Diagnosis Of Pigmented Skin Lesions Research Articles

DERMOSCOPIC FEATURES OF PIGMENTARY DISORDERS IN INDIAN SKIN : A PROSPECTIVE OBSERVATIONAL STUDY

Introduction : Several studies have shown dermoscopy as an easily accessible tool for assisting the noninvasive diagnosis of various general dermatological disorders. The present study was conducted to evaluate the use of dermoscopy for diagnosis of pigmented skin lesions. Methods:In this Observational & Analytical study after Multi-staged Random sampling 100 study subjects /Patients were selected having various pigmentary lesions which were later evaluated by dermoscope. All the photographs were captured using android mobile camera and dermlite DL4 hybrid dermoscope (both polarised and nonpolarized). Results: Among the 100 patients /participants studied, 40% were males &60 % were females with the range of age between 3 to 60 years . The most common pigmentary lesions found were melasma (20%), Vitiligo (12%) , pityriasis versicolor(10%) among other types. Conclusion: Dermoscopy may result in confirmation of clinical diagnosis, oftenavoiding the need for a skin biopsy. Appreciation of the post-treatment effect via dermoscopy oftenprecedes clinical improvement this is especially true of chronic relapsing, recalcitrant dermatoses like melasma, lichen planus pigmentosus (LPP), vitiligo, alopecias, etc.Explaining the natureof the disorder becomes easier by patients showing the lesionaldermoscopic image to the patient.

Design and validation of a new machine-learning-based diagnostic tool for the differentiation of dermatoscopic skin cancer images.

Skin cancer is the most common cancer in the United States. Current estimates are that one in five Americans will develop skin cancer in their lifetime. A skin cancer diagnosis is challenging for dermatologists requiring a biopsy from the lesion and histopathological examinations. In this article, we used the HAM10000 dataset to develop a web application that classifies skin cancer lesions. This article presents a methodological approach that utilizes dermoscopy images from the HAM10000 dataset, a collection of 10015 dermatoscopic images collected over 20 years from two different sites, to improve the diagnosis of pigmented skin lesions. The study design involves image pre-processing, which includes labelling, resizing, and data augmentation techniques to increase the instances of the dataset. Transfer learning, a machine learning technique, was used to create a model architecture that includes EfficientNET-B1, a variant of the baseline model EfficientNET-B0, with a global average pooling 2D layer and a softmax layer with 7 nodes added on top. The results of the study offer a promising method for dermatologists to improve their diagnosis of pigmented skin lesions. The model performs best in detecting melanocytic nevi lesions with an F1 score of 0.93. The F1 score for Actinic Keratosis, Basal Cell Carcinoma, Benign Keratosis, Dermatofibroma, Melanoma, and Vascular lesions was consecutively 0.63, 0.72, 0.70, 0.54, 0.58, and 0.80. We classified seven distinct skin lesions in the HAM10000 dataset with an EfficientNet model reaching an accuracy of 84.3%, which provides a promising outlook for further development of more accurate models.

Light-Dermo: A Lightweight Pretrained Convolution Neural Network for the Diagnosis of Multiclass Skin Lesions.

