Melanoma Lymph Node Metastases Research Articles

Impact of extra-nodal extension and AJCC lymph node staging in predicting recurrence following lymphadenectomy in patients with melanoma

BackgroundRegional lymphadenectomy (RL) has traditionally been recommended in patients with melanoma found to have clinical lymphadenopathy or a positive sentinel lymph node biopsy (SLNB). Regional control of disease is still a relevant issue for patients, even after undergoing lymphadenectomy. The goal of this study was to identify the clinicopathologic characteristics that predict locoregional recurrence in patients who have undergone either therapeutic lymph node dissection (TLND) or completion lymph node dissection (CLND) following SLNB. MethodsRetrospective review of population-based cohort of patients with melanoma lymph node metastasis from the years 2005–2015. Multivariate, proportional hazards regression analysis was performed to determine factors predicting nodal recurrence. Results586 patients underwent a RL, with a median follow up of 35 months. Overall, in-basin recurrence rates in the axilla, groin, and head/neck were 7.7 ​%, 8.7 ​% and 9.2 ​%, respectively. Higher unadjusted recurrence rates occurred following CLND than TLND of the groin (12.8 ​% vs 4.5 ​%) and neck (10.0 ​% vs 4.7 ​%) but not the axilla (7.5 ​% vs 8.0 ​%). Upon multivariate analysis, ENE (HR 2.77; p=<0.0001) and the AJCC lymph node stage (N3 vs N1) (HR 2.51; p ​= ​0.025) were predictive of regional recurrence. ConclusionThe AJCC nodal stage and the presence of extranodal extension were the only variables impacting regional recurrence following regional lymphadenectomy for melanoma. When considering regional disease control, they should be factored into treatment decisions, and surveillance strategies.

Risk factors for sentinel lymph node metastasis in Korean acral and non-acral melanoma patients.

Breslow thickness, ulceration, and mitotic rate are well-known prognostic factors for sentinel lymph node (SLN) metastasis in cutaneous melanoma. We investigated risk factors, including especially the degree of pigmentation, for SLN metastasis in Korean melanoma patients. We enrolled 158, composed of Korean 107 acral and 51 non-acral melanoma patients who underwent SLN biopsy. Clinicopathologic features such as Breslow thickness, ulceration, mitotic rate, and the degree of pigmentation were evaluated. The recurrence-free survival (RFS) rate and date of recurrence were determined. Fifty-four patients (34.2%) had a positive SLN biopsy result. In a multivariate analysis, Breslow thickness (odds ratio [OR] 1.93; 95% confidence interval [CI], 1.12-3.47; p = .022) and heavy pigmentation (OR 13.14; 95% CI, 2.96-95.20, p = .002) were associated with SLN metastasis. Positive SLN patients had a higher rate of loco-regional and/or distant recurrence (hazard ratio 6.32; 95% CI, 3.39-11.79; p < .001). Heavy pigmentation was associated with poor RFS. Heavy pigmentation is an independent predictor of SLN metastasis in both acral and non-acral melanoma. Our results suggest the need for in-depth SLN evaluation of cutaneous melanoma patients with heavy pigmentation and provide clinicians with important information for determining patient prognosis.

Combined WNT-activated deep-penetrating/plexiform melanocytoma: insights into clinicopathological andmolecular characterization.

