Combined Imaging Methods Found to Enhance Detection of SCC

Doug Brunk

May 20, 2021

Combined reflectance confocal microscopy–optical coherence tomography is a noninvasive tool that could prove useful in the detection of squamous cell carcinoma (SCC) and distinguishing SCC in-situ and actinic keratosis (AK) from invasive SCC, results from a small prospective study demonstrated.

Dr Abdullah Aleisa

"A solitary scaly papule or plaque could represent an inflammatory or neoplastic process, and when neoplastic, it could be benign, premalignant, malignant in situ, or invasive malignant," lead study author Abdullah Aleisa, MD, said in an interview during the annual conference of the American Society for Laser Medicine and Surgery. Noninvasive imaging devices, such as reflectance confocal microscopy (RCM) and optical coherence tomography (OCT), "have been used to help in the diagnosis of those clinically suspicious lesions, however each device has its own limitation."

RCM images are horizontal sections of the skin with high cellular resolution but limited to 250 mcm of depth in skin, he said, while OCT images are vertical sections of the skin with low cellular resolution, but image up to 1,000-2,000 mcm of depth in skin.

"Combined RCM-OCT enables high cellular resolution and deep tissue evaluation," said Aleisa, a micrographic surgery and dermatologic oncology fellow at Memorial Sloan Kettering Cancer Center, New York. "The value of combined RCM-OCT has been shown in the detection and depth assessment of basal cell carcinoma, but it has never been studied in SCC. Our objective is to combine RCM and OCT simultaneously to detect SCC and assess the depth of invasion."

Between September and December 2020, Aleisa and colleagues prospectively imaged 36 lesions suspicious of SCC, SCC in situ, or AK between September 2020 and December 2020. The mean age of the cohort was 68 years and 63% were male. Using a prototype device from Andover, Mass.–based Caliber I.D., the investigators performed handheld RCM-OCT imaging at the center of clinically suspected lesions before biopsy and to previously diagnosed lesions before Mohs micrographic surgery (to check for residual tumor) and correlated RCM-OCT findings with histopathology results. A total of 36 lesions were treated.

Aleisa reported that most common RCM-OCT feature for invasive SCC was presence of vertical blood vessels (in 89% of lesions), while for SCC in situ/AK, it was acanthosis and parakeratosis without vertical blood vessels (in 84% of lesions). For the detection of invasive SCC, RCM-OCT had a sensitivity of 82%, a specificity of 92%, a negative predictive value of 92%, and a positive predictive value of 82%. For the detection of SCC in situ/AK, RCM-OCT had a sensitivity of 86%, a specificity of 100%, a negative predictive value of 92%, and a positive predictive value of 100%. The OCT depth measurement correlated well with histopathology with a concordance correlation coefficient of r2 = 0.9.

"Using RCM's high-resolution pictures allowed us to easily spot the vertical 'buttonhole' vessels associated with SCC," Aleisa said. "However, given the depth limitation of RCM, the distinction between SCC in situ and invasive SCC could not be accomplished using RCM alone. Therefore, having simultaneous OCT live feedback to the RCM images in the combined RCM-OCT device enabled us to assess the depth of those vertical 'buttonholes' and distinguish between SCC in situ and invasive SCC."

He acknowledged certain limitations of the approach, including that it requires approximately 20 minutes per imaging session, there is a steep learning curve for interpreting images, and certain anatomical sites are challenging to image, especially the nose, periocular area, and lip.

The study won a "best of session" emerging technologies abstract award from the ASLMS.

Milind Rajadhyaksha, PhD, of Memorial Sloan Kettering Cancer Center helped to develop the prototype device. Aleisa reported having no relevant financial disclosures.

This article originally appeared on, part of the Medscape Professional Network.


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