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Diagnostic Accuracy of Diffusion Tensor Imaging in Amyotrophic Lateral Sclerosis

Rationale and Objectives

There have been a large number of case-control studies using diffusion tensor imaging (DTI) in amyotrophic lateral sclerosis (ALS). The objective of this study was to perform an individual patient data (IPD) meta-analysis for the estimation of the diagnostic accuracy measures of DTI in the diagnosis of ALS using corticospinal tract data.

Materials and Methods

MEDLINE, EMBASE, CINAHL, and Cochrane databases (1966–April 2011) were searched. Studies were included if they used DTI region of interest or tractography techniques to compare mean cerebral corticospinal tract fractional anisotropy values between ALS subjects and healthy controls. Corresponding authors from the identified articles were contacted to collect individual patient data. IPD meta-analysis and meta-regression were performed using Stata. Meta-regression covariate analysis included age, gender, disease duration, and Revised Amyotrophic Lateral Sclerosis Functional Rating Scale scores.

Results

Of 30 identified studies, 11 corresponding authors provided IPD and 221 ALS patients and 187 healthy control subjects were available for study. Pooled area under the receiver operating characteristic curve (AUC) was 0.75 (95% CI: 0.66–0.83), pooled sensitivity was 0.68 (95% CI: 0.62–0.75), and pooled specificity was 0.73 (95% CI: 0.66–0.80). Meta-regression showed no significant differences in pooled AUC for each of the covariates. There was moderate to high heterogeneity of pooled AUC estimates. Study quality was generally high. Data from 19 of the 30 eligible studies were not ascertained, raising possibility of selection bias.

Conclusion

Using corticospinal tract individual patient data, the diagnostic accuracy of DTI appears to lack sufficient discrimination in isolation. Additional research efforts and a multimodal approach that also includes ALS mimics will be required to make neuroimaging a critical component in the workup of ALS.

Amyotrophic lateral sclerosis (ALS) is a fatal degenerative motor neuron disease involving the motor cortex, corticospinal tract (CST), and spinal anterior horn neurons. Clinical presentation of the disease is variable, contributing diagnostic uncertainty and delay . More than 40% of ALS patients undergo inappropriate medical treatment, including surgery . Electromyography can help confirm the diagnosis of lower motor neuron involvement. There is a high interest in developing upper motor neuron diagnostic biomarkers to facilitate an accurate diagnosis at an earlier stage .

A promising biomarker for ALS is diffusion tensor imaging (DTI), an advanced magnetic resonance imaging (MRI) application. Fractional anisotropy (FA), a scalar measurement of water diffusivity, is a key DTI metric. FA reductions have been reported in diseases that degrade white matter tracts, including ALS . Although several studies have reported FA decreases in ALS patients, only a few have addressed test accuracy measures with relative small subject numbers . We have recently completed a group-level meta-analysis of test accuracy measures of DTI for the diagnosis of ALS . However, individual patient data (IPD) meta-analysis approaches are generally considered superior to group-level approaches because more rigorous statistical methods can be employed, including covariate adjustment . Our study objective was to compare ALS patients who underwent DTI to healthy controls to determine diagnostic accuracy measures of FA using IPD meta-analysis techniques.

Methods

Eligibility Criteria

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Selection and Quality Assessment

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Data Extraction and Synthesis

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Retrospective Study

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Statistical Analysis

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Results

Study Selection

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Figure 1, Flowchart illustrating selection of studies. DTI, diffusion tensor imaging; ROI, region of interest.

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Study Characteristics

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Table 1

Individual Study Characteristics

Study Number Author MRI B Value Number of Directions Analysis Method Brain Region Average Disease Duration (months) 1 Bartels 2.9 T 1000 24 ROI-tractography CST ∗ 20 ± 10 2 Ciccarelli 1.5 T 1150 54 Tractography CST 21 ± 16 3 Cosottini 1.5 T 1000 25 ROI-visual CST 33 ± 20 4 Cosottini 1.5 T 1000 31 ROI-visual CST 17 ± 13 5 Ellis 1.5 T 620 7 ROI-visual CST 27 ± 26 6 Filippini 3.0 T 1000 60 Tractography CST ∗ 49 ± 38 7 Foerster 3.0 T 800 15 Tractography CST ∗ 25 ± 15 8 Metwalli 3.0 T 1000 64 ROI-visual IC ∗ , † 26 ± 15 9 Pyra 1.5 T 1000 6 ROI-visual IC ∗ , † 25 ± 17 10 Roccatagliata 1.5 T 1000 51 ROI-visual IC ∗ 12 ± 6 11 Senda 3.0 T 700 6 ROI-tractography IC ∗ 20 ± 9 12 Wang 3.0 T 1000 12 ROI-tractography IC 20 ± 20

CST, average corticospinal tract; IC, internal capsule; MRI, magnetic resonance imaging; ROI, region of interest.

