Bénédicte Maréchal

An evaluation of volume-based morphometry for prediction of mild cognitive impairment and Alzheimer's disease

Voxel-based morphometry from conventional T1-weighted images has proved effective to quantify Alzheimers disease (AD) related brain atrophy and to enable fairly accurate automated classification of AD patients, mild cognitive impaired patients (MCI) and elderly controls. Little is known, however, about the classification power of volume-based morphometry, where features of interest consist of a few brain structure volumes (e.g. hippocampi, lobes, ventricles) as opposed to hundreds of thousands of voxel-wise gray matter concentrations. In this work, we experimentally evaluate two distinct volume-based morphometry algorithms (FreeSurfer and an in-house algorithm called MorphoBox) for automatic disease classification on a standardized data set from the Alzheimers Disease Neuroimaging Initiative. Results indicate that both algorithms achieve classification accuracy comparable to the conventional whole-brain voxel-based morphometry pipeline using SPM for AD vs elderly controls and MCI vs controls, and higher accuracy for classification of AD vs MCI and early vs late AD converters, thereby demonstrating the potential of volume-based morphometry to assist diagnosis of mild cognitive impairment and Alzheimers disease.

Comparison of accelerated T1-weighted whole-brain structural-imaging protocols

Imaging in neuroscience, clinical research and pharmaceutical trials often employs the 3D magnetisation-prepared rapid gradient-echo (MPRAGE) sequence to obtain structural T1-weighted images with high spatial resolution of the human brain. Typical research and clinical routine MPRAGE protocols with ~1mm isotropic resolution require data acquisition time in the range of 5-10min and often use only moderate two-fold acceleration factor for parallel imaging. Recent advances in MRI hardware and acquisition methodology promise improved leverage of the MR signal and more benign artefact properties in particular when employing increased acceleration factors in clinical routine and research. In this study, we examined four variants of a four-fold-accelerated MPRAGE protocol (2D-GRAPPA, CAIPIRINHA, CAIPIRINHA elliptical, and segmented MPRAGE) and compared clinical readings, basic image quality metrics (SNR, CNR), and automated brain tissue segmentation for morphological assessments of brain structures. The results were benchmarked against a widely-used two-fold-accelerated 3T ADNI MPRAGE protocol that served as reference in this study. 22 healthy subjects (age=20-44yrs.) were imaged with all MPRAGE variants in a single session. An experienced reader rated all images of clinically useful image quality. CAIPIRINHA MPRAGE scans were perceived on average to be of identical value for reading as the reference ADNI-2 protocol. SNR and CNR measurements exhibited the theoretically expected performance at the four-fold acceleration. The results of this study demonstrate that the four-fold accelerated protocols introduce systematic biases in the segmentation results of some brain structures compared to the reference ADNI-2 protocol. Furthermore, results suggest that the increased noise levels in the accelerated protocols play an important role in introducing these biases, at least under the present study conditions.

Prospective head motion correction using FID-guided on-demand image navigators

We suggest a motion correction concept that employs free‐induction‐decay (FID) navigator signals to continuously monitor motion and to guide the acquisition of image navigators for prospective motion correction following motion detection.

The impact of automated hippocampal volumetry on diagnostic confidence in patients with suspected Alzheimer's disease: A European Alzheimer's Disease Consortium study

Hippocampal volume is a core biomarker of Alzheimers disease (AD). However, its contribution over the standard diagnostic workup is unclear.

Is impaired cerebral vasoreactivity an early marker of cognitive decline in multiple sclerosis patients

AbstractObjectiveThe link between cerebral vasoreactivity and cognitive status in multiple sclerosis remains unclear. The aim of the present study was to investigate a potential decrease of cerebral vasoreactivity in multiple sclerosis patients and correlate it with cognitive status.MethodsThirty-three patients with multiple sclerosis (nine progressive and 24 remitting forms, median age: 39 years, 12 males) and 22 controls underwent MRI with a hypercapnic challenge to assess cerebral vasoreactivity and a neuropsychological assessment. Cerebral vasoreactivity, measured as the cerebral blood flow percent increase normalised by end-tidal carbon dioxide variation, was assessed globally and by regions of interest using the blood oxygen level-dependent technique. Non-parametric statistics tests were used to assess differences between groups, and associations were estimated using linear models.ResultsCerebral vasoreactivity was lower in patients with cognitive impairment than in cognitively normal patients (p=0.004) and was associated with education level in patients (R2 = 0.35; p = 0.047). There was no decrease in cerebral vasoreactivity between patients and controls.ConclusionsCognitive impairment in multiple sclerosis may be mediated through decreased cerebral vasoreactivity. Cerebral vasoreactivity could therefore be considered as a marker of cognitive decline in multiple sclerosis.Key points• Cerebral vasoreactivity does not differ between multiple sclerosis patients and controls. • Cerebral vasoreactivity measure is linked to cognitive impairment in multiple sclerosis. • Cerebral vasoreactivity is linked to level of education in multiple sclerosis.

