Correcting for the echo-time effect after measuring the cerebral blood flow by arterial spin labeling

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

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.

A double dissociation between two psychotic phenotypes: Periodic catatonia and cataphasia

Schizophrenia as a single liability model was confronted to the multiple psychotic phenotypes model proposed by the Wernicke-Kleist-Leonhard school, focusing on two: periodic catatonia (PC) and cataphasia (C). Both are stable and heritable psychotic phenotypes with no crossed liability and are coming with the buildup of specific residual symptoms: impairment of psychomotricity for PC and a specific disorganization of thought and language in C. Regional cerebral blood flow (rCBF) was used as a biomarker. We attempted to refute the single phenotype model by looking at relevant and specific rCBF anomalies for PC and C, that would exceed anomalies in common relative to controls (CTR), i.e. looking for a double dissociation. Twenty subjects with PC, 9 subjects with C and 27 matched controls had two MRI QUIPSS-II arterial spin labeling sequences converted in rCBF. One SPM analysis was performed for each rCBF measurement and the results were given as the conjunction of both analysis. There was a clear double dissociation of rCBF correlates between PC and C, both being meaningful relative to their residual symptomatology. In PC: rCBF was increased in the left motor and premotor areas. In C: rCBF was decreased bilaterally in the temporo-parietal junctions. Conversely, in both (schizophrenia): rCBF was increased in the left striatum which is known to be an anti-psychotics' effect. This evidence refuts the single schizophrenia model and suggests better natural foundations for PC and C phenotypes. This pleads for further research on them and further research on naturally founded psychotic phenotypes.

CLINICAL TRIAL

Name of the registry: ClinicalTrials.gov Identification: NCT02868879.

Brain perfusion in dementia with Lewy bodies and Alzheimer's disease: an arterial spin labeling MRI study on prodromal and mild dementia stages

Background

We aimed to describe specific changes in brain perfusion in patients with dementia with Lewy bodies (DLB) at both the prodromal (also called mild cognitive impairment) and mild dementia stages, relative to patients with Alzheimer’s disease (AD) and controls.

Methods

Altogether, 96 participants in five groups (prodromal DLB, prodromal AD, DLB with mild dementia, AD with mild dementia, and healthy elderly controls) took part in an arterial spin labeling MRI study. Three analyses were performed: a global perfusion value comparison, a voxel-wise analysis of both absolute and relative perfusion, and a linear discriminant analysis. These were used to assess the global decrease in perfusion, regional changes, and the sensitivity and specificity of these changes.

Results

Patterns of perfusion in DLB differed from AD and controls in both the prodromal stage and dementia, DLB having more deficits in frontal, insular, and temporal cortices whereas AD showed reduced perfusion in parietal and parietotemporal cortices. Decreases but also increases of perfusion in DLB relative to controls were observed in both absolute and relative measurements. All these regional changes of perfusion classified DLB patients with respect to either healthy controls or AD with sensitivity from 87 to 100 % and specificity from 90 to 96 % depending on the stage of the disease.

Conclusions

Our results are consistent with previous studies. We extend the scope of those studies by integrating prodromal DLB patients and by describing both hypo- and hyperperfusion in DLB. While decreases in perfusion may relate to functional impairments, increases might suggest a functional compensation of some brain areas.

Electronic supplementary material

The online version of this article (doi:10.1186/s13195-016-0196-8) contains supplementary material, which is available to authorized users.

Comparing model-based and model-free analysis methods for QUASAR arterial spin labeling perfusion quantification

Amongst the various implementations of arterial spin labeling MRI methods for quantifying cerebral perfusion, the QUASAR method is unique. By using a combination of labeling with and without flow suppression gradients, the QUASAR method offers the separation of macrovascular and tissue signals. This permits local arterial input functions to be defined and "model-free" analysis, using numerical deconvolution, to be used. However, it remains unclear whether arterial spin labeling data are best treated using model-free or model-based analysis. This work provides a critical comparison of these two approaches for QUASAR arterial spin labeling in the healthy brain. An existing two-component (arterial and tissue) model was extended to the mixed flow suppression scheme of QUASAR to provide an optimal model-based analysis. The model-based analysis was extended to incorporate dispersion of the labeled bolus, generally regarded as the major source of discrepancy between the two analysis approaches. Model-free and model-based analyses were compared for perfusion quantification including absolute measurements, uncertainty estimation, and spatial variation in cerebral blood flow estimates. Major sources of discrepancies between model-free and model-based analysis were attributed to the effects of dispersion and the degree to which the two methods can separate macrovascular and tissue signal.