Summary of Methods
This study introduces variables to describe tissue motion and tissue deformation based on ultrasound-generated images (GE-medical Vivid 7, equipped with Tissue velocity imaging (TVI)). The methodology was used on 14 female patients with trapezius myalgia and 13 healthy controls when performing a 3-cm concentric shoulder elevation before and after pain provocation/exercise. A standardized region of interest (ROI) had a shape of an ellipsis and with a size that captures the upper and lower fascia of the trapezius muscle (4-cm width) at rest. The ROI was placed in the first frame of the loop registering the elevation and was subsequently re-anchored frame by frame in all frames of the concentric phase according to a certain acoustic pattern in the basal fascia that was used as a reference tag. In this way, the same tissue area was followed during all frames of the concentric phase and the quantitative measurements were calculated within the same tissue area. Within the ROI, two variables were calculated as a function of time: deformation and deformation rate. Hereafter, max, mean, and quadratic mean values (RMS) of each variable were calculated and compared before and after pain provocation/exercise.
The ultrasound equipment
A GE-Vivid 7 was equipped with separate non-commercial research software. A 12 MHz linear multi-hertz probe was used for all registrations. All analyses were made post-processed on custom-made non-commercial software.
The placement of the probe
To optimize the reproducibility of location of the probe, the SENIAM standard point of the trapezius [37] was used to centre the probe. The line from C7 to the edge of acromion was measured. This distance was divided by two, and the highest point on the shoulder belly at this distance was marked. The linear probe, measuring 4-cm long and 1-cm wide, was put in a coronal position over the landmark. Furthermore, the contour of the probe was drawn at the first placement. The angle of the probe was placed as close to the coronal plane as possible. Care was taken to ensure the same projection image was on the screen in all images.
EMG equipment
In this study, a single bi-polar EMG electrode (Centre to centre distance: 17 mm; Ambu, Ballerud, Denmark) was used to synchronize the ultrasound registration. The EMG electrode was placed at the medial edge of the probe 2 cm from the SENIAM point. The EMG was used as a reference indicating the electrical activation of muscle tissue. It was also used to ensure that the trapezius muscle was relaxed before and after the shoulder activation.
Tissue velocity imaging
To describe tissue activity, two fundamental concepts are used: 'movement' and 'deformation'. The most important difference between them is whether there is a presence of acceleration. To use a metaphor, imagine a train with some cabins. If no accelerating/decelerating force is present, the train will travel with constant speed and at a certain time point a certain distance is reached. The parameters used to describe this situation by way of ultrasound loops is velocity and displacement. However, when the train alters its speed, starts or brakes, an acceleration or deceleration occurs and the distance between the cabins will either be elongated or compressed. Thus, a deformation between the cabins of the train set occurs. Deformation is measured according to rest values and labelled strain when analyzing the ultrasound images, and the rate of deformation is labelled strain rate. In summary, to describe movement the terms velocity and displacement are used; to describe deformation, the terms strain and strain rate are used. The relationships between the four variables are given in Figure 1.
Because the skeletal muscle is an elastic entity, functional movements are part of variations in the neuro-motor activation pattern. This will result in a fine-tuned muscle tissue response. This response can be described in terms of compression or elongation. When a tissue is compressed, shortened, a contraction is present. Consequently tissue elongation is related to relaxation.
Strain
The concept of strain was originally used by Mirsky and Parmley (1973) [38] to describe elasticity and stiffness in the heart muscle as an altered dimension between an object at rest and a force-induced condition calculated according to (strain) = . L
0 is the original length and L is the measured new length of the object. As a consequence, negative strain implicates compression and positive elongation.
Strain rate
Strain rate [27, 39] is the rate by which a deformation occurs, the change in strain as a function of time. A small alteration in length (dL) within a small time segment (dt) is related to the velocities of the endpoints of the object: . Using this technique in the ultrasound loops, the image lines are divided in small distances (offset) in this study by 8 mm and regional velocities within each offset is calculated several times. Hereafter the mean value of the calculations within each offset is calculated. This principle will be further described below. The velocities are measured in the axial direction of the ultrasound beam (Figure 2).