Episodic memory decline in Parkinson’ s disease: relation with white matter hyperintense lesions and influence of quantification method

The relation of white matter hyperintense lesions to episodic memory impairment in patients with Parkinson’s disease (PD) is still controversial. We aimed at evaluating the relation between white matter hyperintense lesions and episodic memory decline in patients with PD. In this multicentric prospective study, twenty-one normal controls, 15 PD patients without mild cognitive impairment (MCI) and 13 PD patients with MCI were selected to conduct a clinico-radiological correlation analysis. Performance during episodic memory testing, age-related white matter changes score, total manual and automated white matter hyperintense lesions volume and lobar white matter hyperintense lesions volumes were compared between groups using the Kruskal-Wallis and Wilcoxon signed-rank tests, and correlations were assessed using the Spearman test. MCI PD patients had impaired free recall. They also had higher total, left prefrontal and left temporal white matter hyperintense lesions volumes than normal controls. Free recall performance was negatively correlated with the total white matter hyperintense lesions volume, either manually or automatically delineated, but not with the age-related white matter changes score. Using automated segmentation, both the left prefrontal and temporal white matter hyperintense lesions volumes were negatively correlated with the free recall performance. Early episodic memory impairment in MCI PD patients may be related to white matter hyperintense lesions, mainly in the prefrontal and temporal lobes. This relation is influenced by the method used for white matter hyperintense lesions quantification. Automated volumetry allows for detecting those changes.

The combined Quantification and interpretation of Multiple Quantitative Magnetic resonance imaging Metrics enlightens longitudinal changes compatible with Brain repair in relapsing-remitting Multiple sclerosis Patients

Objective Quantitative and semi-quantitative MRI (qMRI) metrics provide complementary specificity and differential sensitivity to pathological brain changes compatible with brain inflammation, degeneration, and repair. Moreover, advanced magnetic resonance imaging (MRI) metrics with overlapping elements amplify the true tissue-related information and limit measurement noise. In this work, we combined multiple advanced MRI parameters to assess focal and diffuse brain changes over 2 years in a group of early-stage relapsing-remitting MS patients. Methods Thirty relapsing-remitting MS patients with less than 5 years disease duration and nine healthy subjects underwent 3T MRI at baseline and after 2 years including T1, T2, T2* relaxometry, and magnetization transfer imaging. To assess longitudinal changes in normal-appearing (NA) tissue and lesions, we used analyses of variance and Bonferroni correction for multiple comparisons. Multivariate linear regression was used to assess the correlation between clinical outcome and multiparametric MRI changes in lesions and NA tissue. Results In patients, we measured a significant longitudinal decrease of mean T2 relaxation times in NA white matter (p = 0.005) and a decrease of T1 relaxation times in the pallidum (p < 0.05), which are compatible with edema reabsorption and/or iron deposition. No longitudinal changes in qMRI metrics were observed in controls. In MS lesions, we measured a decrease in T1 relaxation time (p-value < 2.2e−16) and a significant increase in MTR (p-value < 1e−6), suggesting repair mechanisms, such as remyelination, increased axonal density, and/or a gliosis. Last, the evolution of advanced MRI metrics—and not changes in lesions or brain volume—were correlated to motor and cognitive tests scores evolution (Adj-R2 > 0.4, p < 0.05). In summary, the combination of multiple advanced MRI provided evidence of changes compatible with focal and diffuse brain repair at early MS stages as suggested by histopathological studies.