A combined deep-penetrating tumour redefined as WNT-activated deep-penetrating/plexiform melanocytoma (DPM), may pose challenging clinical and histological diagnoses. To review the clinicopathological characteristics of combined DPMs and characterize the molecular profile of atypical and malignant forms. The study included 51 patients with combined DPMs diagnosed at the Hospital Clinic of Barcelona and the University of Florence between 2012 and 2020. Clinical data, dermoscopy images (when available) and histological characteristics were reviewed. Immunohistochemistry for β-catenin, LEF1, HMB45, Ki67, p16 and PRAME (preferentially expressed antigen in melanoma) was performed. Atypical forms underwent next-generation sequencing (NGS) panel analysis, including driver genes implicated in DPMs, TERT-promoter (p) mutations and the investigation of the 9p21 locus via fluorescence in situ hybridization. Among the 51 patients (32 females and 19 males, age range 4-74 years), 68% with available clinical data (15/22) were initially suspected of having melanoma. Except for one patient, complete excision resulted in no recurrences or metastases. One patient who had an incompletely excised combined DPM developed a lymph node melanoma metastasis 10 years later. In the 51 patients, 10 samples (20%) showed atypical histological features; 7 (14%) exhibited a significant loss of p16 expression; and 2 (4%) showed a high-proliferative index (Ki67 over 5%). NGS analysis in 11 patients revealed a double mutation BRAFV600E and exon 3 CTNNB1; no TERTp mutations were detected. Clinical suspicion of melanoma is common in combined DPMs, but malignant progression is infrequent in tumours lacking high-grade atypia or proliferation. These findings are congruent with the consideration of these lesions as intermediate-grade tumours or melanocytomas.

Deep learning detection of melanoma metastases in lymph nodes

BackgroundIn melanoma patients, surgical excision of the first draining lymph node, the sentinel lymph node (SLN), is a routine procedure to evaluate lymphogenic metastases. Metastasis detection by histopathological analysis assesses multiple tissue levels with hematoxylin and eosin and immunohistochemically stained glass slides. Considering the amount of tissue to analyze, the detection of metastasis can be highly time-consuming for pathologists. The application of artificial intelligence in the clinical routine has constantly increased over the past few years. MethodsIn this multi-center study, a deep learning method was established on histological tissue sections of sentinel lymph nodes collected from the clinical routine. The algorithm was trained to highlight potential melanoma metastases for further review by pathologists, without relying on supplementary immunohistochemical stainings (e.g. anti-S100, anti-MelanA). ResultsThe established method was able to detect the existence of metastasis on individual tissue cuts with an area under the curve of 0.9630 and 0.9856 respectively on two test cohorts from different laboratories. The method was able to accurately identify tumour deposits>0.1 mm and, by automatic tumour diameter measurement, classify these into 0.1 mm to −1.0 mm and>1.0 mm groups, thus identifying and classifying metastasis currently relevant for assessing prognosis and stratifying treatment. ConclusionsOur results demonstrate that AI-based SLN melanoma metastasis detection has great potential and could become a routinely applied aid for pathologists. Our current study focused on assessing established parameters; however, larger future AI-based studies could identify novel biomarkers potentially further improving SLN-based prognostic and therapeutic predictions for affected patients.

428 Degree of pigmentation as a risk factor for sentinel lymph node metastasis in cutaneous melanoma

428 Degree of pigmentation as a risk factor for sentinel lymph node metastasis in cutaneous melanoma

ASO Visual Abstract: A Clinical Decision Tool to Calculate Pretest Probability of Sentinel Lymph Node Metastasis in Primary Cutaneous Melanoma.

ASO Visual Abstract: A Clinical Decision Tool to Calculate Pretest Probability of Sentinel Lymph Node Metastasis in Primary Cutaneous Melanoma.

Abstract 6375: Transcriptomic signatures in melanoma lymph node metastasis that relate to immune oncology treatment

