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Figure 1.  Correlation of Basal Cell Carcinoma (BCC) Features on Reflectance Confocal Microscopy (RCM) With BCC Features on Optical Coherence Tomography (OCT)
Correlation of Basal Cell Carcinoma (BCC) Features on Reflectance Confocal Microscopy (RCM) With BCC Features on Optical Coherence Tomography (OCT)

A, The RCM en face image shows tumor nests at the dermal-epidermal junction (black asterisks). B, OCT image shows a roundish, hyporeflective structure (black asterisk) arising from the underside of the epidermis with clefting (yellow arrowheads) along with some dilated vessels in the dermis (white arrowheads). C, RCM en face image shows a central hair follicle surrounded by large tumor nests (black asterisks) with peripheral palisading and clefting on both sides. D, OCT image shows 2 large, gray tumor nests (black asterisks) encompassing the entire dermis.

Figure 2.  Combined Reflectance Confocal Microscopy (RCM)–Optical Coherence Tomography (OCT) for Detection of Residual Basal Cell Carcinoma (BCC) in a Previously Biopsied Lesion
Combined Reflectance Confocal Microscopy (RCM)–Optical Coherence Tomography (OCT) for Detection of Residual Basal Cell Carcinoma (BCC) in a Previously Biopsied Lesion

A, A woman in her 80s had a slightly hyperpigmented papule with fine branching vessels on nasal ala. B, The RCM imaging at the level of the dermis showed branching horizontal vessels with leukocyte trafficking (white arrowheads) above an area with numerous small blood vessels between bright interweaving collagen bundles, which are distinct from background dermal collagen. Numerous adnexal structures (black asterisks) along with structures suggestive of tumor were observed. C, The OCT imaging showed a gray, branching tumor lobule with dark peritumoral rim in the dermis (red asterisk) along with structures suggestive of vellus hair follicles and some prominent vessels. D, Histopathologic examination (hematoxylin-eosin stain) confirmed the presence of tumor lobules in the dermis around the scar tissue (original magnification ×10).

Figure 3.  Combined Reflectance Confocal Microscopy (RCM)–Optical Coherence Tomography (OCT) for Basal Cell Carcinoma (BCC) Diagnosis in a Nonbiopsied Lesion
Combined Reflectance Confocal Microscopy (RCM)–Optical Coherence Tomography (OCT) for Basal Cell Carcinoma (BCC) Diagnosis in a Nonbiopsied Lesion

A, A woman in her 70s had a crusted, small, milky white to pink–colored papule on the nasal ala. B, The RCM imaging at the level of dermis showed a branching tumor nodule with subtle peripheral palisading and a dark peritumoral rim (black asterisk), prominent canalicular vessels with leukocyte trafficking (white arrowheads), and patchy mild inflammation (small round bright cells). C, The optical coherence tomography (OCT) imaging showed disruption in the normal epidermal and dermal patterns by ill-defined hyporeflective structures (red asterisk) throughout the entire field of view. D, Histopathologic examination (toluidine blue–stained) showed an intradermal tumor composed of branching lobules and cords of atypical basaloid cells with peripheral palisading and within the reticular dermis (original magnification ×10).

Figure 4.  Correlation Between Optical Coherence Tomography (OCT)–Estimated Depth and Histopathologically Measured Depth
Correlation Between Optical Coherence Tomography (OCT)–Estimated Depth and Histopathologically Measured Depth

A, High correlation was observed for combined lesions: R value was 0.86 and R2 value was 0.75 (P < .001). B, High correlation was observed for lesions less than 500 μm deep: R value was 0.85 and R2 value was 0.73 (P < .001). C, Moderate correlation was observed for lesions greater than 500 μm deep: R value was 0.65 and R2 value was 0.43 (P < .001).

