Time-dependent Imaging Research Articles

Comparison of water exchange measurements between filter-exchange imaging and diffusion time-dependent kurtosis imaging in the human brain.

Filter-exchange imaging (FEXI) and diffusion time (t)-dependent kurtosis imaging (DKI(t)) are two diffusion-based methods that have been proposed for in vivo measurements of water exchange rates. Few studies have directly compared these methods. We aimed to investigate whether FEXI and DKI(t) yield comparable water exchange measurements in the human brain in vivo. Eight healthy volunteers underwent multiple-direction FEXI and DKI(t) acquisitions on a 3T scanner. We performed region of interest (ROI) analysis to determine correlations between FEXI-derived apparent exchange rate (AXR) and DKI(t)-derived reciprocal of exchange time ( ). In both white matter (WM) and gray matter (GM), DKI(t) revealed substantial diffusion-time dependence of diffusivity and kurtosis. However, at t ≥ 100 ms, the diffusivity showed weak time dependence. In WM, this time dependence may be due to water exchange between myelin water and "free" water with different T1 values, although other factors, such as remaining restrictive effects from microstructural barriers, cannot be excluded. We found a significant correlation between DKI(t)-derived and FEXI-derived AXR in the axial direction within WM. No such correlation was present in GM, although both values showed similar ranges. These results suggest that FEXI and DKI(t) could be sensitive to the same water exchange process only when the diffusion time in DKI(t) is sufficiently long, and only in WM. In both GM and WM, the restrictive effect of microstructure is non-negligible, especially at short diffusion times (<100 ms).

Time-dependent diffusion magnetic resonance imaging for the analysis of parotid gland tumors.

Different parotid tumors differ in terms of treatment strategies due to their distinct biological behaviors. Time-dependent diffusion magnetic resonance imaging (td-dMRI) can characterize and quantify the cytological indexes, and then aid the differential diagnosis of various tumors. However, the value of td-dMRI in the analysis of parotid gland tumors remains unclear. To investigate the value of quantitative parameters derived from td-dMRI in the analysis of parotid gland tumors. In total, 39 patients with parotid gland tumors were prospectively enrolled, including 24 patients with polymorphic adenomas (PAs), eight with Warthin's tumors (WTs), and seven with malignant tumors (MTs). Td-dMRI was performed for preoperative evaluation. Intracellular volume fraction (Vin), mean cell size (d), extracellular diffusion coefficient (Dex), and cellularity were obtained based on the Imaging Microstructural Parameters Using Limited Spectrally Edited Diffusion model, and compared among the three groups. One-way ANOVA, Kruskal-Wallis test, and receiver operating characteristic (ROC) curve analysis were performed for further statistical analysis as appropriate. Significant differences were found in all td-dMRI-derived indexes among PAs, WTs, and MTs (all P < 0.05). Vin was the sole parameter with significant differences for all sub-group comparisons (PAs vs. WTs, P < 0.001; PAs vs. MTs, P = 0.031; WTs vs. MTs, P = 0.047). With Vin values of 0.267, 0.231, and 0.260 as threshold, respectively, optimal performance levels were obtained for differentiating PAs from WTs (area under the ROC curve [AUC]=0.932, sensitivity=0.917, and specificity=0.875), PAs from MTs (AUC=0.744, sensitivity=0.833, and specificity=0.714), and WTs from MTs (AUC=0.750, sensitivity=0.875, and specificity=0.714). Microstructural parameters derived from td-dMRI, especially Vin, might be promising imaging biomarkers for characterizing parotid gland tumors.

Time-dependent diffusion MRI and kinetic heterogeneity as potential imaging biomarkers for diagnosing suspicious breast lesions with 3.0-T breast MRI.

