Abstract
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.
| Original language | English |
|---|---|
| Pages (from-to) | 1099-1106 |
| Number of pages | 8 |
| Journal | Academic Radiology |
| Volume | 20 |
| Issue number | 9 |
| DOIs | |
| State | Published - Sep 1 2013 |
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Keywords
- Amyotrophic lateral sclerosis
- Diagnostic accuracy
- Diagnostic imaging
- Diffusion tensor imaging
- Magnetic resonance imaging
- Meta-analysis
ASJC Scopus subject areas
- Radiology Nuclear Medicine and imaging
Cite this
Diagnostic accuracy of diffusion tensor imaging in amyotrophic lateral sclerosis : A systematic review and individual patient data meta-analysis. / Foerster, Bradley R.; Dwamena, Ben A.; Petrou, Myria; Carlos, Ruth C.; Callaghan, Brian C.; Churchill, Cristina L.; Mohamed, Mona A.; Bartels, Claudia; Benatar, Michael G; Bonzano, Laura; Ciccarelli, Olga; Cosottini, Mirco; Ellis, Cathy M.; Ehrenreich, Hannelore; Filippini, Nicola; Ito, Mizuki; Kalra, Sanjay; Melhem, Elias R.; Pyra, Timothy; Roccatagliata, Luca; Senda, Joe; Sobue, Gen; Turner, Martin R.; Feldman, Eva L.; Pomper, Martin G.
In: Academic Radiology, Vol. 20, No. 9, 01.09.2013, p. 1099-1106.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Diagnostic accuracy of diffusion tensor imaging in amyotrophic lateral sclerosis
T2 - A systematic review and individual patient data meta-analysis
AU - Foerster, Bradley R.
AU - Dwamena, Ben A.
AU - Petrou, Myria
AU - Carlos, Ruth C.
AU - Callaghan, Brian C.
AU - Churchill, Cristina L.
AU - Mohamed, Mona A.
AU - Bartels, Claudia
AU - Benatar, Michael G
AU - Bonzano, Laura
AU - Ciccarelli, Olga
AU - Cosottini, Mirco
AU - Ellis, Cathy M.
AU - Ehrenreich, Hannelore
AU - Filippini, Nicola
AU - Ito, Mizuki
AU - Kalra, Sanjay
AU - Melhem, Elias R.
AU - Pyra, Timothy
AU - Roccatagliata, Luca
AU - Senda, Joe
AU - Sobue, Gen
AU - Turner, Martin R.
AU - Feldman, Eva L.
AU - Pomper, Martin G.
PY - 2013/9/1
Y1 - 2013/9/1
N2 - 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.
AB - 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.
KW - Amyotrophic lateral sclerosis
KW - Diagnostic accuracy
KW - Diagnostic imaging
KW - Diffusion tensor imaging
KW - Magnetic resonance imaging
KW - Meta-analysis
UR - http://www.scopus.com/inward/record.url?scp=84881325362&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84881325362&partnerID=8YFLogxK
U2 - 10.1016/j.acra.2013.03.017
DO - 10.1016/j.acra.2013.03.017
M3 - Article
C2 - 23931423
AN - SCOPUS:84881325362
VL - 20
SP - 1099
EP - 1106
JO - Academic Radiology
JF - Academic Radiology
SN - 1076-6332
IS - 9
ER -