Semi-automatic Crohn’s disease severity estimation on MR imaging

Peter J. Schüffler; Dwarikanath Mahapatra; Robiel Naziroglu; Zhang Li; Carl A.J. Puylaert; Rado Andriantsimiavona; Franciscus M. Vos; Doug A. Pendsé; C. Yung Nio; Jaap Stoker; Stuart A. Taylor; Joachim M. Buhmann

doi:https://doi.org/10.1007/978-3-319-13692-9_12

Semi-automatic Crohn’s disease severity estimation on MR imaging

Peter J. Schüffler, Dwarikanath Mahapatra, Robiel Naziroglu, Zhang Li, Carl A.J. Puylaert, Rado Andriantsimiavona, Franciscus M. Vos, Doug A. Pendsé, C. Yung Nio, Jaap Stoker, Stuart A. Taylor, Joachim M. Buhmann

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

1 Citation (Scopus)

Abstract

Crohn’s disease (CD) is a chronic inflammatory bowel disease which can be visualized by magnetic resonance imaging (MRI). For CD grading, several non-invasive MRI based severity scores are known, most prominent the MaRIA and AIS. As these scores rely on manual MRI readings for individual bowel segments by trained radiologists, automated MRI assessment has been more and more focused in recent research. We show on a dataset of 27 CD patients that semi-automatically measured bowel wall thickness (ABWT) and dynamic contrast enhancement (DCE) completely outperform manual scorings: the segmental correlation to the Crohn’s Disease Endoscopic Index of Severity (CDEIS) of ABWT and DCE is significantly higher (r =.78) than that of MaRIA (r =.45) or AIS (r =.51). Also on a per-patient basis, the models with ABWT and DCE show significantly higher correlation (r =.69) to global CDEIS than MaRIA (r =.46).

Original language	English
Title of host publication	Abdominal Imaging
Subtitle of host publication	Computational and Clinical Applications - 6th International Workshop, ABDI 2014 held in conjunction with MICCAI 2014
Editors	Hiroyuki Yoshida, Janne J. Näppi, Sanjay Saini
Publisher	Springer - Verlag
Pages	128-138
Number of pages	11
ISBN (Electronic)	9783319136912
DOIs	https://doi.org/10.1007/978-3-319-13692-9_12
Publication status	Published - 2014
Externally published	Yes
Event	6th International Workshop on Abdominal Imaging: Computational and Clinical Applications, ABDI 2014 held in conjunction with 17th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2014 - Cambridge, United States Duration: 14 Sept 2014 → 14 Sept 2014

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	8676

Conference

Conference	6th International Workshop on Abdominal Imaging: Computational and Clinical Applications, ABDI 2014 held in conjunction with 17th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2014
Country/Territory	United States
City	Cambridge
Period	14/09/2014 → 14/09/2014

Keywords

Computer vision
Crohns disease
Crohns disease severity
MRI

Access to Document

https://doi.org/10.1007/978-3-319-13692-9_12

Cite this

Schüffler, P. J., Mahapatra, D., Naziroglu, R., Li, Z., Puylaert, C. A. J., Andriantsimiavona, R., Vos, F. M., Pendsé, D. A., Yung Nio, C., Stoker, J., Taylor, S. A., & Buhmann, J. M. (2014). Semi-automatic Crohn’s disease severity estimation on MR imaging. In H. Yoshida, J. J. Näppi, & S. Saini (Eds.), Abdominal Imaging: Computational and Clinical Applications - 6th International Workshop, ABDI 2014 held in conjunction with MICCAI 2014 (pp. 128-138). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8676). Springer - Verlag. https://doi.org/10.1007/978-3-319-13692-9_12

Schüffler, Peter J. ; Mahapatra, Dwarikanath ; Naziroglu, Robiel et al. / Semi-automatic Crohn’s disease severity estimation on MR imaging. Abdominal Imaging: Computational and Clinical Applications - 6th International Workshop, ABDI 2014 held in conjunction with MICCAI 2014. editor / Hiroyuki Yoshida ; Janne J. Näppi ; Sanjay Saini. Springer - Verlag, 2014. pp. 128-138 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{e70c854cbda742558086ae31ba348c6f,

title = "Semi-automatic Crohn{\textquoteright}s disease severity estimation on MR imaging",

abstract = "Crohn{\textquoteright}s disease (CD) is a chronic inflammatory bowel disease which can be visualized by magnetic resonance imaging (MRI). For CD grading, several non-invasive MRI based severity scores are known, most prominent the MaRIA and AIS. As these scores rely on manual MRI readings for individual bowel segments by trained radiologists, automated MRI assessment has been more and more focused in recent research. We show on a dataset of 27 CD patients that semi-automatically measured bowel wall thickness (ABWT) and dynamic contrast enhancement (DCE) completely outperform manual scorings: the segmental correlation to the Crohn{\textquoteright}s Disease Endoscopic Index of Severity (CDEIS) of ABWT and DCE is significantly higher (r =.78) than that of MaRIA (r =.45) or AIS (r =.51). Also on a per-patient basis, the models with ABWT and DCE show significantly higher correlation (r =.69) to global CDEIS than MaRIA (r =.46).",

keywords = "Computer vision, Crohns disease, Crohns disease severity, MRI",

author = "Sch{\"u}ffler, {Peter J.} and Dwarikanath Mahapatra and Robiel Naziroglu and Zhang Li and Puylaert, {Carl A.J.} and Rado Andriantsimiavona and Vos, {Franciscus M.} and Pends{\'e}, {Doug A.} and {Yung Nio}, C. and Jaap Stoker and Taylor, {Stuart A.} and Buhmann, {Joachim M.}",

year = "2014",

doi = "https://doi.org/10.1007/978-3-319-13692-9_12",

language = "English",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer - Verlag",

pages = "128--138",

editor = "Hiroyuki Yoshida and N{\"a}ppi, {Janne J.} and Sanjay Saini",

booktitle = "Abdominal Imaging",

note = "6th International Workshop on Abdominal Imaging: Computational and Clinical Applications, ABDI 2014 held in conjunction with 17th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2014 ; Conference date: 14-09-2014 Through 14-09-2014",