This study aimed to evaluate the diagnostic efficacy of time-dependent diffusion magnetic resonance imaging (td-dMRI) and dynamic contrast-enhanced MRI (DCE-MRI)-based kinetic heterogeneity in differentiating suspicious breast lesions (categorised as Breast Imaging Reporting and Data System 4 or 5). This prospective study included 51 females with suspicious breast lesions who underwent preoperative breast MRI, including DCE-MRI and td-dMRI. Six kinetic parameters, namely peak, persistent, plateau, washout component, predominant curve type, and heterogeneity, were extracted from the DCE series using MATLAB and SPM software. The td-dMRI data were analysed using the JOINT model to obtain five microstructural parameters and apparent diffusion coefficient at 50ms (ADC50ms). Chi-square or Fisher's exact test and the Mann-Whitney U test were used to compare these parameters between benign and malignant breast lesions. Univariate and multivariate logistic regression analyses with forward stepwise covariate selection were performed to identify significant clinical and radiologic variables. Differential diagnostic performance was evaluated using receiver operating characteristic curves and logistic regression analyses. For td-dMRI-derived parameters, the values of fin and cellularity were significantly higher in malignant breast lesions compared to benign lesions (P=0.001 and P<0.001, respectively), while ADC50ms was significantly lower in malignant lesions (P=0.001). In the kinetic heterogeneity analysis, the washout component was higher in malignant lesions compared to benign lesions (P=0.003). When combining significant td-dMRI and kinetic heterogeneity parameters, the area under the curve (AUC) value was 0.875, with an accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of 82.69%, 86.11%, 75.00%, 88.57%, and 70.59%, respectively. Notably, margin and kinetic pattern emerged as independent predictors of malignant breast lesions (P=0.019 and 0.006, respectively). Furthermore, incorporating these two clinical-radiologic characteristics further enhanced diagnostic accuracy, yielding an AUC of 0.969, with accuracy, sensitivity, specificity, PPV, and NPV improving to 90.38%, 86.11%, 100%, 100%, and 76.19%, respectively. Kinetic heterogeneity- and td-dMRI-derived parameters are potentially non-invasive biomarkers for distinguishing suspicious breast lesions.

TDKI-Net: A Joint q-t Space Learning Network for Diffusion-Time-Dependent Kurtosis Imaging.

Time-dependent diffusion magnetic resonance imaging (TDDMRI) is useful for the non-invasive characterization of tissue microstructure. These models require both densely sampled q-t space data for microstructural fitting, leading to very time-consuming acquisition protocols. To overcome this problem, we present a joint q-t space model-tDKI-Net to estimate diffusion-time dependent kurtosis and the transmembrane exchange, using downsampled q-t space data. The tDKI-Net is composed of several q-Encoders and a t-Encoder, designed based on the extragradient mechanism, each integrated with their respective mapping networks. In the tDKI-Net, two types of encoders along with their mapping networks are employed sequentially to generate kurtosis at individual diffusion times and to fit the transmembrane exchange time ( τm) using the time-dependent kurtosis according the Kärger's model. Meanwhile, we proposed a three-stage training strategy, including physics-informed self-supervised pretraining, DKI warm-up, and joint training, to match the network structure. Our results demonstrated that the proposed tDKI-Net could effectively accelerate tDKI scans, resulting in lower estimation error compared with other methods. Our proposed three-stage training strategy demonstrated superior results than those training from scratch, e.g., the normalized root mean square error (NRMSE) of τm decreased by up to 1.4%. We also investigated the training data size effects and found that although we used one-subject training, the network achieved lower NRMSEs for Kavg, K0 and τm (2.50%, 3.04%, 10.86%) than previous work that used three-subject training (3.8%, 9.5%, 12.1%). tDKI-Net can considerably reduce the scan time by 10.5- fold by joint downsampling the q-t space data without compromising the estimation accuracy.

Assessing tumor microstructure with time-dependent diffusion imaging: Considerations and feasibility on clinical MRI and MRI-Linac.