Abstract Background: Frequently, patients with primary cutaneous melanoma develop regional lymph node metastasis (LNM). The outcomes in melanoma patients with LNM can be poor, depending on clinicopathological features including the size and the number of the LNM. Newer immunotherapies including immune checkpoint inhibitors (ICI) have significantly improved outcomes in metastatic melanoma patients, and when tumors respond to ICI the durable responses are noteworthy. The aim of the current study is to identify transcriptomics changes in immune-related genes in LNM that correlate to outcomes in melanoma patients receiving adjuvant ICI therapy. Methods: The analysis were performed in formalin-fixed paraffin-embedded (FFPE) sections from LNM positive (LNM(+); n=17) and LNM negative (LNM(-); n=8) of patients who received surgery at SJHC. For each tissue, a single section was processed and analyzed for 2,002 genes using the direct (mRNA extraction-free) transcriptomic assay of the HTG EdgeSeq AutoImmune Panel (HTG-AI). The HTG-AI transcriptomic normalized data were compared between both groups. For verification of gene signatures, publicly available RNA-seq datasets were obtained from patients with clinical outcomes receiving anti-PD-1. All biostatistical analysis were performed using HTG Reveal and/or GraphPad Prism software. Results: Comparisons between melanoma LNM(+) and LNM(-) samples showed 229 DEGs (Log2fold-change ←2; &amp;gt;2 FDR&amp;lt;0.01), with 213 genes upregulated and 16 downregulated. Pathway analyses using Reactome indicated that the DEGs in LNM(+) were associated with cytokine, interferon (IFN), and chemokine signaling, as well as signaling by receptor tyrosine kinases (FDR&amp;lt;0.0001). The chemokines CXCL8, CXCL2, and CXCL10 were significantly upregulated in LNM(+) (p&amp;lt;0.001). LNM(+) showed significantly higher levels of IFN signaling mediators (STAT1, STAT2, IFI6, IFI30, IFI44) compared to LNM(-) specimens (p&amp;lt;0.001). Also, LNM(+) showed a significant increase in CD276 (B7-H3) levels (p&amp;lt;0.001). Then, we correlated the mRNA levels of IFN signaling (STAT1, STAT2, IFI6, IFI30, and IFI44) obtained from samples before anti-PD-1 therapy (Nivolumab or Pembrolizumab) to overall survival (OS). Of clinical importance, patients with elevated levels of the IFN signaling genes showed better OS for patients receiving adjuvant anti-PD-1 (HR=0.6, CI=0.42-0.86, Log-rank test, p=0.0044). Conclusions: We identified a distinctive transcriptomic profile in LNM(+). Several genes were upregulated and associated with specific pathways. Using publicly available data, we demonstrated that STAT1, STAT2, IFI6, IFI30, and IFI44 gene signature correlated with improved OS for patients receiving adjuvant ICI treatment. The STAT1, STAT2, IFI6, IFI30, and IFI44 genes may represent new biomarkers to assess in biopsies of patients that will receive adjuvant or neoadjuvant ICI therapies. Citation Format: Matias A. Bustos, Shodai Mizuno, Suyeon Ryu, Dave S. Hoon. Transcriptomic signatures in melanoma lymph node metastasis that relate to immune oncology treatment [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6375.

A Clinical Decision Tool to Calculate Pretest Probability of Sentinel Lymph Node Metastasis in Primary Cutaneous Melanoma.

Although sentinel lymph node biopsy (SLNB) status is a strong prognostic indicator for cutaneous melanoma, unnecessary SLNBs have substantial cost and morbidity burden. This study was designed to develop, validate, and present a personalized, clinical, decision-making tool using nationally representative data with clinically actionable probability thresholds (Expected Lymphatic Metastasis Outcome [ELMO]). Data from the Surveillance, Epidemiology, and End Results (SEER) Registry from 2000 to 2017 and the National Cancer Database (NCDB) from 2004 to 2015 were used to develop and internally validate a logistic ridge regression predictive model for SLNB positivity. External validation was done with 1568 patients at a large tertiary referral center. The development cohort included 134,809 patients, and the internal validation cohort included 38,518 patients. ELMO (AUC 0.85) resulted in a 29.54% SLNB reduction rate and greater sensitivity in predicting SLNB status for T1b, T2a, and T2b tumors than previous models. In external validation, ELMO had an accuracy of 0.7586 and AUC of 0.7218. Limitations of this study are potential miscoding, unaccounted confounders, and effect modification. ELMO ( https://melanoma-sentinel.herokuapp.com/ ) has been developed and validated (internally and externally) by using the largest publicly available dataset of melanoma patients and was found to have high accuracy compared with other published models and gene expression tests. Individualized risk estimates for SLNB positivity are critical in facilitating thorough decision-making for healthcare providers and patients with melanoma.

