In vivo identification of amyloid and mucin in basal cell carcinoma with combined reflectance confocal microscopy-optical coherence tomography device and direct histopathologic correlation

Seeing beyond skin deep: High-resolution ultrasound in dermatology-A comprehensive review and future prospects

High-resolution ultrasound (HRUS), operating at frequencies of 20-25 MHz, is a non-invasive imaging tool that offers dermatologists the ability to visualize structures beneath the skin surface. The objective of this review is to present a comprehensive overview of HRUS applications, emphasising its utility in diagnosing, characterising and managing various dermatological conditions. We undertook a comprehensive literature review on the dermatological application of HRUS across Medline, Embase and Cochrane Library databases, while also incorporating our own clinical experience of over 16 years with the tool. In normal skin, the epidermis and dermis are hyperechoic, and the subcutaneous layer is hypoechoic. Basal cell carcinomas appear hypoechoic with irregular margins, while the presence of hyperechoic inclusion bodies suggests aggressive pathology. Squamous cell carcinomas pose challenges due to acoustic shadow artefacts from the thickened stratum corneum. Melanomas are homogenous hypoechoic lesions, with HRUS used to accurately predict Breslow thickness. HRUS provides dermatologists with a valuable adjunct to traditional clinical examination. Future advancement in image resolution and the standardisation of diagnostic parameters may further expand its utility.

In Vivo Characterization of Mucin and Amyloid Deposits in Primary Basal Cell Carcinoma through Reflectance Confocal Microscopy: A Correlation with Histopathology

Basal cell carcinoma (BCC) is the most common keratinocyte carcinoma and the most prevalent skin cancer in humans, worldwide. BCC is histologically characterized by the proliferation of basaloid cells, arranged in globular masses of varying size, often separated from the surrounding stroma by optically empty spaces. Although attributed to tumor retraction during tissue processing for the preparation of pathology slides, these spaces are also seen on cryostat sections. The aim of this study is to in vivo characterize amyloid and mucin deposits in primary BCC lesions through RCM, followed by histopathological correlation. We included twenty-two consecutive subjects totaling thirty-one primary BCCs. Each lesion underwent the same evaluation protocol which included: clinical and dermoscopic images, RCM imaging, excisional biopsy under local anesthesia, and histopathological examination (colloidal iron and cytokeratin 34betaE12 stains). Hypo-reflective peritumoral clefts and hyper-reflective globules were measured on RCM images and compared to mucin and amyloid deposits seen on histology slides. The mean differences between RCM and histology measurements in both mucin and amyloid were not statistically significant. There were medium and strong correlations between RCM and histology regarding mucin and amyloid deposits, respectively.

Nodular and Micronodular Basal Cell Carcinoma Subtypes Are Different Tumors Based on Their Morphological Architecture and Their Interaction with the Surrounding Stroma

Basal cell carcinoma (BCC) is the most frequent cancer of the skin and comprises low-risk and high-risk subtypes. We selected a low-risk subtype, namely, nodular (N), and a high-risk subtype, namely, micronodular (MN), with the aim to identify differences between them using a classical morphometric approach through a gray-level co-occurrence matrix and histogram analysis, as well as an approach based on deep learning semantic segmentation. From whole-slide images, pathologists selected 216 N and 201 MN BCC images. The two groups were then manually segmented and compared based on four morphological areas: center of the BCC islands (tumor, T), peripheral palisading of the BCC islands (touching tumor, TT), peritumoral cleft (PC) and surrounding stroma (S). We found that the TT pattern varied the least, while the PC pattern varied the most between the two subtypes. The combination of two distinct analysis approaches yielded fresh insights into the characterization of BCC, and thus, we were able to describe two different morphological patterns for the T component of the two subtypes.

Angulated small nests and cords: Key diagnostic histopathologic features of infiltrative basal cell carcinoma can be identified using integrated reflectance confocal microscopy-optical coherence tomography

BACKGROUND

Accurate basal cell carcinoma (BCC) subtyping is requisite for appropriate management, but non-representative sampling occurs in 18% to 25% of biopsies. By enabling non-invasive diagnosis and more comprehensive sampling, integrated reflectance confocal microscopy-optical coherence tomography (RCM-OCT) may improve the accuracy of BCC subtyping and subsequent management. We evaluated RCM-OCT images and histopathology slides for the presence of two key features, angulation and small nests and cords, and calculated (a) sensitivity and specificity of these features, combined and individually, for identifying an infiltrative BCC subtype and (b) agreement across modalities.

METHODS

Thirty-three RCM-OCT-imaged, histopathologically-proven BCCs (17 superficial and/or nodular; 16 containing an infiltrative component) were evaluated.

RESULTS

The presence of angulation or small nests and cords was sufficient to identify infiltrative BCC on RCM-OCT with 100% sensitivity and 82% specificity, similar to histopathology (100% sensitivity, 88% specificity, kappa = 0.82). When both features were present, the sensitivity for identifying infiltrative BCC was 100% using either modality and specificity was 88% on RCM-OCT vs 94% on histopathology, indicating near-perfect agreement between non-invasive and invasive diagnostic modalities (kappa = 0.94).

CONCLUSIONS

RCM-OCT can non-invasively identify key histopathologic features of infiltrative BCC offering a possible alternative to traditional invasive biopsy.

Line-field confocal optical coherence tomography of basal cell carcinoma: a descriptive study

BACKGROUND

Early diagnosis and subtype classification of basal cell carcinoma (BCC) are crucial to reduce morbidity and optimize treatment. Good accuracy in differentiating BCC from clinical imitators has been achieved with existing diagnostic strategies but lower performance in discriminating BCC subtypes. Line-field confocal optical coherence tomography (LC-OCT) is a new technology able to combine the technical advantages of reflectance confocal microscopy and OCT.

OBJECTIVES

To identify and describe LC-OCT criteria associated with BCC and explore their association with BCC subtypes.

METHODS

Basal cell carcinoma were imaged with a handheld LC-OCT device before surgical excision. LC-OCT images were retrospectively evaluated by three observers for presence/absence of criteria for BCC. Multivariate logistic regression models were used to find independent predictors of BCC subtypes.

RESULTS

Eighty-nine histopathologically proven BCCs were included, of which 66 (74.2%) were pure subtypes [superficial BCC (sBCC): 19/66 (28.8%); nodular BCC (nBCC): 31/66 (47.0%); infiltrative BCC (iBCC): 16/66 (24.2%)]. Lobules, blood vessels and small bright cells within epidermis/lobules were the most frequent criteria for BCC. LC-OCT criteria independently associated with sBCC were presence of hemispheric lobules, absence of lobule separation from the epidermis, absence of stretching of the stroma; with nBCC were presence of macrolobules, absence of lobule connection to the epidermis; and with iBCC were presence of branched lobules.

CONCLUSIONS

This was the first study describing the characteristics of BCC under LC-OCT examination. We proposed morphologic criteria, which could be potentially useful for diagnosis and subtype classification of BCC, as well as for its therapeutic management. Future studies are needed to assess these hypotheses.