Skin cancer develops due to the unusual growth of skin cells. Early detection is critical for the recognition of multiclass pigmented skin lesions (PSLs). At an early stage, the manual work by ophthalmologists takes time to recognize the PSLs. Therefore, several "computer-aided diagnosis (CAD)" systems are developed by using image processing, machine learning (ML), and deep learning (DL) techniques. Deep-CNN models outperformed traditional ML approaches in extracting complex features from PSLs. In this study, a special transfer learning (TL)-based CNN model is suggested for the diagnosis of seven classes of PSLs. A novel approach (Light-Dermo) is developed that is based on a lightweight CNN model and applies the channelwise attention (CA) mechanism with a focus on computational efficiency. The ShuffleNet architecture is chosen as the backbone, and squeeze-and-excitation (SE) blocks are incorporated as the technique to enhance the original ShuffleNet architecture. Initially, an accessible dataset with 14,000 images of PSLs from seven classes is used to validate the Light-Dermo model. To increase the size of the dataset and control its imbalance, we have applied data augmentation techniques to seven classes of PSLs. By applying this technique, we collected 28,000 images from the HAM10000, ISIS-2019, and ISIC-2020 datasets. The outcomes of the experiments show that the suggested approach outperforms compared techniques in many cases. The most accurately trained model has an accuracy of 99.14%, a specificity of 98.20%, a sensitivity of 97.45%, and an F1-score of 98.1%, with fewer parameters compared to state-of-the-art DL models. The experimental results show that Light-Dermo assists the dermatologist in the better diagnosis of PSLs. The Light-Dermo code is available to the public on GitHub so that researchers can use it and improve it.

Noninvasive detection of the endogenous free radical melanin in human skin melanomas using electron paramagnetic resonance (EPR).

We explored the capability of low-frequency Electron Paramagnetic Resonance (EPR) to noninvasively detect melanin (a stable semiquinone free radical) in the human skin. As previous in vitro studies on biopsies suggested that the EPR signal from melanin was different when measured in skin melanomas or benign nevi, we conducted a prospective first-in-man clinical EPR study in patients with skin lesions suspicious of melanoma. EPR spectra were obtained using a spectrometer operating at 1GHz, with a surface coil placed over the area of interest. Two clinical studies were carried out: 1) healthy volunteers (n=45) presenting different skin phototypes; 2) patients (n=88) with skin lesions suspicious of melanoma (n=100) requiring surgical resection. EPR data obtained before surgery were compared with histopathology results. The method was not sensitive enough to measure differences in melanin content due to changes in skin pigmentation. In patients, 92% of the spectra were analyzable. The EPR signal of melanin was significantly higher (p<0.0001) in melanoma lesions (n=26) than that in benign atypical nevi (n=62). A trend toward a higher signal intensity (though not significant) was observed in high Breslow depth melanomas (a marker of skin invasion) than in low Breslow lesions. To date, no naturally occurring free radicals have been detected by low-frequency EPR systems adapted for clinical studies. Here, we demonstrated for the first time the ability of this technology to detect an endogenous free radical, opening new avenues for evaluating clinical EPR as a potential aid in the diagnosis of pigmented skin lesions.

Neural network classification system for pigmented skin neoplasms with preliminary hair removal in photographs

The article proposes a neural network classification system for pigmented skin neoplasms with a preliminary processing stage to remove hair from the images. The main difference of the proposed system is the use of the stage of preliminary image processing to identify the location of the hair and their further removal. This stage allows you to prepare dermatoscopic images for further analysis in order to carry out automated classification and diagnosis of pigmented skin lesions. Modeling was carried out using the MatLAB R2020b software package on clinical dermatoscopic images from the international open archive ISIC Melanoma Project. The proposed system made it possible to increase the recognition accuracy of pigmented skin lesion images in 10 diagnostically important categories up to 80.81%. The use of the proposed system for the recognition and classification of images of dermatoscopic pigmented lesions by specialists will make it possible to increase the diagnostic efficiency in comparison with methods of visual diagnosis, and will also allow starting treatment at an earlier stage of the disease, which directly affects the survival and recovery rates for patients.

Dermatofluoroscopy diagnostics in different pigmented skin lesions: Strengths and weaknesses

