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Background: Radiomics in neuroimaging has gained momentum as a noninvasive prediction tool not only to differentiate between types of brain tumors, but also to create phenotypic signatures in neurological and neuropsychiatric disorders. However, there is currently little understating about the robustness and reproducibility of radiomic features in a baseline normative population. Purpose To investigate the intra‐ and interscanner reproducibility, spatial robustness, and sensitivity of radiomics on fluid attenuation inversion recovery (FLAIR) images, which are widely used in neuro‐oncology investigations. Study Type: Retrospective. Population Three separate datasets of healthy controls: 1) 87 subjects (age range 12–64 years), 2) intrascanner three timepoints, four subjects, and 3) interscanner, eight subjects at three different sites. Field Strength/Sequence: T2‐weighted FLAIR at 1.5T and 3.0T. Assessment Spatial variance across lobes, and their relation with age/gender, intra‐ and inter‐scanner reproducibility (with and without site harmonization) of radiomics. Statistical Tests: Analysis of variance (ANOVA), interclass correlation (ICC), coefficient of variation (CoV), Bland–Altman analysis. Results: Analysis of data revealed no differences between genders; however, multiple radiomic features were highly associated with age (P < 0.05). Spatial variability was also evaluated where only 29.04% gray matter and 38.7% white matter features demonstrated an ICC >0.5. Furthermore, the results demonstrated intra‐scanner reliability (ICC >0.5); however, inter‐scanner reproducibility was poor, with ICC < 0.5 for 82% gray matter and 78.5% white matter features. The inter‐scanner reliability improved (ICC < 0.5 for 39.67% gray matter and 38% white matter features) using site‐harmonization techniques. Data Conclusion: These findings suggest that, accounting for age, spatial locations in radiomics‐based analysis and use of intersite radiomics harmonization is crucial before interpreting these features for pathological inference. Level of Evidence 3. Technical Efficacy Stage 1. J. MAGN. RESON. IMAGING 2021;53:394–407. [ABSTRACT FROM AUTHOR]

Background: Susceptibility weighted imaging (SWI) provides vascular information and plays an important role in improving the diagnostic accuracy of preoperative glioma grading. Intratumoral susceptibility signal intensities (ITSS) obtained from SWI has been used in glioma grading. However, the current method for estimation of ITSS is semiquantitative, manual count-dependent, and includes hemorrhage as well as vasculature.Purpose: To develop a quantitative approach that calculates the vasculature volume within tumors by filtering out the hemorrhage from ITSS using R2 * values and connected component analysis-based segmentation algorithm; to evaluate the accuracy of the proposed ITSS vasculature volume (IVV) for differentiating various grades of glioma; and compare it with reported semiquantitative ITSS approach.Study Type: Retrospective.Subjects: Histopathologically confirmed 41 grade IV, 19 grade III, and 15 grade II glioma patients.Field Strength/Sequence: SWI (four echoes: 5.6, 11.8, 18, 24.2 msec) along with conventional MRI sequences (T2 -weighted, T1 -weighted, 3D-fluid-attenuated inversion recovery [FLAIR], and diffusion-weighted imaging [DWI]) at 3.0T.Assessment: R2 * relaxation maps were calculated from multiecho SWI. The R2 * cutoff value for hemorrhage ITSS was determined. A segmentation algorithm was designed, based on this R2 * hemorrhage combined with connected component shape analysis, to quantify the IVV from all slices containing tumor by filtering out hemorrhages. Semiquantitative ITSS scoring as well as total ITSS volume (TIV) including hemorrhages were also calculated.Statistical Tests: One-way analysis of variance (ANOVA) and Tukey-Kramer post-hoc tests were performed to see the difference among the three grades of the tumor (II, III, and IV) in terms of semiquantitative ITSS scoring, TIV, and IVV. Receiver operating characteristic (ROC) curve analysis was used to evaluate the performance of the three methods individually in discriminating between grades of glioma.Results: One-way ANOVA showed that only the proposed IVV significantly differentiated different grades of gliomas having visible ITSS. ROC analysis showed that IVV provided the highest AUC for the discrimination of grade II vs. III (0.93), grade III vs. IV (0.98), and grade II vs. IV glioma (0.94). IVV also provided the highest sensitivity and specificity for differentiating grade II vs. III (87.44, 98.41), grade III vs. IV (97.15, 94.12), and grade II vs. IV (98.72, 92.31).Data Conclusion: The proposed quantitative method segregates hemorrhage from tumor vasculature. It scores above the existing semiquantitative method in terms of ITSS estimation and grading accuracy.Level Of Evidence: 4 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2020;51:225-233. [ABSTRACT FROM AUTHOR]