Table.  Diagnostic Accuracy Measures for Reflectance Confocal Microscopy (RCM), Optical Coherence Tomography (OCT), and Combined Readings
Diagnostic Accuracy Measures for Reflectance Confocal Microscopy (RCM), Optical Coherence Tomography (OCT), and Combined Readings
OCT Raster of Normal Skin
1.
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Trakatelli  M, Morton  C, Nagore  E,  et al; BCC Subcommittee of the Guidelines Committee of the European Dermatology Forum.  Update of the European guidelines for basal cell carcinoma management.  Eur J Dermatol. 2014;24(3):312-329. PubMedGoogle Scholar
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Connolly  SM, Baker  DR, Coldiron  BM,  et al; Ad Hoc Task Force; Ratings Panel.  AAD/ACMS/ASDSA/ASMS 2012 appropriate use criteria for Mohs micrographic surgery: a report of the American Academy of Dermatology, American College of Mohs Surgery, American Society for Dermatologic Surgery Association, and the American Society for Mohs Surgery.  J Am Acad Dermatol. 2012;67(4):531-550. doi:10.1016/j.jaad.2012.06.009PubMedGoogle ScholarCrossref
12.
Cheng  HM, Guitera  P.  Systematic review of optical coherence tomography usage in the diagnosis and management of basal cell carcinoma.  Br J Dermatol. 2015;173(6):1371-1380. doi:10.1111/bjd.14042PubMedGoogle ScholarCrossref
13.
Nori  S, Rius-Díaz  F, Cuevas  J,  et al.  Sensitivity and specificity of reflectance-mode confocal microscopy for in vivo diagnosis of basal cell carcinoma: a multicenter study.  J Am Acad Dermatol. 2004;51(6):923-930. doi:10.1016/j.jaad.2004.06.028PubMedGoogle ScholarCrossref
14.
Guitera  P, Menzies  SW, Longo  C, Cesinaro  AM, Scolyer  RA, Pellacani  G.  In vivo confocal microscopy for diagnosis of melanoma and basal cell carcinoma using a two-step method: analysis of 710 consecutive clinically equivocal cases.  J Invest Dermatol. 2012;132(10):2386-2394. doi:10.1038/jid.2012.172PubMedGoogle ScholarCrossref
15.
Kadouch  DJ, Elshot  YS, Zupan-Kajcovski  B,  et al.  One-stop-shop with confocal microscopy imaging vs. standard care for surgical treatment of basal cell carcinoma: an open-label, noninferiority, randomized controlled multicentre trial.  Br J Dermatol. 2017;177(3):735-741. doi:10.1111/bjd.15559PubMedGoogle ScholarCrossref
16.
Kadouch  DJ, Schram  ME, Leeflang  MM, Limpens  J, Spuls  PI, de Rie  MA.  In vivo confocal microscopy of basal cell carcinoma: a systematic review of diagnostic accuracy.  J Eur Acad Dermatol Venereol. 2015;29(10):1890-1897. doi:10.1111/jdv.13224PubMedGoogle ScholarCrossref
17.
Kadouch  DJ, Leeflang  MM, Elshot  YS,  et al.  Diagnostic accuracy of confocal microscopy imaging vs. punch biopsy for diagnosing and subtyping basal cell carcinoma.  J Eur Acad Dermatol Venereol. 2017;31(10):1641-1648. doi:10.1111/jdv.14253PubMedGoogle ScholarCrossref
18.
Xiong  YD, Ma  S, Li  X, Zhong  X, Duan  C, Chen  Q.  A meta-analysis of reflectance confocal microscopy for the diagnosis of malignant skin tumours.  J Eur Acad Dermatol Venereol. 2016;30(8):1295-1302. doi:10.1111/jdv.13712PubMedGoogle ScholarCrossref
19.
Hussain  AA, Themstrup  L, Jemec  GBE.  Optical coherence tomography in the diagnosis of basal cell carcinoma.  Arch Dermatol Res. 2015;307(1):1-10. doi:10.1007/s00403-014-1498-yPubMedGoogle ScholarCrossref
20.
Xiong  Y-Q, Mo  Y, Wen  Y-Q,  et al.  Optical coherence tomography for the diagnosis of malignant skin tumors: a meta-analysis.  J Biomed Opt. 2018;23(2):1-10. doi:10.1117/1.JBO.23.2.020902PubMedGoogle ScholarCrossref
21.
Cheng  HM, Lo  S, Scolyer  R, Meekings  A, Carlos  G, Guitera  P.  Accuracy of optical coherence tomography for the diagnosis of superficial basal cell carcinoma: a prospective, consecutive, cohort study of 168 cases.  Br J Dermatol. 2016;175(6):1290-1300. doi:10.1111/bjd.14714PubMedGoogle ScholarCrossref
22.
Alawi  SA, Kuck  M, Wahrlich  C,  et al.  Optical coherence tomography for presurgical margin assessment of non-melanoma skin cancer—a practical approach.  Exp Dermatol. 2013;22(8):547-551. doi:10.1111/exd.12196PubMedGoogle ScholarCrossref
23.
Olmedo  JM, Warschaw  KE, Schmitt  JM, Swanson  DL.  Correlation of thickness of basal cell carcinoma by optical coherence tomography in vivo and routine histologic findings: a pilot study.  Dermatol Surg. 2007;33(4):421-425. PubMedGoogle Scholar
24.
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25.
Iftimia  N, Yélamos  O, Chen  CJ,  et al.  Handheld optical coherence tomography-reflectance confocal microscopy probe for detection of basal cell carcinoma and delineation of margins.  J Biomed Opt. 2017;22(7):76006. doi:10.1117/1.JBO.22.7.076006PubMedGoogle ScholarCrossref
26.
Marino  ML, Rogers  T, Sierra Gil  H, Rajadhyaksha  M, Cordova  MA, Marghoob  AA.  Improving lesion localization when imaging with handheld reflectance confocal microscope.  Skin Res Technol. 2016;22(4):519-520. doi:10.1111/srt.12280PubMedGoogle ScholarCrossref
27.
Farnetani  F, Scope  A, Braun  RP,  et al.  Skin cancer diagnosis with reflectance confocal microscopy: reproducibility of feature recognition and accuracy of diagnosis.  JAMA Dermatol. 2015;151(10):1075-1080. doi:10.1001/jamadermatol.2015.0810PubMedGoogle ScholarCrossref
28.
Longo  C, Lallas  A, Kyrgidis  A,  et al.  Classifying distinct basal cell carcinoma subtype by means of dermatoscopy and reflectance confocal microscopy.  J Am Acad Dermatol. 2014;71(4):716-724.e1. doi:10.1016/j.jaad.2014.04.067PubMedGoogle ScholarCrossref
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34.
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Original Investigation
October 2018

