Observation of a Triangular to Square Flux Lattice Phase Transition in YBCO

We have used the technique of small-angle neutron scattering to observe magnetic flux lines directly in an YBCO single crystal at fields higher than previously reported. For field directions close to perpendicular to the CuO2 planes, we find that the flux lattice structure changes smoothly from a distorted triangular co-ordination to nearly perfectly square as the magnetic induction approaches 11 T. The orientation of the square flux lattice is as expected from recent d-wave theories, but is 45 deg from that recently observed in LSCO

Does the Analysis of Separate Bands of Echo Intensity Strengthen the Relationship to Muscle Function?

Ultrasound echo intensity (EI) has been proposed as a method of assessing muscle quality through the use of non-invasive imaging. Traditionally, EI is assessed as the mean pixel brightness that ranges from 0-255 within an area of interest. However, it may be reasonable to consider that additional portions of the ultrasound EI signal (i.e., bands of signal) may provide novel insight to muscle function. The determination of which band of signal may be more related to a given functional outcome may increase the sensitivity of EI. Thus far, there is no research analyzing the association between EI bands and fatigue. PURPOSE: The purpose of this study was to compare relationships between mean echo intensity and unique bands of ultrasound signal of the vastus lateralis with metrics of whole muscle performance in healthy adults. METHODS: Twenty-four participants (mean ± age = 22 ± 3.9 yrs; BMI = 25.7 ± 3.4 kg/m2), completed two visits to the laboratory. On the first visit, subjects completed Brightness mode (B-mode) ultrasound imaging and were familiarized with the fatigue assessment. Between two and seven days later, subjects returned for the testing visit. B-mode ultrasound was used to image the vastus lateralis (VL) at 50% muscle length. The VL cross-sectional area was traced using the polygon tool. As much of the muscle was selected without selecting any of the surrounding fascia. Each pixel is assigned a brightness value from 0-255 based on gray scale; 0 representing true black and 255 is pure white. Mean EI was quantified from within the selected portion of the image. Echo intensity bands were calculated in pixel value intervals of 0-49, 50-99, 100-149, 150-199, 200-255. The percentage of pixels per band compared to the total number of pixels in each image was assessed by: (number of pixels in each band/ total number of pixels in the selected portion of the image)*100. For the fatigue assessment, participants completed 100 repeated, maximal, isokinetic muscle actions (120°/sec). Isokinetic peak torque was analyzed offline using custom written software by selecting individual torque peaks from each muscle action. Initial and final isokinetic peak torque were calculated by averaging the highest 3 of the first 5 and the highest 3 of the last 5 contractions. Isokinetic peak torque percent decline (%Decline) was calculated by: %Decline = (initial – PT – final - PT)/initial - PT. Pearson’s correlation coefficient (r) was used to assess the relationship between each EI band and %Decline as well as mean EI and %Decline. The Stieger’s Z procedure was used to compare the correlation coefficients between mean EI and each EI band. RESULTS: There were no significant correlation between mean EI and %Decline (r=0.03, p=0.88) or any of the EI bands and %Decline (r=-0.07-0.3, p=0.16-0.89). Additionally, there were no significant relationships between the mean EI and any of the EI bands (z=0.001-0.88, p=0.38-0.99). CONCLUSION: The findings suggest that unique bands of ultrasound signal do not offer different relationships compared to overall mean EI when assessing fatigue from repetitive isokinetic muscle actions

Reliability of Differing Muscle Size and Quality Analysis Techniques

Brightness-mode (B-mode) ultrasonography is a popular tool to examine anatomical cross-sectional area (ACSA) and echo intensity (EI). Muscle ACSA and EI provide valuable insight into muscle function due to their unique mechanisms which influence performance. Manually analyzing ultrasound images potentially increases variability which may increase error, thus decreasing the reliability of manual image analysis. Recently an automated program was created to improve reliability and reduce the time of ultrasound image analysis. PURPOSE: The purpose of this study was to investigate the reliability of manual compared to automatic ultrasound analyses of muscle cross-sectional area and echo intensity. METHODS: Twenty-two participants (mean ± SD age = 24 ± 4 yrs; BMI = 24.19 ± 3.26 kg/m2) volunteered for this study. The participants completed one visit to the laboratory consisting of two data collection trials separated by 10 minutes. Ultrasound scans were taken with a B-mode ultrasound imaging device and image settings were held constant (i.e., depth = 6 cm, frequency = 12 MHz, gain = 52 dB). For each trial, participants remained supine while ACSA scans of the vastus lateralis (VL) were taken at 50% the length of the proximal to distal musculo-tendon junctions. The ACSA of the VL was manually analyzed by an experienced technician with ImageJ using the polygon tool and tracing the area of interest. Echo intensity was quantified as the mean pixel brightness of the traced portion of the image. Images were automatically analyzed with the Deep Anatomical Cross-Sectional Area (DeepACSA) program which is an algorithm that is designed to automatically trace the area of interest of an ultrasound image. Test-retest reliability statistics (i.e., intraclass correlation coefficient [ICC] model 2,1, standard error of measure expressed as a percentage of the mean [SEM%], and the minimal differences [MD] values needed to be considered real) were calculated for trials 1 and 2. One-way repeated measures analysis of variance determined differences in trial 1 compared to trial 2. RESULTS: Manual analyses of ACSA (ICC2,1 = 0.98, SEM (%) = 3.39%, MD = 2.09 cm2, p = 0.046) were more reliable than automatic analyses (ICC2,1 = 0.87, SEM (%) = 12.33%, MD = 7.77 cm2, p = 0.216). Manual analyses of EI (ICC2,1 = 0.73, SEM (%) = 6.44%, MD = 10.83 cm2, p = 0.514) had similar reliability to the automatic analyses (ICC2,1 = 0.88, SEM (%) = 3.60%, MD = 6.30 cm2, p = 0.003). CONCLUSION: These results suggest that this automated analysis program may be less reliable compared to the manual analysis of muscle ACSA of the VL. Conversely, DeepACSA displayed similar reliability for EI of the VL when compared to the manual analysis

