Technical Note: In vivo Young's modulus mapping of pancreatic ductal adenocarcinoma during HIFU ablation using harmonic motion elastography (HME)

Feasibility of Phase Velocity Imaging Using Multi Frequency Oscillation-Shear Wave Elastography

OBJECTIVE

To assess viscoelasticity, a pathologically relevant biomarker, shear wave elastography (SWE) generally uses phase velocity (PV) dispersion relationship generated via pulsed acoustic radiation force (ARF) excitation pulse. In this study, a multi-frequency oscillation (MFO)- excitation pulse with higher weight to higher frequencies is proposed to generate PV images via the generation of motion with energy concentrated at the target frequencies in contrast to the broadband frequency motion generated in pulsed SWE (PSWE).

METHODS

The feasibility of MFO-SWE to generate PV images at 100 to 1000 Hz in steps of 100 Hz was investigated by imaging 6 and 70 kPa inclusions with 6.5 and 10.4 mm diameter and ex vivo bovine liver with and without the presence of an aberration layer and chicken muscle ex vivo, and 4T1 mouse breast tumor, in vivo with comparisons to PSWE.

RESULTS

MFO-SWE-derived CNR was statistically higher than PSWE for 6 kPa (both with and without aberration) and 70 kPa (with aberration) inclusions and derived SNR of the liver was statistically higher than PSWE at higher frequency (600-1000 Hz). Quantitatively, at 600-1000 Hz, MFO-SWE improved CNR of inclusions (without and with) aberration on an average by (8.2 and 156)% and of the tumor by 122%, respectively, and improved SNR of the liver (without and with) aberration by (20.2 and 51.5)% and of chicken muscle by 72%, respectively compared to the PSWE.

CONCLUSIONS AND SIGNIFICANCE

These results indicate the advantages of MFO-SWE to improve PV estimation at higher frequencies which could improve viscoelasticity quantification and feature delineation.

Optimization of the Tracking Beam Sequence in Harmonic Motion Imaging

Harmonic motion imaging (HMI) is an ultrasound elastography technique that estimates the viscoelastic properties of tissues by inducing localized oscillatory motion using focused ultrasound (FUS). The resulting displacement, assumed to be inversely proportional to the tissue local stiffness, is estimated using an imaging array based on RF speckle tracking. In conventional HMI, this is accomplished with plane-wave (PW) imaging, which inherently suffers from low lateral resolution. Coherent PW compounding (PWC) leverages spatial and temporal resolution using synthetic focusing in transmit. In this study, we introduced focused imaging with parallel tracking in HMI and compared parallel tracking of various transmit F-numbers (F/2.6, 3, 4, and 5) qualitatively and quantitatively with PW and PWC imaging at various compounded angle ranges (6°, 12°, and 18°). An in silico model of a 56-kPa spherical inclusion (diameter: 3.6 mm) embedded in a 5.3-kPa background and a 5.3-kPa elastic phantom with cylindrical inclusions (Young's moduli: 22-56 kPa, diameters: 2.0-8.6 mm) were imaged to assess different tracking beam sequences. Speckle biasing in displacement estimation associated with parallel tracking was also investigated and concluded to be negligible in HMI. Parallel tracking in receive (Rx) resulted in 2%-7% and 8%-12% increase compared to PW imaging ( ) in HMI contrast and contrast-to-noise ratio in silico and phantoms. Focused imaging with parallel tracking in Rx was concluded to be most robust among PW and PWC imaging for displacement estimation, and its preclinical feasibility was demonstrated in postsurgical human cancerous breast tissue specimens and in vivo murine models of breast cancer.

Advances in bioengineering pancreatic tumor-stroma physiomimetic Biomodels

Pancreatic cancer exhibits a unique bioarchitecture and desmoplastic cancer-stoma interplay that governs disease progression, multi-resistance, and metastasis. Emulating the biological features and microenvironment heterogeneity of pancreatic cancer stroma in vitro is remarkably complex, yet highly desirable for advancing the discovery of innovative therapeutics. Diverse bioengineering approaches exploiting patient-derived organoids, cancer-on-a-chip platforms, and 3D bioprinted living constructs have been rapidly emerging in an endeavor to seamlessly recapitulate major tumor-stroma biodynamic interactions in a preclinical setting. Gathering on this, herein we showcase and discuss the most recent advances in bio-assembling pancreatic tumor-stroma models that mimic key disease hallmarks and its desmoplastic biosignature. A reverse engineering perspective of pancreatic tumor-stroma key elementary units is also provided and complemented by a detailed description of biodesign guidelines that are to be considered for improving 3D models physiomimetic features. This overview provides valuable examples and starting guidelines for researchers envisioning to engineer and characterize stroma-rich biomimetic tumor models. All in all, leveraging advanced bioengineering tools for capturing stromal heterogeneity and dynamics, opens new avenues toward generating more predictive and patient-personalized organotypic 3D in vitro platforms for screening transformative therapeutics targeting the tumor-stroma interplay.

