Time-signal Curve Research Articles

Glymphatic transport is reduced in rats with spontaneous pituitary tumor.

Pituitary tumor in patients induces adverse alterations in the brain, accompanied by cognitive deficits. Dysfunction of glymphatic waste clearance results in accumulation of neurotoxic products within the brain, leading to cognitive impairment. However, the status of glymphatic function in the brain with pituitary tumor is unknown. Using magnetic resonance imaging (MRI) and an advanced mathematical modeling, we investigated the changes of glymphatic transport in the rats carrying spontaneous pituitary tumor. Rats (22-24 months, female, Wistar) with and without pituitary tumor (n = 7/per group) underwent the identical experimental protocol. MRI measurements, including T2-weighted imaging and dynamic 3D T1-weighted imaging with intracisternal administration of contrast agent, were performed on each animal. The contrast-induced enhancement in the circle of Willis and in the glymphatic influx nodes were observed on the dynamic images and verified with time-signal-curves (TSCs). Model-derived parameters of infusion rate and clearance rate that characterize the kinetics of glymphatic tracer transport were evaluated in multiple representative brain regions. Our imaging data demonstrated a higher incidence of partially enhanced circle of Willis (86 vs. 14%; p < 0.033) and a lower incidence of enhancement in glymphatic influx nodes of pituitary (71 vs. 100%) and pineal (57 vs. 86%) recesses in the rats with pituitary tumor than in the rats with normal appearance of pituitary gland, indicating an intensification of impaired peri-vascular pathway and impeded glymphatic transport due to the presence of pituitary tumor. Consistently, our kinetic modeling and regional cerebral tissue quantification revealed significantly lower infusion and clearance rates in all examined regions in rats with spontaneous pituitary tumor than in non-tumor rats, representing a suppressed glymphatic transport in the brain with pituitary tumor. Our study demonstrates the compromised glymphatic transport in the rat brain with spontaneous pituitary tumor. The reduced efficiency in cerebral waste clearance increases the risk for neurodegeneration in the brain that may underlie the cognitive impairment commonly seen in patients with pituitary tumors.

Disentangling the impact of cerebrospinal fluid formation and neuronal activity on solute clearance from the brain

BackgroundDespite recent attention, pathways and mechanisms of fluid transposition in the brain are still a matter of intense discussion and driving forces underlying waste clearance in the brain remain elusive. Consensus exists that net solute transport is a prerequisite for efficient clearance. The individual impact of neuronal activity and cerebrospinal fluid (CSF) formation, which both vary with brain state and anesthesia, remain unclear.MethodsTo separate conditions with high and low neuronal activity and high and low CSF formation, different anesthetic regimens in naive rat were established, using Isoflurane (ISO), Medetomidine (MED), acetazolamide or combinations thereof. With dynamic contrast-enhanced MRI, after application of low molecular weight contrast agent (CA) Gadobutrol to cisterna magna, tracer distribution was monitored as surrogate for solute clearance. Simultaneous fiber-based Ca2+-recordings informed about the state of neuronal activity under different anesthetic regimen. T2-weighted MRI and diffusion-weighted MRI (DWI) provided size of subarachnoidal space and aqueductal flow as surrogates for CSF formation. Finally, a pathway and mechanism-independent two-compartment model was introduced to provide a measure of efficiency for solute clearance from the brain.ResultsAnatomical imaging, DWI and Ca2+-recordings confirmed that conditions with distinct levels of neuronal activity and CSF formation were achieved. A sleep-resembling condition, with reduced neuronal activity and enhanced CSF formation was achieved using ISO+MED and an awake-like condition with high neuronal activity using MED alone. CA distribution in the brain correlated with the rate of CSF formation. The cortical brain state had major influence on tracer diffusion. Under conditions with low neuronal activity, higher diffusivity suggested enlargement of extracellular space, facilitating a deeper permeation of solutes into brain parenchyma. Under conditions with high neuronal activity, diffusion of solutes into parenchyma was hindered and clearance along paravascular pathways facilitated. Exclusively based on the measured time signal curves, the two-compartment model provided net exchange ratios, which were significantly larger for the sleep-resembling condition than for the awake-like condition.ConclusionsEfficiency of solute clearance in brain changes with alterations in both state of neuronal activity and CSF formation. Our clearance pathway and mechanism agnostic kinetic model informs about net solute transport, solely based on the measured time signal curves. This rather simplifying approach largely accords with preclinical and clinical findings.

