Diagnosis Of Basal Cell Carcinoma Research Articles

Basal cell carcinoma-a clinical indicator of immunosuppression.

Basal cell carcinoma (BCC) and squamous cell carcinoma (SCC) are skin-derived carcinomas. The literature strongly connects SCC with acquired immunosuppression. Current data regarding BCC's association with immunosuppressive comorbidities are vague. The primary objective of this study was to establish the correlations between BCC and immunosuppressive comorbidities of patients. Materials and methods: We conducted a retrospective cohort study on 275 patients with a histopathological proven diagnosis of BCC from October 2019 to October 2023. Demographic data, BCC characteristics, and patients' comorbidities were analyzed. Comorbidities were classified as non-immunosuppressant and immunosuppressant (primary and secondary immunodeficiencies). We recorded 292 BCCs from 275 patients (142 females, 133 males), with equally distributed skin phototypes. 66.44% of the BCCs were detected in patients with various comorbidities (p < 0.001), of which 81.44% had immunosuppressive comorbidities (p < 0.001). All the immunosuppressive comorbidities were secondary and included diabetes mellitus (47.55%), history of solid or hematogenous cancer in the last 5 years (26.57%), chronic kidney disease (8.39%), chronic infections (9.09%), and antirheumatic immunosuppressive therapies (8.39%) (p < 0.001). BCC patients with immunosuppressive comorbidities did not develop larger BCCs (p = 0.2577) or more aggressive subtypes (p = 0.4269) and BCC did not arise earlier in their life (p < 0.001). BCC on the nasal pyramid was frequent in cancer history patients (p = 0.008). The ulcerated form of BCC is more confined to patients with chronic kidney disease (p = 0.006). Multiple BCCs are more frequent in patients with secondary immunodeficiencies (p = 0.027). BCC represents a clinical indicator of secondary immunodeficiency. Further research should establish if cancer screening campaigns may be beneficial in BCC patients.

Exploring the Utilization of Imaging Modalities in the Diagnosis of Basal Cell Carcinoma: A Scoping Review.

Basal cell carcinoma (BCC) is a common skin cancer that occurs due to various genetic and environmental factors. Diagnosis is made by a combination of clinical appearance, biopsy, imaging, and histopathological analysis. This review describes the current array of imaging modalities available to physicians to aid in the diagnosis of BCC. It is important to stay up-to-date with improvements in diagnostic screening, and knowledge of these options is instrumental in providing the best care to patients. Embase, Medline Industries, and PubMed were searched for articles within the past 10 years based on a search query that looked for imaging modalities used in the diagnosis and evaluation of a variety of dermatologic conditions. The search was further refined to focus on BCC and satisfy the inclusion/exclusion criteria determined by the authors. The research process was detailed in the Preferred Reporting Items for Systematic Reviews and Meta-Analyses diagram. Dermoscopy is a non-invasive in vivo microscopic technique used to evaluate skin lesions. Features of dermoscopy cannot be visualized with the naked eye, and studies found that dermoscopy increased diagnostic accuracy. Reflectance confocal microscopy (RCM) examines skin morphology, and recent studies found that 100% of patients with BCC had tumor-free margins when diagnosed with RCM. It allows for a one-stop-shop for diagnosis. Optical spectroscopy samples multiple sites without removing tissue. It helps detect subtle biophysical differences, allowing for earlier diagnosis. High-frequency ultrasound (HFUS) helps determine tumor size, structure, depth of invasionand spread. Studies found statistically significant positive correlations between depth of spread and HFUS readings. Optical coherence tomography takes cross-sectional images to analyze histopathology and morphology. It produces high-resolution images, confers slightly more accurate results than a biopsy, and expedites the treatment process through an earlier diagnosis without a biopsy.These results will advance the fields of dermatology and radiology as they describe unique uses for these imaging modalities. There are a variety of ways to use microscopy, and these techniques may be applied to many different lesions and help revolutionize the diagnosis and treatment of skin cancer and other lesions without the need for multiple, sometimes disfiguring surgical procedures. With the increase in diagnostic accuracy and decrease in diagnosis time, advanced imaging studies will become an integral part of dermatologic diagnosis and be included in future management and treatment plans, especially in the case of BCC.

