Plane-Wave Imaging Improves Single-Track Location Shear Wave Elasticity Imaging

Shear wave elastography can stratify rectal cancer response to short-course radiation therapy

Rectal cancer is a deadly disease typically treated using neoadjuvant chemoradiotherapy followed by total mesorectal excision surgery. To reduce the occurrence of mesorectal excision surgery for patients whose tumors regress from the neoadjuvant therapy alone, conventional imaging, such as computed tomography (CT) or magnetic resonance imaging (MRI), is used to assess tumor response to neoadjuvant therapy before surgery. In this work, we hypothesize that shear wave elastography offers valuable insights into tumor response to short-course radiation therapy (SCRT)-information that could help distinguish radiation-responsive from radiation-non-responsive tumors and shed light on changes in the tumor microenvironment that may affect radiation response. To test this hypothesis, we performed elastographic imaging on murine rectal tumors (n = 32) on days 6, 10, 12, 16, 18, 20, 23, and 25 post-tumor cell injection. The study revealed that radiation-responsive and non-radiation-responsive tumors had different mechanical properties. Specifically, radiation-non-responsive tumors showed significantly higher shear wave speed SWS (p < 0.01) than radiation-responsive tumors 11 days after SCRT. Furthermore, there was a significant difference in shear wave attenuation (SWA) (p < 0.01) in radiation-non-responsive tumors 16 days after SCRT compared to SWA measured just one day after SCRT. These results demonstrate the potential of shear wave elastography to provide valuable insights into tumor response to SCRT and aid in exploring the underlying biology that drives tumors' responses to radiation.

Evaluating Variability of Commercial Liver Fibrosis Elastography Phantoms

OBJECTIVE

Liver fibrosis has been found to increase the mechanical stiffness of the liver. To mimic different stages of liver fibrosis, commercially available phantoms (Model 039, CIRS, Inc.) have been produced for clinical quality assurance and research purposes. The purpose of this study was to investigate the mechanical property variability of the phantoms in two lots of CIRS Model 039 phantoms.

METHODS

Each lot consisted of phantoms of four stiffness types, and there were 8-10 phantoms of each type. Shear wave elastography measurements were conducted on each phantom at 10 different angles. Group velocity measurements and phase velocity curves were calculated for every SWE acquisition. Multilevel functional principal component analysis (MFPCA) was performed on phase velocity data, which decomposes each phase velocity curve into the sum of eigenfunctions of two levels. The variance of the component scores of levels 1 and 2 were used to represent inter-phantom and intra-phantom variability, respectively. The 95% confidence intervals of phase velocity in a phantom type were calculated to reflect curve variability.

DISCUSSION

The standard deviations of the group velocity for phantoms of any type were less than 0.04 and 0.02 m/s for lots 1 and 2, respectively. For both lots, in every type, the phase velocity curves of most individual phantoms fall within the 95% confidence interval.

CONCLUSION

MFPCA is an effective tool for analyzing the inter- and intra-phantom variability of phase velocity curves. Given the known variability of a fully tested lot, estimation of the variability of a new lot can be performed with a reduced number of phantoms tested.

A New Estimation Scheme for Improving the Performance of Shear Wave Elasticity Imaging

Shear wave velocity (SWV) reconstruction based on time-of-flight (TOF) is widely adopted to realize shear wave elasticity imaging (SWEI). It typically breaks down the reconstruction of a SWV image into many kernels and treats them independently. We hypothesized that information exchange among kernels improves the performance of SWEI. Therefore, we propose the approach of iterative re-weighted least squares based on inter-kernel communication (IKC-IRLS). We also hypothesized that time-to-peak (TTP) is superior to cross-correlation (CC) in visualizing small targets because TTP uses higher shear wave frequencies than CC. To examine the hypotheses, IKC-IRLS was combined with TTP data and compared with four established methods. The five methods were tested by imaging several small-size stiff targets (2.5, 4.0 and 6.4 mm in diameter) using different kernel sizes in the simulation and real experiments. The results indicate that the IKC-IRLS approach can mitigate speckle noise and is robust to TTP outliers. Consequently, the proposed method achieves the highest contrast-to-noise ratio and the lowest mean absolute percentage error of target in almost all tested cases.