Aging-Related Alterations of Glymphatic Transport in Rat: In vivo Magnetic Resonance Imaging and Kinetic Study.

ObjectiveImpaired glymphatic waste clearance function during brain aging leads to the accumulation of metabolic waste and neurotoxic proteins (e.g., amyloid-β, tau) which contribute to neurological disorders. However, how the age-related glymphatic dysfunction exerts its effects on different cerebral regions and affects brain waste clearance remain unclear.MethodsWe investigated alterations of glymphatic transport in the aged rat brain using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and advanced kinetic modeling. Healthy young (3–4 months) and aged (18–20 months) male rats (n = 12/group) underwent the identical MRI protocol, including T2-weighted imaging and 3D T1-weighted imaging with intracisternal administration of contrast agent (Gd-DTPA). Model-derived parameters of infusion rate and clearance rate, characterizing the kinetics of cerebrospinal fluid (CSF) tracer transport via the glymphatic system, were evaluated in multiple representative brain regions. Changes in the CSF-filled cerebral ventricles were measured using contrast-induced time signal curves (TSCs) in conjunction with structural imaging.ResultsCompared to the young brain, an overall impairment of glymphatic transport function was detected in the aged brain, evidenced by the decrease in both infusion and clearance rates throughout the brain. Enlarged ventricles in parallel with reduced efficiency in CSF transport through the ventricular regions were present in the aged brain. While the age-related glymphatic dysfunction was widespread, our kinetic quantification demonstrated that its impact differed considerably among cerebral regions with the most severe effect found in olfactory bulb, indicating the heterogeneous and regional preferential alterations of glymphatic function.ConclusionThe robust suppression of glymphatic activity in the olfactory bulb, which serves as one of major efflux routes for brain waste clearance, may underlie, in part, age-related neurodegenerative diseases associated with neurotoxic substance accumulation. Our data provide new insight into the cerebral regional vulnerability to brain functional change with aging.

Quantitative Three-Dimensional Assessment of the Pharmacokinetic Parameters of Intra- and Peri-tumoural Tissues on Breast Dynamic Contrast-Enhanced Magnetic Resonance Imaging

We aimed to assess the feasibility of three-dimensional (3D) segmentation and to investigate whether semi-quantitative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) parameters are associated with traditional prognostic factors for breast cancer. In addition, we evaluated whether both intra-tumoural and peri-tumoural DCE parameters can differentiate the breast cancers that are more aggressive from those that are less aggressive. Consecutive patients with newly diagnosed invasive breast cancer and structural breast MRI (3.0 T) were included after informed consent. Fifty-six patients (mean age, 57 years) with mass lesions of > 7 mm in diameter were included. A semi-automatic image post-processing algorithm was developed to measure 3D pharmacokinetic information from the DCE-MRI images. The kinetic parameters were extracted from time-signal curves, and the absolute tissue contrast agent concentrations were calculated with a reference tissue model. Markedly, higher intra-tumoural and peri-tumoural tissue concentrations of contrast agent were found in high-grade tumours (n = 44) compared to low-grade tumours (n = 12) at every time point (P = 0.006–0.040), providing positive predictive values of 90.6–92.6% in the classification of high-grade tumours. The intra-tumoural and peri-tumoural signal enhancement ratios correlated with tumour grade, size, and Ki67 activity. The intra-observer reproducibility was excellent. We developed a model to measure the 3D intensity data of breast cancers. Low- and high-grade tumours differed in their intra-tumoural and peri-tumoural enhancement characteristics. We anticipate that pharmacokinetic parameters will be increasingly used as imaging biomarkers to model and predict tumour behavior, prognoses, and responses to treatment.

Dynamic contrast-enhanced magnetic resonance imaging of the lung reveals important pathobiology in idiopathic pulmonary fibrosis.

