In recent years, the clinical assessment of primary brain tumors has been increasingly dependent on advanced magnetic resonance imaging (MRI) techniques in order to infer tumor pathophysiological ...characteristics, such as hemodynamics, metabolism, and microstructure. Quantitative radiomic data extracted from advanced MRI have risen as potential in vivo noninvasive biomarkers for predicting tumor grades and molecular subtypes, opening the era of "molecular imaging" and radiogenomics. This review presents the most relevant advancements in quantitative neuroimaging of advanced MRI techniques, by means of radiomics analysis, applied to primary brain tumors, including lower-grade glioma and glioblastoma, with a special focus on peculiar oncologic entities of current interest. Novel findings from diffusion MRI (dMRI), perfusion-weighted imaging (PWI), and MR spectroscopy (MRS) are hereby sifted in order to evaluate the role of quantitative imaging in neuro-oncology as a tool for predicting molecular profiles, stratifying prognosis, and characterizing tumor tissue microenvironments. Furthermore, innovative technological approaches are briefly addressed, including artificial intelligence contributions and ultra-high-field imaging new techniques. Lastly, after providing an overview of the advancements, we illustrate current clinical applications and future perspectives.
Purpose To evaluate the feasibility of a standardized protocol for acquisition and analysis of dynamic contrast material-enhanced (DCE) and dynamic susceptibility contrast (DSC) magnetic resonance ...(MR) imaging in a multicenter clinical setting and to verify its accuracy in predicting glioma grade according to the new World Health Organization 2016 classification. Materials and Methods The local research ethics committees of all centers approved the study, and informed consent was obtained from patients. One hundred patients with glioma were prospectively examined at 3.0 T in seven centers that performed the same preoperative MR imaging protocol, including DCE and DSC sequences. Two independent readers identified the perfusion hotspots on maps of volume transfer constant (K
), plasma (v
) and extravascular-extracellular space (v
) volumes, initial area under the concentration curve, and relative cerebral blood volume (rCBV). Differences in parameters between grades and molecular subtypes were assessed by using Kruskal-Wallis and Mann-Whitney U tests. Diagnostic accuracy was evaluated by using receiver operating characteristic curve analysis. Results The whole protocol was tolerated in all patients. Perfusion maps were successfully obtained in 94 patients. An excellent interreader reproducibility of DSC- and DCE-derived measures was found. Among DCE-derived parameters, v
and v
had the highest accuracy (are under the receiver operating characteristic curve A
= 0.847 and 0.853) for glioma grading. DSC-derived rCBV had the highest accuracy (A
= 0.894), but the difference was not statistically significant (P > .05). Among lower-grade gliomas, a moderate increase in both v
and rCBV was evident in isocitrate dehydrogenase wild-type tumors, although this was not significant (P > .05). Conclusion A standardized multicenter acquisition and analysis protocol of DCE and DSC MR imaging is feasible and highly reproducible. Both techniques showed a comparable, high diagnostic accuracy for grading gliomas.
RSNA, 2018 Online supplemental material is available for this article.
The power-split architecture is the most promising hybrid electric powertrain. However, a real advantage in energy saving while maintaining high performance can be achieved only by the implementation ...of a proper energy management strategy. This requires an optimized functional design before and a comprehensive analysis of the powertrain losses after, which could be rather challenging owing to the constructive complexity of the power-split transmission, especially for multi-mode architecture with multiple planetary gearing. This difficulty was overcome by a dimensionless model, already available in the literature, that enables the analysis of any power-split transmission, even in full electric operation. This paper relies on this approach to find the operating points of the internal combustion engine and both electric machines which minimize the total power losses. This optimization is carried out for given vehicle speed and demanded torque, by supposing different scenarios in respect of the battery capability of providing or gathering power. The efficiency of the thermal engine and the electric machines is considered, as well as the transmission mechanical power losses. The aim is to provide a global efficiency map that can be exploited to extract data for the implementation of the most suitable real-time control strategy. As a case study, the procedure is applied to the multi-mode power-split system of the Chevrolet Volt.
