Quantification Of Flow Research Articles

Genome-wide quantification of RNA flow across subcellular compartments reveals determinants of the mammalian transcript life cycle

Dissecting the regulatory mechanisms controlling mammalian transcripts from production to degradation requires quantitative measurements of mRNA flow across the cell. We developed subcellular TimeLapse-seq to measure the rates at which RNAs are released from chromatin, exported from the nucleus, loaded onto polysomes, and degraded within the nucleus and cytoplasm in human and mouse cells. These rates varied substantially, yet transcripts from genes with related functions or targeted by the same transcription factors and RNA-binding proteins flowed across subcellular compartments with similar kinetics. Verifying these associations uncovered a link between DDX3X and nuclear export. For hundreds of RNA metabolism genes, most transcripts with retained introns were degraded by the nuclear exosome, while the remaining molecules were exported with stable cytoplasmic lifespans. Transcripts residing on chromatin for longer had extended poly(A) tails, whereas the reverse was observed for cytoplasmic mRNAs. Finally, machine learning identified molecular features that predicted the diverse life cycles of mRNAs.

Mitral Annular Disease at Cardiac MRI: What to Know and Look For.

Accurate evaluation of the mitral valve (MV) apparatus is essential for understanding the mechanisms of MV disease across various clinical scenarios. The mitral annulus (MA) is a complex and crucial structure that supports MV function; however, conventional imaging techniques have limitations in fully capturing the entirety of the MA. Moreover, recognizing annular changes might aid in identifying patients who may benefit from advanced cardiac imaging and interventions. Multimodality cardiovascular imaging plays a major role in the diagnosis, prognosis, and management of MV disease. Transthoracic echocardiography is the first-line modality for evaluation of the MA, but it has limitations. Cardiac MRI (CMR) has emerged as a robust imaging modality for assessing annular changes, with distinct advantages over other imaging techniques, including accurate flow and volumetric quantification and assessment of variations in the measurements and shape of the MA during the cardiac cycle. Mitral annular disjunction (MAD) is defined as atrial displacement of the hinge point of the MV annulus away from the ventricular myocardium, a condition that is now more frequently diagnosed and studied owing to recent technical advances in cardiac imaging. However, several unresolved issues regarding MAD, such as the functional significance of pathologic disjunction and how this disjunction advances in the clinical course, require further investigation. The authors review the role of CMR in the assessment of MA disease, with a focus on MAD and its functional implications in MV prolapse and mitral regurgitation. ©RSNA, 2024 Supplemental material is available for this article. See the invited commentary by Stojanovska and Fujikura in this issue.

Quantification of myocardial blood flow using dynamic myocardial perfusion computed tomography

Quantification of myocardial blood flow using dynamic myocardial perfusion computed tomography

75As Nuclear Magnetic Resonance Spectroscopic Investigation of the Thioarsenate Speciation in Strongly Alkaline Sulfidic Leaching Solutions

Copper ores and concentrates thereof feature an increasingly notable content of impurities such as arsenic and other hazardous elements. As an alternative to the state-of-the-art partial roasting process, arsenic could be removed by the alkaline sulfide leaching of the copper concentrates. In order to optimize and understand the processes, knowledge of the speciation and oxidation states is essential. In addition to methods such as UV/Vis spectroscopy, chromatography and ICP/MS methods, 75As NMR spectroscopy may be useful for the differentiation and quantification of the various species. Although arsenate(V) has been characterized by 75As NMR some time ago, to our knowledge, there are no data on tetrathioarsenate(V) AsS43− and the mixed oxygen/sulfur substituted mono-, di- and trithioarsenates(V) AsOxS4−x3−, x = 3, 2, 1, respectively. Therefore, we investigated several model solutions and samples from Cu-As leaching with 75As NMR. The strongly alkaline conditions of the leaching solution proved to be very advantageous for that purpose. Both the tetrathioarsenate(V) and the mixed species AsOxS4−x3− (x = 1–3) could be characterized and provide valuable data for the quantification of the material flows in the leaching process.

Time-Resolved Dynamic Optical Coherence Tomography for Retinal Blood Flow Analysis.

