Literature DB >> 12807948

Chapter 10: Cervical cancer screening using visualization techniques.

Thomas C Wright1.   

Abstract

There is a resurgence of interest in the use of visual techniques to identify cervical intraepithelial neoplasia (CIN). These visual techniques can be divided into two general categories. One is the simple visual screening method, such as direct visual inspection (DVI), during which the cervix is visualized with either the naked eye or a low-power magnification device after the application of a solution of 3% to 5% acetic acid that is used as a chemical contrast agent to highlight regions of CIN. DVI has been evaluated in a number of large clinical trials and is considered by some to be a possible alternative to cervical cytology for primary cervical cancer screening in low-resource settings. The advantages of DVI compared with cervical cytology for these settings are that it is inexpensive, it does not require a laboratory infrastructure, and it provides an immediate result, allowing the use of "screen and treat" protocols. The major disadvantage of DVI is that it is relatively nonspecific and that its sensitivity is low compared with testing for human papillomavirus. The other category of visual techniques includes devices that use electro-optical sensors and light of specific wavelengths produced by lasers or specialized light sources to identify and localize regions of CIN on the cervix. Although these "high-technology" devices are not yet in routine clinical use, several groups and companies have such devices in clinical trials.

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Year:  2003        PMID: 12807948     DOI: 10.1093/oxfordjournals.jncimonographs.a003485

Source DB:  PubMed          Journal:  J Natl Cancer Inst Monogr        ISSN: 1052-6773


  11 in total

1.  Determinants of VIA (Visual Inspection of the Cervix After Acetic Acid Application) positivity in cervical cancer screening of women in a peri-urban area in Andhra Pradesh, India.

Authors:  Haripriya Vedantham; Michelle I Silver; B Kalpana; C Rekha; B P Karuna; K Vidyadhari; S Mrudula; Brigitte M Ronnett; K Vijayaraghavan; Gayatri Ramakrishna; Pavani Sowjanya; Shantha Laxmi; Keerti V Shah; Patti E Gravitt
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2010-05       Impact factor: 4.254

2.  Quantitative physiology of the precancerous cervix in vivo through optical spectroscopy.

Authors:  Vivide Tuan-Chyan Chang; Peter S Cartwright; Sarah M Bean; Greg M Palmer; Rex C Bentley; Nirmala Ramanujam
Journal:  Neoplasia       Date:  2009-04       Impact factor: 5.715

Review 3.  Review of the Standard and Advanced Screening, Staging Systems and Treatment Modalities for Cervical Cancer.

Authors:  Siaw Shi Boon; Ho Yin Luk; Chuanyun Xiao; Zigui Chen; Paul Kay Sheung Chan
Journal:  Cancers (Basel)       Date:  2022-06-13       Impact factor: 6.575

Review 4.  Screening for cancer: valuable or not?

Authors:  Frank L Meyskens
Journal:  Curr Oncol Rep       Date:  2004-11       Impact factor: 5.075

5.  Impact of patient adherence and test performance on the cost-effectiveness of cervical cancer screening in developing countries: the case of Honduras.

Authors:  Rebecca B Perkins; Sarah M Langrish; Linda J Stern; James F Burgess; Carol J Simon
Journal:  Womens Health Issues       Date:  2009-11-26

6.  Evaluation of a cervical cancer screening program based on HPV testing and LLETZ excision in a low resource setting.

Authors:  Margaret McAdam; Jerol Sakita; Len Tarivonda; James Pang; Ian H Frazer
Journal:  PLoS One       Date:  2010-10-07       Impact factor: 3.240

7.  Cervical cancer risk factors and feasibility of visual inspection with acetic acid screening in Sudan.

Authors:  Ahmed Ibrahim; Vibeke Rasch; Eero Pukkala; Arja R Aro
Journal:  Int J Womens Health       Date:  2011-04-04

8.  Lessons learned from successful Papanicolaou cytology cervical cancer prevention in the Socialist Republic of Vietnam.

Authors:  Eric J Suba; Stephen S Raab
Journal:  Diagn Cytopathol       Date:  2011-03-10       Impact factor: 1.582

9.  The costs of reducing loss to follow-up in South African cervical cancer screening.

Authors:  Jeremy D Goldhaber-Fiebert; Lynette E Denny; Michelle De Souza; Thomas C Wright; Louise Kuhn; Sue J Goldie
Journal:  Cost Eff Resour Alloc       Date:  2005-11-15

10.  Data-Driven Cervical Cancer Prediction Model with Outlier Detection and Over-Sampling Methods.

Authors:  Muhammad Fazal Ijaz; Muhammad Attique; Youngdoo Son
Journal:  Sensors (Basel)       Date:  2020-05-15       Impact factor: 3.576

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