Quantitative volume-based morphometry in focal cortical dysplasia: A pilot study for lesion localization at the individual level

PURPOSE Surgical resection is the most effective treatment for focal cortical dysplasia (FCD). However, many patients with FCD have unremarkable or even negative findings on conventional magnetic resonance imaging (MRI). In this study, we explored the brain volume abnormalities of FCD patients at the individual level using an experimental volume-based morphometry algorithm and further estimated whether the volume abnormalities can help in the detection of FCD lesions. MATERIALS AND METHODS Sixteen patients with histologically-proven FCD lesions were retrospectively studied. Among them, eight patients had no visible abnormalities on routine MRI, three had abnormalities which partly matched the location of the surgical resection regions, and two did not match. For each patient, cerebral high-resolution T1-weighted magnetization-prepared rapid acquisition with gradient echo (MPRAGE) images were segmented into 45 structures, according to a brain anatomy template, and the volume of each structure was compared with an age- and gender-matched normal population at the individual level, based on a MorphoBox prototype. A Receiver Operating Characteristics (ROC) curve was used to evaluate the performance of the prototype in patients. To find the most appropriate threshold value for localizing the epileptogenic zones, deviations from the normative ranges of each resulting volume estimate were assessed by z-scores. RESULTS Volume abnormalities including atrophic and hypertrophic volumes could be found in all the patients. Epileptogenic zones were found in brain structures with an abnormal volume in 87.5% (14/16) of patients. In 71.4% of patients (10/14), these zones were fully located in regions with an atrophic volume. This suggests that FCD lesions are more likely to be in regions with an atrophic volume than in those with a hypertrophic volume. When the best cut-off z-score value was -3.0, the sensitivity, specificity, and ROC area under the curve of the volume estimates were 93.9%, 79.6%, and 0.89, respectively. CONCLUSION Volume abnormalities can assist in the diagnosis of epileptogenic zones at the individual level in FCD patients with negative or positive findings on conventional MR images. Atrophic regions are more likely than hypertrophic ones to represent epileptogenic zones. Volume-based morphometry based on a MorphoBox prototype has potential to assist a careful scrutiny by radiologists with target in atrophic regions in patients who are initially deemed to be MR-negative, further trying to increase the detection rate of FCD.

INTEGRATIVE PREDICTION OF COGNITIVE DECLINE USING ATROPHY NETWORKS, CSF BIOMARKERS, AND GENOTYPE DATA

classification of MCI/SMC (accuracy1⁄46161%) to the CSF benchmark model (accuracy1⁄46161%). Finally, models predicted MCI conversion to AD (mean yrs of conversion 1⁄4 2.161.8) with accuracy of 6864%, similar to the CSF benchmark (7062%). Comparison analyses revealed structural connectome estimates contributed to these models. Conclusions:Our validated results show the feasibility of the multi-modal MRI, particularly structural connectomes, combined with multi-variate machine learning algorithms as an accurate non-invasive brain marker of AD predicting diagnosis and disease progression. Optimizing the high-throughput phenotyping techniques and machine learning algorithms may improve the multi-modal MRI-based predictive modeling.

T1-weighted dynamic contrast-enhanced brain magnetic resonance imaging: A preliminary study with low infusion rate in pediatric patients

Background The aim of this preliminary study is to evaluate the results of T1-weighted dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) in pediatric patients at 1.5T, with a low peripheral intravenous gadoteric acid injection rate of 1 ml/s. Materials and methods Children with neurological symptoms were examined prospectively with conventional MRI and T1-weighted DCE MRI. An magnetic resonance perfusion analysis method was used to obtain time–concentration curves (persistent pattern, type-I; plateau pattern, type-II; washout pattern, type-III) and to calculate pharmacokinetic parameters. A total of two radiologists manually defined regions of interest (ROIs) in the part of the lesion exhibiting the greatest contrast enhancement and in the surrounding normal or contralateral tissue. Lesion/surrounding tissue or contralateral tissue pharmacokinetic parameter ratios were calculated. Tumors were categorized by grade (I–IV) using the World Health Organization (WHO) Grade. Mann–Whitney testing and receiver-operating characteristic (ROC) curves were performed. Results A total of nine boys and nine girls (mean age 10.5 years) were included. Lesions consisted of 10 brain tumors, 3 inflammatory lesions, 3 arteriovenous malformations and 2 strokes. We obtained analyzable concentration–time curves for all patients (6 type-I, 9 type-II, 3 type-III). Ktrans between tumor tissue and surrounding or contralateral tissue was significantly different (p = 0.034). Ktrans ratios were significantly different between grade I tumors and grade IV tumors (p = 0.027) and a Ktrans ratio value superior to 0.63 appeared to be discriminant to determine a grade IV of malignancy. Conclusions Our results confirm the feasibility of pediatric T1-weighted DCE MRI at 1.5T with a low injection rate, which could be of great value in differentiating brain tumor grades.