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A method for estimating intracellular sodium concentration and extracellular volume fraction in brain in vivo using sodium magnetic resonance imaging.

ABSTRACT: In this feasibility study we propose a method based on sodium magnetic resonance imaging (MRI) for estimating simultaneously the intracellular sodium concentration (C1, in mM) and the extracellular volume fraction (α) in grey and white matters (GM, WM) in brain in vivo. Mean C1 over five healthy volunteers was measured ~11 mM in both GM and WM, mean α was measured ~0.22 in GM and ~0.18 in WM, which are in close agreement with standard values for healthy brain tissue (C1 ~ 10-15 mM, α ~ 0.2). Simulation of 'fluid' and 'solid' inclusions were accurately detected on both the C1 and α 3D maps and in the C1 and α distributions over whole GM and WM. This non-invasive and quantitative method could provide new biochemical information for assessing ion homeostasis and cell integrity in brain and help the diagnosis of early signs of neuropathologies such as multiple sclerosis, Alzheimer's disease, brain tumors or stroke.

SUBMITTER: Madelin G

PROVIDER: S-EPMC4762219 | biostudies-literature | 2014 Apr

REPOSITORIES: biostudies-literature

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A method for estimating intracellular sodium concentration and extracellular volume fraction in brain in vivo using sodium magnetic resonance imaging.

Madelin Guillaume G Kline Richard R Walvick Ronn R Regatte Ravinder R RR

Scientific reports 20140423

In this feasibility study we propose a method based on sodium magnetic resonance imaging (MRI) for estimating simultaneously the intracellular sodium concentration (C1, in mM) and the extracellular volume fraction (α) in grey and white matters (GM, WM) in brain in vivo. Mean C1 over five healthy volunteers was measured ~11 mM in both GM and WM, mean α was measured ~0.22 in GM and ~0.18 in WM, which are in close agreement with standard values for healthy brain tissue (C1 ~ 10-15 mM, α ~ 0.2). Sim ...[more]

PMID: 24755879

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Project description:BackgroundHeart failure- (HF) and arrhythmia-related complications are the main causes of morbidity and mortality in patients with nonischemic dilated cardiomyopathy (NIDCM). Cardiovascular magnetic resonance (CMR) imaging is a noninvasive tool for risk stratification based on fibrosis assessment. Diffuse interstitial fibrosis in NIDCM may be a limitation for fibrosis assessment through late gadolinium enhancement (LGE), which might be overcome through quantitative T1 and extracellular volume (ECV) assessment. T1 and ECV prognostic value for arrhythmia-related events remain poorly investigated. We asked whether T1 and ECV have a prognostic value in NIDCM patients.MethodsThis prospective multicenter study analyzed 225 patients with NIDCM confirmed by CMR who were followed up for 2 years. CMR evaluation included LGE, native T1 mapping and ECV values. The primary endpoint was the occurrence of a major adverse cardiovascular event (MACE) which was divided in two groups: HF-related events and arrhythmia-related events. Optimal cutoffs for prediction of MACE occurrence were calculated for all CMR quantitative values.ResultsFifty-eight patients (26%) developed a MACE during follow-up, 42 patients (19%) with HF-related events and 16 patients (7%) arrhythmia-related events. T1 Z-score (p = 0.008) and global ECV (p = 0.001) were associated with HF-related events occurrence, in addition to left ventricular ejection fraction (p < 0.001). ECV > 32.1% (optimal cutoff) remained the only CMR independent predictor of HF-related events occurrence (HR 2.15 [1.14-4.07], p = 0.018). In the arrhythmia-related events group, patients had increased native T1 Z-score and ECV values, with both T1 Z-score > 4.2 and ECV > 30.5% (optimal cutoffs) being independent predictors of arrhythmia-related events occurrence (respectively, HR 2.86 [1.06-7.68], p = 0.037 and HR 2.72 [1.01-7.36], p = 0.049).ConclusionsECV was the sole independent predictive factor for both HF- and arrhythmia-related events in NIDCM patients. Native T1 was also an independent predictor in arrhythmia-related events occurrence. The addition of ECV and more importantly native T1 in the decision-making algorithm may improve arrhythmia risk stratification in NIDCM patients. Trial registration NCT02352129. Registered 2nd February 2015-Retrospectively registered, https://clinicaltrials.gov/ct2/show/NCT02352129.