Optical coherence tomography (OCT) representations in clinical practice are static and do not allow for a dynamic visualization and quantification of blood flow. This study aims to present a method to analyze retinal blood flow dynamics using time-resolved structural OCT. We developed novel imaging protocols to acquire video-rate time-resolved OCT B-scans (1024 × 496 pixels, 10 degrees field of view) at four different sensor integration times (integration time of 44.8 µs at a nominal A-scan rate of 20 kHz, 22.4 µs at 40 kHz, 11.2 µs at 85 kHz, and 7.24 µs at 125 kHz). The vessel centers were manually annotated for each B-scan and surrounding subvolumes were extracted. We used a velocity model based on signal-to-noise ratio (SNR) drops due to fringe washout to calculate blood flow velocity profiles in vessels within five optic disc diameters of the optic disc rim. Time-resolved dynamic structural OCT revealed pulsatile SNR changes in the analyzed vessels and allowed the calculation of potential blood flow velocities at all integration times. Fringe washout was stronger in acquisitions with longer integration times; however, the ratio of the average SNR to the peak SNR inside the vessel was similar across all integration times. We demonstrated the feasibility of estimating blood flow profiles based on fringe washout analysis, showing pulsatile dynamics in vessels close to the optic nerve head using structural OCT. Time-resolved dynamic OCT has the potential to uncover valuable blood flow information in clinical settings.

Quantification of two-phase flow in a microchannel heat exchanger header based on capacitance measurement

The two-phase distribution has always been one of the research focuses of microchannel heat exchangers, because the maldistribution could seriously affect the heat transfer performance. This paper developed a capacitive method to quantify the two-phase distribution of vapor-liquid flow in the aluminum header of a microchannel heat exchanger. A flexible capacitance sensor was used to quantify the two-phase distribution with R134a. The inlet mass fluxes vary from 17.47 kg m−2 s−1 to 52.42 kg m−2 s−1 and inlet vapor qualities range from 0.2 to 0.6. The normalized time-averaged capacitance signal was processed by a Gaussian function to obtain the mathematical expectation and the standard deviation. The local vapor quality in the header was solved for using a correlation derived from the pre-experiments. The distribution of local vapor quality showed that gases were concentrated upstream of the header, while liquids were concentrated in the middle and lower reaches. The local vapor quality reached a minimum and remained constant at 0.1 in the middle and lower reaches, unaffected by changes in inlet conditions. As the mass flux increased, both the local vapor quality maximum point and the minimum point in the header were shifted back toward the downstream. Additionally, the increase of mass flux caused the fluctuation of the standard deviation increased, which meant the stability of the flow decreased. The two-phase flow measurement technique based on flexible capacitance sensors proposed in this study realized the extension of the capacitive method from the experimental stage to the industrial application stage.

Active gas camera mass flow quantification (qOGI): Application in a biogas plant and comparison to state-of-the-art gas cams.

Gas cameras are primarily used to detect gas leaks, but their use has been increasingly extended to mass flow quantification (qOGI). We employ the previously published active illuminated gas camera [Bergau etal. "Real-time active-gas imaging of small gas leaks," J. Sens. Sens. Syst. 12, 61-68 (2023) and Bergau etal. "Flow rate quantification of small methane leaks using laser spectroscopy and deep learning," Process Saf. Environ. Prot. 182, 752-759 (2024)] in a real-world application for quantification, enhancing the camera with two new features: sensitivity adaptation and camera-gas distance detection. This technology was applied to a gas leak found in the pressure swing adsorption room of a biogas plant in Germany. We compare its performance with state-of-the-art quantification gas cameras (qOGI), such as Sensia Mileva 33. Such a comparison between active and passive gas cameras is possible for the first time due to the introduced sensitivity tuning. Additionally, we enclosed the gas leak and measure the methane concentration with a flame ionization detector, providing a gold standard for comparison. Our findings revealed relative offsets to our gold standard of -57% and +319% for the DAS-camera and the Sensia, respectively, suggesting that the accuracy of mass flow quantification could be improved through the use of active gas cameras.

Enhancing the Diagnostic Utility of ASL Imaging in Temporal Lobe Epilepsy through FlowGAN: An ASL to PET Image Translation Framework.

