Automated whole-brain N-acetylaspartate proton MRS quantification.
Ontology highlight
ABSTRACT:
SUBMITTER: Soher BJ
PROVIDER: S-EPMC4212831 | biostudies-other | 2014 Nov
REPOSITORIES: biostudies-other
Similar Datasets
Project description:Proton MRS (1 H MRS) provides noninvasive, quantitative metabolite profiles of tissue and has been shown to aid the clinical management of several brain diseases. Although most modern clinical MR scanners support MRS capabilities, routine use is largely restricted to specialized centers with good access to MR research support. Widespread adoption has been slow for several reasons, and technical challenges toward obtaining reliable good-quality results have been identified as a contributing factor. Considerable progress has been made by the research community to address many of these challenges, and in this paper a consensus is presented on deficiencies in widely available MRS methodology and validated improvements that are currently in routine use at several clinical research institutions. In particular, the localization error for the PRESS localization sequence was found to be unacceptably high at 3 T, and use of the semi-adiabatic localization by adiabatic selective refocusing sequence is a recommended solution. Incorporation of simulated metabolite basis sets into analysis routines is recommended for reliably capturing the full spectral detail available from short TE acquisitions. In addition, the importance of achieving a highly homogenous static magnetic field (B0 ) in the acquisition region is emphasized, and the limitations of current methods and hardware are discussed. Most recommendations require only software improvements, greatly enhancing the capabilities of clinical MRS on existing hardware. Implementation of these recommendations should strengthen current clinical applications and advance progress toward developing and validating new MRS biomarkers for clinical use.
| S-EPMC7179569 | biostudies-literature
Project description:BACKGROUND:The possible role of glutamate in the pathophysiology and treatment of depression is of intense current interest. Proton magnetic resonance spectroscopy (MRS) enables the detection of glutamate in the living human brain and meta-analyses of previous MRS studies in depressed patients have suggested that glutamate levels are decreased in anterior brain regions. Nevertheless, at conventional magnetic field strengths [1.5-3 Tesla (T)], it is difficult to separate glutamate from its metabolite and precursor, glutamine, with the two often being measured together as Glx. In contrast, MRS at 7 T allows clear spectral resolution of glutamate and glutamine. METHOD:We studied 55 un-medicated depressed patients and 50 healthy controls who underwent MRS scanning at 7 T with voxels placed in anterior cingulate cortex, occipital cortex and putamen (PUT). Neurometabolites were calculated using the unsuppressed water signal as a reference. RESULTS:Compared with controls, depressed patients showed no significant difference in glutamate in any of the three voxels studied; however, glutamine concentrations in the patients were elevated by about 12% in the PUT (p < 0.001). CONCLUSIONS:The increase in glutamine in PUT is of interest in view of the postulated role of the basal ganglia in the neuropsychology of depression and is consistent with elevated activity in the descending cortical glutamatergic innervation to the PUT. The basal ganglia have rarely been the subject of MRS investigations in depressed patients and further MRS studies of these structures in depression are warranted.
| S-EPMC6088784 | biostudies-literature
Project description:BackgroundLamotrigine is a useful treatment in bipolar depression but requires several weeks of dose titration before its clinical effects can be assessed. Animal experimental studies suggest that lamotrigine lowers glutamate release. The aim of the current study was to assess the effect of lamotrigine on brain glutamate in depressed bipolar patients and to determine whether baseline glutamate could be used to predict clinical response.MethodsWe studied 21 bipolar patients who received lamotrigine treatment for a current episode of depression. Before starting lamotrigine and after 10-12 weeks treatment, patients underwent proton magnetic resonance spectroscopy (MRS) scanning at 3 Tesla where levels of glutamate (measured as Glx) were determined in anterior cingulate cortex (ACC).ResultsOverall, lamotrigine treatment had no significant effect on Glx levels in ACC. However, in patients who responded clinically to lamotrigine treatment Glx concentrations were significantly increased. Baseline levels of Glx did not predict response to lamotrigine.LimitationsThe main limitation of the study was the modest sample size. Most patients were medicated which may have modified the effect of lamotrigine on glutamate activity. MRS at 3T cannot give a reliable estimate of glutamate separate from its main metabolite, glutamine, and thus changes in Glx may not give a precise estimate of effects of lamotrigine on glutamate itself.ConclusionLamotrigine does not appear to have a direct effect on glutamate levels in ACC in bipolar patients. However, therapeutic improvement during lamotrigine was associated with increased Glx, suggesting that alterations in glutamatergic activity might be related to recovery from bipolar depression.
