Diagnosis Of Melanoma Research Articles

Evaluation of Demographic and Clinical Characteristics of Turkish Patients With Primary Cutaneous Melanoma: A 5-Year Experience of a Tertiary Referral Center.

Data about the demographic and clinical characteristics of melanoma patients in Turkey is limited. Data about the demographic and clinical characteristics of melanoma patients in Turkey is limited. We aimed to review the features of patients with primary cutaneous melanoma (PCM) diagnosed and treated in a tertiary referral center. The medical records of melanoma patients followed up by the Departments of Dermatology and Medical Oncology were retrospectively reviewed. Within a 5-year period, 180 patients had been diagnosed with melanoma. Of all, 158 (87.8%) had PCM, 9 (5%) had mucosal melanoma, 9 (5%) had unknown primary melanoma, and 4 (2.2%) had ocular melanoma. Of 146 patients with PCM, 32.9% had stage I, 28.8% had stage II, 17.8% had stage III, and 20.5% had stage IV disease. The most common subtype was superficial spreading melanoma (38.8%). A statistically significant correlation was found between the patients Breslow thickness and lymph node involvement, histopathological subtype, and tumor ulceration (P < 0.001). Among all PCM patients, those in stage IV had the lowest 5-year survival rate when compared to the other disease stages (P < 0.001). Relatively younger age at melanoma diagnosis, frequent presence of thick (> 4 mm) tumor, and frequent acral lentiginous subtype are the most remarkable features that suggest the low awareness and knowledge of melanoma in our population.

Associations of Social Factors and Self-Efficacy with Skin-Self Examination Intentions Among Hispanics at Risk for Skin Cancer and Their Preferences for Digital Interventions.

Skin cancer ranks as the most prevalent cancer in the United States. Over the past two decades, the incidence of melanoma, the deadliest form of skin cancer, among Hispanics has risen by 20%. Melanoma mortality rates are higher in Hispanics than in non-Hispanic Whites (NHW). Early detection of melanoma via skin self-examination may lead to diagnosis of melanoma at an earlier stage, when they are thinner, less invasive, and more easily treatable, resulting in improved survival rates. Given the gap in research addressing culturally relevant factors related to skin cancer prevention and detection among Hispanics and informed by the Preventive Health Model, this study tested the associations between social and normative factors and self-efficacy with thorough skin self-examination (TSSE) intentions and queried participants about their preferences for skin cancer-related interventions. Among respondents (n = 79), 55.7% were female (n = 44), and 89.9% held a college or higher degree (n = 71). Self-efficacy fully mediated the effects of descriptive norms, injunctive norms, and provider-patient communication on TSSE intentions among Hispanics. On average, respondents demonstrated considerable interest in participating in a skin cancer-related behavioral intervention using a mobile application (75.6%) and/or using WhatsApp (71.8%). These preliminary findings provide new insights for development of future digital skin cancer intervention programs among Hispanics targeting social factors, including social norms and provider-patient communication, and utilizing preferred digital tools.

Preclinical ImmunoPET Imaging Using a Zr-89-Labeled Anti-CD146 Monoclonal Antibody for Diagnosis of Melanoma.

