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Gi, Y. J.

Publications and source records attributed to Gi, Y. J..

3 recordsLinked to original sources

VESTA: Machine Learning-Enabled Estimation of ViscoElastic Ratios from On-Axis Spatio-Temporal ARFI Features

Viscoelastic characterization of tissue has significant diagnostic value in oncology, as tumor progression alters both elasticity and viscosity in ways that neither property alone can fully capture. Existing acoustic radiation force (ARF)-based methods such as Viscoelastic Response (VisR) ultrasound estimate relative elasticity and viscosity through per-A-line nonlinear model fitting, which is computationally intensive and requires auxiliary simulations to correct elasticity-dependent bias. This work presents VESTA (Machine Learning-Enabled Estimation of ViscoElastic Ratios from On-Axis Spatio-Temporal ARFI Features), a two-stage data-driven pipeline that predicts elasticity ratio (ER) and viscosity ratio (VR) directly from seven normalized ARFI displacement features at the A-line level, without model fitting or compensation. Stage 1 is an MLP classifier that detects inclusion boundaries from normalized peak displacement and negative peak velocity ratios; Stage 2 is a dilated Conv1D regression model that estimates ER and VR along the full axial sequence using the predicted mask alongside displacement features. The pipeline was trained on 500 simulated inclusion scenarios spanning three geometries, five focal depths, two F-numbers, and a broad range of material contrasts. In silico, mean predicted ER and VR were within 12% of ground truth across all geometries, with performance best when ER and VR were moderate or decoupled. Experimental validation on a chicken breast phantom demonstrated plausible generalization to real tissue heterogeneity. Applied to an in vivo murine 4T1 breast cancer model, the pipeline tracked treatment-related attenuation of mechanical contrast in paclitaxel-treated tumors relative to controls over a 36-day imaging period, supporting its relevance for tumor monitoring.

bioengineering↗

APRIL: Adaptive Regression-Based Two-Dimensional Quantitative Anisotropy Imaging Using Acoustic Radiation Force Impulse

ObjectiveThis study aims to develop and validate a quantitative, depth-resolved anisotropy imaging framework that extends ARFI-based focal degree-of-anisotropy (DoA) estimation into two-dimensional mapping by modeling the depth-dependent relationship between shear modulus ratio (SMR) and peak displacement ratio (PDR). MethodsWe propose APRIL (Adaptive Polynomial Regression for anisotropy Imaging via ARFI-induced DispLacements), a framework for quantitative, depth-resolved DoA imaging that adaptively selects polynomial regression or shape-preserving spline interpolation based on excitation PSF asymmetry. Training data were generated using an LS-DYNA3D + Field II simulation pipeline in homogeneous transversely isotropic media (SMR 0.9-4.9). Testing included shifted SMRs under varied acoustic conditions and three heterogeneous inclusion configurations (anisotropic inclusion in isotropic background and vice versa). Experimental validation was performed in an in-vivo murine tumor model over the time, ex-vivo chicken breast, and tissue-mimicking gelatin phantoms, using a Verasonics system with an L11-5v transducer. ResultsAPRIL achieved depth-resolved SMR prediction errors below 9% over 10-30 mm, with highest accuracy in the focal region (MAE 2.3%, RMSE < 0.1) and stable performance across PSF transition zones. In heterogeneous phantoms, it reconstructed anisotropy maps with SSIM up to 86% and MPE below 7%, accurately delineating inclusion boundaries. Under acoustic parameter variations, mean absolute errors remained below 10%, demonstrating robustness to system and tissue heterogeneity. ConclusionAPRIL enables robust, two-dimensional anisotropy imaging beyond focal estimates. SignificanceThe method provides a physically grounded and generalizable framework for clinically viable anisotropy biomarkers in muscle, tendon, kidney, tumor and breast tissues. HighlightsO_LINovelty: APRIL introduces LoA-conditioned adaptive polynomial-spline regression to extend ARFI-based anisotropy estimation from focal point estimates into full 2D depth-resolved SMR imaging. C_LIO_LIResults: APRIL achieved SMR prediction errors below 9% over 10-30 mm, SSIM up to 86% in heterogeneous phantoms, MAE below 10% under acoustic variations, tracked tumor anisotropy progression in vivo, and differentiated anisotropic inclusion versus isotropic background in tissue-mimicking gelatin phantom. C_LIO_LISignificance: APRIL enables clinically viable, spatially resolved anisotropy biomarker imaging in muscle, tendon, kidney, and tumor tissues without requiring heterogeneous training data. C_LI

bioengineering↗

Downregulation of LATS1/2 Drives Endothelial Senescence-Associated Stemness (SAS) and Atherothrombotic Lesion Formation

