scholarly journals Signal to noise and b-value analysis for optimal intra-voxel incoherent motion imaging in the brain

PLoS ONE ◽  
2021 ◽  
Vol 16 (9) ◽  
pp. e0257545
Author(s):  
Harri Merisaari ◽  
Christian Federau
Keyword(s):  
B Value ◽  
Quantitative Information ◽  
Physiological Noise ◽  
Value Analysis ◽  
B Values ◽  
High B Value ◽  
Noise Characteristics ◽  
Acquisition Scheme ◽  
The Brain

Intravoxel incoherent motion (IVIM) is a method that can provide quantitative information about perfusion in the human body, in vivo, and without contrast agent. Unfortunately, the IVIM perfusion parameter maps are known to be relatively noisy in the brain, in particular for the pseudo-diffusion coefficient, which might hinder its potential broader use in clinical applications. Therefore, we studied the conditions to produce optimal IVIM perfusion images in the brain. IVIM imaging was performed on a 3-Tesla clinical system in four healthy volunteers, with 16 b values 0, 10, 20, 40, 80, 110, 140, 170, 200, 300, 400, 500, 600, 700, 800, 900 s/mm2, repeated 20 times. We analyzed the noise characteristics of the trace images as a function of b-value, and the homogeneity of the IVIM parameter maps across number of averages and sub-sets of the acquired b values. We found two peaks of noise of the trace images as function of b value, one due to thermal noise at high b-value, and one due to physiological noise at low b-value. The selection of b value distribution was found to have higher impact on the homogeneity of the IVIM parameter maps than the number of averages. Based on evaluations, we suggest an optimal b value acquisition scheme for a 12 min scan as 0 (7), 20 (4), 140 (19), 300 (9), 500 (19), 700 (1), 800 (4), 900 (1) s/mm2.

scholarly journals ADC-Based Stratification of Molecular Glioma Subtypes Using High b-Value Diffusion-Weighted Imaging

2021 ◽  
Vol 10 (16) ◽  
pp. 3451
Author(s):  
Nils C. Nuessle ◽  
Felix Behling ◽  
Ghazaleh Tabatabai ◽  
Salvador Castaneda Vega ◽  
Jens Schittenhelm ◽  
...  
Keyword(s):  
Diffusion Weighted Imaging ◽  
Mean Diffusivity ◽  
Area Under The Curve ◽  
B Value ◽  
Diffusion Kurtosis Imaging ◽  
B Values ◽  
High B Value ◽  
Diffusion Weighted ◽  
Apparent Diffusion

Purpose: To investigate the diagnostic performance of in vivo ADC-based stratification of integrated molecular glioma grades. Materials and methods: Ninety-seven patients with histopathologically confirmed glioma were evaluated retrospectively. All patients underwent pre-interventional MRI-examination including diffusion-weighted imaging (DWI) with implemented b-values of 500, 1000, 1500, 2000, and 2500 s/mm2. Apparent Diffusion Coefficient (ADC), Mean Kurtosis (MK), and Mean Diffusivity (MD) maps were generated. The average values were compared among the molecular glioma subgroups of IDH-mutant and IDH-wildtype astrocytoma, and 1p/19q-codeleted oligodendroglioma. One-way ANOVA with post-hoc Games-Howell correction compared average ADC, MD, and MK values between molecular glioma groups. A Receiver Operating Characteristic (ROC) analysis determined the area under the curve (AUC). Results: Two b-value-dependent ADC-based evaluations presented statistically significant differences between the three molecular glioma sub-groups (p < 0.001, respectively). Conclusions: High-b-value ADC from preoperative DWI may be used to stratify integrated molecular glioma subgroups and save time compared to diffusion kurtosis imaging. Higher b-values of up to 2500 s/mm2 may present an important step towards increasing diagnostic accuracy compared to standard DWI protocol.

scholarly journals Noise and Coupling Affect Signal Detection and Bursting in a Simulated Physiological Neural Network

2002 ◽  
Vol 88 (5) ◽  
pp. 2598-2611 ◽  
Author(s):  
William C. Stacey ◽  
Dominique M. Durand
Keyword(s):  
Signal Detection ◽  
Epileptiform Activity ◽  
Electrical Coupling ◽  
Periodic Signal ◽  
Physiological Noise ◽  
Ca1 Neurons ◽  
Ca1 Region ◽  
Noise Characteristics ◽  
Hippocampal Ca1