The aim of this study was to evaluate the preclinical efficacy of [89Zr]Zr-DFO-Ab253 as a novel positron emission tomography (PET) tracer for CD146-positive malignant melanoma imaging. Considering the high expression of CD146 in malignant melanoma, this study investigated the effect of different CD146 expression levels on the tumor uptake of [89Zr]Zr-DFO-Ab253. CD146 selectivity was investigated by using the CD146-positive human melanoma cell A375 and the CD146-negative human alveolar epithelial cell A549. The cell uptake of [89Zr]Zr-DFO-Ab253 tracers was investigated, and receptor-binding affinities were measured by radioactive enzyme-linked immunosorbent assay. Biodistribution studies and micro-PET imaging of the radiotracers were performed on mice bearing A375 and A549 xenografts under baseline and blocking conditions. An immunohistochemical test was performed using A375 and A549 tissue sections for CD146 expression level analysis. [89Zr]Zr-DFO-Ab253 was obtained with a high radiochemical yield (87.86 ± 4.66%) and a satisfactory radiochemical purity (>98.0%). The specificity and affinity of [89Zr]Zr-DFO-Ab253 were confirmed in melanoma A375 cells and in vivo PET imaging of A375 tumor models. [89Zr]Zr-DFO-IgG and A549 lung tumors were prepared as control radiotracers and negative models to verify the specificity of [89Zr]Zr-DFO-Ab253 on CD146. [89Zr]Zr-DFO-Ab253 has a Kd of 4.01 ± 0.50 nM. PET imaging and biodistribution showed a higher uptake of [89Zr]Zr-DFO-Ab253 in A375 melanomas than that in A549 tumors (42.1 ± 4.04% vs 7.87 ± 1.30% ID/g at 120 h, P < 0.05). A low tumor uptake of [89Zr]Zr-DFO-IgG was observed with uptakes of 1.91 ± 0.41 and 2.80 ± 0.14 ID%/g when blocked at 120 h. The radiation-absorbed dose was calculated to be 0.13 mSv/MBq. This study demonstrates the synthesis and preclinical evaluation of [89Zr]Zr-DFO-Ab253 and indicates that the novel tracer has promising applications in malignant melanoma-specific PET imaging because of its high uptake and long-time retention in malignant melanoma. It also provides feasibility for the development of integrated molecular probes for diagnosis and treatment based on the CD146 target.

Isolated conjunctival cavernous hemangioma: a rare case report

Vascular conjunctival tumors are uncommon, usually benign lesions. Here, we report a 65-year-old male who presented with a nasal interpalpebral bulbar firm, oval, and dark-brown and non-mobile conjunctival mass. The systemic and ocular examinations including fundoscopy and gonioscopy were within normal limits. With a diagnosis of conjunctival malignant melanoma (CMM), the patient underwent excisional biopsy, partial sclerectomy, and cryotherapy. Microscopic examination revealed dilated vascular channels filled by red blood cells, separated by fibrous interstitium and no sign of malignancy. Therefore, a diagnosis of conjunctival cavernous hemangioma was made. Our case demonstrates that the conjunctival cavernous hemangioma can mimic malignant conjunctival lesions as well as extrascleral extension of uveal melanoma or uveal prolapse due to scleral necrosis.

Rapidly progressing scalp melanoma in an elderly patient.

A rapidly progressing scalp melanoma incorrectly diagnosed and managed as a 'chronic wound', lead to delayed referral to dermatologist and correct diagnosis. This case highlights the importance of early diagnosis of scalp melanoma and of frailty screening in elderly patients.

Skin Malignant Melanoma and Matrix Metalloproteinases: Promising Links to Efficient Therapies.

Skin malignant melanoma (MM) is one of the most frequent and aggressive neoplasia worldwide. Its associated high mortality rates are mostly due to its metastases, while diagnosis and treatment of MM in its early stages is of favorable prognostic. Even skin superficial MMs at incipient local stages can already present with lymph node invasion and distant metastases. Therefore, knowledge of the controllable risk factors and pathogenic mechanisms of MM development, spreading, and metastatic pattern, as well as early diagnosis, are essential to decrease the high mortality rates associated with cutaneous malignant melanoma. Genetic factors are incriminated, although lifetime-acquired genetic mutations appear to be even more frequently involved in the development of MM. Skin melanocytes divide only twice per year and have time to accumulate genetic mutations as a consequence of environmental aggressive factors, such as UV exposure. In the search for more promising therapies, matrix metalloproteinases have become of significant interest, such as MMP-1, MMP-2, MMP-9, and MMP-13, which have been linked to more aggressive forms of cancer and earlier metastases. Therefore, the development of specific synthetic inhibitors of MMP secretion or activity could represent a more promising and effective approach to the personalized treatment of MM patients.

