In vivo monitoring of renal tubule volume fraction using dynamic parametric MRI.

PURPOSE: The increasing incidence of kidney diseases is a global concern, and current biomarkers and treatments are inadequate. Changes in renal tubule luminal volume fraction (TVF) serve as a rapid biomarker for kidney disease and improve understanding of renal (patho)physiology. This study uses the amplitude of the long T2 component as a surrogate for TVF in rats, by applying multiexponential analysis of the T2-driven signal decay to examine micromorphological changes in renal tissue. METHODS: Simulations were conducted to identify a low mean absolute error (MAE) protocol and an accelerated protocol customized for the in vivo study of T2 mapping of the rat kidney at 9.4 T. We then validated our bi-exponential approach in a phantom mimicking the relaxation properties of renal tissue. This was followed by a proof-of-principle demonstration using in vivo data obtained during a transient increase of renal pelvis and tubular pressure. RESULTS: Using the low MAE protocol, our approach achieved an accuracy of MAE < 1% on the mechanical phantom. The T2 mapping protocol customized for in vivo study achieved an accuracy of MAE < 3%. Transiently increasing pressure in the renal pelvis and tubules led to significant changes in TVF in renal compartments: ΔTVFcortex = 4.9%, ΔTVFouter_medulla = 4.5%, and ΔTVFinner_medulla = -14.6%. CONCLUSION: These results demonstrate that our approach is promising for research into quantitative assessment of renal TVF in in vivo applications. Ultimately, these investigations have the potential to help reveal mechanism in acute renal injury that may lead to chronic kidney disease, which will support research into renal disorders.

Insights and improvements in correspondence between axonal volume fraction measured with diffusion-weighted MRI and electron microscopy.

Biophysical diffusion-weighted imaging (DWI) models are increasingly used in neuroscience to estimate the axonal water fraction ( f AW ), which in turn is key for noninvasive estimation of the axonal volume fraction ( f A ). These models require thorough validation by comparison with a reference method, for example, electron microscopy (EM). While EM studies often neglect the unmyelinated axons and solely report the fraction of myelinated axons, in DWI both myelinated and unmyelinated axons contribute to the DWI signal. However, DWI models often include simplifications, for example, the neglect of differences in the compartmental relaxation times or fixed diffusivities, which in turn might affect the estimation of f AW . We investigate whether linear calibration parameters (scaling and offset) can improve the comparability between EM- and DWI-based metrics of f A . To this end, we (a) used six DWI models based on the so-called standard model of white matter (WM), including two models with fixed compartmental diffusivities (e.g., neurite orientation dispersion and density imaging, NODDI) and four models that fitted the compartmental diffusivities (e.g., white matter tract integrity, WMTI), and (b) used a multimodal data set including ex vivo diffusion DWI and EM data in mice with a broad dynamic range of fibre volume metrics. We demonstrated that the offset is associated with the volume fraction of unmyelinated axons and the scaling factor is associated with different compartmental T 2 and can substantially enhance the comparability between EM- and DWI-based metrics of f A . We found that DWI models that fitted compartmental diffusivities provided the most accurate estimates of the EM-based f A . Finally, we introduced a more efficient hybrid calibration approach, where only the offset is estimated but the scaling is fixed to a theoretically predicted value. Using this approach, a similar one-to-one correspondence to EM was achieved for WMTI. The method presented can pave the way for use of validated DWI-based models in clinical research and neuroscience.

Tomoelastography and Pancreatic Extracellular Volume Fraction Derived From MRI for Predicting Clinically Relevant Postoperative Pancreatic Fistula.

BACKGROUND: Pancreatic stiffness and extracellular volume fraction (ECV) are potential imaging biomarkers for pancreatic fibrosis. Clinically relevant postoperative fistula (CR-POPF) is one of the most severe complications after pancreaticoduodenectomy. Which imaging biomarker performs better for predicting the risk of CR-POPF remains unknown. PURPOSE: To evaluate the diagnostic performance of ECV and tomoelastography-derived pancreatic stiffness for predicting the risk of CR-POPF in patients undergoing pancreaticoduodenectomy. STUDY TYPE: Prospective. POPULATION: Eighty patients who underwent multiparametric pancreatic MRI before pancreaticoduodenectomy, among whom 16 developed CR-POPF and 64 did not. FIELD STRENGTH/SEQUENCE: 3 T/tomoelastography and precontrast and postcontrast T1 mapping of the pancreas. ASSESSMENT: Pancreatic stiffness was measured on the tomographic c-map, and pancreatic ECV was calculated from precontrast and postcontrast T1 maps. Pancreatic stiffness and ECV were compared with histological fibrosis grading (F0-F3). The optimal cutoff values for predicting CR-POPF were determined, and the correlation between CR-POPF and imaging parameters was evaluated. STATISTICAL TESTS: The Spearman's rank correlation and multivariate linear regression analysis was conducted. The receiver operating characteristic curve analysis and logistic regression analysis was performed. A double-sided P < 0.05 indicated a statistically significant difference. RESULTS: Pancreatic stiffness and ECV both showed a significantly positive correlation with histological pancreatic fibrosis (r = 0.73 and 0.56, respectively). Patients with advanced pancreatic fibrosis had significantly higher pancreatic stiffness and ECV compared to those with no/mild fibrosis. Pancreatic stiffness and ECV were also correlated with each other (r = 0.58). Lower pancreatic stiffness (<1.38 m/sec), lower ECV (<0.28), nondilated main pancreatic duct (<3 mm) and pathological diagnosis other than pancreatic ductal adenocarcinoma were associated with higher risk of CR-POPF at univariate analysis, and pancreatic stiffness was independently associated with CR-POPF at multivariate analysis (odds ratio: 18.59, 95% confidence interval: 4.45, 77.69). DATA CONCLUSION: Pancreatic stiffness and ECV were associated with histological fibrosis grading, and pancreatic stiffness was an independent predictor for CR-POPF. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY STAGE: 5.