From grey scale image to strain rate and strain imaging
The graphical ultrasound interface presents both a qualitative visualization and quantitative results of the described variables. The qualitative information in gained from a colour-coded superimposed image calculated from the velocity calculations described above. Hence, by stacking all images as a function of time, the alteration due to muscle response can be visualized (Figure 2). The quantitative results stem from marking an area, a region of interest, (ROI) within the tissue in the initial frame of the loop; therefore, calculations are limited according to the ROI. As a result of the ROI being followed frame-by-frame, a quantitative curve according to each parameter is presented.
The calculation principle is illustrated in Figure 2. The color-coded images stem from measuring differences between transmitted and received signals along the image lines (vertical lines in the second image). The results from the received signals are converted to a specific colour representing the magnitude and direction of the velocities. To receive the strain rate image, the image lines in themselves are divided according to a chosen offset (sample length), a pattern that forms a grid. Regional velocities are measured every 0.5 mm and the average of the regional velocities within each cell is color coded. As a result, strain rate imaging (3rd image in Figure 2) is a fine-tuned dynamic tissue mapping compared to the velocity images (2nd image in Figure 2; the red/blue image behind the grid), which only visualizes global velocities towards and away from the probe. The fourth image in Figure 2 visualizes the deformation process. Note that the presented images in Figure 2 are extracted from the loop covering approximately 300 frames.
In the first image from the left, the grey scale image of the trapezius muscle is seen. The second image is the velocity mapping where the blue color represents velocities moving away from the probe and red towards the probe. To illustrate how the third image in Figure 3 is calculated, a grid has been placed in the velocity image. When calculating regional velocities within each cell of the grid, the colour-coded result is presented as a superimposed image in the third image. Here, a more fine-tuned activity pattern arises where yellow/green represents passive tissue segments and blue represents contractile segments. The red color marks relaxation and follows the same rules (not present in the example above). Note that the blue color changes in nuance in different parts of the image. Deeper blue segments have higher strain rate than lighter blue nuances. Hence, alterations in the difference in the degree of the speed of segmental tissue contraction is visualized (note also that these images are extracted from a loop covering the whole shoulder elevation). Consequently, the relaxation phase is color coded in a similar manner in different nuances of red, representing various degrees of tissue relaxation (not shown here). It is important to emphasize that this software is developed for measuring tissue velocities in the heart muscle. In this case, heart tissue velocities are measured in the axial direction, i.e., towards and away from the probe. In the original software package, the coding of tissue velocity direction is coloured red representing tissue velocities moving towards the probe (contraction) while blue represent tissue velocities moving away from the probe, i.e., tissue elongation. Hence, when measuring muscle tissue velocities orthogonally projected, velocities are always relative.
The fourth image in Figure 2 is the integrated strain rate curve, strain. The colour-coded image visualizes deep blue tissue segments exceeding 50% (by the analyzer possible choice between 5 – 50%) and medium blue segments deformed between 31 – 50%. Light blue indicates a more passive tissue segment.
Thus, the images in Figure 2 provide qualitative information about the contraction progress and thus the dynamics of tissue response within the trapezius muscle during a shoulder elevation. In turn, the strain rate modality illustrates both the recruitment order of very small tissue segments during the muscle contraction and the rate variation of the tissue responses during the elevation. Thus, strain rate could be seen as related to the neurological innervation of the muscle while strain can be seen as the functional tissue response where tissue activity pattern changes as a function of the progress and nature of the movement.
Quantification of tissue velocities from velocity images
To quantify the tissue activity, a region of interest (ROI) is manually placed in the first frame of the loop (in this case an ellipsis is chosen that captures the centre part of the trapezius). Average strain rate and strain values within the ROI are calculated frame-by-frame and presented as a function of time (Figure 3). As a result, a multimodal presentation is simultaneous presented: the original grey scale loop (lower left), the superimposed colour-coded loop (upper left), and the curve representing the average values of a ROI strain (right part).
Variables calculated from tissue velocity images in the present study
Five variables were calculated from the velocity, strain rate, and strain parameters. According to velocity and strain rate, the mean value and quadratic mean value (root mean square (RMS)) were calculated while mean, RMS, and maximum values consistent with strain were considered.
