Reliability and accuracy of an automated tracking algorithm to measure controlled passive and active muscle fascicle length changes from ultrasound

Abstract

Manual tracking of muscle fascicle length changes from ultrasound images is a subjective and time-consuming process. The purpose of this study was to assess the repeatability and accuracy of an automated algorithm for tracking fascicle length changes in the medial gastrocnemius (MG) muscle during passive length changes and active contractions (isometric, concentric and eccentric) performed on a dynamometer. The freely available, automated tracking algorithm was based on the Lucas-Kanade optical flow algorithm with an affine optic flow extension, which accounts for image translation, dilation, rotation and shear between consecutive frames of an image sequence. Automated tracking was performed by three experienced assessors, and within- and between-examiner repeatability was computed using the coefficient of multiple determination (CMD). Fascicle tracking data were also compared with manual digitisation of the same image sequences, and the level of agreement between the two methods was calculated using the coefficient of multiple correlation (CMC). The CMDs across all test conditions ranged from 0.50 to 0.93 and were all above 0.98 when recomputed after the systematic error due to the estimate of the initial fascicle length on the first ultrasound frame was removed from the individual fascicle length waveforms. The automated and manual tracking approaches produced similar fascicle length waveforms, with an overall CMC of 0.88, which improved to 0.94 when the initial length offset was removed. Overall results indicate that the automated fascicle tracking algorithm was a repeatable, accurate and time-efficient method for estimating fascicle length changes of the MG muscle in controlled passive and active conditions.

UltraTrack: Software for semi-automated tracking of muscle fascicles in sequences of B-mode ultrasound images

“…have been described and their use validated previously [4,7], but for completeness we will also describe it 66…”

“…These employ a variety of methods including Kanade--Lucas--Tomasi feature tracking and 34 affine transformation extensions to optic flow. The validity and reliability of the affine optic flow algorithm 35 of Cronin et al [4] was published some time ago [4,7]. The algorithm and the software implementation 36 have since been substantially expanded and in this paper we present the refined algorithm and freely 37 available software package, UltraTrack version 4.1, the source code for which is written in Matlab (The 38 MathWorks Inc., USA).…”

Differences in contractile behaviour between the soleus and medial gastrocnemius muscles during human walking

“…The probe was secured over the skin surface with a custom-made support device to prevent movement of the probe relative to the skin. MG and soleus muscle fascicle lengths were determined throughout the step cycle using an automated fascicle tracking algorithm validated previously (Cronin et al, 2011a;Gillett et al, 2012). Data were sampled at 10min intervals and analysed from four to five steps per interval for all participants and then averaged.…”

Estimation of longitudinal muscle motion using a primal-dual algorithm

“…Ultrasonography (US) has been one of most attractive ways of assessing human muscles under both static and dynamic conditions since its low cost, high flexibility and extraordinary patient friendliness [9] and has been proved to be able accurately measure the changes of muscle thickness [10] [11], fiber length [12,13], pennation angle [14][15][16] and cross sectional area [17,18]. Some algorithms were reported to be able to track important features of contracting muscle from one frame to the next automatically [19,20]. While other algorithms were focused on the computation of the muscle motion field [21,22], which was called optical flow and involved the computation of various temporal-and spatialderivatives of original image sequences usually.…”