Elevated myocardial extracellular volume fraction is associated with the development of conduction pathway defects following transcatheter aortic valve replacement.

BACKGROUND: Transcatheter aortic valve replacement (TAVR) has become an established method of aortic stenosis treatment but suffers from the risk of heart block and pacemaker requirement. Risk stratification for patients who may develop heart block remains imperfect. Simultaneously, myocardial fibrosis as measured by cardiac magnetic resonance imaging (CMR) has been demonstrated as a prognostic indicator of ventricular recovery and mortality following TAVR. However, the association of CMR-based measures of myocardial fibrosis with post-TAVR conduction disturbances has not yet been explored. AIMS: We evaluated whether myocardial fibrosis, as measured by late gadolinium enhancement and extracellular volume (ECV) from CMR would be associated with new conduction abnormalities following TAVR. METHODS: One hundred seventy patients who underwent CMR within 2 months before TAVR were retrospectively reviewed. Septal late gadolinium enhancement (LGE) and ECV measurements were made as surrogates for replacement and interstitial fibrosis respectively. New conduction abnormalities were defined by the presence of transient or permanent atrioventricular block, new bundle branch blocks, and need for permanent pacemaker. Association of myocardial fibrosis and new conduction derangements were tested using receiver operator curve (ROC) and regression analysis in patients with and without pre-existing conduction issues. RESULTS: Forty-six (27.1%) patients developed post-TAVR conduction deficits. ECV was significantly higher among patients who experienced new conduction defects (26.2 ± 3.45% vs. 24.7% ± 4.15%, p value: 0.020). A greater fraction of patients that had new conduction defects had an elevated ECV of ≥26% (54.3% vs. 36.3%, p value: 0.026). ECV ≥ 26% was independently associated with the development of new conduction defects (odds ratio [OR]: 2.364, p value: 0.030). ROC analysis revealed a significant association of ECV with new conduction defects with an area under the receiver operating characteristic curve (AUC) of 0.632 (95% confidence interval: 0.555-0.705, p value: 0.005). The combination of prior right bundle branch block (RBBB) and ECV revealed a greater AUC of 0.779 (0.709-0.839, p value: <0.001) than RBBB alone (Delong p value: 0.049). No association of LGE/ECV with new conduction defects was observed among patients with pre-existing conduction disease. Among patients without baseline conduction disease, ECV was independently associated with the development of new conduction deficits (OR: 3.685, p value: 0.008). CONCLUSION: The present study explored the association of myocardial fibrosis, as measured by LGE and ECV with conduction deficits post-TAVR. Our results demonstrate an association of ECV, and thereby interstitial myocardial fibrosis, with new conduction derangement post-TAVR and introduce ECV as a potentially new risk stratification tool to identify patients at higher risk for needing post-TAVR surveillance and/or permanent pacemaker.

Extracellular Volume Fraction by Computed Tomography Predicts Prognosis After Transcatheter Aortic Valve Replacement.

BACKGROUND: Extracellular volume fraction (ECV) on magnetic resonance imaging can predict prognosis after aortic valve replacement in patients with aortic stenosis (AS). However, the usefulness of ECV on computed tomography (CT) for patients who have undergone transcatheter aortic valve replacement (TAVR) is unclear, so we investigated whether ECV analysis on CT is associated with clinical outcomes in TAVR candidates.Methods and Results: We analyzed 127 patients with severe AS who underwent preoperative CT for TAVR. We evaluated the utility of ECV analysis on single-energy CT for predicting patient prognosis after TAVR. The primary outcome was a composite of all-cause death and hospitalization due to heart failure (HF) after TAVR. 15 patients (12%) had composite outcomes: 4 deaths and 11 hospitalizations due to HF. In multivariate survival analysis using the Cox proportional hazard model, atrial fibrillation (AF) (hazard ratio (HR), 7.86; 95% confidence interval (CI), 2.57-24.03; P<0.001), history of congestive HF (HR, 4.91; 95% CI, 1.49-16.2; P=0.009) and ECV ≥32.6% on CT (HR, 6.96; 95% CI, 1.92-25.12; P=0.003) were independent predictors of composite outcomes. On Kaplan-Meier analysis, the higher ECV group (≥32.6%) had a significantly greater number of composite outcomes than the lower ECV group (P<0.001). CONCLUSIONS: ECV on CT is an independent predictor of prognosis after TAVR.