Signal detection in the CNS relies on a complex interaction between the numerous synaptic inputs to the detecting cells. Two effects, stochastic resonance (SR) and coherence resonance (CR) have been shown to affect signal detection in arrays of basic neuronal models. Here, an array of simulated hippocampal CA1 neurons was used to test the hypothesis that physiological noise and electrical coupling can interact to modulate signal detection in the CA1 region of the hippocampus. The array was tested using varying levels of coupling and noise with different input signals. Detection of a subthreshold signal in the network improved as the number of detecting cells increased and as coupling was increased as predicted by previous studies in SR; however, the response depended greatly on the noise characteristics present and varied from SR predictions at times. Careful evaluation of noise characteristics may be necessary to form conclusions about the role of SR in complex systems such as physiological neurons. The coupled array fired synchronous, periodic bursts when presented with noise alone. The synchrony of this firing changed as a function of noise and coupling as predicted by CR. The firing was very similar to certain models of epileptiform activity, leading to a discussion of CR as a possible simple model of epilepsy. A single neuron was unable to recruit its neighbors to a periodic signal unless the signal was very close to the synchronous bursting frequency. These findings, when viewed in comparison with physiological parameters in the hippocampus, suggest that both SR and CR can have significant effects on signal processing in vivo.

Diffusion restriction in the human spinal cord characterized in vivo with high b-value STEAM diffusion imaging

NeuroImage ◽  
2013 ◽  
Vol 82 ◽  
pp. 416-425 ◽  
Author(s):  
Novena A. Rangwala ◽  
David B. Hackney ◽  
Weiying Dai ◽  
David C. Alsop
Keyword(s):  
Spinal Cord ◽  
Diffusion Imaging ◽  
B Value ◽  
Diffusion Restriction ◽  
Human Spinal Cord ◽  
High B Value

scholarly journals Accuracy of high b-value diffusion-weighted MRI for prostate cancer detection: a meta-analysis

2017 ◽  
Vol 59 (1) ◽  
pp. 105-113 ◽  
Author(s):  
Keith Craig Godley ◽  
Tom Joseph Syer ◽  
Andoni Paul Toms ◽  
Toby Oliver Smith ◽  
Glyn Johnson ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Diagnostic Accuracy ◽  
Sensitivity And Specificity ◽  
Cancer Detection ◽  
Diagnostic Performance ◽  
Visual Assessment ◽  
B Value ◽  
B Values ◽  
Prostate Cancer Detection ◽  
High B Value

Background The diagnostic accuracy of diffusion-weighted imaging (DWI) to detect prostate cancer is well-established. DWI provides visual as well as quantitative means of detecting tumor, the apparent diffusion coefficient (ADC). Recently higher b-values have been used to improve DWI’s diagnostic performance. Purpose To determine the diagnostic performance of high b-value DWI at detecting prostate cancer and whether quantifying ADC improves accuracy. Material and Methods A comprehensive literature search of published and unpublished databases was performed. Eligible studies had histopathologically proven prostate cancer, DWI sequences using b-values ≥ 1000 s/mm2, less than ten patients, and data for creating a 2 × 2 table. Study quality was assessed with QUADAS-2 (Quality Assessment of diagnostic Accuracy Studies). Sensitivity and specificity were calculated and tests for statistical heterogeneity and threshold effect performed. Results were plotted on a summary receiver operating characteristic curve (sROC) and the area under the curve (AUC) determined the diagnostic performance of high b-value DWI. Results Ten studies met eligibility criteria with 13 subsets of data available for analysis, including 522 patients. Pooled sensitivity and specificity were 0.59 (95% confidence interval [CI], 0.57–0.61) and 0.92 (95% CI, 0.91–0.92), respectively, and the sROC AUC was 0.92. Subgroup analysis showed a statistically significant ( P = 0.03) improvement in accuracy when using tumor visual assessment rather than ADC. Conclusion High b-value DWI gives good diagnostic performance for prostate cancer detection and visual assessment of tumor diffusion is significantly more accurate than ROI measurements of ADC.

