The first step toward diagnosing female genital schistosomiasis by computer image analysis

Sigve Dhondup Holmen; Elisabeth Kleppa; Kristine Lillebø; Pavitra Pillay; Lisette van Lieshout; Myra Taylor; Fritz Albregtsen; Birgitte J Vennervald; Mathias Onsrud; Eyrun Floerecke Kjetland

doi:10.4269/ajtmh.15-0071

The first step toward diagnosing female genital schistosomiasis by computer image analysis

Sigve Dhondup Holmen, Elisabeth Kleppa, Kristine Lillebø, Pavitra Pillay, Lisette van Lieshout, Myra Taylor, Fritz Albregtsen, Birgitte J Vennervald, Mathias Onsrud, Eyrun Floerecke Kjetland

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Abstract

Schistosoma haematobium causes female genital schistosomiasis (FGS), which is a poverty-related disease in sub-Saharan Africa. Furthermore, it is co-endemic with human immunodeficiency virus (HIV), and biopsies from genital lesions may expose the individual to increased risk of HIV infection. However, microscopy of urine and hematuria are nonspecific and insensitive predictors of FGS and gynecological investigation requires extensive training. Safe and affordable diagnostic methods are needed. We explore a novel method of diagnosing FGS using computer color analysis of colposcopic images. In a cross-sectional study on young women in an endemic area, we found strong associations between the output from the computer color analysis and both clinical diagnosis (odds ratio [OR] = 5.97, P < 0.001) and urine microscopy for schistosomiasis (OR = 3.52, P = 0.004). Finally, using latent class statistics, we estimate that the computer color analysis yields a sensitivity of 80.5% and a specificity of 66.2% for the diagnosis of FGS.

Originalsprog	Engelsk
Tidsskrift	American Journal of Tropical Medicine and Hygiene
Vol/bind	93
Udgave nummer	1
Sider (fra-til)	80-86
Antal sider	7
ISSN	0002-9637
DOI	https://doi.org/10.4269/ajtmh.15-0071
Status	Udgivet - 1 jul. 2015

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title = "The first step toward diagnosing female genital schistosomiasis by computer image analysis",

abstract = "Schistosoma haematobium causes female genital schistosomiasis (FGS), which is a poverty-related disease in sub-Saharan Africa. Furthermore, it is co-endemic with human immunodeficiency virus (HIV), and biopsies from genital lesions may expose the individual to increased risk of HIV infection. However, microscopy of urine and hematuria are nonspecific and insensitive predictors of FGS and gynecological investigation requires extensive training. Safe and affordable diagnostic methods are needed. We explore a novel method of diagnosing FGS using computer color analysis of colposcopic images. In a cross-sectional study on young women in an endemic area, we found strong associations between the output from the computer color analysis and both clinical diagnosis (odds ratio [OR] = 5.97, P < 0.001) and urine microscopy for schistosomiasis (OR = 3.52, P = 0.004). Finally, using latent class statistics, we estimate that the computer color analysis yields a sensitivity of 80.5% and a specificity of 66.2% for the diagnosis of FGS.",

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T1 - The first step toward diagnosing female genital schistosomiasis by computer image analysis

AU - Holmen, Sigve Dhondup

AU - Kleppa, Elisabeth

AU - Lillebø, Kristine

AU - Pillay, Pavitra

AU - van Lieshout, Lisette

AU - Taylor, Myra

AU - Albregtsen, Fritz

AU - Vennervald, Birgitte J

AU - Onsrud, Mathias

AU - Kjetland, Eyrun Floerecke

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N2 - Schistosoma haematobium causes female genital schistosomiasis (FGS), which is a poverty-related disease in sub-Saharan Africa. Furthermore, it is co-endemic with human immunodeficiency virus (HIV), and biopsies from genital lesions may expose the individual to increased risk of HIV infection. However, microscopy of urine and hematuria are nonspecific and insensitive predictors of FGS and gynecological investigation requires extensive training. Safe and affordable diagnostic methods are needed. We explore a novel method of diagnosing FGS using computer color analysis of colposcopic images. In a cross-sectional study on young women in an endemic area, we found strong associations between the output from the computer color analysis and both clinical diagnosis (odds ratio [OR] = 5.97, P < 0.001) and urine microscopy for schistosomiasis (OR = 3.52, P = 0.004). Finally, using latent class statistics, we estimate that the computer color analysis yields a sensitivity of 80.5% and a specificity of 66.2% for the diagnosis of FGS.

AB - Schistosoma haematobium causes female genital schistosomiasis (FGS), which is a poverty-related disease in sub-Saharan Africa. Furthermore, it is co-endemic with human immunodeficiency virus (HIV), and biopsies from genital lesions may expose the individual to increased risk of HIV infection. However, microscopy of urine and hematuria are nonspecific and insensitive predictors of FGS and gynecological investigation requires extensive training. Safe and affordable diagnostic methods are needed. We explore a novel method of diagnosing FGS using computer color analysis of colposcopic images. In a cross-sectional study on young women in an endemic area, we found strong associations between the output from the computer color analysis and both clinical diagnosis (odds ratio [OR] = 5.97, P < 0.001) and urine microscopy for schistosomiasis (OR = 3.52, P = 0.004). Finally, using latent class statistics, we estimate that the computer color analysis yields a sensitivity of 80.5% and a specificity of 66.2% for the diagnosis of FGS.

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DO - 10.4269/ajtmh.15-0071

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EP - 86

JO - Journal. National Malaria Society

JF - Journal. National Malaria Society

IS - 1

ER -

The first step toward diagnosing female genital schistosomiasis by computer image analysis

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