Comparison of MRI-based automated segmentation methods and functional neurosurgery targeting with direct visualization of the Ventro-intermediate thalamic nucleus at 7T.
Ontology highlight
ABSTRACT:
SUBMITTER: Najdenovska E
PROVIDER: S-EPMC6361927 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:Background and purposeHigh resolution 7T MRI is increasingly used to investigate hippocampal subfields in vivo, but most studies rely on manual segmentation which is labor intensive. We aimed to evaluate an automated technique to segment hippocampal subfields and the entorhinal cortex at 7T MRI.Materials and methodsThe cornu ammonis (CA)1, CA2, CA3, dentate gyrus, subiculum, and entorhinal cortex were manually segmented, covering most of the long axis of the hippocampus on 0.70-mm(3) T2-weighted 7T images of 26 participants (59 ± 9 years, 46% men). The automated segmentation of hippocampal subfields approach was applied and evaluated by using leave-one-out cross-validation.ResultsComparison of automated segmentations with corresponding manual segmentations yielded a Dice similarity coefficient of >0.75 for CA1, the dentate gyrus, subiculum, and entorhinal cortex and >0.54 for CA2 and CA3. Intraclass correlation coefficients were >0.74 for CA1, the dentate gyrus, and subiculum; and >0.43 for CA2, CA3, and the entorhinal cortex. Restricting the comparison of the entorhinal cortex segmentation to a smaller range along the anteroposterior axis improved both intraclass correlation coefficients (left: 0.71; right: 0.82) and Dice similarity coefficients (left: 0.78; right: 0.77). The accuracy of the automated segmentation versus a manual rater was lower, though only slightly for most subfields, than the intrarater reliability of an expert manual rater, but it was similar to or slightly higher than the accuracy of an expert-versus-manual rater with ∼170 hours of training for almost all subfields.ConclusionsThis work demonstrates the feasibility of using a computational technique to automatically label hippocampal subfields and the entorhinal cortex at 7T MRI, with a high accuracy for most subfields that is competitive with the labor-intensive manual segmentation. The software and atlas are publicly available: http://www.nitrc.org/projects/ashs/.
| S-EPMC4907820 | biostudies-literature
Project description:Deep brain stimulation (DBS) of the subthalamic nucleus (STN) reduces motor symptoms in most patients with Parkinson disease (PD), yet may produce untoward effects. Investigation of DBS effects requires accurate localization of the STN, which can be difficult to identify on magnetic resonance images collected with clinically available 3T scanners. The goal of this study is to develop a high-quality STN atlas that can be applied to standard 3T images. We created a high-definition STN atlas derived from seven older participants imaged at 7T. This atlas was nonlinearly registered to a standard template representing 56 patients with PD imaged at 3T. This process required development of methodology for nonlinear multimodal image registration. We demonstrate mm-scale STN localization accuracy by comparison of our 3T atlas with a publicly available 7T atlas. We also demonstrate less agreement with an earlier histological atlas. STN localization error in the 56 patients imaged at 3T was less than 1 mm on average. Our methodology enables accurate STN localization in individuals imaged at 3T. The STN atlas and underlying 3T average template in MNI space are freely available to the research community. The image registration methodology developed in the course of this work may be generally applicable to other datasets.