IntroductionEvidence suggests that abnormalities occur in the lung microvasculature in idiopathic pulmonary fibrosis (IPF). We hypothesised that dynamic contrast-enhanced (DCE)-magnetic resonance imaging (MRI) could detect alterations in permeability, perfusion and extracellular extravascular volume in IPF, thus providing in vivo regional functional information not otherwise available.MethodsHealthy controls and IPF subjects underwent DCE-MRI of the thorax using a dynamic volumetric radial sampling sequence and administration of gadoterate meglumine at a dose of 0.1 mmol·kg−1 at 2 mL·s−1. Model-free analysis of signal intensity versus time curves in regions of interest from a lower, middle and upper axial plane, a posterior coronal plane and the whole lung yielded parameters reflective of perfusion and permeability (peak enhancement and rate of contrast arrival (kwashin)) and the extracellular extravascular space (rate of contrast clearance (kwashout)). These imaging parameters were compared between IPF and healthy control subjects, and between fast/slow IPF progressors.ResultsIPF subjects (n=16, 56% male, age (range) 67.5 (60–79) years) had significantly reduced peak enhancement and slower kwashin in all measured lung regions compared to the healthy volunteers (n=17, 65% male, age (range) 58 (51–63) years) on unadjusted analyses consistent with microvascular alterations. kwashout, as a measure of the extravascular extracellular space, was significantly slower in the lower lung and posterior coronal regions in the IPF subjects consistent with an increased extravascular extracellular space. All estimates were attenuated after adjusting for age. Similar trends were observed, but only the associations with kwashin in certain lung regions remained statistically significant. Among IPF subjects, kwashout rates nearly perfectly discriminated between those with rapidly progressive disease versus those with stable/slowly progressive disease.ConclusionsDCE-MRI detects changes in the microvasculature and extravascular extracellular space in IPF, thus providing in vivo regional functional information.

A dynamic susceptibility contrast MRI digital reference object for testing software with leakage correction: Effect of background simulation.

Dynamic susceptibility contrast (DSC)-MRI is a perfusion imaging technique from which useful quantitative imaging biomarkers can be derived. Relative cerebral blood volume (rCBV) is such a biomarker commonly used for evaluating brain tumors. To account for the extravasation of contrast agents in tumors, post-processing leakage correction is often applied to improve rCBV accuracy. Digital reference objects (DRO) are ideal for testing the post-processing software, because the biophysical model used to generate the DRO can be matched to the one that the software uses. This study aims to develop DROs to validate the leakage correction of software using Weisskoff model and to examine the effect of background signal time curves that are required by the model. Three DROs were generated using the Weisskoff model, each composed of nine foreground lesion objects with combinations of different levels of rCBV and contrast leakage parameter (K2). Three types of background were implemented for these DROs: (1) a multi-compartment brain-like background, (2) a sphere background with a constant signal time curve, and (3) a sphere background with signal time curve identical to that of the brain-like DRO's white matter (WM). The DROs were then analyzed with an FDA-cleared software with and without leakage correction. Leakage correction was tested with and without brain segmentation. Accuracy of leakage correction was able to be verified using the brain-like phantom and the sphere phantom with WM background. The sphere with constant background did not perform well with leakage correction with or without brain segmentation. The DROs were able to verify that for the particular software tested, leakage correction with brain segmentation achieved the lowest error. DSC-MRI DROs with biophysical model matched to that of the post-processing software can be well used for the software's validation, provided that the background signals are also properly simulated for generating the reference time curve required by the model. Care needs to be taken to consider the interaction of the design of the DRO with the software's implementation of brain segmentation to extract the reference time curve.

MRI Image Segmentation Model with Support Vector Machine Algorithm in Diagnosis of Solitary Pulmonary Nodule.