Quantitating myocardial fibrosis using extracellular extravascular volume determined from computed tomography myocardial perfusion imaging.

PURPOSE: Both of extracellular extravascular volume (EEV) and extracellular volume fraction (ECV) were proposed to quantify enlargement of myocardial interstitial space due to myocardium loss or fibrosis. The study aimed to investigate the feasibility of using EEV derived from myocardial computed tomography (CT) perfusion imaging (VPCT) and extracellular volume quantification with single-energy subtraction CT (ECV- SECT) for quantifying myocardial fibrosis. METHODS: In this study, 17 patients with suspected and known coronary artery disease underwent examination using a dual-source CT scanner. The EEV- VPCT was derived from dynamic whole-heart myocardial perfusion imaging, and the ECV_SECT was calculated from late-enhanced images 5 min after bolus contrast injection by subtracting the noncontrast baseline. The late gadolinium enhancement (LGE) on cardiac magnetic resonance (CMR) imaging was used as a reference. RESULTS: In total, 11 patients and 73 segments exhibited positivity for LGE on CMR imaging. These were classified into three groups according to the segments: fibrotic segments (group I, n = 73), nonfibrotic segments in LGE-positive patients (group II, n = 103), and segments in LGE-negative patients (group III, n = 80). ECV- SECT, EEV- VPCT, myocardial blood flow (MBF), and myocardial blood volume (MBV) significantly differed among these groups (all P < 0.05). ECV- SECT was significantly higher and EEV- VPCT, MBF, and MBV were significantly lower in fibrotic myocardial segments than in nonfibrotic ones (all P < 0.01). ECV- SECT and EEV- VPCT independently affected myocardial fibrosis. There was no significant correlation between ECV- SECT and EEV- VPCT. The capability of EEV- VPCT to diagnose myocardial fibrosis was equivalent to that of ECV- SECT (area under the curve: 0.798 vs. 0.806, P = 0.844). ECV- SECT of > 41.2% and EEV- VPCT of < 10.3% indicated myocardial fibrosis. CONCLUSIONS: EEV- VPCT is actually first-pass distribution volume that can feasibly be used to quantify myocardial fibrosis. Furthermore, the diagnostic efficacy of EEV- VPCT is comparable to that of ECV- SECT.

Liver fat volume fraction measurements based on multi-material decomposition algorithm in patients with nonalcoholic fatty liver disease: the influences of blood vessel, location, and iodine contrast.

BACKGROUND: In recent years, spectral CT-derived liver fat quantification method named multi-material decomposition (MMD) is playing an increasingly important role as an imaging biomarker of hepatic steatosis. However, there are various measurement ways with various results among different researches, and the impact of measurement methods on the research results is unknown. The aim of this study is to evaluate the reproducibility of liver fat volume fraction (FVF) using MMD algorithm in nonalcoholic fatty liver disease (NAFLD) patients when taking blood vessel, location, and iodine contrast into account during measurement. METHODS: This retrospective study was approved by the institutional ethics committee, and the requirement for informed consent was waived because of the retrospective nature of the study. 101 patients with NAFLD were enrolled in this study. Participants underwent non-contrast phase (NCP) and two-phase enhanced CT scanning (late arterial phase (LAP) and portal vein phase (PVP)) with spectral mode. Regions of interest (ROIs) were placed at right posterior lobe (RPL), right anterior lobe (RAL) and left lateral lobe (LLL) to obtain FVF values on liver fat images without and with the reference of enhanced CT images. The differences of FVF values measured under different conditions (ROI locations, with/without enhancement reference, NCP and enhanced phases) were compared. Friedman test was used to compare FVF values among three phases for each lobe, while the consistency of FVF values was assessed between each two phases using Bland-Altman analysis. RESULTS: Significant difference was found between FVF values obtained without and with the reference of enhanced CT images. There was no significant difference about FVF values obtained from NCP images under the reference of enhanced CT images between any two lobes or among three lobes. The FVF value increased after the contrast injection, and there were significant differences in the FVF values among three scanning phases. Poor consistencies of FVF values between each two phases were found in each lobe by Bland-Altman analysis. CONCLUSION: MMD algorithm quantifying hepatic fat was reproducible among different lobes, while was influenced by blood vessel and iodine contrast.

