Magnetic Resonance Imaging with tagging (tMRI) has long been utilized for quantifying tissue motion and strain during deformation. However, a phenomenon known as tag fading, a gradual decrease in tag visibility over time, often complicates post-processing. The first contribution of this study is to model tag fading by considering the interplay between T1 relaxation and the repeated application of radio frequency (RF) pulses during serial imaging sequences. This is a factor that has been overlooked in prior research on tMRI post-processing. Further, we have observed an emerging trend of utilizing raw tagged MRI within a deep learning-based (DL) registration framework for motion estimation. In this work, we evaluate and analyze the impact of commonly used image similarity objectives in training DL registrations on raw tMRI. This is then compared with the Harmonic Phase-based approach, a traditional approach which is claimed to be robust to tag fading. Our findings, derived from both simulated images and an actual phantom scan, reveal the limitations of various similarity losses in raw tMRI and emphasize caution in registration tasks where image intensity changes over time.
Publications by Year: 2024
2024
Magnetic Resonance Elastography (MRE) is a noninvasive method for quantitatively assessing the viscoelastic properties of tissues, such as the brain. MRE has been successfully used to measure the material properties and diagnose diseases based on the difference in mechanical properties between diseased and normal tissue. However, MRE is still an emerging technology that is not part of routine clinical imaging like structural Magnetic Resonance Imaging (MRI), and the acquisition equipment is not widely available. Thus, it is challenging to collect MRE, but there is an increasing interest in it. In this study, we explore using structural MRI images to synthesize the MRE-derived material properties of the human brain. We use deep networks that employ both MRI and Diffusion Tensor Imaging (DTI) to explore the best input images for MRE image synthesis. This work is the first study to report on the feasibility of MRE synthesis from structural MRI and DTI.
Objective: Chronic subdural hematoma (cSDH) is prevalent globally and its management is evolving to minimize morbidity while optimizing theater utilization. We present our institution’s experience with subdural evacuation port system (SEPS) as a first-line treatment approach to cSDHs.
Methods: A retrospective review was performed of patients undergoing bedside SEPS placement in a single institution. Pre- and post-procedural radiographic and clinical data were collected and analyzed to identify predictive variables of procedural success for the SEPS approach. For procedure failures, subsequent procedures were analyzed for rates of success.
Results: 268 patients were identified for a total of 326 initial procedures. Pre-procedural variables associated with improved odds of a good outcome were: unilateral cSDH, prior use of anticoagulation, GCS > 13 at presentation, larger cSDH, and greater degree of midline shift (MLS). 65% success rate was observed for initial SEPS placement and an overall success of 78% after repeat SEPS. Bilateral SDH with bilateral SEPS placement had 56% success, a significantly lower success rate than unilateral placement (p=0.0147). Patients with subsequent failures underwent craniotomy. Patients who had a successful SEPS procedure had an average LOS of 13 ± 39 days compared to 25 ± 65 in incidents of failure (p=0.047). Average follow-up after discharge was 2.8 ± 3.8 months.
Conclusions: Bedside SEPS placement is a low-risk option for first-line treatment of cSDH and may spare patients from the risks of general anesthesia while reducing burden on surgical theaters in resource-limited settings. Performing a repeat SEPS procedure is a reasonable surgical option if the first procedure fails to completely evacuate the cSDH.
Introduction
Computational head injury models are promising tools for understanding and predicting traumatic brain injuries. However, most available head injury models are “average” models that employ a single set of head geometry (e.g., 50th-percentile U.S. male) without considering variability in these parameters across the human population. A significant variability of head shapes exists in U.S. Army soldiers, evident from the Anthropometric Survey of U.S. Army Personnel (ANSUR II). The objective of this study is to elucidate the effects of head shape on the predicted risk of traumatic brain injury from computational head injury models.
