Applications of diffusion-weighted MRI in thoracic spinal cord injury without radiographic abnormality.
Ontology highlight
ABSTRACT:
SUBMITTER: Shen H
PROVIDER: S-EPMC2267593 | biostudies-other | 2007 Jun
REPOSITORIES: biostudies-other
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Project description:IntroductionThis study investigated tissue diffusion properties within the spinal cord of individuals treated for cervical spondylotic myelopathy (CSM) using post-decompression stabilization hardware. While previous research has indicated the potential of diffusion-weighted MRI (DW-MRI) markers of CSM, the metallic implants often used to stabilize the decompressed spine hamper conventional DW-MRI.MethodsUtilizing recent developments in DW-MRI metal-artifact suppression technologies, imaging data was acquired from 38 CSM study participants who had undergone instrumented fusion, as well as asymptomatic (non-instrumented) control participants. Apparent diffusion coefficients were determined in axial slice sections and split into four categories: a) instrumented levels, b) non-instrumented CSM levels, c) adjacent-segment (to instrumentation) CSM levels, and d) non-instrumented control levels. Multi-linear regression models accounting for age, sex, and body mass index were used to investigate ADC measures within each category. Furthermore, the cord diffusivity within CSM subjects was correlated with symptom scores and the duration since fusion procedures.ResultsADC measures of the spinal cord in CSM subjects were globally reduced relative to control subjects (p = 0.005). In addition, instrumented levels within the CSM subjects showed reduced diffusivity relative to controls (p = 0.003), while ADC within non-instrumented CSM levels did not statistically deviate from control levels (p = 0.107).DiscussionMulti-spectral DW-MRI technology can be effectively employed to evaluate cord diffusivity near fusion hardware in subjects who have undergone surgery for CSM. Leveraging this advanced technology, this study had identified significant reductions in cord diffusivity, relative to control subjects, in CSM patients treated with conventional metallic fusion instrumentation.
| S-EPMC10236479 | biostudies-literature
Project description:PurposeDiffusion-weighted imaging has undergone substantial investigation as a potential tool for advanced assessment of spinal cord health. Unfortunately, commonly encountered surgically implanted spinal hardware has historically disrupted these studies. This preliminary investigation applies the recently developed multispectral diffusion-weighted PROPELLER technique to quantitative assessment of the spinal cord immediately adjacent to metallic spinal fusion instrumentation.MethodsMorphological and diffusion-weighted MRI of the spinal cord was collected from 5 subjects with implanted cervical spinal fusion hardware. Conventional and multispectral diffusion-weighted images were also collected on a normative non-instrumented control cohort and utilized for methodological stability analysis. Variance of the ADC values derived from the normative control group was then analyzed on a subject-by-subject basis and qualitatively correlated with clinical morphological interpretations.ResultsNormative control ADC values within the spinal cord were stable across DWI methods for a b value of 600 s/mm2, though this stability degraded at lower b value levels. Susceptibility artifacts precluded conventional DWI analysis of the cord in subjects with spinal fusion hardware in 4 of the 5 test cases. On the contrary, multispectral PROPELLER DWI produced viable ADC measurements within the cord of all 5 instrumented subjects. Instrumented cord regions without obvious pathology (N = 4) showed ADC values that were lower than expected, whereas one subject with diagnosed myelomalacia showed abnormally elevated ADC.ConclusionsIn the absence of instrumentation, multispectral DWI provides quantitative capabilities that match with those of conventional DWI approaches. In a preliminary instrumented subject analysis, cord ADC values showed both expected and unexpected variations from the normative cohort. These slides can be retrieved under Electronic Supplementary Material.