Fluorescence spectral analysis and logistic regression modeling for diagnosing basal cell carcinoma on head and neck

The optical fluorescence method is distinguished by key features such as non-invasiveness, high sensitivity, and resolution, which are superior to traditional diagnostic approaches. Unlike histopathological examinations and biochemical analyses, optical diagnostic methods obviate the need for tissue sampling, enabling the analysis of virtually unlimited material.The research aims to examine the effectiveness of emission spectra analysis in the diagnosis of basal cell carcinoma (BCC) of the scalp and neck. The analysis was based on data provided by Specialized Hospital No. 2 in Bytom comprising a study sample of 10 patients. For each patient, fluorescence emission spectra were recorded from each of 512 points along a 5 mm line.The results obtained from the histopathological examination, the analysis and morphological evaluation of the tissue, and the diagnosis through microscopic observation were used to define a dichotomous variable (presence or absence of a cancerous lesion), adopted in the study as the modeled variable. The next step of the presented study involved constructing a logistic regression model for identifying cancerous lesions depending on the biochemical indicator's relative fluorescence value (RFV) and emission wavelength (ELW) within the 620 nm to 730 nm range. This wavelength range is often used in fluorescence diagnostics to detect various pathologies, including cancerous lesions.The resulting binary logistic regression model, logit(p)=−33.17+0.04ELW+0.01RFV, indicates a statistically significant relationship between wavelength and relative fluorescence values with the probability of detecting cancer. The estimated model exhibits a good fit and high predictive accuracy. The overall model accuracy is 84.8 %, with the correct classification rates at approximately 96 % for healthy individuals and 74 % for individuals with cancer. These findings underscore the potential of photodynamic diagnostics in cancer detection and monitoring.

Basal Cell Carcinoma Diagnosis with Fusion of Deep Learning and Telangiectasia Features

Basal Cell Carcinoma Diagnosis with Fusion of Deep Learning and Telangiectasia Features

[Chinese guildeline on diagnosis and treatment of basal cell carcinoma (2023 edition)].

Basal cell carcinoma (BCC) is the most common skin malignancy, with a higher prevalence in Caucasians than in East Asians. Although there is a lack of epidemiological data in China, it is generally believed that the incidence of BCC in China is increasing due to the aging population. A variety of risk factors are related to the occurrence of BCC, among which ultraviolet rays and gene mutations play a major role, especially the abnormal activation of Hedgehog (Hh) signaling pathway, which is considered to be the most important pathogenesis of BCC. The clinical manifestations of BCC are highly specific, and most experienced doctors can make a preliminary diagnosis by clinical manifestations. Dermoscopy and other imaging methods can greatly improve the accuracy of diagnosis, but there are still some atypical or rare types of BCC that need further confirmation through histopathological examination. This guideline is initiated by the National Clinical Research Center for Skin and Immune Diseases (based on Peking University First Hospital). It has invited a panel of experts consisting of 24 senior dermatologists specializing in dermatologic surgery from the Dermatologic Surgery Group of the Chinese Medical Doctor Association of Dermatology, the Dermatologic Surgery Group of the Dermatology & Venereology Committee, Chinese Association of Integration Medicine, and the Dermatologic Surgery and Cosmetic Branch of Clina Leprosy Association. In addition, experts from the Burn and Plastic Surgery (Maxillofacial), Ophthalmology, Otolaryngology, Head and Neck Surgery, Radiation Therapy, and Pathology were also invited to participate. This panel forms the "Chinese Guideline for the Diagnosis and Treatment of Basal Cell Carcinoma" expert group. Based on the latest domestic and international research findings, the guideline was developed through four rounds of discussions by the expert group and revised to provide valuable references for clinical healthcare providers in the diagnosis and treatment of BCC.

Hybrid Topological Data Analysis and Deep Learning for Basal Cell Carcinoma Diagnosis.