Background: Glioma grading between intermediate grades (Grade II vs. III and Grade III vs. IV) as well as multiclass grades (Grade II vs. III vs. IV) is challenging and needs to be addressed.Purpose: To develop an artificial intelligence-based methodology for glioma grading using T1 perfusion parameters and volume of tumor components, and validate the efficacy of the methodology by grading on a cohort of glioma patients.Study Type: Retrospective.Population: The development set consisted of 53 glioma patients and validation consisted of 13 glioma patients.Field Strength/sequence: Conventional MRI images (2D T1 -W, dual PD-T2 -W, and 3D FLAIR) and 3D T1 perfusion MRI data obtained at 3 T.Assessment: Enhancing and nonenhancing components of glioma were segmented out and combined to form the region of interest (ROI) for glioma grading. Prominent vessels were removed from the selected ROI. Different T1 perfusion parameters from the ROI were combined with volume of tumor components to form the feature set for glioma grading. Optimization was carried out for selection of the statistic of the T1 perfusion parameters and the features to be used for glioma grading using sequential feature selection and random forest-based feature selection method. An optimized support vector machine (SVM) classifier was used for glioma grading.Statistical Tests: Mean ± SD, analysis of variance (ANOVA) followed by the Tukey-Kramer test, ROC analysis.Results: Classification error for Grade II vs. III was 3.7%, for Grade III vs. IV was 5.26%, and for Grade II vs. III vs. IV was 9.43% using the proposed methodology. The mean of the values above the 90th percentile value of T1 perfusion parameters provided a maximum area under the curve (AUC) for intermediate grade differentiation. Random forest obtained optimal feature set provided better grading results than other methods using the SVM classifier.Data Conclusion: It was feasible to achieve low classification error for intermediate as well as multiclass glioma grading using an SVM classifier based on optimized features obtained from T1 perfusion MRI and volumes of tumor components.Level Of Evidence: 4 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2019;50:1295-1306. [ABSTRACT FROM AUTHOR]

Background: Glioma grade along with patient's age and general health are used for treatment planning and prognosis.Purpose: To characterize and quantify the spontaneous blood oxygen level-dependent (BOLD) fluctuations in gliomas using measures based on T2*-weighted signal time-series and to distinguish between high- and low-grade gliomas.Study Type: Retrospective.Subjects: Twenty-one patients with high-grade and 13 patients with low-grade gliomas confirmed on histology were investigated.Field Strength/sequence: Dynamic T2*-weighted (multislice single-shot echo-planar-imaging) magnetic resonance imaging (MRI) was performed on a 3T system with an 8-element receive-only head coil to measure the BOLD fluctuations. In addition, a dynamic T1 -weighted (3D fast field echo) dynamic contrast-enhanced (DCE) perfusion scan was performed.Assessment: Three BOLD measures were determined: the temporal shift (TS), amplitude of low frequency fluctuations (ALFF), and regional homogeneity (ReHo). DCE perfusion-based cerebral blood volume (CBV) and time-to-peak (TTP) maps were concurrently evaluated for comparison.Statistical Tests: An analysis-of-variance test was first used. When the test appeared significant, post-hoc analysis was performed using analysis-of-covariance with age as covariate. Logistic regression and receiver-operator characteristic curve analysis were also performed.Results: TS was significantly advanced in high-grade gliomas compared to the contralateral cortex (P = 0.01) and low-grade gliomas (P = 0.009). In high-grade gliomas, ALFF and CBV were significantly higher than the contralateral cortex (P = 0.041 and P = 0.008, respectively) and low-grade gliomas (P = 0.036 and P = 0.01, respectively). ReHo and TTP did not show significant differences between high- and low-grade gliomas (P = 0.46 and P = 0.42, respectively). The area-under-curve was above 0.7 only for the TS, ALFF, and CBV measures.Data Conclusion: Advanced and amplified hemodynamic fluctuations manifest in high-grade gliomas, but not in low-grade gliomas, and can be assessed using BOLD measures. Preliminary results showed that quantification of spontaneous fluctuations has potential for hemodynamic characterization of gliomas and distinguishing between high- and low-grade gliomas.Level Of Evidence: 4 Technical Efficacy: Stage 5 J. Magn. Reson. Imaging 2018;47:1616-1625. [ABSTRACT FROM AUTHOR]

Purpose: To evaluate T2-relaxation changes in patients with minimal hepatic encephalopathy (MHE) using T2 relaxometry and to correlate T2 values with brain metabolites evaluated using 2D magnetic resonance spectroscopy (MRS). Materials and Methods: Eight MHE patients and 13 healthy subjects were evaluated using T2 relaxometry, and eight patients and nine healthy subjects underwent 2D MRS in right frontal and left occipital regions. Whole-brain T2-relaxation maps were compared between MHE and control subjects using analysis-of-covariance, with age and gender included as covariates. T2 values derived from the right frontal and left occipital lobes were correlated with the metabolite ratios. Results: Multiple brain regions including anterior and mid cingulate cortices, right anterior and left posterior insular cortices, right prefrontal, medial frontal, and right superior temporal cortices showed significantly increased T2 values in MHE patients compared to control subjects. MRS showed significantly increased ratios of glutamine/glutamate (Glx) and decreased ratios of myo-inositol, taurine, choline, and myo-inositol/choline (mICh) with respect to creatine (Cr_d) in patients compared to controls. Frontal Glx/Cr_d showed significantly positive correlation with T2 values. Conclusion: MHE patients showed significantly increased T2 values in multiple brain regions reflecting increased free water content and T2 values in frontal lobe correlated with the increased Glx/Cr_d ratio. J. Magn. Reson. Imaging 2009;30:1034-1041. © 2009 Wiley-Liss, Inc. [ABSTRACT FROM AUTHOR]