Optimizing CNN Kernel Sizes for Enhanced Melanoma Lesion Classification in Dermoscopy Images

Skin cancer, particularly melanoma, presents a significant global health challenge due to its increasing incidence and mortality rates. Current diagnostic methods relying on visual inspection and histopathological examination are subjective and time-consuming, often leading to delayed diagnoses. Recent advancements in machine and deep learning, particularly convolutional neural networks (CNNs), offer a promising avenue for transforming melanoma detection by automating precise classification of dermoscopy images. This study leverages a comprehensive dataset sourced from Kaggle, comprising 10,605 images categorized into benign and malignant classes. Methodologically, a custom CNN architecture is trained and evaluated using varying kernel sizes (3x3, 5x5, 7x7) to optimize melanoma lesion classification. Results demonstrate that smaller kernel sizes, notably 3x3, consistently yield superior accuracy of 93.00% and F1-scores of 96.00%, indicating their efficacy in distinguishing between benign and malignant lesions. The CNN model exhibits robust generalization capabilities with minimal overfitting, supported by high validation accuracy throughout training epochs. Comparative analysis with related studies highlights competitive performance, suggesting potential enhancements through advanced feature selection and optimization techniques. Despite these advancements, challenges such as dataset diversity and model optimization persist, particularly concerning underrepresented darker skin tones. The study underscores the transformative potential of CNNs in enhancing diagnostic accuracy and efficiency in dermatological practice, paving the way for improved patient outcomes through early detection and intervention strategies. Future research directions include refining segmentation techniques and expanding dataset evaluations to ensure the model&amp;apos;s applicability across diverse clinical settings. Ultimately, this research contributes to advancing melanoma diagnosis by integrating cutting-edge deep learning methodologies with clinical practice, thereby addressing current limitations and driving forward innovations in dermatological image analysis.

Diagnosis of metastatic melanoma by fine-needle aspiration biopsy and primary melanoma by using the skin and mucousa imprints

BACKGROUND: Determination of the cytogenetic origin and morphological type of metastatic or primary tumor determines the prescription of therapy and affects the efficiency of patient’s treatment. Currently, a number of publications evaluate the potential of cytological diagnostics of melanoma. AIM: To evaluate the significance of diagnosing metastatic melanoma by fine-needle aspiration biopsy and primary melanoma by using the skin and mucosa imprints. METHODS: In a retrospective study, a comparative analysis of cytological melanoma samples, in comparison with clinical and anamnestic information and the results of histological, immunohistochemical, and molecular genetic studies, was carried out. Information about 109 patients from the cancer registry of the Altai Regional Oncology Dispensary (Barnaul, Russia) for 2022 was used in the study. Traditional and liquid-based methods for preparing samples were used. The samples were stained using Pappenheim and Papanicolaou methods. In some observations, cytological material was used for molecular genetic studies. Using the cancer registry data of the dispensary, the results of histological and of molecular genetic studies, and a final conclusion was given about each patient. RESULTS: Fine-needle aspiration biopsy was carried out in 80 patients. Tumor smears were obtained from 29 patients. The cytological diagnose “melanoma” was consistent with the data of histological and immunohistochemical studies (p 0.001) for all 109 patients. Melanoma was diagnosed for the first time in 66 (60.5%) patients. In other cases, the process of progression was noted within the period from one year to 20 years. Epidermal melanoma was noted in 101 (92.7%) cases, including 9 patients with acral melanoma, and 2 cases with localization on the vulva. Melanomas of mucosa were found in 5 cases (4.5%): in the rectum and anal canal, vagina, and in 2 cases on the hard palate. Non-epidermal (uveal) melanomas metastases were diagnosed in liver by fine-needle aspiration biopsy in 3 patients (2.8%). Based on the cellular composition, epithelioid cell melanoma was determined in 81 (74.3%) patients, mixed cell in 14 (12.8%) cases, spindle cell in 9 (8.2%), pigmentless in 2 (1.8%) cases and nevoid melanoma in 1 (0.9%) case. The mutation status was determined in 96 patients (88.1%). Of these, in 8 patients it was determined using cytological material. In epidermal melanomas, mutations in codon 600 of exon 15 of the BRAF gene were found in 43 (44.8%) patients, including 2 cases of acral melanoma. Mutations V600K, V600E/Ec were found in one patient each. In mucousal melanomas: Q61R mutation was found in exon 3 of the NRAS gene (vaginal melanoma), G12C mutation was identified in exon 2 of the NRAS gene (anal canal melanoma). In uveal melanomas, the assessed mutations were absent (it is necessary to determine mutation is GNAQ11 and BAP1 genes). CONCLUSION: Cytological diagnosis of melanoma by fine-needle aspiration biopsies and imprints from the tumor mass is a highly informative method that allows diagnosing melanoma and verifying the tumor subtype. The obtained results indicate tumor heterogeneity and differences in mutational status depending on the location of melanomas. The molecular classification of melanoma is important when choosing individualized therapy.