Harmonic motion imaging of human breast masses: an in vivo clinical feasibility

Non-invasive diagnosis of breast cancer is still challenging due to the low specificity of the imaging modalities that calls for unnecessary biopsies. The diagnostic accuracy can be improved by assessing the breast tissue mechanical properties associated with pathological changes. Harmonic motion imaging (HMI) is an elasticity imaging technique that uses acoustic radiation force to evaluate the localized mechanical properties of the underlying tissue. Herein, we studied the in vivo feasibility of a clinical HMI system to differentiate breast tumors based on their relative HMI displacements, in human subjects. We performed HMI scans in 10 female subjects with breast masses: five benign and five malignant masses. Results revealed that both benign and malignant masses were stiffer than the surrounding tissues. However, malignant tumors underwent lower mean HMI displacement (1.1 ± 0.5 µm) compared to benign tumors (3.6 ± 1.5 µm) and the adjacent non-cancerous tissue (6.4 ± 2.5 µm), which allowed to differentiate between tumor types. Additionally, the excised breast specimens of the same patients (n = 5) were imaged post-surgically, where there was an excellent agreement between the in vivo and ex vivo findings, confirmed with histology. Higher displacement contrast between cancerous and non-cancerous tissue was found ex vivo, potentially due to the lower nonlinearity in the elastic properties of ex vivo tissue. This preliminary study lays the foundation for the potential complementary application of HMI in clinical practice in conjunction with the B-mode to classify suspicious breast masses.

Preclinical Imaging Using Single Track Location Shear Wave Elastography: Monitoring the Progression of Murine Pancreatic Tumor Liver Metastasis In Vivo

Recently, researchers have discovered the direct impact of the tumor mechanical environment on the growth, drug uptake and prognosis of tumors. While estimating the mechanical parameters (solid stress, fluid pressure, stiffness) can aid in the treatment planning and monitoring, most of these parameters cannot be quantified noninvasively. Shear wave elastography (SWE) has shown promise as a means of noninvasively measuring the stiffness of soft tissue. However, stiffness is still not a recognized imaging biomarker. While SWE has been shown to be capable of measuring tumor stiffness in humans, much important research is done in small animal preclinical models, where tumors are often too small for the resolution of traditional SWE tools. Single-track location SWE (STL-SWE) has previously been shown to overcome the fundamental resolution limit of SWE imposed by ultrasound speckle, which may make it suitable for preclinical imaging. Using STL-SWE, in this work, we demonstrate, for the first time, that the stiffness changes occurring inside metastatic murine pancreatic tumors can be monitored over long time scales (up to 9 weeks). To prevent the respiration motion from degrading the STL-SWE estimates, we developed a real-time software-based respiration gating scheme that we implemented on a Verasonics ultrasound imaging system. By imaging the liver of three healthy mice and performing correlation analysis, we confirmed that the respiration-gated STL-SWE data was free from motion corruption. By performing coregistered power-doppler imaging, we found that the local variability in liver shear wave speed (SWS) measurements increased from 5.4% to 9.9% due to blood flow. We performed a longitudinal study using a murine model of pancreatic cancer liver metastasis to assess the temporal changes (over nine weeks) in SWS in two groups: a controlled group receiving no treatment (n=8), and an experimental group (n=6) treated with Gemcitabine, a chemotherapy agent. We independently evaluated tumor burden using bioluminescence imaging (BLI). The initial and endpoint SWS measurements were statistically different (p<0.05). Additionally, when the liver SWS exceeded 2.5 ± 0.3 and 2.73 ± 0.34 m/s in untreated and treated mice, respectively, the death of the mice was imminent within approximately 10 days. The time taken for the SWS to exceed the thresholds was 17 days (on average) longer in Gemcitabine treated mice compared to the untreated ones. The survival statistics corroborated the effectiveness of Gemcitabine. Spearman correlation analysis revealed a monotonic relationship between SWE measurements (SWS) and BLI measurements (radiance) for tumors whose radiance exceeded 1×10⁷ photons/s/cm²/sr. Longitudinal measurements on the liver of four healthy mice revealed a maximum coefficient of variation of 11.4%. The results of this investigation demonstrate that with appropriate gating, researchers can use STL-SWE for small animal imaging and perform longitudinal studies using preclinical cancer models.

Noninvasive Young's modulus visualization of fibrosis progression and delineation of pancreatic ductal adenocarcinoma (PDAC) tumors using Harmonic Motion Elastography (HME) in vivo

Background and aims: Poor specificity and predictive values of current cross-sectional radiological imaging methods in evaluation of pancreatic adenocarcinoma (PDAC) limit the clinical capability to accurately stage the tumor pre-operatively and provide optimal surgical treatment and improve patient outcomes.

Methods: In this study, we applied Harmonic Motion Elastography (HME), a quantitative ultrasound-based imaging method to calculate Young's modulus (YM) in PDAC mouse models (n = 30) and human pancreatic resection specimens of PDAC (n=32). We compared the YM to the collagen assessment by Picrosirius red (PSR) stain on corresponding histologic sections.

Results: HME is capable of differentiating between different levels of fibrosis in transgenic mice. In mice without pancreatic fibrosis, the measured YM was 4.2 ± 1.3 kPa, in fibrotic murine pancreata, YM was 5.5 ± 2.0 kPa and in murine PDAC tumors, YM was 11.3 ± 1.7 kPa. The corresponding PSR values were 2.0 ± 0.8 %, 9.8 ± 3.4 %, and 13.2 ± 1.2%, respectively. In addition, three regions within each human surgical PDAC specimen were assessed: tumor, which had both the highest Young's modulus (YM > 40 kPa) and collagen density (PSR > 40 %); non-neoplastic adjacent pancreas, which had the lowest Young's modulus (YM < 15 kPa) and collagen density (PSR < 10%) and a transitional peri-lesional region between the tumor and non-neoplastic pancreas with an intermediate value of measured Young's modulus (15 kPa < YM < 40 kPa) and collagen density (15% < PSR < 35 %).

Conclusion: In conclusion, a non-invasive, quantitative imaging tool for detecting, staging and delineating PDAC tumor margins based on the change in collagen density was developed.