This study focused on the application value of MRI images processed by a Support Vector Machine (SVM) algorithm-based model in diagnosis of benign and malignant solitary pulmonary nodule (SPN). The SVM algorithm was constrained by a self-paced regularization item and gradient value to establish the MRI image segmentation model (SVM-L) for lung. Its performance was compared factoring into the Dice index (DI), sensitivity (SE), specificity (SP), and Mean Square Error (MSE). 28 SPN patients who underwent the parallel MRI examination were selected as research subjects and were divided into the benign group (11 patients) and malignant group (17 patients) according to different plans for diagnosis and treatment. The apparent diffusion coefficient (ADC) at different b values was analyzed, and the steepest slope (SS) and washout ratio (WR) values in the two groups were calculated. The result showed that the MSE, DI, SE, SP values, and operation time of the SVM-L model were (0.41 ± 0.02), (0.84 ± 0.13), (0.89 ± 0.04), (0.993 ± 0.004), and (30.69 ± 2.60)s, respectively, apparently superior to those of the other algorithms, but there were no statistic differences (P > 0.05) in the WR value between the two groups of patients. The SS values of the time-signal curve in the benign and malignant groups were (2.52 ± 0.69) %/s and (3.34 ± 00.41) %/s, respectively. Obviously, the SS value of the benign group was significantly lower than that of the malignant group (P < 0.01). The ADC value with different b values in the benign group was significantly lower than that of the malignant group (P < 0.01). It suggested that the SVM-L model significantly improved the quality of lung MRI images and increased the accuracy to differentiate benign and malignant SPN, providing reference for the diagnosis and treatment of SPN patients.

Dynamic contrast-enhanced magnetic resonance imaging for differentiating head and neck paraganglioma and schwannoma.

Morphological assessment with conventional magnetic resonance imaging (MRI) sequences has limited specificity to distinguish between paragangliomas and schwannomas. Assessing the differences in microvascular properties through pharmacokinetic parameters of dynamic contrast-enhanced (DCE)-MRI can provide additional information to aid in this differentiation. A prospective study on MR characterization of neck masses was performed between January 2017 and March 2019 in our department, out of which 40 patients with head and neck paragangliomas (HNPGLs) (33 lesions) and schwannomas (15 lesions) were included in this analysis. MR perfusion using dynamic axial T1WI fat suppressed fast spoiled gradient recalled sequence with parallel imaging was performed in all the patients, in addition to single-shot turbo spin-echo axial diffusion weighted imaging (DWI) and routine MRI. ROI-based method was used to obtain signal-time curves, permeability measurements, and mean apparent diffusion coefficient (ADC) to differentiate paragangliomas from schwannomas. Statistical analysis was done to assess the significance and establish a cutoff to distinguish between the two entities. The available images of DOTANOC PET/CT (34 lesions) were analyzed retrospectively. Correlations between the perfusion, diffusion, and molecular PET/CT parameters were done. Paragangliomas had a higher wash-in rate, wash-out rate, Ktrans, Kep , and Vp (p < 0.001); while schwannomas had a higher relative enhancement (p < 0.012), time to peak, time of onset, brevity of enhancement, and Ve (p < 0.001). Among the perfusion parameters, Kep (area under curve (AUC) 0.994) and Vp (AUC 0.992) were found to have the highest diagnostic value. In diffusion-weighted imaging, paragangliomas had a lower mean ADC compared to schwannomas (p < 0.001). The SUVmax and SUVmean were significantly associated with Ktrans , Kep , and Vp in paragangliomas. DCE-MRI in addition to DWI-MRI can accurately distinguish HNPGL from schwannoma and may replace the need for any additional imaging and preoperative biopsy in most cases.

Clinical value of high-resolution dynamic contrast-enhanced (DCE) MRI in diagnosis of cutaneous squamous cell carcinoma.

While uncomplicated cases of skin squamous cell carcinoma (cSCC) can be treated with surgery topical therapy alone, more objective and non-invasive examination methods are needed to guide clinicians to make more detailed biopsy and surgical plans for lesions with atypical or subcutaneous growth. High-resolution magnetic resonance imaging (HR-MRI) is a novel skin imaging method. Prospective collection of 19 patients with clinically suspected cSCC. All patients underwent high-resolution DCE-MRI using a 70-mm microscopy coil before operation. The imaging features and results of surgical pathology were recorded. Ktrans , Kep , Ve values, and the time-signal curve (TIC) types were determined using DCE images. 16 cases of cSCC, 3 cases of acanthoma. The subcutaneous invasion of all lesions was clearly displayed, of which 8 lesions invaded the subcutaneous fat layer, 5 invaded the muscle layer, 1 invaded the periosteum, 2 invaded the cap fascia, and the layer of all lesions invasion judged by HR-MR imaging was consistent with the postoperative pathology. The main manifestations of cSCC were ill-defined margin, obvious inhomogeneous enhancement, higher perfusion parameters value and type-III TIC, while acanthoma showed well-defined and type-I TIC. Some imaging findings (such as boundary, enhancement) and DCE perfusion parameters of the two groups overlap. High-resolution DCE-MRI can fully and directly display the subcutaneous invasion of cSCC, and more work needs to be done to prove its value. Next, we will expand the sample size, and further explore its value in the differential diagnosis and prognosis evaluation of cSCC from acanthoma or other skin tumors.

