R M Gollifer1, A Menys1, A Plumb1, K Mengoudi2, C A J Puylaert3, J A W Tielbeek3, C Y Ponsioen4, F M Vos5, J Stoker3, S A Taylor6, D Atkinson1. 1. Centre for Medical Imaging, University College London (UCL), London, UK. 2. Centre for Medical Image Computing, University College London (UCL), London, UK. 3. Department of Radiology and Nuclear Medicine, Amsterdam UMC, Academic Medical Center (AMC), University of Amsterdam, Amsterdam, Netherlands. 4. Department of Gastroenterology & Hepatology, Amsterdam UMC, University of Amsterdam, Netherlands. 5. Department of Radiology and Nuclear Medicine, Amsterdam UMC, Academic Medical Center (AMC), University of Amsterdam, Amsterdam, Netherlands; Quantitative Imaging Group, Delft University of Technology, Delft, Netherlands. 6. Centre for Medical Imaging, University College London (UCL), London, UK. Electronic address: stuart.taylor1@nhs.net.
Abstract
AIM: To investigate whether subjective radiologist grading of motility on magnetic resonance enterography (MRE) is as effective as software quantification, and to determine the combination of motility metrics with the strongest association with symptom severity. MATERIALS AND METHODS: One hundred and five Crohn's disease patients (52 male, 53 female, 16-68 years old, mean age 34 years old) recruited from two sites underwent MRE, including a 20 second breath-hold cine motility sequence. Each subject completed a Harvey-Bradshaw Index (HBI) symptom questionnaire. Five features within normally appearing bowel were scored visually by two experienced radiologists, and then quantified using automated analysis software, including (1) mean motility, (2) spatial motility variation, (3) temporal motility variation, (4) area of motile bowel, (5) intestinal distension. Multivariable linear regression derived the combination of features with the highest association with HBI score. RESULTS: The best automated metric combination was temporal variation (p<0.05) plus area of motile bowel (p<0.05), achieving an R2 adjusted value of 0.036. Spatial variation was also associated with symptoms (p<0.05, R2 adjusted = 0.034); however, when visually assessed by radiologists, none of the features had a significant relationship with the HBI score. CONCLUSION: Software quantified temporal and spatial variability in bowel motility are associated with abdominal symptoms in Crohn's disease. Subjective radiologist assessment of bowel motility is insufficient to detect aberrant motility. Automated analysis of motility patterns holds promise as an objective biomarker for aberrant physiology underlying symptoms in enteric disorders.
AIM: To investigate whether subjective radiologist grading of motility on magnetic resonance enterography (MRE) is as effective as software quantification, and to determine the combination of motility metrics with the strongest association with symptom severity. MATERIALS AND METHODS: One hundred and five Crohn's diseasepatients (52 male, 53 female, 16-68 years old, mean age 34 years old) recruited from two sites underwent MRE, including a 20 second breath-hold cine motility sequence. Each subject completed a Harvey-Bradshaw Index (HBI) symptom questionnaire. Five features within normally appearing bowel were scored visually by two experienced radiologists, and then quantified using automated analysis software, including (1) mean motility, (2) spatial motility variation, (3) temporal motility variation, (4) area of motile bowel, (5) intestinal distension. Multivariable linear regression derived the combination of features with the highest association with HBI score. RESULTS: The best automated metric combination was temporal variation (p<0.05) plus area of motile bowel (p<0.05), achieving an R2 adjusted value of 0.036. Spatial variation was also associated with symptoms (p<0.05, R2 adjusted = 0.034); however, when visually assessed by radiologists, none of the features had a significant relationship with the HBI score. CONCLUSION: Software quantified temporal and spatial variability in bowel motility are associated with abdominal symptoms in Crohn's disease. Subjective radiologist assessment of bowel motility is insufficient to detect aberrant motility. Automated analysis of motility patterns holds promise as an objective biomarker for aberrant physiology underlying symptoms in enteric disorders.