arXiv subjects

Ingolf Sack

Publications and source records attributed to Ingolf Sack.

13 recordsLinked to original sources

arXiv2026

Ultra-wideband MRE of the human liver and spleen for viscoelastic model identification in hepatic inflammation

Magnetic resonance elastography (MRE) is established for noninvasive assessment of liver fibrosis. Conventional abdominal MRE is typically limited to 40-60 Hz. Lower frequencies remain largely unexplored, particularly with regard to hepatic inflammation. We developed ultra-wideband MRE covering 5-80 Hz to investigate frequency-resolved viscoelastic dispersion of the liver and spleen and to identify biomechanical markers of hepatic inflammation. Following phantom validation, nine healthy volunteers and nine patients with inflammatory liver disease were examined at 12 frequencies. Spatiotemporal phase unwrapping and frequency-adaptive wavefield preprocessing enabled reconstruction of shear wave speed (SWS), penetration rate (PR), and loss angle ($\phi$). Six rheological models were evaluated. The largest inflammation-associated changes were observed at frequencies below 20 Hz: $\phi$ increased by 63% (p<0.001), PR decreased by 37% (p=0.003), and SWS increased by 8% (p=0.008), indicating predominantly dissipative, rather than stiffness-related, changes and a shift toward fluid-like behavior with minor stiffness changes in the lower frequency regime. The rheological springpot model with serial dashpot provided the best fit and revealed distinct dispersion functions for liver and spleen. In patients, springpot elastic modulus increased (101%, p=0.001), while viscosity and springpot power-law exponent decreased (52%, p=0.002 and 58%, p<0.001) suggesting a shift from soft-fluid to stiff-solid liver properties. Ultra-wideband MRE revealed that inflammatory liver disease is associated with property shifts toward stronger dissipation and fluid-like behavior at low frequencies while displaying solid-like behavior at higher frequencies. Ultra-low frequency MRE may provide a diagnostic window into inflammation-associated liver viscoelasticity without full rheological modeling.

physics.med-ph↗

arXiv2026

ARGUS: Accelerated, Robust, General, and Unsupervised Cell Tracking Solutions

Background and Objective: Quantitative analysis of cell dynamics is central to modern biological research, providing critical insights into immune cell interactions, disease progression, and drug mechanisms. Automated cell tracking in time-lapse microscopy remains challenging due to noise, morphological variations, overlapping cells, and dynamic events such as divisions and fusions. Methods: We present ARGUS, a framework for Accelerated, Robust, General, and Unsupervised Cell Tracking Solutions. ARGUS combines adaptive cell detection, dense Farneback optical-flow prediction, frame-to-frame linear assignment, and a sequence-level tracklet-refinement step that reconnects trajectory fragments across short temporal gaps. Results: On publicly available Cell Tracking Challenge datasets, ARGUS achieved detection accuracy of 0.905-0.971 and tracking accuracy of 0.897-0.964, with runtimes within 1 minute (5-6 seconds for 3 frames). Conclusions: ARGUS is a modular, interpretable framework that can be adapted to different imaging modalities and biological applications without training data or GPU infrastructure. The implementation is publicly available at https://github.com/Gitinc/argus

cs.CV↗

arXiv2026

ILPU: Iterative Laplace-Based Phase Unwrapping via Bi-Level Optimization

Phase unwrapping is an essential preprocessing step for phase-based MRI applications, including susceptibility mapping, field mapping, thermometry, and MR elastography. We present Iterative Laplace-Based Phase Unwrapping (ILPU), a bi-level optimization algorithm. In this method, a lower-level solver recovers a continuous phase increment from an incremental Poisson equation using the discrete cosine transform (DCT), while an upper-level solver refines an integer offset map through quality-guided spatial regularization and a restricted local search. This coupling enables robust unwrapping in low-SNR regions through adaptive smoothness penalties and quality-weighted regularization. We evaluated ILPU on 2D and 3D brain MRI phase images against manually unwrapped reference data, using standard Laplace unwrapping, Flynn, and SEGUE as comparison methods. In 2D, ILPU achieves accuracy comparable to SEGUE. In 3D, ILPU attains a relative error of 2.12% compared with 67.59% for SEGUE and 81.02% for Laplace, demonstrating a clear advantage in volumetric unwrapping. The algorithm has O(N log N) complexity per iteration through DCT-based Laplacian estimation and is numerically faster than both Flynn and SEGUE while preserving superior accuracy. These results indicate that the bi-level optimization framework provides a robust and computationally efficient solution for phase unwrapping in MRI.

math.OC↗

arXiv2026

Simulation Platform To Evaluate Inversion Techniques For Magnetic Resonance Elastography Data

