Magnetic resonance imaging compared with electrodiagnostic studies in patients with suspected carpal tunnel syndrome: predicting symptoms, function, and surgical benefit at 1 year

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Object

The goal in this study of patients with clinical carpal tunnel syndrome (CTS) was to compare the usefulness of magnetic resonance (MR) imaging with that of electrodiagnostic studies (EDSs) for the following purposes: 1) prediction of 1-year outcomes and 2) identification of patients who are likely to benefit from surgical treatment.

Methods

The authors prospectively enrolled 120 patients with clinically suspected CTS. The participants were tested using standardized EDSs, MR imaging, and a battery of questionnaires, including the Carpal Tunnel Syndrome Assessment Questionnaire, a well-validated 5-point score of symptoms and function. The EDSs and MR images were each interpreted independently. Patients were reevaluated after 1 year. The decision to treat patients conservatively or by carpal tunnel release was made by the individual surgeon, who had access to the initial EDS but not MR imaging results. Univariate and multivariate analyses were used to determine associations between 1-year outcomes and baseline diagnostic tests.

Results

The authors recontacted 105 of 120 participants at 12 months. Of these, 30 patients had had surgery and 75 had not. Patients who had undergone surgery showed greater improvement at 1 year than those who had not had surgery. The length of the abnormal T2-weighted nerve signal on MR imaging and median–ulnar sensory latency difference were the strongest predictors of surgical benefit. There was a clear patient preference for the MR imaging over EDSs.

Conclusions

The findings obtained with MR imaging of the carpal tunnel predict surgical benefit independently of nerve conduction studies.

Abbreviations used in this paper: AIC = Akaike Information Criterion; CPT = Current Procedural Terminology; CTS = carpal tunnel syndrome; CTSAQ = Carpal Tunnel Syndrome Assessment Questionnaire; EDS = electrodiagnostic study; FOV = field of view; MR = magnetic resonance; SD = standard deviation; STIR = shorttau inversion recovery.

Abstract

Object

The goal in this study of patients with clinical carpal tunnel syndrome (CTS) was to compare the usefulness of magnetic resonance (MR) imaging with that of electrodiagnostic studies (EDSs) for the following purposes: 1) prediction of 1-year outcomes and 2) identification of patients who are likely to benefit from surgical treatment.

Methods

The authors prospectively enrolled 120 patients with clinically suspected CTS. The participants were tested using standardized EDSs, MR imaging, and a battery of questionnaires, including the Carpal Tunnel Syndrome Assessment Questionnaire, a well-validated 5-point score of symptoms and function. The EDSs and MR images were each interpreted independently. Patients were reevaluated after 1 year. The decision to treat patients conservatively or by carpal tunnel release was made by the individual surgeon, who had access to the initial EDS but not MR imaging results. Univariate and multivariate analyses were used to determine associations between 1-year outcomes and baseline diagnostic tests.

Results

The authors recontacted 105 of 120 participants at 12 months. Of these, 30 patients had had surgery and 75 had not. Patients who had undergone surgery showed greater improvement at 1 year than those who had not had surgery. The length of the abnormal T2-weighted nerve signal on MR imaging and median–ulnar sensory latency difference were the strongest predictors of surgical benefit. There was a clear patient preference for the MR imaging over EDSs.

Conclusions

The findings obtained with MR imaging of the carpal tunnel predict surgical benefit independently of nerve conduction studies.

The diagnosis of CTS is usually based on a combination of signs, symptoms, and results of EDSs.48 Since the mid-1980s, several groups have reported the use of MR imaging14,17,23,25,29,30,37,39–42,45,47,51,59 and ultrasonography studies7,12,15,27,28,32,33,49,51,52 for patients with CTS. In the earlier studies diagnostic accuracy was investigated with respect to anatomy (comparing images with cadaveric specimens), whereas later studies incorporated various gold standard definitions of disease that usually included both the findings of nerve conduction studies and clinical symptoms.

Evaluations of the efficacy of EDSs are difficult because these studies are widely viewed as an integral part of the gold standard definition of disease,48 making it hard to find an independent standard that does not incorporate EDS findings. The importance of diagnosing patients with disease is not only to identify the presence of a condition, but to allow clinicians to choose appropriate therapies and assign prognosis. Examining how well EDSs predict response to therapies circumvents the problem raised by the incorporation of the EDS into the “gold standard” definition of CTS. Rather than focus on how well a diagnostic test classifies patients in terms of the presence or absence of a condition (diagnostic accuracy), another approach is to ask how well the diagnostic test identifies patients who will benefit from a therapeutic intervention. Although EDSs are widely used for patients with suspected CTS, there is varying evidence as to how well they correlate with symptom severity and response to treatment. For example, Priganc and Henry46 found no relationship between symptom severity according to EDSs and such well-accepted measures of clinical disease as the Katz–Stirrat hand pain diagram and the CTSAQ. In contrast, Dennerlein et al.13 found that distal motor and sensory latencies did correspond to preoperative symptom severity. There is also conflicting evidence regarding the ability of EDSs to predict outcome. Several investigators have found a correlation between various EDS parameters and outcomes after surgery.6,9,13,21 For example, Bland9 found that patients with moderate EDS abnormalities did the best after surgery, compared with those with either very severe or very mild findings. Dennerlein et al. showed that distal motor latency correlated with outcome. Others have not found such a relationship.2,19,31,58 In the only randomized controlled trial of surgery compared with conservative therapy for CTS, Gerritsen et al.20 found that EDS results were not a significant predictor of which patients would improve without surgery.

Given this ambiguity regarding EDSs, MR imaging might play a useful role in further clarifying which patients would benefit from surgery for CTS. The current literature is less than definitive regarding the ability of MR imaging studies to predict the outcomes in patients with CTS. Most of the studies of the diagnostic accuracy of MR imaging for CTS have either involved small cohorts or had various biases, such as spectrum bias, that tended to inflate the reported diagnostic accuracy.11,17,23,29,30,37,41,43,44,47,51,53,56,57,59 Several authors have identified swelling of the median nerve and increased signal intensity on T2-weighted images as important indicators of CTS.29,47 Flattening of the median nerve is more controversial, with 1 author advocating the absence of flattening as indicative of CTS,29 whereas another found nerve flattening to be quite specific for CTS.47 Our group had previously reported the diagnostic accuracy of MR imaging for patients with suspected CTS by using a combination of nerve conduction criteria and the hand pain diagram as a gold standard.25 We now report the 1-year follow-up of this group of patients, with our primary goal being to compare the ability of MR imaging and EDSs to predict outcomes following treatment.

Clinical Material and Methods

Patient Population

We obtained 1-year follow-up information on 105 (88%) of 120 prospectively enrolled patients with clinically suspected CTS from 5 clinical sites. These 105 subjects comprise the basis for this report. Details of the cohort's assembly are published elsewhere.25 Briefly, we identified and recruited adult patients when they were referred for EDS testing. The study was approved by our institutional review board, and all participants provided signed informed consent. All data were collected prior to the enactment of the Health Insurance Portability and Accountability Act.

