This study aimed to investigate the spatiotemporal changes in neuromelanin-sensitive MRI signal in the substantia nigra and their relation to clinical scores of disease severity in patients with ...early or progressing Parkinson's disease and patients with idiopathic rapid eye movement sleep behaviour disorder (iRBD) exempt of Parkinsonian signs compared to healthy control subjects. Longitudinal T1-weighted anatomical and neuromelanin-sensitive MRI was performed in two cohorts, including patients with iRBD, patients with early or progressing Parkinson's disease, and control subjects. Based on the aligned substantia nigra segmentations using a study-specific brain anatomical template, parametric maps of the probability of a voxel belonging to the substantia nigra were calculated for patients with various degrees of disease severity and controls. For each voxel in the substantia nigra, probability map of controls, correlations between signal-to-noise ratios on neuromelanin-sensitive MRI in patients with iRBD and Parkinson's disease and clinical scores of motor disability, cognition and mood/behaviour were calculated. Our results showed that in patients, compared to the healthy control subjects, the volume of the substantia nigra was progressively reduced for increasing disease severity. The neuromelanin signal changes appeared to start in the posterolateral motor areas of the substantia nigra and then progressed to more medial areas of this region. The ratio between the volume of the substantia nigra in patients with Parkinson's disease relative to the controls was best fitted by a mono-exponential decay. Based on this model, the pre-symptomatic phase of the disease started at 5.3 years before disease diagnosis, and 23.1% of the substantia nigra volume was lost at the time of diagnosis, which was in line with previous findings using post-mortem histology of the human substantia nigra and radiotracer studies of the human striatum. Voxel-wise patterns of correlation between neuromelanin-sensitive MRI signal-to-noise ratio and motor, cognitive and mood/behavioural clinical scores were localized in distinct regions of the substantia nigra. This localization reflected the functional organization of the nigrostriatal system observed in histological and electrophysiological studies in non-human primates (motor, cognitive and mood/behavioural domains). In conclusion, neuromelanin-sensitive MRI enabled us to assess voxel-wise modifications of substantia nigra's morphology in vivo in humans, including healthy controls, patients with iRBD and patients with Parkinson's disease, and identify their correlation with nigral function across all motor, cognitive and behavioural domains. This insight could help assess disease progression in drug trials of disease modification.
In Parkinson's disease, there is a progressive reduction in striatal dopaminergic function, and loss of neuromelanin-containing dopaminergic neurons and increased iron deposition in the substantia ...nigra. We tested the hypothesis of a relationship between impairment of the dopaminergic system and changes in the iron metabolism. Based on imaging data of patients with prodromal and early clinical Parkinson's disease, we assessed the spatiotemporal ordering of such changes and relationships in the sensorimotor, associative and limbic territories of the nigrostriatal system. Patients with Parkinson's disease (disease duration < 4 years) or idiopathic REM sleep behaviour disorder (a prodromal form of Parkinson's disease) and healthy controls underwent longitudinal examination (baseline and 2-year follow-up). Neuromelanin and iron sensitive MRI and dopamine transporter single-photon emission tomography were performed to assess nigrostriatal levels of neuromelanin, iron, and dopamine. For all three functional territories of the nigrostriatal system, in the clinically most and least affected hemispheres separately, the following was performed: cross-sectional and longitudinal intergroup difference analysis of striatal dopamine and iron, and nigral neuromelanin and iron; in Parkinson's disease patients, exponential fitting analysis to assess the duration of the prodromal phase and the temporal ordering of changes in dopamine, neuromelanin or iron relative to controls; and voxel-wise correlation analysis to investigate concomitant spatial changes in dopamine-iron, dopamine-neuromelanin and neuromelanin-iron in the substantia nigra pars compacta. The temporal ordering of dopaminergic changes followed the known spatial pattern of progression involving first the sensorimotor, then the associative and limbic striatal and nigral regions. Striatal dopaminergic denervation occurred first followed by abnormal iron metabolism and finally neuromelanin changes in the substantia nigra pars compacta, which followed the same spatial and temporal gradient observed in the striatum but shifted in time. In conclusion, dopaminergic striatal dysfunction and cell loss in the substantia nigra pars compacta are interrelated with increased nigral iron content.
Purpose
Little is known about the neuronal substrates of neuropsychiatric symptoms associated with COVID-19 and their evolution during the course of the disease. We aimed at describing the ...longitudinal brain metabolic pattern in COVID-19-related encephalopathy using 18F-FDG-PET/CT.
Methods
Seven patients with variable clinical presentations of COVID-19-related encephalopathy were explored thrice with brain 18F-FDG-PET/CT, once in the acute phase, 1 month later and 6 months after COVID-19 onset. PET images were analysed with voxel-wise and regions-of-interest approaches in comparison with 32 healthy controls.