Evaluation of emphysema severity and progression in a rabbit model: comparison of hyperpolarized 3He and 129Xe diffusion MRI with lung morphometry

2007 ◽  
Vol 102 (3) ◽  
pp. 1273-1280 ◽  
Author(s):  
Jaime F. Mata ◽  
Talissa A. Altes ◽  
Jing Cai ◽  
Kai Ruppert ◽  
Wayne Mitzner ◽  
...  
Keyword(s):  
Model Comparison ◽  
Structural Changes ◽  
Rabbit Model ◽  
B Value ◽  
Saline Control ◽  
Control Group ◽  
B Values ◽  
Apparent Diffusion Coefficients ◽  
Change In Mean

The apparent diffusion coefficients (ADCs) of hyperpolarized 3He and 129Xe gases were measured in the lungs of rabbits with elastase-induced emphysema and correlated against the mean chord length from lung histology. In vivo measurements were performed at baseline and 2, 4, 6, and 8 wk after instillation of elastase (mild and moderate emphysema groups) or saline (control group). ADCs were determined from acquisitions that used two b values. To investigate the effect of b value on the results, b-value pairs of 0 and 1.6 s/cm2 and 0 and 4.0 s/cm2 were used for 3He, and b-value pairs of 0 and 5.0 s/cm2 and 0 and 10.0 s/cm2 were used for 129Xe. At 8 wk after instillation, the rabbits were euthanized, and the lungs were analyzed histologically and morphometrically. ADCs for the rabbits in the control group did not change significantly from baseline to week 8, whereas ADCs for the rabbits in the emphysema groups increased significantly ( P < 0.05) for all gas and b-value combinations except 129Xe with the b-value pair of 0 and 5.0 s/cm2. The largest percent change in mean ADC from baseline to week 8 (15.3%) occurred with 3He and the b-value pair of 0 and 1.6 s/cm2 for rabbits in the moderate emphysema group. ADCs (all b values) were strongly correlated ( r = 0.62–0.80, P < 0.001) with mean chord lengths from histology. These results further support the ability of diffusion-weighted MRI with hyperpolarized gases to detect regional and global structural changes of emphysema within the lung.

scholarly journals Improved temporal resolution for mapping brain metabolism using functional PET and anatomical MRI knowledge

2020 ◽  
Author(s):  
Viswanath P. Sudarshan ◽  
Shenpeng Li ◽  
Sharna D. Jamadar ◽  
Gary F. Egan ◽  
Suyash P. Awate ◽  
...  
Keyword(s):  
Temporal Resolution ◽  
Brain Metabolism ◽  
Visual Stimulation ◽  
Brain Activity ◽  
Brain Activation ◽  
Partial Volume ◽  
Noise Characteristics ◽  
Positron Emission ◽  
The Brain

AbstractFunctional positron emission tomography (fPET) imaging using continuous infusion of [18F]-fluorodeoxyglucose (FDG) is a novel neuroimaging technique to track dynamic glucose utilization in the brain. In comparison to conventional static PET, fPET maintains a sustained supply of glucose in the blood plasma which improves sensitivity to measure dynamic glucose changes in the brain, and enables mapping of dynamic brain activity in task-based and resting-state fPET studies. However, there is a trade-off between temporal resolution and spatial noise due to the low concentration of FDG and the limited sensitivity of multi-ring PET scanners. Images from fPET studies suffer from partial volume errors and residual scatter noise that may cause the cerebral metabolic functional maps to be biased. Gaussian smoothing filters used to denoise the fPET images are suboptimal, as they introduce additional partial volume errors. In this work, a post-processing framework based on a magnetic resonance (MR) Bowsher-like prior was used to improve the spatial and temporal signal to noise characteristics of the fPET images. The performance of the MR guided method was compared with conventional Gaussian filtering using both simulated and in vivo task fPET datasets. The results demonstrate that the MR guided fPET framework reduces the partial volume errors, enhances the sensitivity of identifying brain activation, and improves the anatomical accuracy for mapping changes of brain metabolism in response to a visual stimulation task. The framework extends the use of functional PET to investigate the dynamics of brain metabolic responses for faster presentation of brain activation tasks, and for applications in low dose PET imaging.

