An interactive segmentation tool for quantifying fat in lumbar muscles using axial lumbar-spine MRI

Antony, Joseph; McGuinness, Kevin; Welch, Neil; Coyle, Joe; Franklyn-Miller, Andrew; O’Connor, Noel E.; Moran, Kieran

doi:10.1016/j.irbm.2015.10.004

Cited by 7 publications

(9 citation statements)

References 27 publications

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“…Antony et al implemented an interactive segmentation of the erector spinae and the multifidus muscles using the livewire technique (Fig. 3A,B) 24 .…”

Section: Defining the Novel Region Of Interestmentioning

confidence: 99%

“…They found that fat content increased per quartile from medial to lateral in males, whereas the increase of FI depended more on sagittal than transverse distribution 57 . Antony et al proposed a new method to quantify the fat content in six regions with reference to the center of the spinal column, which represented the axis of spinal rotation 24 . These studies demonstrated that orthopaedists can keep a watchful eye on different muscle regions that might have various effects on pain levels.…”

Section: Defining the Novel Region Of Interestmentioning

confidence: 99%

“…Most studies 9–74 used conventional MRI for measuring FI. In the field of MRI sequence, our results showed that T2‐weighted images 10,12–14,17,18,20,24,25,27,29,30,32–35,37,39–53,55,56,58–63,65,66,69,70 were used in quantitative assessments more often. It is expedient for orthopaedists to evaluate FI on frequently‐used T2‐weighted images.…”

Section: Literature Reviewmentioning

confidence: 99%

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Imaging Evaluation of Fat Infiltration in Paraspinal Muscles on MRI: A Systematic Review with a Focus on Methodology

Han

Jiang

Zhang

et al. 2021

Orthopaedic Surgery

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Purpose: Numerous studies have applied a variety of methods to assess paraspinal muscle degeneration. However, the methodological differences in imaging evaluation may lead to imprecise or inconsistent results. This article aimed to provide a pragmatic summary review of the current imaging modalities, measurement protocols, and imaging parameters in the evaluation of paraspinal muscle fat infiltration (FI) in MRI studies.Methods: Web of Science, EMBASE, and PubMed were searched from January 2005 to March 2020 to identify studies that examined the FI of paraspinal muscles on MRI among patients with lumbar degenerative diseases.Results: Intramyocellular lipids measured by magnetic resonance spectroscopy and FI measured by chemical-shift MRI were both correlated to low back pain and several degenerative lumbar diseases, whereas results on the relationship between FI and degenerative lumbar pathologies using conventional MRI were conflicting. Multi-segment measurement of FI at the lesion segment and adjacent segments could be a prognostic indicator for lumbar surgery. Most studies adopted the center of the intervertebral disc or endplate as the level of slice to evaluate the FI. Compared with visual semiquantitative assessment, quantitative parameters appeared to be precise for eliminating individual or modality differences. It has been demonstrated that fat CSA/total CSA (based on area) and muscle-fat index (based on signal intensity) as quantitative FI parameters are associated with multiple lumbar diseases and clinical outcomes after surgery. Conclusion:Having a good command of the methodology of paraspinal muscle FI on MRI was effective for diagnosis and prognosis in clinical practice.

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“…Antony et al implemented an interactive segmentation of the erector spinae and the multifidus muscles using the livewire technique (Fig. 3A,B) 24 .…”

Section: Defining the Novel Region Of Interestmentioning

confidence: 99%

Section: Defining the Novel Region Of Interestmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

See 1 more Smart Citation

Imaging Evaluation of Fat Infiltration in Paraspinal Muscles on MRI: A Systematic Review with a Focus on Methodology

Han

Jiang

Zhang

et al. 2021

Orthopaedic Surgery

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“…threshold) was not addressed by this group. We are aware of only one recent study that has developed a semi-automated interactive tool for the assessment of paraspinal muscle composition, which considerably simplified the task of paraspinal muscle composition assessment [ 18 ]. However, threshold values using the interactive tool are based on visual inspection, thus remain rater-dependent.…”

Section: Discussionmentioning

confidence: 99%

“…The tedious and rater-dependent nature of such manual thresholding techniques for paraspinal muscle composition assessment provides the impetus for the development of automated or semi-automated segmentation methods. Although, automated and sophisticated methods have been successfully implemented in MR image tissue segmentation of different anatomical structures including the brain, liver, heart [ 13 – 16 ], as well as the quantification of thigh muscle and adipose tissue [ 17 ], we are aware of only one recently developed semi-automated interactive tool for the assessment of paraspinal muscle composition [ 18 ]. The threshold values in the interactive segmentation technique, however, are based on visual inspection and, therefore, remain rater-dependent.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of an automated thresholding algorithm for the quantification of paraspinal muscle composition from MRI images

et al. 2017

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BackgroundThe imaging assessment of paraspinal muscle morphology and fatty infiltration has gained considerable attention in the past decades, with reports suggesting an association between muscle degenerative changes and low back pain (LBP). To date, qualitative and quantitative approaches have been used to assess paraspinal muscle composition. Though highly reliable, manual thresholding techniques are time consuming and not always feasible in a clinical setting. The tedious and rater-dependent nature of such manual thresholding techniques provides the impetus for the development of automated or semi-automated segmentation methods. The purpose of the present study was to develop and evaluate an automated thresholding algorithm for the assessment of paraspinal muscle composition. The reliability and validity of the muscle measurements using the new automated thresholding algorithm were investigated through repeated measurements and comparison with measurements from an established, highly reliable manual thresholding technique.MethodsMagnetic resonance images of 30 patients with LBP were randomly selected cohort of patients participating in a project on commonly diagnosed lumbar pathologies in patients attending spine surgeon clinics. A series of T2-weighted MR images were used to train the algorithm; preprocessing techniques including adaptive histogram equalization method image adjustment scheme were used to enhance the quality and contrast of the images. All muscle measurements were repeated twice using a manual thresholding technique and the novel automated thresholding algorithm, from axial T2-weigthed images, at least 5 days apart. The rater was blinded to all earlier measurements. Inter-method agreement and intra-rater reliability for each measurement method were assessed. The study did not received external funding and the authors have no disclosures.ResultsThere was excellent agreement between the two methods with inter-method reliability coefficients (intraclass correlation coefficients) varying from 0.79 to 0.99. Bland and Altman plots further confirmed the agreement between the two methods. Intra-rater reliability and standard error of measurements were comparable between methods, with reliability coefficient varying between 0.95 and 0.99 for the manual thresholding and 0.97–0.99 for the automated algorithm.ConclusionThe proposed automated thresholding algorithm to assess paraspinal muscle size and composition measurements was highly reliable, with excellent agreement with the reference manual thresholding method.

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An externally validated deep learning model for the accurate segmentation of the lumbar paravertebral muscles

et al. 2022

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An interactive segmentation tool for quantifying fat in lumbar muscles using axial lumbar-spine MRI

Cited by 7 publications

References 27 publications

Imaging Evaluation of Fat Infiltration in Paraspinal Muscles on MRI: A Systematic Review with a Focus on Methodology

Imaging Evaluation of Fat Infiltration in Paraspinal Muscles on MRI: A Systematic Review with a Focus on Methodology

Evaluation of an automated thresholding algorithm for the quantification of paraspinal muscle composition from MRI images

An externally validated deep learning model for the accurate segmentation of the lumbar paravertebral muscles

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