Software for muscle fibre type classification and analysis

Horizontal deformation of skeletal muscle thick sections visualised by confocal microscopy

Certain morphological parameters of the skeletal muscle tissue can be better understood via 3D considerations. Fluorescent confocal microscopy of thick tissue sections is a well-established method for visualising and measuring skeletal muscle fibres and surrounding capillaries in 3D. However, thick tissue sections are prone to deformations which may significantly influence some stereological and morphometric results like muscle fibre diameter and capillary length, but not dimensionless parameters like object number and Euler-Poincaré characteristics. To better understand this phenomenon, we studied the horizontal deformation of thick (100 µm) transverse skeletal muscle sections, by comparing the muscle fibre diameters measured on thick sections to muscle fibre diameters measured on thin (10 µm) sections of the same sample. Diameter changes were further correlated with shrinkage in the Z direction (axial shrinkage) and deviation of the muscle fibre preferential axis from the Z-axis. We showed that the thick sections dilated in horizontal and shrunk in Z direction, and that the magnitude of horizontal dilation was associated with the magnitude of shrinkage in the Z direction. The latter was more pronounced in transversely than obliquely cut tissue sections. The results emphasise that even when shrinkage in the Z direction can be corrected using calibration, it is important to optimise histological protocols to minimise the Z-axis collapse that could cause horizontal dilation. LAY DESCRIPTION: In skeletal muscle research, 3D analysis is especially important for studying the microvasculature. Laser scanning confocal microscopy of skeletal muscle thick tissue sections is a well-established method for visualising and measuring skeletal muscle fibres and surrounding capillaries in 3D. However, such sections are prone to deformations which may significantly influence the study results. To better understand this phenomenon, we studied the horizontal deformation of thick transverse skeletal muscle sections. We compared the average muscle fibre diameters measured on thick skeletal muscle sections, thin fixed skeletal muscle sections and immunohistochemically stained thin skeletal muscle sections with the muscle fibre diameters measured on thin native skeletal muscle sections of the same sample, with the latter condition serving as the standard diameters (ie the control condition). We further studied the association among muscle fibre diameter changes, shrinkage of the thick skeletal muscle sections in the Z direction and their sectioning angle. We showed that the thick skeletal muscle sections dilated in the horizontal direction and shrunk in the Z direction, and that the magnitude of horizontal dilation was associated with the magnitude of shrinkage in Z direction. The shrinkage in the Z direction was more pronounced in transversely than obliquely cut tissue sections. These results emphasise that even when shrinkage in the Z direction can be corrected using Z-axis calibration, it is very important to optimise histological protocols to minimise the Z-axis collapse that could cause horizontal dilation in order to enhance the integrity of study results.

3D analysis of capillary network in skeletal muscle of obese insulin-resistant mice

In obesity, the skeletal muscle capillary network regresses and the insulin-mediated capillary recruitment is impaired. However, it has been shown that in the early stage of advanced obesity, an increased functional vascular response can partially compensate for other mechanisms of insulin resistance. The present study aimed to investigate the changes in the capillary network around individual muscle fibres during the early stage of obesity and insulin resistance in mice using 3D analysis. Capillaries and muscle fibres of the gluteus maximus muscles of seven high-fat-diet-induced obese and insulin-resistant mice and seven age-matched lean healthy mice were immunofluorescently labelled in thick transverse muscle sections. Stacks of images were acquired using confocal microscope. Capillary network characteristics were estimated by methods of quantitative image analysis. Muscle fibre typing was performed by histochemical analysis of myosin heavy chain isoforms on thin serial sections of skeletal muscle. Capillary length per muscle fibre length and capillary length per muscle fibre surface were increased by 27% and 23%, respectively, around small muscle fibres in obese mice, while there were no significant comparative differences around large fibres of obese and lean mice. Furthermore, the capillarization was larger around small compared to large fibres and there was a shift toward fast type myosin heavy chain isoforms, with no significant changes in muscle fibre diameters, tortuosity and anisotropy in obese mice. Overall, the results show that obese insulin-resistant mice have selective increase in capillarization around small predominantly intermediate muscle fibres, which is most likely related to the impaired glucose metabolism characteristic of type 2 diabetes.

Myofibre segmentation in H&E stained adult skeletal muscle images using coherence-enhancing diffusion filtering

BACKGROUND

The correct segmentation of myofibres in histological muscle biopsy images is a critical step in the automatic analysis process. Errors occurring as a result of incorrect segmentations have a compounding effect on latter morphometric analysis and as such it is vital that the fibres are correctly segmented. This paper presents a new automatic approach to myofibre segmentation in H&E stained adult skeletal muscle images that is based on Coherence-Enhancing Diffusion filtering.