Materials and Methods
Magnetic resonance imaging scans of 25 human subjects are collected. These images are registered to the standard MNI152 brain atlas, and the resulting transformation matrix components (called head shape parameters) are used to quantify head shapes of the subjects. A generative machine learning model is used to generate 25 additional head shape parameter datasets to augment our database. Head injury models are developed for these head shapes, and a rapid injurious head rotation event is simulated to obtain several brain injury predictor variables (BIPVs): Peak cumulative maximum principal strain (CMPS), average CMPS, and the volume fraction of brain exceeding an injurious CMPS threshold. A Gaussian process regression model is trained between head shape parameters and BIPVs, which is then used to study the relative sensitivity of the various BIPVs on individual head shape parameters. We distinguish head shape parameters into 2 types: Scaling components Txx, Tyy, and Tzz that capture the breadth, length, and height of the head, respectively, and shearing components (Txy,Txz,Tyx,Tyz,Tzx, and Tzy) that capture the relative skewness of the head shape.
Results
An overall positive correlation is evident between scaling components and BIPVs. Notably, a very high, positive correlation is seen between the BIPVs and the head volume. As an example, a 57% increase in peak CMPS was noted between the smallest and the largest investigated head volume parameters. The variation in shearing components Txy,Txz,Tyx,Tyz,Tzx, and Tzy on average does not cause notable changes in the BIPVs. From the Gaussian process regression model, all 3 BIPVs showed an increasing trend with each of the 3 scaling components, but the BIPVs are found to be most sensitive to the height dimension of the head. From the Sobol sensitivity analysis, the Tzz scaling parameter contributes nearly 60% to the total variance in peak and average CMPS; Tyy contributes approximately 20%, whereas Txx contributes less than 5%. The remaining contribution is from the 6 shearing components. Unlike peak and average CMPS, the VF-CMPS BIPV is associated with relatively evenly distributed Sobol indices across the 3 scaling parameters. Furthermore, the contribution of shearing components on the total variance in this case is negligible.
Conclusions
Head shape has a considerable influence on the injury predictions of computational head injury models. Available “average” head injury models based on a 50th-percentile U.S. male are likely associated with considerable uncertainty. In general, larger head sizes correspond to greater BIPV magnitudes, which point to potentially a greater injury risk under rapid neck rotation for people with larger heads.
Background
Standardized exercise protocols have been shown to improve overall cardiovascular fitness, but direct effects on left ventricular (LV) function, particularly diastolic function and relation to post-transcriptional molecular pathways (microRNAs (miRs)) are poorly understood. This project tested the central hypothesis that adaptive LV remodeling resulting from a large animal exercise training protocol, would be directly associated with specific miRs responsible for regulating pathways relevant to LV myocardial stiffness and geometry.
Methods and results
Pigs (n = 9; 25 Kg) underwent a 4 week exercise training protocol (10 degrees elevation, 2.5 mph, 10 min, 5 days/week) whereby LV chamber stiffness (KC) and regional myocardial stiffness (rKm) were measured by Doppler/speckle tracking echocardiography. Age and weight matched non-exercise pigs (n = 6) served as controls. LV KC fell by approximately 50% and rKm by 30% following exercise (both p < 0.05). Using an 84 miR array, 34 (40%) miRs changed with exercise, whereby 8 of the changed miRs (miR-19a, miR-22, miR-30e, miR-99a, miR-142, miR-144, miR-199a, and miR-497) were correlated to the change in KC (r ≥ 0.5 p < 0.05) and mapped to matrix and calcium handling processes. Additionally, miR-22 and miR-30e decreased with exercise and mapped to a localized inflammatory process, the inflammasome (NLRP-3, whereby a 2-fold decrease in NLRP-3 mRNA occurred with exercise (p < 0.05).
Conclusion
Chronic exercise reduced LV chamber and myocardial stiffness and was correlated to miRs that map to myocardial relaxation processes as well as local inflammatory pathways. These unique findings set the stage for utilization of myocardial miR profiling to identify underlying mechanisms by which exercise causes changes in LV myocardial structure and function.
In general, the present disclosure is directed to an endovascular device. The device may include an outer body comprising a biocompatible polymeric material; and a core comprising a first layer and a second layer, wherein the first layer comprising an anti-contractile agent and the second layer comprising a second agent.
Methods and systems for utilizing myocardial strain imaging in an inverse framework to identify mechanical properties of the heart and to determine structural and functional milestones for the development and progression to heart failure.