Quantitative imaging biomarkers (QIBs) can characterize tumor heterogeneity and provide information for biological guidance in radiotherapy (RT). Time-dependent diffusion MRI (TDD-MRI) derived parameters are promising QIBs, as they describe tissue microstructure with more specificity than traditional diffusion-weighted MRI (DW-MRI). Specifically, TDD-MRI can provide information about both restricted diffusion and diffusional exchange, which are the two time-dependent effects affecting diffusion in tissue, and relevant in tumors. However, exhaustive modeling of both effects can require long acquisitions and complex model fitting. Furthermore, several introduced TDD-MRI measurements can require high gradient strengths and/or complex gradient waveforms that are possibly not available in RT settings. In this study, we investigated the feasibility of a simple analysis framework for the detection of restricted diffusion and diffusional exchange effects in the TDD-MRI signal. To promote the clinical applicability, we use standard gradient waveforms on a conventional 1.5 T MRI system with moderate gradient strength (Gmax=45 mT/m), and on a hybrid 1.5 T MRI-Linac system with low gradient strength (Gmax=15 mT/m). Restricted diffusion and diffusional exchange were simulated in geometries mimicking tumor microstructure to investigate the DW-MRI signal behavior and to determine optimal experimental parameters. TDD-MRI was implemented using pulsed field gradient spin echo with the optimized parameters on a conventional MRI system and a MRI-Linac. Experiments in green asparagus and 10 patients with brain lesions were performed to evaluate the time-dependent diffusion (TDD) contrast in the source DW-images. Simulations demonstrated how the TDD contrast was able to differentiate only dominating diffusional exchange in smaller cells from dominating restricted diffusion in larger cells. The maximal TDD contrast in simulations with typical cancer cell sizes and in asparagus measurements exceeded 5% on the conventional MRI but remained below 5% on the MRI-Linac. In particular, the simulated TDD contrast in typical cancer cell sizes (r=5-10µm) remained below or around 2% with the MRI-Linac gradient strength. In patients measured with the conventional MRI, we found sub-regions reflecting either dominating restricted diffusion or dominating diffusional exchange in and around brain lesions compared to the noisy appearing white matter. On the conventional MRI system, the TDD contrast maps showed consistent tumor sub-regions indicating different dominating TDD effects, potentially providing information on the spatial tumor heterogeneity. On the MRI-Linac, the available TDD contrast measured in asparagus showed the same trends as with the conventional MRI but remained close to typical measurement noise levels when simulated in common cancer cell sizes. On conventional MRI systems with moderate gradient strengths, the TDD contrast could potentially be used as a tool to identify which time-dependent effects to include when choosing a biophysical model for more specific tumor characterization.

Time-dependent diffusion magnetic resonance imaging: measurement, modeling, and applications

Time-dependent diffusion magnetic resonance imaging: measurement, modeling, and applications

In vivo mapping of cellular resolution neuropathology in brain ischemia with diffusion MRI.

Noninvasive mapping of cellular pathology can provide critical diagnostic and prognostic information. Recent advances in diffusion magnetic resonance imaging enabled in vivo examination of tissue microstructures well beyond the imaging resolution. Here, we proposed to use diffusion time-dependent diffusion kurtosis imaging (tDKI) to simultaneously assess cellular morphology and transmembrane permeability in hypoxic-ischemic (HI) brain injury. Through numerical simulations and organoid imaging, we demonstrated the feasibility of capturing effective size and permeability changes using tDKI. In vivo MRI of HI-injured mouse brains detected a shift of the tDKI peak to longer diffusion times, suggesting swelling of the cellular processes. Furthermore, we observed a faster decrease of the tDKI tail, reflecting increased transmembrane permeability associated with up-regulated water exchange or necrosis. Such information, unavailable from a single diffusion time, can predict salvageable tissues. Preliminary applications of tDKI in patients with ischemic stroke suggested increased transmembrane permeability in stroke regions, illustrating tDKI's potential for detecting pathological changes in the clinics.