A critical clinical indicator for basal cell carcinoma (BCC) is the presence of telangiectasia (narrow, arborizing blood vessels) within the skin lesions. Many skin cancer imaging processes today exploit deep learning (DL) models for diagnosis, segmentation of features, and feature analysis. To extend automated diagnosis, recent computational intelligence research has also explored the field of Topological Data Analysis (TDA), a branch of mathematics that uses topology to extract meaningful information from highly complex data. This study combines TDA and DL with ensemble learning to create a hybrid TDA-DL BCC diagnostic model. Persistence homology (a TDA technique) is implemented to extract topological features from automatically segmented telangiectasia as well as skin lesions, and DL features are generated by fine-tuning a pre-trained EfficientNet-B5 model. The final hybrid TDA-DL model achieves state-of-the-art accuracy of 97.4% and an AUC of 0.995 on a holdout test of 395 skin lesions for BCC diagnosis. This study demonstrates that telangiectasia features improve BCC diagnosis, and TDA techniques hold the potential to improve DL performance.

Multipli bazocelularni karcinomi nakon primene radioterapije u lečenju tinea capitis u detinjstvu - prikaz slučaja i pregled literature

Introduction: Basal cell carcinoma (BCC) is the most frequent skin cancer with a rising incidence worldwide. Predilection sites are the head and the neck in 80-85% of cases. Leading risk factors are sun exposure and ionizing radiation. In the middle of the 20th century, radiation-induced epilation was used as an efficient treatment method for tinea capitis. Patient review: We report a case of an 80-year-old man with a 16year history of the successive occurrence of multiple BCCs on the scalp, face, and neck. He also had the history of tinea capitis treated with radiotherapy during childhood. At presentation during clinical and dermoscopic examination approximately 25 BCCs were observed, predominantly on the scalp. The most common BCC lesion was the nodular subtype, followed by the pigmented and superficial subtypes. Histopathological examination confirmed the diagnosis of BCC in multiple lesions and one squamous cell carcinoma (SCC). In personal history, the most important comorbidity was hairy cell leukemia. The therapeutic approach included surgery and 5-fluorouracil 5% cream. Conclusion: Radiation-induced epilation was used as an efficient method for treating tinea capitis. One of its side effects was the appearance of BCC in radiation exposed areas. Surgical excision is the gold standard for BCC treatment. Also, 5-fluorouracil 5% cream may be a good option for patients with multiple BCCs. We present satisfactory results after combined treatment in our patient.

Differentiation and risk stratification of basal cell carcinoma with deep learning on histopathologic images and measuring nuclei and tumor microenvironment features.

Nuclear pleomorphism and tumor microenvironment (TME) play a critical role in cancer development and progression. Identifying most predictive nuclei and TME features of basal cell carcinoma (BCC) may provide insights into which characteristics pathologists can use to distinguish and stratify this entity. To develop an automated workflow based on nuclei and TME features from basaloid cell tumor regions to differentiate BCC from trichoepithelioma (TE) and stratify BCC into high-risk (HR) and low-risk (LR) subtypes, and to identify the nuclear and TME characteristics profile of different basaloid cell tumors. The deep learning systems were trained on 161 H&E -stained sections which contained 51 sections of HR-BCC, 50 sections of LR-BCC and 60 sections of TE from one institution (D1), and externally and independently validated on D2 (46 sections) and D3 (76 sections), from 2015 to 2022. 60%, 20% and 20% of D1 data were randomly splitted for training, validation and testing, respectively. The framework comprised four stages: tumor regions identification by multi-head self-attention (MSA) U-Net, nuclei segmentation by HoVer-Net, quantitative feature by handcrafted extraction, and differentiation and risk stratification classifier construction. Pixel accuracy, precision, recall, dice score, intersection over union (IoU) and area under the curve (AUC) were used to evaluate the performance of tumor segmentation model and classifiers. MSA-U-Net model detected tumor regions with 0.910 precision, 0.869 recall, 0.889 dice score and 0.800 IoU. The differentiation classifier achieved 0.977±0.0159, 0.955±0.0181, 0.885±0.0237 AUC in D1, D2 and D3, respectively. The most discriminative features between BCC and TE contained Homogeneity, Elongation, T-T_meanEdgeLength, T-T_Nsubgraph, S-T_HarmonicCentrality, S-S_Degrees. The risk stratification model can well predict HR-BCC and LR-BCC with 0.920±0.0579, 0.839±0.0176, 0.825±0.0153 AUC in D1, D2 and D3, respectively. The most discriminative features between HR-BCC and LR-BCC comprised IntensityMin, Solidity, T-T_minEdgeLength, T-T_Coreness, T-T_Degrees, T-T_Betweenness, S-T_Degrees. This framework hold potential for future use as a second opinion helping inform diagnosis of BCC, and identify nuclei and TME features related with malignancy and tumor risk stratification.

