ABSTRACT
Hemodynamic functional ultrasound imaging (fUS) of neural activity provides a unique combination of spatial coverage, spatiotemporal resolution and compatibility with freely moving animals. However, deep and transcranial monitoring of brain activity and the imaging of dynamics in slow-flowing blood vessels remains challenging. To enhance fUS capabilities, we introduce biomolecular hemodynamic enhancers based on gas vesicles (GVs), genetically encodable ultrasound contrast agents derived from buoyant photosynthetic microorganisms. We show that intravenously infused GVs enhance ultrafast Doppler ultrasound contrast and visually-evoked hemodynamic contrast in transcranial fUS of the mouse brain. This hemodynamic contrast enhancement is smoother than that provided by conventional microbubbles, allowing GVs to more reliably amplify neuroimaging signals.
Subject(s)
Brain/diagnostic imaging , Contrast Media , Functional Neuroimaging/methods , Hemodynamics , Image Enhancement/methods , Microbubbles , Ultrasonography, Doppler, Transcranial/methods , Animals , Contrast Media/administration & dosage , Functional Neuroimaging/standards , Image Enhancement/standards , Male , Mice , Mice, Inbred C57BL , Photic Stimulation , Reproducibility of Results , Ultrasonography, Doppler, Transcranial/standardsABSTRACT
High-intensity Focused Ultrasound (HIFU) is a promising treatment modality for a wide range of pathologies including prostate cancer. However, the lack of a reliable ultrasound-based monitoring technique limits its clinical use. Ultrasound currently provides real-time HIFU planning, but its use for monitoring is usually limited to detecting the backscatter increase resulting from chaotic bubble appearance. HIFU has been shown to generate stiffening in various tissues, so elastography is an interesting lead for ablation monitoring. However, the standard techniques usually require the generation of a controlled push which can be problematic in deeper organs. Passive elastography offers a potential alternative as it uses the physiological wave field to estimate the elasticity in tissues and not an external perturbation. This technique was adapted to process B-mode images acquired with a clinical system. It was first shown to faithfully assess elasticity in calibrated phantoms. The technique was then implemented on the Focal One® clinical system to evaluate its capacity to detect HIFU lesions in vitro (CNR = 9.2 dB) showing its independence regarding the bubbles resulting from HIFU and in vivo where the physiological wave field was successfully used to detect and delineate lesions of different sizes in porcine liver. Finally, the technique was performed for the very first time in four prostate cancer patients showing strong variation in elasticity before and after HIFU treatment (average variation of 33.0 ± 16.0 % ). Passive elastography has shown evidence of its potential to monitor HIFU treatment and thus help spread its use.
Subject(s)
Elasticity Imaging Techniques , High-Intensity Focused Ultrasound Ablation , Prostatic Neoplasms , Male , Humans , Animals , Swine , Elasticity Imaging Techniques/methods , Ultrasonography , Liver/diagnostic imaging , Liver/surgery , Phantoms, Imaging , Prostatic Neoplasms/diagnostic imaging , Prostatic Neoplasms/surgery , High-Intensity Focused Ultrasound Ablation/methodsABSTRACT
The majority of disease processes involves changes in the micro-structure of the affected tissue, which can translate to changes in the mechanical properties of the corresponding tissue. Harmonic motion imaging (HMI) is an elasticity imaging technique that allows the study of the mechanical parameters of tissue by detecting the tissue response by a harmonic motion field, which is generated by oscillatory acoustic radiation force. HMI has been demonstrated in tumor detection and characterization as well as monitoring of ablation procedures. In this study, an analytical HMI model is demonstrated and compared with a finite element model (FEM), allowing rapid and accurate computation of the displacement, strain, and shear wave velocity (SWV) at any location in a homogenous linear elastic material. Average absolute differences between the analytical model and the FEM were respectively 1.2% for the displacements and 0.5% for the strains for 41 940 force voxels at 0.22 s per displacement evaluation. A convergence study showed that the average difference could be further decreased to 1.0% and 0.15% for the displacements and strains, respectively, if force resolution is increased. SWV fields, as calculated with the FEM and the analytical model, have regional differences in velocities up to 0.57 m s-1with an average absolute difference of 0.11 ± 0.07 m s-1, primarily due to imperfections in the non-reflecting FEM boundary conditions. The apparent SWV differed from the commonly used plane-wave approximation by up to 1.2 m s-1due to near and intermediate field effects. Maximum displacement amplitudes for a model with an inclusion stabilize within 10% of the homogenous model at an inclusion radius of 10 mm while the maximum strain reacts faster, stabilizing at an inclusion radius of 3 mm. In conclusion, an analytical model for HMI stiffness estimation is presented in this paper. The analytical model has advantages over FEM as the full-field displacements do not need to be calculated to evaluate the model at a single measurement point. This advantage, together with the computational speed, makes the analytical model useful for real-time imaging applications. However, the analytical model was found to have restrictive assumptions on tissue homogeneity and infinite dimensions, while the FEM approaches were shown adaptable to variable geometry and non-homogenous properties.