The melanin fluorescence of skin lesions is measurable with two-photon excitation, a process termed dermatofluoroscopy, which has shown a shift from the green spectra in benign melanocytic lesions to the red spectra in melanoma. This study addressed the question as to which kind of pigmented lesions can be correctly diagnosed as melanin-bearing malignant tumors. 476 pigmented lesions including 101 cutaneous melanomas were analyzed with dermatofluoroscopy, measuring the melanin fluorescence in a grid-like fashion with a separation of measurement points of 0.2mm. The results of the dermatofluoroscopy are presented as a diagnostic score with a cut-off score of ≥28 for the diagnosis of melanin-bearing malignant tumors, and were compared to the gold standard of histopathology. A highly significant difference (p<0.0001) between the diagnostic scores of different skin tumors was found. Dermatofluoroscopy scores showed the highest sensitivity for melanomas (92.1%). Interestingly, most pigmented basal cell carcinomas (BCCs, 88.9%) were diagnosed as melanin-bearing malignant tumors. A higher sensitivity for the correct diagnosis was observed in older patients (≥53 years, p=0.003), in patients with skin tanning (p=0.025), and in patients with freckles during childhood (p=0.046). Two-photon fluorescence is an innovative technique for the diagnosis of pigmented skin lesions, and shows a high sensitivity for detection of melanomas and pigmented BCCs.

Analysis of Collective Human Intelligence for Diagnosis of Pigmented Skin Lesions Harnessed by Gamification Via a Web-Based Training Platform: Simulation Reader Study.

BackgroundThe diagnosis of pigmented skin lesion is error prone and requires domain-specific expertise, which is not readily available in many parts of the world. Collective intelligence could potentially decrease the error rates of nonexperts.ObjectiveThe aim of this study was to evaluate the feasibility and impact of collective intelligence for the detection of skin cancer.MethodsWe created a gamified study platform on a stack of established Web technologies and presented 4216 dermatoscopic images of the most common benign and malignant pigmented skin lesions to 1245 human raters with different levels of experience. Raters were recruited via scientific meetings, mailing lists, and social media posts. Education was self-declared, and domain-specific experience was tested by screening tests. In the target test, the readers had to assign 30 dermatoscopic images to 1 of the 7 disease categories. The readers could repeat the test with different lesions at their own discretion. Collective human intelligence was achieved by sampling answers from multiple readers. The disease category with most votes was regarded as the collective vote per image.ResultsWe collected 111,019 single ratings, with a mean of 25.2 (SD 18.5) ratings per image. As single raters, nonexperts achieved a lower mean accuracy (58.6%) than experts (68.4%; mean difference=−9.4%; 95% CI −10.74% to −8.1%; P<.001). Collectives of nonexperts achieved higher accuracies than single raters, and the improvement increased with the size of the collective. A collective of 4 nonexperts surpassed single nonexperts in accuracy by 6.3% (95% CI 6.1% to 6.6%; P<.001). The accuracy of a collective of 8 nonexperts was 9.7% higher (95% CI 9.5% to 10.29%; P<.001) than that of single nonexperts, an improvement similar to single experts (P=.73). The sensitivity for malignant images increased for nonexperts (66.3% to 77.6%) and experts (64.6% to 79.4%) for answers given faster than the intrarater mean.ConclusionsA high number of raters can be attracted by elements of gamification and Web-based marketing via mailing lists and social media. Nonexperts increase their accuracy to expert level when acting as a collective, and faster answers correspond to higher accuracy. This information could be useful in a teledermatology setting.

DermoDeep-A classification of melanoma-nevus skin lesions using multi-feature fusion of visual features and deep neural network

The Scientific community has been developing computer-aided detection systems (CADs) for automatic diagnosis of pigmented skin lesions (PSLs) for nearly 30 years. Several works have addressed this issue and obtained encouraging results, however, there has not been much focus on the pre-processing step, determining the relevance of the features considered and how they may be important indicators of a lesion’s malignancy. To differentiate between nevus and melanoma skin lesions, the development of CAD system is a challenging task due to the use of inaccurate image processing techniques. In this paper, a new classification system is developed for PSLs known as DermoDeep through a fusion of multiple visual features and deep-neural-network approach. A new aggregation of visual features along with descriptors are extracted in a perceptual-oriented color space. Moreover, a new five-layer architecture based DermoDeep system is proposed. This DermoDeep system applied on 2800 region-of-interest (ROI) PSLs including 1400 nevus and 1400 malignant lesions. The classification accuracy of DermoDeep system is compared with the state-of-the-art methods and evaluated by the sensitivity (SE), specificity (SP) and area under the receiver operating characteristics (AUC) curve. The difference between AUC of DermoDeep is statistically significant compared to other techniques with AUC: 0.96 (p < 0.001), SE of 93% and SP of 95%. The obtained results demonstrate that the DermatDeep can be used to assist dermatologists during a screening process.