Imaging the Local Nonlinear Viscoelastic Properties of Soft Tissues: Initial Validation and Expected Benefits

Imaging tissue mechanical properties has shown promise in noninvasive assessment of numerous pathologies. Researchers have successfully measured many linear tissue mechanical properties in laboratory and clinical settings. Currently, multiple complex mechanical effects such as frequency-dependence, anisotropy, and nonlinearity are being investigated separately. However, a concurrent assessment of these complex effects may enable more complete characterization of tissue biomechanics and offer improved diagnostic sensitivity. In this work, we report for the first time a method to map the frequency-dependent nonlinear parameters of soft tissues on a local scale. We recently developed a nonlinear elastography model that combines strain measurements from arbitrary tissue compression with radiation-force-based broadband shear wave speed (WS) measurements. Here, we extended this model to incorporate local measurements of frequency-dependent shear modulus. This combined approach provides a local frequency-dependent nonlinear parameter that can be obtained with arbitrary, clinically realizable tissue compression. Initial assessments using simulations and phantoms validate the accuracy of this approach. We also observed improved contrast in nonlinearity parameter at higher frequencies. Results from ex-vivo liver experiments show 32, 25, 34, and 38 dB higher contrast in elastograms than traditional linear elasticity, elastic nonlinearity, viscosity, and strain imaging methods, respectively. A lesion, artificially created by injection of glutaraldehyde into a liver specimen, showed a 59% increase in the frequency-dependent nonlinear parameter and a 17% increase in contrast ratio.

Plantar Soft Tissue Characterization Using Reverberant Shear Wave Elastography: A Proof-of-Concept Study

Plantar soft tissue stiffness provides relevant information on biomechanical characteristics of the foot. Therefore, appropriate monitoring of foot elasticity could be useful for diagnosis, treatment or health care of people with complex pathologies such as a diabetic foot. In this work, the reliability of reverberant shear wave elastography (RSWE) applied to plantar soft tissue was investigated. Shear wave speed (SWS) measurements were estimated at the plantar soft tissue at the first metatarsal head, the third metatarsal head and the heel from both feet in five healthy volunteers. Experiments were repeated for a test-retest analysis with and without the use of gel pad using a mechanical excitation frequency range between 400 and 600 Hz. Statistical analysis was performed to evaluate the reliability of the SWS estimations. In addition, the results were compared against those obtained with a commercially available shear wave-based elastography technique, supersonic imaging (SSI). The results indicate a low coefficient of variation for test-retest experiments with gel pad (median: 5.59%) and without gel pad (median: 5.83%). Additionally, the values of the SWS measurements increase at higher frequencies (median values: 2.11 m/s at 400 Hz, 2.16 m/s at 450 Hz, 2.24 m/s at 500 Hz, 2.21 m/s at 550 Hz and 2.31 m/s at 600 Hz), consistent with previous reports at lower frequencies. The SWSs at the plantar soft tissue at the first metatarsal head, third metatarsal head and heel were found be significantly (p<0.05) different, with median values of 2.42, 2.16 and 2.03 m/s, respectively which indicates the ability of the method to differentiate between shear wave speeds at different anatomical locations. The results indicated better elastographic signal-to-noise ratios with RSWE compared to SSI because of the artifacts presented in the SWS generation. These preliminary results indicate that the RSWE approach can be used to estimate the plantar soft tissue elasticity, which may have great potential to better evaluate changes in biomechanical characteristics of the foot.