| S-EPMC7225051 | biostudies-literature
Project description:The human spinal cord is a central nervous system structure that plays an important role in normal motor and sensory function, and can be affected by many debilitating neurologic diseases. Due to its clinical importance, the spinal cord is frequently the subject of imaging research. Common methods for visualizing spinal cord anatomy and pathology include histology and magnetic resonance imaging (MRI), both of which have unique benefits and drawbacks. Postmortem microscopic resolution MRI of fixed specimens, sometimes referred to as magnetic resonance microscopy (MRM), combines many of the benefits inherent to both techniques. However, the elongated shape of the human spinal cord, along with hardware and scan time limitations, have restricted previous microscopic resolution MRI studies (both in vivo and ex vivo) to small sections of the cord. Here we present the first MRM dataset of the entire postmortem human spinal cord. These data include 50 μm isotropic resolution anatomic image data and 100 μm isotropic resolution diffusion data, made possible by a 280 h long multi-segment acquisition and automated image segment composition. We demonstrate the use of these data for spinal cord lesion detection, automated volumetric gray matter segmentation, and quantitative spinal cord morphometry including estimates of cross sectional dimensions and gray matter fraction throughout the length of the cord.
| S-EPMC5988447 | biostudies-literature
Project description:ObjectivesCytogenetic abnormalities are predictors of poor prognosis in multiple myeloma (MM). This paper aims to build and validate a multiparametric conventional and functional whole-body MRI-based prediction model for cytogenetic risk classification in newly diagnosed MM.MethodsPatients with newly diagnosed MM who underwent multiparametric conventional whole-body MRI, spinal dynamic contrast-enhanced (DCE-)MRI, spinal diffusion-weighted MRI (DWI) and had genetic analysis were retrospectively included (2011-2020/Ghent University Hospital/Belgium). Patients were stratified into standard versus intermediate/high cytogenetic risk groups. After segmentation, 303 MRI features were extracted. Univariate and model-based methods were evaluated for feature and model selection. Testing was performed using receiver operating characteristic (ROC) and precision-recall curves. Models comparing the performance for genetic risk classification of the entire MRI protocol and of all MRI sequences separately were evaluated, including all features. Four final models, including only the top three most predictive features, were evaluated.ResultsThirty-one patients were enrolled (mean age 66 ± 7 years, 15 men, 13 intermediate-/high-risk genetics). None of the univariate models and none of the models with all features included achieved good performance. The best performing model with only the three most predictive features and including all MRI sequences reached a ROC-area-under-the-curve of 0.80 and precision-recall-area-under-the-curve of 0.79. The highest statistical performance was reached when all three MRI sequences were combined (conventional whole-body MRI + DCE-MRI + DWI). Conventional MRI always outperformed the other sequences. DCE-MRI always outperformed DWI, except for specificity.ConclusionsA multiparametric MRI-based model has a better performance in the noninvasive prediction of high-risk cytogenetics in newly diagnosed MM than conventional MRI alone.Critical relevance statementAn elaborate multiparametric MRI-based model performs better than conventional MRI alone for the noninvasive prediction of high-risk cytogenetics in newly diagnosed multiple myeloma; this opens opportunities to assess genetic heterogeneity thus overcoming sampling bias.Key points• Standard genetic techniques in multiple myeloma patients suffer from sampling bias due to tumoral heterogeneity. • Multiparametric MRI noninvasively predicts genetic risk in multiple myeloma. • Combined conventional anatomical MRI, DCE-MRI, and DWI had the highest statistical performance to predict genetic risk. • Conventional MRI alone always outperformed DCE-MRI and DWI separately to predict genetic risk. DCE-MRI alone always outperformed DWI separately, except for the parameter specificity to predict genetic risk. • This multiparametric MRI-based genetic risk prediction model opens opportunities to noninvasively assess genetic heterogeneity thereby overcoming sampling bias in predicting genetic risk in multiple myeloma.
| S-EPMC11006637 | biostudies-literature
Project description:Neurogenic thoracic outlet syndrome (N-TOS) is a chronic compressive brachial plexopathy that involves the C8, T1 roots, and/or lower trunk. Medial antebrachial cutaneous (MABC) nerve conduction study (NCS) abnormality is reportedly one of the most sensitive findings among the features of N-TOS. The aim of the present study was to report clinical features, imaging findings, treatment, and prognoses of two N-TOS patients with no abnormalities in electrophysiological studies. Both patients presented with paresthesia of unilateral arm, and examination revealed no neurologic deficits. Electrophysiologic studies including MABC NCS were normal. Computed tomography (CT) angiography and brachial plexus magnetic resonance imaging (MRI) of the patients showed compression and displacement of the neurovascular bundle in the thoracic outlet by causative structures. Due to their sensory symptoms and CT angiography and brachial plexus MRI findings, after excluding other diseases, we diagnosed them with N-TOS. With the development of imaging techniques, more patients presenting with clinical features of lower trunk brachial plexopathy and anomalous structures compressing the neurovascular bundle on imaging studies can be diagnosed with N-TOS, even if electrophysiologic studies including MABC NCS do not show abnormalities.
