Collision skin lesions-results of a multicenter study of the International Dermoscopy Society (IDS)

A Rare Case of a Primary Cutaneous Collision Tumor Comprising Malignant Melanoma and Rhabdomyosarcoma

This case reports a 35-year-old man who presented with a painful erythematous nodule on his right posterior calf. He first noticed this nodule several years ago and it often bled upon contact with clothing. An excisional biopsy of the skin lesion revealed two distinct populations of cells. One population of epithelioid cells stained positive for Mart-1, HMB45, and SOX-10, confirming the diagnosis of malignant melanoma. The second population of cells stained positive for desmin and calponin, confirming the diagnosis of sarcoma with muscular differentiation. Subsequently, these unusual findings led to the diagnosis of a collision tumor comprising malignant melanoma and rhabdomyosarcoma. Follow-up PET/CT and brain MRI revealed no metastasis from the primary skin lesion. This case highlights a rare combination of cell types found within a collision tumor in addition to providing details on how to diagnose this skin lesion.

[Collision tumours in skin: usually an incidental finding. A retrospective study with literature revision]

A collision tumour (CT) is a neoplastic lesion comprised of two or more distinct cell populations that maintain distinct borders. Mostly, these are incidental findings in skin biopsies, whose pathologic mechanism and prevalence remain unknown, with few references among literature. Here, we present a retrospective study of CT, diagnosed by a dermatopathologist in our hospital between 2019-2022. Lesions have been defined individually and organized into three categories: benign-benign (BB), benign-malignant (BM) and malignant-malignant (MM). A total of 108 CT were diagnosed (1,4% of the biopsies from the dermatopathologist during this period), from which BM was the most frequent collision (48,5%). Globally, basal cell carcinoma (BCC) was the main malignant lesion and melanocytic nevus (MN) the main benign lesion. We have used the software Stata 14.2 in order to analyse results, and we have detected a statistically significant difference between age and collision type.

Use of Dermatoscopy in Lesions Suspicious for Melanoma: Two Case Reports

Abstract is missing (Short communication)

Combined tumour of aberrant cytokeratin expressing acral lentiginous melanoma and poroma: Diagnostic challenge

Combined tumours are uncommon and therefore these tumours may pose a diagnostic challenge. In the current case report, it is aimed to present the clinicopathological features of a combined tumour including melanoma with aberrant cytokeratin expression and poroma.

Observational study investigating the level of support from a convolutional neural network in face and scalp lesions deemed diagnostically 'unclear' by dermatologists

BACKGROUND

The clinical diagnosis of face and scalp lesions (FSL) is challenging due to overlapping features. Dermatologists encountering diagnostically 'unclear' lesions may benefit from artificial intelligence support via convolutional neural networks (CNN).

METHODS

In a web-based classification task, dermatologists (n = 64) diagnosed a convenience sample of 100 FSL as 'benign', 'malignant', or 'unclear' and indicated their management decisions ('no action', 'follow-up', 'treatment/excision'). A market-approved CNN (Moleanalyzer-Pro®, FotoFinder Systems, Germany) was applied for binary classifications (benign/malignant) of dermoscopic images.

RESULTS

After reviewing one dermoscopic image per case, dermatologists labelled 562 of 6400 diagnoses (8.8%) as 'unclear' and mostly managed these by follow-up examinations (57.3%, n = 322) or excisions (42.5%, n = 239). Management was incorrect in 58.8% of 291 truly malignant cases (171 'follow-up' or 'no action') and 43.9% of 271 truly benign cases (119 'excision'). Accepting CNN classifications in unclear cases would have reduced false management decisions to 4.1% in truly malignant and 31.7% in truly benign lesions (both p < 0.01). After receiving full case information 239 diagnoses (3.7%) remained 'unclear' to dermatologists, now triggering more excisions (72.0%) than follow-up examinations (28.0%). These management decisions were incorrect in 32.8% of 116 truly malignant cases and 76.4% of 123 truly benign cases. Accepting CNN classifications would have reduced false management decisions to 6.9% in truly malignant lesions and to 38.2% in truly benign cases (both p < 0.01).

CONCLUSIONS

Dermatologists mostly managed diagnostically 'unclear' FSL by treatment/excision or follow-up examination. Following CNN classifications as guidance in unclear cases seems suitable to significantly reduce incorrect decisions.