Positron Emission Tomography (PET) using fluorodeoxyglucose (FDG-PET) is a standard imaging modality for detecting areas of hypometabolism associated with the seizure onset zone (SOZ) in temporal lobe epilepsy (TLE). However, FDG-PET is costly and involves the use of a radioactive tracer. Arterial Spin Labeling (ASL) offers an MRI-based quantification of cerebral blood flow (CBF) that could also help localize the SOZ, but its performance in doing so, relative to FDG-PET, is limited. In this study, we seek to improve ASL's diagnostic performance by developing a deep learning framework for synthesizing FDG-PET-like images from ASL and structural MRI inputs. We included 68 epilepsy patients, out of which 36 had well lateralized TLE. We compared the coupling between FDG-PET and ASL CBF values in different brain regions, as well as the asymmetry of these values across the brain. We additionally assessed each modality's ability to lateralize the SOZ across brain regions. Using our paired PET-ASL data, we developed FlowGAN, a generative adversarial neural network (GAN) that synthesizes PET-like images from ASL and T1-weighted MRI inputs. We tested our synthetic PET images against the actual PET images of subjects to assess their ability to reproduce clinically meaningful hypometabolism and asymmetries in TLE. We found variable coupling between PET and ASL CBF values across brain regions. PET and ASL had high coupling in neocortical temporal and frontal brain regions (Spearman's r > 0.30, p < 0.05) but low coupling in mesial temporal structures (Spearman's r < 0.30, p > 0.05). Both whole brain PET and ASL CBF asymmetry values provided good separability between left and right TLE subjects, but PET (AUC = 0.96, 95% CI: [0.88, 1.00]) outperformed ASL (AUC = 0.81; 95% CI: [0.65, 0.96]). FlowGAN-generated images demonstrated high structural similarity to actual PET images (SSIM = 0.85). Globally, asymmetry values were better correlated between synthetic PET and original PET than between ASL CBF and original PET, with a mean correlation increase of 0.15 (95% CI: [0.07, 0.24], p<0.001, Cohen's d = 0.91). Furthermore, regions that had poor ASL-PET correlation (e.g. mesial temporal structures) showed the greatest improvement with synthetic PET images. FlowGAN improves ASL's diagnostic performance, generating synthetic PET images that closely mimic actual FDG-PET in depicting hypometabolism associated with TLE. This approach could improve non-invasive SOZ localization, offering a promising tool for epilepsy presurgical assessment. It potentially broadens the applicability of ASL in clinical practice and could reduce reliance on FDG-PET for epilepsy and other neurological disorders.

Simultaneous assessment of blood flow and myelin content in the brain white matter with dynamic [11C]PiB PET: a test-retest study in healthy controls.

Exploring the relationship between oxygen supply and myelin damage would benefit from a simultaneous quantification of myelin and cerebral blood flow (CBF) in the brain's white matter (WM). To validate an analytical method for quantifying both CBF and myelin content in the WM using dynamic [11C]PiB positron emission tomography (PET). A test-retest study was performed on eight healthy subjects who underwent two consecutive dynamic [11C]PiB-PET scans. Three quantitative approaches were compared: simplified reference tissue model 2 (SRTM2), LOGAN graphical model, and standardized uptake value ratio (SUVR). The sensitivity of methods to the size of the region of interest was explored by simulating lesion masks obtained from 36 subjects with multiple sclerosis. Reproducibility was assessed using the relative difference and interclass correlation coefficient. Repeated measures correlations were used to test for cross-correlations between metrics. Among the CBF measures, the relative delivery (R1) of the simplified reference tissue model 2 (SRTM2) displayed the best reproducibility in the white matter, with a strong influence of the size of regions analyzed, the test-retest variability being below 10% for regions above 68 mm3 in the supratentorial white matter. [11C]PiB PET-derived proxies of CBF demonstrated lower perfusion of white matter compared to grey matter with an overall ratio equal to 1.71 ± 0.09 when the SRTM2-R1 was employed. Tissue binding in the white matter was well estimated by the Logan graphical model through estimation of the distribution volume ratio (LOGAN-DVR) and SRTM2 distribution volume ratio (SRTM2-DVR), with test-retest variability being below 10% for regions exceeding 106 mm3 for LOGAN-DVR and 300 mm3 for SRTM2-DVR. SRTM2-DVR provided a better contrast between white matter and grey matter. The interhemispheric variability was also dependent on the size of the region analyzed, being below 10% for regions above 103 mm3 for SRTM2-R1 and above 110 mm3 for LOGAN-DVR. Whereas the 1 to 8-minute standardized uptake value ratio (SUVR1-8) showed an intermediary reproducibility for CBF assessment, SUVR0-2 for perfusion or SUVR50-70 for tissue binding showed poor reproducibility and correlated only mildly with SRTM2-R1 and LOGAN-DVR estimations respectively. [11C]PiB PET imaging can simultaneously quantify perfusion and myelin content in WM diseases associated with focal lesions. For longitudinal studies, SRTM2-R1 and DVR should be preferred over SUVR for the assessment of regional CBF and myelin content, respectively. European Union Clinical Trials Register EUDRACT; EudraCT Number: 2008-004174-40; Date: 2009-03-06; https//www.clinicaltrialsregister.eu ; number 2008-004174-40.