| S-EPMC5757662 | biostudies-literature
Project description:Novel MR image acquisition strategies have been investigated to elicit contrast within the thalamus, but direct visualization of individual thalamic nuclei remains a challenge because of their small size and the low intrinsic contrast between adjacent nuclei. We present a step-by-step specific optimization of the 3D MPRAGE pulse sequence at 7T to visualize the intra-thalamic nuclei. We first measured T1 values within different sub-regions of the thalamus at 7T in 5 individuals. We used these to perform simulations and sequential experimental measurements (n=17) to tune the parameters of the MPRAGE sequence. The optimal set of parameters was used to collect high-quality data in 6 additional volunteers. Delineation of thalamic nuclei was performed twice by one rater and MR-defined nuclei were compared to the classic Morel histological atlas. T1 values within the thalamus ranged from 1400ms to 1800ms for adjacent nuclei. Using these values for theoretical evaluations combined with in vivo measurements, we showed that a short inversion time (TI) close to the white matter null regime (TI=670ms) enhanced the contrast between the thalamus and the surrounding tissues, and best revealed intra-thalamic contrast. At this particular nulling regime, lengthening the time between successive inversion pulses (TS=6000ms) increased the thalamic signal and contrast and lengthening the ? pulse train time (N*TR) further increased the thalamic signal. Finally, a low flip angle during the gradient echo acquisition (?=4°) was observed to mitigate the blur induced by the evolution of the magnetization along the ? pulse train. This optimized set of parameters enabled the 3D delineation of 15 substructures in all 6 individuals; these substructures corresponded well with the known anatomical structures of the thalamus based on the classic Morel atlas. The mean Euclidean distance between the centers of mass of MR- and Morel atlas-defined nuclei was 2.67mm (±1.02mm). The reproducibility of the MR-defined nuclei was excellent with intraclass correlation coefficient measured at 0.997 and a mean Euclidean distance between corresponding centers of mass found at first versus second readings of 0.69mm (±0.38mm). This 7T strategy paves the way to better identification of thalamic nuclei for neurosurgical planning and investigation of regional changes in neurological disorders.
| S-EPMC3927795 | biostudies-literature
Project description:BackgroundBlood flow velocity and pulsatility of small cerebral perforating arteries can be measured using 7T quantitative 2D phase contrast (PC) MRI. However, ghosting artifacts arising from subject movement and pulsating large arteries cause false positives when applying a previously published perforator detection method.PurposeTo develop a robust, automated method to exclude perforators located in ghosting artifacts.Study typeRetrospective.SubjectsFifteen patients with vascular cognitive impairment or carotid occlusive disease and 10 healthy controls.Field strength/sequence7T/cardiac-gated 2D PC MRI.AssessmentPerforators were automatically excluded from ghosting regions, which were defined as bands in the phase-encoding direction of large arteries. As reference, perforators were manually excluded by two raters (T.A., J.J.M.Z.), based on perforator location with respect to visible ghosting artifacts. The performance of both censoring methods was assessed for the number of (Nincluded ), mean velocity (Vmean ), and pulsatility index (PI) of the included perforators.Statistical testsFor within-method comparisons, inter- and intrarater reliability were assessed for the manual method, and test-retest reliability was assessed for both methods from repeated 2D PC scans (without repositioning). Intraclass correlation coefficients (ICCs) and their 95% confidence intervals (CIs) were determined for Nincluded , Vmean , and PI for all within-method comparisons. The ICC to compare between the two methods was determined with the use of both (test-retest) scans using a multilevel nonlinear mixed model.ResultsThe automated censoring method showed a moderate to good ICC (95% CI) vs. manual censoring for Nincluded (0.73 [0.58-0.87]) and Vmean (0.90 [0.84-0.96]), and a moderate ICC for PI (0.57 [0.37-0.76]). The test-retest reliability of the manual censoring method was considerably lower than the interrater and intrarater reliability, indicating that scanner noise dominates the uncertainty of the analysis.Data conclusionThe proposed automated censoring method can reliably exclude small perforators affected by ghosting artifacts.Level of evidence3.Technical efficacy stage1.
| S-EPMC7754489 | biostudies-literature
Project description:ObjectiveInjuries to the wrist are, due to its small size and complex anatomical structures, difficult to assess by MR, and surgical interventions such as diagnostic arthroscopy are often necessary. Therefore, improved visualization using non-invasive methods could be of clinical value. As a first step of improvement, the purpose of this study was to evaluate visualization of anatomical structures at 7T compared with 3T MR.MethodsEighteen healthy volunteers (three males and three females from each age decade between 20 and 49 years) were examined with 7T and 3T MR. Four musculoskeletal radiologists graded 2D and 3D images on a five-level grading scale for visibility of ligaments, cartilage, nerves, trabecular bone, and tendons, as well as overall image quality (i.e., edge sharpness, perceived tissue contrast, and presence of artefacts). Statistical analysis was done using a visual grading characteristics (VGC) analysis.ResultsVisibility of cartilage, trabecular bone, tendons, nerves, and ligaments was graded significantly higher at 7T with an area under the curve (AUCVGC) of 0.62-0.88 (95% confidence interval [CI] 0.50-0.97, p = < 0.0001-0.03) using either 2D or 3D imaging. Imaging with 3T was not graded as superior to 7T for any structure. Image quality was also significantly superior at 7T, except for artefacts, where no significant differences were found.ConclusionsTendons, trabecular bone, nerves, and ligaments were all significantly better visualized at 7T compared to 3T.Key points• MRI of the wrist at 7T with a commercially available wrist coil is feasible at similar acquisition times as for 3T MRI. • The current study showed 7T to be superior to 3T in the visualization of anatomical structures of the wrist, including ligaments, tendons, nerves, and trabecular bone. • Image quality was significantly superior at 7T, except for artefacts, where no significant differences were found.