On the day of their MR imaging session, our study nurse (an occupational health nurse specialist) administered a standardized hand examination, including 3-point pinch strength (mean score of 3 efforts), Tinel sign, Phalen sign, and the hand pain diagram classification,26 a self-administered instrument that classifies patients into the following categories: 1) classic CTS; 2) probable CTS; 3) possible CTS; and 4) unlikely CTS. Two reviewers classified the hand pain diagrams into 1 of these 4 categories. Discrepancies were discussed and resolved by consensus. In addition, patients completed a battery of questionnaires focused on their hand pain and functional status, general health status, and occupation. These questionnaires included the CTSAQ34 and the general health-related quality of life Short Form-12,54,55 both of whose reliability and responsiveness have been well evaluated. The CTSAQ measures symptoms and function on separate scales, with 5 points the worst score and 1 point the best score for each scale. Physical and mental component summary scores were calculated for the Short Form-12.

All patients then underwent a standardized EDS. Although the EDSs were done at 5 different clinical sites, all participants had a standardized minimum examination consisting of the following: 1) 8-cm transcarpal orthodromic median sensory peak latency; 2) 8-cm transcarpal orthodromic ulnar sensory peak latency; 3) 8-cm median motor wrist stimulation (onset latency and amplitude); and 4) median forearm conduction velocity. The skin temperature over the carpal tunnel was measured and an attempt was made to raise it to > 32°C.24

The MR imaging was performed at 3 centers, all of which had 1.5-T systems. At 2 sites a custom-designed phased-array wrist coil was used, and at the third a quadrature knee coil was used. Our imaging protocol with the phased-array wrist coil consisted of 3 standard sequences: 1) coronal or sagittal localizer T1-weighted spin echo studies (TR 600 msec, TE minimum, 18-cm FOV, 256 × 192 matrix, 4-mm slice thickness, 4 minutes); 2) axial T1-weighted spin echo studies (TR 450 msec, TE minimum, 11-cm FOV, 256 × 256 matrix, 4-mm slice thickness, 1-mm skip, 5.5 minutes); and 3) axial fast STIR imaging (TR 3650 msec, TE 54 msec, TI 160 msec, echo train length 6, 11-cm FOV, 256 × 224 matrix, 4-mm slice thickness, 1-mm skip, 5.25 minutes). Generally, we obtained 11–15 slices in the axial plane covering 55–75 mm. We modified the protocol slightly for the quadrature knee coil, using fat-suppressed T2-weighted images with a slightly larger FOV and slightly smaller slice thickness.

Two readers (both neuroradiologists with at least 10 years of experience and a special interest in peripheral nerve imaging) who were blinded to all clinical and EDS information graded the following parameters on a 4-point scale (normal, mild, moderate, or severe): median nerve signal intensity on T2-weighted images relative to normal-appearing muscle; the degree of nerve compression according to the flattening ratio described by Britz et al.;10 bowing of the flexor retinaculum as determined by extension beyond the line between the insertions of the flexor retinaculum on the trapezium and the hook of the hamate; high signal on T2-weighted images and thickening of the flexor tendon interspace; signal within the palmar bursa; thenar muscle signal; and fascicular prominence. Figure 1 shows a normal-appearing median nerve and Fig. 2 provides examples in which each of the aforementioned items was rated as abnormal. Readers also evaluated the length in millimeters of the abnormally high signal of the median nerve on T2-weighted images, and identified the first and last image on which they believed the median nerve exhibited an abnormally high signal. The length of abnormal signal was the distance between these first and last (inclusive) images, measured in millimeters. Previously we reported that the reliability of these parameters when independently evaluated by 2 neuroradiologists was moderate to substantial.25 One reader interpreted only a subset of studies (in 77 patients) to determine reliability. For our analysis, we used the interpretations of a single reader.

Fig. 1.
Fig. 1.

A and B: Two examples of normal-appearing median nerves demonstrated on STIR images. The median nerves (arrows) are nearly isointense with muscle (asterisks). C: An MR image with a line drawn from the tip of the hook of the hamate (h) to the region of the trapezial tubercle (t) shows no bowing (perpendicular line < 3 mm) of the flexor retinaculum, in contrast to the line in Fig. 2C.

Fig. 2.
Fig. 2.

A: A STIR image depicting a markedly hyperintense median nerve (arrow). B: A STIR image showing a severely flattened median nerve (arrows) at the level of the hook of the hamate. C: A T1-weighted MR image demonstrating bowing of the hypointense flexor retinaculum (arrows). A line is drawn from the tip of the hamate hook to the trapezial tubercle, with a perpendicular line demonstrating how measurements of the flexor retinaculum were performed. D: A STIR image showing high signal and thickening of the flexor tendon interspace and deep palmar bursa (large arrows). The small arrows point to an enlarged and high-signal median nerve with a prominent and irregular fascicular pattern. E: A STIR image obtained in a different patient also shows high-signal median nerve with a prominent and irregular fascicular pattern (arrows).

A third reader, working in a blinded fashion, measured the cross-sectional area of the carpal tunnel at the hook of the hamate as well as the area of the median nerve at the distal radial–ulnar joint, pisiform joint, hamate hook, and metacarpal–phalangeal joint. These measurements were performed in a subset of 85 patients in whom the studies had been performed at 1 of our sites where the imaging data could be transferred to a workstation for analysis.

Participants also answered questions regarding their preference for diagnostic testing. These questions included the following: 1) if they needed to have testing repeated, whether they would prefer having an MR imaging study or an EDS; and 2) how they rated their experience for both the MR imaging and EDS on a 9-point Likert scale (extremely unpleasant to extremely pleasant). Because MR imaging was not part of the routine clinical care but EDS was, the results of the MR studies were not made available to the clinicians or patients. Thus, subsequent treatment decisions could have been based at least in part on the EDSs but not the MR images.

One year after the initial MR imaging and EDSs, patients were recontacted by telephone, and CTSAQ symptom and function scores were obtained, as well as information about interim treatments. These follow-up interviews were focused on the participant's symptoms and functional status, and so we collected only limited information with respect to treatment. This information consisted of whether surgery was performed and the date of the surgery. We did not collect identifying information about the surgeon nor a detailed description of the surgery. Thus, we were unable to compare endoscopic with open approaches. A single research coordinator enrolled all patients and administered both baseline and follow-up questionnaires.

Statistical Analysis

We used univariate logistic regression to identify clinical and EDS predictors of whether surgery would be performed within the follow-up period. We then incorporated those variables with a probability value < 0.1 into a multivariate logistic regression in which both forward and backward stepwise methods were used to identify potential predictors, selecting variables with probability values < 0.1 as potential predictors of surgery.38 Then, controlling for baseline CTSAQ scores and the surgical predictors identified earlier, we used linear multivariate regression to determine associations between baseline variables and 1-year outcomes for the entire cohort (both patients who had and those who had not undergone surgery). Our primary outcome variable was the 1-year CTSAQ function score. Secondary analyses included the CTSAQ symptom score, Short Form-12 physical and mental component summary scores, and measures of disability including days of work lost. Because we deliberately blinded clinicians to the MR imaging results so that these would not influence treatment, we could not examine its influence on predicting subsequent surgery. To determine the ability of a variable to predict the benefit of surgery, we examined the interaction between the dichotomous treatment variable (surgery compared with no-surgery group) and variables that were significantly associated with outcome in our multivariate model.