Unusual PEComa With PRCC :: TFE3 Fusion Mimicking Sinonasal Tract Melanoma.

We report a nasal cavity unusual perivascular epithelioid cell tumor (PEComa) mimicking mucosal melanoma. Immunohistochemistry was performed using BenchMark Ultra and panel of antibodies. The Ion Torrent platform and Ion AmpliSeq cancer hotspot panel were utilized for DNA genotyping. Target-specific RNA libraries for the detection of fusion transcripts were constructed using Archer Universal RNA Reagent Kit v2 and Archer FusionPlex Solid Tumor panel and sequenced on the MiSeqDx instrument. The tumor, diagnosed in 46-year-old female, was composed of spindle cells, and lacked pigmentation. Immunohistochemically, it showed a patchy HMB-45 positivity. Other melanocytic markers (S100 protein, Melan-A, SOX10) were negative. The tumor cells were weakly positive for KIT (CD117) while negative for smooth muscle actin, pancytokeratin cocktail (AE1/AE3), and synaptophysin. Diagnosis of primary sinonasal tract mucosal melanoma was favored. Additional molecular studies detected PRCC :: TFE3 fusion as the sole genetic change, and suggested the diagnosis of unusual PEComa. Previously, TFE3 fusions were reported in a subset of PEComas but not in melanomas, while PRCC involvement has only been documented once in an ocular PEComa. Immunohistochemistry revealed strong nuclear TFE3 expression concordant with the molecular findings. This report emphasis the importance of molecular testing in the differential diagnosis between PEComa and melanoma, especially when the tumor arises in a site typical of melanoma but showing an unusual morphology and immunophenotype. The detection of TFE3 fusion transcripts suggested the diagnosis of SNT PEComa, although it cannot be excluded that this and similar tumors represent a distinct diagnostic category.

A Self-Supervised Learning Based Framework for Eyelid Malignant Melanoma Diagnosis in Whole Slide Images.

Eyelid malignant melanoma (MM) is a rare disease with high mortality. Accurate diagnosis of such disease is important but challenging. In clinical practice, the diagnosis of MM is currently performed manually by pathologists, which is subjective and biased. Since the heavy manual annotation workload, most pathological whole slide image (WSI) datasets are only partially labeled (without region annotations), which cannot be directly used in supervised deep learning. For these reasons, it is of great practical significance to design a laborsaving and high data utilization diagnosis method. In this paper, a self-supervised learning (SSL) based framework for automatically detecting eyelid MM is proposed. The framework consists of a self-supervised model for detecting MM areas at the patch-level and a second model for classifying lesion types at the slide level. A squeeze-excitation (SE) attention structure and a feature-projection (FP) structure are integrated to boost learning on details of pathological images and improve model performance. In addition, this framework also provides visual heatmaps with high quality and reliability to highlight the likely areas of the lesion to assist the evaluation and diagnosis of the eyelid MM. Extensive experimental results on different datasets show that our proposed method outperforms other state-of-the-art SSL and fully supervised methods at both patch and slide levels when only a subset of WSIs are annotated. It should be noted that our method is even comparable to supervised methods when all WSIs are fully annotated. To the best of our knowledge, our work is the first SSL method for automatic diagnosis of MM at the eyelid and has a great potential impact on reducing the workload of human annotations in clinical practice.

