| 1. |
- Agn, Mikael, et al.
(författare)
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A modality-adaptive method for segmenting brain tumors and organs-at-risk in radiation therapy planning
- 2019
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Ingår i: Medical Image Analysis. - : Elsevier BV. - 1361-8415. ; 54, s. 220-237
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Tidskriftsartikel (refereegranskat)abstract
- In this paper we present a method for simultaneously segmenting brain tumors and an extensive set of organs-at-risk for radiation therapy planning of glioblastomas. The method combines a contrast-adaptive generative model for whole-brain segmentation with a new spatial regularization model of tumor shape using convolutional restricted Boltzmann machines. We demonstrate experimentally that the method is able to adapt to image acquisitions that differ substantially from any available training data, ensuring its applicability across treatment sites; that its tumor segmentation accuracy is comparable to that of the current state of the art; and that it captures most organs-at-risk sufficiently well for radiation therapy planning purposes. The proposed method may be a valuable step towards automating the delineation of brain tumors and organs-at-risk in glioblastoma patients undergoing radiation therapy.
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| 2. |
- Akram, Harith, et al.
(författare)
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Connectivity derived thalamic segmentation in deep brain stimulation for tremor
- 2018
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Ingår i: NeuroImage. - : Elsevier. - 2213-1582. ; 18, s. 130-142
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Tidskriftsartikel (refereegranskat)abstract
- The ventral intermediate nucleus (VIM) of the thalamus is an established surgical target for stereotactic ablation and deep brain stimulation (DBS) in the treatment of tremor in Parkinson's disease (PD) and essential tremor (ET). It is centrally placed on a cerebello-thalamo-cortical network connecting the primary motor cortex, to the dentate nucleus of the contralateral cerebellum through the dentato-rubro-thalamic tract (DRT). The VIM is not readily visible on conventional MR imaging, so identifying the surgical target traditionally involved indirect targeting that relies on atlas-defined coordinates. Unfortunately, this approach does not fully account for individual variability and requires surgery to be performed with the patient awake to allow for intraoperative targeting confirmation. The aim of this study is to identify the VIM and the DRT using probabilistic tractography in patients that will undergo thalamic DBS for tremor. Four male patients with tremor dominant PD and five patients (three female) with ET underwent high angular resolution diffusion imaging (HARDI) (128 diffusion directions, 1.5 mm isotropic voxels and b value = 1500) preoperatively. Patients received VIM-DBS using an MR image guided and MR image verified approach with indirect targeting. Postoperatively, using parallel Graphical Processing Unit (GPU) processing, thalamic areas with the highest diffusion connectivity to the primary motor area (M1), supplementary motor area (SMA), primary sensory area (S1) and contralateral dentate nucleus were identified. Additionally, volume of tissue activation (VTA) corresponding to active DBS contacts were modelled. Response to treatment was defined as 40% reduction in the total Fahn-Tolosa-Martin Tremor Rating Score (FTMTRS) with DBS-ON, one year from surgery. Three out of nine patients had a suboptimal, long-term response to treatment. The segmented thalamic areas corresponded well to anatomically known counterparts in the ventrolateral (VL) and ventroposterior (VP) thalamus. The dentate-thalamic area, lay within the M1-thalamic area in a ventral and lateral location. Streamlines corresponding to the DRT connected M1 to the contralateral dentate nucleus via the dentate-thalamic area, clearly crossing the midline in the mesencephalon. Good response was seen when the active contact VTA was in the thalamic area with highest connectivity to the contralateral dentate nucleus. Non-responders had active contact VTAs outside the dentate-thalamic area. We conclude that probabilistic tractography techniques can be used to segment the VL and VP thalamus based on cortical and cerebellar connectivity. The thalamic area, best representing the VIM, is connected to the contralateral dentate cerebellar nucleus. Connectivity based segmentation of the VIM can be achieved in individual patients in a clinically feasible timescale, using HARDI and high performance computing with parallel GPU processing. This same technique can map out the DRT tract with clear mesencephalic crossing.
