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PERFORMANCE OF SMARTPHONE-BASED DIGITAL IMAGES FOR CERVICAL CANCER SCREENING IN A LOW-RESOURCE CONTEXT

Published online by Cambridge University Press:  20 June 2018

Phuong Lien Tran
Affiliation:
Gynecology Division, Department of Gynecology and Obstetrics, Geneva University Hospitalsphuong_lien_tran@yahoo.com
Caroline Benski
Affiliation:
Gynecology Division, Department of Gynecology and Obstetrics, Geneva University Hospitals, Saint Damien Healthcare Centre
Manuela Viviano
Affiliation:
Gynecology Division, Department of Gynecology and Obstetrics, Geneva University Hospitals
Patrick Petignat
Affiliation:
Gynecology Division, Department of Gynecology and Obstetrics, Geneva University Hospitals
Christophe Combescure
Affiliation:
Division of Clinical Epidemiology, Geneva University Hospitals
Jeromine Jinoro
Affiliation:
Saint Damien Healthcare Centre
Josea Lea Herinianasolo
Affiliation:
Saint Damien Healthcare Centre
Pierre Vassilakos
Affiliation:
Geneva Foundation for Medical Education and Research
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Abstract

Objectives:

Colposcopes are expensive, heavy, and need specialized technical service, which may outreach the capacity of low-resource settings. Our aim was to assess the performance of smartphone-based digital images for the detection of cervical intraepithelial neoplasia grade 2 or worse (CIN2+).

Methods:

Human papillomavirus (HPV)-positive women recruited through a cervical cancer screening campaign had VIA/VILI assessment (visual inspection after application of acetic acid/lugol's iodine). Cervical digital images were captured with a smartphone camera, randomly coded with no prior selection and distributed on an online database (Google Forms) for evaluation. Healthcare providers were invited to evaluate the images and identify CIN2+. The gold standard was the histopathological diagnosis. The sensitivity and specificity for the detection of CIN2+ was assessed for each reader and reported with the 95 percent confidence interval (Clopper-Pearson method).

Results:

One hundred twenty-five consecutive HPV-positive women were included, with 19 CIN2+ (15.2 percent). Forty-five gynecologists completed the assessment, one-third were considered as experts (>50 colposcopies) and two-thirds as novices (<50 colposcopies). The sensitivity and specificity for CIN 2+ detection was 71.3 percent (67.0–75.7 percent) and 62.4 percent (57.5–67.4 percent), respectively. The performance of novices and experts was similar. The readers assessed 73.1 percent of images as acceptable for diagnostic.

Conclusion:

Smartphone-based digital images, with its high portability, have a great potential for the diagnosis of CIN2+ in low-resource context.

Information

Type
Assessment
Copyright
Copyright © Cambridge University Press 2018 
Figure 0

Table 1. Characteristics of the Readers (n = 45)

Figure 1

Table 2. Performance of Novice and Expert Readers

Figure 2

Figure 1. Sensitivity and specificity of digital images for novices (circle-shaped), experts (square), and overall readers (triangle).

Figure 3

Figure 2. Reader-specific proportion of images rated of good quality in cases (CIN2+) and in controls (negative and CIN1), among novices (circle-shaped), experts (square).

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