Carl A J Puylaert1, Peter J Schüffler2, Robiel E Naziroglu3, Jeroen A W Tielbeek4, Zhang Li5, Jesica C Makanyanga6, Charlotte J Tutein Nolthenius4, C Yung Nio4, Douglas A Pendsé6, Alex Menys6, Cyriel Y Ponsioen7, David Atkinson6, Alastair Forbes8, Joachim M Buhmann9, Thomas J Fuchs10, Haralambos Hatzakis11, Lucas J van Vliet3, Jaap Stoker4, Stuart A Taylor6, Frans M Vos12. 1. Department of Radiology and Nuclear Medicine, Academic Medical Centre, Meibergdreef 9, P.O 22660, 1100DD, Amsterdam, The Netherlands. Electronic address: c.a.puylaert@amc.uva.nl. 2. Department of Computer Sciences, Eidgenössische Technische Hochschule Zurich, Zurich, Switzerland; Department of Medical Physics, Memorial Sloan-Kettering Cancer Center, New York, New York. 3. Department of Imaging Physics, Delft University of Technology, Delft, The Netherlands. 4. Department of Radiology and Nuclear Medicine, Academic Medical Centre, Meibergdreef 9, P.O 22660, 1100DD, Amsterdam, The Netherlands. 5. Department of Imaging Physics, Delft University of Technology, Delft, The Netherlands; College of Aerospace Science and Engineering, National University of Defense Technology, Changsha, China. 6. Center for Medical Imaging, University College London Hospitals National Health Service Foundation Trust, London, UK. 7. Department of Gastroenterology, Academic Medical Centre, Amsterdam, The Netherlands. 8. Norwich Medical School, University of East Anglia, Norwich, UK. 9. Department of Computer Sciences, Eidgenössische Technische Hochschule Zurich, Zurich, Switzerland. 10. Department of Medical Physics, Memorial Sloan-Kettering Cancer Center, New York, New York. 11. Biotronics3D Ltd, London, UK. 12. Department of Radiology and Nuclear Medicine, Academic Medical Centre, Meibergdreef 9, P.O 22660, 1100DD, Amsterdam, The Netherlands; Department of Imaging Physics, Delft University of Technology, Delft, The Netherlands.
Abstract
RATIONALE AND OBJECTIVES: The objective of this study was to develop and validate a predictive magnetic resonance imaging (MRI) activity score for ileocolonic Crohn disease activity based on both subjective and semiautomatic MRI features. MATERIALS AND METHODS: An MRI activity score (the "virtual gastrointestinal tract [VIGOR]" score) was developed from 27 validated magnetic resonance enterography datasets, including subjective radiologist observation of mural T2 signal and semiautomatic measurements of bowel wall thickness, excess volume, and dynamic contrast enhancement (initial slope of increase). A second subjective score was developed based on only radiologist observations. For validation, two observers applied both scores and three existing scores to a prospective dataset of 106 patients (59 women, median age 33) with known Crohn disease, using the endoscopic Crohn's Disease Endoscopic Index of Severity (CDEIS) as a reference standard. RESULTS: The VIGOR score (17.1 × initial slope of increase + 0.2 × excess volume + 2.3 × mural T2) and other activity scores all had comparable correlation to the CDEIS scores (observer 1: r = 0.58 and 0.59, and observer 2: r = 0.34-0.40 and 0.43-0.51, respectively). The VIGOR score, however, improved interobserver agreement compared to the other activity scores (intraclass correlation coefficient = 0.81 vs 0.44-0.59). A diagnostic accuracy of 80%-81% was seen for the VIGOR score, similar to the other scores. CONCLUSIONS: The VIGOR score achieves comparable accuracy to conventional MRI activity scores, but with significantly improved reproducibility, favoring its use for disease monitoring and therapy evaluation.
RATIONALE AND OBJECTIVES: The objective of this study was to develop and validate a predictive magnetic resonance imaging (MRI) activity score for ileocolonic Crohn disease activity based on both subjective and semiautomatic MRI features. MATERIALS AND METHODS: An MRI activity score (the "virtual gastrointestinal tract [VIGOR]" score) was developed from 27 validated magnetic resonance enterography datasets, including subjective radiologist observation of mural T2 signal and semiautomatic measurements of bowel wall thickness, excess volume, and dynamic contrast enhancement (initial slope of increase). A second subjective score was developed based on only radiologist observations. For validation, two observers applied both scores and three existing scores to a prospective dataset of 106 patients (59 women, median age 33) with known Crohn disease, using the endoscopic Crohn's Disease Endoscopic Index of Severity (CDEIS) as a reference standard. RESULTS: The VIGOR score (17.1 × initial slope of increase + 0.2 × excess volume + 2.3 × mural T2) and other activity scores all had comparable correlation to the CDEIS scores (observer 1: r = 0.58 and 0.59, and observer 2: r = 0.34-0.40 and 0.43-0.51, respectively). The VIGOR score, however, improved interobserver agreement compared to the other activity scores (intraclass correlation coefficient = 0.81 vs 0.44-0.59). A diagnostic accuracy of 80%-81% was seen for the VIGOR score, similar to the other scores. CONCLUSIONS: The VIGOR score achieves comparable accuracy to conventional MRI activity scores, but with significantly improved reproducibility, favoring its use for disease monitoring and therapy evaluation.
Authors: Ryan W Stidham; Binu Enchakalody; Akbar K Waljee; Peter D R Higgins; Stewart C Wang; Grace L Su; Ashish P Wasnik; Mahmoud Al-Hawary Journal: Inflamm Bowel Dis Date: 2020-04-11 Impact factor: 5.325
Authors: Ruaridh M Gollifer; Alex Menys; Jesica Makanyanga; Carl Aj Puylaert; Frans M Vos; Jaap Stoker; David Atkinson; Stuart Andrew Taylor Journal: Br J Radiol Date: 2018-06-19 Impact factor: 3.039