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| 3. |
- Akram, Harith, et al.
(författare)
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L-Dopa Responsiveness Is Associated With Distinctive Connectivity Patterns in Advanced Parkinson's Disease
- 2017
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Ingår i: Movement Disorders. - : Wiley-Blackwell. - 0885-3185 .- 1531-8257. ; 32:6, s. 874-883
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Tidskriftsartikel (refereegranskat)abstract
- Background: Neuronal loss and dopamine depletion alter motor signal processing between cortical motor areas, basal ganglia, and the thalamus, resulting in the motor manifestations of Parkinson's disease. Dopamine replacement therapy can reverse these manifestations with varying degrees of improvement. Methods: To evaluate functional connectivity in patients with advanced Parkinson's disease and changes in functional connectivity in relation to the degree of response to L-dopa, 19 patients with advanced Parkinson's disease underwent resting-state functional magnetic resonance imaging in the on-medication state. Scans were obtained on a 3-Tesla scanner in 3x3x2.5mm(3) voxels. Seed-based bivariate regression analyses were carried out with atlas-defined basal ganglia regions as seeds, to explore relationships between functional connectivity and improvement in the motor section of the UPDRS-III following an L-dopa challenge. False discovery rate-corrected P was set at < 0.05 for a 2-tailed t test. Results: A greater improvement in UPDRS-III scores following L-dopa administration was characterized by higher resting-state functional connectivity between the prefrontal cortex and the striatum (P=0.001) and lower resting-state functional connectivity between the pallidum (P=0.001), subthalamic nucleus (P=0.003), and the paracentral lobule (supplementary motor area, mesial primary motor, and primary sensory areas). Conclusions: Our findings show characteristic basal ganglia resting-state functional connectivity patterns associated with different degrees of L-dopa responsiveness in patients with advanced Parkinson's disease. L-Dopa exerts a graduated influence on remapping connectivity in distinct motor control networks, potentially explaining some of the variance in treatment response.
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| 4. |
- Akram, Harith, et al.
(författare)
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Optimal deep brain stimulation site and target connectivity for chronic cluster headache
- 2017
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Ingår i: Neurology. - : LIPPINCOTT WILLIAMS & WILKINS. - 0028-3878 .- 1526-632X. ; 89:20, s. 2083-2091
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Tidskriftsartikel (refereegranskat)abstract
- Objective: To investigate the mechanism of action of deep brain stimulation for refractory chronic cluster headache and the optimal target within the ventral tegmental area. Methods: Seven patients with refractory chronic cluster headache underwent high spatial and angular resolution diffusion MRI preoperatively. MRI-guided and MRI-verified electrode implantation was performed unilaterally in 5 patients and bilaterally in 2. Volumes of tissue activation were generated around active lead contacts with a finite-element model. Twelve months after surgery, voxel-based morphometry was used to identify voxels associated with higher reduction in headache load. Probabilistic tractography was used to identify the brain connectivity of the activation volumes in responders, defined as patients with a reduction of >= 30% in headache load. Results: There was no surgical morbidity. Average follow-up was 34 +/- 14 months. Patients showed reductions of 76 +/- 33% in headache load, 46 +/- 41% in attack severity, 58 +/- 41% in headache frequency, and 51 +/- 46% in attack duration at the last follow-up. Six patients responded to treatment. Greatest reduction in headache load was associated with activation in an area cantered at 6 mm lateral, 2 mm posterior, and 1 mm inferior to the midcommissural point of the third ventricle. Average responders' activation volume lay on the trigeminohypothalamic tract, connecting the trigeminal system and other brainstem nuclei associated with nociception and pain modulation with the hypothalamus, and the prefrontal and mesial temporal areas. Conclusions: We identify the optimal stimulation site and structural connectivity of the deep brain stimulation target for cluster headache, explicating possible mechanisms of action and disease pathophysiology.
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| 5. |
- Akram, Harith, et al.
