Morphologic Mimickers of Seborrheic Keratoses: Cutaneous Lesions Masquerading as Seborrheic Keratoses

Diep, Darlene; Calame, Antoanella; Cohen, Philip R.

doi:10.7759/cureus.18559

Cited by 3 publications

(3 citation statements)

References 21 publications

(125 reference statements)

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“…The histopathologic findings include a papillomatous or verrucous-like epidermis, dermal capillaries being enlarged, pseudo horn cysts and intraepidermal cysts [ 11 ]. Seborrheic keratosis shows varied clinical and histopathological subtypes such as hyperkeratotic, acanthotic, reticular type, clonal variant, irritated SK, melanoacanthoma and features resembling verrucous SK with keratoacanthoma [ 12 ].…”

Section: Discussionmentioning

confidence: 99%

Perioral Clonal Variant of Seborrheic Keratosis: Diagnostic Challenges

K¹,

M²,

Ramya³

et al. 2023

Cureus

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Seborrheic keratosis is the most common benign tumour of epithelial origin, whose incidence increases with the advance of age. The aetiology of SK is not completely known but exposure to UV radiation may be an associated factor. Most of the cases have a rough, verrucous appearance, slightly elevated, and black or brown in colour. They are usually painless but at times present with pus discharge or ulceration.

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Section: Discussionmentioning

confidence: 99%

Perioral Clonal Variant of Seborrheic Keratosis: Diagnostic Challenges

K¹,

M²,

Ramya³

et al. 2023

Cureus

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“…Additionally, SK may show exophytic or hyperplastic growth [ 2 , 3 , 4 ]. Due to their high variability in clinical and dermatoscopic presentation, SKs are frequently excised to exclude malignant cutaneous tumors [ 5 ]. Bowen’s disease (BD) is a cutaneous squamous cell carcinoma in situ and one of the most frequent malignant tumors worldwide.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of a Deep Learning Approach to Differentiate Bowen’s Disease and Seborrheic Keratosis

Jansen

Baguer

Duschner

et al. 2022

Cancers

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Background: Some of the most common cutaneous neoplasms are Bowen’s disease and seborrheic keratosis, a malignant and a benign proliferation, respectively. These entities represent a significant fraction of a dermatopathologists’ workload, and in some cases, histological differentiation may be challenging. The potential of deep learning networks to distinguish these diseases is assessed. Methods: In total, 1935 whole-slide images from three institutions were scanned on two different slide scanners. A U-Net-based segmentation deep learning algorithm was trained on data from one of the centers to differentiate Bowen’s disease, seborrheic keratosis, and normal tissue, learning from annotations performed by dermatopathologists. Optimal thresholds for the class distinction of diagnoses were extracted and assessed on a test set with data from all three institutions. Results: We aimed to diagnose Bowen’s diseases with the highest sensitivity. A good performance was observed across all three centers, underlining the model’s robustness. In one of the centers, the distinction between Bowen’s disease and all other diagnoses was achieved with an AUC of 0.9858 and a sensitivity of 0.9511. Seborrheic keratosis was detected with an AUC of 0.9764 and a sensitivity of 0.9394. Nevertheless, distinguishing irritated seborrheic keratosis from Bowen’s disease remained challenging. Conclusions: Bowen’s disease and seborrheic keratosis could be correctly identified by the evaluated deep learning model on test sets from three different centers, two of which were not involved in training, and AUC scores > 0.97 were obtained. The method proved robust to changes in the staining solution and scanner model. We believe this demonstrates that deep learning algorithms can aid in clinical routine; however, the results should be confirmed by qualified histopathologists.

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“…There are several clinical morphologies with corresponding pathologic changes. Occasionally malignant tumors, such as squamous cell carcinoma and melanoma, masquerade as a seborrheic keratosis, especially those that are hyperpigmented, reticular, or irritated [1].…”

Section: Introductionmentioning

confidence: 99%