Quantitative MRI Harmonization to Maximize Clinical Impact: The RIN-Neuroimaging Network

Neuroimaging studies often lack reproducibility, one of the cardinal features of the scientific method. Multisite collaboration initiatives increase sample size and limit methodological flexibility, therefore providing the foundation for increased statistical power and generalizable results. However, multisite collaborative initiatives are inherently limited by hardware, software, and pulse and sequence design heterogeneities of both clinical and preclinical MRI scanners and the lack of benchmark for acquisition protocols, data analysis, and data sharing. We present the overarching vision that yielded to the constitution of RIN-Neuroimaging Network, a national consortium dedicated to identifying disease and subject-specific in-vivo neuroimaging biomarkers of diverse neurological and neuropsychiatric conditions. This ambitious goal needs efforts toward increasing the diagnostic and prognostic power of advanced MRI data. To this aim, 23 Italian Scientific Institutes of Hospitalization and Care (IRCCS), with technological and clinical specialization in the neurological and neuroimaging field, have gathered together. Each IRCCS is equipped with high- or ultra-high field MRI scanners (i.e., ≥3T) for clinical or preclinical research or has established expertise in MRI data analysis and infrastructure. The actions of this Network were defined across several work packages (WP). A clinical work package (WP1) defined the guidelines for a minimum standard clinical qualitative MRI assessment for the main neurological diseases. Two neuroimaging technical work packages (WP2 and WP3, for clinical and preclinical scanners) established Standard Operative Procedures for quality controls on phantoms as well as advanced harmonized quantitative MRI protocols for studying the brain of healthy human participants and wild type mice. Under FAIR principles, a web-based e-infrastructure to store and share data across sites was also implemented (WP4). Finally, the RIN translated all these efforts into a large-scale multimodal data collection in patients and animal models with dementia (i.e., case study). The RIN-Neuroimaging Network can maximize the impact of public investments in research and clinical practice acquiring data across institutes and pathologies with high-quality and highly-consistent acquisition protocols, optimizing the analysis pipeline and data sharing procedures

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

Effect of skeletonizationof the internal thoracic artery on vessel wall integrity

Background. This study was conceived to evaluate the effect of internal thoracic artery (ITA) skeletonization on vessel wall integrity. Methods. Forty consecutive patients undergoing coronary artery bypass were randomized to receive a skeletonized (n = 22) or a pedicled (n = 18) ITA graft. ITA harvesting was performed by 2 experienced surgeons using the same instrumentation and technique. Specimens were examined by light and electron microscope in order to assess vascular wall integrity. A specific immunohistochemical staining and a computerized method were used to quantify the degree of endothelial integrity after surgical preparation. Results. Morphologic analysis revealed 2 cases of limited subadventitial hemorrhage tone for each group) and no case of major arterial damage. Immunohistochemical staining demonstrated an extremely high degree of maintenance of the endothelial integrity in both groups (97.2% +/- 1.9% in the skeletonized and 96.8% +/- 2.1% in the pedicled one; p = 0.53). Conclusions. Skeletonization does not affect ITA wall integrity in humans submitted to coronary artery bypass procedures. (C) 1999 by The Society of Thoracic Surgeons

Incidence of intra-procedural complications according to the timing of endovascular treatment in ruptured intracranial aneurysms

BackgroundAlthough endovascular treatment of ruptured intracranial aneurysms is well-established, some critical issues have not yet been clarified, such as the effects of timing on safety and effectiveness of the procedure. The aim of our study was to analyze the incidence of intra-procedural complications according to the timing of treatment, as they can affect morbidity and mortality. Materials and methodsWe retrospectively analyzed all patients who underwent endovascular treatment for ruptured intracranial aneurysms at three high flow center. For all patients, imaging and clinical data, aneurysm's type, mean dimension and different treatment techniques were analyzed. Intra-procedural complications were defined as thrombus formation at the aneurysm's neck, thromboembolic events, and rupture of the aneurysm. Patients were divided into three groups according to time between subarachnoid hemorrhage and treatment (<12 h hyper-early, 12-36 h early, and >36 h delayed). ResultsThe final study population included 215 patients. In total, 84 patients (39%) underwent hyper-early, 104 (48%) early, and 27 (13%) delayed endovascular treatment. Overall, 69% of the patients were treated with simple coiling, 23% with balloon-assisted coiling, 1% with stent-assisted coiling, 3% with a flow-diverter stent, 3% with an intrasaccular flow disruptor device, and 0.5% with parent vessel occlusion. Delayed endovascular treatment was associated with an increased risk of total intra-procedural complications compared to both hyper-early (p = 0.009) and early (p = 0.004) treatments with a rate of complications of 56% (vs. 29% in hyper-early and 26% in early treated group-p = 0.011 and p = 0.008). The delayed treatment group showed a higher rate of thrombus formation and thromboembolic events. The increased risk of total intra-procedural complications in delayed treatment was confirmed, also considering only the patients treated with simple coiling and balloon-assisted coiling (p = 0.005 and p = 0.003, respectively, compared to hyper-early and early group) with a rate of complications of 62% (vs. 28% in hyper-early and 26% in early treatments-p = 0.007 and p = 0.003). Also in this subpopulation, delayed treated patients showed a higher incidence of thrombus formation and thromboembolic events. ConclusionsEndovascular treatment of ruptured intracranial aneurysms more than 36 h after SAH seems to be associated with a higher risk of intra-procedural complications, especially thrombotic and thromboembolic events