Roberta Vasta

The challenge of mapping the human connectome based on diffusion tractography

Tractography based on non-invasive diffusion imaging is central to the study of human brain connectivity. To date, the approach has not been systematically validated in ground truth studies. Based on a simulated human brain data set with ground truth tracts, we organized an open international tractography challenge, which resulted in 96 distinct submissions from 20 research groups. Here, we report the encouraging finding that most state-of-the-art algorithms produce tractograms containing 90% of the ground truth bundles (to at least some extent). However, the same tractograms contain many more invalid than valid bundles, and half of these invalid bundles occur systematically across research groups. Taken together, our results demonstrate and confirm fundamental ambiguities inherent in tract reconstruction based on orientation information alone, which need to be considered when interpreting tractography and connectivity results. Our approach provides a novel framework for estimating reliability of tractography and encourages innovation to address its current limitations.Though tractography is widely used, it has not been systematically validated. Here, authors report results from 20 groups showing that many tractography algorithms produce both valid and invalid bundles.

Tractography-based connectomes are dominated by false-positive connections

Fiber tractography based on non-invasive diffusion imaging is at the heart of connectivity studies of the human brain. To date, the approach has not been systematically validated in ground truth studies. Based on a simulated human brain dataset with ground truth white matter tracts, we organized an open international tractography challenge, which resulted in 96 distinct submissions from 20 research groups. While most state-of-the-art algorithms reconstructed 90% of ground truth bundles to at least some extent, on average they produced four times more invalid than valid bundles. About half of the invalid bundles occurred systematically in the majority of submissions. Our results demonstrate fundamental ambiguities inherent to tract reconstruction methods based on diffusion orientation information, with critical consequences for the approach of diffusion tractography in particular and human connectivity studies in general.

Cortical volume and folding abnormalities in Parkinson's disease patients with pathological gambling

PURPOSE Pathological gambling (PG) is one of the most devastating non-motor complications of Parkinsons disease (PD). Neuroanatomical abnormalities in PD patients with PG are poorly understood. METHODS In the current study we investigated PD patients with and without PG using Voxel Based Morphometry (VBM) and local Gyrification Index (lGI), two neuroimaging techniques useful for detecting complementary morphological metrics in the brain. Twelve PD patients with PG were compared to 12 clinically-matched PD patients without PG and 24 healthy controls. RESULTS PD patients with PG showed grey matter volume loss specifically in the orbitofrontal cortex (OFC) when compared to patients without PG, with the atrophy of this region correlating with the increase of gambling symptoms (G-SAS). Surface-based analysis complemented this evidence revealing that the OFC in the PD patients with PG was also characterized by a reduced lGI. Moreover, when compared to controls, PD patients with PG showed a more widespread anatomical neurodegeneration involving several limbic regions such as: the OFC, cingulate cortex, inferior frontal cortex and insular cortex. Otherwise, demographically-/clinically-matched PD patients without PG did not display significant anatomical changes. DISCUSSION Our study demonstrates that combined grey matter atrophy and reduced lGI in the OFC differentiates PD patients with PG from those without PG, suggesting that this cortical area may play a critical role in the development of this drug-induced behavioral disorder.

Magnetic resonance support vector machine discriminates between Parkinson disease and progressive supranuclear palsy

The aim of the current study was to distinguish patients with Parkinson disease (PD) from those with progressive supranuclear palsy (PSP) at the individual level using pattern recognition of magnetic resonance imaging data.