Chronic Hindlimb Ischemia Induces Alterations of Muscle Transcriptomes Based on Muscle Type

Introduction: Peripheral artery disease (PAD) is a progressive atherothrombotic disorder of the arteries supplying the lower limb and is the most prevalent cardiovascular disease, impacting over 230 million people worldwide. PAD is associated with lower extremity myopathy characterized by myofiber degeneration and fibrosis. Increased proportions of type I muscle fibers are associated with improved patient outcomes, but most studies, human and animal, only analyze the gastrocnemius (gastroc), which contains mixed amounts of type I and type II fibers. To elucidate the impacts of ischemia on muscles comprising mainly type I fibers, we evaluated the differential effect of hindlimb ischemia (HLI) on the soleus and gastroc, hypothesizing that chronic HLI would more severely impact the soleus. Methods: Chronic HLI was induced in Sprague-Dawley male rats with an endovascular iliofemoral artery occlusion approach. Time-dependent laser Doppler perfusion imaging assessed hindlimb perfusion before and after HLI up to 42 days. Myopathy was evaluated 28 days post-HLI by staining muscle cross-sections with Hematoxylin and Eosin (H&amp;E) and Masson trichrome. Quantification of muscle fibrosis, average fiber cross-sectional area, and presence of central nuclei were used to determine muscle pathology. RNAsequencing was used to determine the differences in transcriptomes of the gastroc and soleus in both sham and HLI conditions. Results: Histological analysis revealed that there were significantly increased levels of fibrosis after HLI, but only in the soleus (18.24±7.23 vs. 7.71±2.54 %, n = 8-16, p-value &lt;0.0001). The average fiber cross-sectional area was significantly reduced in the HLI soleus compared to the sham (1556.00±459.60 vs. 3072.00±831.50 μm, n = 8-16, p-value &lt;0.0001), but not between HLI and sham gastroc. Conversely, HLI increased the proportions of centralized nuclei in both muscles (soleus — 22.72±12.46 vs. 1.12±1.49 %, n = 8-16, p-value = 0.0002, gastroc — 12.75±10.17 vs. 0.00±0.00 %, n = 8-16, p-value = 0.0002), indicating prior muscle damage. The HLI soleus exhibited worse outcomes in all parameters compared to the HLI gastroc. These data were substantiated by RNAseq, which showed that the HLI soleus transcriptome contained more differentially expressed genes (DEGs, ~1000 altered genes) than its sham counterpart compared to HLI gastroc, which possessed &lt;100 DEGs (n = 5-6). Moreover, the HLI soleus transcriptome was highly fibrotic, pro-angiogenic, and promoted myoblast fusion, a combination that could explain the histological myopathy findings. Conclusions: Chronic HLI induces alterations of muscle ultrastructure and transcription. These effects occur predominantly in the soleus rather than the gastroc. The results of the present study implicate that the pathophysiology is different for distinct muscles and may result from varying fiber composition. This work can help identify the mechanisms responsible for the myopathy of PAD and may lead to the design of targeted interventions for the care of PAD patients. R01HL169205-01. This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

Hemodynamic property incorporated brain tumor segmentation by deep learning and density-based analysis of dynamic susceptibility contrast-enhanced magnetic resonance imaging (MRI).

Magnetic resonance imaging (MRI) is a primary non-invasive imaging modality for tumor segmentation, leveraging its exceptional soft tissue contrast and high resolution. Current segmentation methods typically focus on structural MRI, such as T1-weighted post-contrast-enhanced or fluid-attenuated inversion recovery (FLAIR) sequences. However, these methods overlook the blood perfusion and hemodynamic properties of tumors, readily derived from dynamic susceptibility contrast (DSC) enhanced MRI. This study introduces a novel hybrid method combining density-based analysis of hemodynamic properties in time-dependent perfusion imaging with deep learning spatial segmentation techniques to enhance tumor segmentation. First, a U-Net convolutional neural network (CNN) is employed on structural images to delineate a region of interest (ROI). Subsequently, Hierarchical Density-Based Scans (HDBScan) are employed within the ROI to augment segmentation by exploring intratumoral hemodynamic heterogeneity through the investigation of tumor time course profiles unveiled in DSC MRI. The approach was tested and evaluated using a cohort of 513 patients from the open-source University of Pennsylvania glioblastoma database (UPENN-GBM) dataset, achieving a 74.83% Intersection over Union (IoU) score when compared to structural-only segmentation. The algorithm also exhibited increased precision and localized predictions of heightened segmentation boundary complexity, resulting in a 146.92% increase in contour complexity (ICC) compared to the reference standard provided by the UPENN-GBM dataset. Importantly, segmenting tumors with the developed new approach uncovered a negative correlation of the tumor volume with the scores in the Karnofsky Performance Scale (KPS) clinically used for assessing the functional status of patients (-0.309), which is not observed with the prevailing segmentation standard. This work demonstrated that including hemodynamic properties of tissues from DSC MRI can improve existing structural or morphological feature-based tumor segmentation techniques with additional information on tumor biology and physiology. This approach can also be applied to other clinical indications that use perfusion MRI for diagnosis or treatment monitoring.