The value of tumor hemodynamics and morphological features in predicting the postoperative recurrence time of breast cancer based on dynamic contrast-enhanced MRI

Objective To investigate the value of tumor hemodynamics and morphological features from conventional dynamic contrast-enhanced MRI (DCE-MRI) scan before surgery in predicting postoperative recurrence time in breast cancer patients. Methods A retrospective analysis of 58 patients with breast cancer who had recurred after operation from November 2012 to December 2014 in Liaoning Cancer Hospital was performed. According to the recurrence time, the patients were divided into early recurrence group (≤2 years after surgery, 33 cases) and late recurrence group (>2 years after surgery, 25 cases). All patients underwent routine DCE-MRI scans before surgery, and hemodynamic features of the three-dimensional volume of the tumor and the morphological and textural features of the tumor in each phase were extracted by computer. The counts and measurement data of patients in early recurrence group and late recurrence group were compared by Fisher′s exact probability method and Mann-Whitney U test, and receiver operating characteristic (ROC) curves were drawn. The multivariate logistic regression was used to calculate the combined efficacy in predicting early recurrence and late recurrence. Kaplan-Meier method was used to analyze the survival prognosis, and Log-Rank test was used to compare the differences in survival curves between groups. Results There was no significant difference in background parenchymal enhancement, lesion margin, lesion internal enhancement characteristics, lesion morphology, time-signal intensity curve type and the degree of whole-breast vascularity increase between early recurrence and late recurrence groups (P>0.05).There were significant differences in the maximum concentration of contrast (Max Conc), the area under the time signal curve (AUC) and the maximum slope value of the time signal curve (Max Slope) (P<0.05). Comparative analysis of the radiomics parameters of 8 phases DCE-MRI found that the sphericity of morphological characteristic parameters in the phase 3 was statistically different between the early recurrence and late recurrence groups (P=0.03). Area under the ROC curve of AUC, Max Conc, Max Slope and parameter sphericity of phase 3 morphological characteristics for predicting early and late recurrence were 0.664, 0.659, 0.684 and 0.670, respectively. The area under the ROC combined with the above four parameters for prediction was 0.765, with a specificity of 63.6% and a sensitivity of 84.0%; the predictive efficacy was higher than that of univariate. Fifty-eight patients were followed up for 17 to 64 months with a median follow-up of 47 months. The disease-free survival and overall survival in the early recurrence group were significantly lower than those in the late recurrence group, and the difference was statistically significant (P<0.05). Conclusion It is of certain value to predict the postoperative recurrence time of breast cancer based on the tumor hemodynamic characteristics combined with morphological characteristics from preoperative non-invasive conventional DCE-MRI. Key words: Breast neoplasms; Magnetic resonance imaging; Texture analysis; Recurrence

A multiscale subvoxel perfusion model to estimate diffusive capillary wall conductivity in multiple sclerosis lesions from perfusion MRI data

We propose a new mathematical model to learn capillary leakage coefficients from dynamic susceptibility contrast MRI data. To this end, we derive an embedded mixed-dimension flow and transport model for brain tissue perfusion on a subvoxel scale. This model is used to obtain the contrast agent concentration distribution in a single MRI voxel during a perfusion MRI sequence. We further present a magnetic resonance signal model for the considered sequence including a model for local susceptibility effects. This allows modeling MR signal-time curves that can be compared with clinical MRI data. The proposed model can be used as a forward model in the inverse modeling problem of inferring model parameters such as the diffusive capillary wall conductivity. Acute multiple sclerosis lesions are associated with a breach in the integrity of the blood-brain barrier. Applying the model to perfusion MR data of a patient with acute multiple sclerosis lesions, we conclude that diffusive capillary wall conductivity is a good indicator for characterizing activity of lesions, even if other patient-specific model parameters are not well-known.