Lima bean (Phaseolus lunatus Linn.) protein isolate as a promising plant protein mixed with xanthan gum for stabilizing oil-in-water emulsions.

BACKGROUND: Lima bean protein isolate (LPI) is an underutilized plant protein. Similar to other plant proteins, it may display poor emulsification properties. In order to improve its emulsifying properties, one effective approach is using protein and polysaccharide mixtures. This work investigated the structural and emulsifying properties of LPI as well as the development of an LPI/xanthan gum (XG)-stabilized oil-in-water emulsion. RESULTS: The highest protein solubility (84.14%) of LPI was observed and the molecular weights (Mw ) of most LPI subunits were less than 35 kDa. The enhanced emulsifying activity index (15.97 m2 g-1 ) of LPI might be associated with its relatively high protein solubility and more low-Mw subunits (Mw < 35 kDa). The effects of oil volume fraction (ϕ) on droplet size, microstructure, rheological behavior and stability of emulsions were investigated. As ϕ increased from 0.2 to 0.8, the emulsion was arranged from spherical and dispersed oil droplets to polyhedral packing of oil droplets adjacent to each other, while the LPI/XG mixtures changed from particles (in the uncrowded interfacial layer) to lamellae (in the crowded interfacial layer). When ϕ was 0.6, the emulsion was in a transitional state with the coexistence of particles and lamellar structures on the oil droplet surface. The LPI/XG-stabilized emulsions with ϕ values of 0.6-0.8 showed the highest stability during a 14-day storage period. CONCLUSION: This study developed a promising plant-based protein resource, LPI, and demonstrates potential application of LPI/XG as an emulsifying stabilizer in foods. © 2023 Society of Chemical Industry.

Histologically Validated Myocardial Fibrosis in Relation to Left Ventricular Geometry and Its Function in Aortic Stenosis.

Background and Objectives: The combination of aortic valve stenosis (AS) and ischemic heart disease (IHD) is quite common and is associated with myocardial fibrosis (MF). The purpose of this study was to evaluate the association between the histologically verified left ventricular (LV) MF and its geometry and function in isolated AS and AS within IHD groups. Materials and Methods: In a single-center, prospective trial, 116 patients underwent aortic valve replacement (AVR) with/without concomitant surgery. The study population was divided into groups of isolated AS with/without IHD. Echocardiography was used, and LV measurements and aortic valve parameters were obtained from all patients. Myocardial tissue was procured from all study patients undergoing elective surgery. Results: There were no statistical differences between isolated AS and AS+IHD groups in LV parameters or systolic and diastolic functions during the study periods. The collagen volume fraction was significantly different between the isolated AS and AS+IHD groups and was 7.3 ± 5.6 and 8.3 ± 6.4, respectively. Correlations between MF and left ventricular end-diastolic diameter (LVEDD) (r = 0.59, p = < 0.001), left ventricular mass (LVM) (r = 0.42, p = 0.011), left ventricular ejection fraction (LVEF) (r = -0.67, p < 0.001) and an efficient orifice area (EOA) (r = 0.371, p = 0.028) were detected in isolated AS during the preoperative period; the same was observed for LVEDD (r = 0.45, p = 0.002), LVM (r = 0.36, p = 0.026), LVEF (r = -0.35, p = 0.026) and aortic annulus (r = 0.43, p = 0.018) in the early postoperative period; and LVEDD (r = 0.35, p ≤ 0.05), LVM (r = 0.43, p = 0.007) and EOA (r = 0.496, p = 0.003) in the follow-up period. In the group of AS and IHD, correlations were found only with LV posterior wall thickness (r = 0.322, p = 0.022) in the follow-up period. Conclusions: Histological MF in AS was correlated with LVM and LVEDD in all study periods. No correlations between MF and LV parameters were found in aortic stenosis in the ischemic heart disease group across all study periods.

Spherical means-based free-water volume fraction from diffusion MRI increases non-linearly with age in the white matter of the healthy human brain.

The term free-water volume fraction (FWVF) refers to the signal fraction that could be found as the cerebrospinal fluid of the brain, which has been demonstrated as a sensitive measure that correlates with cognitive performance and various neuropathological processes. It can be quantified by properly fitting the isotropic component of the magnetic resonance (MR) signal in diffusion-sensitized sequences. Using N=287 healthy subjects (178F/109M) aged 25-94, this study examines in detail the evolution of the FWVF obtained with the spherical means technique from multi-shell acquisitions in the human brain white matter across the adult lifespan, which has been previously reported to exhibit a positive trend when estimated from single-shell data using the bi-tensor signal representation. We found evidence of a noticeably non-linear gain after the sixth decade of life, with a region-specific variate and varying change rate of the spherical means-based multi-shell FWVF parameter with age, at the same time, a heteroskedastic pattern across the adult lifespan is suggested. On the other hand, the FW corrected diffusion tensor imaging (DTI) leads to a region-dependent flattened age-related evolution of the mean diffusivity (MD) and fractional anisotropy (FA), along with a considerable reduction in their variability, as compared to the studies conducted over the standard (single-component) DTI. This way, our study provides a new perspective on the trajectory-based assessment of the brain and explains the conceivable reason for the variations observed in FA and MD parameters across the lifespan with previous studies under the standard diffusion tensor imaging.

