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An Investigation of Fat Infiltration of the Multifidus Muscle in Patients With Severe Neck Symptoms Associated With Chronic Whiplash-Associated Disorder
Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV).
Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics. Linköping University, Center for Medical Image Science and Visualization (CMIV).ORCID iD: 0000-0002-6189-0807
Linköping University, Department of Medical and Health Sciences, Division of Physiotherapy. Linköping University, Faculty of Medicine and Health Sciences.
Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences.
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2016 (English)In: Journal of Orthopaedic and Sports Physical Therapy, ISSN 0190-6011, E-ISSN 1938-1344, Vol. 46, no 10, p. 886-893Article in journal (Refereed) Published
Abstract [en]

STUDY DESIGN: Cross-sectional study. BACKGROUND: Findings of fat infiltration in cervical spine multifidus, as a sign of degenerative morphometric changes due to whiplash injury, need to be verified. OBJECTIVES: To develop a method using water/fat magnetic resonance imaging (MRI) to investigate fat infiltration and cross-sectional area of multifidus muscle in individuals with whiplash associated disorders (WADS) compared to healthy controls. METHODS: Fat infiltration and cross-sectional area in the multifidus muscles spanning the C4 to C7 segmental levels were investigated by manual segmentation using water/fat-separated MRI in 31 participants with WAD and 31 controls, matched for age and sex. RESULTS: Based on average values for data spanning C4 to C7, participants with severe disability related to WAD had 38% greater muscular fat infiltration compared to healthy controls (P = .03) and 45% greater fat infiltration compared to those with mild to moderate disability related to WAD (P = .02). There were no significant differences between those with mild to moderate disability and healthy controls. No significant differences between groups were found for multifidus cross-sectional area. Significant differences were observed for both cross-sectional area and fat infiltration between segmental levels. CONCLUSION: Participants with severe disability after a whiplash injury had higher fat infiltration in the multifidus compared to controls and to those with mild/moderate disability secondary to WAD. Earlier reported findings using T1-weighted MRI were reproduced using refined imaging technology. The results of the study also indicate a risk when segmenting single cross-sectional slices, as both cross-sectional area and fat infiltration differ between cervical levels.

Place, publisher, year, edition, pages
J O S P T , 2016. Vol. 46, no 10, p. 886-893
Keywords [en]
cervical spine; magnetic resonance imaging; WAD
National Category
Physiotherapy
Identifiers
URN: urn:nbn:se:liu:diva-132206DOI: 10.2519/jospt.2016.6553ISI: 000384398400010PubMedID: 27590177OAI: oai:DiVA.org:liu-132206DiVA, id: diva2:1043953
Note

Funding Agencies|Swedish Medical Research Council; Medical Research Council of Southeast Sweden

Available from: 2016-11-01 Created: 2016-10-21 Last updated: 2020-05-07
In thesis
1. Quantitative Muscle Composition Analysis Using Magnetic Resonance Imaging
Open this publication in new window or tab >>Quantitative Muscle Composition Analysis Using Magnetic Resonance Imaging
2020 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Changes in muscle tissue composition, e.g. decrease in volume and/or increase of fat infiltration, are related to adverse health conditions such as sarcopenia, inflammation, muscular dystrophy, and chronic pain. However, the onset and progression of disease and the effect of potential intervention effects are not fully understood, partly due to insufficient measurement tools. For advanced knowledge regarding these diseases, an accurate and precise measurement tool for detecting changes in muscle composition is needed. The tool must be able to detect both local changes on specific muscles for investigating local injuries and generalized muscle composition changes on a whole-body level. Magnetic resonance imaging is an excellent tool due to its superior soft tissue contrast but is normally not quantitative, making it challenging to produce reproducible results. Furthermore, manual analysis of the vast amount of images produced is extremely time consuming and therefore expensive. The aim of this thesis was to develop and validate a new magnetic resonance imaging method for muscle volume quantification and fat infiltration estimation that would have the potential to be used in both large-scale studies and for analyzing small individual muscles.

The method development was divided into four main steps: 1) Rapid acquisition and reconstruction of data with sufficient resolution and calibration giving quantitative images where the relative fat content of each voxel (related to pure fat voxels) is attainable; 2) Automated muscle tissue classification based on non-rigid multi-atlas segmentation followed by probability voting to acquire the region of interest for each muscle; 3) Quantification of muscle tissue volume and fat infiltration from the classification step and the local fat signal; 4) Evaluation of the potential of the method in clinical studies.

In Paper I, a method for automatic muscle volume quantification of both whole-body and regional muscles, i.e. involving steps 1–3, is presented. The automated method showed good agreement compared to manual segmentation. It was robust to an 8-fold resolution difference using two different scanner field strengths. Papers II and III evaluated the clinical relevance and the need for developing methods with high-resolution images to answer the research questions regarding the effect of a whiplash trauma on the multifidus muscles. This involved steps 1–4. The method enabled acquisition of high-resolution data to distinguish the small multifidus muscles (Paper II). The paper also showed a higher fat infiltration in the multifidus muscles in individuals with severe self-reported disability compared to individuals with milder symptoms and to healthy controls. Furthermore, the local fat infiltration was also related to widespread muscle fat infiltration (Paper III). However, the difference in widespread muscle fat infiltration could not alone distinguish between the three different groups. Paper IV showed the robustness of fat infiltration estimation when changing flip angle, and thereby the T1 weighting, of the acquired images (steps 1–3). The higher flip angle also provided better noise characteristics. Therefore, this quantitative method can be used with higher flip angle, and thus a potentially better anatomical contrast, without losing accuracy or precision.