Squamomelanocytic Tumors: A Singular Case Report and Comprehensive Review

Cutaneous neoplasms from different cell types can exist within the same lesion. These can be classified into four subtypes which are collision tumour, combined tumour, colonization and biphenotypic tumour. The presence of a melanoma component in these tumours is very rare. Herein we present a singular case of two synchronous dineoplastic cutaneous tumours: a squamomelanocytic tumour and a collision consisting of melanoma and seborrheic keratosis. Additionally, we performed a literature review of all squamomelanocytic tumours published until date, including our case.

Clinical-Dermoscopic-Histopathological Correlations in Collision Skin Tumours

Objectives

Collision tumours are rare situations characterised by the coincidence of two different skin neoplasms in the same lesion.

Methods

We have analyzed 41 collision skin tumours from one department in the clinical-dermoscopic-histopathologic correlations.

Results

We present 41 collisions tumours. The mean age of our patients was 67.9 years, the mean diameter of the lesion was 11.6 mm. The most frequent locations were trunk (27 lesions) and head/neck (11 lesions). The collisions were classified as benign/benign (13 cases), benign/malignant (25 cases) and malignant/malignant (3 cases). The most frequent participants were seborrheic keratosis (24 cases), malignant melanoma (17 cases), melanocytic nevus (14 cases), basal cell carcinoma (12 cases) and heamangioma (10 cases). Thirty cases were of "dominant/minor" type and 11 cases of "half to half" type. Malignant tumours were a part of 28 collisions; these lesions were larger, patients were older and the malignant part was dominant in most cases. More than half of the collisions were unexpected by the initial clinical examination. Six collisions were missed by the initial histopathological examination.

Conclusions

Collision tumours can be missed by clinical or even histopathological examination. Dermoscopy is very helpful in the recognizing of difficult cases and cooperating with the histopathologist.

The Usefulness of Dermoscopy for the Recognition of Malignant Collision Tumors

BACKGROUND

Preoperative diagnosis of malignant collision tumors (MCT) is extremely difficult. The value of dermoscopy to improve the correct detection of these tumors has not been previously studied. This study aims to evaluate the diagnostic accuracy of MCT with and without dermoscopy and to describe the dermoscopic features of a large series of MCT.

METHODS

Dermoscopic images of 161 MCT were evaluated. Clinical and dermoscopic images of histopathologically proven MCT intermingled with other tumors were randomly presented to clinicians with different levels of experience, blinded to the diagnosis and objective of the study. The clinical and dermoscopic diagnostic accuracies were measured separately.

RESULTS

A total of 161 histopathologically proven cases of MCT were collected. The most frequent MCT was basal cell carcinoma-seborrheic keratosis collision tumor (CT; 37.9%), followed by basal cell carcinoma-melanocytic nevus CT (19.9%), and melanoma-seborrheic keratosis CT (6.8%). Diagnostic accuracy among experts on dermoscopy was 71.4%. The study included 119 participants. The percentage of correct diagnoses was 8% by naked eye examination and 36.4% by dermoscopy (p < 0.001). The presence of the malignant component in the cases of MCT was not recognizable in 19.1% of cases by naked eye examination and in 11.8% of cases by dermoscopy (p < 0.001).

CONCLUSIONS

The diagnosis of MCT can be assisted and clarified by dermoscopy. However, many of these lesions manifest complex morphologies and continue to be challenging, even for experts on dermoscopy. Atypical, uncertain, or non-classifiable lesions still need a complete excision for the final diagnosis.

Skin lesions of face and scalp - Classification by a market-approved convolutional neural network in comparison with 64 dermatologists

BACKGROUND

The clinical differentiation of face and scalp lesions (FSLs) is challenging even for trained dermatologists. Studies comparing the diagnostic performance of a convolutional neural network (CNN) with dermatologists in FSL are lacking.

METHODS

A market-approved CNN (Moleanalyzer-Pro, FotoFinder Systems) was used for binary classifications of 100 dermoscopic images of FSL. The same lesions were used in a two-level reader study including 64 dermatologists (level I: dermoscopy only; level II: dermoscopy, clinical close-up images, textual information). Primary endpoints were the CNN's sensitivity and specificity in comparison with the dermatologists' management decisions in level II. Generalizability of the CNN results was tested by using four additional external data sets.