#2115 Phase-contrast magnetic resonance imaging (PC-MRI) for quantification of volumetric flow in renal transplant arteries: an observational cohort study

Abstract Background and Aims Impaired renal transplant blood flow, a manifestation of severe transplant renal artery stenosis (TRAS), can negatively impact transplant function and survival. Phase-contrast magnetic resonance imaging (PC-MRI) is a non-invasive method of quantifying blood flow volume. Recent work has demonstrated the utility of this technique in measuring native renal blood flow, whilst validating the use of flow measurements taken on the aorta above and below the origin of the renal arteries to calculate flow in the renal arteries [1]. As part of a quality improvement study incorporating PC-MRI into renal transplant assessment, this study set out to (a) establish the normal range for transplant renal blood flow volume and (b) assess whether PC-MRI improved screening for TRAS. Method Between January 2019 and February 2021, PC-MRI sequences were included in the protocols for all magnetic resonance angiograms (MRA) performed as part of clinically-indicated renal transplant assessment. As part of the MRA study, using a coronal localizer MR image, planes were prescribed on the external iliac artery (EIA) both proximal and distal to the transplant artery anastomosis site in a perpendicular orientation (Fig. 1A). Using CV142 software [2], arterial cross-sections were highlighted manually at the pre-determined planes (Fig. 1B) to generate flow curves that coincided with the cardiac cycle (Fig. 1C). Studies were excluded if: the EIA flow waveform was incongruous with the cardiac cycle, contemporaneous heart rate data was not recorded, or the calculated flow volume was a negative value. Results During the study period 392 transplant MRAs were performed, of which 218 were included in this analysis. Potential TRAS was identified in 49 (22.5%) studies, with 19 (8.7%) having this diagnosis confirmed by intra-arterial digital subtraction angiography (IADSA). In the 169 (77.5%) studies without evidence of TRAS, the mean flow in the proximal EIA was 0.90 L/min (95% CI 0.85-0.94 L/min) and in the distal EIA 0.47 L/min (95% CI 0.44-0.50 L/min). The difference between the two measurement points, that is the flow in the transplant renal artery, was 0.42 L/min (95% CI 0.39-0.45 L/min) (Fig. 2A). In the 19 studies with TRAS confirmed by IADSA, mean flow at the time of the initial MRA was 0.34 L/min (95% CI 0.25-0.43 L/min); there was no difference when compared with the group without evidence of TRAS on MRA (p = 0.09) (Fig. 2B). Of the patients who had potential TRAS identified on MRA, 30 patients proceeded to IADSA; there was no difference in PC-MRI flow volume in the 11 who had a diagnosis of TRAS refuted on IADSA and the 19 who had diagnosis of TRAS confirmed (p = 0.97). ROC curve analysis of PC-MRI arterial flow measurement as a diagnostic test for TRAS, whereby the positive group of 19 had IADSA confirmed TRAS, the negative group of 176 had either normal MRA artery appearances or normal IADSA, and the disease prevalence is 13.7% [3], shows AUC 0.62 (95% CI 0.55-0.69) P = 0.09, sensitivity 57.9 specificity 67.1 (Fig. 2C). Conclusion This is the largest study to incorporate functional PC-MRI sequences into MRA protocols for the assessment of people with any form of kidney disease. The results suggest that the blood flow volume in healthy transplant renal arteries lies between 0.39–0.45 L/min. In comparative analysis between patients with healthy transplant arteries and those with IADSA-confirmed TRAS, there was no difference in arterial flow volume, though the study was limited by the small population in the group with IADSA-confirmed TRAS. PC-MRI does not appear to improve the screening accuracy of MRA in identifying TRAS. However, there may be a future role for PC-MRI as part of multi-parametric MR protocols for comprehensive assessment of patients with kidney transplants.