Test-Retest Reliability of Automatic and Manual Image Analyses of Muscle Size

Brightness-mode (B-mode) ultrasound is a non-invasive imaging modality that has risen in popularity. In research settings, B-mode ultrasound is often used to assess skeletal muscle size via the quantification of the anatomical cross-sectional area (ACSA). Typically, these images are analyzed by an experienced investigator using open-source software, though it is a time-consuming process that may introduce implicit bias into the analysis. Recently, a novel, automatic ultrasound image analysis tool has been developed which may reduce bias and increase the reliability of ultrasound ACSA image analysis. PURPOSE: The purpose of the project was to compare the test-retest reliability of manual and automatic ACSA quantification techniques. METHODS: Nine participants (mean ± SD: age = 25 ± 3 years; BMI = 23.96 ± 2.62 kg/m2) completed one laboratory visit where each participant had non-invasive ultrasound imaging performed on their rectus femoris (i.e., RF) for two data collection trials separated by 10 minutes. For each participant, ultrasound image settings were held constant (i = 6 cm, frequency = 10 MHz, gain = 52 dB). All images were manually analyzed by an experienced technician using an open-source image analysis tool. The investigator would carefully select only the surrounding muscle fascia of the RF. Automatic analyses were performed using DeepACSA, a deep learning approach for the assessment of ACSA. Both manual and automatic analyses were conducted on all images. Analysis of variance (ANOVA) was conducted to compare differences between trials and test-retest reliability (i.e., intraclass correlation coefficients [ICC] model 2,1, standard error of measure expressed as a percentage of the mean [SEM%], and the minimal differences [MD] values needed to be considered real) were calculated from the ANOVA output. RESULTS: The manual analyses of ACSA (p = 0.20, ICC2,1 = 0.84, SEM (%) = 11.67%, MD = 1.75 cm2) were more reliable than the DeepACSA analyses (p = 0.13, ICC2,1 = 0.47, SEM (%) = 30.28%, MD = 4.70 cm2). CONCLUSION: The results of the present investigation suggest that the DeepACSA approach may be less reliable compared to the manual quantification of RF muscle size. Future studies should investigate using a larger sample size and additional muscle groups

Bioimpedance Spectroscopy Compared to Ultrasound-derived Measures of Quadriceps Muscle Quality

Muscle quality is often measured using ultrasound-derived echo intensity (EI). Recent works have shown tissue frequency-dependent electrical impedance from bioimpedance spectroscopy may be a modality for assessing tissue quality. PURPOSE: The purpose of the project was to examine the association between ultrasound-derived EI of the quadriceps muscles (i.e., vastus lateralis [VL], vastus medialis [VM], vastus intermedius [VI], rectus femoris [RF]) and measures of thigh tissue frequency-dependent electrical impedance (i.e., R0, R1, C, a, fp). METHODS: Twenty-four participants (13 women; mean ± SD; age: 22 ± 4 years; BMI: 25.47 ± 3.26 kg/m2) were recruited. Participants completed one laboratory visit where quadriceps tissue quality was assessed via ultrasound and bioimpedance spectroscopy (BIS). Participants laid supine on a portable exam table to undergo imaging of the dominant leg VL using ultrasound in conjunction with a multi-frequency linear array probe (L4 – 12t – RS, 4.2-13 MHz, 47.1mm field of view). The VL was marked at the proximal and distal musculo-tendon junctions determined via ultrasound and the length was measured with a tape measure. Participants had cross-sectional scans of the VM, VL, VI, and RF at 25, 50, 75% of the length of the VL. Images were analyzed using the polygon tool in ImageJ to trace the muscles and provide EI values. Subcutaneous fat width was measured using the straight-line tool. Echo intensity was calculated using ImageJ gray-scale analysis and histogram function as well as corrected for subcutaneous fat. For statistical analyses, the average corrected EI for each muscle was created across scan sites. For BIS, participants were seated in a chair with Ag/AgCl electrodes placed above the patella and below the hip. Electrodes were placed 6cm apart and the Cole-impedance model was used to represent frequency-dependent thigh tissue data. Signals were analyzed using a custom-written software program. Pearson’s correlation coefficient (r) was used to determined associations between the VL, VM, VI, RF and BIS variables (R0, R1, C, a, fp). An alpha level of p ≤ 0.05 determined statistical significance. RESULTS: The results suggest that VL, VM, VI and RF echo intensity was significantly related to R0 (r = 0.65 – 0.81; p \u3c 0.01). For VI and RF, they were significantly related to a (r = -0.51 – -0.50; p = 0.01), but not for VL or VM (r = -0.39 - -0.22; p \u3e 0.06). Lastly, R1, C, and fp were not significantly correlated to the quadriceps muscles (r = -0.38 – 0.33; p \u3e 0.07). CONCLUSION: Our findings suggest that BIS-derived R0 may be a metric of muscle quality of the quadriceps as it was significantly related to ultrasound-derived measures of echo intensity of the VL, VM, VI, and RF. Further investigation of other muscle groups may be warranted

Classification of Complex Polynomial Vector Fields in One Complex Variable

A classification of the global structure of monic and centered one-variable complex polynomial vector fields is presented.Comment: 57 pages, 35 figures, submitted to the Journal of Difference Equations and Application

Mobility Disability in Older Adults: At the Intersection of People and Places

Mobility disability is associated with poor lower body function among older adults. This study examines whether specific types of neighborhood characteristics moderate that association