MR Imaging of the Perihepatic Space.
Ontology highlight
ABSTRACT:
SUBMITTER: Bonnin A
PROVIDER: S-EPMC8005346 | biostudies-literature | 2021 Apr
REPOSITORIES: biostudies-literature
Publications
MR Imaging of the Perihepatic Space.
Bonnin Angèle A Durot Carole C Djelouah Manel M Dohan Anthony A Arrivé Lionel L Rousset Pascal P Hoeffel Christine C
Korean journal of radiology 20201119 4
The perihepatic space is frequently involved in a spectrum of diseases, including intrahepatic lesions extending to the liver capsule and disease conditions involving adjacent organs extending to the perihepatic space or spreading thanks to the communication from intraperitoneal or extraperitoneal sites through the hepatic ligaments. Lesions resulting from the dissemination of peritoneal processes may also affect the perihepatic space. Here we discuss how to assess the perihepatic origin of a le ...[more]
Similar Datasets
Project description:PurposeTo develop a robust and rapid imaging technique for hyperpolarized (13)C MR Spectroscopic Imaging and investigate its performance.MethodsA concentric rings readout trajectory with constant angular velocity is proposed for hyperpolarized (13)C spectroscopic imaging and its properties are analyzed. Quantitative analyses of design tradeoffs are presented for several imaging scenarios. The first application of concentric rings on (13)C phantoms and in vivo animal hyperpolarized (13)C MR Spectroscopic Imaging studies were performed to demonstrate the feasibility of the proposed method. Finally, a parallel imaging accelerated concentric rings study is presented.ResultsThe concentric rings MR Spectroscopic Imaging trajectory has the advantages of acquisition timesaving compared to echo-planar spectroscopic imaging. It provides sufficient spectral bandwidth with relatively high efficiency compared to echo-planar spectroscopic imaging and spiral techniques. Phantom and in vivo animal studies showed good image quality with half the scan time and reduced pulsatile flow artifacts compared to echo-planar spectroscopic imaging. Parallel imaging accelerated concentric rings showed advantages over Cartesian sampling in g-factor simulations and demonstrated aliasing-free image quality in a hyperpolarized (13)C in vivo study.ConclusionThe concentric rings trajectory is a robust and rapid imaging technique that fits very well with the speed, bandwidth, and resolution requirements of hyperpolarized (13)C MR Spectroscopic Imaging.
| S-EPMC4476971 | biostudies-literature
Project description:PurposeTo develop a manifold learning-based method that leverages the intrinsic low-dimensional structure of MR Spectroscopic Imaging (MRSI) signals for joint spectral quantification.MethodsA linear tangent space alignment (LTSA) model was proposed to represent MRSI signals. In the proposed model, the signals of each metabolite were represented using a subspace model and the local coordinates of the subspaces were aligned to the global coordinates of the underlying low-dimensional manifold via linear transform. With the basis functions of the subspaces predetermined via quantum mechanics simulations, the global coordinates and the matrices for the local-to-global coordinate alignment were estimated by fitting the proposed LTSA model to noisy MRSI data with a spatial smoothness constraint on the global coordinates and a sparsity constraint on the matrices.ResultsThe performance of the proposed method was validated using numerical simulation data and in vivo proton-MRSI experimental data acquired on healthy volunteers at 3T. The results of the proposed method were compared with the QUEST method and the subspace-based method. In all the compared cases, the proposed method achieved superior performance over the QUEST and the subspace-based methods both qualitatively in terms of noise and artifacts in the estimated metabolite concentration maps, and quantitatively in terms of spectral quantification accuracy measured by normalized root mean square errors.ConclusionJoint spectral quantification using linear tangent space alignment-based manifold learning improves the accuracy of MRSI spectral quantification.