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Meta-Analysis of Sensitivity, Specificity, and AUC

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Figure 2, Area under summary receiver operating characteristic (SROC) curve for diffusion tensor imaging fractional anisotropy values. Each circle represents an individual study result. Dashed circle represents 95% prediction interval of summary sensitivity (SENS) and specificity (SPEC). AUC, area under the curve.

Figure 3, Forest plot of area under the curve (AUC) for amyotrophic lateral sclerosis diagnosis using diffusion tensor imaging fractional anisotropy values.

Figure 4, Forest plots of sensitivity (SENS) (a) and specificity (SPEC) (b) for diagnosis of amyotrophic lateral sclerosis using diffusion tensor imaging fractional anisotropy values.

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AUC Meta-analysis Using Covariates

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Table 2

AUC Measures with Covariates

Age Gender ALSFRS-R Disease Duration Included study numbers ∗ 1, 2, 5–12 1, 2, 5–12 1–4, 6, 7, 9, 10, 12 1, 2, 4, 5, 7, 9, 10, 12 Nonadjusted AUC 0.58 (0.32–0.84) 0.58 (0.32–0.84) 0.65 (0.47–0.84) 0.61 (0.36–0.85) Adjusted AUC 0.58 (0.31–0.85) 0.58 (0.32–0.85) 0.58 (0.40–0.77) 0.61 (0.37–0.86)

ALSFRS-R, Revised Amyotrophic Functional Rating Scale; AUC, area under curve.

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Predictive Values

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Figure 5, Posttest probabilities after diffusion tensor imaging (DTI) for hypothetical populations with different disease pretest probabilities.

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Study Quality, Publication Bias, and Heterogeneity

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Figure 6, Study quality scores. Graph illustrates study quality based on Quality Assessment of Diagnostic Accuracy Studies criteria, expressed as a percent of studies meeting each criterion.

Figure 7, Assessing publication bias. The funnel plot horizontal axis expresses treatment effect; in this instance, measured by area under the receiver operating characteristic curve (AUC). The vertical axis expresses study size, as measured by standard error (SE). Studies with larger standard errors have a wider confidence interval. The graphed vertical line represents the observed mean AUC and the dashed lines represent the 95% confidence limits for the expected distribution for published studies. The points represent the observed distribution of the published studies. Visual inspection demonstrates the presence of publication bias with several of the studies outside the 95% confidence limits. Further, the plot demonstrates that studies with larger standard errors have lower test performance (ie, AUC).

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Discussion

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Acknowledgments

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Appendix

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Table 1

MEDLINE Keyword Search (1966-April 2011)

[amyotrophic lateral sclerosis or Lou Gehrig’s disease to include all subheadings] and [magnetic resonance imaging to include all subheadings] or [diagnostic imaging to include all subheadings] or [diffusion magnetic resonance imaging to include all subheadings] or [diffusion tensor imaging to include all subheadings] or [fractional anisotropy to include all subheadings] or [anisotropy to include all subheadings]

Table 2

Additional Study Information

Study Author Journal Year Number of ALS Patients ALS Age, y (Mean ± SD) Number of HC Subjects HC Age, y (Mean ± SD) 1 Bartels Neuromuscul Disord 2008 12 M:10 F 61 ± 7 5 M:8 F 61 ± 8 2 Ciccarelli Brain 2006 12 M:1 F 54 ± 13 15 M:4 F 39 ± 11 3 Cosottini Radiology 2005 14 M:4 F 64 ± 7 4 M:8 F 65 ± 6 4 Cosottini J Comput Assist Tomogr 2010 14 M:4 F 61 ± 8 2 M:14 F 65 ± 6 5 Ellis Neurology 1999 13 M:7 F 51 ± 11 9 M:11 F 46 ± 13 6 Filippini Neurology 2010 16 M:8 F 59 ± 12 17 M:7 F 58 ± 12 7 Foerster 8 M:6 F 61 ± 9 8 M:6 F 58 ± 6 8 Metwalli Brain Res 2010 10 M:2 F 56 ± 11 11 M:8 F 50 ± 13 9 Pyra Amyotroph Lateral Scler 2010 6 M:8 F 54 ± 15 8 M:6 F 53 ± 12 10. Roccatagliata Amyotroph Lateral Scler 2009 8 M:6 F 63 ± 9 4 M:8 F 61 ± 10 11. Senda Amyotroph Lateral Scler 2009 26 M:20 F 62 ± 10 7 M:12 F 63 ± 9 12. Wang Radiology 2006 12 M:3 F 57 ± 7 5 M:5 F 49 ± 8

ALS, amyotrophic lateral sclerosis; F, female; HC, healthy control; M, male; SD, standard deviation.

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