Conjoint analysis of nitrogen and phosphorus metabolism in urban system: A case study of Dar es Salaam, Tanzania

AbstractNitrogen (N) and phosphorus (P) metabolism is becoming an increasingly complex process during urbanization due to increasing rates of consumption and emission worldwide. Understanding the urban N and P metabolism helps identifying production capacity, consumption demand, and the impact of N and P emissions on the environment, providing a scientific basis for decision‐making in sustainable utilization of N and P resources. Quantifying and mapping the source, path, and sinks of N and P in an urban system is the premise of controlling emissions. In this paper, we used the substance flow analysis (SFA) method to describe the N and P metabolism processes in the urban system of Dar es Salaam (Tanzania) in 2017, and used the scenario‐based analysis method to understand the impact of different N and P metabolisms on potentially recoverable N and P sources by 2030. The results showed that the urban system of Dar es Salaam receives a total input flow of 28,101.8 tN/year and 3,379 tP/year, with a total output flow of 18,859.6 tN/year and 1,849.3 tP/year with net stock changes of 9,242.2 t/year for N and 1,529.7 t/year for P, respectively. We noticed that increased human activities largely represented the city's waste released after the household consumption, and would become the main causes of N and P emissions. In addition to this, 59.38%, 31.25%, and 9.38% of N flow quantification quality were at high, medium, and low levels, respectively, while 74.07%, 11.11%, and 14.81% of P flow quantification quality were at high, medium, and low levels, respectively. Our results suggest that implementing integrated nutrient management measures, such as changes in people's diets and the use of washing products, and improved management and technologies of manure, sewage, and landfill leachate treatment, would be the most effective approach to resolve the urban nutrient emissions in Dar es Salaam.

Quantification of steal flow on Doppler ultrasound in patients with arteriovenous graft for hemodialysis.

Arteriovenous fistula (AVF) is the preferred treatment for long-term hemodialysis patients to allow reliable vascular access. Arteriovenous graft (AVG) is monitored using Doppler sonography to check a vessel's condition and predict complications such as steal syndrome. In this study, we developed an analysis algorithm and method to quantify steal syndrome using Doppler sonography. Doppler sonography was used to determine the pattern of anterograde and retrograde flow. The ratio of blood volumes was calculated with a vision analysis software. First, performance of the developed algorithm was validated by comparing it with commercial Doppler sonography data. Doppler sonography was performed for an artificial vessel to analyze the steal flow. A total of 58 patients with steal flow were enrolled in this study. Of these patients, 23 did not have a difference in fingertip temperature between both sides. The median difference in temperature of 35 patients was 0.8°C (range, 0.3-1.9°C). The ratio of retrograde flow volume/antegrade flow volume in patients with the presence of temperature difference was significantly higher compared to that in patients without the temperature difference (p < .001). The ROC curve for the difference in flow volume had an AUC of 0.770. The optimal cutoff of difference in the flow volume between the two groups was 0.24 (sensitivity of 91.4 % and specificity of 52.2%). The flow volume difference was significantly positively correlated to temperature difference (r = 0.487, p < .003). Our algorithm could measure steal flow volume of a bidirectional waveform by antegrade arterial flow and retrograde reversal flow.

Bibliometric Analysis of Scientific Publications on Communicative Behavior Problems