Evaluation of a Combined Reflectance Confocal Microscopy–Optical Coherence Tomography Device for Detection and Depth Assessment of Basal Cell Carcinoma

Author Affiliations
  • 1Dermatology Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York
  • 2Department of Dermatology, Hospital Clínic, Universitat de Barcelona, Barcelona, Spain
  • 3Biomedical Optics Technologies Group, Physical Sciences Inc, Andover, Massachusetts
  • 4Clinical Development, Caliber Imaging and Diagnostics Inc, Rochester, New York
  • 5SkinMedical Research and Diagnostics, PLLC, Dobbs Ferry, New York
  • 6Department of Pathology, SUNY Downstate Medical Center, Brooklyn, New York
  • 7Department of Dermatology, Facultad de Medicina, Pontificia Universidad Católica de Chile, Santiago, Chile
  • 8Medicine and Medical Specialties Department, Instituto Ramon y Cajal de Investigacion Sanitaria, Alcalá University, Madrid, Spain
  • 9Department of Dermatology, Alcalá University, Madrid, Spain
JAMA Dermatol. 2018;154(10):1175-1183. doi:10.1001/jamadermatol.2018.2446
Key Points

Question  Can a combined reflectance confocal microscopy–optical coherence tomography device facilitate noninvasive, real-time diagnosis and simultaneous depth assessment of basal cell carcinomas?

Findings  In this pilot study of a combined reflectance confocal microscopy–optical coherence tomography device used on 85 lesions from 55 patients, residual tumor was consistently detected in biopsied lesions (with 100% sensitivity), diagnosis of basal cell carcinoma was achieved with high accuracy (100% sensitivity, 75% specificity) in nonbiopsied lesions, and depth was accurately estimated between optical coherence tomography and histopathologic assessment.

Meaning  Combined reflectance confocal microscopy–optical coherence tomography imaging may enable accurate diagnosis and depth assessment in lesions clinically suggestive of basal cell carcinomas, but further validation must be performed.

Abstract

Importance  The limited tissue sampling of a biopsy can lead to an incomplete assessment of basal cell carcinoma (BCC) subtypes and depth. Reflectance confocal microscopy (RCM) combined with optical coherence tomography (OCT) imaging may enable real-time, noninvasive, comprehensive three-dimensional sampling in vivo, which may improve the diagnostic accuracy and margin assessment of BCCs.

Objective  To determine the accuracy of a combined RCM-OCT device for BCC detection and deep margin assessment.

Design, Setting, and Participants  This pilot study was carried out on 85 lesions from 55 patients referred for physician consultation or Mohs surgery at Memorial Sloan Kettering Skin Cancer Center in Hauppauge, New York. These patients were prospectively and consecutively enrolled in the study between January 1, 2017, and December 31, 2017. Patients underwent imaging, with the combined RCM-OCT probe, for previously biopsied, histopathologically confirmed BCCs and lesions clinically or dermoscopically suggestive of BCC. Only patients with available histopathologic examination after imaging were included.

