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Article Dans Une Revue Neuropsychobiology Année : 2020

A Brain Imaging-Based Diagnostic Biomarker for Periodic Catatonia: Preliminary Evidence Using a Bayesian Approach.

Résumé

Periodic catatonia (PC) is a psychomotor phenotype with a progressive-remitting course. While it can fit any disorder diagnosis of the schizoaffective spectrum, its core features consist of a mix of hypo- and hyperkinesias resulting in distortions of expressive movements such as grimacing and parakinesias. The replication of cerebral blood flow (CBF) increases in the left supplementary motor area (L-SMA) and lateral premotor cortex (L-LPM) in acute and remitting PC patients indicates that these increases could be used as diagnostic biomarkers. In this proof-of-concept study, 2 different MRI sequences were repeated on 3 separate days to get reliable measurement values of CBF in 9 PC and 26 non-PC patients during different cognitive tasks. Each patient was compared to 37 controls. In L-SMA [–9; +10; +60] and L-LPM [–46; –12; +43], a test was positive if the t value was >2.02 (α < 0.05; two tailed). The measurements had good analytical performance. Regarding the tests, their sensitivities and specificities were significantly different from the chance level on both measures, except for L-SMA sensitivities. When combining all the tests, among regions and methods, sensitivity was 98% (95% credible interval [CI] 76–100%) and specificity 88% (72–97%). Bayesian inferences of its negative predictive values for PC were >95% regardless of the context, while its positive predictive values reached 94% but only when used in combination with clinical criteria. The case-by-case analysis suggests that non-PC patients with neurological motor deficits are at risk to be false positive.
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Dates et versions

hal-03700154 , version 1 (20-06-2022)

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Citer

Jack Foucher, Clément de Crespin de Billy, Ludovic Jeanjean, Alexandre Obrecht Marchioni, Olivier Mainberger, et al.. A Brain Imaging-Based Diagnostic Biomarker for Periodic Catatonia: Preliminary Evidence Using a Bayesian Approach.. Neuropsychobiology, 2020, 79 (4-5), pp.352-365. ⟨10.1159/000501830⟩. ⟨hal-03700154⟩
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