Many factors contribute to the decline of skeletal muscle that occurs as we age. This is a reality that we may combat, but not prevent because it is written into our genome. The series of records from World Master Athletes reveals that skeletal muscle power begins to decline at the age of 30 years and continues, almost linearly, to zero at the age of 110 years. Here we discuss evidence that denervation contributes to the atrophy and slowness of aged muscle. We compared muscle from lifelong active seniors to that of sedentary elderly people and found that the sportsmen have more muscle bulk and slow fiber type groupings, providing evidence that physical activity maintains slow motoneurons which reinnervate muscle fibers. Further, accelerated muscle atrophy/degeneration occurs with irreversible Conus and Cauda Equina syndrome, a spinal cord injury in which the human leg muscles may be permanently disconnected from the nervous system with complete loss of muscle fibers within 5-8 years. We used histological morphometry and Muscle Color Computed Tomography to evaluate muscle from these peculiar persons and reveal that contraction produced by home-based Functional Electrical Stimulation (h-bFES) recovers muscle size and function which is reversed if h-bFES is discontinued. FES also reverses muscle atrophy in sedentary seniors and modulates mitochondria in horse muscles. All together these observations indicate that FES modifies muscle fibers by increasing contractions per day. Thus, FES should be considered in critical care units, rehabilitation centers and nursing facilities when patients are unable or reluctant to exercise.

This paper illustrates the feasibility and utility of combining cranial anatomy and brain function on the same 3D-printed model, as evidenced by a neurosurgical planning case study of a 29-year-old female patient with a low-grade frontal-lobe glioma. We herein report the rapid prototyping methodology utilized in conjunction with surgical navigation to prepare and plan a complex neurosurgery. The method introduced here combines CT and MRI images with DTI tractography, while using various image segmentation protocols to 3D model the skull base, tumor, and five eloquent fiber tracts. This 3D model is rapid-prototyped and coregistered with patient images and a reported surgical navigation system, establishing a clear link between the printed model and surgical navigation. This methodology highlights the potential for advanced neurosurgical preparation, which can begin before the patient enters the operation theatre. Moreover, the work presented here demonstrates the workflow developed at the National University Hospital of Iceland, Landspitali, focusing on the processes of anatomy segmentation, fiber tract extrapolation, MRI/CT registration, and 3D printing. Furthermore, we present a qualitative and quantitative assessment for fiber tract generation in a case study where these processes are applied in the preparation of brain tumor resection surgery.

Medical imaging is of particular interest in the field of translational myology, as extant literature describes the utilization of a wide variety of techniques to non-invasively recapitulate and quantity various internal and external tissue morphologies. In the clinical context, medical imaging remains a vital tool for diagnostics and investigative assessment. This review outlines the results from several investigations on the use of computed tomography (CT) and image analysis techniques to assess muscle conditions and degenerative process due to aging or pathological conditions. Herein, we detail the acquisition of spiral CT images and the use of advanced image analysis tools to characterize muscles in 2D and 3D. Results from these studies recapitulate changes in tissue composition within muscles, as visualized by the association of tissue types to specified Hounsfield Unit (HU) values for fat, loose connective tissue or atrophic muscle, and normal muscle, including fascia and tendon. We show how results from these analyses can be presented as both average HU values and compositions with respect to total muscle volumes, demonstrating the reliability of these tools to monitor, assess and characterize muscle degeneration.

Objective. Maintaining upright posture is a complex task governed by the integration of afferent sensorimotor and visual information with compensatory neuromuscular reactions. The objective of the present work was to characterize the visual dependency and functional dynamics of cortical activation during postural control.Approach. Proprioceptic vibratory stimulation of calf muscles at 85 Hz was performed to evoke postural perturbation in open-eye (OE) and closed-eye (CE) experimental trials, with pseudorandom binary stimulation phases divided into four segments of 16 stimuli. 64-channel EEG was recorded at 512 Hz, with perturbation epochs defined using bipolar electrodes placed proximal to each vibrator. Power spectra variation and linearity analysis was performed via fast Fourier transformation into six frequency bands (Δ, θ, α, β, γ_low, and γ_high,. Finally, functional connectivity assessment was explored via network segregation and integration analyses.Main Results. Spectra variation showed waveform and vision-dependent activation within cortical regions specific to both postural adaptation and habituation. Generalized spectral variation yielded significant shifts from low to high frequencies in CE adaptation trials, with overall activity suppressed in habituation; OE trials showed the opposite phenomenon, with both adaptation and habituation yielding increases in spectral power. Finally, our analysis of functional dynamics reveals novel cortical networks implicated in postural control using EEG source-space brain networks. In particular, our reported significant increase in local θ connectivity may signify the planning of corrective steps and/or the analysis of falling consequences, while α band network integration results reflect an inhibition of error detection within the cingulate cortex, likely due to habituation.Significance. Our findings principally suggest that specific cortical waveforms are dependent upon the availability of visual feedback, and we furthermore present the first evidence that local and global brain networks undergo characteristic modification during postural control.