The clinical value of combining shear wave elastography, VOCAL technique, and T2* MRI of early gestation placenta to predict pre-eclampsia

OBJECTIVE

To investigate the clinical value of combining shear wave elastography (SWE) with the Volumetric Organ Computer-Aided AnaLysis (VOCAL) technique and T2* magnetic resonance imaging (MRI) to predict pre-eclampsia (PE).

METHODS

From December 2022 to March 2023, we recruited 31 pregnant women diagnosed with PE at our hospital as the observation group and 85 normal pregnant women as the control group. Differences in placental elasticity, vascularization index (VI), flow index (FI), vascularization flow index (VFI), and T2* MRI perfusion fraction (f) were compared between the two groups. Received operating characteristic (ROC) curve analysis was performed to evaluate the diagnostic value of placental elasticity, VI, FI, VFI, f, and their combination for predicting PE.

RESULTS

Placental elasticity was higher in the observation group than in the control group, while VI, FI, VFI, and f were lower in the observation group (all p < 0.05). The area under the curve (AUC) for placental elasticity, VI, FI, VFI, f, and their combination for predicting PE were 0.85, 0.77, 0.78, 0.84, 0.65, and 0.94, respectively. The sensitivity was 71%, 55%, 94%, 65%, 55%, and 81%. The specificity was 92%, 91%, 60%, 92%, 79%, and 98%. The combined prediction model had a higher AUC than the individual predictors (p < 0.05).

CONCLUSION

SWE combined with VOCAL technique and T2* MRI has high value for predicting PE and can provide reference information for clinical diagnosis.

Towards detection of early response in neoadjuvant chemotherapy of breast cancer using Bayesian intravoxel incoherent motion

Introduction

The early identification of good responders to neoadjuvant chemotherapy (NACT) holds a significant potential in the optimal treatment of breast cancer. A recent Bayesian approach has been postulated to improve the accuracy of the intravoxel incoherent motion (IVIM) model for clinical translation. This study examined the prediction and early sensitivity of Bayesian IVIM to NACT response.

Materials and methods

Seventeen female patients with breast cancer were scanned at baseline and 16 patients were scanned after Cycle 1. Tissue diffusion and perfusion from Bayesian IVIM were calculated at baseline with percentage change at Cycle 1 computed with reference to baseline. Cellular proliferative activity marker Ki-67 was obtained semi-quantitatively with percentage change at excision computed with reference to core biopsy.

Results

The perfusion fraction showed a significant difference (p = 0.042) in percentage change between responder groups at Cycle 1, with a decrease in good responders [-7.98% (-19.47-1.73), n = 7] and an increase in poor responders [10.04% (5.09-28.93), n = 9]. There was a significant correlation between percentage change in perfusion fraction and percentage change in Ki-67 (p = 0.042). Tissue diffusion and pseudodiffusion showed no significant difference in percentage change between groups at Cycle 1, nor was there a significant correlation against percentage change in Ki-67. Perfusion fraction, tissue diffusion, and pseudodiffusion showed no significant difference between groups at baseline, nor was there a significant correlation against Ki-67 from core biopsy.

Conclusion

The alteration in tumour perfusion fraction from the Bayesian IVIM model, in association with cellular proliferation, showed early sensitivity to good responders in NACT.

Clinical trial registration

https://clinicaltrials.gov/ct2/show/NCT03501394, identifier NCT03501394.

IVIM Parameters on MRI Could Predict ISUP Risk Groups of Prostate Cancers on Radical Prostatectomy

Purpose

To elucidate the usefulness of intravoxel incoherent motion (IVIM)/apparent diffusion coefficient (ADC) parameters in preoperative risk stratification using International Society of Urological Pathology (ISUP) grades.

Materials and Methods

Forty-five prostate cancer (PCa) patients undergoing radical prostatectomy (RP) after prostate multiparametric magnetic resonance imaging (mpMRI) were included. The ISUP grades were categorized into low-risk (I-II) and high-risk (III-V) groups, and the concordance between the preoperative and postoperative grades was analyzed. The largest region of interest (ROI) of the dominant tumor on each IVIM/ADC image was delineated to obtain its histogram values (i.e., minimum, mean, and kurtosis) of diffusivity (D), pseudodiffusivity (D*), perfusion fraction (PF), and ADC. Multivariable logistic regression analysis of the IVIM/ADC parameters without and with preoperative ISUP grades were performed to identify predictors for the postoperative high-risk group.