Purpose To correlate dynamic contrast-enhanced (DCE) MRI derived perfusion indices with immunohistochemically obtained vascular endothelial growth factor (VEGF) and matrix metalloproteinase-9 (MMP-9) in a cellular fraction of brain tuberculomas (BT). Materials and Methods Thirteen BT patients underwent DCE MRI. Perfusion indices (cerebral blood volume [CBV], transfer coefficient [ktrans] and leakage [ve]) maps were generated for the quantitative analysis. The CBV was corrected for the leaky blood-brain barrier (BBB). The relative CBV (rCBV), ktrans, and ve were calculated by placing 10 regions of interest (ROIs) showing the highest values in the lesion. The percentage area of VEGF and percentage area of MMP-9 and microvessel density (MVD) were quantified from 10 fields per lesion with maximal expression of the excised BT. Pearson correlation analysis between physiological indices and quantitative VEGF, MMP-9, and MVD was performed for each ROI. Results The average value of rCBV, ktrans, ve, VEGF, MMP-9, and MVD were 3.53 ± 0.37, 2.04 ± 0.40 min−1, 0.71 ± 0.09, 12.51 ± 2.56, 18.09 ± 2.06, 10.87 ± 1.99, respectively. The ktrans ( r = 0.918, P < 0.001) and ve ( r = 0.899, P < 0.001) showed significant correlation with MMP-9, while rCBV correlated significantly with MVD ( r = 0.962, P < 0.001) and VEGF ( r = 0.868, P < 0.001). Conclusion We conclude that the expression of MMP-9, a marker of BBB disruption and disease activity in BT correlates with DCE-derived ktrans and thus has the potential to be used as its surrogate marker. J. Magn. Reson. Imaging 2008;28:588-597. © 2008 Wiley-Liss, Inc. [ABSTRACT FROM AUTHOR]

Purpose To estimate precontrast tissue parameter ( T10) using fast spin echo (FSE) and to quantify physiological and hemodynamic parameters with leakage correction using T1-weighted dynamic contrast-enhanced (DCE) perfusion imaging. Materials and Methods Voxel-wise T10 computation was performed followed by the analysis of T1-weighted DCE perfusion data for the conversion of signal intensity time curve to concentration time curve, estimation of hemodynamic and physiological perfusion indices, and a method for leakage correction. Validations of accuracy of the computations have also been carried out. Results The computed T10 and hemodynamic perfusion indices in normal white and gray matter were in good agreement with the literature values. Physiological perfusion indices in these regions were found negligible, validating computations. Cerebral blood volume (CBV) values change negligibly over the length of concentration time curve in white matter, gray matter, and lesion (CBVcorrected), while CBVuncorrected (lesion) shows linear increase over time. Conclusion T1-weighted DCE perfusion data along with FSE-based T1 estimation can be used for an accurate estimation of hemodynamic and physiological perfusion indices. J. Magn. Reson. Imaging 2007;26:871-880. © 2007 Wiley-Liss, Inc. [ABSTRACT FROM AUTHOR]

Purpose To evaluate a localized two-dimensional correlated magnetic resonance spectroscopic (L-COSY) technique in patients with hepatic encephalopathy (HE) and healthy subjects, and to correlate the cerebral metabolite changes with neuropsychological (NP) test scores. Materials and Methods Eighteen minimal hepatic encephalopathy (MHE) patients and 21 healthy controls have been investigated. A GE 1.5-T magnetic resonance (MR) scanner was used in combination with a body MR coil for transmission and a 3-inch surface coil for reception. A 27-mL voxel was localized by three slice-selective radio frequency (RF) pulses (90°-180°-90°) in the anterior cingulate region. The total duration of each two-dimensional L-COSY spectrum was approximately 25 minutes. The NP battery included a total of 15 tests, which were grouped into six domains. Results MR spectroscopic results showed a statistically significant decrease in myo-inositol (mI) and choline (Ch) and an increase in glutamate/glutamine (Glx) in patients when compared to healthy controls. There was also an increase in taurine (Tau) in patients. The NP results indicated a significant correlation between motor function assessed by NP tests and mI ratios recorded using two-dimensional L-COSY. Conclusion The study demonstrated the feasibility of evaluating the two-dimensional L-COSY sequence in a clinical environment. The results showed additional cerebral metabolites that can be measured with the technique in comparison to one-dimensional study. J. Magn. Reson. Imaging 2005;21:398-405. © 2005 Wiley-Liss, Inc. [ABSTRACT FROM AUTHOR]