networks can classify skin images of melanoma and its benign mimickers with high accuracy and potentially improve human performance.