IMPULSED model based cytological feature estimation with U-Net: Application to human brain tumor at 3T.

PURPOSE: This work introduces and validates a deep-learning-based fitting method, which can rapidly provide accurate and robust estimation of cytological features of brain tumor based on the IMPULSED (imaging microstructural parameters using limited spectrally edited diffusion) model fitting with diffusion-weighted MRI data. METHODS: The U-Net was applied to rapidly quantify extracellular diffusion coefficient (Dex ), cell size (d), and intracellular volume fraction (vin ) of brain tumor. At the training stage, the image-based training data, synthesized by randomizing quantifiable microstructural parameters within specific ranges, was used to train U-Net. At the test stage, the pre-trained U-Net was applied to estimate the microstructural parameters from simulated data and the in vivo data acquired on patients at 3T. The U-Net was compared with conventional non-linear least-squares (NLLS) fitting in simulations in terms of estimation accuracy and precision. RESULTS: Our results confirm that the proposed method yields better fidelity in simulations and is more robust to noise than the NLLS fitting. For in vivo data, the U-Net yields obvious quality improvement in parameter maps, and the estimations of all parameters are in good agreement with the NLLS fitting. Moreover, our method is several orders of magnitude faster than the NLLS fitting (from about 5 min to <1 s). CONCLUSION: The image-based training scheme proposed herein helps to improve the quality of the estimated parameters. Our deep-learning-based fitting method can estimate the cell microstructural parameters fast and accurately.

Simultaneous estimation of the cellular water exchange rate, intracellular volume fraction, and longitudinal relaxation rate in cancer cells.

The purpose of the current study was to investigate the feasibility of simultaneously estimating the cellular water efflux rate ( k ie ), intracellular longitudinal relaxation rate ( R 10 i ), and intracellular volume fraction ( v i ) of a cell suspension using multiple samples with different gadolinium concentrations. Numerical simulation studies were conducted to assess the uncertainty in the estimation of k ie , R 10 i , and v i from saturation recovery data using single (SC) or multiple concentrations (MC) of gadolinium-based contrast agent (GBCA). In vitro experiments with 4 T1 murine breast cancer and SCCVII squamous cell cancer models were conducted at 11 T to compare parameter estimation using the SC protocol with that using the MC protocol. The cell lines were challenged with a Na+ /K+ -ATPase inhibitor, digoxin, to assess the treatment response in terms of k ie , R 10 i , and v i . Data analysis was conducted using the two-compartment exchange model for parameter estimation. The simulation study data demonstrate that the MC method, compared with the SC method, reduces the uncertainty of the estimated k ie by decreasing the interquartile ranges from 27.3% ± 3.7% to 18.8% ± 5.1% and the median differences from ground truth from 15.0% ± 6.3% to 7.2% ± 4.2%, while estimating R 10 i and v i simultaneously. In the cell studies, the MC method demonstrated reduced uncertainty in overall parameter estimation compared with the SC approach. MC method-measured parameter changes in cells treated with digoxin increased R 10 i by 11.7% (p = 0.218) and k ie by 5.9% (p = 0.234) for 4 T1 cells, respectively, and decreased R 10 i by 28.8% (p = 0.226) and k ie by 1.6% (p = 0.751) for SCCVII cells, respectively. v i did not change noticeably by the treatment. The results of this study substantiate the feasibility of using saturation recovery data of multiple samples with different GBCA concentrations for simultaneous measurement of the cellular water efflux rate, intracellular volume fraction, and intracellular longitudinal relaxation rate in cancer cells.

T1 mapping and extracellular volume fraction measurement to evaluate the poor-prognosis factors in patients with cervical squamous cell carcinoma.