Impacto del Índice neutrófilo/linfocito en el Melanoma Lentiginoso Acral

Introduction: Acral lentiginous melanoma (ALM) is the fourth type of cutaneous melanoma and is the most common subtype in some countries in Latin America and Asia. The neutrophil-lymphocyte ratio (NLR) is an inflammatory marker that has been shown to be useful as a prognostic tool in several malignant neoplasms. Objective: The objective of the study was to evaluate whether NLR has prognostic value in ALM. A retrospective study was conducted that included patients with ALM between 2010 and 2015. Methods: An observational, analytical and retrospective cohort design was used. We worked with a total population of 69 patients with the diagnosis of acral lentiginous melanoma. For the statistical analysis, the SPSS statistical package version 26 was used. Univariate and multivariate Cox proportional regression models were performed. Results: A total of 69 patients with ALM were included. The median age was 68 years, with a predominance of females (55%). Most patients had T4 (34%), lymph node involvement (57.1%), and Clark III (34.4%). In univariate analysis, Clark level III/IV, anaplasia, lymphocytic infiltration, stage III-IV, and NLR were associated with prognoses. In the multivariate analysis, NLR &gt;3.5 (HR 3.9, 95% CI 1.5-10.3, p=0.005) and Clark level III-IV (HR 3.5, 95% CI 1.6-7.8, p= 0.002) were associated with poor overall survival (OS). Conclusions: NLR is an independent prognostic factor for survival in ALM.

P058 Healthcare disparity affecting delayed diagnosis in acral lentiginous melanoma

P058 Healthcare disparity affecting delayed diagnosis in acral lentiginous melanoma

BT05 Comparing the number-needed-to-biopsy ratio for melanoma diagnosis between teledermatology, an artificial intelligence device with teledermatology, and face-to-face models of care

BT05 Comparing the number-needed-to-biopsy ratio for melanoma diagnosis between teledermatology, an artificial intelligence device with teledermatology, and face-to-face models of care

Primary vulval melanoma and genital lichen sclerosus.

Lichen sclerosus (LS) is a chronic, inflammatory skin disease with a predilection for the genitalia. Although, the association between squamous cell cancer and genital LS is well established, a link with genital melanoma has not been thoroughly explored. However, we have recently published a case series of penile melanoma where 9/11 (82%) of patients seen over a 10year period with penile melanoma were retrospectively found to have histological and/or clinical evidence of genital LS on review. The aim of this study was to illuminate further the relationship between vulval melanoma and genital LS by reviewing all the cases managed by our hospital and undertaking a literature review. We identified all the cases with a diagnosis of vulval melanoma over a 16-year period (2006-2022) where histology was available. The clinical notes were retrospectively reviewed, and the histological features of all cases were reassessed by two independent mutually 'blinded' histopathologists. We also performed a literature review of genital LS in patients with vulval melanoma. A total of 11 patients with vulval melanoma were identified for the review. Histopathological review found evidence of genital LS in seven of them (64%). Genital LS was not documented in any of the original histology reports. Clinical notes and letters were available in nine cases. The literature review identified 12 relevant studies with a total of 18 patients. Twelve cases concerned adult women, and six concerned female children. The presence of genital LS in as high as 64% of our vulval melanoma cases might indicate a causative relationship between genital LS and vulval melanoma. The pathogenesis of vulval melanoma remains largely unknown. Although ultraviolet radiation is an important pathogenic factor for cutaneous melanoma, it cannot be a factor in vulval melanoma. While possible mechanisms behind this association remain unclear, it is possible that chronic inflammation from genital LS leads to melanocytic distress and increased mutagenesis.

Exploring of miR-155-5p, miR-181b-5p, and miR-454-3p Expressions in Circulating Cell-Free RNA: Insights from Peripheral Blood of Uveal Malignant Melanoma Patients.