scholarly journals Using DWI-MRI parameters from multi- B values acquisition and a histogram approach for assessment of early therapeutic response in glioblastoma

2019 ◽  
Vol 21 (Supplement_4) ◽  
pp. iv3-iv3
Author(s):  
Shah Islam ◽  
Melanie Morrison ◽  
Matthew Orton ◽  
Matthew Grech-Sollars ◽  
Adam Waldman
Keyword(s):  
Treatment Response ◽  
Therapeutic Response ◽  
Diffusion Imaging ◽  
B Value ◽  
Subsequent Treatment ◽  
Longitudinal Assessment ◽  
Value Analysis ◽  
B Values ◽  
Early Evaluation ◽  
Early Treatment Response

Abstract Early evaluation of therapeutic response of GBM on imaging is limited by poor biological specificity of clinical MRI. Clinical DWI-MRI models assume diffusion is mono-exponential when derived from only two B-values, although it has been proven diffusion is multiexponential. Purpose: To assess the utility of quantitative diffusion MRI derived from multi B-value acquisitions in the assessment of treatment response. Methods: 13 patients were enrolled into our multicentre study. Imaging was performed pre-RT and mid-RT using a multi B-value acquisition. Histograms within ROIs defined by abnormal FLAIR signal. Changes in histogram percentile profiles were evaluated across the two timepoints and compared with RANO assessment. Results: Following treatment, 5 patients had PD, 4 SD and 4 CR. Patients with PD showed a histogram shift to the left across all models, in keeping with increased cellularity. Parameters DDC and f are the most predictive of PD against RANO assessment, and appear superior to ADC. Reduction in 75th centile (f) and 95th centile (DDC) are the most sensitive histogram metrics for predicting early PD. Discussion: This is the first study to use histogram analysis as a marker of early treatment response in GBM. Results suggest association between early changes in specific diffusion components and subsequent treatment response. Spatially-independent diffusion parameter comparisons provide unbiased sampling of tumour heterogeneity. Conclusion: Our preliminary data suggest differential changes in diffusion parameters early in treatment, and provide proof of principle for multi B-value analysis and spatially-independent longitudinal assessment of diffusion imaging for therapeutic assessment in GBM.

scholarly journals Estimating intra-axonal axial diffusivity in the presence of fibre orientation dispersion

2020 ◽  
Author(s):  
Amy FD Howard ◽  
Frederik J Lange ◽  
Jeroen Mollink ◽  
Michiel Cottaar ◽  
Mark Drakesmith ◽  
...  
Keyword(s):  
White Matter ◽  
Fibre Orientation ◽  
Free Water ◽  
Orientation Distribution ◽  
B Value ◽  
Axial Diffusivity ◽  
High B Value ◽  
Axonal Compartment ◽  
Two Parameters

AbstractBy analysing the diffusion MRI signal, we can infer information about the microscopic structure of the brain. Two parameters of interest - the intra-axonal axial diffusivity and fibre orientation dispersion - are potential biomarkers for very different aspects of the white matter microstructure, yet they are difficult to disentangle. The parameters covary such that, if one is not accurately accounted for, the other will be biased. In this work we use high b-value data to isolate the signal from the intra-axonal compartment and resolve any degeneracies with the extra-axonal compartment. In the high b-value regime, we then use a model of dispersed sticks to estimate the intra-axonal axial diffusivity and fibre orientation distribution on a voxelwise basis. Our results in in vivo, human data show an intra-axonal axial diffusivity of ~ 2.3 – 3 μm2/ms, where 3 μm2/ms is the diffusivity of free water at 37°C. The intra-axonal axial diffusivity is seen to vary considerably across the white matter. For example, in the corpus callosum we find high values in the genu and splenium, and lower values in the midbody. Furthermore, the axial diffusivity and orientation dispersion appear negatively correlated, behaviour which we show is consistent with the presence of fibre undulations but not consistent with a degeneracy between fanning fibres and axial diffusivity. Finally, we demonstrate that the parameter maps output from Neurite Orientation Dispersion and Density Imaging (NODDI) change substantially when the assumed axial diffusivity was increased from 1.7 to 2.5 or 3 μm2/ms.

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