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

Abstract

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.

Fig. 1:

(a) Illustrating a respiration-gated pSTL-SWE sequence. Each push-detect ensemble, consisting of a push beam followed by a compounded plane wave tracking, is initiated following the inhalation and exhalation of the animal. From one push-detect to the next, the push line is laterally translated. (b) Flowchart illustrates the repiration triggering technique implemented on the Verasonics. (c) Representative repiration profile used to calibrate for the motion triggerring threshold parameters. The lowest amplitude reduction of NCC (dotted red line) was used as the threshold for detecting the beginning of a respiration cycle (T₁). The mean NCC during the quiet zones was used as the threshold for detecting quiet zones (T₂).

Fig. 2:

(a) Graphical illustration of the imaging system. (b)-(d) The system with a mouse, without a mouse, and during imaging, respectively.

Fig. 3:

Respiration rate analysis on three mice at different anesthetic levels using B-mode cross-correlation. Motion due to inhalation and exhalation appeared as reductions in temporal NCC profiles. Increasing the anesthetic level decreased the respiration rate and increased the duration of quiet zones in respiration cycles. Plots (g)-(i) are reproduced in (j)-(l), respectively, with a smaller y-axis range to visualize the variation in NCC within the quiet zones.

Fig. 4:

Illustrating the presence of motion in the SWE data from three free-breathing mice. The NCC profile was computed by performing cross-correlation between the first tracking frame (in B-mode form) of a motion-free push-detect ensemble (marked with a red circle) and the first frames of the remaining push-detect ensembles. The gated acquisitions exhibited smooth decay in the NCC profiles while the gating-free acquisitons exhibited reductions in temporal NCC. The push-detect ensembles with low NCC were identified (marked with red arrows) and used to isolate the corresponding motion-corrupted columns in the SWS maps (in Figure 5).

Fig. 5:

Elastograms of the livers of three mice obtained using pSTL-SWE without repiration gating and with respiration gating. Images in (a)-(r) correspond to the SWE acquisitions shown in Figure 4 (a)-(r), respectively. Images were obtained using 2%, 3%, and 4% isoflurane. For each mouse, the images were acquired from a fixed cross-section within the liver. The columns in the elastograms that were reconstructed from the motion-corrupted push-detect events (from Figure 4) are indicated with red vertical arrows.

Fig. 6:

Shows the results of repeated acquisitions from three mice. B-modes, power doppler images and pSTL-SWE elastograms are shown for three mice in (a)-(u). To evaluate temporal variability, two ROIs were selected for each mouse: one within a relatively vessel-free region and one containing strong PD signal. The white arrows indicate the ROIs. The mean SWS within these ROIs over three acquisitions are shown in (v)-(x) for Mouse 1–3, respectively.

Fig. 7:

B-mode and overlaid SWS maps for an untreated mouse at all observed time points up to demise. The black vertical lines indicate the push beam transmission region that was used to facilitate the selection of the ROI during the imaging session. The white lines that were manually traced from the B-mode images indicate the liver region used in the statistical analysis.

Fig. 8:

B-mode and overlaid SWS maps for a mouse treated with Gemcitabine at all observed time points up to demise. The black vertical lines indicate the push beam transmission region that was used to facilitate the selection of the ROI during the imaging session. The white lines that were manually traced from the B-mode images indicate the liver region used in the statistical analysis.

Fig. 9:

(a) B-mode and overlaid elastogram of a primary tumor. (b) the correponding B-mode and elastogram obtained from the liver of the same mouse.

Fig. 10:

Radiance maps obtained from BLI overlaid on the photographs of the animals at two time points. Images were generated the by the Living Image software (ParkinElmer Inc., Waltham, MA) used to operate the IVIS Spectrum system. The red circles indicate the ROIs used to calculate the mean radiance.

Fig. 11:

Quantitative longitudinal measurements obtained from the untreated mice using pSTL-SWEI and BLI. Results show the SWS of the liver, SWS of primary tumors ((a) and (d) only) and radiance measured in the abdomen. In SWS measurements, the errorbar indicate the spatial standard deviation of SWS. The dotted vertical arrows indicate the time of death.

Fig. 12:

Quantitative longitudinal measurements obtained from the Gemcitabine treated mice using pSTL-SWEI and BLI. Results show the SWS of the liver, SWS of primary tumors ((c) and (d) only) and radiance measured in the abdomen. In SWS measurements, the errorbar indicate the spatial standard deviation of SWS. The dotted vertical arrows indicate the time of death. Mice corresponding to (i)-(k) were excluded from statistical analysis due to insufficient cell injection.

Fig. 13:

(a) SWS measured at the first timepoint (pre-treatment) and immediately before death for untreated and Gemcitabine treated mice. (b) shows the SWS_threshold computed as the mean of initial (mean of first three) and endpoint (mean of last three) SWS measurements for untreated and treated mice. (c) shows the time taken for the SWS measurements to exceed SWS_threshold values. (d) shows the duration over which the mice from both groups were alive once the SWS measurements exceeded SWS_threshold. (e) Survival statistics (n=10) shows that Gemcitabine prolonged the life of the mice.

Fig. 14:

Scatterplot showing the paired SWS and radiance measaurements obtained using pSTL-SWEI and BLI aggregated from all time points in 19 mice.

Fig. 15:

Longitudinal SWS measurements in healthy livers of four mice. Coefficient of variation (COV) of the measurements are indicated in the plot.