A Prediction Model to Discriminate Small Choroidal Melanoma from Choroidal Nevus

Objective: To develop a validated machine learning model to diagnose small choroidal melanoma. Design: Cohort study Subjects, Participants, and/or Controls: The training data included 123 patients diagnosed as small choroidal melanocytic tumor (5.0-16.0 mm in largest basal diameter and 1.0 mm to 2.5 mm in height; Collaborative Ocular Melanoma Study criteria). Those diagnosed as melanoma (n=61) had either documented growth or pathologic confirmation. 62 patients with stable lesions classified as choroidal nevus, were used as negative controls. The external validation data set included 240 patients managed at a different tertiary clinic, also with small choroidal melanocytic tumor, observed for malignant growth. Methods: In the training data, lasso logistic regression was used to select variables for inclusion in the final model for the association with melanoma versus choroidal nevus. Internal and external validation were performed to assess model performance. Main Outcome Measures: Predicted probability of small choroidal melanoma Results: Distance to optic disc ≥3mm and drusen were associated with decreased odds of melanoma whereas male versus female sex, increased height, subretinal fluid, and orange pigment were associated with increased odds of choroidal melanoma. The area under the receiver operating characteristic (AUROC) “discrimination value” for this model was 0.880. The top four variables that were most frequently selected for inclusion in the model on internal validation, implying their importance as predictors of melanoma, were subretinal fluid, height, distance to optic disc, and orange pigment. When tested against the validation data, the prediction model could distinguish between choroidal nevus and melanoma with high discrimination of 0.861. The final prediction model was converted into an online calculator to generate predicted probability of melanoma. Conclusions: To minimize diagnostic uncertainty, a machine learning based diagnostic prediction calculator can be readily applied for decision making and counselling patients with small choroidal melanoma.

Cutaneous Melanocytic Tumor with CRTC1::TRIM11 Fusion: Review of the Literature of a Potentially Novel Entity

“Cutaneous melanocytic tumor with CRTC1::TRIM11 fusion” (CMTCT) is a recently described entity belonging to the family of superficial tumors displaying melanocytic differentiation. Thirteen cases have been reported so far, on the head and neck, extremities, and trunk of adults of all ages (12 cases) and one in an 11-year-old child. Histopathologically, it is a nodular or multilobulated tumor composed of spindle and epithelioid cells arranged in nests, fascicles, or bundles that are surrounded by thin collagenous septa. By immunohistochemistry, the tumor shows variable immunoreactivity for S100-protein, SOX10, and MITF, as well as specific melanocytic markers such as MelanA and HMB-45. The neoplasm’s biologic behavior remains uncertain since the reported cases are limited and the follow-up is short (median 12 months). However, local recurrence and synchronous distant metastasis after 13 years of initial resection has been described in one case. Herein, we present a comprehensive literature review of CMTCT hoping to raise awareness among the dermatopathologists of this potentially novel entity.

Quantitative Multispectral Imaging Differentiates Melanoma from Seborrheic Keratosis

Melanoma is a melanocytic tumor that is responsible for the most skin cancer-related deaths. By contrast, seborrheic keratosis (SK) is a very common benign lesion with a clinical picture that may resemble melanoma. We used a multispectral imaging device to distinguish these two entities, with the use of autofluorescence imaging with 405 nm and diffuse reflectance imaging with 525 and 660 narrow-band LED illumination. We analyzed intensity descriptors of the acquired images. These included ratios of intensity values of different channels, standard deviation and minimum/maximum values of intensity of the lesions. The pattern of the lesions was also assessed with the use of particle analysis. We found significantly higher intensity values in SKs compared with melanoma, especially with the use of the autofluorescence channel. Moreover, we found a significantly higher number of particles with high fluorescence in SKs. We created a parameter, the SK index, using these values to differentiate melanoma from SK with a sensitivity of 91.9% and specificity of 57.0%. In conclusion, this imaging technique is potentially applicable to distinguish melanoma from SK based on the analysis of various quantitative parameters. For this application, multispectral imaging could be used as a screening tool by general physicians and non-experts in the everyday practice.

Pigmented Epithelioid Melanocytoma: Case Report

Pigmented epithelioid melanocytoma is a rare, newly described melanocytic tumor that encompasses lesions previously classified as animal type melanomas and epithelioid blue nevus of the Carney complex. Pigmented epithelioid melanocytoma is a specific clinicopathological entity with particular clinical presentation and histological features. We present the case of a 5 year old female patient with a heavily pigmented papule on her right thigh that showed histological findings compatible with pigmented epithelioid melanocytoma and discuss the relevance /clinical significance of sentinel lymph node biopsy as a staging procedure in this particular neoplasm.

Expanding spectrum of “spitzoid” lesions: a small series of 4 cases with MAP2K1 mutations

The molecular background of a significant proportion of spitzoid neoplasms is still unknown. Recently, activating mutations in MAP2K1 have been described in a few spitzoid lesions, but not in benign Spitz nevi. We report four cases of melanocytic tumors with spitzoid features in which a MAP2K1 mutation was detected. The lesions did not show a single distinct phenotype and ranged from benign to malignant. Two cases resembled desmoplastic Spitz nevi. Based on the combination of morphological, immunohistochemical, and molecular findings, one case was classified as benign, one as probably benign, possibly intermediate low-grade (MELTUMP—melanocytic tumor of unknown malignant potential), one case was classified as intermediate (MELTUMP), and one case was considered a superficial spreading melanoma with spitzoid features. Based on this, we conclude that MAP2K1 mutations can indicate a spitzoid genetic signature and can be found in both benign and malignant spitzoid neoplasms.