Using acetowhite opacity index for detecting cervical intraepithelial neoplasia

Abstract

Cervical intraepithelial neoplasia (CIN) exhibits certain morphologic features that can be identified during a colposcopic exam. Immature metaplastic and dysplastic cervical squamous epithelia turn white after application of acetic acid during the exam. The whitening process occurs visually over several minutes and subjectively helps to discriminate between dysplastic and normal tissue. Digital imaging technologies enable us to assist the physician in analyzing acetowhite (acetic-acid-induced) lesions in a fully automatic way. We report a study designed to measure multiple parameters of the acetowhitening process from two images captured with a digital colposcope. One image is captured before the acetic acid application, and the other is captured after the acetic acid application. The spatial change of the acetowhitening is extracted using color and texture information in the post-acetic-acid image; the temporal change is extracted from the intensity and color changes between the post-acetic-acid and pre-acetic-acid images with an automatic alignment. In particular, we propose an automatic means to calculate an opacity index that indicates the grades of temporal change. The imaging and data analysis system is evaluated with a total of 99 human subjects. The proposed opacity index demonstrates a sensitivity and specificity of 94 and 87%, respectively, for discriminating high-grade dysplasia (CIN2+) from normal and low-grade subjects, considering histology as the gold standard.

Dynamic spectral imaging colposcopy: higher sensitivity for detection of premalignant cervical lesions

“…Although the DSI acquisition period lasts approximately 3 minutes, the acetowhitening effect can last several minutes more, 13,17,18 which is the reason why no second DSI assessment can be performed immediately after the first. At the end of the examination, the DSI information is concisely presented in the form of a colour-coded map, which can be overlaid onto the colour image of the tissue (Figure 2), to assist the identification of the location and severity of cervical lesions.…”

“…13,17,18 This is not always practical in the day-to-day clinic routine. Sometimes it would have been convenient to repeat the examination, for instance when during the first examination only part of the transformation zone could be visualised.…”

“…Furthermore, no second DSI examination can be performed directly after the first because of the acetowhitening effect which can last up to 45 minutes and can interfere with a DSI measurement. 13,17,18 This is not always practical in the day-to-day clinic routine. Sometimes it would have been convenient to repeat the examination, for instance when during the first examination only part of the transformation zone could be visualised.…”

Development of algorithms for automated detection of cervical pre-cancers with a low-cost, point-of-care, Pocket colposcope

“…Several groups working to create algorithms for automated computer-aided colposcopy have shown proof of concept and feasibility using traditional classification methods with handcrafted feature extraction, classifier training, and validation [18][19][20][21][22][23][24][25][26][27][28]. The majority of these methods have been applied to the use of VIA only, which, on its own, suffers from limitations in sensitivity and specificity [7,8,[29][30][31][32][33].…”

Wavelet and physical parametric analysis of the AcetoWhitening optical effect: Comparative evaluation of performances in non-invasive diagnosis of cervical Neoplasia

“…Wu et al [12] [14] propose an automated calculation of the so called opacity index to discriminate high grade lesions from low grade and normal tissue with 94% SE and 87% SP. Acosta-Mesa et al [15] reports results from the use of a 20-Nearest Neighbor (NN) classifier over the entire time course of the A W temporal pattern to distinguish automatically normal from abnormal lesions with the method reaching 71 % SE and 59% SP.…”