| S-EPMC6368663 | biostudies-literature
Project description:IntroductionPodocyte depletion is a histomorphologic indicator of glomerular injury and predicts clinical outcomes. Podocyte estimation methods or podometrics are semiquantitative, technically involved, and laborious. Implementation of high-throughput podometrics in experimental and clinical workflows necessitates an automated podometrics pipeline. Recognizing that computational image analysis offers a robust approach to study cell and tissue structure, we developed and validated PodoCount (a computational tool for automated podocyte quantification in immunohistochemically labeled tissues) using a diverse data set.MethodsWhole-slide images (WSIs) of tissues immunostained with a podocyte nuclear marker and periodic acid-Schiff counterstain were acquired. The data set consisted of murine whole kidney sections (n = 135) from 6 disease models and human kidney biopsy specimens from patients with diabetic nephropathy (DN) (n = 45). Within segmented glomeruli, podocytes were extracted and image analysis was applied to compute measures of podocyte depletion and nuclear morphometry. Computational performance evaluation and statistical testing were performed to validate podometric and associated image features. PodoCount was disbursed as an open-source, cloud-based computational tool.ResultsPodoCount produced highly accurate podocyte quantification when benchmarked against existing methods. Podocyte nuclear profiles were identified with 0.98 accuracy and segmented with 0.85 sensitivity and 0.99 specificity. Errors in podocyte count were bounded by 1 podocyte per glomerulus. Podocyte-specific image features were found to be significant predictors of disease state, proteinuria, and clinical outcome.ConclusionPodoCount offers high-performance podocyte quantitation in diverse murine disease models and in human kidney biopsy specimens. Resultant features offer significant correlation with associated metadata and outcome. Our cloud-based tool will provide end users with a standardized approach for automated podometrics from gigapixel-sized WSIs.
| S-EPMC9174049 | biostudies-literature
Project description:The differentiation grade of cervical cancer is histologically assessed by examining biopsies or surgical specimens. MRS is a highly sensitive technique that images tissue metabolism and can be used to increase the specificity of tissue characterization in a non-invasive manner. We aim to explore the feasibility of using in vivo 1 H-MRS at 7 T in women with cervical cancer to study tissue fatty acid composition. 10 women with histologically proven Stage IB1-IIB cervical cancer were scanned with a whole-body 7 T MR system with a multi-transmit system and an internal receive only monopole antenna. A STEAM sequence was used to obtain 1 H-MRS data. Fatty acid resonances were fitted with Lorentzian curves and the 2.1 ppm/1.3 ppm ratios were calculated. 1 H-MRS data showed fatty acid signals resonating at 2.1 ppm, 1.9 ppm, 1.5 ppm, 1.3 ppm and 0.9 ppm. Mean 2.1/1.3 ppm ratios were 0.019 ± 0.01, 0.021 ± 0.006, 0.12 ± 0.089 and 0.39 ± 0.27 for normal, Grade I, Grade II and Grade III groups respectively. Poorly differentiated tumor tissue (Grade III) showed elevated fatty acid ratios when compared with the well differentiated tumor (Grade I) or normal tissue. 1 H-MRS in cervical cancer at 7 T is feasible and individual fatty acid signals were detected. In addition, poorly differentiated tumors show more fatty acid unsaturation. The 2.1 ppm/1.3 ppm ratio has potential for tumor characterization in a non-invasive manner for uterine cervical cancer.