Tractography in amyotrophic lateral sclerosis using a novel probabilistic tool: A study with tract-based reconstruction compared to voxel-based approach

BACKGROUND Diffusion tensor imaging (DTI) is one of the most sensitive MRI tools for detecting subtle cerebral white matter abnormalities in amyotrophic lateral sclerosis (ALS). Nowadays a plethora of DTI tools have been proposed, but very few methods have been translated into clinical practice. NEW METHOD The aim of this study is to validate the objective measurement of fiber tracts as provided by a new unbiased and automated tractography reconstruction tool named as TRActs Constrained by UnderLying Anatomy (TRACULA). The reliability of this tract-based approach was evaluated on a dataset of 14 patients with definite ALS compared with 14 age/sex-matched healthy controls. To further corroborate these measurements, we used a well-known voxelwise approach, called tract-based spatial statistics (TBSS), on the same dataset. RESULTS TRACULA showed specific significant alterations of several DTI parameters in the corticospinal tract of the ALS group with respect to controls. COMPARISON WITH EXISTING METHOD The same finding was detected using the well-known TBSS analysis. Similarly, both methods depicted also additional microstructural changes in the cingulum. CONCLUSIONS DTI tractography metrics provided by TRACULA perfectly agree with those previously reported in several post-mortem and DTI studies, thus demonstrating the accuracy of this method in characterizing the microstructural changes occurring in ALS. With further validation (i.e. considering the heterogeneity of other clinical phenotypes), this method has the potential to become useful for clinical practice providing objective measurements that might aid radiologists in the interpretation of MR images and improve diagnostic accuracy of ALS.

Hippocampal Subfield Atrophies in Converted and Not-Converted Mild Cognitive Impairments Patients by a Markov Random Fields Algorithm

Although measurement of total hippocampal volume is considered as an important hallmark of Alzheimers disease (AD), recent evidence demonstrated that atrophies of hippocampal subregions might be more sensitive in predicting this neurodegenerative disease. The vast majority of neuroimaging papers investigating this topic are focused on the difference between AD and patients with mild cognitive impairment (MCI), not considering the impact of MCI patients who will or not convert in AD. For this reason, the aim of this study was to determine if measurements of hippocampal subfields provide advantages over total hippocampal volume for discriminating these groups. Hippocampal subfields volumetry was extracted in 55 AD, 32 converted and 89 not-converted MCI (c/nc-MCI) and 47 healthy controls, using an atlas-based automatic algorithm based on Markov random fields embedded in the Freesurfer framework. To evaluate the impact of hippocampal atrophy in discriminating the insurgence of AD-like phenotypes we used three classification methods: Support Vector Machine, Naïve Bayesian Classifier and Neural Networks Classifier. Taking into account only the total hippocampal volume, all classification models, reached a sensitivity of about 66% in discriminating between c-MCI and nc-MCI. Otherwise, classification analysis considering all segmenting subfields increased accuracy to diagnose c-MCI from 68% to 72%. This effect resulted to be strongly dependent upon atrophies of the subiculum and presubiculum. Our multivariate analysis revealed that the magnitude of the difference considering hippocampal subfield volumetry, as segmented by the considered atlas-based automatic algorithm, offers an advantage over hippocampal volume in distinguishing early AD from nc-MCI.

Detection of hippocampal atrophy in patients with temporal lobe epilepsy: A 3-Tesla MRI shape

In patients with mesial temporal lobe epilepsy (MTLE), brain MRI often detects hippocampal sclerosis (HS). Almost half of patients with MTLE do not show any hippocampal damage on visual or volumetric assessment. Here, we wished to prospectively assess 65 patients with MTLE (41 women, mean age: 39±10years, range: 21-69; right (12/65 patients) (MRI-negative) nMTLE; right (14/65 patients) (MRI-positive with HS) pMTLE; left (24/65 patients) nMTLE; and left (15/65 patients) pMTLE) using shape analysis (SA). There were significant differences among pMTLE versus nMTLE for age at seizure onset (20.2±12.8 vs. 31.8±16.7years; p=.0029), duration of epilepsy (14.6±12.7 vs. 21.3±9.6years; p=.0227), risk of refractoriness (p=.0067), frequency of antecedent febrile convulsions (FCs) (p<.001), as well as a history of epilepsy or FCs (p=.0104). All the subjects underwent the same 3-Tesla MRI protocol. Shape analysis of hippocampal formation was conducted comparing each group versus 44 matched controls. In all four subgroups, SA detected a significant atrophy in the corresponding hippocampus that coincided with the epileptogenic area. The damage was significantly more severe in patients with pMTLE (F value: 5.00) than in subgroups with nMTLE (F value: 3.50) and mainly corresponded to the CA1 subregion and subiculum. In the patients with MTLE, SA detects hippocampal damage that lateralizes with the epileptogenic area. Such damage is most prominent in the CA1 subregion and subiculum that are crucial in the pathogenesis of MTLE.