Results
Patients’ neurological manifestations during acute encephalopathy were heterogeneous. However, all of them presented with predominant cognitive and behavioural frontal disorders. SARS-CoV-2 RT-PCR in the CSF was negative for all patients. MRI revealed no specific abnormalities for most of the subjects. All patients had a consistent pattern of hypometabolism in a widespread cerebral network including the frontal cortex, anterior cingulate, insula and caudate nucleus. Six months after COVID-19 onset, the majority of patients clinically had improved but cognitive and emotional disorders of varying severity remained with attention/executive disabilities and anxio-depressive symptoms, and lasting prefrontal, insular and subcortical 18F-FDG-PET/CT abnormalities.
Conclusion
The implication of this widespread network could be the neural substrate of clinical features observed in patients with COVID-19, such as frontal lobe syndrome, emotional disturbances and deregulation of respiratory failure perception. This study suggests that this network remains mildly to severely impaired 6 months after disease onset.
Objectives
The aim of this work was investigating the methods based on coupling cerebral perfusion (ASL) and amino acid metabolism (
18
FDOPA-PET) measurements to evaluate the diagnostic performance ...of PET/MRI in glioma follow-up.
Methods
Images were acquired using a 3-T PET/MR system, on a prospective cohort of patients addressed for possible glioma progression. Data were preprocessed with statistical parametric mapping (SPM), including registration on T1-weighted images, spatial and intensity normalization, and tumor segmentation. As index tests, tumor isocontour maps of
18
FDOPA-PET and ASL T-maps were created and metabolic/perfusion abnormalities were evaluated with the asymmetry index
z
-score. SPM map analysis of significant size clusters and semi-quantitative PET and ASL map evaluation were performed and compared to the gold standard diagnosis. Lastly, ASL and PET topography of significant clusters was compared to that of the initial tumor.
Results
Fifty-eight patients with unilateral treated glioma were included (34 progressions and 24 pseudo-progressions). The tumor isocontour maps and T-maps showed the highest specificity (100%) and sensitivity (94.1%) for ASL and
18
FDOPA analysis, respectively. The sensitivity of qualitative SPM maps and semi-quantitative rCBF and rSUV analyses were the highest for glioblastoma.
Conclusion
Tumor isocontour T-maps and combined analysis of CBF and
18
FDOPA-PET uptake allow achieving high diagnostic performance in differentiating between progression and pseudo-progression in treated gliomas. The sensitivity is particularly high for glioblastomas.
Key Points
•
Applied separately, MRI and PET imaging modalities may be insufficient to characterize the brain glioma post-therapeutic profile.
•
Combined ASL and
18
FDOPA-PET map analysis allows differentiating between tumor progression and pseudo-progression.
Objectives
Our aim was to evaluate the contribution of pseudo-continuous arterial spin labelling (pCASL) in the detection of a postoperative residual lesion in adult brain tumours.
Methods
...Seventy-five patients were prospectively included. Following the results of preoperative DSC-PWI assessment, intra-axial lesions, including high-grade gliomas (
n
= 43) and certain metastases (
n
= 14), were classified as hyper-vascular (HV+ group,
n
= 57); other lesions, including low-grade gliomas and certain metastases, were classified as non-hyper-vascular (HV− group,
n
= 18). To confirm the absence/presence of a residual lesion or disease progression, postoperative MRI including pCASL sequence and follow-up-MRI were performed within 72 h and 1–6 months after the resection, respectively. Two raters evaluated the images. Mean and maximal ASL cerebral blood flow (CBF) values were measured in the perioperative region and normalised to the contralateral tissue. The pCASL-CBF maps and post-contrast T1WI were visually assessed for residual lesion. Quantitative data were analysed with unpaired Student
t
and Mann-Whitney
U
tests and the visual diagnostic performance with the McNemar test.
Results
In the HV+ group, the mean normalised CBF was 1.97 ± 0.59 and 0.97 ± 0.29 (
p
< 0.0001, AUC = 0.964, cut-off = 1.27) for patients with or without residual tumours, respectively. The mean normalised CBF was not discriminative for assessing residual tumours in the HV− group (
p
= 0.454). Visual CBF evaluation allowed 92.98% patients belonging to the HV+ group to be correctly classified (sensitivity 93.02%, specificity 92.86%,
p
< 0.001). Visual evaluation was correlated with contrast enhancement evaluation and with the mean normalised CBF values (
r
= 0.505,
p
< 0.0001 and 0.838,
p
< 0.0001, respectively).
Conclusion
Qualitative and quantitative ASL evaluation shows high diagnostic performance in postoperative assessment of hyper-perfused tumours. In this case, postoperative pCASL may be useful, especially if contrast injection cannot be performed or when contrast enhancement is doubtful.
Key Points
• Evaluation of postoperative residual lesion in the case of brain tumours is an imaging challenge.
• This prospective monocentric study showed that increased normalised cerebral blood flow assessed by pseudo-continuous arterial spin labelling (pCASL) correlates well with the presence of a residual tumour in the case of hyper-vascular tumour diagnosed on preoperative MRI.