}

Schüffler, PJ, Mahapatra, D, Naziroglu, R, Li, Z, Puylaert, CAJ, Andriantsimiavona, R, Vos, FM, Pendsé, DA, Yung Nio, C, Stoker, J, Taylor, SA & Buhmann, JM 2014, Semi-automatic Crohn’s disease severity estimation on MR imaging. in H Yoshida, JJ Näppi & S Saini (eds), Abdominal Imaging: Computational and Clinical Applications - 6th International Workshop, ABDI 2014 held in conjunction with MICCAI 2014. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 8676, Springer - Verlag, pp. 128-138, 6th International Workshop on Abdominal Imaging: Computational and Clinical Applications, ABDI 2014 held in conjunction with 17th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2014, Cambridge, United States, 14/09/2014. https://doi.org/10.1007/978-3-319-13692-9_12

Semi-automatic Crohn’s disease severity estimation on MR imaging. / Schüffler, Peter J.; Mahapatra, Dwarikanath; Naziroglu, Robiel et al.
Abdominal Imaging: Computational and Clinical Applications - 6th International Workshop, ABDI 2014 held in conjunction with MICCAI 2014. ed. / Hiroyuki Yoshida; Janne J. Näppi; Sanjay Saini. Springer - Verlag, 2014. p. 128-138 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8676).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

TY - GEN

T1 - Semi-automatic Crohn’s disease severity estimation on MR imaging

AU - Schüffler, Peter J.

AU - Mahapatra, Dwarikanath

AU - Naziroglu, Robiel

AU - Li, Zhang

AU - Puylaert, Carl A.J.

AU - Andriantsimiavona, Rado

AU - Vos, Franciscus M.

AU - Pendsé, Doug A.

AU - Yung Nio, C.

AU - Stoker, Jaap

AU - Taylor, Stuart A.

AU - Buhmann, Joachim M.

PY - 2014

Y1 - 2014

N2 - Crohn’s disease (CD) is a chronic inflammatory bowel disease which can be visualized by magnetic resonance imaging (MRI). For CD grading, several non-invasive MRI based severity scores are known, most prominent the MaRIA and AIS. As these scores rely on manual MRI readings for individual bowel segments by trained radiologists, automated MRI assessment has been more and more focused in recent research. We show on a dataset of 27 CD patients that semi-automatically measured bowel wall thickness (ABWT) and dynamic contrast enhancement (DCE) completely outperform manual scorings: the segmental correlation to the Crohn’s Disease Endoscopic Index of Severity (CDEIS) of ABWT and DCE is significantly higher (r =.78) than that of MaRIA (r =.45) or AIS (r =.51). Also on a per-patient basis, the models with ABWT and DCE show significantly higher correlation (r =.69) to global CDEIS than MaRIA (r =.46).

AB - Crohn’s disease (CD) is a chronic inflammatory bowel disease which can be visualized by magnetic resonance imaging (MRI). For CD grading, several non-invasive MRI based severity scores are known, most prominent the MaRIA and AIS. As these scores rely on manual MRI readings for individual bowel segments by trained radiologists, automated MRI assessment has been more and more focused in recent research. We show on a dataset of 27 CD patients that semi-automatically measured bowel wall thickness (ABWT) and dynamic contrast enhancement (DCE) completely outperform manual scorings: the segmental correlation to the Crohn’s Disease Endoscopic Index of Severity (CDEIS) of ABWT and DCE is significantly higher (r =.78) than that of MaRIA (r =.45) or AIS (r =.51). Also on a per-patient basis, the models with ABWT and DCE show significantly higher correlation (r =.69) to global CDEIS than MaRIA (r =.46).

KW - Computer vision

KW - Crohns disease

KW - Crohns disease severity

KW - MRI

UR - http://www.scopus.com/inward/record.url?scp=84927604814&partnerID=8YFLogxK

U2 - https://doi.org/10.1007/978-3-319-13692-9_12

DO - https://doi.org/10.1007/978-3-319-13692-9_12

M3 - Conference contribution

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 128

EP - 138

BT - Abdominal Imaging

A2 - Yoshida, Hiroyuki

A2 - Näppi, Janne J.

A2 - Saini, Sanjay

PB - Springer - Verlag

T2 - 6th International Workshop on Abdominal Imaging: Computational and Clinical Applications, ABDI 2014 held in conjunction with 17th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2014

Y2 - 14 September 2014 through 14 September 2014

ER -

Schüffler PJ, Mahapatra D, Naziroglu R, Li Z, Puylaert CAJ, Andriantsimiavona R et al. Semi-automatic Crohn’s disease severity estimation on MR imaging. In Yoshida H, Näppi JJ, Saini S, editors, Abdominal Imaging: Computational and Clinical Applications - 6th International Workshop, ABDI 2014 held in conjunction with MICCAI 2014. Springer - Verlag. 2014. p. 128-138. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: https://doi.org/10.1007/978-3-319-13692-9_12

Semi-automatic Crohn’s disease severity estimation on MR imaging

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