AXL inhibition improves BRAF-targeted treatment in melanoma

More than half of metastatic melanoma patients receiving standard therapy fail to achieve a long-term survival due to primary and/or acquired resistance. Tumor cell ability to switch from epithelial to a more aggressive mesenchymal phenotype, attributed with AXLhigh molecular profile in melanoma, has been recently linked to such event, limiting treatment efficacy. In the current study, we investigated the therapeutic potential of the AXL inhibitor (AXLi) BGB324 alone or in combination with the clinically relevant BRAF inhibitor (BRAFi) vemurafenib. Firstly, AXL was shown to be expressed in majority of melanoma lymph node metastases. When treated ex vivo, the largest reduction in cell viability was observed when the two drugs were combined. In addition, a therapeutic benefit of adding AXLi to the BRAF-targeted therapy was observed in pre-clinical AXLhigh melanoma models in vitro and in vivo. When searching for mechanistic insights, AXLi was found to potentiate BRAFi-induced apoptosis, stimulate ferroptosis and inhibit autophagy. Altogether, our findings propose AXLi as a promising treatment in combination with standard therapy to improve therapeutic outcome in metastatic melanoma.

Machine learning directed sentinel lymph node biopsy in cutaneous head and neck melanoma.

The specificity of sentinel lymph node biopsy (SLNB) for detecting lymph node metastasis in head and neck melanoma (HNM) is low under current National Comprehensive Cancer Network (NCCN) treatment guidelines. Multiple machine learning (ML) algorithms were developed to identify HNM patients at very low risk of occult nodal metastasis using National Cancer Database (NCDB) data from 8466 clinically node negative HNM patients who underwent SLNB. SLNB performance under NCCN guidelines and ML algorithm recommendations was compared on independent test data from the NCDB (n=2117) and an academic medical center (n=96). The top-performing ML algorithm (AUC=0.734) recommendations obtained significantly higher specificity compared to the NCCN guidelines in both internal (25.8% vs. 11.3%, p < 0.001) and external test populations (30.1% vs. 7.1%, p < 0.001), while achieving sensitivity >97%. Machine learning can identify clinically node negative HNM patients at very low risk of nodal metastasis, who may not benefit from SLNB.

Melanocytic nevi in sentinel lymph nodes: association with cutaneous nevi and clinical relevance in patients with cutaneous melanomas

PurposeMelanocytic nevi in lymph nodes (NNs) are an important histological differential diagnosis of initial sentinel lymph node (SN) metastasis in melanoma. Our aim was to associate NN in SNs with clinicopathologic features and survival rates in 1, 250 patients with SN biopsy for melanoma.MethodsTo compare patients with present and absent NN, we used Fisher's exact test, Mann–Whitney U test, and multivariate logistic regression models in this retrospective observational study based on a prospectively maintained institutional database.ResultsNN prevalence in axillary, cervical, and groin SNs was 16.5%, 19.4%, and 9.8%, respectively. NN were observed in combination with all growth patterns of melanoma, but more frequently when the primary was histologically associated with a cutaneous nevus. We observed a decreasing NN prevalence with increasing SN metastasis diameter. Multiple logistic regression determined a significantly increased NN probability for SNs of the neck or axilla, for individuals with ≥ 50 cutaneous nevi, midline primary melanomas, and for individuals who reported non-cutaneous malignancies in their parents. Cancer in parents was also significantly more frequently reported by melanoma patients who had more than 50 cutaneous nevi. In SN-negative patients, NN indicated a tendency for slightly lower melanoma-specific survival.ConclusionsWe found a highly significant association between NN diagnosis and multiple cutaneous nevi and provided circumstantial evidence that cutaneous nevi in the drainage area of lymph nodes are particularly important. The trend toward lower melanoma-specific survival in SN-negative patients with NN suggests that careful differentiation of SN metastases is important.

27573 A clinical decision tool to calculate probability of sentinel lymph node metastasis in cutaneous melanoma

Objective: Sentinel lymph node status is a strong prognostic indicator for patients with cutaneous melanoma and is used to select patients for adjuvant therapy. However, unnecessary sentinel lymph node biopsy (SLNB) specimens have substantial cost and morbidity burden. Previous attempts to predict SLNB outcomes have relied on single-institution data and/or gene expression testing. Here we present Expected Lymphatic Metastasis Outcome (ELMO; https://melanoma-sentinel.herokuapp.com/), the first personalized clinical decision-making tool developed using nationally representative data with clinically actionable probability thresholds.