PURPOSE: To evaluate the clinical feasibility of T1 mapping and extracellular volume fraction (ECV) measurement in assessing prognostic factors in patients with cervical squamous cell carcinoma (CSCC). MATERIALS AND METHODS: A total of 117 CSCC patients and 59 healthy volunteers underwent T1 mapping and diffusion-weighted imaging (DWI) on a 3 T system. Native T1 , contrast-enhanced T1 , ECV, and apparent diffusion coefficient (ADC) were calculated and compared based on surgico-pathologically verified deep stromal infiltration, parametrial invasion (PMI), lymphovascular space invasion (LVSI), lymph node metastasis, stage, histologic grade, and the Ki-67 labeling index (LI). RESULTS: Native T1 , contrast-enhanced T1 , ECV, and ADC values were significantly different between CSCC and the normal cervix (all p < 0.05). No significant differences were observed in any parameters of CSCC when the tumors were grouped by stromal infiltration or lymph node status, respectively (all p > 0.05). In subgroups of the tumor stage and PMI, native T1 was significantly higher for advanced-stage (p = 0.032) and PMI-positive CSCC (p = 0.001). In subgroups of the grade and Ki-67 LI, contrast-enhanced T1 was significantly higher for high-grade (p = 0.012) and Ki-67 LI ≥ 50% tumors (p = 0.027). ECV was significantly higher in LVSI-positive CSCC than in LVSI-negative CSCC (p < 0.001). ADC values showed a significant difference for the grade (p < 0.001) but none for the other subgroups. CONCLUSION: Both T1 mapping and DWI could stratify the CSCC histologic grade. In addition, T1 mapping and ECV measurement might provide more quantitative metrics for noninvasively predicting poor prognostic factors and aiding in preoperative risk assessment in CSCC patients.

Blood-based graphene oxide nanofluid flow through capillary in the presence of electromagnetic fields: A Sutterby fluid model.

Pumping devices with the electrokinetics phenomena are important in many microscale transport phenomena in physiology. This study presents a theoretical and numerical investigation on the peristaltic pumping of non-Newtonian Sutterby nanofluid through capillary in presence of electromagnetohydrodynamics. Here blood (Sutterby fluid) is taken as a base fluid and nanofluid is prepared by the suspension of graphene oxide nanoparticles in blood. Graphene oxide is extremely useful in the medical domain for drug delivery and cancer treatment. The modified Buongiorno model for nanofluids and Poisson-Boltzmann ionic distribution is adopted for the formulation of the present problem. Constitutive flow equations are linearized by the implementation of approximations of low Reynolds number, large wavelength, and the Debye-Hückel linearization. The numerical solution of reduced coupled and nonlinear set of equations is computed through Mathematica and graphical illustration is presented. Further, the impacts of buoyancy forces, thermal radiation, and mixed convection are also studied. It is revealed in this investigation that the inclusion of a large number of nanoparticles alters the flow characteristics significantly and boosts the heat transfer mechanism. Moreover, the pumping power of the peristaltic pump can be enhanced by the reduction in the width of the electric double layer which can be done by altering the electrolyte concentration.

Quantification of Early Diffuse Myocardial Fibrosis Through 7.0 T Cardiac Magnetic Resonance T1 Mapping in a Type 1 Diabetic Mellitus Mouse Model.

BACKGROUND: Diffuse myocardial interstitial fibrosis (DMIF) is a key factor for heart failure (HF) in diabetic cardiomyopathy. MRI T1-mapping technique can quantitatively evaluate DMIF. PURPOSE: To evaluate of early DMIF in a type 1 diabetes mellitus (T1DM) mouse model through 7.0 T MRI T1 mapping. STUDY TYPE: Prospective. ANIMAL MODEL: A total of 50 8-week-old C57Bl/6J male mice were divided into control (n = 20) and T1DM (n = 30) groups. FIELD STRENGTH/SEQUENCE: A 7.0 T small animal MRI; gradient echo Look-Locker inversion recovery T1-mapping sequence; cine MRI. Scans were acquired in control and T1DM mice every 4 weeks until 24 weeks. ASSESSMENT: End-diastolic volume (EDV), end-systolic volume (ESV), ejection fraction (EF), left ventricle (LV) mass, fractional shortening (FS), and E/A ratio. They were evaluated through echocardiography and cine MRI. The extracellular volume fraction (ECV) was calculated. Sirius Red staining was performed and calculated collagen volume fraction (CVF). STATISTICAL TESTS: Differences in ECV and CVF between two groups were analyzed using one-way analysis of variance. The correlation between ECV and CVF was assessed using Pearson's correlations. RESULTS: Compared with the control group, a progressive decrease in FS, EF, and E/A ratio was observed in the T1DM group. Both ECV and CVF values gradually increased during diabetes progression. A significant increase in ECV and CVF values was observed at 12 weeks (ECV: 32.5% ± 1.6% vs. 28.1% ± 1.8%; CVF: 6.9% ± 1.8% vs. 3.3% ± 1.1%). ECV showed a strong correlation with CVF (r = 0.856). DATA CONCLUSION: ECV is an accurate and feasible imaging marker that can be used to quantitatively assess DMIF changes over time in T1DM mice. ECV has potential to accurately detect DMIF in the early stage and may be a useful imaging tool to assess the need for early intervention in T1DM mice. EVIDENCE LEVEL: 1 TECHNICAL EFFICACY: Stage 3.

Preliminary MRI Study of Extracellular Volume Fraction for Identification of Lymphovascular Space Invasion of Cervical Cancer.