Cell viability imaging in tumor spheroids via DNA binding of a ruthenium(II) light-switch complex.

The famous ''light-switch'' ruthenium complex [Ru(bpy)2(dppz)](PF6)2 (1) has been long known for its DNA binding properties in vitro. However, the biological utility of this compound has been hampered by its poor cellular uptake in living cells. Here we report a bioimaging application of 1 as cell viability probe in both 2D cells monolayer and 3D multi-cellular tumor spheroids of various human cancer cell lines (U87, HepG2, A549). When compared to propidium iodide, a routinely used cell viability probe, 1 was found to enhance the staining of dead cells in particular in tumor spheroids. 1 has high photostability, longer Stokes shift, and displays lower cytotoxicity compared to propidium iodide, which is a known carcinogenic. Finally, 1 was also found to displace the classical DNA binding dye Hoechst in dead cells, which makes it a promising dye for time-dependent imaging of dead cells in cell cultures, including multi-cellular tumor spheroids.

Differentiating primary central nervous system lymphoma from glioblastoma by time-dependent diffusion using oscillating gradient

BackgroundThis study aimed to elucidate the impact of effective diffusion time setting on apparent diffusion coefficient (ADC)-based differentiation between primary central nervous system lymphomas (PCNSLs) and glioblastomas (GBMs) and to investigate the usage of time-dependent diffusion magnetic resonance imaging (MRI) parameters.MethodsA retrospective study was conducted involving 21 patients with PCNSLs and 66 patients with GBMs using diffusion weighted imaging (DWI) sequences with oscillating gradient spin-echo (Δeff = 7.1 ms) and conventional pulsed gradient (Δeff = 44.5 ms). In addition to ADC maps at the two diffusion times (ADC7.1 ms and ADC44.5 ms), we generated maps of the ADC changes (cADC) and the relative ADC changes (rcADC) between the two diffusion times. Regions of interest were placed on enhancing regions and non-enhancing peritumoral regions. The mean and the fifth and 95th percentile values of each parameter were compared between PCNSLs and GBMs. The area under the receiver operating characteristic curve (AUC) values were used to compare the discriminating performances among the indices.ResultsIn enhancing regions, the mean and fifth and 95th percentile values of ADC44.5 ms and ADC7.1 ms in PCNSLs were significantly lower than those in GBMs (p = 0.02 for 95th percentile of ADC44.5 ms, p = 0.04 for ADC7.1 ms, and p < 0.01 for others). Furthermore, the mean and fifth and 95th percentile values of cADC and rcADC were significantly higher in PCNSLs than in GBMs (each p < 0.01). The AUC of the best-performing index for ADC7.1 ms was significantly lower than that for ADC44.5 ms (p < 0.001). The mean rcADC showed the highest discriminating performance (AUC = 0.920) among all indices. In peritumoral regions, no significant difference in any of the three indices of ADC44.5 ms, ADC7.1 ms, cADC, and rcADC was observed between PCNSLs and GBMs.ConclusionsEffective diffusion time setting can have a crucial impact on the performance of ADC in differentiating between PCNSLs and GBMs. The time-dependent diffusion MRI parameters may be useful in the differentiation of these lesions.