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Project description:The DREAM study will assess the diagnostic accuracy of diffusion-weighted MRI in combination with other imaging modalities (multiparametric MRI and CT Scan) in determining the true status of disappearing liver metastasis (DLM) detected after conversion systemic therapy for unresectable or borderline resectable colorectal liver metastasis (CRLM).
| 2215891 | ecrin-mdr-crc
Project description:Some studies have suggested that early surgical treatment can effectively improve the prognosis of cervical spinal cord injury without radiological abnormality, but no research has focused on the development of a prognostic model of cervical spinal cord injury without radiological abnormality. This retrospective analysis included 43 patients with cervical spinal cord injury without radiological abnormality. Seven potential factors were assessed: age, sex, external force strength causing damage, duration of disease, degree of cervical spinal stenosis, Japanese Orthopaedic Association score, and physiological cervical curvature. A model was established using multiple binary logistic regression analysis. The model was evaluated by concordant profiling and the area under the receiver operating characteristic curve. Bootstrapping was used for internal validation. The prognostic model was as follows: logit(P) = -25.4545 + 21.2576VALUE + 1.2160SCORE - 3.4224TIME, where VALUE refers to the Pavlov ratio indicating the extent of cervical spinal stenosis, SCORE refers to the Japanese Orthopaedic Association score (0-17) after the operation, and TIME refers to the disease duration (from injury to operation). The area under the receiver operating characteristic curve for all patients was 0.8941 (95% confidence interval, 0.7930-0.9952). Three factors assessed in the predictive model were associated with patient outcomes: a great extent of cervical stenosis, a poor preoperative neurological status, and a long disease duration. These three factors could worsen patient outcomes. Moreover, the disease prognosis was considered good when logit(P) ≥ -2.5105. Overall, the model displayed a certain clinical value. This study was approved by the Biomedical Ethics Committee of the Second Affiliated Hospital of Xi'an Jiaotong University, China (approval number: 2018063) on May 8, 2018.
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Project description:Diffusion magnetic resonance images may suffer from geometric distortions due to susceptibility induced off resonance fields, which cause geometric mismatch with anatomical images and ultimately affect subsequent quantification of microstructural or connectivity indices. State-of-the art diffusion distortion correction methods typically require data acquired with reverse phase encoding directions, resulting in varying magnitudes and orientations of distortion, which allow estimation of an undistorted volume. Alternatively, additional field maps acquisitions can be used along with sequence information to determine warping fields. However, not all imaging protocols include these additional scans and cannot take advantage of state-of-the art distortion correction. To avoid additional acquisitions, structural MRI (undistorted scans) can be used as registration targets for intensity driven correction. In this study, we aim to (1) enable susceptibility distortion correction with historical and/or limited diffusion datasets that do not include specific sequences for distortion correction and (2) avoid the computationally intensive registration procedure typically required for distortion correction using structural scans. To achieve these aims, we use deep learning (3D U-nets) to synthesize an undistorted b0 image that matches geometry of structural T1w images and intensity contrasts from diffusion images. Importantly, the training dataset is heterogenous, consisting of varying acquisitions of both structural and diffusion. We apply our approach to a withheld test set and show that distortions are successfully corrected after processing. We quantitatively evaluate the proposed distortion correction and intensity-based registration against state-of-the-art distortion correction (FSL topup). The results illustrate that the proposed pipeline results in b0 images that are geometrically similar to non-distorted structural images, and more closely match state-of-the-art correction with additional acquisitions. In addition, we show generalizability of the proposed approach to datasets that were not in the original training / validation / testing datasets. These datasets included varying populations, contrasts, resolutions, and magnitudes and orientations of distortion and show efficacious distortion correction. The method is available as a Singularity container, source code, and an executable trained model to facilitate evaluation.