Incidence of malignant eyelid tumors: A 6-year period review (2015–2021)

Abstract Background: Basal cell carcinoma (BCC), the most common malignant tumor, accounts for 85%–95% of cases of eyelid malignant tumors. Demographic factors such as age, gender, tumor location, and subtype play a crucial role in epidemiological knowledge. We investigated eyelid BCC diagnosis and treatment at the Department of Ophthalmology in Centro Hospitalar de Setúbal (CHS). Methods: A retrospective study was conducted on patient cases with suspected eyelid epithelial tumors who underwent excisional biopsy surgery. The study included data from the CHS database between 2015 and 2021. Data collection and subsequent analysis were based on histopathological results. Results: In our study, were analyzed a total of 47 tumor cases, with 68.1% located on the lower eyelids and 31.9% on the upper eyelids. Among these cases, 25 (53.2%) were classified as benign, while 22 (46.8%) were identified as malignant eyelid tumors. BCCs accounted for 90.9% of all malignant cases, with an average age of 71.7 ± 16.6 years. The nodular subtype was the most prevalent, followed by infiltrative and superficial subtypes. Superficial BCC patients were older than infiltrative BCC patients (median age = 69.5 years vs. 61.5 years). BCC primarily affected the lower eyelids compared to the upper eyelid, and there was a slight female predominance (n = 11). All diagnosed BCCs correlated with sun-exposed regions. Conclusions: Timely intervention is crucial for reducing morbidity. These findings emphasize the need for improved registration and notification systems to enhance the prevention and treatment of eyelid BCCs. Furthermore, despite advancements in ultraviolet-blocking technologies, further development of sunscreen specifically formulated for ocular use remains necessary to reduce the incidence of eyelid tumors.

Dermatoscopy and reflectance confocal microscopy for basal cell carcinoma diagnosis and diagnosis prediction score: A prospective and multicenter study on 1005 lesions

BackgroundBasal cell carcinoma is usually diagnosed by clinical and dermoscopy examination, but diagnostic accuracy may be suboptimal. Reflectance confocal microscopy (RCM) imaging increases skin cancer diagnostic accuracy. ObjectiveTo evaluate additional benefit in diagnostic accuracy of handheld RCM in a prospective controlled clinical setting MethodsA prospective, multicenter study in 3 skin cancer reference centers in Italy enrolling consecutive lesions with clinical-dermoscopic suspicion of basal cell carcinoma. Clinicaltrials.gov; NCT04789421 ResultsA total of 1005 lesions were included, of which 474 histopathologically confirmed versus 531 diagnosed by clinical-dermoscopic-RCM correlation, confirmed with 2 years of follow up. Specifically, 740 were confirmed basal cell carcinomas. Sensitivity and specificity for dermoscopy alone was 93.2% (CI 95% 91.2 - 94.9) and 51.7% (CI 95% 45.5 - 57.9); PPV was 84.4 (CI 95% 81.7 – 86.8) and NPV 73.3 (66.3 - 79.5). Adjunctive reflectance confocal microscopy reported higher rates: 97.8 (CI 95% 96.5 - 98.8) sensitivity and 86.8 (CI 95% 82.1 - 90.6) specificity, with PPV of 95.4 (CI 95% 93.6 – 96.8) and NPV 93.5 (89.7 - 96.2). LimitationsStudy conducted in one single Country ConclusionAdjunctive handheld RCM assessment of lesions clinically suspicious for basal cell carcinoma permits higher diagnostic accuracy with minimal false negative lesions.

Management of Nodular Nasal Basal Cell Carcinoma with Wide Excision, Transpositional Median Forehead Flap, Forehead Split Thickness Skin Graft: Case Report