The HAM10000 dataset, a large collection of multi-source dermatoscopic images of common pigmented skin lesions

Training of neural networks for automated diagnosis of pigmented skin lesions is hampered by the small size and lack of diversity of available datasets of dermatoscopic images. We tackle this problem by releasing the HAM10000 (“Human Against Machine with 10000 training images”) dataset. We collected dermatoscopic images from different populations acquired and stored by different modalities. Given this diversity we had to apply different acquisition and cleaning methods and developed semi-automatic workflows utilizing specifically trained neural networks. The final dataset consists of 10015 dermatoscopic images which are released as a training set for academic machine learning purposes and are publicly available through the ISIC archive. This benchmark dataset can be used for machine learning and for comparisons with human experts. Cases include a representative collection of all important diagnostic categories in the realm of pigmented lesions. More than 50% of lesions have been confirmed by pathology, while the ground truth for the rest of the cases was either follow-up, expert consensus, or confirmation by in-vivo confocal microscopy.

COMMON PIGMENTED SKIN LESIONS

Objectives: The purpose of this study is; firstly, to study the histopathologicalspectrum of the pigmented skin lesions in the community, to signify that not all pigmented skinlesions are malignant melanomas; secondly, to assess the age-wise distribution of the commonpigmented skin lesions; and thirdly, to determine the commonly affected body sites by thesepigmented skin lesions. Study Design: Retrospective/Observational study. Setting: CharsadaTeaching Hospital affiliated with Jinnah Medical College Peshawar. Period: 100 consecutivecases with clinical diagnosis of pigmented skin lesion, starting in the year 2013. Methods: Inthis study, 100 consecutive surgical pathology cases with clinical diagnosis of pigmented skinlesion were retrieved from the archives of Charsada Teaching Hospital affiliated with JinnahMedical College Peshawar. All the specimens were incisional biopsies of skin, fixed in 10%formalin, embedded in paraffin, and stained with Hematoxylin and Eosin stains. Results: Onanalyzing 100 consecutive pigmented skin lesions (n=100) starting from the year 2013, it wasfound thatthe large majority of these lesions were benign. The most common pigmented skinlesion was melanocytic nevus. Moreover, majority of pigmented skin lesions were seen infemales. Seborrheic keratosis and malignant tumors, like basal cell carcinoma and squamouscell carcinomas, were more commonly seen in males in the 6th and 7th decades of life; whereas,dermatofibroma and post-inflammatory pigmentation were more common in females in the 4thand 5th decades of life. Overall, the pigmented skin lesions were more common in the 3rd, 4th, and5th decades of life with peak in the 4th decade. Skin of face was the most common site affectedby melanocytic nevi and malignant epidermal skin tumors. Conclusions: In conclusion, mostof the pigmented skin lesions are benign, encountered in the 4th decade of life, and commonlyaffect the skin of face. Also, most of the melanocytic nevi are encountered in females, whilemost of the malignant epidermal neoplasms are encountered in males affecting the skin of face.

