Background. Basal cell carcinoma (BCC) is the most common skin cancer in the general population. Treatments vary from Mohs surgery to topical therapy, depending on the subtype. Dermoscopy, reflectance confocal microscopy (RCM) and optical coherence tomography (OCT) have gained a foothold in daily clinical practice to optimize diagnosis and subtype-oriented treatment. The new technique of line-field confocal OCT (LC-OCT) allows imaging at high resolution and depth, but its use has not yet been investigated in larger studies. Aim. To evaluate the main LC-OCT criteria for the diagnosis and subtyping of BCC compared with histopathology, OCT and RCM. Methods. In total, 52 histopathologically confirmed BCCs were evaluated for imaging criteria. Their frequency, predictive values and ROC curves were calculated. A multinominal regression with stepwise variables selection to distinguish BCC subtypes was performed. Results. Nodular BCCs were mainly characterized by atypical keratinocytes, altered dermoepidermal junction (DEJ), tumour nests in the dermis, dark clefting, prominent vascularization and white hyper-reflective stroma. Superficial BCCs showed a thickening of the epidermis due to a series of tumour lobules with clear connection to the DEJ (string of pearls pattern). Infiltrative BCCs were characterized by elongated hyporeflective tumour strands, surrounded by bright collagen (shoal of fish pattern). The overall BCC subtype agreement between LC-OCT and conventional histology was 90.4% (95% CI 79.0-96.8). Conclusion. LC-OCT allows noninvasive, real-time identification of BCCs and their subtypes in vertical, horizontal and three-dimension mode compared with histology, RCM and OCT. Further larger studies are needed to better explore the clinical applications of this promising device.
Background The treatment of keratinocyte cancers (KC) strictly depends on their differentiation and invasiveness. Non‐invasive diagnostic techniques can support the diagnosis in real time, avoiding unnecessary biopsies. This study aimed to preliminarily define main imaging criteria and histological correlations of actinic keratosis (AK), Bowen’s disease (BD) and squamous cell carcinoma (SCC) using the novel device line‐field confocal optical coherence tomography (LC‐OCT). Methods Dermoscopy and LC‐OCT images of 73 histopathologically confirmed lesions (46 AKs, 11 BD and 16 SCCs) were included in the study. Exemplary lesions (10 AKs, 5 BD and 5 SCCs) were additionally investigated with optical coherence tomography and reflectance confocal microscopy. Results Most common LC‐OCT findings of KC in the descriptive statistics were hyperkeratosis/parakeratosis, disruption of stratum corneum, broadened epidermis, basal and suprabasal keratinocyte atypia, dilated vessels/neoangiogenesis and elastosis/collagen alterations. In the univariate multinomial logistic regression, a preserved DEJ was less common in SCC compared with AK and BD, BD displayed marked keratinocyte atypia involving all epidermal layers (bowenoid pattern), while SCC showed ulceration, increased epidermal thickness, keratin plugs, acantholysis, not visible/interrupted DEJ and epidermal bright particles. LC‐OCT increased the diagnostic confidence by 24.7% compared with dermoscopy alone. Conclusions Our study describes for the first time specific LC‐OCT features of different stages of KC and their histopathological correlates, focusing on keratinocyte morphology and architecture of the epidermis and DEJ. LC‐OCT may open new scenarios in the bedside diagnosis, treatment planning and follow‐up of KC.
Until now, the clinical differentiation between a nevus and a melanoma is still challenging in some cases. Line-field confocal optical coherence tomography (LC-OCT) is a new tool with the aim to change that. The aim of the study was to evaluate LC-OCT for the discrimination between nevi and melanomas. A total of 84 melanocytic lesions were examined with LC-OCT and 36 were also imaged with RCM. The observers recorded the diagnoses, and the presence or absence of the 18 most common imaging parameters for melanocytic lesions, nevi, and melanomas in the LC-OCT images. Their confidence in diagnosis and the image quality of LC-OCT and RCM were evaluated. The most useful criteria, the sensitivity and specificity of LC-OCT vs. RCM vs. histology, to differentiate a (dysplastic) nevus from a melanoma were analyzed. Good image quality correlated with better diagnostic performance (Spearman correlation: 0.4). LC-OCT had a 93% sensitivity and 100% specificity compared to RCM (93% sensitivity, 95% specificity) for diagnosing a melanoma (vs. all types of nevi). No difference in performance between RCM and LC-OCT was observed (McNemar’s p value = 1). Both devices falsely diagnosed dysplastic nevi as non-dysplastic (43% sensitivity for dysplastic nevus diagnosis). The most significant criteria for diagnosing a melanoma with LC-OCT were irregular honeycombed patterns (92% occurrence rate; 31.7 odds ratio (OR)), the presence of pagetoid spread (89% occurrence rate; 23.6 OR) and the absence of dermal nests (23% occurrence rate, 0.02 OR). In conclusion LC-OCT is useful for the discrimination between melanomas and nevi.