Introduction: Basal cell carcinoma (BCC) is the most common skin type cancer with an incidence rate of around 75-80%. The most common location is in the head and neck area around 70-80% and followed by other body parts around 25% consist of the penis, vulva or perianal area and 5% on the skin. BCC occurs more frequently in light-skinned individuals compared to dark-skinned individuals. The incidence rate is relatively lower in Asians, blacks ethnic, and Hispanics.&#x0D; Case Presentation: A 66 years-old woman complained of scabs on the right side of her nose which had become increasingly widespread for the past 2 years. The wound was initially the size of a mole and was scratched until it spread until the patient was hospitalized. Physical examination showed a wound in the nasal area measuring 4 x 5 x 1 cm, irregular wound edges, cartilaginous wound base with necrotic tissue and pus. The first biopsy examination showed poorly differentiated basal cell carcinoma. The patient was treated with Nasal Reconstruction surgery consisting of wide excision was performed by surgical oncologist, transpositional median forehead Flap and forehead Split Thickness Skin Graft were performed by reconstructive plastic surgeon.&#x0D; Discussion: The diagnosis of BCC in this patient was based on regarding history taking, physical examination and histopathological examination. However, for defects with a diameter of more than 1.5 to 2 cm, generally recommended using axial pattern flaps such as forehead flaps, nasolabial flaps and dorsal nose flaps. In this case, the patient was treated with wide excision followed by nasal reconstruction with a transpositional forehead flap and forehead split thickness skin graft.&#x0D; Conclusion: Nevertheless, regional flaps remain the recommended procedure for nasal reconstruction after wide excision of the tumor. Accurate analysis of the damage combined with evaluation of the patient's clinical condition is necessary to select the best surgical technique. Thorough knowledge of regional vascular anatomy and a comprehensive multidisciplinary approach are important first steps for proper treatment of nasal skin cancer, so that the procedure for wide excision of nasal basal cell carcinoma followed by nasal reconstruction with transpositional forehead flap and split thickness skin graft, can provide satisfactory result.

Advancements in Basal Cell Carcinoma Diagnosis: Non-Invasive Imaging and Multimodal Approach.

(1) Background: The aim of this study was to correlate the diagnostic criteria described in dermatoscopy, ultrasonography (US), ex vivo confocal microscopy, and histology to the most common subtypes of basal cell carcinoma (BCC). (2) Methods: We conducted a prospective study including 46 BCC cases, which were analyzed with dermatoscopy using the Delta 30 dermatoscope and Vidix 4.0 videodermoscope, with US using a high-resolution 20 MHz linear probe, with confocal microscopy, along with histopathological analysis. (3) Results: This study categorized BCC by histological subtype, with nodular being the most common (84.8%) and various other subtypes represented. US measurements of tumor thickness correlated strongly with the histopathological depth of invasion index (DI). Dermatoscopy analysis revealed significant associations between specific features and BCC subtypes. The DI was directly related to arborized vessels but inversely related to short, fine telangiectasias, maple-leaf-like areas, and spoke-wheel areas. The presence of ulceration was directly related to the DI. Confocal microscopy images exhibited several characteristics, including fluorescence, nuclear crowding, peripheral palisading, clefting, increased nuclear-cytoplasmic (N/C) ratio, and a "cauliflower-like" appearance. (4) Conclusion: The advanced detection of BCC through imagistic techniques like dermatoscopy, confocal microscopy, and ultrasound improves the diagnosis and may offer valuable insights for treatment in the future by evaluating lesion characteristics.

Comparison of optical coherence tomography and in vivo reflectance confocal microscopy with dermoscopy for the diagnosis and management of nonmelanoma skin cancer: A randomized controlled trial

AbstractBackgroundOptical coherence tomography (OCT) and reflectance confocal microscopy (RCM) can yield improved diagnostic accuracy of nonmelanoma skin cancer (NMSC) in comparison with dermoscopy alone.ObjectivesThe aim of this study was to compare the diagnostic performance of OCT and RCM together and individually with that of dermoscopy.MethodsPatients with lesions suspicious for NMSC were randomized into two groups in a prospective, single‐centre study. In the intervention group (IG), every lesion was examined with dermoscopy, OCT and RCM, while in the control group (CG), every lesion was examined with dermoscopy alone.ResultsA total of 365 lesions of 250 patients (105 female, 145 male) were included in the study. A total of 208 basal cell carcinomas (BCCs), 65 squamous cell carcinomas (SCCs) and 31 SCCs in situ were examined histologically. The IG involved significantly fewer biopsies than the CG (14 vs. 27, p = 0.029) and required fewer additional inpatient stays due to positive biopsy results (2 vs. 12, p = 0.001). For the diagnosis of BCC, diagnostic accuracy was 81% with dermoscopy, 84% with OCT, 83% with RCM and 85% with the combination of OCT and RCM (OCT/RCM). The diagnostic accuracy of OCT for BCC subtypes was as follows: superficial, 89%; nodular, 79%; sclerodermiform, 82%; and nodular‐cystic BCC, 75%. For the diagnosis of SCC, diagnostic accuracy was 85% with dermoscopy, 87% with OCT, 89% with RCM and 87% with OCT/RCM. For the diagnosis of in situ SCC, diagnostic accuracy was 87% with dermoscopy, 89% with OCT, 89% with RCM and 91% with OCT/RCM.ConclusionsDiagnostic accuracy increased with OCT and RCM and was even higher when both methods were used together. OCT and RCM could facilitate optimization of lesion management by reducing the number of punch biopsies and reducing additional inpatient stays due to positive biopsy results.