One common approach to model selection is the AIC. The AIC can be thought of as balancing the goodness of fit of a model with the number of parameters included in the model. By minimizing the AIC, one can identify the most parsimonious yet best-fitting model, or in other words, the most information for the fewest variables.1

We used a change in the AIC to identify variables that independently predicted surgical benefit. A statistically significant interaction between a predictor variable and the surgical treatment indicator implies that there is change in the comparison of outcome among surgically and conservatively treated patients across the levels of the covariate. For certain values of the covariate there may be a large benefit associated with surgery, whereas for other values there may be no benefit or even a detrimental effect. We first built models by using both the CTSAQ function and symptom scores as the dependent variables. Using a multivariate linear regression, we examined which clinical baseline characteristics were predictors of 1-year outcome. We controlled for the baseline CTSAQ function score and the predictors of surgery. Finally, we constructed interaction terms between variables that significantly predicted outcome in our multivariate model and the type of treatment (surgery compared with no-surgery groups), thus measuring surgical benefit. We then included these terms in a new model predicting 1-year outcome. Because of the limited sample size, we had to limit the number of covariates in our model and chose to control for the major category of surgery compared with no surgery, rather than subcategories of surgery or conservative treatment type.

All analyses were performed using the statistical software packages SPSS version 11.0 or Stata.

Results

Cohort Characteristics

There were no statistically significant baseline differences between the 105 patients we contacted for follow-up and the 15 we were unable to contact, except that the proportion of women was higher in the group with follow-up (49% compared with 20%; p = 0.05, Fisher exact test). Table 1 displays the baseline demographic variables for the cohort as a whole as well as by surgical status during the year of follow-up. The mean baseline CTSAQ symptom and function scores were significantly higher for the group that underwent surgery than for the nonsurgical group (p = 0.03 for symptom summary score and p = 0.04 for function summary score).

TABLE 1

Baseline characteristics of the study cohort of 105 patients*

Category
FactorEntire CohortNonsurgical at 1 YrSurgical at 1 Yr
no. of patients1057530
baseline demographic data
age in yrs
 mean42.041.443.8
 range18–7018–6929–70
sex (% female)48.645.356.7
race (%)
 Caucasian84.081.390.0
 African-American3.84.03.3
 Asian/Pacific Islander2.92.73.3
 American Indian2.94.00
 other6.78.03.4
% w/ or applied for disability comp57.162.743.3
% w/ other musculoskeletal disorders48.653.346.7
body mass index
 mean28.628.329.3
 range19.4–44.720.4–44.719.4–39.4
baseline signs, symptoms, & risk factors
symptom duration at presentation for EDS (%)
 <6 wks10.912.76.7
 6 wks–3 mos10.99.913.3
 3 mos–1 yr27.732.416.7
 >1 yr50.545.163.3
no. of previous episodes (%)
 none69.271.663.3
 1–59.69.510.0
 >53.82.76.7
 continuous symptoms17.316.220.0
% w/ hand pain diagram classification
 classic17.114.723.3
 probable20.016.030.0
 possible59.064.046.7
 not CTS3.85.30
% w/ Phalen sign73.579.757.1
% w/ Tinel sign46.742.756.7
% w/ thenar atrophy7.75.413.3
% w/ repetitive hand motion at work (>20 hrs/wk)58.954.070.4
% w/ forceful hand motion at work (>20 hrs/wk)47.847.648.1
% w/ awkward hand position at work (> 20 hrs/wk)46.746.048.1
% w/ handheld vibrating tool (>20 hrs/wk)30.829.733.3
% w/ keyboard use (>20 hrs/wk)25.026.222.2
% currently working56.254.760.0
mean pinch strength (kg)7.45 ± 2.887.90 ± 2.816.36 ± 2.82
mean CTSAQ function2.46 ± 0.852.33 ± 0.792.77 ± 0.92
mean CTSAQ symptoms2.98 ± 0.842.88 ± 0.863.24 ± 0.74
% w/ bilat symptoms58.852.873.3
% w/ night awakening due to pain42.236.156.7
% w/ night awakening due to numbness48.343.162.5
% w/ severe night numbness91.387.7100.0
% w/ severe night pain32.123.353.4
% w/ frequent day pain65.766.065.0
% w/ flick test positive21.619.227.6
% w/ dominant hand most symptomatic84.884.086.7
baseline EDS findings
abnormal median–ulnar sensory difference (%)43.844.043.3
mean median nerve sensory latency (msec)2.56 ± 0.592.44 ± 0.512.90 ± 0.69
mean median–ulnar sensory latency difference (msec)0.60 ± 0.600.49 ± 0.500.92 ± 0.74
mean median motor latency (msec)4.86 ± 1.514.61 ± 1.435.51 ± 1.54
mean median motor amplitude (mV)9.09 ± 3.619.07 ± 3.149.14 ± 4.65
baseline MR imaging findings
mean length of median nerve high signal (mm)22.4 ± 17.520.9 ± 17.626.6 ± 17.3
mean median nerve signal2.6 ± 1.12.5 ± 1.12.8 ± 1.1
mean degree of median nerve flattening2.0 ± 1.02.1 ± 1.02.0 ± 1.0
mean degree of flexor retinaculum bowing1.5 ± 0.81.5 ± 0.81.4 ± 0.7
mean degree of flexor tendon interspace thickening1.7 ± 0.71.7 ± 0.71.6 ± 0.7
mean degree of thenar muscle STIR signal1.1 ± 0.41.1 ± 0.31.1 ± 0.4

* The means are given ± SDs where appropriate. Abbreviation: comp = compensation.

† Includes osteoarthritis, rheumatoid arthritis, fibromyalgia, and others.

‡ All variables except the length of abnormal signal were scored on a 0–3 scale, with 0 designating normal and 3 defined as severely abnormal.

Baseline Diagnostic Tests and Clinical Characteristic Correlation

Neither MR imaging nor EDS findings correlated with measures of symptoms or functional status at baseline (Table 2). Patient acceptance of MR imaging was much higher than that of EDS. Experience was rated from −4 (very unpleasant) to +4 (very pleasant), with 0 designating indifferent. The mean experience rating for EDS was −1.7 (range −4 to +3 [SD 1.9]) compared with 1.0 (range −4 to +4 [SD 2.2]) for MR imaging (p < 0.001, Wilcoxon signed-rank test). When dichotomized to pleasant versus unpleasant, 79 (76%) of 104 patients rated the EDS experience as unpleasant, whereas only 22 (21%) of 104 rated the MR imaging session as unpleasant. (Not all patients answered all questions, so the number of responses varies from item to item.) Of those with a preference for having one or the other test again (99 of 104), 91 (92%) of 99 patients preferred to have MR imaging again compared with 8 (8%) of 99 preferring to have the EDS again (p < 0.001, chi-square test).

TABLE 2

Pearson correlation coefficients calculated between baseline diagnostic tests, symptoms, and function*

TestMean CTSAQ Symptom Baseline Scorep Value (two-tailed)Mean CTSAQ Function Baseline Scorep Value (two-tailed)
MRI T2 signal intensity of median nerve0.0830.3670.1200.194
MRI median nerve configuration−0.0170.8500.0750.415
MRI length of T2 abnormal signal0.0360.7040.0720.442
EDS median sensory velocity0.0480.632−0.0600.548
EDS median–ulnar difference0.0430.672−0.0550.585
EDS median motor latency0.0810.3830.0070.940

* All correlation coefficients are the Pearson correlation coefficients.