SERS-based DNA methylation profiling allows the differential diagnosis of malignant lymphadenopathy

This study highlights the potential of surface-enhanced Raman scattering (SERS) to differentiate between B-cell lymphoma (BCL), T-cell lymphoma (TCL), lymph node metastasis of melanoma (Met) and control (Ctr) samples based on the specific SERS signal of DNA extracted from lymph node tissue biopsy. Differences in the methylation profiles as well as the specific interaction of malignant and non-malignant DNA with the metal nanostructure are captured in specific variations of the band at 1005 cm−1, attributed to 5-methylcytosine and the band at 730 cm−1, attributed to adenine. Thus, using the area ratio of these two SERS marker bands as input for univariate classification, an area under the curve (AUC) of 0.70 was achieved in differentiating between malignant and non-malignant DNA. In addition, DNA from the BCL and TCL groups exhibited differences in the area of the SERS band at 730 cm−1, yielding an AUC of 0.84 in differentiating between these two lymphadenopathies. Lastly, using multivariate data analysis techniques, an overall accuracy of 94.7% was achieved in the differential diagnosis between the BCL, TCL, Met and Ctr groups. These results pave the way towards the implementation of SERS as a novel tool in the clinical setting for improving the diagnosis of malignant lymphadenopathy.

Fallen dogmas – recent advances in locoregionally advanced melanoma

Last decade brought new achievements in the melanoma research, which resulted in an important changes in the clinical management of stage III melanoma. The article summarizes recent updates with particular focus on practical aspects. Results from surgical studies, Multicenter Selective Lymphadenectomy Trial II (MSLT-II) and German Dermatologic Cooperative Oncology Group (DeCOG-SLT) proved that surgical dogmatic approach that all sentinel node melanoma metastasis warrants completion lymphadenectomy is no longer valid; omission of completion lymphadenectomy in large proportion of sentinel node positive melanoma patients has no negative impact on survival rates. Moreover oncological trials (COMBI-AD, EORTC 1325/KEYNOTE-054 and CheckMate 238) showed that in stage III melanoma patients' chances of recurrence-free survival can be improved by 10-20% by modern immunotherapy and/or molecular targeted therapy. These findings led to fall of another dogma in oncology: lack of effective adjuvant therapy for stage III melanoma at acceptable toxicity. At the end of the day in 2021 modern multidisciplinary approach incorporating newest findings offer stage III melanoma patients less surgical complications of better tailored surgery and longer survival in result of efficient adjuvant therapy.

CT diagnosis of ilioinguinal lymph node metastases in melanoma using radiological characteristics beyond size and asymmetry.

BackgroundDiagnosis of lymph node (LN) metastasis in melanoma with non-invasive methods is challenging. The aim of this study was to evaluate the diagnostic accuracy of six LN characteristics on CT in detecting melanoma-positive ilioinguinal LN metastases, and to determine whether inguinal LN characteristics can predict pelvic LN involvement.MethodsThis was a single-centre retrospective study of patients with melanoma LN metastases at a tertiary cancer centre between 2008 and 2016. Patients who had preoperative contrast-enhanced CT assessment and ilioinguinal LN dissection were included. CT scans containing significant artefacts obscuring the pelvis were excluded. CT scans were reanalysed for six LN characteristics (extracapsular spread (ECS), minimum axis (MA), absence of fatty hilum (FH), asymmetrical cortical nodule (CAN), abnormal contrast enhancement (ACE) and rounded morphology (RM)) and compared with postoperative histopathological findings.ResultsA total of 90 patients were included. Median age was 58 (range 23–85) years. Eighty-eight patients (98 per cent) had pathology-positive inguinal disease and, of these, 45 (51 per cent) had concurrent pelvic disease. The most common CT characteristics found in pathology-positive inguinal LNs were MA greater than 10 mm (97 per cent), ACE (80 per cent), ECS (38 per cent) and absence of RM (38 per cent). In multivariable analysis, inguinal LN characteristics on CT indicative of pelvic disease were RM (odds ratio (OR) 3.3, 95 per cent c.i. 1.2 to 8.7) and ECS (OR 4.2, 1.6 to 11.3). Cloquet’s node is known to be a poor predictor of pelvic spread. Pelvic LN disease was present in 50 per cent patients, but only 7 per cent had a pathology-positive Cloquet’s node.ConclusionAdditional CT radiological characteristics, especially ECS and RM, may improve diagnostic accuracy and aid clinical decisions regarding the need for inguinal or ilioinguinal dissection.