Subject(s)
Elasticity Imaging Techniques , Ultrasonics/methods , Elasticity Imaging Techniques/methods , MotionABSTRACT
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.
Subject(s)
Carcinoma, Pancreatic Ductal/diagnostic imaging , Elastic Modulus , Elasticity Imaging Techniques/methods , Pancreas , Pancreatic Neoplasms/diagnostic imaging , Adult , Aged , Aged, 80 and over , Animals , Disease Progression , Female , Fibrosis/diagnostic imaging , Humans , Male , Mice , Middle Aged , Neoplasm Staging , Pancreas/diagnostic imaging , Pancreas/pathologyABSTRACT
PURPOSE: Pancreatic ductal adenocarcinoma (PDA) is a common, deadly cancer that is challenging both to diagnose and to manage. Its hallmark is an expansive, desmoplastic stroma characterized by high mechanical stiffness. In this study, we sought to leverage this feature of PDA for two purposes: differential diagnosis and monitoring of response to treatment. EXPERIMENTAL DESIGN: Harmonic motion imaging (HMI) is a functional ultrasound technique that yields a quantitative relative measurement of stiffness suitable for comparisons between individuals and over time. We used HMI to quantify pancreatic stiffness in mouse models of pancreatitis and PDA as well as in a series of freshly resected human pancreatic cancer specimens. RESULTS: In mice, we learned that stiffness increased during progression from preneoplasia to adenocarcinoma and also effectively distinguished PDA from several forms of pancreatitis. In human specimens, the distinction of tumors versus adjacent pancreatitis or normal pancreas tissue was even more stark. Moreover, in both mice and humans, stiffness increased in proportion to tumor size, indicating that tuning of mechanical stiffness is an ongoing process during tumor progression. Finally, using a brca2-mutant mouse model of PDA that is sensitive to cisplatin, we found that tissue stiffness decreases when tumors respond successfully to chemotherapy. Consistent with this observation, we found that tumor tissues from patients who had undergone neoadjuvant therapy were less stiff than those of untreated patients. CONCLUSIONS: These findings support further development of HMI for clinical applications in disease staging and treatment response assessment in PDA.
Subject(s)
Elasticity Imaging Techniques/methods , Pancreatic Neoplasms/drug therapy , Pancreatic Neoplasms/pathology , Phantoms, Imaging , Signal Processing, Computer-Assisted/instrumentation , Ultrasonography/methods , Aged , Aged, 80 and over , Animals , Diagnosis, Differential , Disease Models, Animal , Female , Humans , Male , Mice , Mice, Inbred BALB C , Mice, Transgenic , Middle Aged , Motion , Neoplasm Staging , Pancreatic Neoplasms/diagnostic imaging , Treatment OutcomeABSTRACT
Angiogenesis, the formation of new vessels, is one of the key mechanisms in tumor development and an appealing target for therapy. Non-invasive, high-resolution, high-sensitivity, quantitative 3-D imaging techniques are required to correctly depict tumor heterogeneous vasculature over time. Ultrafast Doppler was recently introduced and provides an unprecedented combination of resolution, penetration depth and sensitivity without requiring any contrast agents. The technique was further extended to three dimensions with ultrafast Doppler tomography (UFD-T). In this work, UFD-T was applied to the monitoring of tumor angiogenesis in vivo, providing structural and functional information at different stages of development. UFD-T volume renderings revealed that our murine model's vasculature stems from pre-existing vessels and sprouts to perfuse the whole volume as the tumor grows until a critical size is reached. Then, as the network becomes insufficient, the tumor core is no longer irrigated because the vasculature is concentrated mainly in the periphery. In addition to spatial distribution and growth patterns, UFD-T allowed a quantitative analysis of vessel size and length, revealing that the diameter distribution of vessels remained relatively constant throughout tumor growth. The network is dominated by small vessels at all stages of tumor development, with more than 74% of the vessels less than 200 µm in diameter. This study also found that cumulative vessel length is more closely related to tumor radius than volume, indicating that the vascularization becomes insufficient when a critical mass is reached. UFD-T was also compared with dynamic contrast-enhanced ultrasound and found to provide complementary information regarding the link between structure and perfusion. In conclusion, UFD-T is capable of in vivo quantitative assessment of the development of tumor vasculature (vessels with blood speed >1 mm/s [sensitivity limit] assessed with a resolution limit of 80 µm) in 3 dimensions. The technique has very interesting potential as a tool for treatment monitoring, response assessment and treatment planning for optimal drug efficiency.