| S-EPMC9892363 | biostudies-literature
Project description:A novel denoising algorithm termed k-space weighted image average (KWIA) was proposed to improve the signal-to-noise ratio (SNR) of dynamic MRI, such as arterial spin labeling (ASL)-based dynamic magnetic resonance angiography (dMRA) and perfusion imaging. KWIA divides the k-space of each time frame into multiple rings, the central ring of the k-space remains intact to preserve the image contrast and temporal resolution, while outer rings are progressively averaged with neighboring time frames to increase SNR. Simulations and in-vivo dMRA and multi-delay ASL studies were performed to evaluate the performance of KWIA under various MRI acquisition conditions. SNR ratios and temporal signal errors between KWIA-processed and the original data were measured. Visualization of dynamic blood flow signals as well as quantitative parametric maps were evaluated for KWIA-processed images as compared to the original images. KWIA achieved a SNR ratio of 1.73 for dMRA and 2.0 for multi-delay ASL respectively, which were in accordance with the theoretical predictions. Improved visualization of dynamic blood flow signals was demonstrated using KWIA in distal small vessels in dMRA and small brain structures in multi-delay ASL. Approximately 5% temporal errors were observed in both KWIA-processed dMRA and ASL signals. Fine anatomical features were revealed in the quantitative parametric maps of dMRA, and the residuals of model fitting were reduced for multi-delay ASL. Compared to other conventional denoising methods, KWIA is a flexible denoising algorithm that improves the SNR of ASL-based dMRA and perfusion MRI by up to 2-fold without compromising spatial and temporal resolution or quantification accuracy.
| S-EPMC8713133 | biostudies-literature
Project description:Background and purposeA number of parameters derived from dynamic contrast-enhanced MR imaging and separate histologic features have been identified as potential prognosticators in high-grade glioma. This study evaluated the relationships between dynamic contrast-enhanced MRI-derived parameters and histologic features in glioblastoma multiforme.Materials and methodsTwenty-eight patients with newly presenting glioblastoma multiforme underwent preoperative imaging (conventional imaging and T1 dynamic contrast-enhanced MRI). Parametric maps of the initial area under the contrast agent concentration curve, contrast transfer coefficient, estimate of volume of the extravascular extracellular space, and estimate of blood plasma volume were generated, and the enhancing fraction was calculated. Surgical specimens were used to assess subtype and were graded (World Health Organization classification system) and were assessed for necrosis, cell density, cellular atypia, mitotic activity, and overall vascularity scores. Quantitative assessment of endothelial surface area, vascular surface area, and a vascular profile count were made by using CD34 immunostaining. The relationships between MR imaging parameters and histopathologic features were examined.ResultsHigh values of contrast transfer coefficient were associated with the presence of frank necrosis (P = .005). High values of the estimate of volume of the extravascular extracellular space were associated with a fibrillary histologic pattern (P < .01) and with increased mitotic activity (P < .05). No relationship was found between mitotic activity and histologic pattern, suggesting that the correlation between the estimate of volume of the extravascular extracellular space and mitotic activity was independent of the histologic pattern.ConclusionsA correlation between the estimate of volume of the extravascular extracellular space and mitotic activity is reported. Further work is warranted to establish how dynamic contrast-enhanced MRI parameters relate to more quantitative histologic measurements, including markers of proliferation and measures of vascular endothelial growth factor expression.
| S-EPMC4817231 | biostudies-literature
Project description:ObjectiveHypoxic-ischemic encephalopathy can lead to lifelong morbidity and premature death in full-term newborns. Here, we aimed to determine the efficacy of diffusion kurtosis (DK) [mean kurtosis (MK)] and diffusion tensor (DT) [fractional anisotropy (FA), mean diffusion (MD), axial diffusion (AD), and radial diffusion (RD)] parameters for the early diagnosis of early brain histopathological changes and the prediction of neurodegenerative events in a full-term neonatal hypoxic-ischemic brain injury (HIBD) rat model.MethodsThe HIBD model was generated in postnatal day 7 Sprague-Dawley rats to assess the changes in DK and DT parameters in 10 specific brain structural regions involving the gray matter, white matter, and limbic system during acute (12 h) and subacute (3 d and 5 d) phases after hypoxic ischemia (HI), which were validated against histology. Sensory and cognitive parameters were assessed by the open field, novel object recognition, elevated plus maze, and CatWalk tests.ResultsRepeated-measures ANOVA revealed that specific brain structures showed similar trends to the lesion, and the temporal pattern of MK was substantially more varied than DT parameters, particularly in the deep gray matter. The change rate of MK in the acute phase (12 h) was significantly higher than that of DT parameters. We noted a delayed pseudo-normalization for MK. Additionally, MD, AD, and RD showed more pronounced differences between males and females after HI compared to MK, which was confirmed in behavioral tests. HI females exhibited anxiolytic hyperactivity-like baseline behavior, while the memory ability of HI males was affected in the novel object recognition test. CatWalk assessments revealed chronic deficits in limb gait parameters, particularly the left front paw and right hind paw, as well as poorer performance in HI males than HI females.ConclusionsOur results suggested that DK and DT parameters were complementary in the immature brain and provided great value in assessing early tissue microstructural changes and predicting long-term neurobehavioral deficits, highlighting their ability to detect both acute and long-term changes. Thus, the various diffusion coefficient parameters estimated by the DKI model are powerful tools for early HIBD diagnosis and prognosis assessment, thus providing an experimental and theoretical basis for clinical treatment.