Subsequent Treatment

Of the 105 patients contacted at 1 year, 30 (29%) had undergone surgery. Patients in both groups had received a variety of other therapies: 36 had wrist splinting, 22 had taken nonsteroidal antiinflammatory agents, 19 had undergone occupational and/or physical therapy, and 2 had received steroid injections. The proportion of those who had compared with those who did not have these other treatments was not statistically significantly different between the surgical and nonsurgical groups.

Predictors of Surgery

Table 3 lists the baseline variables that were associated with surgery, using either a forward or backward stepwise model. Five variables attained the threshold (p < 0.1) to be included in subsequent models as predictors of surgery: median motor latency, Phalen sign, baseline CTSAQ symptom score, awakening with night numbness, and pinch strength. Of note is the fact that the median nerve sensory latency and the median–ulnar nerve sensory latency difference were not independent predictors of surgery. All variables had effects in the expected direction except for the Phalen sign, in which case patients with a positive Phalen were less likely to have surgery. A closer inspection of the data confirmed this association. Of those with a positive Phalen sign, 59 (79%) of 75 did not have surgery, whereas 15 (56%) of the 27 with a negative Phalen sign did not have surgery.

TABLE 3

Predictors of surgery in patients with CTS

Baseline VariableAdjusted Odds Ratiop Value
forward stepwise model
 CTSAQ symptom score2.820.02
 Phalen sign0.190.03
 median motor latency2.1100.02
backward stepwise model
 nighttime numbness awakening3.120.09
 grip strength0.770.04
 Phalen sign0.180.03
 median motor latency2.090.03

Surgical Benefit

Body mass index was the only baseline clinical variable significantly associated with outcome at 1 year (a higher body mass index was associated with worse outcome).

After controlling for the 5 variables that predicted surgery, when we added the EDS to the regression, only the interaction between surgery and the difference between the median and ulnar nerve sensory latencies were significant. A similar analysis that used the MR imaging variables rather than the EDS variables revealed only that the interaction between surgery and the length of signal abnormality was close to significance (p = 0.067, β statistic –0.317). This interaction coefficient means that for every millimeter increase in signal abnormality the difference between the mean CTSAQ score among patients who had surgery and those who were treated conservatively increased by 0.317 points. In other words, the longer the signal length, the greater the benefit of having surgery. This is illustrated in Table 4, which examines the change in CTSAQ scores from baseline to follow-up as a function of the length of abnormal MR imaging signal, stratified by the patients' surgical status. Patients in the nonsurgical group with the longest category of abnormal signal (> 3 cm) were the only subgroup to have actually worsened over time. In contrast, patients with shorter segments of signal abnormality did not deteriorate symptomatically.

TABLE 4

Change in functional status based on signal length*

Length of Abnormal Signal
Factor<1 cm1–2 cm2–3 cm>3 cm
no. of patients33191933
change in mean CTSAQ function (nonsurgical patients)−0.250 ± 0.617−0.245 ± 0.690−0.364 ± 0.6230.242 ± 0.773
change in mean CTSAQ function (surgical patients)−0.229 ± 0.8710.121 ± 0.664−1.06 ± 0.975−1.28 ± 1.03

* The means are given ± SDs.

Table 5 summarizes the findings of our multivariate regression model, which includes as the main effects the following: 1) the baseline CTSAQ function; 2) the 2 diagnostic test variables median motor latency and length of abnormal MR imaging signal; and 3) the interactions between treatment (surgery compared with no surgery) and the diagnostic test variables. The baseline CTSAQ function score is a strong and highly significant predictor of outcome, and abnormal signal length is a strong and significant predictor of surgical benefit.

TABLE 5

Predictors of follow-up CTSAQ function score from multivariate model*

95% CI for β Statistic
Factorβ StatisticLowerUpperp Value
baseline CTSAQ0.6050.4500.757<0.001
follow-up op (yes/no)1.6690.6252.7130.002
length of abnormal signal on STIR T2-weighted MRI−0.002−0.0110.0070.656
interaction btwn treatment & MRI signal length−0.024−0.042−0.0070.008
median motor latency (msec)0.020−0.0880.1280.717
interaction btwn treatment& median motor latency−0.253−0.448−0.0580.012

* CI = confidence interval.

To determine how abnormal signal length on MR imaging compares with median motor latency in their ability to predict outcome, we built 3 models, each with the follow-up CTSAQ function score as the dependent variable and controlling for the CTSAQ function score at baseline. The variable of interest for the first model was the median motor latency, for the second model it was the length of the abnormal MR imaging signal, and for the third model it was both of these variables (Table 5). The values of AIC for each of the models were as follows: first model AIC = 224.7; second model AIC = 225.5; and third model AIC = 220.9. When we incorporated the interaction between surgery and the variable of interest, the values became as follows: first model AIC = 215.8; second model AIC = 213.8; and third model AIC = 206.3. The AIC additively penalizes each model as the number of additional variables increases, and models with lower values of AIC are therefore considered to provide a better fit to the data. These results suggest that including both the abnormal MR imaging signal length and the median motor latency provides better explanatory power for 1-year outcome than a model that includes only one variable or the other. Furthermore, these results suggest that both the abnormal MR imaging signal length and the median motor latency could be useful measures for predicting who would benefit from a surgical intervention.

After controlling for predictors of surgery, the median nerve sensory latency and median–ulnar nerve sensory latency difference were not predictors of outcome. Nor were the interactions between surgery and these sensory latency variables predictive of surgical benefit.

Discussion

Our study demonstrates that both EDSs and MR imaging can predict which patients will benefit from surgical intervention. Better functional status after surgery was predicted by greater length of abnormal signal within the median nerve and bowing of the flexor retinaculum. The longer the median motor latency and the smaller the median motor amplitude (both indicating worse median motor function), the greater the benefit of surgery.

Our results, although in agreement with some previous studies, are at odds with the paper by Radack et al.,47 who did not find that nerve signal intensity on MR imaging was an accurate finding for CTS. We can speculate that a number of factors might be responsible for this discrepancy. First, the degree of high nerve signal is often difficult to assess because it is subjective and influenced by a number of factors, including the precise imaging parameters chosen (repetition time and echo time), artifacts, and shading of the image due to surface coil effects. In contrast, the length of high nerve signal is in many respects more straightforward to assess and might in the long run be a better parameter for assessment of abnormality. In addition, the length of nerve that demonstrates high signal on STIR images, a presumptive measure of the intraneural edema “burden,” may be more important than the brightness of any given segment of the nerve.

There is still debate regarding the sensitivity and specificity of EDSs. In a population-based study, Atroshi et al.4 found that EDSs had a sensitivity of only 70% among patients who had clinically certain CTS. Two other studies reported sensitivities of 745 and 78%.18 This is in contrast to a sensitivity of > 85% described in a widely accepted EDS practice parameter.3 In their 2003 article, Atroshi et al. also reported a poorer specificity of the EDS results (82%) than had been included in the previously mentioned consensus statement. Others have previously published similarly low estimates of specificity.8,16,22 In addition, EDSs are uncomfortable, and according to our data are less well accepted than MR imaging.

Our study is simply a first step. Although we have now shown that MR imaging has the potential to predict surgical benefit in some patients, we have not shown that it is equivalent to EDSs.

The major strength of our study design was that we guarded against the biases that commonly occur with the evaluation of diagnostic technologies. By recruiting only patients referred for nerve conduction studies, we assured that our cohort consisted of the clinically relevant spectrum of patients. Because the interpretations of both the MR images and EDSs occurred before the assessment of outcomes, we avoided test-review and diagnosis-review bias.