Main Outcomes and Measures  Improvements in sensitivity, specificity, and diagnostic accuracy for BCC using the combined RCM-OCT probe as well as the correlation between OCT-estimated depth and histopathologically measured depth were investigated.

Results  In total, 85 lesions from 55 patients (27 [49%] were female and 28 [51%] were male with a median [range] age of 59 [21-90] years) were imaged. Imaging was performed on 25 previously biopsied and histopathologically confirmed BCCs and 60 previously nonbiopsied but clinically or dermoscopically suspicious lesions. Normal skin and BCC features were correlated and validated with histopathologic examination. In previously biopsied lesions, residual tumors were detected in 12 of 25 (48%) lesions with 100% sensitivity (95% CI, 73.5%-100%) and 23.1% specificity (95% CI, 5.0%-53.8%) for combined RCM-OCT probe. In previously nonbiopsied and suspicious lesions, BCCs were diagnosed in 48 of 60 (80%) lesions with 100% sensitivity (95% CI, 92.6%-100%) and 75% specificity (95% CI, 42.8%-94.5%). Correlation was observed between depth estimated with OCT and depth measured with histopathologic examination: the coefficient of determination (R2) was 0.75 (R = 0.86; P < .001) for all lesions, 0.73 (R = 0.85; P < .001) for lesions less than 500 μm deep, and 0.65 (R = 0.43; P < .001) for lesions greater than 500 μm deep.

Conclusions and Relevance  Combined RCM-OCT imaging may be prospectively used to comprehensively diagnose lesions suggestive of BCC and triage for treatment. Further validation of this device must be performed on a larger cohort.

Introduction

The diagnosis of basal cell carcinoma (BCC), prognostic assessment of high risk and low risk tumors, and choice between aggressive and conservative treatment approaches are determined by clinical presentation and histopathologic examination.1-5 However, skin biopsy is an invasive procedure, the specimen takes days to process for disease, and the limited sampling may lead to an incomplete diagnostic assessment. Limited sampling during biopsy and pathological processing6,7 fails to identify deeper and aggressive tumors in 1 of 6 cases, especially in mixed histological subtypes8,9 and in superficial and nodular BCCs with deeper components.7,10 However, a complete and accurate assessment of tumor subtype and depth is important for precise diagnosis and management, especially because skin cancer treatment guidelines list nonsurgical options for the shallower and less-aggressive subtypes, such as superficial and early nodular BCCs (depth, approximately 0.2-0.5 mm), and surgical treatment for the aggressive and deeper subtypes, such as micronodular, sclerosing, and infiltrative.3,4,11 Noninvasive optical imaging may help overcome these limitations and enable a more comprehensive assessment of lesions as well as facilitate improved diagnosis, subtyping, and depth estimation. Such an approach would be especially useful for cosmetically sensitive areas.

Reflectance confocal microscopy (RCM) and optical coherence tomography (OCT) are 2 imaging methods that can noninvasively diagnose BCCs with high sensitivity (80%-95%) and specificity (70%-90%).12-20 In addition, OCT can accurately detect depth.21-23 However, when used independently, each technology cannot provide comprehensive information to guide both diagnosis and treatment. Reflectance confocal microscopy provides en face images with quasi-histological resolution but is limited to a depth of approximately 200 μm. Conversely, OCT produces orthogonal and en face images to a depth of approximately 1000 μm but with approximately 10-μm resolution. Therefore, integrating RCM and OCT imaging into a combined RCM-OCT system can provide complementary, comprehensive 3-dimensional, real-time sampling and may lead to improvements in noninvasive BCC diagnosis and margin assessment.

Previous studies have described a combined RCM-OCT bench-top instrument for ex vivo imaging of BCCs24 and a handheld probe for in vivo applications.25 Here, we report a clinical study that tested the handheld probe on patients. We conducted imaging on 2 types of lesions: (1) previously biopsied, histopathologically proven BCCs and (2) previously nonbiopsied lesions clinically or dermoscopically suggestive of BCCs. The aims of this study were to (1) describe and correlate BCC features on RCM and on OCT alongside histopathologic examination; (2) assess the detection of residual tumors in previously biopsied, histopathologically proven lesions; (3) evaluate the diagnostic accuracy in previously nonbiopsied, clinically or dermoscopically suspicious lesions; and (4) correlate OCT-estimated depth with histopathologically measured depth.

