Skip to main content
Key Specialties
Cardiology Diabetology Endocrinology Gastroenterology Geriatrics and Gerontology Gynecology and Obstetrics Hematology Infectious Disease Internal Medicine Nephrology Neurology Oncology Pediatrics Respiratory Medicine Rheumatology Surgery
Congress Coverage
2024 ACC Congress 2023 ESMO Congress 2023 EASD Congress 2023 ERS Congress 2023 ESC Congress
Clinical Collections
Advances in Alzheimer’s

Keynote webinar | Spotlight on medication adherence

LIVE: Thursday 27th June 2024, 18:00-19:30 (CEST)
Join our expert panel to discover why you need to understand the drivers of non-adherence in your patients, and how you can optimize medication adherence in your clinics to drastically improve patient outcomes.
ADVANCED SEARCH
Log in
Top
European Radiology
Published in: European Radiology 11/2016

01-11-2016 | Chest

Diffusion weighted imaging in cystic fibrosis disease: beyond morphological imaging

Authors: Pierluigi Ciet, Goffredo Serra, Eleni Rosalina Andrinopoulou, Silvia Bertolo, Mirco Ros, Carlo Catalano, Stefano Colagrande, Harm A. W. M. Tiddens, Giovanni Morana

Published in: European Radiology | Issue 11/2016

Login to get access

Abstract

Objectives

To explore the feasibility of diffusion-weighted imaging (DWI) to assess inflammatory lung changes in patients with Cystic Fibrosis (CF)

Methods

CF patients referred for their annual check-up had spirometry, chest-CT and MRI on the same day. MRI was performed in a 1.5 T scanner with BLADE and EPI-DWI sequences (b = 0–600 s/mm2). End-inspiratory and end-expiratory scans were acquired in multi-row scanners. DWI was scored with an established semi-quantitative scoring system. DWI score was correlated to CT sub-scores for bronchiectasis (CF-CTBE), mucus (CF-CTmucus), total score (CF-CTtotal-score), FEV1, and BMI. T-test was used to assess differences between patients with and without DWI-hotspots.

Results

Thirty-three CF patients were enrolled (mean 21 years, range 6–51, 19 female). 4 % (SD 2.6, range 1.5-12.9) of total CF-CT alterations presented DWI-hotspots. DWI-hotspots coincided with mucus plugging (60 %), consolidation (30 %) and bronchiectasis (10 %). DWItotal-score correlated (all p < 0.0001) positively to CF-CTBE (r = 0.757), CF-CTmucus (r = 0.759) and CF-CTtotal-score (r = 0.79); and negatively to FEV1 (r = 0.688). FEV1 was significantly higher (p < 0.0001) in patients without DWI-hotspots.

Conclusions

DWI-hotspots strongly correlated with radiological and clinical parameters of lung disease severity. Future validation studies are needed to establish the exact nature of DWI-hotspots in CF patients.

