Muscle Morphology, Mechanics, and Performance Laboratory
University of Colorado :: RMR VAMC :: ECHS GRECC
Automated ultrasound image acquisition to aid criterion-based examiner training and reliability testing
Harris-Love MO, Ismail C, Monfaredi R, Hernandez HJ, Pennington D, Woletz P, McIntosh V, Adams B, Blackman MR, 2016 (doi:10.7717/peerj.2146)
Our group has utilized automated B-mode image acquisition featuring a portable ultrasound unit (SonoSite Titan M-Turbo) with a 6 MHz linear array sound transducer with a custom interface integrated with a load cell (FC22 Compression Load Cell; 0–44.48 ± 0.45 N). Automated image acquisition and sound transducer positioning were performed with the Kuka light weight arm (LWA) robot (7 degrees of freedom; motion error, ±0.05 mm) to attain uniform force and angle targets.
In determining the interrater reliablity of our novice and experienced staff using force feedback augmented imaging, no differences in material dimension measures were detected among the 6 examiners. Additionally, there was a high degree of association among the material thickness values obtained by the examiners and the Kuka LWA robot (R squared = .86-.97, p < .001). The initial data suggests that sonography with augmented force feedback allows examiners with varied experience levels to exhibit high interrater reliability.
Kuka LWA robot provided courtesy of the Sheikh Zayed Institute for Pediatric Surgical Innovation at Children's National Hospital
Custom muscle tissue mimetic used to calibrate diagnostic ultrasound devices and quantify soundwave attenuation characteristics.
Changes in serial sonographic image characteristics based on examiner force and sound transducer orientation
Harris-Love MO, Monfaredi R, Ismail C, Blackman MR, Cleary K, 2014. (doi:10.3389/fnagi.2014.00172)
The top panels of the figure (A–C) depict transverse views of a muscle tissue mimetic phantom with a progressive magnitude of stress imposed on the phantom surface by the sound transducer. The material deformation (thickness, centimeter) secondary to the stress progression was as follows: (A) 3.78 cm, (B) 3.45 cm, and (C) 3.21 cm.
The bottom panels (D–F) depict similar sonographic views as the preceding panels. The echointensity observed in the serial images is based on a progressively increasing cranial/caudal tilt angle of the sound transducer applied to the phantom surface. The changes in echointensity (grayscale, unitless, 0–255) secondary to the angle progression were as follows: (D) 56.64, (E) 48.10, and (F) 36.90. (All images were acquired using a 6 MHz linear array sound transducer and a muscle mimetic phantom with anechoic gel via automated image capture by the Kuka LWA robot.)
These serial images illustrate that progressive shifts in cranial/caudal tilting of 10° resulted in a >15% decrease in echointensity, and suggest that force feedback may enhance the consistency of manual image acquisition.
Understanding how the reliability of rehabilitative ultrasound is affected by the method used to select of the region of interest
Harris-Love MO, Seamon BA, Teixeira C, Ismail C., 2016. (doi.org/10.7717/peerj.1721)
The reliability of quantitative methods used during rehabilitative ultrasound procedures may be affected by many factors after image acquisition. We examined the impact of two image analysis factors: 1) the method used to select the region of interest (ROI), and 2) the software platform used for the grayscale histogram analyses.
The Bland-Altman plots in the figure depict the agreement between the grayscale measurements across the two image analysis platforms for Examiner 1. The limits of agreement for grayscale measures obtained using the Free Hand method (FHT) for ROI selection were wider than comparable measures obtained using the Rectangular Marquee Tool (RMT) method. The mean difference between the echogenicity estimates obtained with the RMT and FHT methods was .87 grayscale levels (95% CI [.54–1.21]; p < .0001) using data obtained with both Photoshop and ImageJ.
The RMT method facilitates a rapid selection of the region of interest, and use of the ImageJ software platform yielded lower measurement errors. However, the measurement differences were minimal between the methods, and the FHT method may be advantageous for muscles or tissues with irregular boundaries.
(RMT, Rectangular Marquee Tool; FHT, Free Hand Tool; diff., difference; grayscale level range = 0–255.)
Goodness of fit among the models in 2 representative US images from younger and older participants. Visually, the mixture of 2 gamma distributions provides a closer fit to the grayscale histogram than the other 3 distributions. However, the negative binomial dispersion parameter k may be an ideal independent variable to consider when examining the association of muscle tissue heterogeneity with strength in older adults.
Modeling estimates of muscle tissue heterogeneity in young and old adults
Harris-Love MO, Gonzales TI, Wei Q, et al., 2018. (doi.org/10.1002/jum.14864)
Tissue and body composition analysis via medical imaging results from indirect estimate methods and invariably has measurement limitations. Potential confounders of echogenicity measures include interfacility device variation, time‐gain compensation settings, and sound transducer parameters. Consequently, image‐processing and analysis strategies that are not wholly derived from image luminescence have been used to characterize muscle tissue morphologic characteristics.
Representative B‐mode US images of the rectus femoris muscle from a younger participant (A) and an older participant (D). Four statistical models were fitted to and overlaid (B and E) on the grayscale histograms of the pixel intensities in the ROIs (A and D). Comparisons of the χ2 goodness of fit (C and F) of the 4 statistical models were then evaluated relative to the grayscale histograms.
Grayscale values were significantly associated with peak grip strength force in younger adult participants (R2 = 0.36; P < .008). However, the negative binomial dispersion parameter k (adjusted R2 = 0.70; P < .001) and gamma shape parameter α (adjusted R2 = 0.68; P < .01) showed the highest associations with peak grip strength force in older adult participants.