Purpose of research. The purpose of the study is to analyze the dynamics of the publication activity of scientific research in the field of studying communicative behavior. Communicative behavior is an object with an interdisciplinary research status. It falls into the area of research interest of various scientific fields. A bibliometric analysis of publication activity was carried out in connection with solving several tasks: to find out areas of knowledge in which the greatest publication activity is concentrated, to study the methods that are used in various fields of communicative behavior analysis, to identify organizations that are included in this research search.Methods. The study was conducted in two scientific electronic databases: the Russian Scientific Electronic Library Elibrary.ru and the international open platform for researchers and scientific organizations Lens. The bibliometric analysis was used as the research method. It involves the quantification of documentary information flows and it is based on quantitative research indicators reflecting the state of science as a whole or its individual branches.Results. As a result of the bibliometric analysis of publication activity on the problems of scientific research in the field of communicative behavior, communicative behavior in the digital environment and communicative behavior in social networks, a significant increase in publication activity was revealed in both international and Russian information databases over the past 10 years (2013 - 2023). It is also noted that the predominant number of publications on the issues studied is concentrated in the field of psychology. However, we can trace a shift in the focus of foreign research on communicative behavior towards digitalization in information technology, and Russian research towards the field of digital technologies in the educational environment.Conclusion. The results obtained indicate the high relevance, as well as the scientific and practical significance of the research topic on the problems of communicative behavior in general, as well as communicative behavior in the digital environment and social networks, in particular.

Unwrapping phase contrast MRI by iterative graph cuts.

To develop and evaluate a phase unwrapping method for cine phase contrast MRI based on graph cuts. A proposed Iterative Graph Cuts method was evaluated in 10 cardiac patients with two-dimensional flow quantification which was repeated at low venc settings to provoke wrapping. The images were also unwrapped by a path-following method (ROMEO), and a Laplacian-based method (LP). Net flow was quantified using semi-automatic vessel segmentation. High venc images were also wrapped retrospectively to asses the residual amount of wrapped voxels. The absolute net flow error after unwrapping at venc = 100cm/s was 1.8mL, which was 0.83mL smaller than for LP. The repeatability error at high venc without unwrapping was 2.5mL. The error at venc = 50cm/s was 7.5mL, which was 8.2mL smaller than for ROMEO and 5.7mL smaller than for LP. For retrospectively wrapped images with synthetic venc of 100/50/25cm/s, the residual amount of wrapped voxels was 0.00/0.12/0.79%, which was 0.09/0.26/8.0percentage points smaller than for LP. With synthetic venc of 25cm/s, omitting magnitude information resulted in 3.2 percentage points more wrapped voxels, and only spatial/temporal unwrapping resulted in 4.6/21 percentage points more wrapped voxels compared to spatiotemporal unwrapping. Iterative Graph Cuts enables unwrapping of cine phase contrast MRI with very small errors, except for at extreme blood velocities, with equal or better performance compared to ROMEO and LP. The use of magnitude information and spatiotemporal unwrapping is recommended.

Test-retest reliability of resting-state cerebral blood flow quantification using pulsed Arterial Spin Labeling (PASL) over 3 weeks vs 8 weeks in healthy controls

Arterial Spin Labeling is a valuable functional imaging tool for both clinical and research purposes. However, little is known about the test-retest reliability of cerebral blood flow measurements over longer periods. In this study, we investigated the reliability of pulsed Arterial Spin Labeling in assessing cerebral blood flow over a 3 (n = 28) vs 8 (n = 19) weeks interscan interval in 47 healthy participants. As a measure of cerebral blood flow reliability, we calculated voxel-wise, whole-brain, and regions of interest intraclass correlation coefficients. The whole-brain mean resting-state cerebral blood flow showed good to excellent reliability over time for both periods (intraclass correlation coefficients = 0.85 for the 3-week delay, intraclass correlation coefficients = 0.53 for the 8-week delay). However, the voxel-wise and regions of interest intraclass correlation coefficients fluctuated at 8-week compared to the 3-week interval, especially within cortical areas. These results confirmed previous findings that Arterial Spin Labeling could be used as a reliable method to assess brain perfusion. However, as the reliability seemed to decrease over time, caution is warranted when performing correlations with other variables, especially in clinical populations.

TAI-GAN: A Temporally and Anatomically Informed Generative Adversarial Network for early-to-late frame conversion in dynamic cardiac PET inter-frame motion correction

Inter-frame motion in dynamic cardiac positron emission tomography (PET) using rubidium-82 (82Rb) myocardial perfusion imaging impacts myocardial blood flow (MBF) quantification and the diagnosis accuracy of coronary artery diseases. However, the high cross-frame distribution variation due to rapid tracer kinetics poses a considerable challenge for inter-frame motion correction, especially for early frames where intensity-based image registration techniques often fail. To address this issue, we propose a novel method called Temporally and Anatomically Informed Generative Adversarial Network (TAI-GAN) that utilizes an all-to-one mapping to convert early frames into those with tracer distribution similar to the last reference frame. The TAI-GAN consists of a feature-wise linear modulation layer that encodes channel-wise parameters generated from temporal information and rough cardiac segmentation masks with local shifts that serve as anatomical information. Our proposed method was evaluated on a clinical 82Rb PET dataset, and the results show that our TAI-GAN can produce converted early frames with high image quality, comparable to the real reference frames. After TAI-GAN conversion, the motion estimation accuracy and subsequent myocardial blood flow (MBF) quantification with both conventional and deep learning-based motion correction methods were improved compared to using the original frames. The code is available at https://github.com/gxq1998/TAI-GAN.