RMS is a statistical calculation that measures the magnitude of a varying curve. It is especially useful when the measurements vary between positive and negative. The RMS calculation for a collection of n values x
1, x
2, ..., x
n
is calculated using
Furthermore, with respect to each variable the differences between the values before and after pain provocation were calculated. These variables form the basis of describing the results of the study.
Subjects
To study the above described method, trapezius myalgia patients were recruited along with healthy controls. The patients were recruited among female out-patients who had been referred to the Pain and Rehabilitation Centre, University Hospital, Linköping, Sweden due to chronic neck and shoulder pain. Exclusion criteria were widespread pain, prior neck trauma, rheumatoid arthritis, drug or alcohol abuse, overweight, and grave depression. Medical records were assessed and former patients were identified as possible participants. These potential subjects were invited by mail to participate in the study. The participants were examined using a standardized clinical examination [40]. To ensure the myalgic trapezius muscle was the problem, the following inclusion criteria were used:
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1.
Pain present in the neck and shoulder region at the clinical examination two weeks before and on the experimental day;
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2.
A tight trapezius muscle: a feeling of stiffness in the descending region of the trapezius muscle reported by the patients during lateral flexion of the head;
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3.
Palpatory tenderness of the trapezius muscle of the painful side; and
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4.
Normal or slightly decreased range of movement of the cervical columna.
In all, 14 women – mean age: 38 years, median 40 years (range: 24–48); mean height: 168 cm, median height 168 cm (range: 158–175); mean weight: 65 kg, median weight 63 kg (range: 51–81) – comprised the pain group. No detailed information was available concerning the duration of chronic pain, but the medical records clearly reported ongoing pain of more than 6 months duration.
Thirteen healthy women without neck and shoulder pain in the same age groups – mean age: 43 years, median 41 years (range: 36–55); mean height 168 cm, median height 168 cm (range: 158–175 cm); mean weight: 65 kg, median weight 56 kg (range: 47–75) – were recruited among staff and students at the Linköping University Hospital. The healthy controls were investigated using the same exclusion criteria and clinical examination as the patients. One patient and one healthy control were excluded due to a shadowing scapula during the shoulder elevation according to the ultrasound registrations. One healthy control was excluded for not being present at the time of the tests.
The person handling the ultrasound equipment knew whether the subjects were patients or controls.
All participants of both groups gave their informed written consent and the study conformed to The Declaration of Helsinki, and the study was approved by the Ethical Committee of Linköping University (Dnr M103-06).
Examination protocol
Two weeks after the clinical examination, the ultrasound (US) investigation was performed. The participants were asked not to use any medications due to pain 48 hours before the experimental day and were instructed not to perform any shoulder or neck-training exercise for 48 hours before the study, except for ordinary daily working and/or leisure duties. Furthermore, the participants were asked not to use nicotine or caffeine in any forms after midnight the day before the US examination.
Muscle contractions before pain provocation
The dynamic movement registered by the ultrasound image sequence (approximately 3-sec duration) covered the whole shoulder movement; i.e., both the concentric and the eccentric phase. The results of the present study are based on the concentric phase. The frame rate of the registrations is 141 frames per second giving a time resolution of approximately 7 ms. Thus, the rate at which the shoulder movement is registered is reasonably high enough to capture small intramuscular changes.