A major limitation of our study is that participants were not randomly assigned to treatment, so the ability of MR imaging and EDSs to predict outcome could be confounded by treatment type (surgical compared with nonsurgical) as well as other factors that might be related to treatment selection. We tried to address this by controlling for treatment, but the ability of any retrospective study to control for other factors is always limited. One example of this may have been the unexpected finding that patients with a positive Phalen test were less likely to undergo surgery. This may be due to confounding by unmeasured factors, or it may simply reflect the fact that our surgeons do not rely on the Phalen test for their surgical decision making. In our study the Phalen test was administered by our trained occupational nurse specialist. We do not know how often clinicians performed the Phalen test or what the results were outside of the study setting. We are currently conducting a randomized controlled trial that will address these limitations more definitively.36

Another limitation of our study was the relatively small sample size. Although only 30 patients had surgery, we were nevertheless able to demonstrate that both MR imaging and nerve conduction studies identified which subjects benefited from surgery. Due to small numbers, however, we were not able to explore in depth the ability of other variables to predict surgical benefit.

There are advantages and disadvantages to both EDSs and MR imaging, and they may turn out to be complementary examinations, perhaps being performed sequentially in case the first test is ambiguous. When a new diagnostic test is added to the work-up of a condition, costs frequently increase. Although a formal cost-effectiveness analysis is beyond the scope of this report, the range of Medicare reimbursement (both professional and technical components) for wrist MR imaging for CPT 73221 (the code used for MR of the median nerve at the carpal tunnel), depending on the carrier/locality, is $296.52–$603.98 with the average carrier paying $417.48. The cost of an EDS is more complex, because multiple nerve tests are usually performed in a single session. The American Association of Electrodiagnostic Medicine has issued recommendations regarding the reasonable maximum number of studies to charge for the evaluation of CTS: 3 motor (CPT 95900), 4 sensory (CPT 95904), and 1 electromyography study (CPT 95860). The range of Medicare reimbursement (both professional and technical components) for this reasonable maximum battery of tests is $365.13–$668.30, with the average carrier paying $483.53. It must be emphasized that the EDS gives information in addition to that for the median nerve, and it can help exclude other conditions in the differential diagnosis, such as diffuse peripheral neuropathies. The onus is on investigators to demonstrate that if there are added costs due to MR imaging, there is added value as well. Demonstrating that outcomes would be favorably altered by a diagnostic test is difficult, but it is increasingly recognized as a necessary step in the dissemination of new technology.

Patients appear to have a clear preference for MR imaging over EDSs. Although patient preference should not outweigh the importance of useful diagnostic information, if MR imaging proves its clinical worth in subsequent studies, patient preference is an important factor that can help to decide which diagnostic test to order, and potentially represents added value.

Similar to 2 other studies, we found a poor correlation between symptom and function severity and the use of EDSs.35,50 We found a similarly poor correlation of MR imaging results with symptom and function severity. The lack of correlation with symptoms at baseline emphasizes that EDSs and MR images are measuring something different from patient symptoms.

Our data indicate that EDSs and MR imaging are independent predictors of outcome in patients with CTS, although a major caveat is that our study did not randomly assign treatment. It remains to be seen in larger, randomized studies what combination of EDSs, MR imaging, and symptoms is the most cost-effective way to triage patients with CTS.

Conclusions

Both MR imaging and nerve conduction studies predicted which patients benefited from surgery based on 1-year outcomes. The length of the abnormal T2 nerve signal on MR imaging and the median–ulnar nerve sensory latency difference were the strongest predictors that patients would do better with surgery than without. There was a clear patient preference for MR imaging over EDSs. The ability of MR imaging findings in the carpal tunnel to predict outcome independently compared with nerve conduction studies indicates that MR imaging could supplement or even substitute for EDSs.

Disclosure

Dr. Jarvik is a stockholder and consultant for Nevro, a company that develops software for the analysis of MR images of peripheral nerves.

Acknowledgments

We thank Stanley Cheng, M.D., Lawrence Robinson, M.D., and Cynthia Bradley, M.S., M.P.H., for their contributions to data collection and analysis. We also acknowledge Terri Smith-Weller, R.N., for her excellent efforts at coordinating this study as well as Rae Wu for her help with the statistical analysis.

References

  • 1

    Akaike H: A new look at the statistical model identification. IEEE Trans Automat Contr 19:7167231974

  • 2

    al-Qattan MMBowen VManktelow RT: Factors associated with poor outcome following primary carpal tunnel release in non-diabetic patients. J Hand Surg [Br] 19:6226251994

  • 3

    American Association of Electrodiagnostic Medicine: American Academy of Neurology: American Academy of Physical Medicine and Rehabilitation: Practice parameter for electrodiagnostic studies in carpal tunnel syndrome: summary statement. Muscle Nerve 25:9189222002

  • 4

    Atroshi IGummesson CJohnsson ROrnstein E: Diagnostic properties of nerve conduction tests in population-based carpal tunnel syndrome. BMC Musculoskelet Disord 4:92003

  • 5

    Atroshi IJohnsson R: Evaluation of portable nerve conduction testing in the diagnosis of carpal tunnel syndrome. J Hand Surg [Am] 21:6516541996

  • 6

    Atroshi IJohnsson ROrnstein E: Patient satisfaction and return to work after endoscopic carpal tunnel surgery. J Hand Surg [Am] 23:58651998

  • 7

    Beekman RVisser LH: Sonography in the diagnosis of carpal tunnel syndrome: a critical review of the literature. Muscle Nerve 27:26332003

  • 8

    Bingham RCRosecrance JCCook TM: Prevalence of abnormal median nerve conduction in applicants for industrial jobs. Am J Ind Med 30:3553611996

  • 9

    Bland JD: Do nerve conduction studies predict the outcome of carpal tunnel decompression?. Muscle Nerve 24:9359402001

  • 10

    Britz GWHaynor DRKuntz CGoodkin RGitter AKliot M: Carpal tunnel syndrome: correlation of magnetic resonance imaging, clinical, electrodiagnostic, and intraoperative findings. Neurosurgery 37:109711031995

  • 11

    Britz GWHaynor DRKuntz CGoodkin RGitter AMaravilla K: Ulnar nerve entrapment at the elbow: correlation of magnetic resonance imaging, clinical, electrodiagnostic, and intraoperative findings. Neurosurgery 38:4584651996

  • 12

    Buchberger WJudmaier WBirbamer GLener MSchmidauer C: Carpal tunnel syndrome: diagnosis with high-resolution sonography. AJR Am J Roentgenol 159:7937981992

  • 13

    Dennerlein JTSoumekh FSFossel AHAmick BC IIIKeller RBKatz JN: Longer distal motor latency predicts better outcomes of carpal tunnel release. J Occup Environ Med 44:1761832002

  • 14

    Deryani EAki SMuslumanoglu LRozanes I: MR imaging and electrophysiological evaluation in carpal tunnel syndrome. Yonsei Med J 44:27322003

  • 15

    Erel EDilley AGreening JMorris VCohen BLynn B: Longitudinal sliding of the median nerve in patients with carpal tunnel syndrome. J Hand Surg [Br] 28:4394432003

  • 16

    Ferry SSilman AJPritchard TKeenan JCroft P: The association between different patterns of hand symptoms and objective evidence of median nerve compression: a community-based survey. Arthritis Rheum 41:7207241998

