Comparison of cervical screening using visual inspection with acetic acid (VIA) with Swede score using Gynocular in detecting cervical intraepithelial Neoplasia (CIN) lesions

2014 ◽  
Author(s):  
Ahmed Sekotory M Ahmed
Keyword(s):  
Acetic Acid ◽  
Cervical Intraepithelial Neoplasia ◽  
Visual Inspection ◽  
Cervical Screening ◽  
Intraepithelial Neoplasia

scholarly journals Detection of cervical intraepithelial neoplasia (CIN) by visual inspection of cervix with acetic acid (VIA) and its comparison to cervical cytology

2019 ◽  
Vol 31 (1) ◽  
pp. 15-20
Author(s):  
Nargis Zahan ◽  
Mosammat Nargis Shamima ◽  
Sharmin Sultana ◽  
Mohd Alamgir Hossain
Keyword(s):  
Cervical Cancer ◽  
Acetic Acid ◽  
Cervical Intraepithelial Neoplasia ◽  
Visual Inspection ◽  
Pap Smear ◽  
Early Stage ◽  
Invasive Cervical Cancer ◽  
Screening Method ◽  
Intraepithelial Neoplasia ◽  
Screening Tools

Background: Cervical cancer is the second most common cancer in women throughout the world, and it is the leading cause of cancer death among women in underdeveloped countries like Bangladesh is preventable and curable if detected at and early stage using proper screening tools. This study was done to see the effectiveness of VIA and find out the CIN and introduce as a complementary to cytology for diagnosing precancerous form of cervix. Materials & Methods: A total 175 subjects were studied & relevant data of cervix related patients have been collected. The data regarding Pap smear, VIA and biopsy have been taken and collected data was analysis by SPSS. Results: Out of 175 Patients VIA positive 53 (30.3%), Pap smear reports, 84 (48.0%) had inflammatory findings and 38 (21.7%) had dysplasia and biopsy result 41(23.4%) CIN positive. Sensitivity of VlA was 90.2%, specificity 88.1%, PPV 69.8%, NPV 96.7% and accuracy 88.6%. Sensitivity of Pap smear reports was 80.5%, specificity 96.3%, PPV 86.8%, NPV 94.2% and accuracy 92.6%. Conclusion: Visual inspection of cervix after application of acetic acid (VIA) is valid as cytology test for the identification of pre-invasive cervical cancer (CIN). Thus VIA is a useful screening method of Cervical Intraepithelial Neoplasia lesion as Pap smear. TAJ 2018; 31(1): 15-20

scholarly journals Accuracy of Smartphone Images of the Cervix After Acetic Acid Application for Diagnosing Cervical Intraepithelial Neoplasia Grade 2 or Greater in Women With Positive Cervical Screening: A Systematic Review and Meta-Analysis

2021 ◽  
pp. 1711-1721
Author(s):  
Emma R. Allanson ◽  
Natacha Phoolcharoen ◽  
Mila P. Salcedo ◽  
Bryan Fellman ◽  
Kathleen M. Schmeler
Keyword(s):  
Systematic Review ◽  
Acetic Acid ◽  
Positive Predictive Value ◽  
Cervical Intraepithelial Neoplasia ◽  
Predictive Value ◽  
Precancerous Lesions ◽  
Meta Analysis ◽  
Cervical Screening ◽  
Intraepithelial Neoplasia ◽  
Cervical Intraepithelial Neoplasia Grade

PURPOSE Smartphones are used in cervical screening for visual inspection after acetic acid or Lugol's iodine (VIA/VILI) application to capture and share images to improve the sensitivity and interobserver variability of VIA/VILI. We undertook a systematic review and meta-analysis assessing the diagnostic accuracy of smartphone images of the cervix at the time of VIA/VILI (termed S-VIA) in the detection of precancerous lesions in women undergoing cervical screening. METHODS This systematic review was conducted in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Studies from January 1, 2010, to June 30, 2020, were assessed. MEDLINE/PubMed, Embase, CINAHL, Cochrane, and LILACS were searched. Cohort and cross-sectional studies were considered. S-VIA was compared with the reference standard of histopathology. We excluded studies where additional technology was added to the smartphone including artificial intelligence, enhanced visual assessment, and other algorithms to automatically diagnose precancerous lesions. The primary outcome was the accuracy of S-VIA for the diagnosis of cervical intraepithelial neoplasia grade 2 or greater (CIN 2+). Data were extracted, and we plotted the sensitivity, specificity, negative predictive value, and positive predictive value of S-VIA using forest plots. This study was prospectively registered with The International Prospective Register of Systematic Reviews:CRD42020204024. RESULTS Six thousand three studies were screened, 71 full texts assessed, and eight studies met criteria for inclusion, with six included in the final meta-analysis. The sensitivity of S-VIA for the diagnosis of CIN 2+ was 74.56% (95% CI, 70.16 to 78.95; I2 61.30%), specificity was 61.75% (95% CI, 56.35 to 67.15; I2 95.00%), negative predictive value was 93.71% (95% CI, 92.81 to 94.61; I2 0%), and positive predictive value was 26.97% (95% CI, 24.13 to 29.81; I2 61.3%). CONCLUSION Our results suggest that S-VIA has accuracy in the detection of CIN 2+ and may provide additional support to health care providers delivering care in low-resource settings.

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

2018 ◽  
Author(s):  
Mercy Nyamewaa Asiedu ◽  
Anish Simhal ◽  
Usamah Chaudhary ◽  
Jenna L. Mueller ◽  
Christopher T. Lam ◽  
...  
Keyword(s):  
Acetic Acid ◽  
Visual Inspection ◽  
Point Of Care ◽  
Low Cost ◽  
Intraepithelial Neoplasia ◽  
Support Vector ◽  
Machine Model ◽  
Data Set ◽  
Automatic Feature Extraction ◽  
Lugol’S Iodine

AbstractGoalIn this work, we propose methods for (1) automatic feature extraction and classification for acetic acid and Lugol’s iodine cervigrams and (2) methods for combining features/diagnosis of different contrasts in cervigrams for improved performance.MethodsWe developed algorithms to pre-process pathology-labeled cervigrams and to extract simple but powerful color and textural-based features. The features were used to train a support vector machine model to classify cervigrams based on corresponding pathology for visual inspection with acetic acid, visual inspection with Lugol’s iodine, and a combination of the two contrasts.ResultsThe proposed framework achieved a sensitivity, specificity, and accuracy of 81.3%, 78.6%, and 80.0%, respectively when used to distinguish cervical intraepithelial neoplasia (CIN+) relative to normal and benign tissues. This is superior to the average values achieved by three expert physicians on the same data set for discriminating normal/benign cases from CIN+ (77% sensitivity, 51% specificity, 63% accuracy).ConclusionThe results suggest that utilizing simple color- and textural-based features from visual inspection with acetic acid and visual inspection with Lugol’s iodine images may provide unbiased automation of cervigrams.SignificanceThis would enable automated, expert-level diagnosis of cervical pre-cancer at the point-of-care.

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