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Assessment of lumbar paraspinal muscle morphology using mDixon Quant magnetic resonance imaging (MRI): a cross-sectional study in healthy subjects

Identifikátory výsledku

  • Kód výsledku v IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F65269705%3A_____%2F24%3A00080303" target="_blank" >RIV/65269705:_____/24:00080303 - isvavai.cz</a>

  • Nalezeny alternativní kódy

    RIV/00216224:14110/24:00137281

  • Výsledek na webu

    <a href="https://qims.amegroups.org/article/view/126986/html" target="_blank" >https://qims.amegroups.org/article/view/126986/html</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.21037/qims-23-1796" target="_blank" >10.21037/qims-23-1796</a>

Alternativní jazyky

  • Jazyk výsledku

    angličtina

  • Název v původním jazyce

    Assessment of lumbar paraspinal muscle morphology using mDixon Quant magnetic resonance imaging (MRI): a cross-sectional study in healthy subjects

  • Popis výsledku v původním jazyce

    Background: Lumbar paraspinal muscles (LPM) are a part of the deep spinal stabilisation system and play an important role in stabilising the lumbar spine and trunk. Inadequate function of these muscles is thought to be an essential aetiological factor in low back pain, and several neuromuscular diseases are characterised by dysfunction of LPM. The main aims of our study were to develop a methodology for LPM assessment using advanced magnetic resonance imaging (MRI) methods, including a manual segmentation process, to confirm the measurement reliability, to evaluate the LPM morphological parameters [fat fraction (FF), total muscle volume (TMV) and functional muscle volume (FMV)] in a healthy population, to study the influence of physiological factors on muscle morphology, and to build equations to predict LPM morphological parameters in a healthy population. Methods: This prospective cross-sectional observational comparative single-centre study was conducted at the University Hospital in Brno, enrolling healthy volunteers from April 2021 to March 2023. MRI of the lumbar spine and LPM (erector spinae muscle and multifidus muscle) were performed using a 6-point Dixon gradient echo sequence. The segmentation of the LPM and the control muscle (psoas muscle) was done manually to obtain FF and TMV in a range from Th12/L1 to L5/S1. Intra-rater and inter-rater reliability were evaluated. Linear regression models were constructed to assess the effect of physiological factors on muscle FF, TMV and FMV. Results: We enrolled 90 healthy volunteers (median age 38 years, 45 men). The creation of segmentation masks and the assessment of FF and TMV proved reliable (Dice coefficient 84% to 99%, intraclass correlation coefficient GREATER-THAN OR EQUAL TO0.97). The univariable models showed that FF of LPM was influenced the most by age (39.6% to 44.8% of variability, P&lt;0.001); TMV and FMV by subject weight (34.9% to 67.6% of variability, P&lt;0.001) and sex (24.7% to 64.1% of variability, P&lt;0.001). Multivariable linear regression models for FF of LPM included age, body mass index and sex, with R-squared values ranging from 45.4% to 51.1%. Models for volumes of LPM included weight, age and sex, with R-squared values ranged from 37.4% to 76.8%. Equations were developed to calculate predicted FF, TMV and FMV for each muscle. Conclusions: A reliable methodology has been developed to assess the morphological parameters (biomarkers) of the LPM. The morphological parameters of the LPM are significantly influenced by physiological factors. Equations were constructed to calculate the predicted FF, TMV and FMV of individual muscles in relation to anthropometric parameters, age, and sex. This study, which presented LPM assessment methodology and predicted values of LPM morphological parameters in a healthy population, could improve our understanding of diseases involving LPM (low back pain and some neuromuscular diseases). (C) Quantitative Imaging in Medicine and Surgery. All rights reserved.

  • Název v anglickém jazyce

    Assessment of lumbar paraspinal muscle morphology using mDixon Quant magnetic resonance imaging (MRI): a cross-sectional study in healthy subjects

  • Popis výsledku anglicky

    Background: Lumbar paraspinal muscles (LPM) are a part of the deep spinal stabilisation system and play an important role in stabilising the lumbar spine and trunk. Inadequate function of these muscles is thought to be an essential aetiological factor in low back pain, and several neuromuscular diseases are characterised by dysfunction of LPM. The main aims of our study were to develop a methodology for LPM assessment using advanced magnetic resonance imaging (MRI) methods, including a manual segmentation process, to confirm the measurement reliability, to evaluate the LPM morphological parameters [fat fraction (FF), total muscle volume (TMV) and functional muscle volume (FMV)] in a healthy population, to study the influence of physiological factors on muscle morphology, and to build equations to predict LPM morphological parameters in a healthy population. Methods: This prospective cross-sectional observational comparative single-centre study was conducted at the University Hospital in Brno, enrolling healthy volunteers from April 2021 to March 2023. MRI of the lumbar spine and LPM (erector spinae muscle and multifidus muscle) were performed using a 6-point Dixon gradient echo sequence. The segmentation of the LPM and the control muscle (psoas muscle) was done manually to obtain FF and TMV in a range from Th12/L1 to L5/S1. Intra-rater and inter-rater reliability were evaluated. Linear regression models were constructed to assess the effect of physiological factors on muscle FF, TMV and FMV. Results: We enrolled 90 healthy volunteers (median age 38 years, 45 men). The creation of segmentation masks and the assessment of FF and TMV proved reliable (Dice coefficient 84% to 99%, intraclass correlation coefficient GREATER-THAN OR EQUAL TO0.97). The univariable models showed that FF of LPM was influenced the most by age (39.6% to 44.8% of variability, P&lt;0.001); TMV and FMV by subject weight (34.9% to 67.6% of variability, P&lt;0.001) and sex (24.7% to 64.1% of variability, P&lt;0.001). Multivariable linear regression models for FF of LPM included age, body mass index and sex, with R-squared values ranging from 45.4% to 51.1%. Models for volumes of LPM included weight, age and sex, with R-squared values ranged from 37.4% to 76.8%. Equations were developed to calculate predicted FF, TMV and FMV for each muscle. Conclusions: A reliable methodology has been developed to assess the morphological parameters (biomarkers) of the LPM. The morphological parameters of the LPM are significantly influenced by physiological factors. Equations were constructed to calculate the predicted FF, TMV and FMV of individual muscles in relation to anthropometric parameters, age, and sex. This study, which presented LPM assessment methodology and predicted values of LPM morphological parameters in a healthy population, could improve our understanding of diseases involving LPM (low back pain and some neuromuscular diseases). (C) Quantitative Imaging in Medicine and Surgery. All rights reserved.

Klasifikace

  • Druh

    J<sub>imp</sub> - Článek v periodiku v databázi Web of Science

  • CEP obor

  • OECD FORD obor

    30224 - Radiology, nuclear medicine and medical imaging

Návaznosti výsledku

  • Projekt

  • Návaznosti

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Ostatní

  • Rok uplatnění

    2024

  • Kód důvěrnosti údajů

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Údaje specifické pro druh výsledku

  • Název periodika

    Quantitative Imaging in Medicine and Surgery

  • ISSN

    2223-4292

  • e-ISSN

    2223-4306

  • Svazek periodika

    14

  • Číslo periodika v rámci svazku

    8

  • Stát vydavatele periodika

    CN - Čínská lidová republika

  • Počet stran výsledku

    21

  • Strana od-do

    6015-6035

  • Kód UT WoS článku

    001312974100010

  • EID výsledku v databázi Scopus

    2-s2.0-85199952531