Project description:BackgroundMyocardial fibrosis is a common feature in various cardiac diseases. It causes adverse cardiac remodeling and is associated with poor clinical outcomes. Late gadolinium enhancement (LGE) and extracellular volume fraction (ECV) are the standard magnetic resonance imaging techniques for detecting focal and diffuse myocardial fibrosis. However, these contrast-enhanced techniques require the administration of gadolinium contrast agents, which is not applicable to patients with gadolinium contraindications. To eliminate the need for contrast agents, we developed and applied an endogenous free-breathing T1ρ dispersion imaging technique (FB-MultiMap) for diagnosing diffuse myocardial fibrosis in a cohort with suspected cardiomyopathies.MethodsThe proposed FB-MultiMap technique, enabling T2, T1ρ, and their difference (myocardial fibrosis index [mFI]) quantification in a single scan was developed in phantoms and 15 healthy subjects. In the clinical study, 55 patients with suspected cardiomyopathies were imaged using FB-MultiMap, conventional native T1 mapping, LGE, and ECV imaging. The accuracy of the endogenous parameters for predicting increased ECV was evaluated using receiver operating characteristic curve analysis. In addition, the correlation of native T1, T1ρ, and mFI with ECV was, respectively, assessed using Pearson correlation coefficients.ResultsFB-MultiMap showed a good agreement with conventional separate breath-hold mapping techniques in phantoms and healthy subjects. Considering all the patients, T1ρ was more accurate than mFI and native T1 for predicting increased ECV, with area under the curve (AUC) values of 0.91, 0.79, and 0.75, respectively, and showed a stronger correlation with ECV (correlation coefficient r: 0.72 vs 0.52 vs 0.40). In the subset of 47 patients with normal T2 values, the diagnostic performance of mFI was significantly strengthened (AUC = 0.90, r = 0.83), outperforming T1ρ and native T1.ConclusionThe proposed free-breathing T1ρ dispersion imaging technique enabling simultaneous quantification of T2, T1ρ, and mFI in a single scan has shown great potential for diagnosing diffuse myocardial fibrosis in patients with complex cardiomyopathies without contrast agents.

Project description:ObjectiveT1 mapping provides valuable information regarding cardiomyopathies. Manual drawing is time consuming and prone to subjective errors. Therefore, this study aimed to test a DL algorithm for the automated measurement of native T1 and extracellular volume (ECV) fractions in cardiac magnetic resonance (CMR) imaging with a temporally separated dataset.Materials and methodsCMR images obtained for 95 participants (mean age ± standard deviation, 54.5 ± 15.2 years), including 36 left ventricular hypertrophy (12 hypertrophic cardiomyopathy, 12 Fabry disease, and 12 amyloidosis), 32 dilated cardiomyopathy, and 27 healthy volunteers, were included. A commercial deep learning (DL) algorithm based on 2D U-net (Myomics-T1 software, version 1.0.0) was used for the automated analysis of T1 maps. Four radiologists, as study readers, performed manual analysis. The reference standard was the consensus result of the manual analysis by two additional expert readers. The segmentation performance of the DL algorithm and the correlation and agreement between the automated measurement and the reference standard were assessed. Interobserver agreement among the four radiologists was analyzed.ResultsDL successfully segmented the myocardium in 99.3% of slices in the native T1 map and 89.8% of slices in the post-T1 map with Dice similarity coefficients of 0.86 ± 0.05 and 0.74 ± 0.17, respectively. Native T1 and ECV showed strong correlation and agreement between DL and the reference: for T1, r = 0.967 (95% confidence interval [CI], 0.951-0.978) and bias of 9.5 msec (95% limits of agreement [LOA], -23.6-42.6 msec); for ECV, r = 0.987 (95% CI, 0.980-0.991) and bias of 0.7% (95% LOA, -2.8%-4.2%) on per-subject basis. Agreements between DL and each of the four radiologists were excellent (intraclass correlation coefficient [ICC] of 0.98-0.99 for both native T1 and ECV), comparable to the pairwise agreement between the radiologists (ICC of 0.97-1.00 and 0.99-1.00 for native T1 and ECV, respectively).ConclusionThe DL algorithm allowed automated T1 and ECV measurements comparable to those of radiologists.