Diagnosis and Monitoring Value of Diffusion-Weighted Magnetic Resonance Imaging Using Neuroendocrine Analysis During Radiotherapy for Laryngeal Cancer

We used 1.5T magnetic resonance imaging (MRI) to investigate the role of semiquantitative parameters related to dynamic contrast-enhanced (DCE)-MRI and the apparent diffusion coefficient (ADC) of diffusion-weighted imaging (DWI) in predicting and monitoring the efficacy of concurrent radiotherapy and chemotherapy for laryngeal cancer. The data from 58 patients with newly diagnosed laryngeal cancer who had been treated at our hospital from August 2016 to March 2018 were collected. The 58 patients included 56 men and 2 women, with a median age of 57 years. The pathologic examination of the biopsy specimens revealed squamous cell carcinoma. The time signal curve (TIC) of the tumor and related semiquantitative parameters was measured before, during (radiation dose, 50 Gy), and at the end of treatment (monitoring value after treatment). The results revealed that the TIC types and DCE-MRI-related semiquantitative parameters can predict the efficacy of concurrent chemoradiotherapy for laryngeal and hypopharyngeal cancer. Of the semiquantitative parameters, the signal enhancement ratio at 56 seconds had the greatest predictive value. Patients with TIC type I before treatment had a better prognosis than those with TIC type III. The pre-ADC value was not enough to predict the efficacy. The ADC value, DCE-MRI-related semiquantitative parameters, and their change before treatment had a certain effect in monitoring the changes in water molecule diffusion movement and hemodynamic changes after tumor treatment. However, these were not enough to predict the efficacy.

The Relationship Between Serum Angiogenic Factor Levels and Disease Activity in Rheumatoid Arthritis.

Objectives This study aims to evaluate the relationship between serum angiogenic factor levels and disease activity in patients with rheumatoid arthritis (RA) using both clinical and dynamic wrist magnetic resonance imaging (MRI) data.Patients and methods Simultaneous serum angiogenesis markers [vascular endothelial growth factor (VEGF), angiopoietin-1 (ANG1), ANG2, and tyrosine-protein kinase receptor for angiopoietin (Tie-2)] were studied in 40 patients with RA (13 males, 27 females; mean age 51.1±10.8 years; range, 23 to 69 years) and 20 healthy controls (11 males, 9 females; mean age 47.3±12.8 years; range, 29 to 69 years) and dynamic contrast-enhanced wrist MRI was performed in 40 RA patients and seven controls. Rate of early in 55th second (REE) and Relative enhancement (REt) values were calculated from the signal time curve values obtained from the analysis of images. In clinical assessment, duration of morning stiffness, patient pain assessment [visual analog scale (VAS)], physician and patient global assessments (VAS) were recorded. The number of tender joints and swollen joints were determined. Disease activity score 28 and Ritchie scores were calculated. Health assessment questionnaire was used for functional evaluation. Anti-cyclic citrullinated peptide, rheumatoid factor, erythrocyte sedimentation rate and high sensitive C-reactive protein analyses were performed. Results Serum VEGF, REE and REt values were significantly higher in RA patients than healthy controls (p=0.002, p=0.00, p=0.00, respectively). There was no significant correlation between serum angiogenesis markers and clinical parameters or REE and REt (p>0.05). VEGF value correlated positively with disease duration (p=0.024).Conclusion Serum VEGF was higher in RA patients. While its level was associated with disease duration, no significant correlation was found with disease activity. As a diagnostic test, dynamic contrast-enhanced MRI was a valuable method for showing disease activity.

Delayed ventilation assessment using fast dynamic hyperpolarised Xenon-129 magnetic resonance imaging