Diagnosing clinically unclear basal cell carcinomas (BCCs) can be challenging. Line-field confocal optical coherence tomography (LC-OCT) is able to display morphological features of BCC subtypes with good histological correlation. The aim of this study was to investigate the accuracy of LC-OCT in diagnosing clinically unsure cases of BCC compared to dermoscopy alone and in distinguishing between superficial BCCs and other BCC subtypes. Moreover, we addressed pitfalls in false positive cases. We prospectively enrolled 182 lesions of 154 patients, referred to our department to confirm or to rule out the diagnosis of BCC. Dermoscopy and LC-OCT images were evaluated by two experts independently. Image quality, LC-OCT patterns and criteria, diagnosis, BCC subtype, and diagnostic confidence were assessed. Sensitivity and specificity of additional LC-OCT were compared to dermoscopy alone for identifying BCC in clinically unclear lesions. In addition, key LC-OCT features to distinguish between BCCs and non-BCCs and to differentiate superficial BCCs from other BCC subtypes were determined by linear regressions. Diagnostic confidence was rated as “high” in only 48% of the lesions with dermoscopy alone compared to 70% with LC-OCT. LC-OCT showed a high sensitivity (98%) and specificity (80%) compared to histology, and these were even higher (100% sensitivity and 97% specificity) in the subgroup of lesions with high diagnostic confidence. Interobserver agreement was nearly perfect (95%). The combination of dermoscopy and LC-OCT reached a sensitivity of 100% and specificity of 81.2% in all cases and increased to sensitivity of 100% and specificity of 94.9% in cases with a high diagnostic confidence. The performance of LC-OCT was influenced by the image quality but not by the anatomical location of the lesion. The most specific morphological LC-OCT criteria in BCCs compared to non-BCCs were: less defined dermoepidermal junction (DEJ), hyporeflective tumor lobules, and dark rim. The most relevant features of the subgroup of superficial BCCs (sBCCs) were: string of pearls pattern and absence of epidermal thinning. Our diagnostic confidence, sensitivity, and specificity in detecting BCCs in the context of clinically equivocal lesions significantly improved using LC-OCT in comparison to dermoscopy only. Operator training for image acquisition is fundamental to achieve the best results. Not only the differential diagnosis of BCC, but also BCC subtyping can be performed at bedside with LC-OCT.
It is known that actinic keratoses (AKs) can progress to invasive squamous cell carcinoma (SCC). The histological PRO grading of AKs is based on the growth pattern of basal keratinocytes and relates to their progression risk. AKs can be non-invasively characterized by line-field confocal optical coherence tomography (LC-OCT). The aim of the study was to define criteria for an LC-OCT grading of AKs based on the PRO classification and to correlate it with its histological counterpart. To evaluate the interobserver agreement for the LC-OCT PRO classification, fifty AKs were imaged by LC-OCT and biopsied for histopathology. PRO histological grading was assessed by an expert consensus, while two evaluator groups separately performed LC-OCT grading on vertical sections. The agreement between LC-OCT and histological PRO grading was 75% for all lesions (weighted kappa 0.66, 95% CI 0.48–0.83, p ≤ 0.001) and 85.4% when comparing the subgroups PRO I vs. PRO II/III (weighted kappa 0.64, 95% CI 0.40–0.88, p ≤ 0.001). The interobserver agreement for LC-OCT was 90% (Cohen’s kappa 0.84, 95% CI 0.71–0.91, p ≤ 0.001). In this pilot study, we demonstrated that LC-OCT is potentially able to classify AKs based on the basal growth pattern of keratinocytes, in-vivo reproducing the PRO classification, with strong interobserver agreement and a good correlation with histopathology.
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