| S-EPMC10543095 | biostudies-literature
Project description:ObjectivesTo quantify the brain maturation process during childhood using combined amide proton transfer (APT) and conventional magnetization transfer (MT) imaging at 3 Tesla.MethodsEighty-two neurodevelopmentally normal children (44 males and 38 females; age range, 2-190 months) were imaged using an APT/MT imaging protocol with multiple saturation frequency offsets. The APT-weighted (APTW) and MT ratio (MTR) signals were quantitatively analyzed in multiple brain areas. Age-related changes in MTR and APTW were evaluated with a non-linear regression analysis.ResultsThe APTW signals followed a decreasing exponential curve with age in all brain regions measured (R(2) = 0.7-0.8 for the corpus callosum, frontal and occipital white matter, and centrum semiovale). The most significant changes appeared within the first year. At maturation, larger decreases in APTW and lower APTW values were found in the white matter. On the contrary, the MTR signals followed an increasing exponential curve with age in the same brain regions measured, with the most significant changes appearing within the initial 2 years. There was an inverse correlation between the MTR and APTW signal intensities during brain maturation.ConclusionsTogether with MT imaging, protein-based APT imaging can provide additional information in assessing brain myelination in the paediatric population.Key points• APTW signals followed a decreasing exponential curve with age. • The most significant APTW changes appeared within the first year • At maturation, larger APTW decreases and lower APTW appeared in white matter • MTR signals followed an increasing exponential curve with age.
| S-EPMC5747245 | biostudies-literature
Project description:Current risk stratification for stroke is still based upon percentage of carotid stenosis, despite this measure providing minimal patient-specific information on the actual risk of stroke for both symptomatic individuals without significant carotid artery stenosis as well as asymptomatic carotid stenosis patients. A continuously growing body of literature suggests that the identification and quantification of certain carotid plaque characteristics, including lipid-rich necrotic core (LRNC), thin/ruptured fibrous cap (FC), and intraplaque hemorrhage (IPH), provide a superior means of predicting future stroke. These characteristics are identifiable via magnetic resonance imaging (MRI), with most features detectable using commercially available coils and sequences utilized in routine clinical practice in as little as 4 minutes. The presence of LRNC, a thin/ruptured FC, and IPH is associated with increased risk of future stroke or TIA. Plaques with greater than 40% LRNC with a thin overlying FC are prone to rupture. LRNC is T2 hypointense and lacks enhancement on contrast enhanced T1 weighted images. Increasing LRNC size is associated with the development of new ulceration, FC rupture, increasing plaque burden, as well as fatal and nonfatal myocardial infarction, ischemic stroke, hospitalization for acute coronary syndrome (ACS), and symptom-driven revascularization, allowing for MR biomarkers of carotid plaque vulnerability to be utilized for systemic athero-thrombotic risk and not just stroke/TIA. LRNC typically shrinks with appropriate statin therapy, with PCSK9 inhibitors possibly playing a role in patients with inadequate response. Carotid plaques with IPH represent a more advanced stage of atherosclerotic disease. IPH is detectable with field strengths of both 3.0 T and 1.5 T and will demonstrate high signal on all T1 weighted imaging sequences. The presence of IPH increases the risk of future stroke in both symptomatic and asymptomatic patients, with multivariate analysis identifying IPH as a predictor of stroke, independent of percent stenosis, with no statistical difference in men vs. women, demonstrating that simple carotid stenosis measurements and traditional risk factor analysis may be inadequate in identifying patients at the highest risk for adverse cerebrovascular events. In the evaluation for recurrent stroke in recently symptomatic patients with >50% carotid stenosis, the estimated annual stroke risk is 23.2% in IPH+ patients and only 0.6% in IPH- patients, calling into question the current risk-benefit assessment for CEA. Additionally, a recent meta-analysis suggests that IPH+ plaque in patients with symptomatic <50% stenosis may be the etiology of embolic strokes previously labeled as "embolic stroke of undetermined source" (ESUS). There are no prospective drug trials testing the ability of any lipid-lowering therapies to decrease IPH and/or total plaque volume (TPV). Given the continuously increasing evidence of IPH as a significant predictor of carotid plaque progression and future adverse vascular events, trials aimed at targeted therapy for IPH represents a significant need.
