Diffusion-Weighted Imaging Distinguishes Between Osteomyelitis, Bone Marrow Edema, and Healthy Bone on Forefoot Magnetic Resonance Imaging.
bone marrow diseases
diffusion magnetic resonance imaging
magnetic resonance imaging
osteomyelitis
Journal
Journal of magnetic resonance imaging : JMRI
ISSN: 1522-2586
Titre abrégé: J Magn Reson Imaging
Pays: United States
ID NLM: 9105850
Informations de publication
Date de publication:
11 2022
11 2022
Historique:
revised:
16
01
2022
received:
20
11
2021
accepted:
19
01
2022
pubmed:
3
2
2022
medline:
15
10
2022
entrez:
2
2
2022
Statut:
ppublish
Résumé
Diagnosis of osteomyelitis by imaging can be challenging. The feasibility of diffusion-weighted imaging (DWI) as ancillary sequence was evaluated in this study. To evaluate DWI for differentiation between osteomyelitis, bone marrow edema, and healthy bone on forefoot magnetic resonance imaging (MRI). Prospective. A total of 60 consecutive patients undergoing forefoot MRI divided into three study groups (20 subjects each): osteomyelitis, bone marrow edema, and healthy bone. A 1.5T and 3T MRI scanners; readout-segmented multishot echo planar DWI. Two independent radiologists measured apparent diffusion coefficient (ADC) values within abnormal or healthy bone. ADC values were compared between groups (pairwise t-test with Bonferroni-Holm correction for multiple testing). Intraclass correlation coefficient (ICC) was calculated to assess inter-reader agreement. Threshold ADC values were determined as the cutoffs that maximized the sum of sensitivity and specificity. Receiver operating characteristic (ROC) analysis was performed with statistical threshold of P < 0.05. Inter-reader agreement was 0.92 in the healthy bone group and 0.78 in both the edema and osteomyelitis groups. Average ADC values were significantly different between groups: 1432 ± 222 × 10 DWI with ADC maps distinguishes between healthy and abnormal bone on forefoot MRI. Calculated cutoff values allow confirmation or exclusion of osteomyelitis in a high proportion of subjects. 2 TECHNICAL EFFICACY: Stage 2.
Sections du résumé
BACKGROUND
Diagnosis of osteomyelitis by imaging can be challenging. The feasibility of diffusion-weighted imaging (DWI) as ancillary sequence was evaluated in this study.
PURPOSE
To evaluate DWI for differentiation between osteomyelitis, bone marrow edema, and healthy bone on forefoot magnetic resonance imaging (MRI).
STUDY TYPE
Prospective.
SUBJECTS
A total of 60 consecutive patients undergoing forefoot MRI divided into three study groups (20 subjects each): osteomyelitis, bone marrow edema, and healthy bone.
FIELD STRENGTH/SEQUENCE
A 1.5T and 3T MRI scanners; readout-segmented multishot echo planar DWI.
ASSESSMENT
Two independent radiologists measured apparent diffusion coefficient (ADC) values within abnormal or healthy bone.
STATISTICAL TESTS
ADC values were compared between groups (pairwise t-test with Bonferroni-Holm correction for multiple testing). Intraclass correlation coefficient (ICC) was calculated to assess inter-reader agreement. Threshold ADC values were determined as the cutoffs that maximized the sum of sensitivity and specificity. Receiver operating characteristic (ROC) analysis was performed with statistical threshold of P < 0.05.
RESULTS
Inter-reader agreement was 0.92 in the healthy bone group and 0.78 in both the edema and osteomyelitis groups. Average ADC values were significantly different between groups: 1432 ± 222 × 10
DATA CONCLUSION
DWI with ADC maps distinguishes between healthy and abnormal bone on forefoot MRI. Calculated cutoff values allow confirmation or exclusion of osteomyelitis in a high proportion of subjects.
EVIDENCE LEVEL
2 TECHNICAL EFFICACY: Stage 2.
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
1571-1579Informations de copyright
© 2022 International Society for Magnetic Resonance in Medicine.
Références
Huisman TAGM. Diffusion-weighted imaging: Basic concepts and application in cerebral stroke and head trauma. Eur Radiol 2003;13:2283-2297. https://doi.org/10.1007/s00330-003-1843-6.
