Differential diagnosis of neurodegenerative dementias with the explainable MRI based machine learning algorithm MUQUBIA

Biomarker-based differential diagnosis of the most common forms of dementia is becoming increasingly important. Machine learning (ML) may be able to address this challenge. The aim of this study was to develop and interpret a ML algorithm capable of differentiating Alzheimer's dementia, frontotemporal dementia, dementia with Lewy bodies and cognitively normal control subjects based on sociodemographic, clinical, and magnetic resonance imaging (MRI) variables. 506 subjects from 5 databases were included. MRI images were processed with FreeSurfer, LPA, and TRACULA to obtain brain volumes and thicknesses, white matter lesions and diffusion metrics. MRI metrics were used in conjunction with clinical and demographic data to perform differential diagnosis based on a Support Vector Machine model called MUQUBIA (Multimodal Quantification of Brain whIte matter biomArkers). Age, gender, Clinical Dementia Rating (CDR) Dementia Staging Instrument, and 19 imaging features formed the best set of discriminative features. The predictive model performed with an overall Area Under the Curve of 98%, high overall precision (88%), recall (88%), and F1 scores (88%) in the test group, and good Label Ranking Average Precision score (0.95) in a subset of neuropathologically assessed patients. The results of MUQUBIA were explained by the SHapley Additive exPlanations (SHAP) method. The MUQUBIA algorithm successfully classified various dementias with good performance using cost-effective clinical and MRI information, and with independent validation, has the potential to assist physicians in their clinical diagnosis

Sleep apnea: Altered brain connectivity underlying a working-memory challenge

Obstructive sleep apnea (OSA) is characterized by the frequent presence of neuro-cognitive impairment. Recent studies associate cognitive dysfunction with altered resting-state brain connectivity between key nodes of the executive and default-mode networks, two anti-correlated functional networks whose strength of activation increases or decreases with cognitive activity, respectively. To date no study has investigated a relationship between cognitive impairment in OSA and brain connectivity during an active working-memory challenge. We thus investigated the effect of OSA on working-memory performance and underlying brain connectivity.OSA patients and matched healthy controls underwent functional magnetic resonance imaging (fMRI) scanning while performing a 2-back working-memory task. Standard fMRI analyses highlighted the brain regions activated at increasing levels of working-memory load, which were used as seeds in connectivity analyses. The latter were based on a multiregional Psycho-Physiological-Interaction (PPI) approach, to unveil group differences in effective connectivity underlying working-memory performance.Compared with controls, in OSA patients normal working-memory performance reflected in: a) reduced interhemispheric effective connectivity between the frontal “executive” nodes of the working-memory network, and b) increased right-hemispheric connectivity among regions mediating the “salience-based” switch from the default resting-state mode to the effortful cognitive activity associated with the executive network. The strength of such connections was correlated, at increasing task-demands, with executive (Stroop test) and memory (Digit Span test) performance in neuro-cognitive evaluations.The analysis of effective connectivity changes during a working-memory challenge provides a complementary window, compared with resting-state studies, on the mechanisms supporting preserved performance despite functional and structural brain modifications in OSA. Keywords: Obstructive sleep apnea, Executive functions, Working-memory, fMRI, Cognitive disorders, Brain connectivit

Comparison of 3D TOF-MRA and 3D CE-MRA at 3 T for imaging of intracranial aneurysms

Purpose: To compare 3 T elliptical-centric CE MRA with 3 T TOF MRA for the detection and characterizationof unruptured intracranial aneurysms (UIAs), by using digital subtracted angiography (DSA) as reference.Materials and methods: Twenty-nine patients (12 male, 17 female; mean age: 62 years) with 41 aneurysms(34 saccular, 7 fusiform; mean diameter: 8.85 mm [range 2.0\u201326.4 mm]) were evaluated with MRA at3 T each underwent 3D TOF-MRA examination without contrast and then a 3D contrast-enhanced (CE-MRA) examination with 0.1 mmol/kg bodyweight gadobenate dimeglumine and k-space elliptic mapping(Contrast ENhanced Timing Robust Angiography [CENTRA]). Both TOF and CE-MRA images were used toevaluate morphologic features that impact the risk of rupture and the selection of a treatment. Almosthalf (20/41) of UIAs were located in the internal carotid artery, 7 in the anterior communicating artery,9 in the middle cerebral artery and 4 in the vertebro-basilar arterial system.All patients also underwent DSA before or after the MR examination.Results: The CE-MRA results were in all cases consistent with the DSA dataset. No differences werenoted between 3D TOF-MRA and CE-MRA concerning the detection and location of the 41 aneurysmsor visualization of the parental artery. Differences were apparent concerning the visualization of mor-phologic features, especially for large aneurysms (>13 mm). An irregular sac shape was demonstratedfor 21 aneurysms on CE-MRA but only 13/21 aneurysms on 3D TOF-MRA. Likewise, CE-MRA permittedvisualization of an aneurismal neck and calculation of the sac/neck ratio for all 34 aneurysms with aneck demonstrated at DSA. Conversely, a neck was visible for only 24/34 aneurysms at 3D TOF-MRA. 3DCE-MRA detected 15 aneurysms with branches originating from the sac and/or neck, whereas brancheswere recognized in only 12/15 aneurysms at 3D TOF-MRA.Conclusion: For evaluation of intracranial aneurysms at 3 T, 3D CE-MRA is superior to 3D TOF-MRA forassessment of sac shape, detection of aneurysmal neck, and visualization of branches originating fromthe sac or neck itself, if the size of the aneurysm is greater than 13 mm. 3 T 3D CE-MRA is as accurate andeffective as DSA for the evaluation of UIAs