To conclude, this thesis presents a method that quantifies muscle volume and estimates fat infiltration robustly and reproducibly. The versatility of the method allows for both high-resolution images of small muscles and rapid acquisition of whole-body data. The method can be a useful tool in clinical studies regarding small individual muscles. Furthermore, the combination of being quantitative and automatic means that the method has potential to be used in longitudinal, multi-center, and large-scale studies for advanced understanding of muscular diseases.

Abstract [sv]

Den här avhandlingen presenterar en metod som kan mäta kroppens muskelvolym och även beräkna hur mycket fett som lagrats in i musklerna. Aktuell forskning visar att en minskning av muskelvolym samt en ökning av fettinlagringen i musklerna är kopplat till en rad olika sjukdomar och nedsättningar som till exempel kronisk smärta, diabetes, inflammation och åldrande. Även om dessa samband har visats genom forskning finns det idag inte tillräcklig kunskap om varför det sker och vilka som drabbas. Detta beror delvis på att bra metoder för att mäta muskler saknats. För att tidigt kunna ställa diagnos och sätta in rätt behandlingsmetod behövs teknik som noggrant kan se förändringar i muskelsammansättningen.

De metoder som idag används inom vården för att analysera muskler är främst baserade på att testa muskelfunktionen genom olika styrketester eller storleksmätning av exempelvis omkretsen kring överarmen. Problemet med dessa metoder är att muskelstyrka och omkrets båda är trubbiga mått. Muskelstyrkan är bara ett indirekt mått på hur mycket muskler du har. En förändring i omkrets säger heller ingenting om huruvida sammansättningen har ändrats. En minskning av muskelvolymen och en ökning av fettet skulle kunna ge oförändrat resultat på omkretsmätningen.

En magnetkameraundersökning är ett alternativ när vi behöver noggranna mätningar av kroppens muskler. Från magnetkameran kan vi skapa en tredimensionell bild av kroppens organ och fettdepåer. Eftersom fett och muskler ger olika signal kan vi också se fettinlagringen. Dock kvarstår utmaningar innan noggranna analyser av förändringar i muskelsammansättning är möjliga kliniskt och inom forskningen. Avhandlingen handlar om att lösa några av dessa utmaningar.

En utmaning är att göra resultatet från magnetkameraundersökningen kvantitativ. Du kommer inte att få samma intensitet på fettsignalen även om du samlar in data direkt efter varandra med exakt samma inställningar. Därför använder jag i denna avhandling en teknik som kan kalibrera varje bildelement efter hur mycket fett det avbildar, vilket gör den kvantitativ. Avhandlingen visar att analysmetoden ger samma resultat även om kameror med olika starkt magnetfält används eller om upplösningen ändras.

En annan utmaning är att göra analyskedjan effektiv. Att samla in och analysera data med en magnetkamera är tidskrävande. Att manuellt definera en muskel tar ca 45 minuter och är inte applicerbart i annat än ganska små studier. Därför utvecklades en metod för att automatisera definieringen av olika muskelgrupper. Den automatiska metoden används just nu för att anlaysera fyra olika muskler i världens hittills största bildstudie där magnetkamerabilder på 100 000 individer samlas in. Om analyserna istället gjorts helt manuellt skulle det ta runt 300 000 timmar, vilket motsvarar 175 år heltidsarbete.

Metoden applicerades även i en klinisk forskningsstudie. Individer med högre självupplevd kronisk smärta efter ett whiplash-våld mot nacken hade högre fettinlagring i sina nackmuskler jämfört med både individer som hade mindre ont och friska kontroller.

Avhandlingen visar att analysmetoden som presenteras är noggrann, effektiv och har klinisk relevans. Den har därmed potential att kunna användas i stora kliniska longitudinella studier med syfte att öka kunskapen om muskelrelaterade sjukdomar och nedsättningar som människor lider av idag.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2020. p. 75
Series
Linköping Studies in Science and Technology. Dissertations, ISSN 0345-7524 ; 2057
Keywords
Muscle Composition, Muscle fat Infiltration, Magnetic Resonance Imaging
National Category
Medical Engineering
Identifiers
urn:nbn:se:liu:diva-163501 (URN)10.3384/diss.diva-163501 (DOI)9789179298807 (ISBN)
Public defence
2020-06-11, Linden, Building 421, Campus US, Linköping, 14:00 (English)
Opponent
Supervisors
Available from: 2020-05-07 Created: 2020-05-06 Last updated: 2020-05-15Bibliographically approved

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