Shear Wave Velocity Estimation Using the Real-Time Curve Tracing Method in Ultrasound Elastography

The estimation of shear wave velocity is very important in ultrasonic shear wave elasticity imaging (SWEI). Since the stability and accuracy of ultrasonic testing equipment have been greatly improved, in order to further improve the accuracy of shear wave velocity estimation and increase the quality of shear wave elasticity maps, we propose a novel real-time curve tracing (RTCT) technique to accurately reconstruct the motion trace of shear wave fronts. Based on the curve fitting of each frame shear wave, the propagation velocity of two-dimensional shear waves can be estimated. In this paper, shear wave velocity estimation and shear wave image reconstruction are implemented for homogeneous regions and stiff spherical inclusion regions with different elasticity, respectively. The experimental result shows that the proposed shear wave velocity estimation method based on the real-time curve tracing method has advantages in accuracy and anti-noise performance. Moreover, by eliminating artifacts of shear wave videos, the velocity map acquired can restore the shape of inclusions better. The real-time curve tracing method can provide a new idea for the estimation of shear wave velocity and elastic parameters.

DSWE-Net: A deep learning approach for shear wave elastography and lesion segmentation using single push acoustic radiation force

Ultrasound-based non-invasive elasticity imaging modalities have received significant consideration for tissue characterization over the last few years. Though substantial advances have been made, the conventional Shear Wave Elastography (SWE) methods still suffer from poor image quality in regions far from the push location, particularly those which rely on single focused ultrasound push beam to generate shear waves. In this study, we propose DSWE-Net, a novel deep learning-based approach that is able to construct Young's modulus maps from ultrasonically tracked tissue velocity data resulting from a single acoustic radiation force (ARF) push. The proposed network employs a 3D convolutional encoder, followed by a recurrent block consisting of several Convolutional Long Short-Term Memory (ConvLSTM) layers to extract high-level spatio-temporal features from different time-frames of the input velocity data. Finally, a pair of coupled 2D convolutional decoder blocks reconstructs the modulus image and additionally performs inclusion segmentation by generating a binary mask. We also propose a multi-task learning loss function for end-to-end training of the network with 1260 data samples obtained from a simulation environment which include both bi-level and multi-level phantom structures. The performance of the proposed network is evaluated on 140 synthetic test data and the results are compared both qualitatively and quantitatively with that of the current state of the art method, Local Phase Velocity Based Imaging (LPVI). With an average SSIM of 0.90, RMSE of 0.10 and 20.69 dB PSNR, DSWE-Net performs much better on the imaging task compared to LPVI. Our method also achieves an average IoU score of 0.81 for the segmentation task which makes it suitable for localizing inclusions as well. In this initial study, we also show that our method gains an overall improvement of 0.09 in SSIM, 4.81 dB in PSNR, 2.02 dB in CNR, and 0.09 in RMSE over LPVI on a completely unseen set of CIRS tissue mimicking phantom data. This proves its better generalization capability and shows its potential for use in real-world clinical practice.

H-scan, Shear Wave and Bioluminescent Assessment of the Progression of Pancreatic Cancer Metastases in the Liver

The non-invasive quantification of tumor burden and the response to therapies remain an important objective for imaging modalities. To characterize the performance of two newly optimized ultrasound-based analyses, we applied shear wave and H-scan scattering analyses to repeated trans-abdominal ultrasound scans of a murine model of metastatic pancreatic cancer. In addition, bioluminescence measurements were obtained as an alternative reference. The tumor metastases grow aggressively and result in death at approximately 4 wk if untreated, but longer for those treated with chemotherapy. We found that our three imaging methods (shear wave speed, H-scan, bioluminescence) trended toward increasing output measures with time during tumor growth, and these measures were delayed for the group receiving chemotherapy. The relative sensitivity of H-scan tracked closely with bioluminescence measurements, particularly in the early to mid-stages of tumor growth. The correlation between H-scan and bioluminescence was found to be strong, with a Spearman's rank correlation coefficient greater than 0.7 across the entire series. These preliminary results suggest that non-invasive ultrasound imaging analyses are capable of tracking the response of tumor models to therapeutic agents.

