Characteristics of Blood Vessels in Female Genital Schistosomiasis: Paving the Way for Objective Diagnostics at the Point of Care

Sigve Holmen, Hashini Nilushika Galappaththi-Arachchige, Elisabeth Kleppa, Pavitra Pillay, Thajasvarie Naicker, Myra Taylor, Mathias Onsrud, Eyrun Floerecke Kjetland, Fritz Albregtsen, Sigve Holmen, Hashini Nilushika Galappaththi-Arachchige, Elisabeth Kleppa, Pavitra Pillay, Thajasvarie Naicker, Myra Taylor, Mathias Onsrud, Eyrun Floerecke Kjetland, Fritz Albregtsen

Abstract

Background: The mucosal changes associated with female genital schistosomiasis (FGS) encompass abnormal blood vessels. These have been described as circular, reticular, branched, convoluted and having uneven calibre. However, these characteristics are subjective descriptions and it has not been explored which of them are specific to FGS.

Methods: In colposcopic images of young women from a schistosomiasis endemic area, we performed computerised morphologic analyses of the cervical vasculature appearing on the mucosal surface. Study participants where the cervix was classified as normal served as negative controls, women with clinically diagnosed FGS and presence of typical abnormal blood vessels visible on the cervical surface served as positive cases. We also included women with cervical inflammatory conditions for reasons other than schistosomiasis. By automating morphological analyses, we explored circular configurations, vascular density, fractal dimensions and fractal lacunarity as parameters of interest.

Results: We found that the blood vessels typical of FGS are characterised by the presence of circular configurations (p < 0.001), increased vascular density (p = 0.015) and increased local connected fractal dimensions (p = 0.071). Using these features, we were able to correctly classify 78% of the FGS-positive cases with an accuracy of 80%.

Conclusions: The blood vessels typical of FGS have circular configurations, increased vascular density and increased local connected fractal dimensions. These specific morphological features could be used diagnostically. Combined with colourimetric analyses, this represents a step towards making a diagnostic tool for FGS based on computerised image analysis.

Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1. Image analysis of female genital…
Fig 1. Image analysis of female genital schistosomiasis of the uterine cervix.
A. The original colour image. Note that there is a light reflection at 6 o'clock and parts of the speculum can be seen on the right hand side (artefacts). These were removed automatically in the image processing. B. The product of multiplying the inverted "green channel" (from the "Red-Green-Blue" (RGB) colour space with the "saturation channel" (from the "Hue-Saturation-Value" (HSV) colour space). C. The region of interest (ROI) of image B with all pixels below the mean grey value removed. D. The result of convolution of the circular template and image C. The darker areas represent higher degrees of roundness. E. The result of adaptive local thresholding of image B using a modified Niblack method. F. The final output image automatically generated by the image analysis. It shows the ectocervix with numerous abnormal blood vessels (black skeleton) and the centres of circular structures identified by template matching (yellow dots).
Fig 2. Scatterplots showing the co-variation of…
Fig 2. Scatterplots showing the co-variation of variables included in the regression model.
The distribution of values of each of the variables included in the regression model differ between the women with FGS and the two other groups: The number of circular template matches is higher, the distance between vessels is lower and the mean local connected fractal dimension tends to be lower, although the latter is not significant.
Fig 3. Receiver operating characteristics curve for…
Fig 3. Receiver operating characteristics curve for the diagnosis of FGS by blood vessel analysis.
The curve was generated using the regression model presented in Table 3. Area under the curve = 0.872.

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