'Pitfalls for differentiating basal cell carcinoma from non-basal cell carcinoma on optical coherence tomography: A clinical series'.

Optical coherence tomography (OCT), a non-invasive diagnostic modality, may replace biopsy for diagnosing basal cell carcinoma (BCC) if a high-confidence BCC diagnosis can be established. In other cases, biopsy remains necessary to establish a histopathological diagnosis and treatment regimen. It is, therefore, essential that OCT assessors have a high specificity for differentiating BCC from non-BCC lesions. To establish high-confidence BCC diagnoses, specific morphological BCC characteristics on OCT are used. This study aimed to review several cases of non-BCC lesions that were misclassified as BCC by experienced OCT assessors, thereby providing insight into the causes of these misclassifications and how they may be prevented. The study population consisted of patients who had a histopathologically-verified non-BCC lesion. Patients from Maastricht University Medical Center+ from February 2021 to April 2021 were included in the study. Two independent OCT assessors assessed OCT scans. One OCT assessor recorded the presence or absence of validated morphological BCC characteristics. A false-positive OCT test result was defined as certainty of BCC presence in a non-BCC lesion. The frequency of misclassifications and the presence or absence of morphological BCC features are discussed. A total of 124 patients with non-BCC lesions were included. Six patients were misclassified by both OCT assessors and are discussed in more detail. Histopathological diagnoses were squamous cell carcinoma (n = 2/21), actinic keratosis (n = 2/29), squamous cell carcinoma insitu/Bowen's disease (n = 1/16), or interphase dermatitis (n = 1/4). In all misclassified cases, multiple, apparent morphological BCC characteristics on OCT were present. Most non-BCC lesions are recognized as such by OCT assessors. However, there remains a small risk that a high-confidence BCC diagnosis is established in non-BCC lesions wherein features mimicking validated BCC characteristics are present. Misclassification may be prevented by careful delineation of epidermal layers and good differentiation between dermal ovoid structures typical of BCC versus squamous cell carcinoma.

Applying an artificial intelligence deep learning approach to routine dermatopathological diagnosis of basal cell carcinoma.

Institutes of dermatopathology are faced with considerable challenges including a continuously rising numbers of submitted specimens and a shortage of specialized health care practitioners. Basal cell carcinoma (BCC) is one of the most common tumors in the fair-skinned western population and represents a major part of samples submitted for histological evaluation. Digitalizing glass slides has enabled the application of artificial intelligence (AI)-based procedures. To date, these methods have found only limited application in routine diagnostics. The aim of this study was to establish an AI-based model for automated BCC detection. In three dermatopathological centers, daily routine practice BCC cases were digitalized. The diagnosis was made both conventionally by analog microscope and digitally through an AI-supported algorithm based on a U-Net architecture neural network. In routine practice, the model achieved a sensitivity of 98.23% (center 1) and a specificity of 98.51%. The model generalized successfully without additional training to samples from the other centers, achieving similarly high accuracies in BCC detection (sensitivities of 97.67% and 98.57% and specificities of 96.77% and 98.73% in centers 2 and 3, respectively). In addition, automated AI-based basal cell carcinoma subtyping and tumor thickness measurement were established. AI-based methods can detect BCC with high accuracy in a routine clinical setting and significantly support dermatopathological work.

Multiple aggregated yellow-white globules are a major dermoscopic sign of basal cell carcinoma regardless of their histological subtype.