3-T magnetic resonance imaging simultaneous automated multimodal approach improves detection of ambiguous visual hippocampal sclerosis

To evaluate if an automatic magnetic resonance imaging (MRI) processing system may improve detection of hippocampal sclerosis (Hs) in patients with mesial temporal lobe epilepsy (MTLE).

Near-Infrared Spectroscopy in Gait Disorders: Is It Time to Begin?

Walking is a complex motor behavior with a special relevance in clinical neurology. Many neurological diseases, such as Parkinson’s disease and stroke, are characterized by gait disorders whose neurofunctional correlates are poorly investigated. Indeed, the analysis of real walking with the standard neuroimaging techniques poses strong challenges, and only a few studies on motor imagery or walking observation have been performed so far. Functional near-infrared spectroscopy (fNIRS) is becoming an important research tool to assess functional activity in neurological populations or for special tasks, such as walking, because it allows investigating brain hemodynamic activity in an ecological setting, without strong immobility constraints. A systematic review following PRISMA guidelines was conducted on the fNIRS-based examination of gait disorders. Twelve of the initial yield of 489 articles have been included in this review. The lesson learnt from these studies suggest that oxy-hemoglobin levels within the prefrontal and premotor cortices are more sensitive to compensation strategies reflecting postural control and restoration of gait disorders. Although this field of study is in its relative infancy, the evidence provided encourages the translation of fNIRS in clinical practice, as it offers a unique opportunity to explore in depth the activity of the cortical motor system during real walking in neurological patients. We also discuss to what extent fNIRS may be applied for assessing the effectiveness of rehabilitation programs.

Relationship between Hippocampal Subfields and Category Cued Recall in AD and PDD: A Multimodal MRI Study

Alzheimers disease (AD) and Parkinsons disease with dementia (PDD) are characterized by a different mnesic failure, particularly in memory cued recall. Although hippocampal involvement has been shown in both these diseases, it remains unknown whether a selective damage of specific subfields within the hippocampus may be responsible for the peculiar mnesic profile observed in AD and PDD. To explore this topic, we combined a multimodal 3 T-MRI hippocampal evaluation (whole-brain T1-weighted and diffusion tensor imaging) with a hippocampal-targeted neuropsychological assessment (Free and Cued Selective Reminding Test [FCSRT]) in 22 AD subjects, 18 PDD and 17 healthy controls. Macro- and microstructural features (volume; shape; mean diffusivity [MD]; fractional anisotropy [FA]) of bilateral hippocampi (whole and subfields) were obtained. Correlations between MRI-derived parameters and neuropsychological evaluations were performed. In the comparison between AD and PDD, the multimodal analysis allowed us to identify that subiculum, CA1 and CA4-DG were differently involved in these diseases and correlated with immediate and delayed total recall items of FCSRT. Moreover, compared to controls, AD showed a reduction in almost all subfields, with a MD increase in the same regions, whereas PDD displayed a volume loss, less severe than AD, more evident in the CA2-3 and presubiculum subfields. Our study provides new evidence that hippocampal subregions had different vulnerability to damage related to AD and PDD. The combination of the in vivo analysis of hippocampal subfields with the FCSRT paradigm provided important insights into whether changes within specific hippocampal subfields are related to the different mnesic profile in AD and PDD patients.