Monitoring the young planet host V1298 Tau with SPIRou: planetary system and evolving large-scale magnetic field

ABSTRACT We report results of a spectropolarimetric monitoring of the young Sun-like star V1298 Tau based on data collected with the near-infrared spectropolarimeter SPIRou at the Canada–France–Hawaii Telescope between late 2019 and early 2023. Using Zeeman–Doppler Imaging and the Time-dependent Imaging of Magnetic Stars methods on circularly polarized spectra, we reconstructed the large-scale magnetic topology of the star (and its temporal evolution), found to be mainly poloidal and axisymmetric with an average strength varying from 90 to 170 G over the ∼3.5 yr of monitoring. The magnetic field features a dipole whose strength evolves from 85 to 245 G, and whose inclination with respect to the stellar rotation axis remains stable until 2023 where we observe a sudden change, suggesting that the field may undergo a polarity reversal, potentially similar to those periodically experienced by the Sun. Our data suggest that the differential rotation shearing the surface of V1298 Tau is about 1.5 times stronger than that of the Sun. When coupling our data with previous photometric results from K2 and TESS and assuming circular orbits for all four planets, we report a 3.9σ detection of the radial velocity signature of the outermost planet (e), associated with a most probable mass, density, and orbital period of $M_\mathrm{e}=0.95^{+0.33}_{-0.24}$ MꝜ, $\rho _\mathrm{e}=1.66^{+0.61}_{-0.48}$$\rm g\, cm^{-3}$, and Pe = 53.0039 ± 0.0001 d, respectively. For the three inner planets, we only derive 99 per cent confidence upper limits on their mass of 0.44, 0.22, and 0.25 MꝜ, for b, c, and d, respectively.

A novel fluorescent probe for the detection of peroxynitrite and its application in mice epileptic brain model

Herein, a fluorescent probe, GYP, was developed for the detection of ONOO− in KA-induced epileptic brains. In solution, as a ratiometric probe, GYP indicated practical properties including steadiness under wide pH range (3.0–12.0), rapid response (within 20 s), stability over 48 h, high sensitivity (LOD = 0.27 μM) and high selectivity. In living PC12 cells, in spite of the low toxicity, GYP could achieve the time-dependent and dose-dependent imaging of ONOO−, while the generation and elimination were checked by introduction of SIN-1 and NAC, respectively. Further, GYP could cross Blood-Brain Barrier (BBB) rapidly and steadily during the imaging in KA-induced mice epileptic brain model. Thus, this work raised a practical implement for the detection of ONOO− in brain region, which might be helpful for further understanding of the epilepsy mechanism in future.

Differentiating brain metastasis from glioblastoma by time-dependent diffusion MRI

BackgroundThis study was designed to investigate the use of time-dependent diffusion magnetic resonance imaging (MRI) parameters in distinguishing between glioblastomas and brain metastases.MethodsA retrospective study was conducted involving 65 patients with glioblastomas and 27 patients with metastases using a diffusion-weighted imaging sequence with oscillating gradient spin-echo (OGSE, 50 Hz) and a conventional pulsed gradient spin-echo (PGSE, 0 Hz) sequence. In addition to apparent diffusion coefficient (ADC) maps from two sequences (ADC50Hz and ADC0Hz), we generated maps of the ADC change (cADC): ADC50Hz − ADC0Hz and the relative ADC change (rcADC): (ADC50Hz − ADC0Hz)/ ADC0Hz × 100 (%).ResultsThe mean and the fifth and 95th percentile values of each parameter in enhancing and peritumoral regions were compared between glioblastomas and metastases. The area under the receiver operating characteristic curve (AUC) values of the best discriminating indices were compared. In enhancing regions, none of the indices of ADC0Hz and ADC50Hz showed significant differences between metastases and glioblastomas. The mean cADC and rcADC values of metastases were significantly higher than those of glioblastomas (0.24 ± 0.12 × 10−3mm2/s vs. 0.14 ± 0.03 × 10−3mm2/s and 23.3 ± 9.4% vs. 14.0 ± 4.7%; all p < 0.01). In peritumoral regions, no significant difference in all ADC indices was observed between metastases and glioblastomas. The AUC values for the mean cADC (0.877) and rcADC (0.819) values in enhancing regions were significantly higher than those for ADC0Hz5th (0.595; all p < 0.001).ConclusionsThe time-dependent diffusion MRI parameters may be useful for differentiating brain metastases from glioblastomas.