Shear Induced Non-Linear Elasticity Imaging: Elastography for Compound Deformations

The goal of non-linear ultrasound elastography is to characterize tissue mechanical properties under finite deformations. Existing methods produce high contrast non-linear elastograms under conditions of pure uni-axial compression, but exhibit bias errors of 10-50% when the applied deformation deviates from the uni-axial condition. Since freehand transducer motion generally does not produce pure uniaxial compression, a motion-agnostic non-linearity estimator is desirable for clinical translation. Here we derive an expression for measurement of the Non-Linear Shear Modulus (NLSM) of tissue subject to combined shear and axial deformations. This method gives consistent nonlinear elasticity estimates irrespective of the type of applied deformation, with a reduced bias in NLSM values to 6-13%. The method combines quasi-static strain imaging with Single-Track Location-Shear Wave Elastography (STL-SWEI) to generate local estimates of axial strain, shear strain, and Shear Wave Speed (SWS). These local values were registered and non-linear elastograms reconstructed with a novel nonlinear shear modulus estimation scheme for general deformations. Results on tissue mimicking phantoms were validated with mechanical measurements and multiphysics simulations for all deformation types with an error in NLSM of 6-13%. Quantitative performance metrics with the new compound-motion tracking strategy reveal a 10-15 dB improvement in Signal-to-Noise Ratio (SNR) for simple shear versus pure compressive deformation for NLSM elastograms of homogeneous phantoms. Similarly, the Contrast-to-Noise Ratio (CNR) of NLSM elastograms of inclusion phantoms improved by 25-30% for simple shear over pure uni-axial compression. Our results show that high fidelity NLSM estimates may be obtained at ~30% lower strain under conditions of shear deformation as opposed axial compression. The reduction in strain required could reduce sonographer effort and improve scan safety.

Parallel Receive Beamforming Improves the Performance of Focused Transmit-Based Single-Track Location Shear Wave Elastography

Single-track location shear wave elastography (STL-SWEI) is robust against speckle-induced noise in shear wave speed (SWS) estimates; however, it is not immune to other incoherent sources of noise (such as electronic noise) that increases the variance in SWS estimates. Although estimation averaging enabled by parallel receive beamforming adequately suppresses these noise sources, these beamforming techniques often rely on broad transmit beams (plane or diverging). While broad beam approaches, such as plane-wave imaging, are becoming ubiquitous in research ultrasound systems, clinical systems usually employ focused transmit beams due to compatibility with hardware beamforming and deeper penetration. Consequently, improving the noise robustness of focused transmit-based STL-SWEI may enable easier translation to clinical scenarios. In this article, we experimentally evaluated the performance of parallel beamforming for STL-SWEI using fixed or multiple transmit focus. By imaging tissue-mimicking phantoms, we found that parallel beamforming improved the focal zone elastographic signal-to-noise ratio (SNR_e) by 40.9%. For a receive line spacing equivalent to transducer pitch, averaging estimates from three parallel lines produced peak SNR_e at the focal zone (25 mm), while, at the shallower regions (< 20 mm), a larger number of parallel lines (>7) were needed. Increasing the beamforming line density by a factor of 8 increased the focal zone SNR_e only by 13.2%. When SWS quantification was desirable at a fixed depth (such as within the push focal depth), using a deeper tracking focal zone enabled higher parallel line count and improved the peak SNR_e by 33%. The multifocusing strategy produced a lower SNR_e than the single-focus configurations. For a fixed tracking focal zone, a depth-dependent averaging based on the simulated transmit intensity adequately accounted for the transmit beamwidth. The results in this work demonstrated that STL-SWEI can be implemented using focused transmit beams with robust noise-suppression capability.