  • 17

    Filler AGKliot MHowe FAHayes CESaunders DEGoodkin R: Application of magnetic resonance neurography in the evaluation of patients with peripheral nerve pathology. J Neurosurg 85:2993091996

  • 18

    Finsen VRusswurm H: Neurophysiology not required before surgery for typical carpal tunnel syndrome. J Hand Surg [Br] 26:61642001

  • 19

    Gerritsen AKorthals-de Bos IBLaboyrie PMde Vet HCScholten RJBouter LM: Splinting for carpal tunnel syndrome: prognostic indicators of success. J Neurol Neurosurg Psychiatry 74:134213442003

  • 20

    Gerritsen AAScholten RJAssendelft WJKuiper Hde Vet HCBouter LM: Splinting or surgery for carpal tunnel syndrome? Design of a randomized controlled trial. BMC Neurol 1:82001

  • 21

    Higgs PEEdwards DFMartin DSWeeks PM: Relation of pre-operative nerve-conduction values to outcome in workers with surgically treated carpal tunnel syndrome. J Hand Surg [Am] 22:2162211997

  • 22

    Homan MMFranzblau AWerner RAAlbers JWArmstrong TJBromberg MB: Agreement between symptom surveys, physical examination procedures and electrodiagnostic findings for the carpal tunnel syndrome. Scand J Work Environ Health 25:1151241999

  • 23

    Horch REAllmann KHLaubenberger JLanger MStark GB: Median nerve compression can be detected by magnetic resonance imaging of the carpal tunnel. Neurosurgery 41:76831997

  • 24

    Jablecki CKAndary MTSo YTWilkins DEWilliams FH: Literature review of the usefulness of nerve conduction studies and electromyography for the evaluation of patients with carpal tunnel syndrome. AAEM Quality Assurance Committee. Muscle Nerve 16:139214141993

  • 25

    Jarvik JGYuen EHaynor DRBradley CMFulton-Kehoe DSmith-Weller T: MR nerve imaging in a prospective cohort of patients with suspected carpal tunnel syndrome. Neurology 58:159716022002

  • 26

    Katz JNStirrat CR: A self-administered hand diagram for the diagnosis of carpal tunnel syndrome. J Hand Surg [Am] 15:3603631990

  • 27

    Keberle MJenett MKenn WReiners KPeter MHaerten R: Technical advances in ultrasound and MR imaging of carpal tunnel syndrome. Eur Radiol 10:104310502000

  • 28

    Kele HVerheggen RBittermann HJReimers CD: The potential value of ultrasonography in the evaluation of carpal tunnel syndrome. Neurology 61:3893912003

  • 29

    Kleindienst AHamm BHildebrandt GKlug N: Diagnosis and staging of carpal tunnel syndrome: comparison of magnetic resonance imaging and intra-operative findings. Acta Neurochir (Wien) 138:2282331996

  • 30

    Kleindienst AHamm BLanksch WR: Carpal tunnel syndrome: staging of median nerve compression by MR imaging. J Magn Reson Imaging 8:111911251998

  • 31

    Kouyoumdjian JAMorita MPMolina AFZanetta DMSato AKRocha CE: Long-term outcomes of symptomatic electrodiagnosed carpal tunnel syndrome. Arq Neuropsiquiatr 61:1941982003

  • 32

    Lee Dvan Holsbeeck MTJanevski PKGanos DLDitmars DMDarian VB: Diagnosis of carpal tunnel syndrome. Ultrasound versus electromyography. Radiol Clin North Am 37:8598721999

  • 33

    Leonard LRangan ADoyle GTaylor G: Carpal tunnel syndrome—is high-frequency ultrasound a useful diagnostic tool?. J Hand Surg [Br] 28:77792003

  • 34

    Levine DWSimmons BPKoris MJDaltroy LHHohl GGFossel AH: A self-administered questionnaire for the assessment of severity of symptoms and functional status in carpal tunnel syndrome. J Bone Joint Surg Am 75:158515921993

  • 35

    Longstaff LMilner RHO'Sullivan SFawcett P: Carpal tunnel syndrome: the correlation between outcome, symptoms and nerve conduction study findings. J Hand Surg [Br] 26:4754802001

  • 36

    Martin BILevenson LMHollingworth WKliot MHeagerty PJTurner JA: Randomized clinical trial of surgery versus conservative therapy for carpal tunnel syndrome. BMC Musculoskelet Disord 6:22005

  • 37

    Mesgarzadeh MSchneck CDBonakdarpour A: Carpal tunnel: MR imaging. Part I. normal anatomy. Radiology 171:7437481989

  • 38

    Mickey RMGreenland S: The impact of confounder selection criteria on effect estimation. Am J Epidemiol 129:1251371989

  • 39

    Middleton WDKneeland JBKellman GMCates JDSanger JRJesmanowicz A: MR imaging of the carpal tunnel: normal anatomy and preliminary findings in the carpal tunnel syndrome. AJR Am J Roentgenol 148:3073161987

  • 40

    Monagle KDai GChu ABurnham RSSnyder RE: Quantitative MR imaging of carpal tunnel syndrome. AJR Am J Roentgenol 172:158115861999

  • 41

    Murphy RX JrChernofsky MAOsborne MAWolson AH: Magnetic resonance imaging in the evaluation of persistent carpal tunnel syndrome. J Hand Surg [Am] 18:1131201993

  • 42

    Musluoglu LCelik MTabak HForta H: Clinical, electrophysiological and magnetic resonance imaging findings in carpal tunnel syndrome. Electromyogr Clin Neurophysiol 44:1611652004

  • 43

    Oneson SRScales LMErickson SJTimins ME: MR imaging of the painful wrist. Radiographics 16:99710081996

  • 44

    Pierre-Jerome CBekkelund SIHusby GMellgren SIOsteaux MNordstrom R: MRI of anatomical variants of the wrist in women. Surg Radiol Anat 18:37411996

  • 45

    Pierre-Jerome CBekkelund SIMellgren SINordstrom R: Quantitative MRI and electrophysiology of preoperative carpal tunnel syndrome in a female population. Ergonomics 40:6426491997

  • 46

    Priganc VWHenry SM: The relationship among five common carpal tunnel syndrome tests and the severity of carpal tunnel syndrome. J Hand Ther 16:2252362003

  • 47

    Radack DMSchweitzer METaras J: Carpal tunnel syndrome: are the MR findings a result of population selection bias?. AJR Am J Roentgenol 169:164916531997

  • 48

    Rempel DEvanoff BAmadio PCde Krom MFranklin GFranzblau A: Consensus criteria for the classification of carpal tunnel syndrome in epidemiologic studies. Am J Public Health 88:144714511998

  • 49

    Sarria LCabada TCozcolluela RMartinez-Berganza TGarcia S: Carpal tunnel syndrome: usefulness of sonography. Eur Radiol 10:192019252000

  • 50

    Schrijver HMGerritsen AAStrijers RLUitdehaag BMScholten RJde Vet HC: Correlating nerve conduction studies and clinical outcome measures on carpal tunnel syndrome: lessons from a randomized controlled trial. J Clin Neurophysiol 22:2162212005

  • 51

    Soccetti ARaffaelli PGiovagnoni AErcolani PMercante OPelliccioni G: MR imaging in the diagnosis of carpal tunnel syndrome. Ital J Orthop Traumatol 18:1231271992

