Cervical lesion assessment using real-time microendoscopy image analysis in Brazil: The CLARA study

Abstract

We conducted a prospective evaluation of the diagnostic performance of high-resolution microendoscopy (HRME) to detect cervical intraepithelial neoplasia (CIN) in women with abnormal screening tests. Study participants underwent colposcopy, HRME and cervical biopsy. The prospective diagnostic performance of HRME using an automated morphologic image analysis algorithm was compared to that of colposcopy using histopathologic detection of CIN as the gold standard. To assess the potential to further improve performance of HRME image analysis, we also conducted a retrospective analysis assessing performance of a multi-task convolutional neural network to segment and classify HRME images. One thousand four hundred eighty-six subjects completed the study; 435 (29%) subjects had CIN Grade 2 or more severe (CIN2+) diagnosis. HRME with morphologic image analysis for detection of CIN Grade 3 or more severe diagnoses (CIN3+) was similarly sensitive (95.6% vs 96.2%, P = .81) and specific (56.6% vs 58.7%, P = .18) as colposcopy. HRME with morphologic image analysis for detection of CIN2+ was slightly less sensitive (91.7% vs 95.6%, P < .01) and specific (59.7% vs 63.4%, P = .02) than colposcopy. Images from 870 subjects were used to train a multi-task convolutional neural network-based algorithm and images from the remaining 616 were used to validate its performance. There were no significant differences in the sensitivity and specificity of HRME with neural network analysis vs colposcopy for detection of CIN2+ or CIN3+. Using a neural network-based algorithm, HRME has comparable sensitivity and specificity to colposcopy for detection of CIN2+. HRME could provide a low-cost, point-of-care alternative to colposcopy and biopsy in the prevention of cervical cancer.

Keywords: cervical cancer prevention; deep learning; diagnostic imaging; high-resolution microendoscopy; point-of-care.

Conflict of interest statement

Conflict of interest

R. Richards-Kortum is an inventor on patents owned by the University of Texas licensed to Remicalm LLC. P. E. Castle has received HPV tests and assays for research at a reduced or no cost from Roche, Becton Dickinson, Cepheid, and Arbor Vita Corporation. No potential conflicts of interest were disclosed by the other authors.

© 2021 UICC.

Figures

Figure 1:

Photograph of high-resolution microendoscope (HRME) and colposcope in the clinic.

Figure 2:

Flow diagram of subjects assessed for study eligibility and participants enrolled in and completing the study. * Positive cytology test results included the following: ASC-US, ASC-H, LSIL, HSIL, and AGC, positive HPV test results included: HPV16 positive, HPV18 positive, pooled hrHPV positive (31, 33, 35, 39, 45, 51, 52, 56, 58, 59, 66 and 68) † Exclusions are reported as n (%), with percentages based on the total from the previous box.

Figure 3:

Diagnostic performance of colposcopy and HRME with morphologic image analysis using histopathology as the gold standard. (A) Per-patient HRME morphologic abnormality scores stratified by histopathology result. The solid line represents the prospective cutoff for positivity by morphologic image analysis. Bars overlaid on scatter plots indicate mean and 95% confidence intervals within each category. (B-C) Receiver operator characteristic curves of HRME with morphologic image analysis for detection of CIN2+ and CIN3+. Prospective performance of colposcopy (low-grade or more severe) and HRME with morphologic image analysis using the prospective positivity threshold are plotted on ROC curves for reference. (D) Cross tabulation of outcomes for colposcopy (low-grade or more severe) and HRME with morphologic image analysis by pathology result for each patient. (E-F) Comparisons of the sensitivity and specificity of colposcopy and HRME with morphologic image analysis for detection of CIN2+ and CIN3+. Error bars represent 95% confidence intervals. The following symbols indicate p-value results as follows: ns (P>0.05), *(P≤0.05), **(P≤0.01), ***(P≤0.001), ****(P≤0.0001).

Figure 4:. Diagnostic performance of HRME using a multi-task CNN.

(A) Per-patient HRME multi-task CNN scores stratified by histopathology result. The solid line represents the cutoff for positivity by multi-task CNN for comparison with colposcopy (low-grade or more severe). Bars overlaid on scatter plots indicate mean and 95% confidence intervals within each column. (B-C) Receiver operator characteristic curves of HRME with multi-task CNN analysis for detection of CIN2+ and CIN3+. Performance of colposcopy (low-grade or more severe) are HRME with multi-task CNN analysis using the post-hoc positivity threshold are plotted on ROC curves for reference. (D) Cross tabulation of outcomes for colposcopy (low-grade or more severe) and multi-task CNN HRME classification by pathology result for each patient. (E-F) Comparisons of the sensitivity and specificity of colposcopy and HRME with multi-task CNN analysis for detection of both CIN2+ and CIN3+. Error bars represent 95% confidence intervals. The following symbols indicate p-value results as follows: ns (P>0.05), *(P≤0.05), **(P≤0.01).

Figure 5:. Diagnostic performance of HRME using morphologic image analysis and the multi-task CNN.

ROC analysis comparing CIN2+ detection using morphologic image analysis with the multi-task CNN. (A) ROC curves for all 789 images in the validation/test sets. (B) ROC curves for 559 images with a colposcopic impression of squamous tissue. (C) ROC curves for 225 images with a colposcopic impression of columnar tissue or metaplasia.

Figure 6:. Example HRME images.

(A) Colposcopically normal, squamous epithelium with small, round, uniform nuclei. The image was classified as negative by real-time morphologic image analysis as well as histopathology. (B) Colposcopically abnormal squamous epithelium exhibiting enlarged, crowded, pleomorphic nuclei. The image was classified as positive by morphologic image analysis and the multi-task CNN; the histopathology result was high-grade dysplasia (CIN3). (C) Colposcopically abnormal, metaplastic epithelium with moderate nuclei crowding. The histopathology result was low-grade dysplasia (CIN1) with columnar tissue present. This image was incorrectly classified as positive by the prospective morphologic image analysis but correctly classified as negative by multi-task CNN analysis.