A parametric evaluation of shear wave speeds estimated with time-of-flight calculations in viscoelastic media

Shear wave elasticity imaging (SWEI) uses an acoustic radiation force to generate shear waves, and then soft tissue mechanical properties are obtained by analyzing the shear wave data. In SWEI, the shear wave speed is often estimated with time-of-flight (TOF) calculations. To characterize the errors produced by TOF calculations, three-dimensional (3D) simulated shear waves are described by time-domain Green's functions for a Kelvin-Voigt model evaluated for multiple combinations of the shear elasticity and the shear viscosity. Estimated shear wave speeds are obtained from cross correlations and time-to-peak (TTP) calculations applied to shear wave particle velocities and shear wave particle displacements. The results obtained from these 3D shear wave simulations indicate that TTP calculations applied to shear wave particle displacements yield effective estimates of the shear wave speed if noise is absent, but cross correlations applied to shear wave particle displacements are more robust when the effects of noise and shear viscosity are included. The results also show that shear wave speeds estimated with TTP methods and cross correlations using shear wave particle velocities are more sensitive to increases in shear viscosity and noise, which suggests that superior estimates of the shear wave speed are obtained from noiseless or noisy shear wave particle displacements.

A parametric evaluation of shear wave speeds estimated with time-of-flight calculations in viscoelastic media

Shear wave elasticity imaging (SWEI) uses an acoustic radiation force to generate shear waves, and then soft tissue mechanical properties are obtained by analyzing the shear wave data. In SWEI, the shear wave speed is often estimated with time-of-flight (TOF) calculations. To characterize the errors produced by TOF calculations, three-dimensional (3D) simulated shear waves are described by time-domain Green's functions for a Kelvin-Voigt model evaluated for multiple combinations of the shear elasticity and the shear viscosity. Estimated shear wave speeds are obtained from cross correlations and time-to-peak (TTP) calculations applied to shear wave particle velocities and shear wave particle displacements. The results obtained from these 3D shear wave simulations indicate that TTP calculations applied to shear wave particle displacements yield effective estimates of the shear wave speed if noise is absent, but cross correlations applied to shear wave particle displacements are more robust when the effects of noise and shear viscosity are included. The results also show that shear wave speeds estimated with TTP methods and cross correlations using shear wave particle velocities are more sensitive to increases in shear viscosity and noise, which suggests that superior estimates of the shear wave speed are obtained from noiseless or noisy shear wave particle displacements.

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.

Shear Wave Elastography Can Differentiate between Radiation-Responsive and Non-responsive Pancreatic Tumors: An ex Vivo Study with Murine Models

Neither contrast-enhanced computed tomography nor magnetic resonance imaging can monitor changes in the pancreatic ductal adenocarcinoma microenvironment during therapy. We hypothesized that shear wave elastography could overcome this limitation. To test this hypothesis, we measured the shear modulus of two groups of murine pancreatic tumors (KCKO, n = 30; PAN02, n = 30) treated with stereotactic body radiation therapy (SBRT). The mean shear modulus of KCKO tumors was 7.651 kPa higher than that of PAN02 tumors (p < 0.001). SBRT reduced the shear modulus in KCKO tumors by 8.914 kPa (p < 0.001). No significant difference in the shear modulus of SBRT-treated PAN02 tumors was observed. Additionally, necrotic and collagen densities were reduced only in the SBRT-treated KCKO tumors. Shear modulus was dependent on collagen distribution and histological texture parameters (i.e., entropy and fractional dimension). Shear wave elastography imaging differentiates between SBRT-responsive (KCKO) and non-responsive (PAN02) tumors.

Nonlinear Shear Modulus Estimation With Bi-Axial Motion Registered Local Strain

Nonlinear elasticity imaging provides additional information about tissue behavior that is potentially diagnostic and avoids errors inherent in applying a linear elastic model to tissue under large strains. Nonlinear elasticity imaging is challenging to perform due to the large deformations required to obtain sufficient tissue strain to elicit nonlinear behavior. This work uses a method of axial and lateral displacement tracking to estimate local axial strain with simultaneous measurement of shear modulus at multiple compression levels. By following the change in apparent shear modulus and the stress deduced from the strain maps, we are able to accurately quantify nonlinear shear modulus (NLSM). We have validated our technique with a mechanical NLSM measurement system. Our results demonstrate that 2-D tracking provides more consistent NLSM estimates than those obtained by 1-D (axial) tracking alone, especially where lateral motion is significant. The elastographic contrast-to-noise ratio in heterogeneous phantoms was 12.5%-60% higher using our method than that of 1-D tracking. Our method is less susceptible to mechanical variations, with deviations in mean elastic values of 2%-4% versus 5%-37% for 1-D tracking.