| S-EPMC8795032 | biostudies-literature
Project description:ObjectivesTraditional targeting methods for thalamic deep brain stimulation (DBS) performed to address tremor have predominantly relied on indirect atlas-based methods that focus on the ventral intermediate nucleus despite known variability in thalamic functional anatomy. Improvements in preoperative targeting may help maximize outcomes and reduce thalamic DBS-related complications. In this study, we evaluated the ability of thalamic parcellation with structural connectivity-based segmentation (SCBS) to predict tremor improvement following thalamic DBS.MethodsIn this retrospective analysis of 40 patients with essential tremor, hard segmentation of the thalamus was performed by using probabilistic tractography to assess structural connectivity to 7 cortical targets. The volume of tissue activated (VTA) was modeled in each patient on the basis of the DBS settings. The volume of overlap between the VTA and the 7 thalamic segments was determined and correlated with changes in preoperative and postoperative Fahn-Tolosa-Marin Tremor Rating Scale (TRS) scores by using multivariable linear regression models.ResultsA significant association was observed between greater VTA in the supplementary motor area (SMA) and premotor cortex (PMC) thalamic segment and greater improvement in TRS score when considering both the raw change (P?=?.001) and percentage change (P?=?.011). In contrast, no association was observed between change in TRS score and VTA in the primary motor cortex thalamic segment (P???.19).ConclusionsOur data suggest that greater VTA in the thalamic SMA/PMC segment during thalamic DBS was associated with significant improvement in TRS score in patients with tremor. These findings support the potential role of thalamic SCBS as an independent predictor of tremor improvement in patients who receive thalamic DBS.
| S-EPMC6308387 | biostudies-literature
Project description:PurposeTo develop a fast and accurate convolutional neural network based method for segmentation of thalamic nuclei.MethodsA cascaded multi-planar scheme with a modified residual U-Net architecture was used to segment thalamic nuclei on conventional and white-matter-nulled (WMn) magnetization prepared rapid gradient echo (MPRAGE) data. A single network was optimized to work with images from healthy controls and patients with multiple sclerosis (MS) and essential tremor (ET), acquired at both 3 T and 7 T field strengths. WMn-MPRAGE images were manually delineated by a trained neuroradiologist using the Morel histological atlas as a guide to generate reference ground truth labels. Dice similarity coefficient and volume similarity index (VSI) were used to evaluate performance. Clinical utility was demonstrated by applying this method to study the effect of MS on thalamic nuclei atrophy.ResultsSegmentation of each thalamus into twelve nuclei was achieved in under a minute. For 7 T WMn-MPRAGE, the proposed method outperforms current state-of-the-art on patients with ET with statistically significant improvements in Dice for five nuclei (increase in the range of 0.05-0.18) and VSI for four nuclei (increase in the range of 0.05-0.19), while performing comparably for healthy and MS subjects. Dice and VSI achieved using 7 T WMn-MPRAGE data are comparable to those using 3 T WMn-MPRAGE data. For conventional MPRAGE, the proposed method shows a statistically significant Dice improvement in the range of 0.14-0.63 over FreeSurfer for all nuclei and disease types. Effect of noise on network performance shows robustness to images with SNR as low as half the baseline SNR. Atrophy of four thalamic nuclei and whole thalamus was observed for MS patients compared to healthy control subjects, after controlling for the effect of parallel imaging, intracranial volume, gender, and age (p < 0.004).ConclusionThe proposed segmentation method is fast, accurate, performs well across disease types and field strengths, and shows great potential for improving our understanding of thalamic nuclei involvement in neurological diseases.
