Fully automated, semiautomated, and manual morphometric analysis of corneal subbasal nerve plexus in individuals with and without diabetes

Purpose The aim of the study was to determine the association, agreement, and detection capability of manual, semiautomated, and fully automated methods of corneal nerve fiber length (CNFL) quantification of the human corneal subbasal nerve plexus (SNP). Methods Thirty-three participants with diabetes and 17 healthy controls underwent laser scanning corneal confocal microscopy. Eight central images of the SNP were selected for each participant and analyzed using manual (CCMetrics), semiautomated (NeuronJ), and fully automated (ACCMetrics) software to quantify the CNFL. Results For the entire cohort, mean CNFL values quantified by CCMetrics, NeuronJ, and ACCMetrics were 17.4 ± 4.3 mm/mm2, 16.0 ± 3.9 mm/mm2, and 16.5 ± 3.6 mm/mm2, respectively (P < 0.01). CNFL quantified using CCMetrics was significantly higher than those obtained by NeuronJ and ACCMetrics (P < 0.05). The 3 methods were highly correlated (correlation coefficients 0.87–0.98, P < 0.01). The intraclass correlation coefficients were 0.87 for ACCMetrics versus NeuronJ and 0.86 for ACCMetrics versus CCMetrics. Bland–Altman plots showed good agreement between the manual, semiautomated, and fully automated analyses of CNFL. A small underestimation of CNFL was observed using ACCMetrics with increasing the amount of nerve tissue. All 3 methods were able to detect CNFL depletion in diabetic participants (P < 0.05) and in those with peripheral neuropathy as defined by the Toronto criteria, compared with healthy controls (P < 0.05). Conclusions Automated quantification of CNFL provides comparable neuropathy detection ability to manual and semiautomated methods. Because of its speed, objectivity, and consistency, fully automated analysis of CNFL might be advantageous in studies of diabetic neuropathy.

A comparison land-water environment of maximal voluntary isometric contraction during manual muscle testing through surface electromyography

Background The aim of this study was to compare through surface electromyographic (sEMG) recordings of the maximum voluntary contraction (MVC) on dry land and in water by manual muscle test (MMT). Method Sixteen healthy right-handed subjects (8 males and 8 females) participated in measurement of muscle activation of the right shoulder. The selected muscles were the cervical erector spinae, trapezius, pectoralis, anterior deltoid, middle deltoid, infraspinatus and latissimus dorsi. The MVC test conditions were random with respect to the order on the land/in water. Results For each muscle, the MVC test was performed and measured through sEMG to determine differences in muscle activation in both conditions. For all muscles except the latissimus dorsi, no significant differences were observed between land and water MVC scores (p = 0.063–0.679) and precision (%Diff = 7–10%) were observed between MVC conditions in the muscles trapezius, anterior deltoid and middle deltoid. Conclusions If the procedure for data collection is optimal, under MMT conditions it appears that comparable MVC sEMG values were achieved on land and in water and the integrity of the EMG recordings were maintained during wáter immersion.

No specific role for the manual motor system in processing the meanings of words related to the hand

The present study explored whether semantic and motor systems are functionally interwoven via the use of a dual-task paradigm. According to embodied language accounts that propose an automatic and necessary involvement of the motor system in conceptual processing, concurrent processing of hand-related information should interfere more with hand movements than processing of unrelated body-part (i.e., foot, mouth) information. Across three experiments, 100 right-handed participants performed left- or right-hand tapping movements while repeatedly reading action words related to different body-parts, or different body-part names, in both aloud and silent conditions. Concurrent reading of single words related to specific body-parts, or the same words embedded in sentences differing in syntactic and phonological complexity (to manipulate context-relevant processing), and reading while viewing videos of the actions and body-parts described by the target words (to elicit visuomotor associations) all interfered with right-hand but not left-hand tapping rate. However, this motor interference was not affected differentially by hand-related stimuli. Thus, the results provide no support for proposals that body-part specific resources in cortical motor systems are shared between overt manual movements and meaning-related processing of words related to the hand.

Limitations of the manual supination resistance test

The aim of this study was to asses results obtained from a range of commonly performed lower extremity “open and closed” chain kinetic tests used for predicting foot function and correlate these test findings to data obtained from the Zebris WinFDM-T system®. When performed correctly these tests are thought to be indicators of lower extremity function. Podiatrists frequently perform examinations of joint and muscle structures to understand biomechanical function; however the relationship between these routine tests and forces generated during the gait cycle are not always well understood. This can introduce a degree of variability in clinical interpretation which creates conjecture regarding the value of these tests.

Morphology-based interslice interpolation on manual segmentations of joint bones and muscles in MRI

This paper presents a validation study on the application of a novel interslice interpolation technique for musculoskeletal structure segmentation of articulated joints and muscles on human magnetic resonance imaging data. The interpolation technique is based on morphological shape-based interpolation combined with intensity based voxel classification. Shape-based interpolation in the absence of the original intensity image has been investigated intensively. However, in some applications of medical image analysis, the intensity image of the slice to be interpolated is available. For example, when manual segmentation is conducted on selected slices, the segmentation on those unselected slices can be obtained by interpolation. We proposed a two- step interpolation method to utilize both the shape information in the manual segmentation and local intensity information in the image. The method was tested on segmentations of knee, hip and shoulder joint bones and hamstring muscles. The results were compared with two existing interpolation methods. Based on the calculated Dice similarity coefficient and normalized error rate, the proposed method outperformed the other two methods.