PATTERN AND DISTRIBUTION

Objectives: The purpose of this study is; firstly, to study the histopathologicalspectrum of the pigmented skin lesions in the community, to signify that not all pigmented skinlesions are malignant melanomas; secondly, to assess the age-wise distribution of the commonpigmented skin lesions; and thirdly, to determine the commonly affected body sites by thesepigmented skin lesions. Study Design: Retrospective/Observational study. Setting: CharsadaTeaching Hospital affiliated with Jinnah Medical College Peshawar. Period: 100 consecutivecases with clinical diagnosis of pigmented skin lesion, starting in the year 2013. Methods: Inthis study, 100 consecutive surgical pathology cases with clinical diagnosis of pigmented skinlesion were retrieved from the archives of Charsada Teaching Hospital affiliated with JinnahMedical College Peshawar. All the specimens were incisional biopsies of skin, fixed in 10%formalin, embedded in paraffin, and stained with Hematoxylin and Eosin stains. Results: Onanalyzing 100 consecutive pigmented skin lesions (n=100) starting from the year 2013, it wasfound thatthe large majority of these lesions were benign. The most common pigmented skinlesion was melanocytic nevus. Moreover, majority of pigmented skin lesions were seen infemales. Seborrheic keratosis and malignant tumors, like basal cell carcinoma and squamouscell carcinomas, were more commonly seen in males in the 6th and 7th decades of life; whereas,dermatofibroma and post-inflammatory pigmentation were more common in females in the 4thand 5th decades of life. Overall, the pigmented skin lesions were more common in the 3rd, 4th, and5th decades of life with peak in the 4th decade. Skin of face was the most common site affectedby melanocytic nevi and malignant epidermal skin tumors. Conclusions: In conclusion, mostof the pigmented skin lesions are benign, encountered in the 4th decade of life, and commonlyaffect the skin of face. Also, most of the melanocytic nevi are encountered in females, whilemost of the malignant epidermal neoplasms are encountered in males affecting the skin of face.

Techniques and algorithms for computer aided diagnosis of pigmented skin lesions—A review

Abstract Computerized image analysis methods for dermoscopy are primarily of great interest and benefit, as it provides significant information about the lesion, which can be of pertinence for the clinicians and a stand-alone warning implement. Computer-based diagnostic systems require dedicated image processing algorithms to provide mathematical descriptions of the suspected regions, such systems hold a great potential in oncology. In this paper, we have performed a review of the state of art techniques used in computer-aided diagnostic systems, by giving the domain aspects of melanoma followed by the prominent techniques used in each of the steps. The steps include dermoscopic image pre-processing, segmentation, extraction and selection of peculiar features, and relegation of skin lesions. The paper also presents cognizance to judge the consequentiality of every methodology utilized in the literature, in addition to the corresponding results obtained in this perspective. The inadequacies and the future research directions are accentuated.

Atypical dermoscopic presentation of an acral congenital melanocytic nevus in an adult: parallel ridge pattern and its histologic correlation.

Acral melanoma is the most frequent subtype in the Asian and Mexican mestizo populations. Dermoscopy is a noninvasive diagnostic technique that helps the differential diagnosis of pigmented skin lesions on acral volar skin.We, herein, present a case of acral congenital melanocytic nevus with a parallel ridge dermoscopic pattern. Since the parallel ridge pattern in a melanocytic lesion of the acral skin is classically ascribed to melanoma, the present case can be definitely labeled as “atypical” and worth of being elucidated in its histopathological correlates.

PO-156: Pitfalls for diagnosis of pigmented skin lesions

PO-156: Pitfalls for diagnosis of pigmented skin lesions

Dermoscopic Findings for the Early Detection of Melanoma: An Analysis of 200 Cases