The identification of novel non-invasive biomarkers is imperative for the early diagnosis and monitoring of malignant melanoma. The objective of this study is to examine the expression levels of miR-155-5p, miR-181b-5p, and miR-454-3p in circulating cell-free RNA obtained from plasma samples of the 72 uveal malignant melanoma patients and to compare these levels with those of 72 healthy controls. The analysis showed that the expression level of the miR-181b-5p has increased 9.25 fold, and expression level of miR-155-5p has increased 6.67 fold, and miR-454-3p expression level has increased 4.14 fold in the patient group compared with the levels in the healthy control group (p = 0.005). It was found that the high expression levels of the three miRNAs were statistically significant in patients compared with in the healthy control group. The statistical evaluations between miRNA expression levels and clinical data showed that miR-155-5p had significant association with radiation therapy (p = 0.040), and miR-454-3p showed a significant association with smoking and alcohol use respectively (p = 0.009, and p = 0.026). The significantly elevated expression levels of miR-181b-5p, miR-155-5p, and miR-454-3p in the circulating cell-free RNA of plasma from uveal melanoma patients, in comparison to those in the healthy control group, suggest the potential usefulness of these biomarkers for both early diagnosis and disease monitoring. However, more extensive and future studies are needed to use these molecules in early diagnosis and disease monitoring.

Skin lesion segmentation via Neural Cellular Automata

Skin melanoma is one of the most dangerous tumor lesions. In recent years, the number of cases and deaths caused by melanoma has been increasing. The discovery and segmentation of the lesion area are crucial for the timely diagnosis and treatment of melanoma. However, the lesion area is often similar to the healthy area, and the size scale changes greatly, which makes the segmentation of the skin lesion area a very challenging task. Neural Cellular Automata (NCA) is a model that can be described as a recurrent convolutional network. It achieves global consistency through multiple local information exchanges, thereby completing the processing of information. Recent research on NCA shows that such a local interactive model can segment low-resolution images well. However, for high-resolution images, direct use of NCA for processing is limited by high memory requirements and difficulty in model convergence. In this paper, in order to overcome these limitations, we propose a new NCA-based segmentation model, named UNCA. UNCA is a model with a U-shaped structure. The high-resolution image is down-sampled to obtain high-dimensional low-resolution features, which are then input into the NCA for information processing. Finally, the image size is restored by upsampling. The experimental results show that the UNCA proposed in this paper has achieved good results on the ISIC2017 dataset, surpassing most of the current methods.

Identifying novel circadian rhythm biomarkers for diagnosis and prognosis of melanoma by an integrated bioinformatics and machine learning approach.

Melanoma is a highly malignant skin tumor with poor prognosis. Circadian rhythm is closely related to melanoma pathogenesis. This study aimed to identify key circadian rhythm genes (CRGs) in melanoma and explore their potential as diagnostic and prognostic biomarkers. Microarray data of melanoma tissues and normal skins were obtained. Differentially expressed genes were identified and weighted gene co-expression network analysis (WGCNA) was performed to screen hub genes associated with melanoma. By overlapping hub genes with known CRGs, 125 melanoma-related CRGs were identified. Functional enrichment analysis revealed these CRGs were mainly involved in circadian rhythm and other cancer-related pathways. Three machine learning algorithms including LASSO regression, support vector machine-recursive feature elimination (SVM-RFE), and random forest were utilized to select key CRGs. Six CRGs (ABCC2, CA14, EGR3, FBXW7, LDHB, and PSEN2) were identified as key CRGs for melanoma diagnosis and prognosis. Diagnostic values of key CRGs were evaluated by ROC analysis in training and validation sets. Prognostic values of key CRGs were assessed by survival analysis and a multivariate Cox regression prognostic model was constructed. The prognostic model could effectively stratify melanoma patients into high- and low-risk groups with significantly different survival. A nomogram integrating clinical variables and risk score was built to predict 3-, 5- and 10-year overall survival of melanoma patients. In summary, six CRGs were identified as key genes associated with melanoma pathogenesis and may serve as promising diagnostic and prognostic biomarkers. The prognostic model and nomogram could facilitate personalized prognosis evaluation of melanoma patients.