Methods
Patient Recruitment

The study was carried out under the protocol approved by the institutional review board of Memorial Sloan Kettering Cancer Center. Written and verbal informed consent were obtained from each patient before imaging. From January 1, 2017, to December 31, 2017, we prospectively and consecutively enrolled patients referred for physician consultation or Mohs surgery at Memorial Sloan Kettering Skin Cancer Center in Hauppauge, New York. Prior to treatment, patients underwent imaging, with the combined RCM-OCT probe. We included 2 types of lesions: (1) previously biopsied, histopathologically confirmed BCCs and (2) clinically or dermoscopically suggestive of BCC. Lesions were excluded if histopathologic examination was unavailable after imaging.

We included the first group of patients to image and identify well-known features in these histopathologically confirmed BCC lesions using the new RCM-OCT probe. This group was also tested for residual BCCs. After imaging, the lesions were excised through Mohs surgery and step-sectioned in orthogonal planes for the systematic evaluation of tumor presence and tumor depth. The second group of patients with clinically or dermoscopically suspicious lesions were imaged so as to allow us to calculate diagnostic accuracy. After imaging, these lesions were excised by either shave excision or Mohs surgery. Orthogonal sections were prepared from the Mohs tissue for measurement of tumor depth.

Imaging Protocol

Clinical and dermoscopic images of the lesions were captured with a handheld dermatoscope (VeosDS3; Canfield Scientific). The combined RCM-OCT imaging was performed using the handheld probe, the technical details for which are described elsewhere.25 The RCM imaging was with a lateral resolution of approximately 1 μm, an optical sectioning of approximately 3 μm, and an en face field of view (FOV) of 750 × 750 μm. The OCT imaging was with a lateral resolution of approximately 5 μm, an axial resolution of 10 μm, and an orthogonal FOV of 1000 μm deep ×2000 μm wide. The en face RCM images were centered on the OCT FOV, and both images were viewed simultaneously in real time on a monitor (eFigure 1A and B in the Supplement).

Following a previously proven method,25,26 we placed adhesive paper rings (3M) at the clinical margins for image navigation. Dermoscopic examination of the area within the paper ring was subsequently carried out with a handheld dermatoscope. The ring divided the lesion into 4 hypothetical quadrants; the imaging in dermoscopically suspicious areas was guided through these quadrants and clock positions. If dermoscopically suspicious areas were found in any of the quadrants, we noted the clock position and then explored BCC features by maneuvering the combined RCM-OCT probe in those areas. On encountering suspicious foci, we acquired RCM stacks and OCT rasters (eFigure 1C and D in the Supplement). Images of perilesional skin were also taken in a subset of patients. Annotation of features on RCM and OCT was performed on the RCM stacks and OCT rasters immediately afterward. The entire procedure of imaging and image annotation took 20 to 30 minutes.

Image Annotation and Histopathologic Examination Correlation

We annotated BCC features that were identified from the literature. The features on RCM included cordlike structures, tumor nests, palisading, streaming, dark peritumoral rim (clefting), stroma with plump cells and bright dots, and horizontal vessels.13,14,16,27-29 The features on OCT were hyporeflective or gray structures attached to the dermal-epidermal junction (DEJ), disruption of the DEJ, hyporeflective or gray ovoid structures in the dermis, dark peritumoral rim (clefting), hyperreflective peritumoral stroma, hyperreflective streaks, and branched vessels.12,30-32

Individual RCM and OCT diagnoses and diagnostic confidence (low or high) along with a combined RCM-OCT diagnosis were noted and blinded to histopathologic examination. In positive cases, the deep margin was estimated in OCT images with a software tool. All findings were validated by subsequent histopathologic examination. Sensitivity, specificity, negative predictive value, and positive predictive value were calculated for RCM, OCT, and combined RCM-OCT. Correlation between the depths measured by OCT and by histopathologic examination was calculated for positive cases using Pearson correlation and determination coefficient at 0.05 level of significance. For most positive cases, varying depth was observed across the lesion. The maximum depths observed in OCT images and histopathologic sections were employed for correlation analysis. Because of the depth limitation of OCT at 1000 μm, the depth of deeper BCC tumors was analyzed as 1000 μm. The coefficient of determination (R2) and coefficient of correlation (R) were calculated initially for lesions of all depths. Subsequently, lesions were categorized into less than 500 μm deep and greater than 500 μm deep on histopathologic examination, and the correlation was calculated for these categories. Statistical analysis was performed with SPSS Statistics, version 24 (IBM Corp).