IntroductionDermoscopy is a complementary technique that has led to major advances in the diagnosis of pigmented skin lesions. The aim of this study was to describe the dermoscopic features of a series of melanomas and analyze the differences between melanomas in situ and invasive melanomas. Material and methodsWe retrospectively recorded epidemiological, clinical, histologic, and dermoscopic features of a series of 200 primary melanomas. We performed a descriptive and analytical study of the dermoscopic features identified. ResultsThe mean age of the patients was 63 years and there was a similar distribution of male and female patients. The most common histologic subtypes were superficial spreading melanoma (62.5%) and lentigo maligna (25.5%); 67% of the melanomas had a Breslow thickness of less than 1mm and 24.5% were melanomas in situ. Overall,the most common global dermoscopic features were the multicomponent pattern (33.5%), the reticular pattern (18%), and the nonspecific pattern (15.5%). The most common local features were structureless homogeneous areas (67.5%), white-blue structures (58%), an atypical pigmented network (55.5%), and irregularly distributed dots and globules (44%). The following features were more common in invasive melanomas than in melanomas in situ: blue, gray, red and white colors, multicomponent and homogeneous patterns, dots and globules, blue-white structures, homogeneous areas, a blue-white veil, white shiny structures, a reverse pigment network, and milky-red areas. The reticular pattern was more common in melanomas in situ. DiscussionThe use of dermoscopy has contributed to the early diagnosis of melanoma. The most common dermoscopic features of melanoma are multiple structures and colors (multicomponent pattern), an atypical reticular pattern (with wide, irregular meshes), and an absence of distinguishing features (nonspecific pattern) associated with the presence of vascular structures. ConclusionsDermoscopy facilitates the diagnosis of melanoma and could be useful for differentiating between melanoma in situ and invasive melanoma.

Computer-automated ABCD versus dermatologists with different degrees of experience in dermoscopy

Dermoscopy is a very useful and non-invasive technique for in vivo observation and preoperative diagnosis of pigmented skin lesions (PSLs) inasmuch as it enables analysis of surface and subsurface structures that are not discernible to the naked eye. The authors used the ABCD rule of dermoscopy to test the accuracy of melanoma diagnosis with respect to a panel of 165 PSLs and the intra- and inter-observer diagnostic agreement obtained between three dermatologists with different degrees of experience, one General Practitioner and a DDA for computer-assisted diagnosis (Nevuscreen(®), Arkè s.a.s., Avezzano, Italy). 165 Pigmented Skin Lesions from 165 patients were selected. Histopathological examination revealed 132 benign melanocytic skin lesions and 33 melanomas. The kappa statistic, sensitivity, specificity and predictive positive and negative values were calculated to measure agreement between all the human observers and in comparison with the automated DDA. Our results revealed poor reproducibility of the semi-quantitative algorithm devised by Stolz et al. independently of observers' experience in dermoscopy. Nevuscreen(®) (Arkè s.a.s., Avezzano, Italy) proved to be 'user friendly' to all observers, thus enabling a more critical evaluation of each lesion and representing a helpful tool for clinicians without significant experience in dermoscopy in improving and achieving more accurate diagnosis of PSLs.

Hallazgos dermoscópicos para la detección precoz del melanoma. Análisis de 200 casos

IntroductionDermoscopy is a complementary technique that has led to major advances in the diagnosis of pigmented skin lesions. The aim of this study was to describe the dermoscopic features of a series of melanomas and analyze the differences between melanomas in situ and invasive melanomas. Material and methodsWe retrospectively recorded epidemiological, clinical, histologic, and dermoscopic features of a series of 200 primary melanomas. We performed a descriptive and analytical study of the dermoscopic features identified. ResultsThe mean age of the patients was 63 years and there was a similar distribution of male and female patients. The most common histologic subtypes were superficial spreading melanoma (62.5%) and lentigo maligna (25.5%); 67% of the melanomas had a Breslow thickness of less than 1mm and 24.5% were melanomas in situ. Overall,the most common global dermoscopic features were the multicomponent pattern (33.5%), the reticular pattern (18%), and the nonspecific pattern (15.5%). The most common local features were structureless homogeneous areas (67.5%), white-blue structures (58%), an atypical pigmented network (55.5%), and irregularly distributed dots and globules (44%). The following features were more common in invasive melanomas than in melanomas in situ: blue, gray, red and white colors, multicomponent and homogeneous patterns, dots and globules, blue-white structures, homogeneous areas, a blue-white veil, white shiny structures, a reverse pigment network, and milky-red areas. The reticular pattern was more common in melanomas in situ. DiscussionThe use of dermoscopy has contributed to the early diagnosis of melanoma. The most common dermoscopic features of melanoma are multiple structures and colors (multicomponent pattern), an atypical reticular pattern (with wide, irregular meshes), and an absence of distinguishing features (nonspecific pattern) associated with the presence of vascular structures. ConclusionsDermoscopy facilitates the diagnosis of melanoma and could be useful for differentiating between melanoma in situ and invasive melanoma.