| S-EPMC7530079 | biostudies-literature
Project description:Orthostatic tremor (OT) was first described in 1977. It is characterized by rapid tremor of 13-18 Hz and can be recorded in the lower limbs and trunk muscles. OT remains difficult to treat, although some success has been reported with deep brain stimulation (DBS).We report a 68-year-old male with OT who did not improve significantly after bilateral thalamic stimulation.Although some patients were described who improved after DBS surgery, more information is needed about the effect of these treatment modalities on OT, ideally in the form of randomized trial data.
| S-EPMC5628322 | biostudies-other
Project description:Ventral intermediate thalamic deep brain stimulation is a standard therapy for the treatment of medically refractory essential tremor and tremor-dominant Parkinson's disease. Despite the therapeutic benefits, the mechanisms of action are varied and complex, and the pathophysiology and genesis of tremor remain unsubstantiated. This intraoperative study investigated the effects of high frequency microstimulation on both neuronal firing and tremor suppression simultaneously. In each of nine essential tremor and two Parkinson's disease patients who underwent stereotactic neurosurgery, two closely spaced (600 µm) microelectrodes were advanced into the ventral intermediate nucleus. One microelectrode recorded action potential firing while the adjacent electrode delivered stimulation trains at 100 Hz and 200 Hz (2-5 s, 100 µA, 150 µs). A triaxial accelerometer was used to measure postural tremor of the contralateral hand. At 200 Hz, stimulation led to 68 ± 8% (P < 0.001) inhibition of neuronal firing and a 53 ± 5% (P < 0.001) reduction in tremor, while 100 Hz reduced firing by 26 ± 12% (not significant) with a 17 ± 6% (P < 0.05) tremor reduction. The degree of cell inhibition and tremor suppression were significantly correlated (P < 0.001). We also found that the most ventroposterior stimulation sites, closest to the border of the ventral caudal nucleus, had the best effect on tremor. Finally, prior to the inhibition of neuronal firing, microstimulation caused a transient driving of neuronal activity at stimulus onset (61% of sites), which gave rise to a tremor phase reset (73% of these sites). This was likely due to activation of the excitatory glutamatergic cortical and cerebellar afferents to the ventral intermediate nucleus. Temporal characteristics of the driving responses (duration, number of spikes, and onset latency) significantly differed between 100 Hz and 200 Hz stimulation trains. The subsequent inhibition of neuronal activity was likely due to synaptic fatigue. Thalamic neuronal inhibition seems necessary for tremor reduction and may function in effect as a thalamic filter to uncouple thalamo-cortical from cortico-spinal reflex loops. Additionally, our findings shed light on the gating properties of the ventral intermediate nucleus within the cerebello-thalamo-cortical tremor network, provide insight for the optimization of deep brain stimulation technologies, and may inform controlled clinical studies for assessing optimal target locations for the treatment of tremor.
| S-EPMC6022553 | biostudies-literature
Project description:PurposeManagement of vestibular schwannoma (VS) is based on tumour size as observed on T1 MRI scans with contrast agent injection. The current clinical practice is to measure the diameter of the tumour in its largest dimension. It has been shown that volumetric measurement is more accurate and more reliable as a measure of VS size. The reference approach to achieve such volumetry is to manually segment the tumour, which is a time intensive task. We suggest that semi-automated segmentation may be a clinically applicable solution to this problem and that it could replace linear measurements as the clinical standard.MethodsUsing high-quality software available for academic purposes, we ran a comparative study of manual versus semi-automated segmentation of VS on MRI with 5 clinicians and scientists. We gathered both quantitative and qualitative data to compare the two approaches; including segmentation time, segmentation effort and segmentation accuracy.ResultsWe found that the selected semi-automated segmentation approach is significantly faster (167 s vs 479 s, [Formula: see text]), less temporally and physically demanding and has approximately equal performance when compared with manual segmentation, with some improvements in accuracy. There were some limitations, including algorithmic unpredictability and error, which produced more frustration and increased mental effort in comparison with manual segmentation.ConclusionWe suggest that semi-automated segmentation could be applied clinically for volumetric measurement of VS on MRI. In future, the generic software could be refined for use specifically for VS segmentation, thereby improving accuracy.
| S-EPMC7419453 | biostudies-literature