METHODS

The procedure can be broadly divided into four steps: 1) pre-processing of the images to extract only the eosinophilic structures, 2) performing of Coherence-Enhancing Diffusion filtering to enhance the myofibre boundaries whilst smoothing the interior regions, 3) morphological filtering to connect unconnected boundary regions and remove noise, and 4) marker controlled watershed transform to split touching fibres.

RESULTS

The method has been tested on a set of adult cases with a total of 2,832 fibres. Evaluation was done in terms of segmentation accuracy and other clinical metrics.

CONCLUSIONS

The results show that the proposed approach achieves a segmentation accuracy of 89% which is a significant improvement over existing methods.

Charisma: an integrated approach to automatic H&E-stained skeletal muscle cell segmentation using supervised learning and novel robust clump splitting

Histological image analysis plays a key role in understanding the effects of disease and treatment responses at the cellular level. However, evaluating histology images by hand is time-consuming and subjective. While semi-automatic and automatic approaches for image segmentation give acceptable results in some branches of histological image analysis, until now this has not been the case when applied to skeletal muscle histology images. We introduce Charisma, a new top-down cell segmentation framework for histology images which combines image processing techniques, a supervised trained classifier and a novel robust clump splitting algorithm. We evaluate our framework on real-world data from intensive care unit patients. Considering both segmentation and cell property distributions, the results obtained by our method correspond well to the ground truth, outperforming other examined methods.

Quantifiable diagnosis of muscular dystrophies and neurogenic atrophies through network analysis

BACKGROUND

The diagnosis of neuromuscular diseases is strongly based on the histological characterization of muscle biopsies. However, this morphological analysis is mostly a subjective process and difficult to quantify. We have tested if network science can provide a novel framework to extract useful information from muscle biopsies, developing a novel method that analyzes muscle samples in an objective, automated, fast and precise manner.

METHODS

Our database consisted of 102 muscle biopsy images from 70 individuals (including controls, patients with neurogenic atrophies and patients with muscular dystrophies). We used this to develop a new method, Neuromuscular DIseases Computerized Image Analysis (NDICIA), that uses network science analysis to capture the defining signature of muscle biopsy images. NDICIA characterizes muscle tissues by representing each image as a network, with fibers serving as nodes and fiber contacts as links.

RESULTS

After a 'training' phase with control and pathological biopsies, NDICIA was able to quantify the degree of pathology of each sample. We validated our method by comparing NDICIA quantification of the severity of muscular dystrophies with a pathologist's evaluation of the degree of pathology, resulting in a strong correlation (R = 0.900, P <0.00001). Importantly, our approach can be used to quantify new images without the need for prior 'training'. Therefore, we show that network science analysis captures the useful information contained in muscle biopsies, helping the diagnosis of muscular dystrophies and neurogenic atrophies.

CONCLUSIONS

Our novel network analysis approach will serve as a valuable tool for assessing the etiology of muscular dystrophies or neurogenic atrophies, and has the potential to quantify treatment outcomes in preclinical and clinical trials.

Human masseter muscle fibers from the elderly express less neonatal Myosin than those of young adults

In contrast to limb muscles where neonatal myosin (MyHC-neo) is present only shortly after birth, adult masseter muscles contain a substantial portion of MyHC-neo, which is coexpressed with mature MyHC isoforms. Changes in the numerical and area proportion of muscle fibers containing MyHC-neo in masseter muscle with aging could be expected, based on previously reported findings that (i) developmental MyHC-containing muscle fibers exhibit lower shortening velocities compared to fibers with exclusively fast MyHC isoforms and (ii) transformation toward faster phenotype occurs in elderly compared to young masseter muscle. In this study, we detected MyHC isoforms in the anterior superficial part of the human masseter muscle in a sufficiently large sample of young, middle-aged, and elderly subjects to reveal age-related changes in the coexpression of MyHC-neo with adult MyHC isoforms. MyHC isoforms were visualized with immunoperoxidase method and the results were presented by (i) the area proportion of fibers containing particular MyHC isoforms and (ii) the numerical proportion of fiber types defined by MyHC-1, -2a, -2x, and -neonatal isoform expression from a successive transverse sections. We found a lower numerical and area proportion of fibers expressing MyHC-neo as well as a lower area proportion of fibers containing MyHC-1 in elderly than in young subjects. We conclude that the diminished expression of MyHC-neo with age could point to a lower regeneration capacity of masseter muscle in the elderly.