16613 PD-1, PD-L1, and BIM as predictors of sentinel lymph node metastasis in primary cutaneous melanoma

Here we tested whether the expression of the immune checkpoint program cell death protein 1 (PD-1), its ligand PD-L1, or its downstream effector Bcl-2 interacting mediator of cell death (BIM) in primary cutaneous melanoma (PCM) diagnostic biopsy tissue is associated with PCM metastasis to sentinel lymph nodes (SLN). We obtained a cohort of 754 patients with thin and intermediate thickness PCM who underwent SLN biopsy within 90 days of diagnosis. We then used real-time quantitative PCR to quantify gene expression in diagnostic biopsy tissue. We found that the expression of BIM but not PD-1 or PD-L1 was significantly associated with SLN metastasis (P = .004). The absence of a significant association between PD-1 and PD-L1 expression in PCM diagnostic biopsy tissue and SLN metastasis was confirmed by immunohistochemistry in a cohort subset. Predictive models that considered the clinicopathologic variables Breslow depth and age were not significantly improved by adding the gene expression variables BIM, PD-1, or PD-L1. In contrast, a highly significant improvement in the predictive ability among the 754 studied patients was observed with the CP-GEP model from SkylineDx. We conclude that while the PD-1/PD-L1 immune checkpoint drives immune tolerance and disease progression its global expression in PCM diagnostic biopsy tissue is not associated with regional metastasis.

CSIG-01. IDENTIFICATION OF PATHOGENESIS-RELEVANT microRNAs IN BRAIN METASTASIS

Abstract When brain metastasis develops, the prognosis of cancer is dismal. Insights into the biology of the primary cancer and the brain metastasis are necessary to inform more effective and targeted treatments. To study the role of microRNAs in brain metastasis, we performed differential expression profiling of 12 primary tumors and their paired brain metastases using smRNAseq (the 12 primary tumors included three non-small cell carcinomas, three melanomas, three endometrial carcinomas, one breast carcinoma, one thyroid carcinoma and one renal-cell carcinoma). To start, we identified microRNAs that were either highly upregulated or downregulated in the brain metastasis samples as compared to the paired primary tumors. After confirmation with real-time quantitative PCR, we further investigated the top microRNAs from both groups through functional assays performed in cell lines generated from primary melanoma, melanoma lymph node metastasis, and melanoma brain metastasis. From this top-down, patient sample to model cell-line approach we identified two microRNAs that are potentially important regulators in the development of brain metastasis. Characterization of their targets and their interactions may offer a therapeutic opportunity to improve the prognosis of patients with brain metastasis.

Validation of a clinicopathological and gene expression profile model for sentinel lymph node metastasis in primary cutaneous melanoma.

SummaryBackgroundThe Clinicopathological and Gene Expression Profile (CP‐GEP) model was developed to accurately identify patients with T1–T3 primary cutaneous melanoma at low risk for nodal metastasis.ObjectivesTo validate the CP‐GEP model in an independent Dutch cohort of patients with melanoma.MethodsPatients (aged ≥ 18 years) with primary cutaneous melanoma who underwent sentinel lymph node biopsy (SLNB) between 2007 and 2017 at the Erasmus Medical Centre Cancer Institute were eligible. The CP‐GEP model combines clinicopathological features (age and Breslow thickness) with the expression of eight target genes involved in melanoma metastasis (ITGB3, PLAT, SERPINE2, GDF15, TGFBR1, LOXL4, CXCL8 and MLANA). Using the pathology result of SLNB as the gold standard, performance measures of the CP‐GEP model were calculated, resulting in CP‐GEP high risk or low risk for nodal metastasis.ResultsIn total, 210 patients were included in the study. Most patients presented with T2 (n = 94, 45%) or T3 (n = 70, 33%) melanoma. Of all patients, 27% (n = 56) had a positive SLNB, with nodal metastasis in 0%, 30%, 54% and 16% of patients with T1, T2, T3 and T4 melanoma, respectively. Overall, the CP‐GEP model had a negative predictive value (NPV) of 90·5% [95% confidence interval (CI) 77·9–96.2], with an NPV of 100% (95% CI 72·2–100) in T1, 89·3% (95% CI 72·8–96·3) in T2 and 75·0% (95% CI 30·1–95·4) in T3 melanomas. The CP‐GEP indicated high risk in all T4 melanomas.ConclusionsThe CP‐GEP model is a noninvasive and validated tool that accurately identified patients with primary cutaneous melanoma at low risk for nodal metastasis. In this validation cohort, the CP‐GEP model has shown the potential to reduce SLNB procedures in patients with melanoma.