Results

Thirty-two (71.1%) of 45 patients had concordant preoperative and postoperative ISUP grades. D_mean, D*_kurtosis, PF_kurtosis, ADC_min, and ADC_mean were significantly associated with the postoperative ISUP risk group (all p < 0.05). D_mean and D*_kurtosis (model I, both p < 0.05) could predict the postoperative ISUP high-risk group with an area under the curve (AUC) of 0.842 and a 95% confidence interval (CI) of 0.726-0.958. The addition of D*_kurtosis to the preoperative ISUP grade (model II) may enhance prediction performance, with an AUC of 0.907 (95% CI 0.822-0.992).

Conclusions

The postoperative ISUP risk group could be predicted by D_mean and D*_kurtosis from mpMRI, especially D*_kurtosis. Obtaining the biexponential IVIM parameters is important for better risk stratification for PCa.

Magnet-targeted delivery of bone marrow-derived mesenchymal stem cells improves therapeutic efficacy following hypoxic-ischemic brain injury

Stem cell transplantation may represent a feasible therapeutic option for the recovery of neurological function in children with hypoxic-ischemic brain injury; however, the therapeutic efficacy of bone marrow-derived mesenchymal stem cells largely depends on the number of cells that are successfully transferred to the target. Magnet-targeted drug delivery systems can use a specific magnetic field to attract the drug to the target site, increasing the drug concentration. In this study, we found that the double-labeling using superparamagnetic iron oxide nanoparticle and poly-L-lysine (SPIO-PLL) of bone marrow-derived mesenchymal stem cells had no effect on cell survival but decreased cell proliferation 48 hours after labeling. Rat models of hypoxic-ischemic brain injury were established by ligating the left common carotid artery. One day after modeling, intraventricular and caudal vein injections of 1 × 10⁵ SPIO-PLL-labeled bone marrow-derived mesenchymal stem cells were performed. Twenty-four hours after the intraventricular injection, magnets were fixed to the left side of the rats’ heads for 2 hours. Intravoxel incoherent motion magnetic resonance imaging revealed that the perfusion fraction and the diffusion coefficient of rat brain tissue were significantly increased in rats treated with SPIO-PLL-labeled cells through intraventricular injection combined with magnetic guidance, compared with those treated with SPIO-PLL-labeled cells through intraventricular or tail vein injections without magnetic guidance. Hematoxylin-eosin and terminal deoxynucleotidyl transferase dUTP nick-end labeling (TUNEL) staining revealed that in rats treated with SPIO-PLL-labeled cells through intraventricular injection under magnetic guidance, cerebral edema was alleviated, and apoptosis was decreased. These findings suggest that targeted magnetic guidance can be used to improve the therapeutic efficacy of bone marrow-derived mesenchymal stem cell transplantation for hypoxic-ischemic brain injury. This study was approved by the Animal Care and Use Committee of The Second Hospital of Dalian Medical University, China (approval No. 2016-060) on March 2, 2016.

Evaluation of Placental Perfusion Based on Intravoxel Incoherent Motion Diffusion Weighted Imaging (IVIM-DWI) and Its Predictive Value for Late-Onset Fetal Growth Restriction

Objective The aim of this study was to investigate placental blood perfusion in middle and late pregnancy and explore its predictive value for fetal growth restriction (FGR).

Methods All pregnant women included in the study were examined using placental intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI). Three IVIM parameters (D, f, D*) were obtained for each pregnant woman and analyzed using Image J software. Perfusion fraction f is a radiological marker of placental perfusion. The pulsatility index (PI) of the uterine artery is used to indirectly evaluate placental function.

Results f-values were significantly lower in the late-onset FGR group compared to the normal late pregnancy group (19.07 vs. 27.78%). In addition, uterine artery PI values were markedly increased in the late-onset FGR group compared to the normal late pregnancy group (1.96 vs. 1.03), and neonatal weight was significantly lower in the late-onset FGR group (2.75 vs. 3.18 kg). There was a significant positive correlation between f-value, uterine artery PI and neonatal weight (r = 0.968, p < 0.01; r = 0.959, p < 0.01). There was a significant negative correlation between f-value and age of gestation (r = − 0.534, p < 0.01).

Conclusion Perfusion fraction f was strongly correlated with uterine artery blood flow resistance as measured by color Doppler and had a certain predictive value for late-onset FGR.

Quantitative parameters of intravoxel incoherent motion diffusion weighted imaging (IVIM-DWI): potential application in predicting pathological grades of pancreatic ductal adenocarcinoma

Background

The aim of this study was to compare intravoxel incoherent motion diffusion weighted imaging (IVIM-DWI) parameters such as standard apparent diffusion coefficient (ADC_standard), pure diffusion coefficient (D_slow), pseudodiffusion coefficient (D_fast) and perfusion fraction (ƒ) for differentiating pancreatic ductal adenocarcinoma (PDAC) with different pathological grades.