Background:
Paclitaxel (PTX) is touted as an essential medicine due to its extensive use as a chemotherapeutic agent for various cancers and an antiproliferative agent for endovascular applications. Emerging studies in cardio-oncology implicate various vascular complications of chemotherapeutic agents.
Methods:
We evaluated the inflammatory response induced by the systemic administration of PTX. The investigation included RNAseq analysis of primary human endothelial cells (ECs) treated with PTX to identify transcriptional changes in pro-inflammatory mediators. Additionally, we used dexamethasone (DEX), a well-known antiinflammatory compound, to assess its effectiveness in counteracting these PTX-induced changes. Further, we studied the effects of PTX on monocyte chemoattractant protein-1 (MCP-1) levels in the media of ECs. The study also extended to in vivo analysis, where a group of mice was injected with PTX and subsequently harvested at different times to assess the immediate and delayed effects of PTX on inflammatory mediators in blood and aortic ECs.
Results:
Our RNAseq analysis revealed that PTX treatment led to significant transcriptional perturbations in pro-inflammatory mediators such as MCP-1 and CD137 within primary human ECs. These changes were effectively abrogated when DEX was administered. In vitro experiments showed a marked increase in MCP-1 levels in EC media following PTX treatment, which returned to baseline upon treatment with DEX. In vivo, we observed a threefold increase in MCP-1 levels in blood and aortic ECs 12 h post-PTX administration. Similar trends were noted for CD137 and other downstream mediators like tissue factor, vascular cell adhesion molecule 1, and E-selectin in aortic ECs.
Conclusion:
Our findings illustrate that PTX exposure induces an upregulation of atherothrombotic mediators, which can be alleviated with concurrent administration of DEX. Considering these observations, further long-term investigations should focus on understanding the systemic implications associated with PTX-based therapies and explore the clinical relevance of DEX in mitigating such risks.
Left ventricular pressure overload (LVPO) can lead to heart failure with a preserved ejection fraction (HFpEF) and LV chamber stiffness (LV Kc) is a hallmark. This project tested the hypothesis that the development of HFpEF due to an LVPO stimulus will alter posttranscriptional regulation, specifically microRNAs (miRs). LVPO was induced in pigs (n = 9) by sequential ascending aortic cuff and age- and weight-matched pigs (n = 6) served as controls. LV function was measured by echocardiography and LV Kc by speckle tracking. LV myocardial miRs were quantified using an 84-miR array. Treadmill testing and natriuretic peptide-A (NPPA) mRNA levels in controls and LVPO were performed (n = 10, n = 9, respectively). LV samples from LVPO and controls (n = 6, respectively) were subjected to RNA sequencing. LV mass and Kc increased by over 40% with LVPO (P < 0.05). A total of 30 miRs shifted with LVPO of which 11 miRs correlated to LV Kc (P < 0.05) that mapped to functional domains relevant to Kc such as fibrosis and calcium handling. LVPO resulted in reduced exercise tolerance (oxygen saturation, respiratory effort) and NPPA mRNA levels increased by fourfold (P < 0.05). RNA analysis identified several genes that mapped to specific miRs that were altered with LVPO. In conclusion, a specific set of miRs are changed in a large animal model consistent with the HFpEF phenotype, were related to LV stiffness properties, and several miRs mapped to molecular pathways that may hold relevance in terms of prognosis and therapeutic targets.
G-protein-coupled receptors (GPCRs) mediate many critical physiological processes. Their spatial organization in plasma membrane (PM) domains is believed to encode signaling specificity and efficiency. However, the existence of domains and, crucially, the mechanism of formation of such putative domains remain elusive. Here, live-cell imaging (corrected for topography-induced imaging artifacts) conclusively established the existence of PM domains for GPCRs. Paradoxically, energetic coupling to extremely shallow PM curvature (<1 µm-1) emerged as the dominant, necessary and sufficient molecular mechanism of GPCR spatiotemporal organization. Experiments with different GPCRs, H-Ras, Piezo1 and epidermal growth factor receptor, suggest that the mechanism is general, yet protein specific, and can be regulated by ligands. These findings delineate a new spatiomechanical molecular mechanism that can transduce to domain-based signaling any mechanical or chemical stimulus that affects the morphology of the PM and suggest innovative therapeutic strategies targeting cellular shape.