Time-dependent diffusion tensor imaging and diffusion modeling of age-related differences in the medial gastrocnemius and feasibility study of correlations to histopathology.

Implement STEAM-DTI to model time-dependent diffusion eigenvalues using the random permeable barrier model (RPBM) to study age-related differences in the medial gastrocnemius (MG) muscle. Validate diffusion model-extracted fiber diameter for histological assessment. Diffusion imaging at different diffusion times (Δ) was performed on seven young and six senior participants. Time-dependent diffusion eigenvalues (λ2 (t), λ3 (t), and D⊥ (t); average of λ2 (t) and λ3 (t)) were fit to the RPBM to extract tissue microstructure parameters. Biopsy of the MG tissue for histological assessment was performed on a subset of participants (four young, six senior). λ3 (t) was significantly higher in the senior cohort for the range of diffusion times. RPBM fits to λ2 (t) yielded fiber diameters in agreement to those from histology for both cohorts. The senior cohort had lower values of volume fraction of membranes, ζ, in fits to λ2 (t), λ3 (t), and D⊥ (t) (significant for fit to λ3 (t)). Fits of fiber diameter from RPBM to that from histology had the highest correlation for the fit to λ2 (t). The age-related patterns in λ2 (t) and λ3 (t) could tentatively be explained from RPBM fits; these patterns may potentially arise from a decrease in fiber asymmetry and an increase in permeability with age.

From cell membrane to mitochondria: Time-dependent AIE photosensitizer for fluorescence imaging and photodynamic anticancer therapy

Aggregation-induced emission photosensitizers (AIE-PSs) targeting different subcellular organelles with time-dependent manner are highly promising for clinical applications but rarely reported. Herein, we designed and synthesized the near-infrared (NIR) emission AIE-PS (CTQ-S) with broad absorption and excellent type I reactive oxygen species (ROS) generation efficiency that was superior to the widely used PS (Rose Bengal and Chlorine 6). With short-term incubation, CTQ-S anchored on the cell membrane (Rr: 0.843, Rr is for Pearson correlation coefficient) and gradually entered the mitochondria (Rr: 0.937) of cancer cells, showing excellent time-dependent fluorescence fluorescent imaging effect. Furthermore, CTQ-S realized the selective photodynamic therapy (PDT) effect in a time-dependent manner under white light irradiation. This work provided a new way for cancer cells fluorescence imaging and PDT.

In Vivo Microstructure Imaging in Oropharyngeal Squamous Cell Carcinoma Using the Random Walk With Barriers Model.

Apparent diffusion coefficient is not specifically sensitive to tumor microstructure and therapy-induced cellular changes. To investigate time-dependent diffusion imaging with the short-time-limit random walk with barriers model (STL-RWBM) for quantifying microstructure parameters and early cancer cellular response to therapy. Prospective. Twenty-seven patients (median age of 58 years and 7.4% of females) with p16+/p16- oropharyngeal/oral cavity squamous cell carcinomas (OPSCC/OCSCC) underwent MRI scans before therapy, of which 16 patients had second scans at 2 weeks of the 7-weeks chemoradiation therapy (CRT). 3-T, diffusion sequence with oscillating gradient spine echo (OGSE) and pulse gradient spin echo (PGSE). Diffusion weighted images were acquired using OGSE and PGSE. Effective diffusion times were derived for the STL-RWBM to estimate free diffusion coefficient D0 , volume-to-surface area ratio of cellular membranes V/S, and cell membrane permeability κ. Mean values of these parameters were calculated in tumor volumes. Tumor microstructure parameters were compared with clinical stages of p16+ I-II OPSCC, p16+ III OPSCC, and p16- IV OCSCC by Spearman's rank correlation and with digital pathological analysis of a resected tissue sample. Tumor microstructure parameter responses during CRT in the 16 patients were assessed by paired t-tests. A P-value of <0.05 was considered statistically significant. The derived effective diffusion times affected estimated values of V/S and κ by 40%. The tumor V/S values were significantly correlated with clinical stages (r = 0.47) as an increase from low to high clinical stages. The in vivo estimated cell size agreed with one from pathological analysis of a tissue sample. Early tumor cellular responses showed a significant increase in D0 (14%, P = 0.03) and non-significant increases in κ (56%, P = 0.6) and V/S (10%, P = 0.1). Effective diffusion time estimation might impact microstructure parameter estimation. The tumor V/S was correlated with OPSCC/OCSCC clinical stages. 1 TECHNICAL EFFICACY STAGE: 1.