ObjectivesTo investigate the use of a fast dynamic hyperpolarised 129Xe ventilation magnetic resonance imaging (DXeV-MRI) method for detecting and quantifying delayed ventilation in patients with chronic obstructive pulmonary disease (COPD).MethodsThree male participants (age range 31–43) with healthy lungs and 15 patients (M/F = 12:3, age range = 48–73) with COPD (stages II–IV) underwent spirometry tests, quantitative chest computed tomography (QCT), and DXeV-MRI at 1.5-Tesla. Regional delayed ventilation was captured by measuring the temporal signal change in each lung region of interest (ROI) in comparison to that in the trachea. In addition to its qualitative assessment through visual inspection by a clinical radiologist, delayed ventilation was quantitatively captured by calculating a covariance measurement of the lung ROI and trachea signals, and quantified using both the time delay, and the difference between the integrated areas covered by the signal-time curves of the two signals.ResultsRegional temporal ventilation, consistent with the expected physiological changes across a free breathing cycle, was demonstrated with DXeV-MRI in all patients. Delayed ventilation was observed in 13 of the 15 COPD patients and involved variable lung ROIs. This was in contrast to the control group, where no delayed ventilation was demonstrated (p = 0.0173).ConclusionsDXeV-MRI offers a non-invasive way of detecting and quantifying delayed ventilation in patients with COPD, and provides physiological information on regional pulmonary function during a full breathing cycle.Key Points• Dynamic xenon MRI allows for the non-invasive detection and measurement of delayed ventilation in COPD patients.• Dynamic xenon MRI during a free breathing cycle can provide unique information about pulmonary physiology and pulmonary disease pathophysiology.• With further validation, dynamic xenon MRI could offer a non-invasive way of measuring collateral ventilation which can then be used to guide lung volume reduction therapy (LVRT) for certain COPD patients.

Effects of motion on MRI signal decay from micron-scale particles.

Transverse decay rate (R2∗) mapping is an established method for measuring iron overload in various biological tissues. Recently, R2∗ mapping was used to measure the mean 3D concentration distribution of micron-size particles dispersed in turbulent flows. However, some discrepancy was observed between the measured R2∗ and the expected decay based on existing theory. The present paper examines three flow-related mechanisms that could be responsible for this discrepancy. Computational simulations were used to study the effects of relative particle-fluid motion and preferential concentration by turbulence, while the effect of enhanced proton dispersion due to turbulence was examined via the existing MRI relaxation theory. Each flow phenomenon was shown to produce a different effect on the signal-time curve, as well as the extracted R2∗. Comparison to experimental data in a square channel flow showed that relative motion between the particles and fluid was the most likely cause of the discrepancy in the previous experiments; however, all three effects may be present in both medical and non-medical flows, and their differing effects on the MRI signal may eventually allow for their identification from MRI data.

Correlation Analysis of Breast Cancer DWI Combined with DCE-MRI Imaging Features with Molecular Subtypes and Prognostic Factors.

This study aimed to deeply analyze the application of DWI and DCE-MRI imaging in breast cancer, the correlation between the imaging characteristics of DWI and DCE-MRI and the molecular subtypes and prognostic factors of breast cancer was studied. Firstly, DWI and DCE-MRI scans of all patients before interventional therapy were performed, and relevant information of the subjects was introduced in turn. Secondly, molecular subtypes were determined according to immunohistochemical results and gene amplification. Siemens 3.0T post-processing workstation was used for image post-processing. The time signal curve (TIC), early enhancement rate (EER) and ADC values were measured, morphological characteristics were recorded, and the correlation between each image feature and molecular subtypes, prognostic factors (tumor size, pathological grade, lymph node metastasis, ER, PR, HER2, Ki67) was analyzed. The results showed that parameters such as ADC value, EER, lobulation sign, burr sign, enhancement way and TIC type were correlated with prognostic factors and molecular subtypes. And Bayesian model discriminant analysis showed that the above imaging parameters couldn't well predict the expression of immunohistochemical factors and molecular subtypes. However, the above characteristics had a good effect on the prediction of pathological grade, with a false diagnosis rate of 9.69%.

Identifying perfusion deficits on CT perfusion images using temporal similarity perfusion (TSP) mapping.