Chromatic Pupillometry for Screening and Monitoring of Retinitis Pigmentosa

Early diagnosis of Inherited Retinal Diseases, such as Retinitis Pigmentosa (RP) is challenging in pediatric patients, because their diagnosis mainly relies on relatively invasive tests. We conducted a pilot study to evaluate the usefulness of chromatic pupillometry in RP

Toward a Novel Medical Device Based on Chromatic Pupillometry for Screening and Monitoring of Inherited Ocular Disease: A Pilot Study

Chromatic pupillometry is a relatively novel research tool for the evaluation of retina function and may be a novel way to diagnose and monitor inherited retinal diseases in paediatric population. Nevertheless, although the method is clinically feasible in paediatric populations, as shown by several non-ocular studies, only few studies, on a small size sample of paediatric ophthalmic subjects, are available. Moreover, to the best of the authors’ knowledge, no medical device based on chromatic pupillometry was CE-marked for diagnosis and / or monitoring of inherited ocular disease. Therefore, we designed a pilot study in order to evaluate clinical feasibility and utility of chromatic pupillometry. The study sample consists of sixty patients, affected by inherited ocular diseases. A pupillometric system, including definition of pupillometric protocols, have been set up. In the current paper, we present the comparison between the measurements obtained in one patient affected by Retinitis Pigmentosa and a healthy age-matched control in order to show the differences in chromatic pu-pillometry parameters between case and control

fMRI-Targeted High-Angular Resolution Diffusion MR Tractography to Identify Functional Language Tracts in Healthy Controls and Glioma Patients.

BackgroundMR Tractography enables non-invasive preoperative depiction of language subcortical tracts, which is crucial for the presurgical work-up of brain tumors; however, it cannot evaluate the exact function of the fibers.PurposeA systematic pipeline was developed to combine tractography reconstruction of language fiber bundles, based on anatomical landmarks (Anatomical-T), with language fMRI cortical activations. A fMRI-targeted Tractography (fMRI-T) was thus obtained, depicting the subsets of the anatomical tracts whose endpoints are located inside a fMRI activation. We hypothesized that fMRI-T could provide additional functional information regarding the subcortical structures, better reflecting the eloquent white matter structures identified intraoperatively.MethodsBoth Anatomical-T and fMRI-T of language fiber tracts were performed on 16 controls and preoperatively on 16 patients with left-hemisphere brain tumors, using a q-ball residual bootstrap algorithm based on High Angular Resolution Diffusion Imaging (HARDI) datasets (b = 3000 s/mm2; 60 directions); fMRI ROIs were obtained using picture naming, verbal fluency, and auditory verb generation tasks. In healthy controls, normalized MNI atlases of fMRI-T and Anatomical-T were obtained. In patients, the surgical resection of the tumor was pursued by identifying eloquent structures with intraoperative direct electrical stimulation mapping and extending surgery to the functional boundaries. Post-surgical MRI allowed to identify Anatomical-T and fMRI-T non-eloquent portions removed during the procedure.ResultsMNI Atlases showed that fMRI-T is a subset of Anatomical-T, and that different task-specific fMRI-T involve both shared subsets and task-specific subsets - e.g., verbal fluency fMRI-T strongly involves dorsal frontal tracts, consistently with the phonogical-articulatory features of this task. A quantitative analysis in patients revealed that Anatomical-T removed portions of AF-SLF and IFOF were significantly greater than verbal fluency fMRI-T ones, suggesting that fMRI-T is a more specific approach. In addition, qualitative analyses showed that fMRI-T AF-SLF and IFOF predict the exact functional limits of resection with increased specificity when compared to Anatomical-T counterparts, especially the superior frontal portion of IFOF, in a subcohort of patients.ConclusionThese results suggest that performing fMRI-T in addition to the 'classic' Anatomical-T may be useful in a preoperative setting to identify the 'high-risk subsets' that should be spared during the surgical procedure