Methods

Institutional Review Board of our hospital approved this study protocol. Subjects comprised 38 PDACs confirmed by pathology. Pancreatic multiple b values DWI with 15 b values of 0, 10, 20, 40, 60, 80, 100, 150, 200, 400, 800, 1,000, 1200, 1,500, and 2,000 s/mm² was performed using GE Discovery MR750 3.0T scanner. ADC_standard, D_slow, D_fast and ƒ values of all PDACs were calculated using mono- and bi-exponential models. Parameters of well/moderately differentiated and poorly differentiated PDAC were compared using Independent Sample t-test. P values <0.05 were considered significant.

Results

Mean D_slow value of well/moderately differentiated PDAC was significantly lower than that of poorly differentiated PDAC (0.540×10^-3vs. 0.676×10^-3 mm²/s, P<0.001). Mean ƒ value of well/moderately differentiated PDAC was significantly higher than that of poorly differentiated PDAC (60.3% vs. 38.4%, P<0.001). The area under curve value of ƒ in differentiating well/moderately differentiated PDAC from poorly differentiated PDAC was slightly higher than that of D_slow (0.894>0.865). When the D_slow value was less than or equal to 0.599×10^-3 mm²/s, the sensitivity and specificity were 100% and 84.6% respectively. When ƒ value was greater than 49.6%, the sensitivity and specificity were 92.0% and 84.6% respectively.

Conclusions

D_slow and ƒ derived from IVIM-DWI model can be used to distinguish well/moderately differentiated PDAC from poorly differentiated PDAC. And to serve this purpose, D_slow and ƒ have high diagnostic performance. IVIM-DWI is a promising and non-invasive tool for predicting pathological grade of PDAC.

Intravoxel incoherent motion MRI in the brain: Impact of the fitting model on perfusion fraction and lesion differentiability

PURPOSE

To investigate the effect of the choice of the curve-fitting model on the perfusion fraction (f_IVIM ) with regard to tissue type characterization, correlation with microvascular anatomy, and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) parameters. Several curve-fitting models coexist in intravoxel incoherent motion (IVIM) MRI to derive the (f_IVIM ).

MATERIALS AND METHODS

In all, 29 patients with brain lesions (12 gliomas, 11 meningiomas, three metastases, two gliotic scars, one multiple sclerosis) underwent IVIM-MRI (32 b-values, 0 to 2000 s/mm² ) at 3T. f_IVIM was determined by classic monoexponential, biexponential, and a novel nonnegative least squares (NNLS) fitting in 352 regions of interest (lesion-containing and normal-appearing tissue) and tested their correlation with DCE-MRI kinetic parameters and microvascular anatomy derived from 57 region of interest (ROI)-based biopsies and their capacities to differentiate histologically different lesions.

RESULTS

f_IVIM differed significantly between all three models and all tissue types (monoexponential confidence interval in percent [CI 3.4-3.8]; biexponential [CI 11.21-12.45]; NNLS [CI 2.06-2.60]; all P < 0.001). For all models an increase in f_IVIM was associated with a shift to larger vessels and higher vessel area / tissue area ratio (regression coefficient 0.07-0.52; P = 0.04-0.001). Correlation with kinetic parameters derived from DCE-MRI was usually not significant. Only biexponential fitting allowed differentiation of both gliosis from edema and high- from low-grade glioma (both P < 0.001).

CONCLUSION

The curve-fitting model has an important impact on f_IVIM and its capacity to differentiate tissues. f_IVIM may possibly be used to assess microvascular anatomy and is weakly correlated with DCE-MRI kinetic parameters.

LEVEL OF EVIDENCE

2 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2017;46:1187-1199.

Quantification of microcirculatory parameters by joint analysis of flow-compensated and non-flow-compensated intravoxel incoherent motion (IVIM) data

The aim of this study was to improve the accuracy and precision of perfusion fraction and blood velocity dispersion estimates in intravoxel incoherent motion (IVIM) imaging, using joint analysis of flow-compensated and non-flow-compensated motion-encoded MRI data. A double diffusion encoding sequence capable of switching between flow-compensated and non-flow-compensated encoding modes was implemented. In vivo brain data were collected in eight healthy volunteers and processed using the joint analysis. Simulations were used to compare the performance of the proposed analysis method with conventional IVIM analysis. With flow compensation, strong rephasing was observed for the in vivo data, approximately cancelling the IVIM effect. The joint analysis yielded physiologically reasonable perfusion fraction maps. Estimated perfusion fractions were 2.43 ± 0.81% in gray matter, 1.81 ± 0.90% in deep gray matter, and 1.64 ± 0.72% in white matter (mean ± SD, n = 8). Simulations showed improved accuracy and precision when using joint analysis of flow-compensated and non-flow-compensated data, compared with conventional IVIM analysis. Double diffusion encoding with flow compensation was feasible for in vivo imaging of the perfusion fraction in the brain. The strong rephasing implied that blood flowing through the cerebral microvascular system was closer to the ballistic limit than the diffusive limit.