MRI Evaluation of Microstructural and Perfusion Changes in Patients with Hemsensory Neurological Syndromes

Background: Hemisensory syndrome is characterized by a nondermatomal sensory deficit involving one half of the body. With the conventional imaging techniques, researches find low diagnostic yield in this condition; however, with the advancements in MRI imaging, there is hope to find the pathophysiological basis of hemisensory symptoms. Objective: To evaluate microstructural and perfusion changes in brain parenchyma in patients with hemisensory syndrome on MRI with diffusion tensor imaging (DTI) and arterial spin labeling (ASL). Material and Methods: A total of 20 patients with hemisensory symptoms and 10 age-matched controls were enrolled and divided in two study groups – a) case vs. control and b) affected vs. nonaffected cerebral hemisphere in cases. Quantification of absolute cerebral blood flow (aCBF), fractional anisotropy (FA), and mean diffusivity (MD) was done in both groups. Results: On ASL, there was significantly increased aCBF in thalamus on the contralateral-affected side. DTI revealed significantly decreased FA in the thalamus and increased FA in corona radiata of the affected side. There was a significant difference for MD of corona radiata between affected and nonaffected hemisphere. The mean value of MD in corona radiata is decreased on the affected side. Conclusion: Changes in advanced neuroimaging techniques like ASL and DTI along the pain processing pathway suggest an alteration in neuronal density and activity at the microstructural level. These findings may provide an insight into the etiopathogenesis of pain syndromes.

Method of storage impacts graft immune cell populations in intestinal transplantation

Intestinal transplantation (IT) is the only treatment for intestinal failure patients who cannot tolerate parenteral nutrition. Although cold storage (CS) is the gold standard for intestinal allograft preservation, normothermic machine perfusion (NMP) has improved transplantation success in other organs. Allograft immune modulation is thought to contribute to this success. The objective of this study was to assess the impact of NMP on intestinal immune cell populations as it relates to ultimate allograft and recipient health. We hypothesized that NMP would stabilize overall immune cell populations while reducing pro-inflammatory cohorts, thus improving IT success. Porcine intestines were stored for 6H at 4°C (CS-T6, n=6) or perfused at 34°C (NMP-T6, n=8) and transplanted. Samples were collected following intestinal procurement (T0), storage (T6), 1-hour post-transplant (T1PT), and euthanasia (T48). Flow cytometric profiling and quantification of intraepithelial (IEL) and lamina propria (LP) lymphocytes and NK cells were performed at T0, T6, and T48. Immunofluorescence (IF) identified CD3+ T-cells at T1PT. One-way ANOVA analyzed cell counts with significance set at p&lt; 0.05. Flow cytometry revealed that NMP preserved CD3+ IELs in the jejunum at T6 (63.74% vs 32.79%, p&lt; 0.0001), and in the ileum at T6 (51.31% vs 42.77%, p&lt; 0.0001) and at T48 (57.73% vs 34.21%, p&lt;0.0001). Immunofluorescent cell quantification confirmed this preservation of CD3+ IEL at T1PT in the crypts of the jejunum (4.9% vs 2.1 %, p&lt; 0.05) and ileum (6.9% vs 2.8%, p&lt; 0.001) compared to CS. However, upon further subpopulation analyses using flow cytometry, ileal IEL T-cells were reduced throughout NMP compared to CS (T6 28.7% vs 44.0%; T48 16.65% vs 22.37%; p&lt; 0.0001). NK cells were also decreased in ileal and jejunal LP at NMP-T6 compared to T0 (3.6% vs 5.6%, p&lt; 0.01; 2.4% vs 4.3% p&lt; 0.05). NMP reduces NK cells, a cell type known to be associated with rejection. Interestingly, NMP preserved the overall CD3+ T cell populations in the jejunum and ileum at T6, T1PT, and T48. The subpopulation of IELs, however, were reduced in the ileum following NMP. The role of these populations, specifically in IT, has yet to be determined. Further characterization of T-cell subpopulations and dynamics is needed. Complimentary evaluations of the microbiome and proteomic responses to IT NMP are ongoing. Understanding immune cell dynamics will improve IT outcomes for patients requiring this critical, lifesaving surgery. U.S. Department of Defense PR181265; NIH K01OD010199 SERCA, T32OD011130-15. 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.

