3D multimodal spatial fuzzy segmentation of intramuscular connective and adipose tissue from ultrashort TE MR images of calf muscle

Application of MRI images based on Spatial Fuzzy Clustering Algorithm guided by Neuroendoscopy in the treatment of Tumors in the Saddle Region

Objective:

The paper applies spatial fuzzy clustering algorithm to explore the role and value of neuroendoscopic assisted technology in the operation of tumors in the saddle region, and analyze the MRI image characteristics of tumors in the saddle region.

Methods:

The clinical data of 63 patients from our hospital who underwent neuroendoscopic assisted microscopy to remove tumors in the saddle area from 2017 to 2019 (neuroendoscopy-assisted group) were collected. Seventy six patients who occupied the saddle area by microscopic resection only in the same period (Simple microscope group) clinical data. By comparing the patient’s tumor resection rate, postoperative complication rate and postoperative recurrence rate, the surgical effect was evaluated.

Results:

The total resection rates of the tumors in the neuroendoscopy-assisted group and the microscope-only group were 95.24% (60/63) and 80.26% (61/76). The incidence of postoperative vasospasm was 3.17% (2/63) and 13.16% (10/76), the incidence of nerve injury was 0 (0/63) and 6.58% (5/76), the difference was statistically significant (P <0.05). There was no significant difference in the incidence of postoperative infection, cerebrospinal fluid leakage and postoperative recurrence rate between the two groups (P> 0.05).

Conclusion:

Neuroendoscopy-assisted microscopy-based removal of the saddle area occupying space based on spatial fuzzy clustering algorithm can increase the total tumor resection rate and reduce the incidence of complications.

Role of the Extracellular Matrix in Loss of Muscle Force With Age and Unloading Using Magnetic Resonance Imaging, Biochemical Analysis, and Computational Models

The focus of this review is the application of advanced MRI to study the effect of aging and disuse related remodeling of the extracellular matrix (ECM) on force transmission in the human musculoskeletal system. Structural MRI includes (i) ultra-low echo times (UTE) maps to visualize and quantify the connective tissue, (ii) diffusion tensor imaging (DTI) modeling to estimate changes in muscle and ECM microstructure, and (iii) magnetization transfer contrast imaging to quantify the macromolecular fraction in muscle. Functional MRI includes dynamic acquisitions during contraction cycles enabling computation of the strain tensor to monitor muscle deformation. Further, shear strain extracted from the strain tensor may be a potential surrogate marker of lateral transmission of force. Biochemical and histological analysis of muscle biopsy samples can provide "gold-standard" validation of some of the MR findings. The review summarizes biochemical studies of ECM adaptations with age and with disuse. A brief summary of animal models is included as they provide experimental confirmation of longitudinal and lateral force transmission pathways. Computational muscle models enable exploration of force generation and force pathways and elucidate the link between structural adaptations and functional consequences. MR image findings integrated in a computational model can explain and predict subject specific functional changes to structural adaptations. Future work includes development and validation of MRI biomarkers using biochemical analysis of muscle tissue as a reference standard and potential translation of the imaging markers to the clinic to noninvasively monitor musculoskeletal disease conditions and changes consequent to rehabilitative interventions.

Automated postoperative muscle assessment of hip arthroplasty patients using multimodal imaging joint segmentation

BACKGROUND AND OBJECTIVE

In patients treated with hip arthroplasty, the muscular condition and presence of inflammatory reactions are assessed using magnetic resonance imaging (MRI). As MRI lacks contrast for bony structures, computed tomography (CT) is preferred for clinical evaluation of bone tissue and orthopaedic surgical planning. Combining the complementary information of MRI and CT could improve current clinical practice for diagnosis, monitoring and treatment planning. In particular, the different contrast of these modalities could help better quantify the presence of fatty infiltration to characterise muscular condition and assess implant failure. In this work, we combine CT and MRI for joint bone and muscle segmentation and we propose a novel Intramuscular Fat Fraction estimation method for the quantification of muscle atrophy.

METHODS

Our multimodal framework is able to segment healthy and pathological musculoskeletal structures as well as implants, and develops into three steps. First, input images are pre-processed to improve the low quality of clinically acquired images and to reduce the noise associated with metal artefact. Subsequently, CT and MRI are non-linearly aligned using a novel approach which imposes rigidity constraints on bony structures to ensure realistic deformation. Finally, taking advantage of a multimodal atlas we created for this task, a multi-atlas based segmentation delineates pelvic bones, abductor muscles and implants on both modalities jointly. From the obtained segmentation, a multimodal estimation of the Intramuscular Fat Fraction can be automatically derived.

RESULTS

Evaluation of the segmentation in a leave-one-out cross-validation study on 22 hip sides resulted in an average Dice score of 0.90 for skeletal and 0.84 for muscular structures. Our multimodal Intramuscular Fat Fraction was benchmarked on 27 different cases against a standard radiological score, showing stronger association than a single modality approach in a one-way ANOVA F-test analysis.

CONCLUSIONS

The proposed framework represents a promising tool to support image analysis in hip arthroplasty, being robust to the presence of implants and associated image artefacts. By allowing for the automated extraction of a muscle atrophy imaging biomarker, it could quantitatively inform the decision-making process about patient's management.

MRI adipose tissue and muscle composition analysis-a review of automation techniques

MRI is becoming more frequently used in studies involving measurements of adipose tissue and volume and composition of skeletal muscles. The large amount of data generated by MRI calls for automated analysis methods. This review article presents a summary of automated and semi-automated techniques published between 2013 and 2017. Technical aspects and clinical applications for MRI-based adipose tissue and muscle composition analysis are discussed based on recently published studies. The conclusion is that very few clinical studies have used highly automated analysis methods, despite the rapidly increasing use of MRI for body composition analysis. Possible reasons for this are that the availability of highly automated methods has been limited for non-imaging experts, and also that there is a limited number of studies investigating the reproducibility of automated methods for MRI-based body composition analysis.

Advanced body composition assessment: from body mass index to body composition profiling

This paper gives a brief overview of common non-invasive techniques for body composition analysis and a more in-depth review of a body composition assessment method based on fat-referenced quantitative MRI. Earlier published studies of this method are summarized, and a previously unpublished validation study, based on 4753 subjects from the UK Biobank imaging cohort, comparing the quantitative MRI method with dual-energy X-ray absorptiometry (DXA) is presented. For whole-body measurements of adipose tissue (AT) or fat and lean tissue (LT), DXA and quantitative MRIs show excellent agreement with linear correlation of 0.99 and 0.97, and coefficient of variation (CV) of 4.5 and 4.6 per cent for fat (computed from AT) and LT, respectively, but the agreement was found significantly lower for visceral adipose tissue, with a CV of >20 per cent. The additional ability of MRI to also measure muscle volumes, muscle AT infiltration and ectopic fat, in combination with rapid scanning protocols and efficient image analysis tools, makes quantitative MRI a powerful tool for advanced body composition assessment.