Magnetic Resonance Elastography (MRE) has become an essential tool in assessing the mechanical properties of soft tissues in-vivo, prompting significant progress in new inversion algorithms. This creates a need for a benchmarking framework to promote uniformity and accessibility. To address this, we introduce a comprehensive in-silico dataset acquired by solving the forward Finite Element calculations of shear wave propagation in a linear visco-elastic material. This dataset aims to serve as a platform for evaluating inversion schemes by providing data that can be used as input with known mechanical properties to these methods. It includes simulations on homogeneous cuboidal domains of varying spatial and temporal resolution, and an extension to more physiological variations, including material inhomogeneity and internal arterial pulsation. We present a comprehensive case study using simulated data as an input to a direct inversion (DI) scheme, which allows for an expedient local inversion into the underlying material parameters. When aiming to reconstruct the parameters describing the linear visco-elastic material behavior via DI, we find that due to compromised convergence properties of frequency-domain stencils, stemming from truncation and subtractive cancellation errors, the reconstruction accuracy depends non-monotonically on the spatial and temporal resolution of the measurement grid. For inhomogeneous domains, the reconstruction was successful with notable interface boundaries. In the presence of pressurized vascular inclusions, a general stiffening of the domain was noted, as the recovered shear modulus was higher than the one assumed in forward modeling. Our study highlights the potential of this dataset as a vital benchmarking tool for advancing the development and refinement of MRE techniques, contributing to more accurate and reliable assessment of soft tissue mechanics.

math.NA↗

arXiv2026

Crossover Frequency as a Model-Independent Viscoelastic Constant for Soft Tissue Biomechanics

Magnetic resonance elastography (MRE) and related elastography techniques are emerging as quantitative diagnostic tools for assessing tissue microstructure and pathology. To determine descriptive parameters of the tissues' properties, a frequency-dependent viscoelastic material model is required, which is calibrated to the measured response in a parameter identification process. However, the selection of this model and the fitting strategy is challenging, since it may influence the identified viscoelastic parameters notably. Here, we address this limitation by proposing the crossover frequency (fc, defined as the frequency at which storage and loss moduli intersect G'(fc) = G''(fc)) as a model-independent viscoelastic constant for soft tissues. Fresh porcine specimens of the corona radiata, the putamen, the thalamus, and the liver were investigated using tabletop MRE and the frequency-dependent viscoelasticity was characterized with a fractional Kelvin-Voigt model. By validating the crossover frequency against the viscoelastic parameters, we demonstrated that the crossover frequency accurately reflects the viscoelastic behavior, independent of the material model or the fitting strategy. Across all samples, fc distinguished brain regions and separated brain from liver tissue by median frequencies of 85Hz (95% CI: 69-269Hz) in the corona radiata, 423Hz (95% CI: 316-575Hz) in the putamen, 426Hz (95% CI: 302-601Hz) in the thalamus and 1174Hz (95% CI: 1074-1300Hz) in the liver (p<0.001). These results suggest that crossover frequencies capture distinct viscoelastic fingerprints without requiring viscoelastic model selection. The crossover frequency may therefore serve as a practical, model-independent biomaterial constant to improve comparability of viscoelastic measurements across elastography studies.

physics.med-ph↗

arXiv2025

In Vivo Quantification of Glioma-Induced Solid Stress Using MR Elastography and Deformable Image Registration

Solid stress is increasingly being recognized as a key driver of tumor progression and aggressiveness, yet it has not been directly measured in patients so far. Here, we combine multifrequency magnetic resonance elastography with 3D magnetic resonance imaging (MRI)-based diffeomorphic deformable image registration network analysis to noninvasively quantify glioma-induced solid stress. In both a mouse model and patients, we identified spatially heterogeneous deformation patterns extending well beyond tumor margins. While deformation magnitude was not found to correlate with tumor size or clinical outcome, excess solid stress - defined as the product of peritumoral volumetric strain and stiffness differential between unaffected brain and peritumoral tissue - was inversely associated with patient survival, highlighting its potential as a quantitative, imaging-derived biomarker. To our knowledge, this study provides the first direct quantification of mechanical stress in patients with glioma.

physics.med-ph↗

arXiv2025

In Vivo Wideband MR Elastography for Assessing Age-Related Viscoelastic Changes of the Human Brain