Although free vibrations of thin-walled cylinders have been extensively addressed in the relevant literature, finding a good balance between accuracy and simplicity of the procedures used for natural ...frequency assessment is still an open issue. This paper proposes a novel approach with a high potential for practical application for rapid esteem of natural frequencies of thin-walled cylinders under different boundary conditions. Starting from Donnell–Mushtari’s shell theory, the differential problem is simplified by using the principle of virtual work and introducing the flexural waveforms of a beam as constrained as the cylinder. Hence, the formulation is reduced to the eigenvalue problem of an equivalent 3 × 3 dynamic matrix, which depends on the cylinder geometry, material, and boundary conditions. Several comparisons with experimental, numerical, and analytical approaches are presented to prove model reliability and practical interest. An excellent balance between fast usability and accuracy is achieved. The user-friendliness of the model makes it suitable to be implemented during the design stage without requiring any deep knowledge of the topic.
This paper aims to develop a comprehensive and subject-specific model to predict the drug reach in Convection-Enhanced Delivery (CED) interventions. To this end, we make use of an advance diffusion ...imaging technique, namely the Neurite Orientation Dispersion and Density Imaging (NODDI), to incorporate a more precise description of the brain microstructure into predictive computational models. The NODDI dataset is used to obtain a voxel-based quantification of the extracellular space volume fraction that we relate to the white matter (WM) permeability. Since the WM can be considered as a transversally isotropic porous medium, two equations, respectively for permeability parallel and perpendicular to the axons, are derived from a numerical analysis on a simplified geometrical model that reproduces flow through fibre bundles. This is followed by the simulation of the injection of a drug in a WM area of the brain and direct comparison of the outcomes of our results with a state-of-the-art model, which uses conventional diffusion tensor imaging. We demonstrate the relevance of the work by showing the impact of our newly derived permeability tensor on the predicted drug distribution, which differs significantly from the alternative model in terms of distribution shape, concentration profile and infusion linear penetration length.
Highlights • In cerebral gliomas, DCE-MRI is able to overcome DSC-MRI shortcomings. • DCE-MRI is as accurate as DSC-MRI for glioma grading. • Hotspot and histogram analyses performed equally for ...glioma grading. • The combination of DCE-derived Vp and Ktrans improves the diagnostic performance.
A scorecard to evaluate magnetic resonance imaging (MRI) findings during the course of leptomeningeal metastases (LM) has been proposed by the Response Assessment in Neuro-Oncology (RANO) group.
To ...explore the feasibility of the Leptomeningeal Assessment in Neuro-Oncology (LANO) scorecard, cerebrospinal MRIs of 22 patients with LM from solid tumors were scored by 10 neuro-oncologists and 9 neuroradiologists at baseline and at follow-up after treatment. Raters were blinded for clinical data including treatment. Agreement between raters of single items was evaluated using a Krippendorff alpha coefficient. Agreement between numerical parameters such as scores for changes between baseline and follow-up and total scores was evaluated by determining the intraclass coefficient of correlation.
Most raters experienced problems with the instructions of the scorecard. No acceptable alpha concordance coefficient was obtained for the rating of single items at baseline or follow-up. The most concordant ratings were obtained for spinal nodules. The concordances were worst for brain linear leptomeningeal enhancement and cranial nerve enhancement. Discordance was less prominent among neuroradiologists than among neuro-oncologists. High variability was also observed for evaluating changes between baseline and follow-up and for total scores.
Assessing response of LM by MRI remains challenging. Central imaging review is therefore indispensable for clinical trials. Based on the present results, we propose a new, simplified scorecard that will require validation using a similar approach as pursued here. The main challenges are to define measurable versus nonmeasurable (target) lesions and measures of change that allow assessment of response.
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