The subjects were asked to stand in an upright position with their arms hanging beside their body and their hands in a neutral position. The test subjects held a 1-kg dumbbell in the hand on the same side as the shoulder with pain; for the non-pain controls, the right arm was used. To standardize the shoulder elevation, a stand with an orthogonally placed level arm was used. The level arm was individually placed at each subject's shoulder at rest and a stop level was placed 3 cm above the shoulder in the elevation direction. The tempo of the movement was measured by a metronome and was set to 30 beats per minute. The subjects were instructed about the movements by the test leader and verbally led through the exercises concerning the tempo when performing the movements. Each subject performed two separate shoulder elevations at the start of the test. During the first elevation, the probe was held in a coronal position; during the second elevation, the probe was in a sagital position. Just a very short rest was present between the two elevations coinciding with the same procedure of the US loop. In this study, the coronal projection was used as this projection made it possible to follow a region of interest in the image sequence during the elevation. Thus, the before pain provocation procedure consisted of two subsequent elevations, which was registered by ultrasound. Hereafter, in mean three additional subsequent elevations were performed to achieve a pain intensity of 6 out of 10 according to a visual analogue scale (VAS; with the endpoints 0 = no pain and 10 = maximal pain intensity) without ultrasound registrations. When the patient had reached VAS 6, two subsequent ultrasound registrations were performed where ultrasound registrations were captured (i.e., after pain provocation procedure). As for the healthy controls, the procedure was 2 + 6 + 2 elevations where ultrasound registrations were performed during the first and last two elevations.
The pain/exercise provocation
The next step was pain/exercise provocation. The patients were asked to perform repetitive arm abductions holding the 1-kg dumbbell until the pain intensity according to VAS reached the level of 6. When the level was reached, the applicator provided two additional shoulder elevations in the same manner as at the start. First the applicator held the probe in a coronal position and then in the sagital projection. The number of additional repetitions varied slightly (between 2 and 3). As the healthy controls didn't report any pain at all, a standard choice of six repetitions was carried out by the controls. This choice was to make sure that the healthy subjects did not perform fewer repetitions than the patients (as the healthy patients were scheduled according to their possibility to attend in the study) without becoming fatigued.
Muscle contractions after pain/exercise provocation
Immediately after this provocation, the same procedure concerning shoulder elevation and probe position was repeated as before pain provocation. All US registrations were stored for post-process analysis.
Statistics
All statistical evaluations were made using the statistical packages SPSS (version 12.0) for traditional statistics and SIMCA-P+ (version 11.5) for multivariate statistics. Generally, results in the text and tables are given as mean values ± one standard deviation (± 1SD). As the number of subjects incorporated in this pilot study was small, non-parametric statistics were used. Mann Whitney, Wilcoxon, and Fisher's Exact tests were used to test group differences and differences within groups.
Principal component analysis (PCA) was used for the multivariate analyses. PCA can be viewed as a multivariate correlation analysis. The PCA also gives the opportunity to multivariately investigate how subjects cluster into subgroups and how certain subgroups differ. PCA detects whether a number of variables reflect a smaller number of underlying components by linear combinations. A cross-validation method, which keeps part of the data out of the model development, is used to assess the predictive power of the model. The result of this procedure is a test of the significance of the components. A graphical plot is provided by the components. This plot could be seen of as a window (a plane) that is built on two t-vectors. All original variables are then projected onto this plane and receive a t-score represented by the coordinate values in plane. Next the orientation of the plane is calculated in relation to the original variable space where the angles between the plane and original space reveal the closeness between the model and the original space. Hence each variable receives a weight that expresses the impact each variable has on the model. Therefore, this projection window is called a loading plot. These projection techniques generate two corresponding plots, one for the observations and one for the variables. These plots are correlated according to the positions in one plot and correspond to the same position in the other plot. The score plot is used in the interpretation in such a way that correlation patterns among the observations are revealed, and the loading plot reveals the impact of each variable on the model. Variables that have high loadings (with either positive or negative sign) on the same component are inter-correlated. A component consists of a vector of numerical values between -1 and 1, referred to as loadings. When obtaining more than one component, the vectors are orthogonally projected to each other and thus uncorrelated. Variables that have high loadings (positive or negative sign) on the same component are inter-correlated. Items with high loadings (ignoring the sign) are considered to be of large or moderate importance for the component under consideration.
Two concepts are further used to describe the results: R2 and Q2. R2 describes the goodness of fit – the fraction of sum of squares of all the variables explained by a principal component. Q2 describes the goodness of prediction – the fraction of the total variation of the variables that can be predicted by a principal component using cross validation methods. Outliers were identified using the two powerful methods available in SIMCA-P: score plots in combination with Hotelling's T2 (identifies strong outliers) and distance to model in X-space (DModX) (identifies moderate outliers). In all statistical analysis, p ≤ 0.05 was regarded as significant.