| S-EPMC7487401 | biostudies-literature
Project description:Breast MR imaging is the most sensitive imaging method for the detection of breast cancer and detects more aggressive malignancies than mammography and ultrasound examination. Despite these advantages, breast MR imaging has low use rates for breast cancer screening. Abbreviated breast MR imaging, in which a limited number of breast imaging sequences are obtained, has been proposed as a way to solve cost and patient tolerance issues while preserving the high cancer detection rate of breast MR imaging. This review discusses abbreviated breast MR imaging, including protocols, multicenter clinical trial results, clinical workflow implementation challenges, and future directions.
| S-EPMC8211370 | biostudies-literature
Project description:To summarize the distribution of glioma location within a patient population, registration of individual MR images to anatomical reference space is required. In this study, we quantified the accuracy of MR image registration to anatomical reference space with linear and non-linear transformations using estimated tumor targets of glioblastoma and lower-grade glioma, and anatomical landmarks at pre- and post-operative time-points using six commonly used registration packages (FSL, SPM5, DARTEL, ANTs, Elastix, and NiftyReg). Routine clinical pre- and post-operative, post-contrast T1-weighted images of 20 patients with glioblastoma and 20 with lower-grade glioma were collected. The 2009a Montreal Neurological Institute brain template was used as anatomical reference space. Tumors were manually segmented in the patient space and corresponding healthy tissue was delineated as a target volume in the anatomical reference space. Accuracy of the tumor alignment was quantified using the Dice score and the Hausdorff distance. To measure the accuracy of general brain alignment, anatomical landmarks were placed in patient and in anatomical reference space, and the landmark distance after registration was quantified. Lower-grade gliomas were registered more accurately than glioblastoma. Registration accuracy for pre- and post-operative MR images did not differ. SPM5 and DARTEL registered tumors most accurate, and FSL least accurate. Non-linear transformations resulted in more accurate general brain alignment than linear transformations, but tumor alignment was similar between linear and non-linear transformation. We conclude that linear transformation suffices to summarize glioma locations in anatomical reference space.
| S-EPMC7290158 | biostudies-literature
Project description:Background and purposeThe surgical approach to parotid tumors is different for benign and malignant neoplasms, but the clinical symptoms do not correlate well with histology. Difficulties in tumor classification also arise in imaging modalities, in which sonography has the lowest and MR imaging, the highest accuracy. The purpose of this study was to review our experience using conventional MR imaging of the neck in the evaluation of parotid tumors and to evaluate which MR imaging findings are best able to predict malignant histology.Materials and methodsEighty-four consecutive patients (43 males, 41 females; median age, 56 years; range, 9-85 years) with parotid gland tumors who underwent MR imaging before surgery were prospectively included in the present study and retrospectively analyzed. Histology was available for all tumors. We analyzed the following MR imaging parameters: signal intensity, contrast enhancement, lesion margins (well-defined versus ill-defined), lesion location (deep/superficial lobe), growth pattern (focal, multifocal, or diffuse), and extension into neighboring structures, perineural spread, and lymphadenopathy.ResultsThe 57 (68%) benign and 27 (32%) malignant tumors consisted of 29 pleomorphic adenomas, 17 Warthin tumors, 11 various benign tumors, 5 mucoepidermoid carcinomas, 3 adenoid cystic carcinomas, 1 acinic cell carcinoma, 1 carcinoma ex pleomorphic adenoma, 9 metastases, and 8 various malignant neoplasms. Specific signs predictive of malignancy were the following: T2 hypointensity of the parotid tumor (P = .048), ill-defined margins (P = .001), diffuse growth (P = .012), infiltration of subcutaneous tissue (P = .0034), and lymphadenopathy (P = .012).ConclusionsLow signal intensity on T2-weighted images and postcontrast ill-defined margins of a parotid tumor are highly suggestive of malignancy.
| S-EPMC7966029 | biostudies-literature