Pozzi G, Garcia Parra C, Stradiotti P, Tien TV, Luzzati A, Zerbi A. Diffusion-weighted MR imaging in differentiation between osteoporotic and neoplastic vertebral fractures. Eur Spine J 2012;21(Suppl 1):123-127. https://doi.org/10.1007/s00586-012-2227-x.
Schmid-Tannwald C, Schmid-Tannwald CM, Morelli JN, et al. Role of diffusion-weighted MRI in differentiation of hepatic abscesses from non-infected fluid collections. Clin Radiol 2014;69:687-694. https://doi.org/10.1016/j.crad.2014.01.028.
Barendregt AM, Mazzoli V, van Gulik EC, et al. Juvenile idiopathic arthritis: Diffusion-weighted MRI in the assessment of arthritis in the knee. Radiology 2020;295:373-380. https://doi.org/10.1148/radiol.2020191685.
Tang L, Zhou XJ. Diffusion MRI of cancer: From low to high b-values. J Magn Reson Imaging 2019;49:23-40. https://doi.org/10.1002/jmri.26293.
Dallaudière B, Lecouvet F, Vande Berg B, et al. Diffusion-weighted MR imaging in musculoskeletal diseases: Current concepts. Diagn Interv Imaging 2015;96:327-340. https://doi.org/10.1016/j.diii.2014.10.008.
Kaur A, Thukral CL, Khanna G, Singh P. Role of diffusion-weighted magnetic resonance imaging in the evaluation of vertebral bone marrow lesions. Pol J Radiol 2020;85:215-223. https://doi.org/10.5114/pjr.2020.95441.
Ozgen B, Oguz KK, Cila A. Diffusion MR imaging features of skull base osteomyelitis compared with skull base malignancy. AJNR Am J Neuroradiol 2011;32:179-184. https://doi.org/10.3174/ajnr.A2237.
Stejskal EO, Tanner JE. Spin diffusion measurements: Spin echoes in the presence of a time-dependent field gradient. J Chem Phys 1965;42:288-292. https://doi.org/10.1063/1.1695690.
Raya JG, Dietrich O, Reiser MF, Baur-Melnyk A. Techniques for diffusion-weighted imaging of bone marrow. Eur J Radiol 2005;55:64-73. https://doi.org/10.1016/j.ejrad.2005.01.014.
Bergeest JP, Jäger F. A comparison of five methods for signal intensity standardization in MRI. In: Tolxdorff T, Braun J, Deserno TM, Horsch A, Handels H, Meinzer HP, editors. Bildverarbeitung für Die Medizin. Informatik aktuell. Berlin, Heidelberg: Springer; 2008. https://doi.org/10.1007/978-3-540-78640-5_8.
Michoux NF, Ceranka JW, Vandemeulebroucke J, et al. Repeatability and reproducibility of ADC measurements: A prospective multicenter whole-body-MRI study. Eur Radiol 2021;31:4514-4527. https://doi.org/10.1007/s00330-020-07522-0.
Lavdas I, Miquel ME, McRobbie DW, Aboagye EO. Comparison between diffusion-weighted MRI (DW-MRI) at 1.5 and 3 tesla: A phantom study. J Magn Reson Imaging 2014;40:682-690. https://doi.org/10.1002/jmri.24397.
Eguchi Y, Ohtori S, Yamashita M, et al. Diffusion magnetic resonance imaging to differentiate degenerative from infectious endplate abnormalities in the lumbar spine. Spine 2011;36:E198-E202. https://doi.org/10.1097/BRS.0b013e3181d5ff05.
Zhang L, Wang Q, Wu X, et al. Baseline bone marrow ADC value of diffusion-weighted MRI: A potential independent predictor for progression and death in patients with newly diagnosed multiple myeloma. Eur Radiol 2021;31:1843-1852. https://doi.org/10.1007/s00330-020-07295-6.
Razek AAKA, Samir S. Diagnostic performance of diffusion-weighted MR imaging in differentiation of diabetic osteoarthropathy and osteomyelitis in diabetic foot. Eur J Radiol 2017;89:221-225. https://doi.org/10.1016/j.ejrad.2017.02.015.