New diagnostic toll for the diagnosis of pigmented skin lesion via multispectral imaging

New diagnostic toll for the diagnosis of pigmented skin lesion via multispectral imaging

Dermoscopic features of cutaneous melanoma are associated with clinical characteristics of patients and tumours and with MC1R genotype

Several algorithms are available for the dermoscopic diagnosis of pigmented skin lesions. The MC1R gene is a key determinant of pigmentation characteristics that are established host-related melanoma risk factors. To investigate the association of dermoscopic features of sporadic cutaneous melanomas with clinical characteristics of patients and corresponding tumours and with genetic changes in the MC1R and BRAF genes. A total of 64 dermoscopic images of 62 patients were scored by ABCD rule and modified pattern analysis. Detailed patients' and melanomas' characteristics were collected. Patients were screened for germline MC1R variants and related melanomas for somatic V600 BRAF mutations. A lower total dermoscopic score (TDS) was observed in melanomas of patients with red hair (P = 0.019), due to reduced dermoscopic structures (P < 0.0001). Thicker melanomas showed higher TDS values (P = 0.021) due to sharper borders (P < 0.0001) and higher number of colors (P = 0.004). An atypical pigment network was prevalent in superficial spreading melanomas (P = 0.010), in individuals with dark skin (P = 0.043) and hair color (P = 0.001). An atypical vascular pattern was more frequent in nodular (P < 0.0001) and thick (P < 0.0001) melanomas, in individuals with skin type I-II (P = 0.037), blond or red hair color (P = 0.032) and blue or green eyes (P = 0.014). Melanomas of MC1R R carriers showed lower TDS value (P = 0.037), reduced dermoscopic structures (P = 0.001) and lower prevalence of atypical pigment network (P = 0.001). No differences were identified between BRAF-mutated or wild-type melanomas. We suggest a phenotypic/MC1R profile for melanoma patients and their tumours. Melanomas of MC1R R carriers show a significant lower TDS value, with reduced dermoscopic structures, and a lower prevalence of an atypical pigment network. Non-carriers of MC1R R variants develop melanomas dermoscopically characterized by an atypical pigment network which is prevalent in superficial spreading melanomas, in patients with dark complexion and less frequent in red-haired individuals.

Palpation as a useful diagnostic tool for skin lesions

Early identification and accurate diagnosis of malignant pigmented skin lesions is essential for effective management and cost containment. The aim was to investigate the additional value of tactile descriptive information from lesion palpation on the diagnostic accuracy of pigmented skin lesions by medical students using computer-driven learning. Sixth year medical students (n = 152) from the University of Adelaide were invited to participate in an online teaching module on pigmented skin lesions. Users were asked to describe, diagnose and manage 15 pigmented skin lesions in three separate case studies based on pertinent clinical history and visual images of the lesions. Tactile descriptive information was then provided and users were asked to reflect on their diagnosis and management. A total of 66 (43%) of the sixth year students successfully completed the online module. Diagnostic accuracy improved significantly with the provision of tactile descriptive information for seborrhoeic keratosis (p = 0.012), basal cell carcinoma (p = 0.001), squamous cell carcinoma (p = 0.02), and dysplastic naevi (p = 0.035). Tactile descriptive information was stated by 23% of medical students to be important in the clinical diagnosis of pigmented skin lesion. Students managed all malignant pigmented skin lesions with either appropriate biopsy or specialist referral. Palpation information about skin lesions offers useful information for improvement of diagnostic accuracy in an online computer learning setting for medical students.