Distributing Synthetic Focusing Over Multiple Push-Detect Events Enhances Shear Wave Elasticity Imaging Performance

Plane wave (PW) imaging is a commonly used method for tracking waves during shear wave elasticity imaging (SWEI), but its unfocused transmission beam reduces tracking accuracy and precision. Coherent compounding minimizes this problem, but SWEI's stringent frame rate requirement and the coarse pitch of most clinical transducers limit its effectiveness. Synthetic aperture imaging (SAI) is an alternate ultrasound imaging approach with a much tighter focus than PW imaging, but its lower transmission power has deterred researchers from using SAI in SWEI. Hadamard-encoded multielement SAI can overcome this limitation. However, only a limited number of subapertures (3-5) can be transmitted in a single push-detect event. We have developed methods to distribute more subapertures or more compounding angles over multiple push-detect events. In this paper, we report the results of experiments conducted on phantoms to assess SWEI's performance when using Hadamard-encoded distributed-multielement synthetic aperture (HDMSA) imaging or distributed plane wave compounding (DPWC) to track shear waves. Tracking shear waves with HDMSA improved the elastographic signal-to-noise ratio (SNR_e) by 61.6%-89.5% depending on the phantom employed. Similarly, DPWC tracking improved SNR_e by 56.2%-93.3% for the same group of phantoms. Compared to focused ultrasound tracking (at the focus), SNR_e improved by 28.6% and 32.5% when tracking shear waves with HDMSA and DPWC, respectively. Long acquisitions could introduce decoding errors that decrease the performance when performing HDMSA tracking within the clinical setting. Nevertheless, the results of studies performed on the bicep muscle of three healthy volunteers demonstrate that for stationary organs, tracking shear waves with HDMSA yielded repeatable elastograms that offer better elastographic performance than those produced with current tracking methods.

Elastography Can Map the Local Inverse Relationship between Shear Modulus and Drug Delivery within the Pancreatic Ductal Adenocarcinoma Microenvironment

PURPOSE

High tissue pressure prevents chemotherapeutics from reaching the core of pancreatic tumors. Therefore, targeted therapies have been developed to reduce this pressure. While point probes have shown the effectiveness of these pressure-reducing therapies via single-location estimates, ultrasound elastography is now widely available as an imaging technique to provide real-time spatial maps of shear modulus (tissue stiffness). However, the relationship between shear modulus and the underlying tumor microenvironmental causes of high tissue pressure has not been investigated. In this work, elastography was used to investigate how shear modulus influences drug delivery in situ, and how it correlates with collagen density, hyaluronic acid content, and patent vessel density-features of the tumor microenvironment known to influence tissue pressure.

EXPERIMENTAL DESIGN

Intravenous injection of verteporfin, an approved human fluorescent drug, was used in two pancreatic cancer xenograft models [AsPC-1 (n = 25) and BxPC-3 (n = 25)].

RESULTS

Fluorescence intensity was higher in AsPC-1 tumors than in BxPC-3 tumors (P < 0.0001). Comparing drug uptake images and shear wave elastographic images with histologic images revealed that: (i) drug delivery and shear modulus were inversely related, (ii) shear modulus increased linearly with increasing collagen density, and (iii) shear modulus was marginally correlated with the local assessment of hyaluronic acid content.

CONCLUSIONS

These results demonstrate that elastography could guide targeted therapy and/or identify patients with highly elevated tissue pressure.See related commentary by Nia et al., p. 2024.