Dataset Information

Detecting Corticospinal Tract Impairment in Tumor Patients With Fiber Density and Tensor-Based Metrics.

ABSTRACT: Tumors infiltrating the motor system lead to significant disability, often caused by corticospinal tract injury. The delineation of the healthy-pathological white matter (WM) interface area, for which diffusion magnetic resonance imaging (dMRI) has shown promising potential, may improve treatment outcome. However, up to 90% of white matter (WM) voxels include multiple fiber populations, which cannot be correctly described with traditional metrics such as fractional anisotropy (FA) or apparent diffusion coefficient (ADC). Here, we used a novel fixel-based along-tract analysis consisting of constrained spherical deconvolution (CSD)-based probabilistic tractography and fixel-based apparent fiber density (FD), capable of identifying fiber orientation specific microstructural metrics. We addressed this novel methodology's capability to detect corticospinal tract impairment. We measured and compared tractogram-related FD and traditional microstructural metrics bihemispherically in 65 patients with WHO grade III and IV gliomas infiltrating the motor system. The cortical tractogram seeds were based on motor maps derived by transcranial magnetic stimulation. We extracted 100 equally distributed cross-sections along each streamline of corticospinal tract (CST) for along-tract statistical analysis. Cross-sections were then analyzed to detect differences between healthy and pathological hemispheres. All metrics showed significant differences between healthy and pathologic hemispheres over the entire tract and between peritumoral segments. Peritumoral values were lower for FA and FD, but higher for ADC within the entire cohort. FD was more specific to tumor-induced changes in CST than ADC or FA, whereas ADC and FA showed higher sensitivity. The bihemispheric along-tract analysis provides an approach to detect subject-specific structural changes in healthy and pathological WM. In the current clinical dataset, the more complex FD metrics did not outperform FA and ADC in terms of describing corticospinal tract impairment.

SUBMITTER: Fekonja LS

PROVIDER: S-EPMC7873606 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Detecting Corticospinal Tract Impairment in Tumor Patients With Fiber Density and Tensor-Based Metrics.

Fekonja Lucius S LS Wang Ziqian Z Aydogan Dogu B DB Roine Timo T Engelhardt Melina M Dreyer Felix R FR Vajkoczy Peter P Picht Thomas T

Frontiers in oncology 20210127

Tumors infiltrating the motor system lead to significant disability, often caused by corticospinal tract injury. The delineation of the healthy-pathological white matter (WM) interface area, for which diffusion magnetic resonance imaging (dMRI) has shown promising potential, may improve treatment outcome. However, up to 90% of white matter (WM) voxels include multiple fiber populations, which cannot be correctly described with traditional metrics such as fractional anisotropy (FA) or apparent di ...[more]

PMID: 33585250

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Project description:Abstract Along tract statistics enables white matter characterization using various diffusion MRI metrics. These diffusion models reveal detailed insights into white matter microstructural changes with development, pathology and function. Here, we aim at assessing the clinical utility of diffusion MRI metrics along the corticospinal tract, investigating whether motor glioma patients can be classified with respect to their motor status. We retrospectively included 116 brain tumour patients suffering from either left or right supratentorial, unilateral World Health Organization Grades II, III and IV gliomas with a mean age of 53.51 ± 16.32 years. Around 37% of patients presented with preoperative motor function deficits according to the Medical Research Council scale. At group level comparison, the highest non-overlapping diffusion MRI differences were detected in the superior portion of the tracts’ profiles. Fractional anisotropy and fibre density decrease, apparent diffusion coefficient axial diffusivity and radial diffusivity increase. To predict motor deficits, we developed a method based on a support vector machine using histogram-based features of diffusion MRI tract profiles (e.g. mean, standard deviation, kurtosis and skewness), following a recursive feature elimination method. Our model achieved high performance (74% sensitivity, 75% specificity, 74% overall accuracy and 77% area under the curve). We found that apparent diffusion coefficient, fractional anisotropy and radial diffusivity contributed more than other features to the model. Incorporating the patient demographics and clinical features such as age, tumour World Health Organization grade, tumour location, gender and resting motor threshold did not affect the model’s performance, revealing that these features were not as effective as microstructural measures. These results shed light on the potential patterns of tumour-related microstructural white matter changes in the prediction of functional deficits. Shams et al. report that glioma patients’ motor status is predicted accurately by diffusion MRI metrics along the corticospinal tract based on support vector machine method, reaching an overall accuracy of 77%. They show that these metrics are more effective than demographic and clinical variables. Graphical Abstract Graphical abstract