Results
Patient Demographics and Histopathologic Examination

In total, 85 lesions from 55 patients (27 [49%] were female and 28 [51%] were male with a median [range] age of 59 [21-90] years) belonging to 2 different categories underwent imaging. Patient demographics are summarized in eFigure 2 in the Supplement. The first group comprised 25 previously biopsied BCCs, and the second group comprised 60 lesions clinically or dermoscopically suggestive of BCC. A single suspicious lesion was imaged on most patients. The face was the most common site (38 [45%]) followed by the trunk (35 [41%]). Of the 85 lesions, 60 (71%) were found to be positive for BCC on histopathologic examination after imaging. For previously biopsied lesions, 12 of 25 (48%) showed residual BCC features. In the remaining lesions, the BCC may have been entirely removed during biopsy or cleared because of inflammation. In nonbiopsied clinically or dermoscopically suspicious lesions, 48 of 60 (80%) were BCCs. Other diagnoses for the remaining lesions included 3 seborrheic keratosis, 1 sebaceous hyperplasia, 2 lichenoid keratosis, 1 squamous cell carcinoma, 2 scar, 1 dermal fibrosis and actinic changes, 1 acanthoma, and 1 cylindroma.

Features of Normal Skin and BCC on RCM and OCT

Normal skin features on RCM and OCT, such as hair follicles and blood vessels, were visually correlated and validated (eFigure 3A in the Supplement). On RCM, features of BCC, such as cordlike structures, tumor nests, dark peritumoral rim (clefting), and horizontal vessels, were observed and correlated with corresponding features on OCT, such as hyporeflective or gray structures at the DEJ or deeper in the dermis, dark peritumoral rim (clefting), hyperreflective peritumoral stroma, hyperreflective streaks, and branched vessels (eFigure 3B to E in the Supplement). The features on RCM and OCT for tumor at the DEJ and large tumor nests in the dermis are shown in Figure 1. Some of the RCM and OCT features could not be correlated because of the differences in resolution, FOV, and/or depth.

Detection of Residual BCCs in Previously Biopsied Lesions

We performed imaging on previously biopsied lesions in and around the biopsied area to detect the presence or absence of residual BCCs. On RCM, 20 of 25 (80%) lesions demonstrated features suggestive of BCC, whereas on OCT, 22 of 25 lesions (88%) demonstrated these features. Biopsy-induced stromal changes made RCM diagnosis challenging. The larger FOV and depth of OCT imaging facilitated the visualization of tumor-like structures below and surrounding the scar, making OCT more reliable for final diagnosis. A representative case is shown in Figure 2. The combined RCM-OCT images showed BCC features in 22 of 25 cases (88%). Histopathologic examination identified residual BCCs in only 12 lesions, indicating that RCM overdiagnosed residual BCCs in 8 of 20 lesions (40%), whereas OCT and combined RCM-OCT overdiagnosed these tumors in 10 of 22 lesions (45%) (false positives). Sensitivity for residual BCC detection was 100% (95% CI, 73.5%-100%) for RCM, OCT, and combined RCM-OCT; however, the specificity was lower: 38.5% (95% CI, 13.9%-68.4%) for RCM and 23.1% (95% CI, 5.0%-53.8%) for both OCT and combined RCM-OCT (Table).

Diagnosis of BCCs in Clinically or Dermoscopically Suspicious Lesions

Diagnostic accuracy for BCC was subsequently evaluated in nonbiopsied, clinically or dermoscopically suspicious lesions. The RCM imaging correctly diagnosed BCC in 47 of 48 lesions (98%), and most (43 of 47 [91%]) diagnoses were with high confidence. The OCT imaging identified BCCs in 48 of 48 lesions (100%), and did so with high confidence for 42 of these lesions (88%). Low-confidence RCM cases had cords or tumor islands without clear palisading and/or clefting. Low-confidence OCT cases manifested as very superficial or dark areas in the deeper dermis. In all lesions identified with low confidence by either RCM or OCT, the complementary technology (OCT or RCM) helped increase confidence in the diagnosis. A representative case demonstrating how RCM improved the overall diagnosis for a low-confidence OCT case is shown in Figure 3. The combined RCM-OCT imaging also had correct diagnoses for all 48 BCCs and detected the absence of BCC in 9 of 12 cases, yielding 100% sensitivity (95% CI, 92.6%-100%), 75% specificity (95% CI, 42.8%-94.5%), 94.1% positive predictive value (95% CI, 83.8%-98.8%), 100% negative predictive value (95% CI, 66.4%-100%) (Table).