• Qualitative and quantitative pCASL is an informative sequence for hyper-vascular residual tumour, especially if acquired more than 48 h after brain tumour surgery, when contrast enhancement can give ambiguous results due to blood-brain barrier disruption.
The diagnosis of Parkinson's disease and atypical Parkinsonism remains clinically difficult, especially at the early stage of the disease, since there is a significant overlap of symptoms. Multimodal ...MRI has significantly improved diagnostic accuracy and understanding of the pathophysiology of Parkinsonian disorders. Structural and quantitative MRI sequences provide biomarkers sensitive to different tissue properties that detect abnormalities specific to each disease and contribute to the diagnosis. Machine learning techniques using these MRI biomarkers can effectively differentiate atypical Parkinsonian syndromes. Such approaches could be implemented in a clinical environment and improve the management of Parkinsonian patients. This review presents different structural and quantitative MRI techniques, their contribution to the differential diagnosis of atypical Parkinsonian disorders and their interest for individual-level diagnosis.The diagnosis of Parkinson's disease and atypical Parkinsonism remains clinically difficult, especially at the early stage of the disease, since there is a significant overlap of symptoms. Multimodal MRI has significantly improved diagnostic accuracy and understanding of the pathophysiology of Parkinsonian disorders. Structural and quantitative MRI sequences provide biomarkers sensitive to different tissue properties that detect abnormalities specific to each disease and contribute to the diagnosis. Machine learning techniques using these MRI biomarkers can effectively differentiate atypical Parkinsonian syndromes. Such approaches could be implemented in a clinical environment and improve the management of Parkinsonian patients. This review presents different structural and quantitative MRI techniques, their contribution to the differential diagnosis of atypical Parkinsonian disorders and their interest for individual-level diagnosis.
To date, the most frequently used Parkinson’s disease (PD) biomarkers are the brain imaging measures of dopaminergic dysfunction using positron emission tomography and single photon emission computed ...tomography. However, major advances have occurred in the development of magnetic resonance imaging (MRI) biomarkers for PD in the past decade. Although conventional structural imaging remains normal in PD, advanced techniques have shown changes in the substantia nigra and the cortex. The most well-developed MRI markers in PD include diffusion imaging and iron load using T2/T2* relaxometry techniques. Other quantitative biomarkers such as susceptibility-weighted imaging for iron load, magnetization transfer and ultra-high-field MRI have shown great potential. More sophisticated techniques such as tractography and resting state functional connectivity give access to anatomical and functional connectivity changes in the brain, respectively. Brain perfusion can be assessed using non-contrast-agent techniques such as arterial spin labelling and spectroscopy gives access to metabolites concentrations. However, to date these techniques are not yet fully validated and standardized quantitative metrics for PD are still lacking. This review presents an overview of new structural, perfusion, metabolic and anatomo-functional connectivity biomarkers, their use in PD and their potential applications to improve the clinical diagnosis of Parkinsonian syndromes and the quality of clinical trials.
Objectives
QyScore® is an imaging analysis tool certified in Europe (CE marked) and the US (FDA cleared) for the automatic volumetry of grey and white matter (GM and WM respectively), hippocampus ...(HP), amygdala (AM), and white matter hyperintensity (WMH). Here we compare QyScore® performances with the consensus of expert neuroradiologists.
Methods
Dice similarity coefficient (DSC) and the relative volume difference (RVD) for GM, WM volumes were calculated on 50 3DT1 images. DSC and the F1 metrics were calculated for WMH on 130 3DT1 and FLAIR images. For each index, we identified thresholds of reliability based on current literature review results. We hypothesized that DSC/F1 scores obtained using QyScore® markers would be higher than the threshold. In contrast, RVD scores would be lower. Regression analysis and Bland–Altman plots were obtained to evaluate QyScore® performance in comparison to the consensus of three expert neuroradiologists.
Results
The lower bound of the DSC/F1 confidence intervals was higher than the threshold for the GM, WM, HP, AM, and WMH, and the higher bounds of the RVD confidence interval were below the threshold for the WM, GM, HP, and AM. QyScore®, compared with the consensus of three expert neuroradiologists, provides reliable performance for the automatic segmentation of the GM and WM volumes, and HP and AM volumes, as well as WMH volumes.
Conclusions
QyScore® represents a reliable medical device in comparison with the consensus of expert neuroradiologists. Therefore, QyScore® could be implemented in clinical trials and clinical routine to support the diagnosis and longitudinal monitoring of neurological diseases.
Key Points
• QyScore® provides reliable automatic segmentation of brain structures in comparison with the consensus of three expert neuroradiologists.
• QyScore® automatic segmentation could be performed on MRI images using different vendors and protocols of acquisition. In addition, the fast segmentation process saves time over manual and semi-automatic methods.
• QyScore® could be implemented in clinical trials and clinical routine to support the diagnosis and longitudinal monitoring of neurological diseases.