Project description:BackgroundMotor outcome after stroke is associated with reorganisation of cortical networks and corticospinal tract (CST) integrity. However, the relationships between motor severity, CST damage, and functional brain connectivity are not well understood. Here, the main objective was to study the effect of CST damage on the relationship between functional motor network connectivity and hand motor function in two groups of stroke patients: the severely (n=8) and the mildly impaired (n=14).MethodsTwenty-two carotid stroke patients with motor deficits were studied with magnetic resonance imaging (MRI) at 3 weeks, at 3 and 6 months. Healthy subjects (n=28) were scanned once. The CST injury was assessed by fractional anisotropy values. Functional connectivity was studied from a whole-hand grip task fMRI in a cortical and cerebellar motor network. Functional connectivity indexes were computed between these regions at each time point. The relationship between hand motor strength, ipsilesional CST damage and functional connectivity from the primary motor cortex (M1) was investigated using global and partial correlations.FindingsIn mildly impaired patients, cortico-cortical connectivity was disturbed at three weeks but returned to a normal pattern after 3 months. Cortico-cerebellar connectivity was still decreased at 6 months. In severely impaired patients, the cortico-cortical connectivity tended to return to a normal pattern, but the cortico-cerebellar connectivity was totally abolished during the follow-up. In the entire group of patients, the hand motor strength was correlated to the ipsilesional functional connectivity from M1. Partial correlations revealed that these associations were not anymore significant when the impact of CST damage was removed, except for the ipsilesional M1-contralateral cerebellum connectivity.ConclusionFunctional brain connectivity changes can be observed, even in severely impaired patients with no recovery. Upper limb function is mainly explained by the CST damage and by the ipsilesional cortico-cerebellar connectivity.

Project description:Several studies have questioned the traditional belief that the corticospinal tract (CST) arises exclusively from the precentral gyrus and passes through the anterior half of the posterior limb of the internal capsule (PLIC) in humans; however, no direct evidence existed from structural imaging, and developmental aspects of CST origin have not been clarified. We used diffusion tensor imaging (DTI) tractography to test the hypotheses that CST can originate from both pre- and postcentral gyri and is located posteriorly in the PLIC, and we also determined how age, sex, or handedness affected these locations.Forty-two healthy children (2.6-17.5 years of age; 20 girls) underwent DTI. Subsequently, tractography was performed on the basis of fiber assignment by continuous tracking (FACT) algorithm and brute force approach, with a fractional anisotropy (FA) threshold of <0.2 and an angle threshold of >50 degrees . The CST was isolated by using a knowledge-based region-of-interest approach, and its cortical origin and location on the PLIC was determined.DTI revealed that the CST originated from both pre- and postcentral gyri in 71.4% of hemispheres, from the precentral gyrus only in 19%, and from the postcentral gyrus only in 7.1%. The overall distribution was similar in both hemispheres. However, children with CST originating from both pre- and postcentral gyri were older (mean, 11.1 years of age) than those with precentral origin (mean, 5.8 years of age) or postcentral origin (mean, 7.8 years of age) only (P = .00003). The center of the CST was localized at 65% of the length (from its anterior margin) of the PLIC, and the CST occupied 26.5% of its anteroposterior length. There was a significant positive correlation between age and FA of the CST (r = 0.49; P = .002). The volume of the precentral portion of the left CST was significantly higher than that of its postcentral portion (P = .01) and that of the right CST (P = .0002). The pattern of cortical origin of CST, its location at the level of PLIC, and its volume and FA were unaffected by sex or handedness.The CST most frequently originates from both pre- and postcentral gyri, especially in older children, and is typically centered approximately two thirds of the distance from the anterior margin of the PLIC and occupies about a quarter of its anteroposterior length. In young children, the CST can often be seen originating exclusively from the precentral gyrus by DTI.

Project description:BackgroundAn assessment of the degree of white matter tract injury is important in neurosurgical planning for patients with gliomas. The main objective of this study was to assess the injury grade of the corticospinal tract (CST) in rats with glioma using diffusion tensor imaging (DTI).MethodsA total 17 rats underwent 7.0T MRI on day 10 after tumor implantation. The apparent diffusion coefficient (ADC) and fractional anisotropy (FA) were acquired in the tumor, peritumoral and contralateral areas, and the ADC ratio (ipsilateral ADC/contralateral ADC) and rFA (relative FA = ipsilateral FA/contralateral FA) in the peritumoral areas were measured. The CST injury was divided into three grades and delineated by diffusion tensor tractography reconstruction imaging. The fiber density index (FDi) of the ipsilateral and contralateral CST and rFDi (relative FDi = ipsilateral FDi/contralateral FDi) in the peritumoral areas were measured. After the mice were sacrificed, the invasion of glioma cells and fraction of proliferating cells were observed by hematoxylin-eosin and Ki67 staining in the tumor and peritumoral areas. The correlations among the pathology results, CST injury grade and DTI parameter values were calculated using a Spearman correlation analysis. One-way analysis of variance was performed to compare the different CST injury grade by the rFA, rFDi and ADC ratio values.ResultsThe tumor cells and proliferation index were positively correlated with the CST injury grade (r = 0.8857, 0.9233, P < 0.001). A negative correlation was demonstrated between the tumor cells and the rFA and rFDi values in the peritumoral areas (r = -0.8571, -0.5588), and the proliferation index was negatively correlated with the rFA and rFDi values (r = -0.8571, -0.5588), while the ADC ratio was not correlated with the tumor cells or proliferation index. The rFA values between the CST injury grades (1 and 3, 2 and 3) and the rFDi values in grades 1 and 3 significantly differed (P < 0.05).ConclusionsDiffusion tensor imaging may be used to quantify the injury degrees of CST involving brain glioma in rats. Our data suggest that these quantitative parameters may be used to enhance the efficiency of delineating the relationship between fiber tracts and malignant tumor.

Dataset Information

Detecting Corticospinal Tract Impairment in Tumor Patients With Fiber Density and Tensor-Based Metrics.

Publications

Detecting Corticospinal Tract Impairment in Tumor Patients With Fiber Density and Tensor-Based Metrics.

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