| S-EPMC6588007 | biostudies-literature
Project description:Neonatal hypoxic-ischemic brain injury (HII) and arterial ischemic stroke (AIS) result in irreversibly injured (core) and salvageable (penumbral) tissue regions. Identification and reliable quantification of salvageable tissue is pivotal to any effective and safe intervention. Magnetic resonance imaging (MRI) is the current standard to distinguish core from penumbra using diffusion-perfusion mismatch (DPM). However, subtle MR signal variations between core-penumbral regions make their visual delineation difficult. We hypothesized that computational analysis of MRI data provides a more accurate assessment of core and penumbral tissue evolution in HII/AIS. We used two neonatal rat-pup models of HII/AIS (unilateral and global hypoxic-ischemia) and clinical data sets from neonates with AIS to test our noninvasive, automated computational approach, Hierarchical Region Splitting (HRS), to detect and quantify ischemic core-penumbra using only a single MRI modality (T2- or diffusion-weighted imaging, T2WI/DWI). We also validated our approach by comparing core-penumbral images (from HRS) to DPM with immunohistochemical validation of HII tissues. Our translational and clinical data results showed that HRS could accurately and reliably distinguish the ischemic core from penumbra and their spatiotemporal evolution, which may aid in the vetting and execution of effective therapeutic interventions as well as patient selection.
| S-EPMC3520032 | biostudies-literature
Project description:BackgroundMagnetic Resonance Spectroscopy (MRS) can measure in vivo brain tissue metabolism that exhibits unique biochemical characteristics in brain tumors. For clinical application, an efficient and versatile quantification method of MRS would be an important tool for medical research, particularly for exploring the scientific problem of tumor monitoring. The objective of our study is to propose an automated MRS quantitative approach and assess the feasibility of this approach for glioma grading, prognosis and boundary detection.MethodsAn automated quantitative approach based on a convex envelope (AQoCE) is proposed in this paper, including preprocessing, convex-envelope based baseline fitting, bias correction, sectional baseline removal, and peak detection, in a total of 5 steps. Some metabolic ratios acquired by this quantification are selected for statistical analysis. An independent sample t-test and the Kruskal-Wallis test are used for distinguishing low-grade gliomas (LGG) and high-grade gliomas (HGG) and for detecting the tumor, peritumoral and contralateral areas, respectively. Seventy-eight cases of pre-operative brain gliomas with pathological reports are included in this study.ResultsCho/NAA, Cho/Cr and Lip-Lac/Cr (LL/Cr) calculated by AQoCE in the tumor area differ significantly between LGG and HGG, with p≤0.005. Using logistic regression combining Cho/NAA, Cho/Cr and LL/Cr to generate a ROC curve, AQoCE achieves a sensitivity of 92.9%, a specificity of 72.2%, and an area under ROC curve (AUC) of 0.860. Moreover, both Cho/NAA and Cho/Cr in the AQoCE approach show a significant difference (p≤0.019) between tumoral, peritumoral, and contralateral areas. The comparison between the results of AQoCE and Siemens MRS processing software are also discussed in this paper.ConclusionsThe AQoCE approach is an automated method of residual water removal and metabolite quantification. It can be applied to multi-voxel 1H-MRS for evaluating brain glioma grading and demonstrating characteristics of brain glioma metabolism. It can also detect infiltration in the peritumoral area. Under the limited clinical data used, AQoCE is significantly more versatile and efficient compared to the reference approach of Siemens.
| S-EPMC4569259 | biostudies-literature
Project description:PurposeTo develop a 3D downfield (DF) MRSI protocol with whole brain coverage and post-processing pipeline for creation of metabolite maps.MethodsA 3D, circularly phase-encoded version of the previously developed 2D DF MRSI sequence with 13‾31‾$$ 1\overline{3}3\overline{1} $$ spectral-spatial excitation and frequency selective refocusing was implemented and tested in five healthy volunteers at 3T. The DF metabolite maps with a nominal spatial resolution of 0.7 cm3 were recorded in eight slices at 3T in a scan time of 22 m 40 s. An MRSI post-processing pipeline was developed to create DF metabolite maps. Metabolite concentrations and uncertainty estimates were compared between region differences for nine DF peaks.ResultsLCModel analysis showed Cramer Rao lower bounds average values of 3%-4% for protein amide resonances in the three selected regions (anterior cingulate, dorsolateral prefrontal cortex, and centrum semiovale); Cramer Rao lower bounds were somewhat higher for individual peaks but for the most part were less than 20%. While DF concentration maps were visually quite homogeneous throughout the brain, general linear regression analysis corrected for multiple comparisons found significant differences between centrum semiovale and dorsolateral prefrontal cortex for peaks at 7.09 ppm (p = 0.014), 7.90 ppm (p = 0.009), 8.18 ppm (p = 0.009), combined amides (p = 0.009), and between anterior cingulate and dorsolateral prefrontal cortex for the 7.30 ppm peak (p = 0.020). Cramer Rao lower bounds values were not significantly different between brain regions for any of the DF peaks.ConclusionThe 3D DF MRSI of the human brain at 3T with wide spatial coverage for the mapping of exchangeable amide and other resonances is feasible at a nominal spatial resolution of 0.7 cm3 .