OCT-Estimated and Histopathologically Measured Depth Correlation

Histopathologically measured depth was available for 55 of 60 BCCs (91.7%). Good correlation between histopathologically measured depth and OCT-estimated depth was observed; the coefficient of determination (R2) was 0.75 (R = 0.86; P < .001) for all lesions, 0.73 (R = 0.85; P < .001) for lesions less than 500 μm deep, and 0.65 (R = 0.43; P < .001) for lesions greater than 500 μm deep (Figure 4). The OCT imaging correctly estimated all tumors (17 of 17 [100%]) with a depth less than 500 μm as “shallow” and 34 of 38 (89.4%) tumors with a depth greater than 500 μm as “deeper.”

Discussion

The results of this pilot study and our experience show that RCM and OCT imaging, when combined into a single probe and when the images are viewed simultaneously in real time, complement each other. Orthogonal OCT images help to localize suspicious structures, and the cellular resolution of en face RCM stacks identifies these structures. Furthermore, OCT raster scans provide volumetric information, which helps to confirm suspicious features that mimic tumors or tumor-related features (eg, vellus follicles and tumor nests) on RCM.33 (Normal and tumor OCT rasters are presented in Video 1 and Video 2, respectively.)

Previously biopsied lesions were difficult to assess, probably because of fibrosis and inflammation. High sensitivity (100%) but reduced specificity (23.1%) for the combined RCM-OCT probe was observed in these lesions. The lower specificity may be related to scar tissue and, to a lesser extent, our limited experience with reading OCT images. Despite its low specificity, however, the probe’s sensitivity was 100%. No residual BCCs were missed, suggesting that the combined RCM-OCT device could be used to screen previously biopsied lesions for residual tumor. Approximately half of previously biopsied lesions did not show residual tumors, likely because of the complete removal during biopsy or clearing by the inflammatory response after biopsy. Better prospective identification of these cases, using the combined RCM-OCT probe, could prevent unnecessary treatment without affecting the outcome.

In addition, our study on previously nonbiopsied, clinically or dermoscopically suspicious lesions demonstrated the enhanced capability of the combined RCM-OCT probe, over individual modalities, to diagnose BCC. Furthermore, the probe led to an improvement in the sensitivity (100%) for BCC diagnosis, compared with the 93% reported with handheld RCM-only imaging.34 This higher sensitivity may be attributed to the OCT-enabled scanning of larger FOVs and the probe-guided RCM imaging (while obviating the need for mosaicking), providing more representative sampling for diagnosis.

Along with its diagnostic capability, OCT enabled the measurement of deep margins, simultaneously within the same FOV as RCM, which highlights a key advantage of the combined probe. High correlation between depth estimated by OCT and depth measured in histopathologic examination was observed for all BCCs, which is in concordance with findings in other published studies.21 The differences in depth between OCT and histopathologic measurements could be attributed to possible misregistration between OCT and histological sections and tissue retraction and shrinkage effects.35 The lower correlation for deeper lesions (>500 μm) is likely the result of poorer image quality and decreased resolution and contrast of OCT when used for greater depths. In addition, because of the maximum depth limitation of OCT (1000 μm), greater differences from (and lower correlations with) histological measurements are to be expected. However, higher correlation was observed for lesions less than 500 μm deep. This finding is significant for the management of superficial and early nodular BCCs (approximately 0.2-0.5 mm deep), which can be treated with nonsurgical alternatives.1,4,13,14 In addition, McKay et al35 showed that the topical immunomodulatory agent imiquimod was effective in treating BCCs less than 0.4 mm deep. In our study, we used 0.5 mm as the limit to account for tissue retraction and shrinkage.34 We measured depth at only selected (dermoscopically suspicious) foci within the lesion to establish proof of principle. Maximum depth estimation to guide appropriate treatment will be carried out in prospective studies through a more systematic and comprehensive evaluation of the complete lesion.