Project description:BackgroundThe calculation of extracellular volume (ECV) in cardiac magnetic resonance requires hematocrit, limiting its applicability in clinical practice. Based on the linear relationship between hematocrit and blood T1 relaxivity, a synthetic ECV could be estimated without a blood sample. We aim to develop and test regression models for synthetic ECV without blood sampling in 1.5-T and 3.0-T scanners.MethodsA total of 1101 subjects who underwent cardiac magnetic resonance scanning with native and postcontrast T1 mapping and venous hematocrit within 24 hours were retrospectively enrolled. Subjects were randomly split into derivation (n=550) and validation (n=551) subgroups for each scanner. Different regression models were derived controlling for sex, field strength, and left ventricle/right ventricle blood pool and validated in the validation group. We performed additional validation analyses in subgroups of patients with histological validation (n=17), amyloidosis (n=29), anemia (n=185), and reduced ejection fraction (n=322).ResultsIn the derivation group, 8 specific models and 2 common estimate models were derived. In the validation group, using specific models, synthetic ECV had high agreement with conventional ECV (R2, 0.87; P<0.0001 and R2, 0.88, P<0.0001; -0.16% and -0.10%, left ventricle and right ventricle model, respectively). Common models also performed well (R2, 0.88; P<0.0001 and R2, 0.89, P<0.0001; -0.21% and -0.18%, left ventricle and right ventricle model, respectively). Histological validation demonstrated equal performance of synthetic and measured ECV. Synthetic ECV as calculated by the common model showed a bias in the anemia cohort significantly reduced by the specific model (-2.45 to -1.28, right ventricle common and specific model, respectively).ConclusionsSynthetic ECV provided a promising way to calculate ECV without blood sampling. Specific models could provide the most accurate value, while common models could be more suitable in routine clinical practice because of their simplicity while maintaining adequate accuracy.

Project description:ObjectivesTo investigate the effect of the phantom-based correction method for standardizing myocardial native T1 and extracellular volume fraction (ECV) in healthy subjects.MethodsSeventy-one healthy asymptomatic adult (≥ 20 years) volunteers of five different age groups (34 men and 37 women, 45.5 ± 15.5 years) were prospectively enrolled in three academic hospitals. Cardiac MRI including Modified Look - Locker Inversion recovery T1 mapping sequence was performed using a 3-Tesla system with a different type of scanner for each hospital. Native T1 and ECV were measured in the short-axis T1 map and analyzed for mean values of the 16 entire segments. The myocardial T1 value of each subject was corrected based on the site-specific equation derived from the T1 Mapping and ECV Standardization phantom. The global native T1 and ECV were compared between institutions before and after phantom-based correction, and the variation in native T1 and ECV among institutions was assessed using a coefficient of variation (CoV).ResultsThe global native T1 value significantly differed between the institutions (1198.7 ± 32.1 ms, institution A; 1217.7 ± 39.9 ms, institution B; 1232.7 ± 31.1 ms, institution C; p = 0.002), but the mean ECV did not (26.6-27.5%, p = 0.355). After phantom-based correction, the global native T1 and ECV were 1289.7 ± 32.4 ms and 25.0 ± 2.7%, respectively, and CoV for native T1 between the three institutions decreased from 3.0 to 2.5%. The corrected native T1 value did not significantly differ between institutions (1284.5 ± 31.5 ms, institution A; 1296.5 ± 39.1 ms, institution B; 1291.3 ± 29.3 ms, institution C; p = 0.440), and neither did the ECV (24.4-25.9%, p = 0.078).ConclusionsThe phantom-based correction method can provide standardized reference T1 values in healthy subjects.Key points• After phantom-based correction, the global native T1 of 16 entire myocardial segments on 3-T cardiac MRI is 1289.4 ± 32.4 ms, and the extracellular volume fraction was 25.0 ± 2.7% for healthy subjects. • After phantom - based correction was applied, the differences in the global native T1 among institutions became insignificant, and the CoV also decreased from 3.0 to 2.5%.

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A method for estimating intracellular sodium concentration and extracellular volume fraction in brain in vivo using sodium magnetic resonance imaging.

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A method for estimating intracellular sodium concentration and extracellular volume fraction in brain in vivo using sodium magnetic resonance imaging.

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