| S-EPMC7394453 | biostudies-literature
Project description:Neural tissue is a hierarchical multiscale system with intracellular and extracellular diffusion compartments at different length scales. The normal diffusion of bulk water in tissues is not able to detect the specific features of a complex system, providing nonlocal, diffusion measurement averaged on a 10-20 μm length scale. Being able to probe tissues with sub-micrometric diffusion length and quantify new local parameters, transient anomalous diffusion (tAD) would dramatically increase the diagnostic potential of diffusion MRI (DMRI) in detecting collective and sub-micro architectural changes of human tissues due to pathological damage. In DMRI, the use of tAD parameters quantified using specific DMRI acquisition protocols and their interpretation has often aroused skepticism. Although the derived formulas may accurately fit experimental diffusion-weighted data, the relationships between the postulated dynamical feature and the underlying geometrical structure remains elusive, or at most only suggestive. This work aimed to elucidate and validate the image contrast and information that can be obtained using the tAD model in white matter (WM) through a direct comparison between different diffusion metrics and histology. Towards this goal, we compared tAD metrics extracted from pure subdiffusion (α-imaging) and super-pseudodiffusion (γ-imaging) in excised mouse spinal cord WM, together with T2 and T2* relaxometry, conventional (normal diffusion-based) diffusion tensor imaging (DTI) and q-space imaging (QSI), with morphologic measures obtained by optical microscopy, to determine which structural and topological characteristics of myelinated axons influenced tAD contrast. Axon diameter (AxDiam), the standard deviation of diameters (SD ax.diam ), axonal density (AxDens) and effective local density (ELD) were extracted from optical images in several WM tracts. Among all the diffusion parameters obtained at 9.4 T, γ-metrics confirmed a strong dependence on magnetic in-homogeneities quantified by R2* = 1/T2* and showed the strongest associations with AxDiam and ELD. On the other hand, α-metrics showed strong associations with SD ax.diam and was significantly related to AxDens, suggesting its ability to quantify local heterogeneity degree in neural tissue. These results elucidate the biophysical mechanism underpinning tAD parameters and show the clinical potential of tAD-imaging, considering that both physiologic and pathologic neurodegeneration translate into alterations of WM morphometry and topology.
| S-EPMC8885723 | biostudies-literature
Project description:OBJECTIVE:To investigate the clinical feasibility of synthetic diffusion-weighted imaging (sDWI) at different b-values in patients with breast cancer by assessing the diagnostic image quality and the quantitative measurements compared with conventional diffusion-weighted imaging (cDWI). MATERIALS AND METHODS:Fifty patients with breast cancer were assessed using cDWI at b-values of 800 and 1500 s/mm² (cDWI800 and cDWI1500) and sDWI at b-values of 1000 and 1500 s/mm² (sDWI1000 and sDWI1500). Qualitative analysis (normal glandular tissue suppression, overall image quality, and lesion conspicuity) was performed using a 4-point Likert-scale for all DWI sets and the cancer detection rate (CDR) was calculated. We also evaluated cancer-to-parenchyma contrast ratios for each DWI set in 45 patients with the lesion identified on any of the DWI sets. Statistical comparisons were performed using Friedman test, one-way analysis of variance, and Cochran's Q test. RESULTS:All parameters of qualitative analysis, cancer-to-parenchyma contrast ratios, and CDR increased with increasing b-values, regardless of the type of imaging (synthetic or conventional) (p < 0.001). Additionally, sDWI1500 provided better lesion conspicuity than cDWI1500 (3.52 ± 0.92 vs. 3.39 ± 0.90, p < 0.05). Although cDWI1500 showed better normal glandular tissue suppression and overall image quality than sDWI1500 (3.66 ± 0.78 and 3.73 ± 0.62 vs. 3.32 ± 0.90 and 3.35 ± 0.81, respectively; p < 0.05), there was no significant difference in their CDR (90.0%). Cancer-to-parenchyma contrast ratios were greater in sDWI1500 than in cDWI1500 (0.63 ± 0.17 vs. 0.55 ± 0.18, p < 0.001). CONCLUSION:sDWI1500 can be feasible for evaluating breast cancers in clinical practice. It provides higher tumor conspicuity, better cancer-to-parenchyma contrast ratio, and comparable CDR when compared with cDWI1500.
| S-EPMC7371621 | biostudies-literature