Abstract:
OBJECTIVES:The aim of this study was to apply texture analysis (TA) on paraspinal musculature in T2-weighted (T2w) magnetic resonance images (MRI) of symptomatic lumbar spinal stenosis (LSS) patients and correlate the findings with clinical outcome measures. METHODS:Ninety patients were prospectively enrolled in the multi-centric Lumbar Stenosis Outcome Study (LSOS). All patients received a T2w MRI, from which we selected axial images perpendicular to the intervertebral disc at level L3/4 for TA. Regions-of-interest (ROI) were drawn of the paraspinal musculature and 304 TA features/ ROI were calculated. As clinical outcome measurements, we analysed three commonly applied measures: Spinal Stenosis Measure (SSM), Roland-Morris Disability Questionnaire (RMDQ), as well as the Numeric Rating Scale (NRS). We used two machine learning-based classifiers: Decision table, and k-nearest neighbours (k-NN). RESULTS:We observed no meaningful correlation between TA in paraspinal musculature and the two clinical outcome measures SSM symptoms and SSM function, while a moderate correlation was observed regarding the outcome measures RMDQ (k-NN: r = 0.56) and NRS (Decision Table: r = 0.72). CONCLUSIONS:In conclusion, MR TA is a viable tool to quantify medical images and illustrate correlations of microarchitectural changes invisible to a human reader with potential clinical impact. KEY POINTS:• TA is feasible on paraspinal musculature using MRI. • TA on paraspinal musculature correlates with SSM and RMDQ. • TA may enable a statement regarding clinical impact of imaging findings.
journal_name
Eur Radioljournal_title
European radiologyauthors
Mannil M,Burgstaller JM,Held U,Farshad M,Guggenberger Rdoi
10.1007/s00330-018-5552-6subject
Has Abstractpub_date
2019-01-01 00:00:00pages
22-30issue
1eissn
0938-7994issn
1432-1084pii
10.1007/s00330-018-5552-6journal_volume
29pub_type
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pub_type: 临床试验,杂志文章
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