6 research outputs found

    Segmentation of glioblastomas in early post-operative multi-modal MRI with deep neural networks

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    Extent of resection after surgery is one of the main prognostic factors for patients diagnosed with glioblastoma. To achieve this, accurate segmentation and classification of residual tumor from post-operative MR images is essential. The current standard method for estimating it is subject to high inter- and intra-rater variability, and an automated method for segmentation of residual tumor in early post-operative MRI could lead to a more accurate estimation of extent of resection. In this study, two state-of-the-art neural network architectures for pre-operative segmentation were trained for the task. The models were extensively validated on a multicenter dataset with nearly 1000 patients, from 12 hospitals in Europe and the United States. The best performance achieved was a 61% Dice score, and the best classification performance was about 80% balanced accuracy, with a demonstrated ability to generalize across hospitals. In addition, the segmentation performance of the best models was on par with human expert raters. The predicted segmentations can be used to accurately classify the patients into those with residual tumor, and those with gross total resection

    Blood flow lateralization and collateral compensatory mechanisms in patients with carotid artery stenosis

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    Background and Purpose: Four-dimensional phase-contrast magnetic resonance imaging enables quantification of blood flow rate (BFR; mL/min) in multiple cerebral arteries simultaneously, making it a promising technique for hemodynamic investigation in patients with stroke. The aim of this study was to quantify the hemodynamic disturbance and the compensatory pattern of collateral flow in patients with symptomatic carotid stenosis. Methods: Thirty-eight patients (mean, 72 years; 27 men) with symptomatic carotid stenosis (>/=50%) or occlusion were investigated using 4-dimensional phase-contrast magnetic resonance imaging. For each patient, BFR was measured in 19 arteries/locations. The ipsilateral side to the symptomatic carotid stenosis was compared with the contralateral side. Results: Internal carotid artery BFR was lower on the ipsilateral side (134+/-87 versus 261+/-95 mL/min; P<0.001). BFR in anterior cerebral artery (A1 segment) was lower on ipsilateral side (35+/-58 versus 119+/-72 mL/min; P<0.001). Anterior cerebral artery territory bilaterally was primarily supplied by contralateral internal carotid artery. The ipsilateral internal carotid artery mainly supplied the ipsilateral middle cerebral artery (MCA) territory. MCA was also supplied by a reversed BFR found in the ophthalmic and the posterior communicating artery routes on the ipsilateral side (-5+/-28 versus 10+/-28 mL/min, P=0.001, and -2+/-12 versus 6+/-6 mL/min, P=0.03, respectively). Despite these compensations, BFR in MCA was lower on the ipsilateral side, and this laterality was more pronounced in patients with severe carotid stenosis (>/=70%). Although comparing ipsilateral MCA BFR between stenosis groups (<70% and >/=70%), there was no difference ( P=0.95). Conclusions: With a novel approach using 4-dimensional phase-contrast magnetic resonance imaging, we could simultaneously quantify and rank the importance of collateral routes in patients with carotid stenosis. An important observation was that contralateral internal carotid artery mainly secured the bilateral anterior cerebral artery territory. Because of the collateral recruitment, compromised BFR in MCA is not necessarily related to the degree of carotid stenosis. These findings highlight the importance of simultaneous investigation of the hemodynamics of the entire cerebral arterial tree
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