Dataset Information

Quantification of cervical spinal stenosis by automated 3D MRI segmentation of spinal cord and cerebrospinal fluid space.

ABSTRACT:

Design

Prospective diagnostic study.

Objectives

Anatomical evaluation and graduation of the severity of spinal stenosis is essential in degenerative cervical spine disease. In clinical practice, this is subjectively categorized on cervical MRI lacking an objective and reliable classification. We implemented a fully-automated quantification of spinal canal compromise through 3D T2-weighted MRI segmentation.

Setting

Medical Center - University of Freiburg, Germany.

Methods

Evaluation of 202 participants receiving 3D T2-weighted MRI of the cervical spine. Segments C2/3 to C6/7 were analyzed for spinal cord and cerebrospinal fluid space volume through a fully-automated segmentation based on a trained deep convolutional neural network. Spinal canal narrowing was characterized by relative values, across sever segments as adapted Maximal Canal Compromise (aMCC), and within the index segment as adapted Spinal Cord Occupation Ratio (aSCOR). Additionally, all segments were subjectively categorized by three observers as "no", "relative" or "absolute" stenosis. Computed scores were applied on the subjective categorization.

Results

798 (79.0%) segments were subjectively categorized as "no" stenosis, 85 (8.4%) as "relative" stenosis, and 127 (12.6%) as "absolute" stenosis. The calculated scores revealed significant differences between each category (p ≤ 0.001). Youden's Index analysis of ROC curves revealed optimal cut-offs to distinguish between "no" and "relative" stenosis for aMCC = 1.18 and aSCOR = 36.9%, and between "relative" and "absolute" stenosis for aMCC = 1.54 and aSCOR = 49.3%.

Conclusion

The presented fully-automated segmentation algorithm provides high diagnostic accuracy and objective classification of cervical spinal stenosis. The calculated cut-offs can be used for convenient radiological quantification of the severity of spinal canal compromise in clinical routine.

SUBMITTER: Hohenhaus M

PROVIDER: S-EPMC11230899 | biostudies-literature | 2024 Jul

REPOSITORIES: biostudies-literature

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Publications

Quantification of cervical spinal stenosis by automated 3D MRI segmentation of spinal cord and cerebrospinal fluid space.

Hohenhaus Marc M Klingler Jan-Helge JH Scholz Christoph C Watzlawick Ralf R Hubbe Ulrich U Beck Jürgen J Reisert Marco M Würtemberger Urs U Kremers Nico N Wolf Katharina K

Spinal cord 20240416 7

<h4>Design</h4>Prospective diagnostic study.<h4>Objectives</h4>Anatomical evaluation and graduation of the severity of spinal stenosis is essential in degenerative cervical spine disease. In clinical practice, this is subjectively categorized on cervical MRI lacking an objective and reliable classification. We implemented a fully-automated quantification of spinal canal compromise through 3D T2-weighted MRI segmentation.<h4>Setting</h4>Medical Center - University of Freiburg, Germany.<h4>Methods ...[more]

PMID: 38627568

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Project description:BackgroundDegenerative cervical spinal cord compression is becoming increasingly prevalent, yet the MRI criteria that define compression are vague, and vary between studies. This contribution addresses the detection of compression by means of the Spinal Cord Toolbox (SCT) and assesses the variability of the morphometric parameters extracted with it.MethodsProspective cross-sectional study. Two types of MRI examination, 3 and 1.5 T, were performed on 66 healthy controls and 118 participants with cervical spinal cord compression. Morphometric parameters from 3T MRI obtained by Spinal Cord Toolbox (cross-sectional area, solidity, compressive ratio, torsion) were combined in multivariate logistic regression models with the outcome (binary dependent variable) being the presence of compression determined by two radiologists. Inter-trial (between 3 and 1.5 T) and inter-rater (three expert raters and SCT) variability of morphometric parameters were assessed in a subset of 35 controls and 30 participants with compression.ResultsThe logistic model combining compressive ratio, cross-sectional area, solidity, torsion and one binary indicator, whether or not the compression was set at level C6/7, demonstrated outstanding compression detection (area under curve =0.947). The single best cut-off for predicted probability calculated using a multiple regression equation was 0.451, with a sensitivity of 87.3% and a specificity of 90.2%. The inter-trial variability was better in Spinal Cord Toolbox (intraclass correlation coefficient was 0.858 for compressive ratio and 0.735 for cross-sectional area) compared to expert raters (mean coefficient for three expert raters was 0.722 for compressive ratio and 0.486 for cross-sectional area). The analysis of inter-rater variability demonstrated general agreement between SCT and three expert raters, as the correlations between SCT and raters were generally similar to those of the raters between one another.ConclusionsThis study demonstrates successful semi-automated compression detection based on four parameters. The inter-trial variability of parameters established through two MRI examinations was conclusively better for Spinal Cord Toolbox compared with that of three experts' manual ratings.

Project description:BackgroundThe influence of coughing, on the biomechanical environment in the spinal subarachnoid space (SAS) in the presence of a cerebrospinal fluid flow stenosis, is thought to be an important etiological factor in craniospinal disorders, including syringomyelia (SM), Chiari I malformation, and hydrocephalus. The aim of this study was to investigate SAS and syrinx pressures during simulated coughing using in vitro models and to provide information for the understanding of the craniospinal fluid system dynamics to help develop better computational models.MethodsFour in vitro models were constructed to be simplified representations of: 1) non-communicating SM with spinal SAS stenosis; 2) non-communicating SM due to spinal SAS stenosis with a distensible spinal column; 3) non-communicating SM post surgical removal of a spinal SAS stenosis; and 4) a spinal SAS stenosis due to spinal trauma. All of the models had a flexible spinal cord. To simulate coughing conditions, an abrupt CSF pressure pulse (~ 5 ms) was imposed at the caudal end of the spinal SAS by a computer-controlled pump. Pressure measurements were obtained at 4 cm intervals along the spinal SAS and syrinx using catheter tip transducers.ResultsPressure measurements during a simulated cough, showed that removal of the stenosis was a key factor in reducing pressure gradients in the spinal SAS. The presence of a stenosis resulted in a caudocranial pressure drop in the SAS, whereas pressure within the syrinx cavity varied little caudocranially. A stenosis in the SAS caused the syrinx to balloon outward at the rostral end and be compressed at the caudal end. A >90% SAS stenosis did not result in a significant Venturi effect. Increasing compliance of the spinal column reduced forces acting on the spinal cord. The presence of a syrinx in the cord when there was a stenosis in the SAS, reduced pressure forces in the SAS. Longitudinal pressure dissociation acted to suck fluid and tissue caudocranially in the SAS with a stenosis.ConclusionsPressures in the spinal SAS during a simulated cough in vitro had similar peak, transmural, and longitudinal pressures to in vivo measurements reported in the literature. The pressure wave velocities and pressure gradients during coughing (longitudinal pressure dissociation and transmural pressure) were impacted by alterations in geometry, compliance, and the presence of a syrinx and/or stenosis.

Dataset Information

Quantification of cervical spinal stenosis by automated 3D MRI segmentation of spinal cord and cerebrospinal fluid space.

Design

Objectives

Setting

Methods

Results

Conclusion

Publications

Quantification of cervical spinal stenosis by automated 3D MRI segmentation of spinal cord and cerebrospinal fluid space.

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