  • 52

    Swen WAJacobs JWBussemaker FEde Waard JWBijlsma JW: Carpal tunnel sonography by the rheumatologist versus nerve conduction study by the neurologist. J Rheumatol 28:62692001

  • 53

    Timins MEO'Connell SEErickson SJOneson SR: MR imaging of the wrist: normal findings that may simulate disease. Radiographics 16:9879951996

  • 54

    Ware JE JrKosinski MKeller SD: SF-12: How to Score the SF-12 Physical and Mental Health Summary Scales ed 2BostonHealth Institute, New England Medical Center1995

  • 55

    Ware J JrKosinski MKeller SD: A 12-item short-form health survey. Med Care 34:2202331996

  • 56

    West GAHaynor DRGoodkin RTsuruda JSBronstein ADKraft G: Magnetic resonance imaging signal changes in denervated muscles after peripheral nerve injury. Neurosurgery 35:107710861994

  • 57

    Yoshioka SOkuda YTamai KHirasawa YKoda Y: Changes in carpal tunnel shape during wrist joint motion. MRI evaluation of normal volunteers. J Hand Surg [Br] 18:6206231993

  • 58

    Yu GZFirrell JCTsai TM: Pre-operative factors and treatment outcome following carpal tunnel release. J Hand Surg [Br] 17:6466501992

  • 59

    Zeiss JSkie MEbraheim NJackson WT: Anatomic relations between the median nerve and flexor tendons in the carpal tunnel: MR evaluation in normal volunteers. AJR Am J Roentgenol 153:5335361989

Supported by the Royalty Research Fund, University of Washington, and in part by Grant #P60-AR48093-01 from National Institute for Arthritis and Musculoskeletal and Skin Diseases: Principal Investigator of Project 1—Jeffrey G. Jarvik, M.D., M.P.H.

Article Information

Address correspondence to: Jeffrey G. Jarvik, M.D., M.P.H., Department of Radiology, Box 357115, University of Washington, 1959 NE Pacific, Seattle, Washington 98195. email: jarvikj@u.washington.edu.

© AANS, except where prohibited by US copyright law.

Headings

Figures

  • View in gallery

    A and B: Two examples of normal-appearing median nerves demonstrated on STIR images. The median nerves (arrows) are nearly isointense with muscle (asterisks). C: An MR image with a line drawn from the tip of the hook of the hamate (h) to the region of the trapezial tubercle (t) shows no bowing (perpendicular line < 3 mm) of the flexor retinaculum, in contrast to the line in Fig. 2C.

  • View in gallery

    A: A STIR image depicting a markedly hyperintense median nerve (arrow). B: A STIR image showing a severely flattened median nerve (arrows) at the level of the hook of the hamate. C: A T1-weighted MR image demonstrating bowing of the hypointense flexor retinaculum (arrows). A line is drawn from the tip of the hamate hook to the trapezial tubercle, with a perpendicular line demonstrating how measurements of the flexor retinaculum were performed. D: A STIR image showing high signal and thickening of the flexor tendon interspace and deep palmar bursa (large arrows). The small arrows point to an enlarged and high-signal median nerve with a prominent and irregular fascicular pattern. E: A STIR image obtained in a different patient also shows high-signal median nerve with a prominent and irregular fascicular pattern (arrows).

References

1

Akaike H: A new look at the statistical model identification. IEEE Trans Automat Contr 19:7167231974

2

al-Qattan MMBowen VManktelow RT: Factors associated with poor outcome following primary carpal tunnel release in non-diabetic patients. J Hand Surg [Br] 19:6226251994

3

American Association of Electrodiagnostic Medicine: American Academy of Neurology: American Academy of Physical Medicine and Rehabilitation: Practice parameter for electrodiagnostic studies in carpal tunnel syndrome: summary statement. Muscle Nerve 25:9189222002

4

Atroshi IGummesson CJohnsson ROrnstein E: Diagnostic properties of nerve conduction tests in population-based carpal tunnel syndrome. BMC Musculoskelet Disord 4:92003

5

Atroshi IJohnsson R: Evaluation of portable nerve conduction testing in the diagnosis of carpal tunnel syndrome. J Hand Surg [Am] 21:6516541996

6

Atroshi IJohnsson ROrnstein E: Patient satisfaction and return to work after endoscopic carpal tunnel surgery. J Hand Surg [Am] 23:58651998

7

Beekman RVisser LH: Sonography in the diagnosis of carpal tunnel syndrome: a critical review of the literature. Muscle Nerve 27:26332003

8

Bingham RCRosecrance JCCook TM: Prevalence of abnormal median nerve conduction in applicants for industrial jobs. Am J Ind Med 30:3553611996

9

Bland JD: Do nerve conduction studies predict the outcome of carpal tunnel decompression?. Muscle Nerve 24:9359402001

10

Britz GWHaynor DRKuntz CGoodkin RGitter AKliot M: Carpal tunnel syndrome: correlation of magnetic resonance imaging, clinical, electrodiagnostic, and intraoperative findings. Neurosurgery 37:109711031995

11

Britz GWHaynor DRKuntz CGoodkin RGitter AMaravilla K: Ulnar nerve entrapment at the elbow: correlation of magnetic resonance imaging, clinical, electrodiagnostic, and intraoperative findings. Neurosurgery 38:4584651996

12

Buchberger WJudmaier WBirbamer GLener MSchmidauer C: Carpal tunnel syndrome: diagnosis with high-resolution sonography. AJR Am J Roentgenol 159:7937981992

13

Dennerlein JTSoumekh FSFossel AHAmick BC IIIKeller RBKatz JN: Longer distal motor latency predicts better outcomes of carpal tunnel release. J Occup Environ Med 44:1761832002

14

Deryani EAki SMuslumanoglu LRozanes I: MR imaging and electrophysiological evaluation in carpal tunnel syndrome. Yonsei Med J 44:27322003

15

Erel EDilley AGreening JMorris VCohen BLynn B: Longitudinal sliding of the median nerve in patients with carpal tunnel syndrome. J Hand Surg [Br] 28:4394432003

16

Ferry SSilman AJPritchard TKeenan JCroft P: The association between different patterns of hand symptoms and objective evidence of median nerve compression: a community-based survey. Arthritis Rheum 41:7207241998

17

Filler AGKliot MHowe FAHayes CESaunders DEGoodkin R: Application of magnetic resonance neurography in the evaluation of patients with peripheral nerve pathology. J Neurosurg 85:2993091996

18

Finsen VRusswurm H: Neurophysiology not required before surgery for typical carpal tunnel syndrome. J Hand Surg [Br] 26:61642001

19

Gerritsen AKorthals-de Bos IBLaboyrie PMde Vet HCScholten RJBouter LM: Splinting for carpal tunnel syndrome: prognostic indicators of success. J Neurol Neurosurg Psychiatry 74:134213442003

20

Gerritsen AAScholten RJAssendelft WJKuiper Hde Vet HCBouter LM: Splinting or surgery for carpal tunnel syndrome? Design of a randomized controlled trial. BMC Neurol 1:82001

21

Higgs PEEdwards DFMartin DSWeeks PM: Relation of pre-operative nerve-conduction values to outcome in workers with surgically treated carpal tunnel syndrome. J Hand Surg [Am] 22:2162211997

