Magnetic Resonance Neurography

Kronlage, Moritz; Schwehr, Véronique; Schwarz, Dániel; Godel, Tim; Heiland, Sabine; Bendszus, Martin; Bäumer, Philipp

doi:10.1007/s00062-017-0633-5

Cited by 23 publications

(23 citation statements)

References 30 publications

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“…Our method could assist clinicians by providing a quantification of nerve volume, CSA, and lesion burden through a combination of morphometry and signal intensity analysis as shown in Figure 5 . Such analyses might allow distinguishing between healthy nerve and diseased nerve, and peripheral neuropathy type as it has been shown by others ( 5 , 7 – 11 ). Additionally, our segmentation could serve as a volume of interest for other quantitative MR methods like diffusion-weighted imaging, magnetization transfer imaging, and relaxometry ( 3 – 8 , 10 ), which might further be applied to assess total lesion burden, distribution pattern of lesions, and multi-model characterization of lesions.…”

Section: Discussionmentioning

confidence: 86%

Segmentation of Peripheral Nerves From Magnetic Resonance Neurography: A Fully-Automatic, Deep Learning-Based Approach

et al. 2018

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Diagnosis of peripheral neuropathies relies on neurological examinations, electrodiagnostic studies, and since recently magnetic resonance neurography (MRN). The aim of this study was to develop and evaluate a fully-automatic segmentation method of peripheral nerves of the thigh. T2-weighted sequences without fat suppression acquired on a 3 T MR scanner were retrospectively analyzed in 10 healthy volunteers and 42 patients suffering from clinically and electrophysiologically diagnosed sciatic neuropathy. A fully-convolutional neural network was developed to segment the MRN images into peripheral nerve and background tissues. The performance of the method was compared to manual inter-rater segmentation variability. The proposed method yielded Dice coefficients of 0.859 ± 0.061 and 0.719 ± 0.128, Hausdorff distances of 13.9 ± 26.6 and 12.4 ± 12.1 mm, and volumetric similarities of 0.930 ± 0.054 and 0.897 ± 0.109, for the healthy volunteer and patient cohorts, respectively. The complete segmentation process requires less than one second, which is a significant decrease to manual segmentation with an average duration of 19 ± 8 min. Considering cross-sectional area or signal intensity of the segmented nerves, focal and extended lesions might be detected. Such analyses could be used as biomarker for lesion burden, or serve as volume of interest for further quantitative MRN techniques. We demonstrated that fully-automatic segmentation of healthy and neuropathic sciatic nerves can be performed from standard MRN images with good accuracy and in a clinically feasible time.

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Section: Discussionmentioning

confidence: 86%

Segmentation of Peripheral Nerves From Magnetic Resonance Neurography: A Fully-Automatic, Deep Learning-Based Approach

et al. 2018

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“…To the authors' knowledge, normal T2 values of the sciatic nerve have been primarily gathered from few control groups of healthy subjects or asymptomatic patients that were formed for comparisons to diseased cohorts with symptoms, with only one recent study being available to date that aimed on the distinct exploration of normal T2 values of the sciatic nerve [31]. This study investigated 60 healthy individuals by applying a MESE sequence for T2 relaxometry at 3 Tesla and demonstrated physiological T2 values in 5 men and 5 women of every decade between 20 and 80 years [31]. The study reported mean T2 values of 70.85 ± 4.91 ms [31].…”

Section: Discussionmentioning

confidence: 99%

“…This study investigated 60 healthy individuals by applying a MESE sequence for T2 relaxometry at 3 Tesla and demonstrated physiological T2 values in 5 men and 5 women of every decade between 20 and 80 years [31]. The study reported mean T2 values of 70.85 ± 4.91 ms [31]. These values are, however, clearly higher in comparison to the T2 values obtained with the 3D T2-prepared TSE sequence in the present study, which were 44.6 ± 3.0 ms for the left and 44.5 ± 2.6 ms for the right distal sciatic nerve (according to measurements of R1).…”

Section: Discussionmentioning

confidence: 99%

“…To date, the report of normal values regarding T2 of the sciatic nerve is restricted to few data of control groups of healthy or asymptomatic patients formed for comparisons to patients with diseases and focal or systemic PNS affections. A recent study explicitly focused on the assessment of normal T2 values of the sciatic nerve by investigating a cohort of 60 healthy individuals by means of MRN using a multi-echo spin-echo (MESE) sequence for T2 relaxometry at 3 Tesla [ 31 ]. This study reported on physiological T2 values in five men and five women of every decade between 20 and 80 years and additionally evaluated associations with demographic variables [ 31 ].…”