Expanding Sgr A* dynamical imaging capabilities with an African extension to the Event Horizon Telescope

Context. The Event Horizon Telescope (EHT) has recently published the first images of the supermassive black hole at the center of our Galaxy, Sagittarius A* (Sgr A*). Imaging Sgr A* is plagued by two major challenges: variability on short (approximately minutes) timescales and interstellar scattering along our line of sight. While the scattering is well studied, the source variability continues to push the limits of current imaging algorithms. In particular, movie reconstructions are hindered by the sparse and time-variable coverage of the array. Aims. In this paper, we study the impact of the planned Africa Millimetre Telescope (AMT, in Namibia) and Canary Islands telescope (CNI) additions to the time-dependent coverage and imaging fidelity of the EHT array. This African array addition to the EHT further increases the eastwest (u, v) coverage and provides a wider time window to perform high-fidelity movie reconstructions of Sgr A*. Methods. We generated synthetic observations of Sgr A*’s accretion flow and used dynamical imaging techniques to create movie reconstructions of the source. To test the fidelity of our results, we used one general-relativistic magneto-hydrodynamic model of the accretion flow and jet to represent the quiescent state and one semi-analytic model of an orbiting hotspot to represent the flaring state. Results. We found that the addition of the AMT alone offers a significant increase in the (u, v) coverage, leading to robust averaged images during the first hours of the observating track. Moreover, we show that the combination of two telescopes on the African continent, in Namibia and in the Canary Islands, produces a very sensitive array to reconstruct the variability of Sgr A* on horizon scales. Conclusions. We conclude that the African expansion to the EHT increases the fidelity of high-resolution movie reconstructions of Sgr A* to study gas dynamics near the event horizon.

Skin Capacitive Image Stitching and Occlusion Measurements

The aim of this study is to develop new analysis techniques for skin capacitive image stitching and occlusion measurements. Through image stitching, small skin capacitive images can be stitched into large skin capacitive images and, therefore, provide more skin image information. Through occlusion, e.g., keeping the measurement device on skin for a period of time, the skin health status can be studied through time-dependent response curves. Results show that time-dependent skin capacitive imaging curves can tell us the information about transdermal water loss (TEWL) as well as skin surface profiles. By using the structural similarity index measure (SSIM), the TEWL map can be constructed, which shows the water loss map on the skin surface. We first present the theoretical background and then the experimental results.

Targeting the nervous system of the parasitic worm, Haemonchus contortus with quercetin

Prevalence of infection, limited choice of drugs, and emerging resistance against contemporary medications lead to a pressing need to develop new anthelmintic drugs and drug targets. However, little understanding of worms' physiology has substantially delayed the process. Here, we are reporting the tissue morphology of Haemonchus contortus, intestinal parasitic helminths found in small ruminants, and targeting its nervous system with quercetin, a naturally occurring flavonoid. Quercetin showed anthelmintic activity against all of the developmental stages of H. contortus. Further, histological analysis demonstrated damage to various body parts, including isthmus, brut, pseudocoele, and other organs. Mechanistic studies revealed the generation of oxidative stress and alterations in the activities of the stress response enzymes, such as catalase, superoxide dismutase, and glutathione peroxidase. Moreover, the time-dependent imaging of reactive oxygen species (ROS) generated due to quercetin treatment disclosed neuropils as the primary targets of quercetin in adult worms, which eventually lead to the paralysis and death of the worms. Thus, this work demonstrates that the nervous system of the parasitic helminth, H. contortus, is a novel target of the drug quercetin.