Diagnostic Value of Real-Time Elastography in Diagnosing Lymph Node Metastasis of Skin Cancer.

ObjectiveThe purpose of this study was to examine the diagnostic performance of real-time tissue elastography in detecting lymph node involvement in skin cancers.MethodologyWe retrospectively analyzed B-mode sonography and real-time elastography (RTE) images of 70 lymph nodes from 34 patients diagnosed with squamous cell carcinoma (SCC) or malignant melanoma (MM). In the B-mode examination, the appearance or loss of the hilar architecture in the lymph node, contour lobulation, and the presence of focal cortical thickening were evaluated. Elastography scores were classified according to the ratio of soft and hard areas across the lymph node on a 4-point scale system. Largely soft lymph nodes were scored as “1” and largely hard lymph nodes were scored as “4”.ResultsWhen patients with SCC and MM were evaluated together, the sensitivity of elastography was 94%, specificity was 70%, and the accuracy rate was 86% in detecting lymph node involvement. When both tumor groups were evaluated separately, for SCC, the sensitivity of elastography was 90%, specificity was 61%, and the accuracy rate was 80% in detecting lymph node involvement. When the receiver operating characteristic (ROC) curve was taken, the area under the curve (AUC) was 0.78 for SCC. Elastography showed full compliance with pathology in lymph node metastases of MM and the AUC was 1.00.ConclusionsBased on our findings, RTE provides important contributions to B-mode ultrasonography (USG) in evaluating lymph node metastases of skin cancers.

Evaluation of accuracy for 18 F-FDG positron emission tomography and computed tomography for detection of lymph node metastasis in canine oral malignant melanoma.

Tumour stage has been demonstrated to have prognostic significance in canine oral malignant melanoma (OMM). Various evaluation techniques of positron emission tomography/computed tomography (PET/CT) have been reported for staging of head-and-neck tumours in people, but canine-specific data are limited, and reports for CT accuracy have been variable. In this prospective study, the head/neck of client-owned dogs with cytologically or histologically diagnosed OMM were imaged with 18 Fluorine-fluorodeoxyglucose (18 F-FDG) PET/ CT. Bilateral mandibular lymphadenectomy was performed for histopathologic assessment. Two evaluation techniques for CT and PET were applied by four independent observers. CT evaluation utilized both a standardized grading scheme and a subjective clinical interpretation. PET evaluation was first performed solely on 18 F-FDG-uptake in lymph nodes compared to background on a truncated scan excluding the oral cavity. Subsequently, the entire head/neck scan and standardized uptake value (SUV) measurements were available. Receiver operating characteristic analysis was performed with histopathology as gold standard. Twelve dogs completed the study and metastatic OMM was identified in six mandibular lymph nodes from five dogs. Of the CT-interpretation techniques, use of clinical grading performed best (sensitivity=83% and specificity=94%). Both PET techniques resulted in 100% sensitivity, but primary tumour site evaluation and use of SUV increased specificity from 78% to 94%. The SUVmax cut-point, 3.3, led to 100% sensitivity and 83% specificity. In this population of dogs, PET appeared to be highly sensitive but at risk of being less specific without use of appropriate parameters and thresholds.