Key Points

• DWI hotspots only partly overlapped structural abnormalities on morphological imaging
• DWI strongly correlated with radiological and clinical indicators of CF-disease severity
• Patients with more DWI hotspots had lower lung function values
• Mucus score best predicted the presence of DWI-hotspots with restricted diffusion.
Appendix
Available only for authorised users
Literature
1.
Tiddens HAWM, Donaldson SH, Rosenfeld M, Paré PD (2010) Cystic fibrosis lung disease starts in the small airways: can we treat it more effectively? Pediatr Pulmonol 45:107–117CrossRefPubMed
2.
Loeve M, Gerbrands K, Hop WC et al (2011) Bronchiectasis and pulmonary exacerbations in children and young adults with cystic fibrosis. Chest 140:178–185CrossRefPubMed
3.
Conway S, Balfour-Lynn IM, De Rijcke K et al (2014) European cystic fibrosis society standards of care: framework for the cystic fibrosis centre. J Cyst Fibros 13:S3–S22CrossRefPubMed
4.
5.
Eichinger M, Heussel C-P, Kauczor H-U et al (2010) Computed tomography and magnetic resonance imaging in cystic fibrosis lung disease. J Magn Reson Imaging 32:1370–1378CrossRefPubMed
6.
Loeve M, Hop WCJ, De Bruijne M et al (2012) Chest computed tomography scores are predictive of survival in patients with cystic fibrosis awaiting lung transplantation. Am J Respir Crit Care Med 185:1096–1103CrossRefPubMed
7.
Kuo W, Ciet P, Tiddens HAWM et al (2014) Monitoring cystic fibrosis lung disease by computed tomography. Radiation risk in perspective. Am J Respir Crit Care Med 189:1328–1336CrossRefPubMed
8.
Wielpütz MO, Eichinger M, Puderbach M (2013) Magnetic resonance imaging of cystic fibrosis lung disease. J Thorac Imaging 28:151–159CrossRefPubMed
9.
Failo R, Wielopolski PA, Tiddens HAWM et al (2009) Lung morphology assessment using MRI: a robust ultra-short TR/TE 2D steady state free precession sequence used in cystic fibrosis patients. Magn Reson Med 61:299–306CrossRefPubMed
10.
11.
Ma W, Sheikh K, Svenningsen S et al (2015) Ultra-short echo-time pulmonary MRI: Evaluation and reproducibility in COPD subjects with and without bronchiectasis. J Magn Reson Imaging 41:1465–1474CrossRefPubMed
12.
Dournes G, Grodzki D, Macey J et al (2015) Quiet submillimeter MR imaging of the lung is feasible with a PETRA sequence at 1.5 T. Radiology 276:258–265CrossRefPubMed
13.
Tiddens HAWM, Stick SM, Wild JM et al (2015) Respiratory tract exacerbations revisited: ventilation, inflammation, perfusion, and structure (VIPS) monitoring to redefine treatment. Pediatr Pulmonol 50:S57–S65CrossRefPubMed
14.
Bauman G, Puderbach M, Heimann T et al (2013) Validation of fourier decomposition MRI with dynamic contrast-enhanced MRI using visual and automated scoring of pulmonary perfusion in young cystic fibrosis patients. Eur J Radiol 82:2371–2377CrossRefPubMed
15.
van Beek EJR, Hill C, Woodhouse N et al (2007) Assessment of lung disease in children with cystic fibrosis using hyperpolarized 3-Helium MRI: comparison with shwachman score, chrispin-Norman score and spirometry. Eur Radiol 17:1018–1024CrossRefPubMed
16.
Stadler A, Stiebellehner L, Jakob PM et al (2007) Quantitative and o(2) enhanced MRI of the pathologic lung: findings in emphysema, fibrosis, and cystic fibrosis. Int J Biomed Imaging 2007:23624CrossRefPubMedPubMedCentral
17.
18.
Attariwala R, Picker W (2013) Whole body MRI: improved lesion detection and characterization with diffusion weighted techniques. J Magn Reson Imaging 38:253–268CrossRefPubMedPubMedCentral
19.
Luna A, Sánchez-Gonzalez J, Caro P (2011) Diffusion-weighted imaging of the chest. Magn Reson Imaging Clin N Am 19:69–94CrossRefPubMed
20.
Gaviani P, Schwartz RB, Hedley-Whyte ET et al (2005) Diffusion-weighted imaging of fungal cerebral infection. Am J Neuroradiol 26:1115–1121PubMed
21.