(författare)
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Subthalamic deep brain stimulation sweet spots and hyperdirect cortical connectivity in Parkinson's disease
- 2017
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Ingår i: NeuroImage. - : Elsevier. - 1053-8119 .- 1095-9572. ; 158, s. 332-345
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Tidskriftsartikel (refereegranskat)abstract
- Objectives: Firstly, to identify subthalamic region stimulation clusters that predict maximum improvement in rigidity, bradykinesia and tremor, or emergence of side-effects; and secondly, to map-out the cortical fingerprint, mediated by the hyperdirect pathways which predict maximum efficacy.Methods: High angular resolution diffusion imaging in twenty patients with advanced Parkinson's disease was acquired prior to bilateral subthalamic nucleus deep brain stimulation. All contacts were screened one-year from surgery for efficacy and side-effects at different amplitudes. Voxel-based statistical analysis of volumes of tissue activated models was used to identify significant treatment clusters. Probabilistic tractography was employed to identify cortical connectivity patterns associated with treatment efficacy.Results: All patients responded well to treatment (46% mean improvement off medication UPDRS-III [p < 0.0001]) without significant adverse events. Cluster corresponding to maximum improvement in tremor was in the posterior, superior and lateral portion of the nucleus. Clusters corresponding to improvement in bradykinesia and rigidity were nearer the superior border in a further medial and posterior location. The rigidity cluster extended beyond the superior border to the area of the zona incerta and Forel-H-2 field. When the clusters where averaged, the coordinates of the area with maximum overall efficacy was X = -10(-9.5), Y = -3(-1) and Z = -7(-3) in MNI(AC-PC) space. Cortical connectivity to primary motor area was predictive of higher improvement in tremor; whilst that to supplementary motor area was predictive of improvement in bradykinesia and rigidity; and connectivity to prefrontal cortex was predictive of improvement in rigidity.Interpretation: These findings support the presence of overlapping stimulation sites within the subthalamic nucleus and its superior border, with different cortical connectivity patterns, associated with maximum improvement in tremor, rigidity and bradykinesia.
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| 6. |
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| 7. |
- Callaghan, Martina F, et al.
(författare)
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Example dataset for the hMRI toolbox
- 2019
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Ingår i: Data in Brief. - : Elsevier BV. - 2352-3409.
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Tidskriftsartikel (refereegranskat)abstract
- The hMRI toolbox is an open-source toolbox for the calculation of quantitative MRI parameter maps from a series of weighted imaging data, and optionally additional calibration data. The multi-parameter mapping (MPM) protocol, incorporating calibration data to correct for spatial variation in the scanner’s transmit and receive fields, is the most complete protocol that can be handled by the toolbox. Here we present a dataset acquired with such a full MPM protocol, which is made freely available to be used as a tutorial by following instructions provided on the associated toolbox wiki pages, which can be found at http://hMRI.info, and following the theory described in: hMRI – A toolbox for quantitative MRI in neuroscience and clinical research.
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| 8. |
- Deans, Andrew R, et al.
(författare)
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Finding Our Way through Phenotypes.
- 2015
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Ingår i: PLoS Biology. - : Public Library of Science (PLoS). - 1545-7885. ; 13:1
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Tidskriftsartikel (refereegranskat)abstract
- Despite a large and multifaceted effort to understand the vast landscape of phenotypic data, their current form inhibits productive data analysis. The lack of a community-wide, consensus-based, human- and machine-interpretable language for describing phenotypes and their genomic and environmental contexts is perhaps the most pressing scientific bottleneck to integration across many key fields in biology, including genomics, systems biology, development, medicine, evolution, ecology, and systematics. Here we survey the current phenomics landscape, including data resources and handling, and the progress that has been made to accurately capture relevant data descriptions for phenotypes. We present an example of the kind of integration across domains that computable phenotypes would enable, and we call upon the broader biology community, publishers, and relevant funding agencies to support efforts to surmount today's data barriers and facilitate analytical reproducibility.
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| 10. |
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