BackgroundAtherothrombosis, the main event leading to acute coronary syndrome (ACS), is strongly linked to disturbed blood flow (d-flow) regions. Although the involvement of the Hippo pathway and its kinases Large Tumor Suppressor Kinase 1and 2 (LATS 1 and 2) in mechanical stress responses is known, the mechanisms by which d-flow simultaneously induces senescence, proliferation, and atherothrombosis remain unclear. MethodsThe role of endothelial cells (EC)-specific LATS1/2 was examined using EC specific knock-out (EKO) mice in a partial left carotid ligation (PLCL) model. Plaque spatial multi-omics analysis was performed by integrating imaging mass cytometry, sequential immunofluorescence (COMET), and spatial metabolomics at the single-cell level in human and mouse atherosclerotic plaques. ResultsIn tamoxifen-inducible Lats1homo(-/-) /Lats2 homo(-/-) EC-specific knockout (EKO) mice, deletion of LATS1/2 induced by tamoxifen led to fatal outcomes, characterized by severe systemic edema and markedly increased vascular permeability. In contrast, Lats1het(+/-)/Lats2 homo(-/-)-EKO mice survived and developed atherothrombotic plaques exhibiting neovascularization even without further additional dietary or genetic intervention. Spatial proteomics analysis revealed that LATS1/2 depletion in ECs triggered a senescence-associated stemness (SAS) phenotype, primarily driven by CD38 upregulation. Complementary spatial metabolomics profiling demonstrated a significant increase in sulfite and taurine within LATS1/2-deficient plaques, indicating lowered sulfite oxidase (SUOX) activity. Mechanistically, CD38 upregulation was found to suppress SUOX expression, induce the reverse mode of mitochondrial complex V, and increase succinate dehydrogenase (SDH) activity along with ATP consumption. Paradoxically, despite ATP depletion, this metabolic disturbance enhanced glutamate metabolism and the tricarboxylic acid (TCA) cycle, sustaining EC proliferation under energetically stressed conditions. The combined effect of LATS1/2 deletion and CD38 activation established a unique EC phenotype defined by increased SAS, leading to proliferation, senescence, and eventual cell death. These pathological processes culminated in the formation of atherothrombotic plaques, which were attenuated by inhibition of CD38. Notably, a similar phenotype--marked by metabolically active ECs--was observed in human atherothrombotic plaques, suggesting translational relevance. ConclusionLoss of LATS1/2 in ECs induces SAS state that promotes excessive EC proliferation, senescent cell accumulation, and the development of structurally fragile, leaky neo vessels--hallmarks of atherothrombotic lesions. CD38-mediated SUOX deficiency further amplifies this pathological process by inducing mitochondrial dysfunction, depleting ATP, and triggering compensatory upregulation of glutamate and TCA cycle metabolism. These findings identify a novel LATS1/2-CD38-SUOX axis in ECs that orchestrates SAS-driven atherothrombosis. Targeting CD38 may represent a promising therapeutic strategy to mitigate vascular dysfunction and plaque instability in high-risk ACS patients. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=191 HEIGHT=200 SRC="FIGDIR/small/660635v1_ufig1.gif" ALT="Figure 1"> View larger version (35K): org.highwire.dtl.DTLVardef@149d313org.highwire.dtl.DTLVardef@1c0988borg.highwire.dtl.DTLVardef@15efec9org.highwire.dtl.DTLVardef@1a96e03_HPS_FORMAT_FIGEXP M_FIG C_FIG Under normal physiological conditions, LATS1/2 and Lamin A work together to suppress CD38 expression. Lamin A binds directly to the CD38 promoter to repress transcription, and LATS1/2 interact with Lamin A to reinforce this suppression. This collaboration helps maintain low CD38 activity and preserves cellular NAD levels. However, under disturbed flow (d-flow), both LATS1/2 and Lamin A are downregulated. The loss of this dual repression leads to increased CD38 NADase expression. Elevated CD38 accelerates NAD consumption, causing NAD depletion--a hallmark of cellular senescence. Reduced NAD disrupts key metabolic and stress-response pathways, contributing to the onset of the senescent state. At the same time, CD38 suppresses sulfite oxidase (SUOX), leading to sulfite accumulation and mitochondrial redox imbalance. This shift activates the reverse mode of mitochondrial Complex V, which decreases ATP production and increases mitochondrial ROS, intensifying metabolic and oxidative stress in endothelial cells (ECs). In response, ECs compensate by upregulating succinate dehydrogenase (SDH), enhancing TCA cycle activity and glutamate metabolism. This metabolic adaptation provides the biosynthetic building blocks needed for cell growth and proliferation. As a result, ECs adopt a paradoxical phenotype: they show classical features of stress-induced senescence (such as NAD depletion, oxidative stress, and cell cycle arrest signals), while simultaneously undergoing metabolic activation and proliferation, also mediated by YAP. This defines a non-canonical endothelial program known as senescence-associated stemness (SAS), characterized by the formation of abnormal, proliferative, yet fragile neovessels. These dysfunctional vessels contribute to atherothrombosis, setting this process apart from the more stable lesions typical of conventional atherosclerosis.

molecular biology↗