RESULTS

The CNN's sensitivity, specificity and ROC AUC were 96.2% [87.0%-98.9%], 68.8% [54.7%-80.1%] and 0.929 [0.880-0.978], respectively. In level II, the dermatologists' management decisions showed a mean sensitivity of 84.2% [82.2%-86.2%] and specificity of 69.4% [66.0%-72.8%]. When fixing the CNN's specificity at the dermatologists' mean specificity (69.4%), the CNN's sensitivity (96.2% [87.0%-98.9%]) was significantly higher than that of dermatologists (84.2% [82.2%-86.2%]; p < 0.001). Dermatologists of all training levels were outperformed by the CNN (all p < 0.001). In confirmation, the CNN's accuracy (83.0%) was significantly higher than dermatologists' accuracies in level II management decisions (all p < 0.001). The CNN's performance was largely confirmed in three additional external data sets but particularly showed a reduced specificity in one Australian data set including FSL on severely sun-damaged skin.

CONCLUSIONS

When applied as an assistant system, the CNN's higher sensitivity at an equivalent specificity may result in an improved early detection of face and scalp skin cancers.

Multiple Skin Neoplasms at One Site (MUSK IN A NEST): A Comprehensive Review of Basal Cell Carcinoma and Benign or Malignant "Collision" Tumors at the Same Cutaneous Location

Multiple skin neoplasms at one site (MUSK IN A NEST), initially referred to as a collision tumor, describes the occurrence of two or more benign or malignant neoplasms that are adjacent or intermingled at the same cutaneous site. A mononeoplastic cutaneous tumor refers to a single tumor at any cutaneous site. Two, three, four, five, and six tumors at the same site are described as dineoplastic, trineoplastic, tetraneoplastic, pentaneoplastic, and hexaneoplastic cutaneous tumors, respectively; the prefixes are based on the numerical multiplier used by the International Union of Pure and Applied Chemistry (IUPAC). MUSK IN A NEST can be classified based upon their mechanism of pathogenesis-either being composed of mixed clones of cells (clonalium, which has three subtypes: collision, colonization, and combination) or the same clone of cells that has undergone clonal evolution (clonalidem, which has one subtype: biphenotypic). Basal cell carcinoma (BCC)-associated MUSK IN A NEST can be observed with either benign tumors, malignant tumors, or both. Nevi and seborrheic keratoses are the most common benign tumors associated with BCC; melanoma in situ and invasive melanoma are the most commonly reported malignant tumors associated with BCC. The definitive etiology of BCC-associated MUSK IN A NEST remains to be established-whether the development of the BCC at that site occurs as a direct or indirect consequence of the coexisting neoplasm or whether the occurrence of the BCC and the other neoplasm is merely the result of a coincidental juxtaposition of the tumors.

Collision tumors: A review of their types, pathogenesis, and diagnostic challenges

A collision tumor is a neoplastic lesion comprised of two or more distinct cell populations that maintain distinct borders. Collision tumors, which are rare but well documented, can be composed of two benign tumors, a benign and malignant tumor, and two malignant tumors. Although case reports and reviews on specific types of collision tumors exist, a cohesive source discussing these tumors is lacking. We critically reviewed the literature by analyzing case reports and retrospective studies in order to evaluate the following regarding collision tumors: definitions, types, pathogenesis, diagnosis, and management. Reports of these tumors are infrequent but not insignificant, and accurate classification and diagnosis will lead to better patient outcomes.

Treatment of Actinic Keratoses Facilitates Dermatoscopic Diagnosis of Early Basal Cell Carcinoma: A Case Report and Review

Chronic exposure to ultraviolet radiation induces gradual changes in cutaneous morphology, which with increasing damage leads to the appearance of cancerous skin lesions. Among them, basal cell carcinomas (BCCs) and actinic keratoses (AKs) are the most common entities. Both lesions often develop as two separate lesions in a single individual at a conspicuous distance, close proximity or as collision lesions, which are characterized by the coexistence of both cancers in the same anatomical site. Collision lesions in which AK precisely overlies BCC is a rarely reported entity. We report a case where the presence of BCC was dermatoscopically detected after an overlying AK was treated with topical chemotherapy, thus indicating that treatment of AK allows better visualization of other underlying malignancies.