Magnetic Resonance Elastography (MRE) noninvasively maps brain biomechanics and is highly sensitive to alterations associated with aging and neurodegenerative disease. Most implementations use a single frequency or a narrow frequency band, limiting the analysis of frequency-dependent viscoelastic parameters. We developed a dual-actuator wideband MRE (5-50 Hz) protocol and acquired wavefields at 13 frequencies in 24 healthy adults (young: 23-39 years; older: 50-63 years). Shear wave speed (SWS) maps were generated as a proxy for stiffness, and SWS dispersion was modeled using Newtonian, Kelvin-Voigt, and power-law rheological models. Whole-brain stiffness declined with age, with the strongest effect observed at low frequencies (5-16 Hz: -0.24%/year; p=0.019) compared with mid (20-35 Hz: -0.12%/year; p=0.030) and high frequencies (40-50 Hz: -0.10%/year; p=0.165). Compared to older brains, younger adults showed 14.3% higher baseline stiffness in the power-law model (p=0.001) and 8.5-9.0% higher viscosity according to the Newtonian and Kelvin-Voigt model (p<0.05). White and cortical gray matter exhibited similar age-related decreases, while deep gray matter showed an increase in the power-law exponent (+0.001/year; p=0.036), suggesting a transition toward more fluid-like properties associated with aging. Wideband MRE revealed frequency-dependent and region-specific biomechanical alterations with aging, with the strongest effects observed at low frequencies. Extending brain MRE into the low frequency regime potentially enhances sensitivity to solid-fluid interactions. Therefore, low frequency MRE may serve as an early biomechanical marker of microstructural brain changes due to aging and neurodegeneration.

physics.med-ph↗

arXiv2025

Technical recommendation on multiplex MR elastography for tomographic mapping of abdominal stiffness with a focus on the pancreas and pancreatic ductal adenocarcinoma

Objectives: MR elastography (MRE) offers valuable mechanical tissue characterization, however, in deep abdominal organs like the pancreas conventional single-driver, single-frequency approaches often fail. This study evaluates whether multiplex MRE using multiple drivers and vibration frequencies can overcome these limitations. Methods: This study used single-shot spin-echo MRE in 18 healthy volunteers targeting the liver, pancreas, kidneys, and spleen. Each healthy volunteer underwent 16 MRE examinations with different sets of four vibration frequencies (30-60 Hz) and four driver combinations, and an additional null experiment without vibrations. Further, a cohort of 14 patients with pancreatic ductal adenocarcinoma (PDAC) were retrospectively assessed. The quality of shear-wave fields and stiffness maps was assessed by displacement amplitudes and image sharpness. Results: In healthy volunteers, abdominal coverage with displacement amplitudes above the pre-determined noise level of 4 {\mu}m varied between MRE configurations: 24.2% ([0.0%-56.2%], single-driver, 60 Hz), 66.9% ([24.8%-97.7%], single-driver, 30-60 Hz), 70.2% ([0.0%-92.5%], multi-driver, 60 Hz) and 99.9% ([89.4%-100%], multi-driver, 30-60 Hz). In the pancreas, >60% coverage was achieved in all subjects using four drivers and multiple frequencies. This was achieved in only 2/18 subjects using single-driver/single-frequency MRE. Patients with PDAC had 99.1% [91.4%-100%] coverage in the pancreas and 96.3% [63.1%-100%] abdominal coverage (multi-driver, 30-60 Hz). Conclusion: MRE with four drivers and multiple vibration frequencies between 30-60 Hz enables tomographic mapping of tissue stiffness across the entire abdomen, including the pancreas. Multiplex MRE offers a promising approach for generating detailed images of abdominal stiffness, potentially enhancing clinical diagnostics for abdominal and pancreatic diseases.

physics.med-ph↗

arXiv2024

Time-Harmonic Optical Flow with Applications in Elastography

In this paper, we propose mathematical models for reconstructing the optical flow in time-harmonic elastography. In this image acquisition technique, the object undergoes a special time-harmonic oscillation with known frequency so that only the spatially varying amplitude of the velocity field has to be determined. This allows for a simpler multi-frame optical flow analysis using Fourier analytic tools in time. We propose three variational optical flow models and show how their minimization can be tackled via Fourier transform in time. Numerical examples with synthetic as well as real-world data demonstrate the benefits of our approach. Keywords: optical flow, elastography, Fourier transform, iteratively reweighted least squares, Horn--Schunck method

math.NA↗

arXiv2023

Optical time-harmonic elastography for multiscale stiffness mapping across the phylogenetic tree

Rapid mapping of the mechanical properties of soft biological tissues from light microscopy to macroscopic imaging could transform fundamental biophysical research by providing clinical biomarkers to complement in vivo elastography. We here introduce superfast optical time-harmonic elastography (OTHE) to remotely encode surface and subsurface shear wave fields for generating maps of tissue stiffness with unprecedented detail resolution. OTHE rigorously exploits the space-time propagation characteristics of time-harmonic waves to address current limitations of biomechanical imaging and elastography. Key solutions are presented for stimulation, encoding, and stiffness reconstruction of time-harmonic, multifrequency shear waves, all tuned to provide consistent stiffness values across resolutions from microns to millimeters. OTHE's versatility is demonstrated in Bacillus subtilis biofilms, zebrafish embryos, adult zebrafish, and human skeletal muscle, reflecting the diversity of the phylogenetic tree from a mechanics perspective. By zooming in on stiffness details from coarse to finer scales, OTHE advances developmental biology and offers a way to perform biomechanics-based tissue histology that consistently matches in vivo time-harmonic elastography in patients.

