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A novel semi-automatic segmentation method for volumetric assessment of the colon based on magnetic resonance imaging

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Abstract

Purpose

To develop a novel semi-automatic segmentation method for quantification of the colon from magnetic resonance imaging (MRI).

Methods

Fourteen abdominal T2-weighted and dual-echo Dixon-type water-only MRI scans were obtained from four healthy subjects. Regions of interest containing the colon were outlined manually on the T2-weighted images. Segmentation of the colon and feces was obtained using k-means clustering and image registration. Regional colonic and fecal volumes were obtained. Inter-observer agreement between two observers was assessed using the Dice similarity coefficient as measure of overlap.

Results

Colonic segmentations showed wide variation in volume and morphology between subjects. Colon volumes of the four healthy subjects for both observers were (median [interquartile range]) ascending colon 200 mL [169.5–260], transverse 200.5 mL [113.5–242.5], descending 148 mL [121.5–178.5], sigmoid-rectum 277 mL [192–345], and total 819 mL [687–898.5]. Overlap agreement for the total colon segmentation between the two observers was high with a Dice similarity coefficient of 0.91 [0.84–0.94]. The colon volume to feces volume ratio was on average 0.7.

Conclusion

Regional colon volumes were comparable to previous findings using fully manual segmentation. The method showed good agreement between observers and may be used in future studies of gastrointestinal disorders to assess colon and fecal volume and colon morphology. Novel insight into morphology and quantitative assessment of the colon using this method may provide new biomarkers for constipation and abdominal pain compared to radiography which suffers from poor reliability.

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Acknowledgements

This study was supported by funding from Innovation Fund Denmark.

Conflict of interest

The authors declare that they have no conflict of interest.

Compliance with ethical standards

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Human and animal rights and informed consent

This article does not contain any studies with animals performed by any of the authors. Informed consent was obtained from all individual participants included in the study.

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Authors and Affiliations

  1. Mech-Sense, Department of Gastroenterology & Hepatology, Aalborg University Hospital, Mølleparkvej 4, 9000, Aalborg, Denmark

    Thomas Holm Sandberg, Matias Nilsson, Jakob Lykke Poulsen, Mikkel Gram & Asbjørn Mohr Drewes

  2. Mech-Sense, Department of Radiology, Aalborg University Hospital, Aalborg, Denmark

    Jens Brøndum Frøkjær

  3. Department of Health Science and Technology, Aalborg University, Aalborg, Denmark

    Lasse Riis Østergaard

  4. Department of Clinical Medicine, Aalborg University, Aalborg, Denmark

    Jens Brøndum Frøkjær & Asbjørn Mohr Drewes

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  1. Thomas Holm Sandberg
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Correspondence to Asbjørn Mohr Drewes.

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Sandberg, T.H., Nilsson, M., Poulsen, J.L. et al. A novel semi-automatic segmentation method for volumetric assessment of the colon based on magnetic resonance imaging. Abdom Imaging 40, 2232–2241 (2015). https://doi.org/10.1007/s00261-015-0475-z

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