| S-EPMC10330175 | biostudies-literature
Project description:BackgroundRecent studies have questioned the value of adding whole-brain radiotherapy (WBRT) to stereotactic radiosurgery (SRS) for brain metastasis treatment. Neurotoxicity, including radiation-induced brain volume reduction, could be one reason why not all patients benefit from the addition of WBRT. In this study, we quantified brain volume reduction after WBRT and assessed its prognostic significance.MethodsBrain volumes of 91 patients with cerebral metastases were measured during a 150-day period after commencing WBRT and were compared with their pretreatment volumes. The average daily relative change in brain volume of each patient, referred to as the "brain volume reduction rate," was calculated. Univariate and multivariate Cox regression analyses were performed to assess the prognostic significance of the brain volume reduction rate, as well as of 3 treatment-related and 9 pretreatment factors. A one-way analysis of variance was used to compare the brain volume reduction rate across recursive partitioning analysis (RPA) classes.ResultsOn multivariate Cox regression analysis, the brain volume reduction rate was a significant predictor of overall survival after WBRT (P < 0.001), as well as the number of brain metastases (P = 0.002) and age (P = 0.008). Patients with a relatively favorable prognosis (RPA classes 1 and 2) experienced significantly less brain volume decrease after WBRT than patients with a poor prognosis (RPA class 3) (P = 0.001). There was no significant correlation between delivered radiation dose and brain volume reduction rate (P = 0.147).ConclusionIn this retrospective study, a smaller decrease in brain volume after WBRT was an independent predictor of longer overall survival.
| S-EPMC5777481 | biostudies-literature
Project description:Treatment planning for whole-brain radiation treatment is technically a simple process, but in practice it takes valuable clinical time of repetitive and tedious tasks. This report presents a method that automatically segments the relevant target and normal tissues, and creates a treatment plan in only a few minutes after patient simulation. Segmentation of target and critical structures is performed automatically through morphological operations on the soft tissue and was validated by comparing with manual clinical segmentation using the Dice coefficient and Hausdorff distance. The treatment plan is generated by searching a database of previous cases for patients with similar anatomy. In this search, each database case is ranked in terms of similarity using a customized metric designed for sensitivity by including only geometrical changes that affect the dose distribution. The database case with the best match is automatically modified to replace relevant patient info and isocenter position while maintaining original beam and MLC settings. Fifteen patients with marginally acceptable treatment plans were used to validate the method. In each of these cases the anatomy was accurately segmented, but the beams and MLC settings led to a suboptimal treatment plan by either underdosing the brain or excessively irradiating critical normal tissues. For each case, the anatomy was automatically segmented with the proposed method, and the automated and anual segmentations were then compared. The mean Dice coefficient was 0.97, with a standard deviation of 0.008 for the brain, 0.85 ± 0.009 for the eyes, and 0.67 ± 0.11 for the lens. The mean Euclidian distance was 0.13 ± 0.13 mm for the brain, 0.27± 0.31 for the eye, and 2.34 ± 7.23 for the lens. Each case was then subsequently matched against a database of 70 validated treatment plans and the best matching plan (termed autoplanned), was compared retrospectively with the clinical plans in terms of brain coverage and maximum doses to critical structures. Maximum doses were reduced by a maximum of 8.37 Gy for the left eye (mean 2.08), 11.67 for the right eye (1.90) and, respectively, 25.44 (5.59) for the left lens and 24.40 (4.85) for the right lens. Time to generate the autoplan, including the segmentation, was 3-4min. Automated database- based matching is an alternative to classical treatment planning that improves quality while providing a cost-effective solution to planning through modifying previous validated plans to match a current patient's anatomy.
| S-EPMC5690177 | biostudies-literature