22

Homan MMFranzblau AWerner RAAlbers JWArmstrong TJBromberg MB: Agreement between symptom surveys, physical examination procedures and electrodiagnostic findings for the carpal tunnel syndrome. Scand J Work Environ Health 25:1151241999

23

Horch REAllmann KHLaubenberger JLanger MStark GB: Median nerve compression can be detected by magnetic resonance imaging of the carpal tunnel. Neurosurgery 41:76831997

24

Jablecki CKAndary MTSo YTWilkins DEWilliams FH: Literature review of the usefulness of nerve conduction studies and electromyography for the evaluation of patients with carpal tunnel syndrome. AAEM Quality Assurance Committee. Muscle Nerve 16:139214141993

25

Jarvik JGYuen EHaynor DRBradley CMFulton-Kehoe DSmith-Weller T: MR nerve imaging in a prospective cohort of patients with suspected carpal tunnel syndrome. Neurology 58:159716022002

26

Katz JNStirrat CR: A self-administered hand diagram for the diagnosis of carpal tunnel syndrome. J Hand Surg [Am] 15:3603631990

27

Keberle MJenett MKenn WReiners KPeter MHaerten R: Technical advances in ultrasound and MR imaging of carpal tunnel syndrome. Eur Radiol 10:104310502000

28

Kele HVerheggen RBittermann HJReimers CD: The potential value of ultrasonography in the evaluation of carpal tunnel syndrome. Neurology 61:3893912003

29

Kleindienst AHamm BHildebrandt GKlug N: Diagnosis and staging of carpal tunnel syndrome: comparison of magnetic resonance imaging and intra-operative findings. Acta Neurochir (Wien) 138:2282331996

30

Kleindienst AHamm BLanksch WR: Carpal tunnel syndrome: staging of median nerve compression by MR imaging. J Magn Reson Imaging 8:111911251998

31

Kouyoumdjian JAMorita MPMolina AFZanetta DMSato AKRocha CE: Long-term outcomes of symptomatic electrodiagnosed carpal tunnel syndrome. Arq Neuropsiquiatr 61:1941982003

32

Lee Dvan Holsbeeck MTJanevski PKGanos DLDitmars DMDarian VB: Diagnosis of carpal tunnel syndrome. Ultrasound versus electromyography. Radiol Clin North Am 37:8598721999

33

Leonard LRangan ADoyle GTaylor G: Carpal tunnel syndrome—is high-frequency ultrasound a useful diagnostic tool?. J Hand Surg [Br] 28:77792003

34

Levine DWSimmons BPKoris MJDaltroy LHHohl GGFossel AH: A self-administered questionnaire for the assessment of severity of symptoms and functional status in carpal tunnel syndrome. J Bone Joint Surg Am 75:158515921993

35

Longstaff LMilner RHO'Sullivan SFawcett P: Carpal tunnel syndrome: the correlation between outcome, symptoms and nerve conduction study findings. J Hand Surg [Br] 26:4754802001

36

Martin BILevenson LMHollingworth WKliot MHeagerty PJTurner JA: Randomized clinical trial of surgery versus conservative therapy for carpal tunnel syndrome. BMC Musculoskelet Disord 6:22005

37

Mesgarzadeh MSchneck CDBonakdarpour A: Carpal tunnel: MR imaging. Part I. normal anatomy. Radiology 171:7437481989

38

Mickey RMGreenland S: The impact of confounder selection criteria on effect estimation. Am J Epidemiol 129:1251371989

39

Middleton WDKneeland JBKellman GMCates JDSanger JRJesmanowicz A: MR imaging of the carpal tunnel: normal anatomy and preliminary findings in the carpal tunnel syndrome. AJR Am J Roentgenol 148:3073161987

40

Monagle KDai GChu ABurnham RSSnyder RE: Quantitative MR imaging of carpal tunnel syndrome. AJR Am J Roentgenol 172:158115861999

41

Murphy RX JrChernofsky MAOsborne MAWolson AH: Magnetic resonance imaging in the evaluation of persistent carpal tunnel syndrome. J Hand Surg [Am] 18:1131201993

42

Musluoglu LCelik MTabak HForta H: Clinical, electrophysiological and magnetic resonance imaging findings in carpal tunnel syndrome. Electromyogr Clin Neurophysiol 44:1611652004

43

Oneson SRScales LMErickson SJTimins ME: MR imaging of the painful wrist. Radiographics 16:99710081996

44

Pierre-Jerome CBekkelund SIHusby GMellgren SIOsteaux MNordstrom R: MRI of anatomical variants of the wrist in women. Surg Radiol Anat 18:37411996

45

Pierre-Jerome CBekkelund SIMellgren SINordstrom R: Quantitative MRI and electrophysiology of preoperative carpal tunnel syndrome in a female population. Ergonomics 40:6426491997

46

Priganc VWHenry SM: The relationship among five common carpal tunnel syndrome tests and the severity of carpal tunnel syndrome. J Hand Ther 16:2252362003

47

Radack DMSchweitzer METaras J: Carpal tunnel syndrome: are the MR findings a result of population selection bias?. AJR Am J Roentgenol 169:164916531997

48

Rempel DEvanoff BAmadio PCde Krom MFranklin GFranzblau A: Consensus criteria for the classification of carpal tunnel syndrome in epidemiologic studies. Am J Public Health 88:144714511998

49

Sarria LCabada TCozcolluela RMartinez-Berganza TGarcia S: Carpal tunnel syndrome: usefulness of sonography. Eur Radiol 10:192019252000

50

Schrijver HMGerritsen AAStrijers RLUitdehaag BMScholten RJde Vet HC: Correlating nerve conduction studies and clinical outcome measures on carpal tunnel syndrome: lessons from a randomized controlled trial. J Clin Neurophysiol 22:2162212005

51

Soccetti ARaffaelli PGiovagnoni AErcolani PMercante OPelliccioni G: MR imaging in the diagnosis of carpal tunnel syndrome. Ital J Orthop Traumatol 18:1231271992

52

Swen WAJacobs JWBussemaker FEde Waard JWBijlsma JW: Carpal tunnel sonography by the rheumatologist versus nerve conduction study by the neurologist. J Rheumatol 28:62692001

53

Timins MEO'Connell SEErickson SJOneson SR: MR imaging of the wrist: normal findings that may simulate disease. Radiographics 16:9879951996

54

Ware JE JrKosinski MKeller SD: SF-12: How to Score the SF-12 Physical and Mental Health Summary Scales ed 2BostonHealth Institute, New England Medical Center1995

55

Ware J JrKosinski MKeller SD: A 12-item short-form health survey. Med Care 34:2202331996

56

West GAHaynor DRGoodkin RTsuruda JSBronstein ADKraft G: Magnetic resonance imaging signal changes in denervated muscles after peripheral nerve injury. Neurosurgery 35:107710861994

57

Yoshioka SOkuda YTamai KHirasawa YKoda Y: Changes in carpal tunnel shape during wrist joint motion. MRI evaluation of normal volunteers. J Hand Surg [Br] 18:6206231993

58

Yu GZFirrell JCTsai TM: Pre-operative factors and treatment outcome following carpal tunnel release. J Hand Surg [Br] 17:6466501992

59

Zeiss JSkie MEbraheim NJackson WT: Anatomic relations between the median nerve and flexor tendons in the carpal tunnel: MR evaluation in normal volunteers. AJR Am J Roentgenol 153:5335361989

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