Dual stack black blood carotid artery CMR at 3T: Application to wall thickness visualization

<p>Abstract</p> <p>Background</p> <p>The increasing understanding of atherosclerosis as an important risk factor for the development of acute ischemic events like ischemic stroke has stimulated increasing interest in non-invasive assessment of the structure, composition and burden of plaque depositions in the carotid artery wall. Vessel wall imaging by means of cardiovascular magnetic resonance (CMR) is conventionally done by 2D dual inversion recovery (DIR) techniques, which often fail in covering large volumes of interest as required in plaque burden assessment. Although the technique has been extended to 2D multislice imaging, its straight extension to 3D protocols is still limited by the prolonged acquisition times and incomplete blood suppression. A novel approach for rapid overview imaging of large sections of the carotid artery wall at isotropic spatial resolutions is presented, which omits excitation of the epiglottis. By the interleaved acquisition of two 3D stacks with the proposed motion sensitized segmented steady-state black-blood gradient echo technique (MSDS) the coverage of the carotid artery trees on both sides in reasonable scan times is enabled.</p> <p>Results</p> <p>10 patients were investigated with the proposed technique and compared to conventional transversal DIR turbo spin and gradient echo approaches centered at the height of the carotid bifurcation. In all MSDS experiments sufficient black-blood contrast could be obtained over the entire covered volumes. The contrast to noise ratio between vessel and suppressed blood was improved by 73% applying the motion sensitizing technique. In all patients the suspicious areas of vessel wall thickening could be clearly identified and validated by the conventional local imaging approach. The average assessable vessel wall segment length was evaluated to be 18 cm. While in 50% of the cases motion artifacts could be appreciated in the conventional images, none were detected for the MSDS technique.</p> <p>Conclusion</p> <p>The proposed technique enables the time efficient coverage of large areas of the carotid arteries without compromising wall-lumen CNR to get an overview about detrimental alterations of the vessel wall. Thickening of the vessel wall can be identified and the suspicious segments can be targeted for subsequent high-resolution CMR. The exclusion of the epiglottis may further facilitate reduction of swallowing induced motion artifacts.</p

Lack of robustness of textural measures obtained from 3D brain tumor MRIs impose a need for standardization

Purpose Textural measures have been widely explored as imaging biomarkers in cancer. However, their robustness under dynamic range and spatial resolution changes in brain 3D magnetic resonance images (MRI) has not been assessed. The aim of this work was to study potential variations of textural measures due to changes in MRI protocols. Materials and methods Twenty patients harboring glioblastoma with pretreatment 3D T1-weighted MRIs were included in the study. Four different spatial resolution combinations and three dynamic ranges were studied for each patient. Sixteen three-dimensional textural heterogeneity measures were computed for each patient and configuration including co-occurrence matrices (CM) features and run-length matrices (RLM) features. The coefficient of variation was used to assess the robustness of the measures in two series of experiments corresponding to (i) changing the dynamic range and (ii) changing the matrix size. Results No textural measures were robust under dynamic range changes. Entropy was the only textural feature robust under spatial resolution changes (coefficient of variation under 10% in all cases). Conclusion Textural measures of three-dimensional brain tumor images are not robust neither under dynamic range nor under matrix size changes. Standards should be harmonized to use textural features as imaging biomarkers in radiomic-based studies. The implications of this work go beyond the specific tumor type studied here and pose the need for standardization in textural feature calculation of oncological images