In our experience, the combined probe and the real-time interplay between OCT and RCM imaging are efficient for BCC diagnosis and depth estimation and have proven helpful in improving the speed, efficiency, and confidence level of diagnosis at the bedside. In biopsied lesions, OCT helped confirm the diagnosis of residual BCC in cases in which RCM confidence was low. Conversely, RCM was able to increase specificity and make a correct diagnosis in instances in which superficial and weakly scattering structures were difficult to diagnose on OCT. Furthermore, cellular-level resolution of RCM can also prevent dangerous misinterpretation of amelanotic melanoma as BCC, which has previously been reported using OCT alone.23 Because the combined RCM-OCT probe noninvasively facilitates both diagnosis and depth assessment, BCCs may be treated through a “one-stop shop” (ie, single patient visit) approach without the need for a biopsy. Such an approach, implemented with either surgical or nonsurgical treatment, has been demonstrated for RCM imaging.15,36

Limitations

The limitations of this study include the small sample size, our limited experience with using and reading OCT images, the suboptimal OCT image quality, and the small FOV for RCM imaging (ie, lack of mosaicking capabilities). A bright, horizontal, back-scattered reflection artifact was present in the OCT images, limiting our evaluation of the DEJ. Although the handheld probe offers free-form navigation over a lesion and is optimal for performing body contour imaging, it may miss small focal areas and thus lead to sampling bias. Video mosaicking with RCM permits the capture of 2-dimensional mosaics obtained from videos, allowing the examination of larger areas.37-41 Future developments toward improving OCT image quality, miniaturizing the RCM-OCT probe, incorporating a dermoscopic camera, and enhancing mosaicking capabilities are important before prospective clinical integration.

Conclusions

A combined RCM-OCT imaging device detects normal skin and BCC features in both previously biopsied lesions and clinically or dermoscopically suspicious lesions and yields higher sensitivity (100%) and no loss of specificity (75%). Furthermore, the probe allows for the simultaneous determination of tumor depth (shallower or deeper than 500 μm). Large cohort studies and multicenter trials are needed to further test and validate this multimodal approach.

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Article Information

Accepted for Publication: June 6, 2018.

Corresponding Author: Chih-Shan J. Chen, MD, PhD, Dermatology Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, 800 Veterans Memorial Hwy, Hauppauge, NY 11788 (chenc2@mskcc.org).

Published Online: August 22, 2018. doi:10.1001/jamadermatol.2018.2446

Author Contributions: Drs Sahu and Yélamos contributed equally. Drs Sahu and Chen had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Study concept and design: Sahu, Yélamos, Iftimia, Cordova, Rossi, Rajadhyaksha, Chen.

Acquisition, analysis, or interpretation of data: All authors.

Drafting of the manuscript: Sahu, Yélamos, Iftimia, Alessi-Fox, Navarrete-Dechent, Rossi, Rajadhyaksha, Chen.

Critical revision of the manuscript for important intellectual content: Yélamos, Iftimia, Cordova, Alessi-Fox, Gill, Maguluri, Navarrete-Dechent, Dusza, Gonzalez, Rossi, Marghoob, Rajadhyaksha, Chen.

Statistical analysis: Sahu, Yélamos, Navarrete-Dechent, Dusza.

Obtained funding: Iftimia, Rajadhyaksha.

Administrative, technical, or material support: Yélamos, Iftimia, Cordova, Maguluri, Navarrete-Dechent, Rajadhyaksha, Chen.

Study supervision: Iftimia, Gonzalez, Rossi, Rajadhyaksha, Chen.

Conflict of Interest Disclosures: Dr Iftimia reported owning patent US9655521 B2 that is assigned to Physical Sciences Inc and Memorial Sloan Kettering Cancer Center and is related to the technology described in this study. Ms Alessi-Fox reported being employed by and owning equity in Caliber Imaging and Diagnostics Inc (formerly Lucid Inc), the company that manufactures and sells the VivaScope confocal microscope. Dr Rajadhyaksha reported being a former employee of and owning equity in Caliber Imaging and Diagnostics; the VivaScope is the commercial version of an original laboratory prototype he developed at Massachusetts General Hospital, Harvard Medical School. Dr Gill reported being a consultant for the Dermatology Service, Memorial Sloan Kettering Cancer Center. This research was completed without financial support from Caliber ID, Memorial Sloan Kettering Cancer Center, or Physical Sciences Inc. The data were acquired and processed by coauthors unaffiliated with any commercial entity. No other disclosures were reported.

Funding/Support: This study was supported in part by Small Business Innovation Research grant R44CA162561 from the National Institutes of Health/National Cancer Institute (NIH/NCI), by grant R01EB020029 from the NIH/National Institute of Biomedical Imaging and Bioengineering, by the Beca Excelencia Fundacion Piel Sana (Dr Yelamos), and by grant P30 CA008748 from the NIH/NCI Cancer Center Support.

Role of the Funder/Sponsor: The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Additional Contributions: We thank the patients depicted in Figure 2 and Figure 3 for granting permission to publish this information.

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