Moritani T, Kim J, Capizzano AA et al (2014) Pyogenic and non-pyogenic spinal infections: emphasis on diffusion-weighted imaging for the detection of abscesses and pus collections. Br J Radiol 87:20140011CrossRefPubMedPubMedCentral
22.
Qi J, Olsen NJ, Price RR et al (2008) Diffusion-weighted imaging of inflammatory myopathies: polymyositis and dermatomyositis. J Magn Reson Imaging 27:212–217CrossRefPubMed
23.
Ream JM, Dillman JR, Adler J et al (2013) MRI diffusion-weighted imaging (DWI) in pediatric small bowel Crohn disease: correlation with MRI findings of active bowel wall inflammation. Pediatr Radiol 43:1077–1085CrossRefPubMed
24.
Miller MR, Hankinson J, Brusasco V et al (2005) Standardisation of spirometry. Eur Respir J 26:319–338CrossRefPubMed
25.
Tepper LA, Ciet P, Caudri D et al (2015) Validating chest MRI to detect and monitor cystic fibrosis lung disease in a pediatric cohort. Pediatr Pulmonol. doi:10.​1002/​ppul.​23328
26.
Tepper LA, Utens EMWJ, Caudri D et al (2013) Impact of bronchiectasis and trapped air on quality of life and exacerbations in cystic fibrosis. Eur Respir J 42:371–379CrossRefPubMed
27.
Liu H, Liu Y, Yu T, Ye N (2010) Usefulness of diffusion-weighted MR imaging in the evaluation of pulmonary lesions. Eur Radiol 20:807–815CrossRefPubMed
28.
Tanaka R, Horikoshi H, Nakazato Y et al (2009) Magnetic resonance imaging in peripheral lung adenocarcinoma: correlation with histopathologic features. J Thorac Imaging 24:4–9CrossRefPubMed
29.
Uto T, Takehara Y, Nakamura Y et al (2009) Higher sensitivity and specificity for diffusion-weighted imaging of malignant lung lesions without apparent diffusion coefficient quantification. Radiology 252:247–254CrossRefPubMed
30.
Cohen J (1988) Statistical power analysis for the behavioral sciences, 2 edn. Routledge
31.
32.
Burnham KP (2004) Multimodel Inference: understanding AIC and BIC in model selection. Sociol Methods Res 33:261–304CrossRef
33.
Deng Y, Li X, Lei Y, Liang C, Liu Z (2015) Use of diffusion-weighted magnetic resonance imaging to distinguish between lung cancer and focal inflammatory lesions: a comparison of intravoxel incoherent motion derived parameters and apparent diffusion coefficient. Acta Radiol 1–8. doi:10.​1177/​0284185115586091​
34.
Le Bihan D (2008) Intravoxel incoherent motion perfusion MR imaging: a wake-up call. Radiology 249:748–752CrossRefPubMed
35.
Chavhan GB, Alsabban Z, Babyn PS (2014) Diffusion-weighted imaging in pediatric body MR imaging: principles, technique, and emerging applications. Radiographics 34:E73–E88CrossRefPubMed
Metadata
Title
Diffusion weighted imaging in cystic fibrosis disease: beyond morphological imaging
Authors
Pierluigi Ciet
Goffredo Serra
Eleni Rosalina Andrinopoulou
Silvia Bertolo
Mirco Ros
Carlo Catalano
Stefano Colagrande
Harm A. W. M. Tiddens
Giovanni Morana
Publication date
01-11-2016
Publisher
Springer Berlin Heidelberg
Published in
European Radiology / Issue 11/2016
Print ISSN: 0938-7994
Electronic ISSN: 1432-1084
DOI
https://doi.org/10.1007/s00330-016-4248-z

Other articles of this Issue 11/2016

European Radiology 11/2016 Go to the issue

Interventional

Balloon pulmonary angioplasty: applicability of C-Arm CT for procedure guidance

Magnetic Resonance

Graph theoretical analysis reveals the reorganization of the brain network pattern in primary open angle glaucoma patients

Interventional

First clinical experience with a dedicated MRI-guided high-intensity focused ultrasound system for breast cancer ablation

Cardiac

Cardiac magnetic resonance findings predicting mortality in patients with pulmonary arterial hypertension: a systematic review and meta-analysis

Breast

Preoperative axillary lymph node evaluation in breast cancer patients by breast magnetic resonance imaging (MRI): Can breast MRI exclude advanced nodal disease?

Neuro

Optimising MR perfusion imaging: comparison of different software-based approaches in acute ischaemic stroke