Ensemble variational Bayesian approximation for the inversion and uncertainty quantification of Darcy flows in heterogeneous porous media with random parameters

The inversion and uncertainty quantification of physical parameters are important for many science and engineering problems. For nonlinear parameter inversion problems of flows in hydrocarbon reservoirs, estimating the true posterior probability distribution function for the random parameter is difficult when the dimension of the parameter is relatively high. Inversion methods such as gradient-based or heuristic optimization methods searching for the maximum a posterior are generally point-estimate, while uncertainty quantification using MCMC is computationally expensive. In the current study, a new ensemble variational Bayesian approximation method is developed to estimate the posterior probability density using an ensemble of realizations regarded as a trial sample distribution. The objective is to optimize the trial sample distribution such that the evidence lower bound is maximized indicating that the distance between the trial and true posterior distribution is minimized. A subspace is built using principle component analysis based on finite samples to obtain a diagonal positive-definite covariance matrix, and ensemble-based data assimilation is used to optimize the trial distribution efficiently. Heterogeneous 2D and 3D test cases of transient single- and two-phase Darcy flows are presented for validation.

Arterial Input Function (AIF) Correction Using AIF Plus Tissue Inputs with a Bi-LSTM Network.

Background: The arterial input function (AIF) is vital for myocardial blood flow quantification in cardiac MRI to indicate the input time-concentration curve of a contrast agent. Inaccurate AIFs can significantly affect perfusion quantification. Purpose: When only saturated and biased AIFs are measured, this work investigates multiple ways of leveraging tissue curve information, including using AIF + tissue curves as inputs and optimizing the loss function for deep neural network training. Methods: Simulated data were generated using a 12-parameter AIF mathematical model for the AIF. Tissue curves were created from true AIFs combined with compartment-model parameters from a random distribution. Using Bloch simulations, a dictionary was constructed for a saturation-recovery 3D radial stack-of-stars sequence, accounting for deviations such as flip angle, T2* effects, and residual longitudinal magnetization after the saturation. A preliminary simulation study established the optimal tissue curve number using a bidirectional long short-term memory (Bi-LSTM) network with just AIF loss. Further optimization of the loss function involves comparing just AIF loss, AIF with compartment-model-based parameter loss, and AIF with compartment-model tissue loss. The optimized network was examined with both simulation and hybrid data, which included in vivo 3D stack-of-star datasets for testing. The AIF peak value accuracy and ktrans results were assessed. Results: Increasing the number of tissue curves can be beneficial when added tissue curves can provide extra information. Using just the AIF loss outperforms the other two proposed losses, including adding either a compartment-model-based tissue loss or a compartment-model parameter loss to the AIF loss. With the simulated data, the Bi-LSTM network reduced the AIF peak error from -23.6 ± 24.4% of the AIF using the dictionary method to 0.2 ± 7.2% (AIF input only) and 0.3 ± 2.5% (AIF + ten tissue curve inputs) of the network AIF. The corresponding ktrans error was reduced from -13.5 ± 8.8% to -0.6 ± 6.6% and 0.3 ± 2.1%. With the hybrid data (simulated data for training; in vivo data for testing), the AIF peak error was 15.0 ± 5.3% and the corresponding ktrans error was 20.7 ± 11.6% for the AIF using the dictionary method. The hybrid data revealed that using the AIF + tissue inputs reduced errors, with peak error (1.3 ± 11.1%) and ktrans error (-2.4 ± 6.7%). Conclusions: Integrating tissue curves with AIF curves into network inputs improves the precision of AI-driven AIF corrections. This result was seen both with simulated data and with applying the network trained only on simulated data to a limited in vivo test dataset.