Myosin heavy chain composition of the human sternocleidomastoid muscle

The sternocleidomastoid (SCM) muscle is one of the neck muscles responsible for head posture and control of head movement. It functions in rotation, inclination, protraction, extension and flexion of the head, whilst chewing and in exerting increased respiratory efforts. This study is the first one describing the myosin heavy chain (MyHC) isoform composition of the SCM muscle of presumably healthy young males for the purpose of better understanding the contractile properties of the muscle as well as to help in evaluation of pathologically altered structure of the muscle. Autopsy samples were processed immunohistochemically to reveal the MyHC isoform composition. The muscle fibres expressed MyHC-1 (31.5%), -2a (29.7%) and -2x (4.3%) or co-expressed MyHC-2a with MyHC-2x (26.8%), MyHC-1 with MyHC-2a (4.1%) and/or MyHC-1, -2a with -2x (1.1%). In addition to the MyHC isoforms, characteristic of adult limb muscles, a very low percentage of muscle fibres (0.2-2.7%) expressed MyHC-neo, which is normally not found in adult limb muscles. Only two samples exhibited MyHC-neo at a rather higher percentage (6.3% and 7.5%) of muscle fibres. The high share of hybrid fibres and the presence of MyHC-neo in the SCM muscle differ from that of adult limb muscles where hybrid fibres are rare and the expression of immature MyHC isoforms occurs only in pathological or experimental conditions. Since the SCM muscle shares the same embryogenic potential as limb muscles, its distinct MyHC expression appears to be associated with twin innervation and with the intrinsic specialisation to perform multiple functions.

Wearing of complete dentures reduces slow fibre and enhances hybrid fibre fraction in masseter muscle

Edentulous conditions and use of complete dentures alter the function of jaw muscles, which is presumably reflected in the myosin heavy chain (MyHC) isoform composition. This study is the first dealing with MyHC isoforms expression in edentulous persons with the aim to clarify to which extent the decreased functional load following teeth loss contributes to the changed muscle phenotype during ageing. We analysed MyHC expression in old masseter muscle at decreased and full functional load by comparing age-matched edentulous and dentate subjects. Edentulous subjects had upper and lower complete dentures. Dentate subjects had at least 24 natural teeth in continuous dental arches with two molars present in each quadrant and normal intermaxillary relationship. The adaptive response to the reduced masticatory load was lower numerical and area proportion of MyHC-1 expressing fibres and higher numerical proportion of hybrid fibres in edentulous compared with dentate subjects with no significant difference in the proportion of MyHC-neo-expressing fibres between both groups. We conclude that the observed differences in the proportion of fibre types between denture wearers and dentate subjects cannot be ascribed to degenerative changes intrinsic to the ageing muscle, but to functional differences in muscle activity and to morphological alterations of stomatognathic system accompanying the complete teeth loss.

Microscopic image analysis for quantitative characterization of muscle fiber type composition

Skeletal muscles consist of muscle fibers that are responsible for contracting and generating force. Skeletal muscle fibers are categorized into distinct subtypes based on several characteristics such as contraction time, force production and resistance to fatigue. The composition of distinct muscle fibers in terms of their number and cross-sectional areas is characterized by a histological examination. However, manual delineation of individual muscle fibers from digitized muscle histology tissue sections is extremely time-consuming. In this study, we propose an automated image analysis system for quantitative characterization of muscle fiber type composition. The proposed system operates on digitized histological muscle tissue slides and consists of the following steps: segmentation of muscle fibers, registration of successive slides with distinct stains, and classification of muscle fibers into distinct subtypes. The performance of the proposed approach was tested on a dataset consisting of 25 image pairs of successive muscle histological cross-sections with different ATPase stain. Experimental results demonstrate a promising overall segmentation and classification accuracy of 89.1% in identifying muscle fibers of distinct subtypes.

Development of image analysis tool for the classification of muscle fibre type using immunohistochemical staining

An accurate characterisation of muscle fibres is essential for studying muscle plasticity. During some transient events such as ageing, myogenesis, physical activity or conversion of muscle to meat, the morphological parameters and/or the fibre type distribution may change. Nowadays, this information is generally obtained using immunohistology techniques, but these analyses are acknowledged to be laborious and time-consuming. In fact, each myofibre, from thousands, must be measured individually and its expression profile in response to different anti-myosin antibodies must be established step by step. In this paper, we describe a new histological approach using double-labelling (laminin, myosin) serial sections, fluorescence microscopy visualisation and, finally, semi-automatic image analysis. The goal of the study was to propose a tool allowing faster fibre type characterisation, including the identification of hybrid fibres from pure ones. The steps in the image processing prone to subjectivity have been fully automated. On the other hand, the expert retained control of all image analysis procedures requiring visual diagnosis. The tool that we developed with the Visilog software allowed a rapid and objective fibre typing and morphometric characterisation of two different bovine muscles. The results were in agreement with our previous histological and densitometric assays. The method and the tool proved to be potentially more efficient than other techniques used in our institute or described in the literature. A more global evaluation will be considered in other laboratories as well as on other animal species.