Section: Introductionmentioning

confidence: 99%

“…A recent study explicitly focused on the assessment of normal T2 values of the sciatic nerve by investigating a cohort of 60 healthy individuals by means of MRN using a multi-echo spin-echo (MESE) sequence for T2 relaxometry at 3 Tesla [ 31 ]. This study reported on physiological T2 values in five men and five women of every decade between 20 and 80 years and additionally evaluated associations with demographic variables [ 31 ]. However, the issue of reliability has not been explicitly addressed, and it remains unclear whether the sequence used is optimal for realistic assessment of T2 values.…”

Section: Introductionmentioning

confidence: 99%

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T2 mapping of the distal sciatic nerve in healthy subjects and patients suffering from lumbar disc herniation with nerve compression

Sollmann

Weidlich

Klupp

et al. 2020

Magn Reson Mater Phy

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Objective To measure T2 values for magnetic resonance neurography (MRN) of the healthy distal sciatic nerve and compare those to T2 changes in patients with nerve compression. Materials and methods Twenty-one healthy subjects and five patients with sciatica due to disc herniation underwent MRN using a T2-prepared turbo spin echo (TSE) sequence of the distal sciatic nerve bilaterally. Six and one of those healthy subjects further underwent a commonly used multi-echo spin-echo (MESE) sequence and magnetic resonance spectroscopy (MRS), respectively. Results T2 values derived from the T2-prepared TSE sequence were 44.6 ± 3.0 ms (left) and 44.5 ± 2.6 ms (right) in healthy subjects and showed good inter-reader reliability. In patients, T2 values of 61.5 ± 6.2 ms (affected side) versus 43.3 ± 2.4 ms (unaffected side) were obtained. T2 values of MRS were in good agreement with measurements from the T2-prepared TSE, but not with those of the MESE sequence. Discussion A T2-prepared TSE sequence enables precise determination of T2 values of the distal sciatic nerve in agreement with MRS. A MESE sequence tends to overestimate nerve T2 compared to T2 from MRS due to the influence of residual fat on T2 quantification. Our approach may enable to quantitatively assess direct nerve affection related to nerve compression.

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Multiparametric Quantitative MRI of Peripheral Nerves in the Leg: A Reliability Study

Chen

Baraz

Xuan

et al. 2023

Magnetic Resonance Imaging

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BackgroundPatients with polyneuropathies typically have demyelination and/or axonal degeneration in peripheral nerves. Currently, there is a lack of imaging biomarkers to track the changes in these pathologies.PurposeTo develop and evaluate the reliability of a multiparametric quantitative magnetic resonance imaging (qMRI) method of peripheral nerves in the leg.Study TypeProspective.SubjectsSeventeen healthy volunteers (36.2 ± 13.8 years old, 9 males) with 10 of them scanned twice for test–retest.Field Strength/Sequence3 T, three‐dimensional gradient echo and diffusion tensor imaging.AssessmentA qMRI protocol and processing pipeline was established for quantifying the following nerve parameters that are sensitive to myelin and axonal pathologies: magnetization transfer (MT) ratio (MTR), MT saturation index (MTsat), T2*, T1, proton density (PD), fractional anisotropy (FA), and mean/axial/radial diffusivities (MD, AD, and RD). The qMRI protocol also measures the volume of nerve fascicles (fVOL) and the fat fraction (FF) of muscles.Statistical TestsThe intersession reproducibility and inter‐rater reliability of each qMRI parameter were assessed by Bland–Altman analysis and intraclass correlation coefficient (ICC). Pairwise Pearson correlation analyses were performed to investigate the intrinsic association between qMRI parameters. Distal‐to‐proximal variations were evaluated by paired t‐tests with Bonferroni‐Holm multiple comparison corrections. P < 0.05 was considered statistically significant.ResultsThe MTR, MTsat, T2*, T1, PD, FA, AD, and fVOL of the sciatic and tibial nerves, and the FF of leg muscles, had an overall good‐to‐excellent test–retest agreement (ICC varying from 0.78 to 0.99). All the qMRI parameters had good‐to‐excellent inter‐rater reliability (ICC > 0.80). The data demonstrated a pattern of distal‐to‐proximal changes of an increased nerve MTsat and FA, and a decreased nerve T1, PD, MD, and RD, as well as a significantly increased muscle FF.Data ConclusionThe proposed multiparametric qMRI method of the peripheral nerves is highly reproducible and provided healthy control data which will be used in developing monitoring biomarkers in patients with polyneuropathies.Level of Evidence1Technical EfficacyStage 2

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Magnetic Resonance Neurography

Cited by 23 publications

References 30 publications

Segmentation of Peripheral Nerves From Magnetic Resonance Neurography: A Fully-Automatic, Deep Learning-Based Approach

Segmentation of Peripheral Nerves From Magnetic Resonance Neurography: A Fully-Automatic, Deep Learning-Based Approach

T2 mapping of the distal sciatic nerve in healthy subjects and patients suffering from lumbar disc herniation with nerve compression

Multiparametric Quantitative MRI of Peripheral Nerves in the Leg: A Reliability Study

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