physics.bio-ph↗

arXiv2022

Displacement and pressure reconstruction from magnetic resonance elastography images: application to an in silico brain model

Magnetic resonance elastography is a motion-sensitive image modality that allows to measure in vivo tissue displacement fields in response to mechanical excitations. This paper investigates a data assimilation approach for reconstructing tissue displacement and pressure fields in an in silico brain model from partial elastography data. The data assimilation is based on a parametrized-background data weak methodology, in which the state of the physical system -- tissue displacements and pressure fields -- is reconstructed from the available data assuming an underlying poroelastic biomechanics model. For this purpose, a physics-informed manifold is built by sampling the space of parameters describing the tissue model close to their physiological ranges to simulate the corresponding poroelastic problem, and computing a reduced basis via Proper Orthogonal Decomposition. Displacements and pressure reconstruction is sought in a reduced space after solving a minimization problem that encompasses both the structure of the reduced-order model and the available measurements. The proposed pipeline is validated using synthetic data obtained after simulating the poroelastic mechanics of a physiological brain. The numerical experiments demonstrate that the framework can exhibit accurate joint reconstructions of both displacement and pressure fields. The methodology can be formulated for an arbitrary resolution of available displacement data from pertinent images.

math.NA↗

arXiv2021

Liquid-liver phantom: mimicking the viscoelastic dispersion of human liver for elastography in ultrasound and MRI

Different clinical elastography devices show different liver-stiffness values in the same subject, hindering comparison of values and establishment of system-independent thresholds for disease detection. Therefore, authorities request standardized phantoms that address the viscosity-related dispersion of stiffness over frequency. A linear polymerized polyacrylamide phantom (PAAm) was calibrated to the viscoelastic properties of healthy human liver in vivo. Shear-wave speed as a surrogate of stiffness was quantified between 5 Hz and 3000 Hz frequency-range by shear rheometry, ultrasound-based time-harmonic elastography, clinical MR elastography (MRE), and tabletop MRE. Imaging parameters for ultrasound were close to those of liver in vivo. Reproducibility, aging behavior and temperature dependency were assessed and fulfilled requirements for quantitative elastography. In addition, the phantom was used to characterize the frequency bandwidth of shear-wave speed of several clinical elastography methods. The liquid-liver phantom has favorable properties for standardization and development of liver elastography: first, it can be used across clinical and experimental elastography devices in ultrasound and MRI. Second, being a liquid, it can easily be adapted in size and shape to specific technical requirements, and by adding inclusions and scatterers. Finally, since the phantom is based on non-crosslinked linear PAA constituents, it is easy to produce, indicating potential widespread use among researchers and vendors to standardize liver-stiffness measurements.

physics.bio-ph↗

arXiv2021

Fully automated quantification of in vivo viscoelasticity of prostate zones using magnetic resonance elastography with Dense U-net segmentation

Magnetic resonance elastography (MRE) for measuring viscoelasticity heavily depends on proper tissue segmentation, especially in heterogeneous organs such as the prostate. Using trained network-based image segmentation, we investigated if MRE data suffice to extract anatomical and viscoelastic information for automatic tabulation of zonal mechanical properties of the prostate. Overall, 40 patients with benign prostatic hyperplasia (BPH) or prostate cancer (PCa) were examined with three magnetic resonance imaging (MRI) sequences: T2-weighted MRI (T2w), diffusion-weighted imaging (DWI), and MRE-based tomoelastography yielding six independent sets of imaging data per patient (T2w, DWI, apparent diffusion coefficient (ADC), MRE magnitude, shear wave speed, and loss angle maps). Combinations of these data were used to train Dense U-nets with manually segmented masks of the entire prostate gland (PG), central zone (CZ), and peripheral zone (PZ) in 30 patients and to validate them in 10 patients. Dice score (DS), sensitivity, specificity, and Hausdorff distance were determined. We found that segmentation based on MRE magnitude maps alone (DS, PG: 0.93$\pm$0.04, CZ: 0.95$\pm$0.03, PZ: 0.77$\pm$0.05) was more accurate than magnitude maps combined with T2w and DWI_b (DS, PG: 0.91$\pm$0.04, CZ: 0.91$\pm$0.06, PZ: 0.63$\pm$0.16) or T2w alone (DS, PG: 0.92$\pm$0.03, CZ: 0.91$\pm$0.04, PZ: 0.65$\pm$0.08). Automatically tabulated MRE values were not different from ground-truth values (P>0.05). In conclusion: MRE combined with Dense U-net segmentation allows tabulation of quantitative imaging markers without manual analysis and independent of other MRI sequences and can thus contribute to PCa detection and classification.

eess.IV↗