Prediction of motor recovery after ischemic stroke using diffusion tensor imaging: A meta-analysis

doi:10.5847/wjem.j.1920-8642.2017.02.003

Abstract

Abstract:

BACKGROUND: This systematic review aims to investigate the prediction value of diffusion tensor imaging for motor function recovery of ischemic stroke patients.

METHODS: Cochrane Central Register of Controlled Trials (CENTRAL) (the Cochrane Library 2016, Issue 9), PubMed, Embase, Clarivate Analytics, Scopus, CINAHL, Chinese Biomedical Literature Database, China National Knowledge Infrastructure and Google Scholar were searched for either motor recovery or corticospinal tract integrity by diffusion tensor imaging in different stroke phase from January 1, 1970, to October 31, 2016. The study design and participants were subjected to metrological analysis. Correlation coefficient (r) was used for evaluating the relationship between fractional anisotropy (FA) and motor function outcome. Correlation coefficient values were extracted from each study, and 95% confidence intervals (CIs) were calculated by Fisher's z transformation. Meta-analysis was conducted by STATA software.

RESULTS: Fifteen studies with a total of 414 patients were included. Meta-analysis showed that FA in the subacute phase had the significant correlation with motor function outcome (ES=0.75, 95%CI 0.62-0.87), which showed moderate quality based on GRADE system. The weight correlation coefficient revealed that an effect size (ES) of FA in acute phase and chronic phase was 0.51 (95%CI 0.33-0.68) and 0.62 (95%CI 0.47-0.77) respectively.

CONCLUSION: This meta-analysis reveals that FA in the subacute phase after ischemic stroke is a good predictor for functional motor recovery, which shows moderate quality based on the GRADE system.

Key words: Diffusion tensor imaging, Motor function recovery, Ischemic stroke

Jing-fen Jin, Zhi-ting Guo, Yu-ping Zhang, Yuan-yuan Chen. Prediction of motor recovery after ischemic stroke using diffusion tensor imaging: A meta-analysis[J]. World Journal of Emergency Medicine, 2017, 8(2): 99-105.

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Authors & year	Country	Number of patients	Time of inclusion	Lesion location	Age (Mean±SD)	Gender (male/female)	Time of DTI after stroke	DTI parameter	Measurement of outcome	Follow up
Vargas^[5] 2013	France	18	3 w	C/SC/CSC	58	6/12	3 w/3m	FA/MD	m-NIHSS/mRS	3 w/3 m
Groisser^[14] 2014	USA	10	3-7 d	MCA/CR/IC	52.6	5/5	1-2 m	FA	Grip/MI/NHPT	6-7 m
Puig^[15] 2011	Canada	60	12 h	IC	67.9	37/23	30 d	FA	m-NIHSS	90 d
Chen^[17] 2013	USA	11	4-26 m	MCA	57.5	8/3	4-26 m	FA	UE-FM	4-26 m
Chen^[20] 2013	China	42	20 h-7d	MCA	57.17±14.48	31/11	<3 d	FA	MRC/BI	15 d
Yu^[23] 2009	China	9	<7 d	IC/CR/BG	48±5	9/0	<2 w	FA	MI/NIHSS	1 y
Koyam^[24] 2014	Japan	16	14-18 d	MCA	67.9	11/5	>3 m	FA	BRS/FIM	>3 m
Song^[25] 2012	China	10	3 m	IC/BG	59.7	8/2	3 m	FA	NIHSS/FMA	3 m
Yang^[26] 2015	China	40	<3 d	IC/CR/BG	60.28±14.3	30/10	<3 d/2 m/3 m	FA	NIHSS	<3 d/2 m/3 m
Radlinska^[27] 2010	Canada	13	12 d	PT	80.5	5/13	12 d	FA	NIHSS/RMFT	12 d/180 d
Puig^[28] 2010	Canada	60	12 h	MCA	67.9	37/23	30 d	FA	NIHSS/m-NIHSS	30 d
Liu^[29] 2012	China	8	3-21 d	CST	50±10	7/1	8 m	FA/ADC	BC	8 m
Liang^[30] 2008	China	14	<7 d	PB	58.9	8/6	12 w	FA	NIHSS/FMA/BI	12 w
Jang^[31] 2014	Korea	82	>3 m	CST	53.2±11.7	54/28	>3 m	FA/FN	MRC/MBC/FAC	>3 m
Ali^[32] 2012	Egypt	21	0.8-3 d	CR/IC/T	54.8	14/7	0.8-3 d	FA	NIHSS	15-30 d

Items	Ali 2012	Chen 2013	Groisser 2014	Jang 2014	Liu 2012	Koyama 2014	Radlinska 2010	Song 2012	Puig 2011	Yu 2009	Puig 2010	Yang 2015	Chen 2015	Vargas 2013	Liang 2008
1 Was study based on a random or pseudo-random sample?	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
2 Were the criteria for inclusion in the sample clearly defined?	Y	Y	Y	Y	Y	Y	Y	Y	Y	Y	Y	Y	Y	Y	Y
3 Were confounding factors identified and strategies to deal with them stated?	Y	Y	Y	Y	Y	Y	Y	Y	Y	Y	Y	UC	Y	Y	Y
4 Were outcomes assessed using objective criteria?	Y	Y	Y	Y	Y	Y	Y	Y	Y	Y	Y	Y	Y	Y	Y
5 If comparisons are being made, was there sufficient descriptions of the groups?	Y	Y	Y	Y	Y	Y	Y	Y	Y	Y	Y	Y	Y	Y	Y
6 Was follow up carried out over a sufficient time period?	N	Y	Y	Y	Y	Y	Y	Y	Y	Y	N	Y	N	Y	Y
7 Were the outcomes of people who withdrew described and included in the analysis?	Y	Y	Y	Y	Y	Y	Y	Y	Y	Y	Y	Y	Y	Y	Y
8 Were outcomes measured in a reliable way?	Y	Y	Y	Y	Y	Y	Y	Y	Y	Y	Y	Y	Y	Y	Y
9 Was appropriate statistical analysis used?	Y	Y	Y	Y	Y	Y	Y	Y	Y	Y	Y	Y	Y	Y	Y
Total level	B	A	A	A	A	A	A	A	A	A	B	B	B	A	A

Participants (studies) Risk of bias Inconsistency Indirectness Imprecision Publication bias						Effect Size (95%CI) Overall quality of evidence
Acute phase prediction motor function
103 (3 studies)	No serious risk of bias	No serious inconsistency	No serious indirectness	No serious imprecision	Likely	0.51 (0.33,0.68)	Very low, due to likely bias and plausible confounding that would change the effect
Subacute phase prediction motor function
210 (7 studies)	No serious risk of bias	No serious inconsistency	No serious indirectness	No serious imprecision	Undetected	0.75 (0.62, 0.87)	Moderate, due to large effect, plausible confounding that would change the effect
Chronic phase prediction motor function
199 (8 studies)	No serious risk of bias	No serious inconsistency	No serious indirectness	No serious imprecision	Undetected	0.62 (0.47, 0.77)	Low, due to plausible confounding that would change the effect

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