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

11 Citations (Scopus)

134 Downloads (Pure)

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.

Original language	English
Journal	American Journal of Tropical Medicine and Hygiene
Volume	93
Issue number	1
Pages (from-to)	80-86
Number of pages	7
ISSN	0002-9637
DOIs	https://doi.org/10.4269/ajtmh.15-0071
Publication status	Published - 1 Jul 2015

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.4269/ajtmh.15-0071

The first step toward diagnosing female genital schistosomiasis by computer image analysisFinal published version, 252 KB

http://www.ajtmh.org/deliver/fulltext/14761645/93/1/80.pdf?itemId=%2Fcontent%2Fjournals%2F10.4269%2Fajtmh.15-0071&mimeType=pdf&containerItemId=content/journals/14761645Licence: CC BY

Cite this

@article{7c6339a8a5784719a8d5b95c54c3dbe6,

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.",

author = "Holmen, {Sigve Dhondup} and Elisabeth Kleppa and Kristine Lilleb{\o} and Pavitra Pillay and {van Lieshout}, Lisette and Myra Taylor and Fritz Albregtsen and Vennervald, {Birgitte J} and Mathias Onsrud and Kjetland, {Eyrun Floerecke}",

note = "{\textcopyright} The American Society of Tropical Medicine and Hygiene.",

year = "2015",

month = jul,

day = "1",

doi = "10.4269/ajtmh.15-0071",

language = "English",

volume = "93",

pages = "80--86",

journal = "American Journal of Tropical Medicine and Hygiene",

issn = "0002-9637",

publisher = "American Society of Tropical Medicine and Hygiene",

number = "1",

}

TY - JOUR

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

PY - 2015/7/1

Y1 - 2015/7/1

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.

U2 - 10.4269/ajtmh.15-0071

DO - 10.4269/ajtmh.15-0071

M3 - Journal article

C2 - 25918212

SN - 0002-9637

VL - 93

SP - 80

EP - 86

JO - American Journal of Tropical Medicine and Hygiene

JF - American Journal of Tropical Medicine and Hygiene

IS - 1

ER -

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

Abstract

UN SDGs

Access to Document

Fingerprint

Cite this