Bluish veil detection and lesion classification using custom deep learnable layers with explainable artificial intelligence (XAI)

Melanoma, one of the deadliest types of skin cancer, accounts for thousands of fatalities globally. The bluish, blue-whitish, or blue-white veil (BWV) is a critical feature for diagnosing melanoma, yet research into detecting BWV in dermatological images is limited. This study utilizes a non-annotated skin lesion dataset, which is converted into an annotated dataset using a proposed imaging algorithm (color threshold techniques) on lesion patches based on color palettes. A Deep Convolutional Neural Network (DCNN) is designed and trained separately on three individual and combined dermoscopic datasets, using custom layers instead of standard activation function layers. The model is developed to categorize skin lesions based on the presence of BWV. The proposed DCNN demonstrates superior performance compared to the conventional BWV detection models across different datasets. The model achieves a testing accuracy of 85.71 % on the augmented PH2 dataset, 95.00 % on the augmented ISIC archive dataset, 95.05 % on the combined augmented (PH2+ISIC archive) dataset, and 90.00 % on the Derm7pt dataset. An explainable artificial intelligence (XAI) algorithm is subsequently applied to interpret the DCNN's decision-making process about the BWV detection. The proposed approach, coupled with XAI, significantly improves the detection of BWV in skin lesions, outperforming existing models and providing a robust tool for early melanoma diagnosis.

Predictive and Prognostic Factors in Melanoma Central Nervous System Metastases-A Cohort Study.

Melanoma is the cancer with the highest risk of dissemination to the central nervous system (CNS), one of the leading causes of mortality from this cancer. To identify patients at higher risk of developing CNS metastases and to evaluate associated prognostic factors. A cohort study (1998-2023) assessed patients who developed CNS melanoma metastases. Multivariate logistic regression was used to identify predictive factors at melanoma diagnosis for CNS metastasis. Cox regression analysis evaluated the CNS-independent metastasis-related variables impacting survival. Out of 4718 patients, 380 (8.05%) developed CNS metastases. Multivariate logistic regression showed that a higher Breslow index, mitotic rate ≥ 1 mm2, ulceration, and microscopic satellitosis were significant risk factors for CNS metastasis development. Higher patient age and the location of the primary tumor in the upper or lower extremities were protective factors. In survival analysis, post-CNS metastasis, symptomatic disease, prior non-CNS metastases, CNS debut with multiple metastases, elevated LDH levels, and leptomeningeal involvement correlated with poorer survival. Predictive factors in the primary tumor independently associated with brain metastases include microscopic satellitosis, ulceration, higher Breslow index, and trunk location. Prognostic factors for lower survival in CNS disease include symptomatic disease, multiple CNS metastases, and previous metastases from different sites.

Comparison of Extended Skin Cancer Screening Using a Three-Step Advanced Imaging Programme vs. Standard-of-Care Examination in a High-Risk Melanoma Patient Cohort.

Modern diagnostic procedures, such as three-dimensional total body photography (3D-TBP), digital dermoscopy (DD), and reflectance confocal microscopy (RCM), can improve melanoma diagnosis, particularly in high-risk patients. This study assessed the benefits of combining these advanced imaging techniques in a three-step programme in managing high-risk patients. This study included 410 high-risk melanoma patients who underwent a specialised imaging consultation in addition to their regular skin examinations in outpatient care. At each visit, the patients underwent a 3D-TBP, a DD for suspicious findings, and an RCM for unclear DD findings. The histological findings of excisions initiated based on imaging consultation and outpatient care were compared. Imaging consultation detected sixteen confirmed melanomas (eight invasive and eight in situ) in 39 excised pigmented lesions. Outpatient care examination detected seven confirmed melanomas (one invasive and six in situ) in 163 excised melanocytic lesions. The number needed to excise (NNE) in the imaging consultation was significantly lower than that in the outpatient care (2.4 vs. 23.3). The NNE was 2.6 for DD and 2.3 for RCM. DD, 3D-TBP, or RCM detected melanomas that were not detected by the other imaging methods. The three-step imaging programme improves melanoma detection and reduces the number of unnecessary excisions in high-risk patients.