Magnetic resonance imaging-estimated placental perfusion in fetal growth assessment

OBJECTIVE

To evaluate in-vivo placental perfusion fraction, estimated by magnetic resonance imaging (MRI), as a marker of placental function.

METHODS

A study population of 35 pregnant women, of whom 13 had pre-eclampsia (PE), were examined at 22-40 weeks' gestation. Within a 24-h period, each woman underwent an MRI diffusion-weighted sequence (from which we calculated the placental perfusion fraction), venous blood sampling and an ultrasound examination including estimation of fetal weight, amniotic fluid index and Doppler velocity measurements. The perfusion fractions in pregnancies with and without fetal growth restriction were compared and correlations between the perfusion fraction and ultrasound estimates and plasma markers were estimated using linear regression. The associations between the placental perfusion fraction and ultrasound estimates were modified by the presence of PE (P  <  0.05) and therefore we included an interaction term between PE and covariates in the models.

RESULTS

The median placental perfusion fractions in pregnancies with and without fetal growth restriction were 21% and 32%, respectively (P = 0.005). The correlations between placental perfusion fraction and ultrasound estimates and plasma markers were highly significant (P = 0.002 and P = 0.0001, respectively). The highest coefficient of determination (R(2)  = 0.56) for placental perfusion fraction was found for a model that included pulsatility index in the ductus venosus, plasma level of soluble fms-like tyrosine kinase-1, estimated fetal weight and presence of PE.

CONCLUSION

The placental perfusion fraction has the potential to contribute to the clinical assessment of cases with placental insufficiency.

Orientation dependence of microcirculation-induced diffusion signal in anisotropic tissues

PURPOSE

To seek a better understanding of the effect of organized capillary flow on the MR diffusion-weighted signal.

METHODS

A theoretical framework was proposed to describe the diffusion-weighted MR signal, which was then validated both numerically using a realistic model of capillary network and experimentally in an animal model of isolated perfused heart preparation with myocardial blood flow verified by means of direct arterial spin labeling measurements.

RESULTS

Microcirculation in organized tissues gave rise to an MR signal that could be described as a combination of the bi-exponential behavior of conventional intravoxel incoherent motion (IVIM) theory and diffusion tensor imaging (DTI) -like anisotropy of the vascular signal, with the flow-related pseudo diffusivity represented as the linear algebraic product between the encoding directional unit vector and an appropriate tensor entity. Very good agreement between theoretical predictions and both numerical and experimental observations were found.

CONCLUSION

These findings suggest that the DTI formalism of anisotropic spin motion can be incorporated into the classical IVIM theory to describe the MR signal arising from diffusion and microcirculation in organized tissues. Magn Reson Med 76:1252-1262, 2016. © 2015 Wiley Periodicals, Inc.

Correlative assessment of tumor microcirculation using contrast-enhanced perfusion MRI and intravoxel incoherent motion diffusion-weighted MRI: is there a link between them?

The purpose of this study was to correlate intravoxel incoherent motion (IVIM) imaging with classical perfusion-weighted MRI metrics in human gliomas. Parametric images for slow diffusion coefficient (D), fast diffusion coefficient (D*), and fractional perfusion-related volume (f) in patients with high-grade gliomas were generated. Maps of Fp (plasma flow), vp (vascular plasma volume), PS (permeability surface-area product), ve (extravascular, extracellular volume), E (extraction ratio), ke (influx ratio into the interstitium), and tc (vascular transit time) from dynamic contrast-enhanced (DCE) and dynamic susceptibility contrast-enhanced (DSC) MRI were also generated. A region-of-interest analysis on the contralateral healthy white matter and on the tumor areas was performed and the extracted parameter values were tested for any significant differences among tumor grades or any correlations. Only f could be significantly correlated to DSC-derived vp and tc in healthy brain tissue. Concerning the tumor regions, Fp was significantly positively correlated with D* and inversely correlated with f in DSC measurements. The D*, f, and f × D* values in the WHO grade III gliomas were non-significantly different from those in the grade IV gliomas. There was a trend to significant negative correlations between f and PS as well as between f × D* and ke in DCE experiments. Presumably due to different theoretical background, tracer properties and modeling of the tumor vasculature in the IVIM theory, there is no clearly evident link between D*, f and DSC- and DCE-derived metrics.