Deconvolution-derived maps of CT perfusion (CTP) data may be confounded by transit delays. We propose temporal similarity perfusion (TSP) analysis to decrease CTP maps' dependence on transit times and investigate its sensitivity to detect perfusion deficits. CTP data of acute stroke patients obtained within 9h of symptom onset was analyzed using a delay-insensitive singular value decomposition method and with TSP. The TSP method applies an iterative process whereby a pixel's highest Pearson's R value is obtained through comparison of a pixel's time-shifted signal density time-series curve and the average whole brain signal density time-series curve. Our evaluation included a qualitative and quantitative rating of deconvolution maps (MTT, CBV, and TTP), of TSP maps, and of follow-up CT. Sixty-five patients (mean 68 (SD 13) years, 34 male) were included. A perfusion deficit was identified in 90%, 86%, 65%, and 84% of MTT, TTP, CBV, and TSP maps. The agreement of MTT, TTP, and TSP with CT follow-up was comparable but noticeably lower for CBV. CBV had the best relationship with final infarct volume (R2 = 0.77, p < 0.001), followed by TSP (R2 = 0.63, p < 0.001). Intra-rater agreement of an inexperienced reader was higher for TSP than for CBV/MTT maps (kappa's of 0.79-0.84 and 0.63-0.7). Inter-rater agreement for experienced readers was comparable across maps. TSP maps are easier to interpret for inexperienced readers. Perfusion deficits detected by TSP are smaller which may suggest less dependence on transit delays although more investigation is required. • Temporal similarity perfusion mapping assesses CTP data based on similarities in signal time-curves. • TSP maps are comparable in perfusion deficit detection to deconvolution maps. • TSP maps are easier to interpret for inexperienced readers.

Modeling glymphatic system of the brain using MRI

The glymphatic system is functional waste clearance path from the brain parenchyma through dynamic exchange of cerebrospinal fluid (CSF) with interstitial fluid (ISF). Impairment of glymphatic waste clearance is involved in the development of neurodegenerative conditions. Despite many recent studies investigating the glymphatic system, few studies have tried to use a mathematical model to describe this system, quantitatively. In this study, we aim to model the glymphatic system from the kinetics of Gd-DTPA tracer measured using MRI in order to: 1) map the glymphatic system path, 2) derive kinetic parameters of the glymphatic system, and 3) provide quantitative maps of the structure and function of this system. In the proposed model, the brain is clustered to similar regions with respect to the profile of contrast agent (CA) density measured by MRI. Then, each region is described as a two-compartment kinetic model ‘derived from’ or ‘clears to’ its neighbors with local input function. We thus fit our model to the local cerebral regions rather than to the averaged time signal curve (TSC) of the whole brain. The estimated parameters showed distinctive differences between diabetes mellitus (DM) and control rats. The results suggest that in a typical DM brain the CSF bulk speed in the para-vasculature network is low. In addition, the resulting maps indicate that there may be increased binding and decreased absorbing of large molecules in a diabetic compared with a non-diabetic brain. The important contribution of this work was to fit the model to the local regions rather than to the averaged time signal curve (TSC) of the whole brain. This enabled us to derive quantitative maps of the glymphatic system from MRI.

Evaluation of Uterine Tumor Angiogenesis with Quantitative Magnetic Resonance Imaging Perfusion Parameters

The development and metastasis of uterine tumors depend highly on tumor angiogenesis. Multiphase dynamic contrast-enhanced magnetic resonance imaging can quantitatively describe the hemodynamic changes of uterine tumors based on a variety of tracer kinetic models and time-signal curves and by simulating the distribution of contrast inside and outside the blood vessels. Functional parameters can accurately and noninvasively assess tumor angiogenesis. It provides a non-invasive functional evaluation method for the differential diagnosis,staging,response evaluation,and prognostic prediction of uterine tumors.

Research on measuring method of shot exit time for muzzle vibration analysis

The measurement of shot exit time is very important to measuring data analysis of muzzle vibration. Optoelectronic method, which is based on the optical-electrical conversion theory and timed with the muzzle flame, is a general method of measuring the shot exit time for the major caliber gun. However, it has not been identified that the shot exit time corresponds to which characteristic point in the voltage pulse time signal curve obtained by the optoelectronic method. In this paper, by combining the high speed digital photography and the optoelectronic method, both the triggering time signal of the high speed digital photography and the voltage signal output by the optoelectronic sensor were obtained simultaneously. Then by comparing the voltage time curve of the optoelectronic sensor with the photographs obtained by the digital photography, the relationship between the characteristic points in the signal curve and the shot exit time was identified. It has been shown that, the voltage pulse beginning time is the same with the muzzle flame beginning, which is later than the time when the projectile band leaves from muzzle.