Multiple aggregated yellow-white globules (MAY globules) have been recently described as dermoscopic structures of high specificity associated with high-risk non-pigmented basal cell carcinoma (BCC). To evaluate the diagnostic accuracy of MAY globules in a cohort of pigmented and non-pigmented BCC of all histological types. This was a retrospective case-control study. Dermoscopic and clinical images were all histopathologically confirmed as BCCs of patients seen consecutively at dermatology consultation. Control cases were benign or malignant tumours randomly selected from the database of 8,250 patients. A total of 389 BCCs were included. MAY globules were present in 192 (49%) cases in the BCC group and in only 25 cases in the control group (6,4%). The odds ratio for the diagnosis of BCC was 14.2 (95%CI: 9.62-20.95]). The presence of MAY globules was significant in three histological subtypes, including superficial BCCs. This study shows that MAY globules are a major dermoscopic sign for the diagnosis of BCC, regardless of their histological subtype and their pigmentation.

Melanoma and basal cell carcinoma: Mimickers of each other

Basal cell carcinoma and malignant melanoma display unique dermoscopic features, at times they can mimic each other. A few clinical and dermoscopic algorithms, including the ABCD rule and the seven-point checklist, have been developed to simplify the diagnostic process. However, these tumors may present ambiguous dermoscopic patterns, lacking typical dermoscopic criteria. We present four cases where dermoscopic structures act as a confounding factor for the incorrect diagnosis of basal cell carcinoma and malignant melanoma. This work aims to improve the differentiation between melanoma and basal cell carcinoma. These tumors can sometimes be clinically similar and this can interfere with treatment if the correct diagnosis is not made.

[The molecular genetic aspects of basal cell carcinoma from the position of population health preservation].

The exploration of molecular genetic mechanisms that underlie carcinogenesis, hereditary factors of various oncological diseases, including basal cell carcinoma, the most common type of skin cancer is especially actual and significant for target strategies of public health. The diagnosis of basal cell carcinoma is based on complex clinical, radiologic and genetic examination data. The further research in the field of somatic or hereditary mutations in genes associated with basal cell carcinoma, including Patched 1 (PTCH1), Patched 2 (PTCH2), Smoothed (SMO) continue to be topical. The strategies of primary prevention of basal cell carcinoma, discussions of complex issues of decision-making concerning treatment at primary health care level, training courses and development of guidelines for general practitioners and interdisciplinary recommendations for effective early diagnosis and comprehensive care of basal cell carcinoma are to be suggested.

Machine learning identification of patient clusters for cutaneous melanoma.

Cutaneous melanoma is a cancer arising in melanocyte skin cells and is the deadliest form of skin cancer worldwide. Although some risk factors are known, accurate prediction of disease progression and probability for metastasis are difficult to ascertain, given the complexity of the disease and the absence of reliable predictive markers. Since early detection and treatment are essential to enhance survival, this study utilizing machine learning (ML) aims to further delineate additional risk factors associated with cutaneous melanoma. A Bayesian Gaussian Mixture ML model was created with data from 2056 patients diagnosed with cutaneous melanoma and then used to group the patients into six Clusters based on a Silhouette Score analysis. A t-distributed stochastic neighbor embedding (t-SNE) model was used to visualize the six Clusters. Statistical analysis revealed that Cluster 4 showed a significantly higher rate of metastatic disease, as well as higher Breslow depth at diagnosis, compared to the other five Clusters. Compared to the other five Clusters, patients represented in Cluster 4 also had lower healthcare utilization, fewer dermatology clinic visits, fewer primary care providers, and less frequent colonoscopies and mammograms, and were more likely to smoke and less likely to have a prior diagnosis of basal cell carcinoma. This study uncovers gaps in healthcare utilization of services among patient groups with cutaneous melanoma as well as possible implications for management of disease progression. Data-driven analyses emphasize the importance of routine clinic visits to dermatologists and/or primary care physicians (PCPs) for early detection and management of cutaneous melanoma. The findings from this study demonstrate that unsupervised ML methodology may serve to define the best candidate patients to benefit from enhanced dermatology/primary care which, in turn, is expected to improve outcomes for cutaneous melanoma.

Rotation flap of the nose.

A 84 years old woman came to our attention with an ulcerated lesion of the nose referred to be present for about 4 months. Clinical diagnosis of basal cell carcinoma was made, and surgical removal was scheduled.