European radiology · 2016
Substantia nigra fractional anisotropy is not a diagnostic biomarker of Parkinson's disease: A diagnostic performance study and meta-analysis.
СтатьяМетаанализСистематический обзорНазвание и аннотация: Перевод пока не подготовлен
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Hirata Fabiana C C, Sato João R, Vieira Gilson, Lucato Leandro T, Leite Claudia C, Bor-Seng-Shu Edson, Pastorello Bruno F, Otaduy Maria C G, Chaim Khallil T, Campanholo Kenia R, Novaes Natalia P, Melo Luciano Magalhães, Gonçalves Márcia R, do Nascimento Felipe Barjud Pereira, Teixeira Manoel Jacobsen, Barbosa Egberto Reis, Amaro Edson, Cardoso Ellison Fernando
Аннотация
OBJECTIVES: Our goal was to estimate the diagnostic accuracy of substantia nigra fractional anisotropy (SN-FA) for Parkinson's disease (PD) diagnosis in a sample similar to the clinical setting, including patients with essential tremor (ET) and healthy controls (HC). We also performed a systematic review and meta-analysis to estimate mean change in SN-FA induced by PD and its diagnostic accuracy.
METHODS: Our sample consisted of 135 subjects: 72 PD, 21 ET and 42 HC. To address inter-scanner variability, two 3.0-T MRI scans were performed. MRI results of this sample were pooled into a meta-analysis that included 1,432 subjects (806 PD and 626 HC). A bivariate model was used to evaluate diagnostic accuracy measures.
RESULTS: In our sample, we did not observe a significant effect of disease on SN-FA and it was uninformative for diagnosis. The results of the meta-analysis estimated a 0.03 decrease in mean SN-FA in PD relative to HC (CI: 0.01-0.05). However, the discriminatory capability of SN-FA to diagnose PD was low: pooled sensitivity and specificity were 72 % (CI: 68-75) and 63 % (CI: 58-70), respectively. There was high heterogeneity between studies (I2 = 91.9 %).
CONCLUSIONS: SN-FA cannot be used as an isolated measure to diagnose PD.
KEY POINTS: • SN-FA appears insufficiently sensitive and specific to diagnose PD. • Radiologists must be careful when translating mean group results to clinical practice. • Imaging protocol and analysis standardization is necessary for developing reproducible quantitative biomarkers.
METHODS: Our sample consisted of 135 subjects: 72 PD, 21 ET and 42 HC. To address inter-scanner variability, two 3.0-T MRI scans were performed. MRI results of this sample were pooled into a meta-analysis that included 1,432 subjects (806 PD and 626 HC). A bivariate model was used to evaluate diagnostic accuracy measures.
RESULTS: In our sample, we did not observe a significant effect of disease on SN-FA and it was uninformative for diagnosis. The results of the meta-analysis estimated a 0.03 decrease in mean SN-FA in PD relative to HC (CI: 0.01-0.05). However, the discriminatory capability of SN-FA to diagnose PD was low: pooled sensitivity and specificity were 72 % (CI: 68-75) and 63 % (CI: 58-70), respectively. There was high heterogeneity between studies (I2 = 91.9 %).
CONCLUSIONS: SN-FA cannot be used as an isolated measure to diagnose PD.
KEY POINTS: • SN-FA appears insufficiently sensitive and specific to diagnose PD. • Radiologists must be careful when translating mean group results to clinical practice. • Imaging protocol and analysis standardization is necessary for developing reproducible quantitative biomarkers.