BACKGROUND: Lymphovascular space invasion (LVSI) is a risk factor for poor prognosis of cervical cancer. Preoperative identification of LVSI is very difficult. PURPOSE: To evaluate the potential of extracellular volume (ECV) fraction based on T1 mapping in preoperative identification of LVSI in cervical cancer compared with dynamic contrast-enhanced MRI (DCE-MRI). STUDY TYPE: Retrospective. SUBJECTS: A total of 79 patients (median age 54 years) with cervical cancer were classified into LVSI group (n = 29) and without LVSI group (n = 50) according to postoperative pathology. FIELD STRENGTH/SEQUENCE: A 3-T, noncontrast and contrast-enhanced T1 mapping performed with volume interpolated breath hold examination (VIBE) sequence, DCE-MRI applied with 3D T1-weighted VIBE sequence. ASSESSMENT: Regions of interest along the medial edge of the lesion were drawn on slices depicting the maximum cross-section of the tumor. The noncontrast and contrast-enhanced T1 value of the tumor and arteries in the same slice were measured, and ECV was calculated from T1 values. The parametric maps (Ktrans , kep , and ve ) derived from DCE-MRI standard Toft's model were evaluated. STATISTICAL TESTS: ECV, Ktrans , kep , and ve between groups with and without LVSI were compared using Student's t-test. The receiver operating characteristic (ROC) curve and DeLong test were used to evaluate and compare the diagnostic performance of ECV, Ktrans , kep , and ve for differentiating LVSI. P < 0.05 was considered statistically significant. RESULTS: The ECV and Ktrans of the LVSI group were significantly higher than that of non-LVSI group (52.86% vs. 36.77%, 0.239 vs. 0.176, respectively), and no significant differences in Kep or ve values were observed (P = 0.071 and P = 0.168, respectively). The ECV fraction showed significantly higher area under ROC curve than Ktrans for differentiating LVSI (0.874 vs. 0.655, respectively). DATA CONCLUSION: ECV measurements based on T1 mapping might improve the discrimination between patients with and without LVSI in cervical cancer, showing better performance for this purpose than DCE-MRI. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 2.

Early detection of myocardial fibrosis in cardiomyopathy in the absence of late enhancement: role of T1 mapping and extracellular volume analysis.

OBJECTIVES: To analyze myocardial fibrosis in dilated cardiomyopathy (DCM) patients with no late gadolinium enhancement (LGE) on cardiac magnetic resonance (CMR) using T1 mapping and extracellular volume (ECV) and investigate the potential correlation with left ventricular (LV) dilation and dysfunction. METHODS: The study included 41 DCM patients without LGE and 79 healthy controls. T1 and ECV were compared between the two groups using multivariable logistic regression analysis. The correlations between histological and functional parameters were evaluated using Pearson's correlation. RESULTS: Mean native myocardial T1 and ECV were significantly higher in the DCM group compared to controls (p ≤ 0.001, respectively). Multivariable logistic regression revealed that ECV (mean, minimum), LV ejection fraction (LVEF), and LV end-diastolic diameter (LVEDD) were independent discriminators for LGE-negative DCM; the area under the curve (AUC) of LVEF, LVEDD, ECV mean, and ECV minimum were 0.97, 0.96, 0.88, and 0.68, respectively. In the DCM group, LVEDD and LVEF were positively and negatively correlated with ECV, respectively. LVEDV index and LV end-systolic volume (LVESV) index were positively correlated with native-T1 and ECV, and the absolute value of LV global strain had a negative correlation with ECV. CONCLUSIONS: Early myocardial fibrosis in DCM could be detected by prolonged native T1 and elevated ECV despite the absence of LGE on CMR. Moreover, the change of histological characteristics of myocardium in DCM was correlated with LV dilation and dysfunction. KEY POINTS: • At an early stage, patients with DCM may have myocardial fibrosis despite the absence of LGE. • T1 mapping and ECV are efficient methods for early detection of potential myocardial fibrosis. • Increased native T1 and ECV are correlated with left ventricular dilation and dysfunction in LGE-negative DCM patients.

A novel cardiac magnetic resonance-based personalized risk stratification model in dilated cardiomyopathy: a prospective study.

