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Utility of Optical Coherence Tomography in Basal Cell Carcinoma Diagnosis

This review assesses the use of Optical Coherence Tomography (OCT) in diagnosing basal cell carcinoma (BCC). It examines the sensitivity, specificity, and correlation of OCT features with histopathological findings in BCC. Results show promising diagnostic accuracy, highlighting the importance of OCT in BCC diagnosis.

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Utility of Optical Coherence Tomography in Basal Cell Carcinoma Diagnosis

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  1. The utility of optical coherence tomography for diagnosis of basal cell carcinoma: a quantitative review N. Reddy and B.T. Nguyen Department of Dermatology, Tufts Medical Centre British Journal of Dermatology. DOI: 10.111/bjd.17201

  2. Introduction What’s already known? • Optical coherence tomography (OCT) is a noninvasive imaging modality using near infrared light, that can be used to diagnose basal cell carcinoma (BCC). • Morphological features found on OCT images correlate with specific histopathological findings. • OCT can also detect subclinical extension of tumours and improve preoperative delineation of surgical margins.

  3. Objective • To estimate the sensitivity and specificity of different OCT systems for in-vivo diagnosis of BCC. • To measure the correlation between OCT features and histopathological findings of BCC. • To assess the impact of tumour and machine factors on BCC depth estimation by OCT.

  4. Methods • Search Methodology • Search of the MEDLINE and Embase databases using MeSH and manuscript keywords • Inclusion criteria • English studies on the use of OCT on in vivo human skin to aid in the diagnosis of BCC • BCC diagnosis confirmed by gold-standard histopathology • Available primary data on OCT morphological features • OCT and histopathological tumour depth data • Exclusion criteria • Studies on OCT detection of BCC local recurrences • Data on SCC, premalignant and in-situ lesions

  5. Methods • Study quality assessment • Newcastle–Ottawa Scale (NOS) • Cochrane Risk of Bias Tool • Data analysis • Average sensitivity, specificity and predictive values • Prevalence of BCC morphological features on OCT • Bland–Altman analysis on aggregate tumour depth data • Concordance and Pearson’s correlation between OCT depth and histopathological depth

  6. Results • The sensitivity and specificity were 89.3% and 60.3% overall and were highest for FD-OCT.

  7. Results • The most prevalent morphological features were lobular pattern and hyper-reflective peritumoral stroma. • HD-OCT and FD-OCT were superior to TD-OCT at identifying morphological features.

  8. Results • Concordance between OCT and histopathological tumour depth categories was moderate overall and highest for tumours < 1 mm and those on the extremities.

  9. Discussion • Overall specificity was lower due to the higher false positive rates for both TD-OCT and FD-OCT in this aggregated cohort. • FD-OCT has superior diagnostic accuracy than TD-OCT thanks to better resolution and higher depth penetration.

  10. Discussion • Many of the histological features of BCC have correlates that are commonly found with OCT. • These features can serve as OCT diagnostic criteria for BCC. • HD-OCT outperformed TD-OCT and FD-OCT in detecting morphological features due to its higher resolution, which enables better delineation of structural features.

  11. Discussion • TD-OCT tends to overestimate BCC tumour depth while FD-OCT generally underestimates it. • A possible contributor to the poorer depth characterization of OCT is the presence of inflammation in the tissue. • Challenges of imaging the concave and convex contours of the head and neck region may have contributed to poorer accuracy of depth prediction by OCT.

  12. ConclusionsWhat does this study add? • Analysedtumour-level data from 31 published studies encompassing 901 BCCs. • Calculated the diagnostic sensitivity and specificity of different OCT systems. • Determined the degree of correlation between OCT morphological features and BCC diagnosis. • Analysedtumour and machine factors that affect OCT estimation of tumour depth.

  13. Call for correspondence • Why not join the debate on this article through our correspondence section? • Rapid responses should not exceed 350 words, four references and one figure. • Further details can be found here.

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