Dietrich O, Biffar A, Reiser M, Baur-Melnyk A. Diffusion-weighted imaging of bone marrow. Semin Musculoskelet Radiol 2009;13:134-144. https://doi.org/10.1055/s-0029-1220884.
Padhani AR, van Ree K, Collins DJ, D'Sa S, Makris A. Assessing the relation between bone marrow signal intensity and apparent diffusion coefficient in diffusion-weighted MRI. Am J Roentgenol 2013;200:163-170. https://doi.org/10.2214/AJR.11.8185.
Ballon D, Dyke J, Schwartz LH, et al. Bone marrow segmentation in leukemia using diffusion and T (2) weighted echo planar magnetic resonance imaging. NMR Biomed 2000;13:321-328.
Ward R, Caruthers S, Yablon C, Blake M, DiMasi M, Eustace S. Analysis of diffusion changes in posttraumatic bone marrow using navigator-corrected diffusion gradients. Am J Roentgenol 2000;174:731-734. https://doi.org/10.2214/ajr.174.3.1740731.
Pui MH, Mitha A, Rae WID, Corr P. Diffusion-weighted magnetic resonance imaging of spinal infection and malignancy. J Neuroimaging 2005;15:164-170. https://doi.org/10.1111/j.1552-6569.2005.tb00302.x.
Giurato L, Meloni M, Izzo V, Uccioli L. Osteomyelitis in diabetic foot: A comprehensive overview. World J Diabetes 2017;8:135-142. https://doi.org/10.4239/wjd.v8.i4.135.
Rios AM, Rosenberg ZS, Bencardino JT, Rodrigo SP, Theran SG. Bone marrow edema patterns in the ankle and hindfoot: Distinguishing MRI features. AJR Am J Roentgenol 2011;197:W720-W729. https://doi.org/10.2214/AJR.10.5880.
Zanetti M, Bruder E, Romero J, Hodler J. Bone marrow edema pattern in osteoarthritic knees: Correlation between MR imaging and histologic findings. Radiology 2000;215:835-840. https://doi.org/10.1148/radiology.215.3.r00jn05835.
Bihan DL, Poupon C, Amadon A, Lethimonnier F. Artifacts and pitfalls in diffusion MRI. J Magn Reson Imaging 2006;24:478-488. https://doi.org/10.1002/jmri.20683.
Porter DA, Heidemann RM. High resolution diffusion-weighted imaging using readout-segmented echo-planar imaging, parallel imaging and a two-dimensional navigator-based reacquisition. Magn Reson Med 2009;62:468-475. https://doi.org/10.1002/mrm.22024.
Koo TK, Li MY. A guideline of selecting and reporting intraclass correlation coefficients for reliability research. J Chiropr Med 2016;15:155-163. https://doi.org/10.1016/j.jcm.2016.02.012.
Kim TK. T test as a parametric statistic. Korean J Anesthesiol 2015;68:540-546. https://doi.org/10.4097/kjae.2015.68.6.540.
Park SH, Goo JM, Jo C-H. Receiver operating characteristic (ROC) curve: Practical review for radiologists. Korean J Radiol 2004;5:11-18. https://doi.org/10.3348/kjr.2004.5.1.11.
Ahmadi ME, Morrison WB, Carrino JA, Schweitzer ME, Raikin SM, Ledermann HP. Neuropathic arthropathy of the foot with and without superimposed osteomyelitis: MR imaging characteristics. Radiology 2006;238:622-631. https://doi.org/10.1148/radiol.2382041393.
Tan PL, Teh J. MRI of the diabetic foot: Differentiation of infection from neuropathic change. BJR 2007;80:939-948. https://doi.org/10.1259/bjr/30036666.
Martín Noguerol T, Luna Alcalá A, Beltrán LS, Gómez Cabrera M, Broncano Cabrero J, Vilanova JC. Advanced MR imaging techniques for differentiation of neuropathic arthropathy and osteomyelitis in the diabetic foot. Radiographics 2017;37:1161-1180. https://doi.org/10.1148/rg.2017160101.