OBJECTIVES: To explore individual weight of cardiac magnetic resonance (CMR) metrics to predict mid-term outcomes in patients with dilated cardiomyopathy (DCM), and develop a risk algorithm for mid-term outcome based on CMR biomarkers. MATERIALS AND METHODS: Patients with DCM who underwent CMR imaging were prospectively enrolled in this study. The primary endpoint was a composite of heart failure (HF) death, sudden cardiac death (SCD), aborted SCD, and heart transplantation. RESULTS: A total of 407 patients (age 48.1 ± 13.8 years, 331 men) were included in the final analysis. During a median follow-up of 21.7 months, 63 patients reached the primary endpoint. NYHA class III/IV (HR = 2.347 [1.073-5.133], p = 0.033), left ventricular ejection fraction (HR = 0.940 [0.909-0.973], p < 0.001), late gadolinium enhancement (LGE) > 0.9% and ≤ 6.6% (HR = 3.559 [1.020-12.412], p = 0.046), LGE > 6.6% (HR = 6.028 [1.814-20.038], p = 0.003), and mean extracellular volume (ECV) fraction ≥ 32.8% (HR = 5.922 [2.566-13.665], p < 0.001) had a significant prognostic association with the primary endpoints (C-statistic: 0.853 [0.810-0.896]). Competing risk regression analyses showed that patients with mean ECV fraction ≥ 32.8%, LGE ≥ 5.9%, global circumferential strain ≥ - 5.6%, or global longitudinal strain ≥ - 7.3% had significantly shorter event-free survival due to HF death and heart transplantation. Patients with mean ECV fraction ≥ 32.8% and LGE ≥ 5.9% had significantly shorter event-free survival due to SCD or aborted SCD. CONCLUSION: ECV fraction may be the best independently risk factor for the mid-term outcomes in patients with DCM, surpassing LVEF and LGE. LGE has a better prognostic value than other CMR metrics for SCD and aborted SCD. The risk stratification model we developed may be a promising non-invasive tool for decision-making and prognosis. CLINICAL RELEVANCE STATEMENT: "One-stop" assessment of cardiac function and myocardial characterization using cardiac magnetic resonance might improve risk stratification of patients with DCM. In this prospective study, we propose a novel risk algorithm in DCM including NYHA functional class, LVEF, LGE, and ECV. KEY POINTS: • The present study explores individual weight of CMR metrics for predicting mid-term outcomes in dilated cardiomyopathy. • We have developed a novel risk algorithm for dilated cardiomyopathy that includes cardiac functional class, ejection fraction, late gadolinium enhancement, and extracellular volume fraction. • Personalized risk model derived by CMR contributes to clinical assessment and individual decision-making.

Clinical manifestations and MRI features of Danon disease: a case series.

BACKGROUND: Danon disease (DD) is an exceptionally uncommon X-linked dominant lysosomal glycogen storage disorder characterized by pronounced ventricular hypertrophy and cardiac insufficiency. The timely identification of cardiac impairment in individuals with DD holds significant clinical importance. CASE PRESENTATION: We present a case of Danon Disease in a three-generation pedigree from Anhui Province, China. Clinical features and laboratory data were collected and analyzed for a 16-year-old male proband (III-1) and two affected female family members (II-2 and II-3). The proband exhibited Wolf-Parkinson-White syndrome, hypertrophic cardiomyopathy, abnormal cognitive function, and muscle weakness. Gene sequencing confirmed a mutation (c.963G > A) in the LAMP-2 gene. CONCLUSION: Patients with DD may present both dilated and hypertrophic cardiomyopathy. Comprehensive myocardial tissue characterization by MRI plays a key role in the diagnosis of the disease.

Machine learning to predict left ventricular reverse remodeling by guideline-directed medical therapy by utilizing texture feature of extracellular volume fraction in patients with non-ischemic dilated cardiomyopathy.

Extracellular volume fraction (ECV) by cardiac magnetic resonance (CMR) allows for the non-invasive quantification of diffuse myocardial fibrosis. Texture analysis and machine learning are now gathering attention in the medical field to exploit the ability of diagnostic imaging for various diseases. This study aimed to investigate the predictive value of texture analysis of ECV and machine learning for predicting response to guideline-directed medical therapy (GDMT) for patients with non-ischemic dilated cardiomyopathy (NIDCM). A total of one-hundred and fourteen NIDCM patients [age: 63 ± 12 years, 91 (81%) males] were retrospectively analyzed. We performed texture analysis of ECV mapping of LV myocardium using dedicated software. We calculated nine histogram-based features (mean, standard deviation, maximum, minimum, etc.) and five gray-level co-occurrence matrices. Five machine learning techniques and the fivefold cross-validation method were used to develop prediction models for LVRR by GDMT based on 14 texture parameters on ECV mapping. We defined the LVRR as follows: LVEF increased ≥ 10% points and decreased LVEDV ≥ 10% on echocardiography after GDMT > 12 months. Fifty (44%) patients were classified as non-responders. The area under the receiver operating characteristics curve for predicting non-responder was 0.82 for eXtreme Gradient Boosting, 0.85 for support vector machine, 0.76 for multi-layer perception, 0.81 for Naïve Bayes, 0.77 for logistic regression, respectively. Mean ECV value was the most critical factor among texture features for differentiating NIDCM patients with LVRR and those without (0.28 ± 0.03 vs. 0.36 ± 0.06, p < 0.001). Machine learning analysis using the support vector machine may be helpful in detecting high-risk NIDCM patients resistant to GDMT. Mean ECV is the most crucial feature among texture features.