Subject(s)
Imaging, Three-Dimensional/methods , Neoplasms/blood supply , Neoplasms/diagnostic imaging , Neovascularization, Pathologic/diagnostic imaging , Tomography, X-Ray Computed/methods , Ultrasonography, Doppler/methods , Animals , Disease Models, Animal , Mice , Multimodal Imaging/methodsABSTRACT
Harmonic motion imaging (HMI) is a radiation-force-based ultrasound elasticity imaging technique, which is designed for both tissue relative stiffness imaging and reliable high-intensity focused ultrasound treatment monitoring. The objective of this letter is to develop and demonstrate the feasibility of 2-D focused ultrasound (FUS) beam steering for HMI using a 93-element, FUS phased array. HMI with steered FUS beam was acquired in tissue-mimicking phantoms. The HMI displacement was imaged within the steering range of ±1.7 mm laterally and ±2 mm axially. Using the steered FUS beam, HMI can be used to image a larger tissue volume with higher efficiency and without requiring mechanical movement of the transducer.
Subject(s)
Elasticity Imaging Techniques/methods , Ultrasonography, Interventional/methods , Biomechanical Phenomena , Humans , Models, Biological , Phantoms, Imaging , TransducersABSTRACT
PURPOSE: Noninvasive quantitative assessment of coagulated tissue during high-intensity focused ultrasound (HIFU) ablation is one of the essential steps for tumor treatment, especially in such cases as the Pancreatic Ductal Adenocarcinoma (PDA) that has low probability of diagnosis at the early stages and high probability of forming solid carcinomas resistant to chemotherapy treatment at the late stages. METHODS: Harmonic motion elastography (HME) is a technique for the localized estimation of tumor stiffness. This harmonic motion imaging (HMI)-based technique is designed to map the tissue Young's modulus or stiffness noninvasively. A focused ultrasound (FUS) transducer generates an oscillating, acoustic radiation force in its focal region. The two-dimensional (2D) shear wave speed, and consequently the Young's modulus maps, is generated by tracking the radio frequency (RF) signals acquired at high frame rates. By prolonging the sonication for more than 50 s using the same methodology, the 2D Young's modulus maps are reconstructed while HIFU is applied and ablation is formed on PDA murine tumors. RESULTS: The feasibility of this technique in measuring the regional Young's modulus was first assessed in tissue-mimicking phantoms. The contrast-to-noise ratio (CNR) was found to be higher than 11.7 dB for each 2D reconstructed Young's modulus map. The mean error in this validation study was found to be equal to less than 19%. Then HME was applied on two transgenic mice with pancreatic ductal adenocarcinoma tumors. The Young's modulus median value of this tumor at the start of the HIFU application was equal to 2.1 kPa while after 45 s of sonication it was found to be approximately three times stiffer (6.7 kPa). CONCLUSIONS: The HME was described herein and showed its capability of measuring tissue stiffness noninvasively by measuring the shear wave speed propagation inside the tissue and reconstructing a 2D Young's modulus map. Application of the methodology in vivo and during HIFU were thus reported here for the first time.
Subject(s)
Adenocarcinoma/diagnostic imaging , Adenocarcinoma/therapy , Elastic Modulus , Elasticity Imaging Techniques , High-Intensity Focused Ultrasound Ablation , Pancreatic Neoplasms/diagnostic imaging , Pancreatic Neoplasms/therapy , Animals , Mice , Phantoms, ImagingABSTRACT
The successful clinical application of high intensity focused ultrasound (HIFU) ablation depends on reliable monitoring of the lesion formation. Harmonic motion imaging guided focused ultrasound (HMIgFUS) is an ultrasound-based elasticity imaging technique, which monitors HIFU ablation based on the stiffness change of the tissue instead of the echo intensity change in conventional B-mode monitoring, rendering it potentially more sensitive to lesion development. Our group has shown that predicting the lesion location based on the radiation force-excited region is feasible during HMIgFUS. In this study, the feasibility of a fast lesion mapping method is explored to directly monitor the lesion map during HIFU. The harmonic motion imaging (HMI) lesion map was generated by subtracting the reference HMI image from the present HMI peak-to-peak displacement map, as streamed on the computer display. The dimensions of the HMIgFUS lesions were compared against gross pathology. Excellent agreement was found between the lesion depth (r 2 = 0.81, slope = 0.90), width (r 2 = 0.85, slope = 1.12) and area (r 2 = 0.58, slope = 0.75). In vivo feasibility was assessed in a mouse with a pancreatic tumor. These findings demonstrate that HMIgFUS can successfully map thermal lesions and monitor lesion development in real time in vitro and in vivo. The HMIgFUS technique may therefore constitute a novel clinical tool for HIFU treatment monitoring.
Subject(s)
Elasticity Imaging Techniques/methods , High-Intensity Focused Ultrasound Ablation/methods , Radiotherapy, Image-Guided/methods , Animals , Mice , Pancreatic Neoplasms/diagnostic imaging , Pancreatic Neoplasms/radiotherapyABSTRACT
Longitudinal imaging techniques are needed that can meaningfully probe the tumor microenvironment and its spatial heterogeneity. Contrast-enhanced ultrasound, shear wave elastography and quantitative ultrasound are ultrasound-based techniques that provide information on the vascular function and micro-/macroscopic tissue structure. Modifications of the tumor microenvironment induced by cytotoxic and anti-angiogenic molecules in ectopic murine Lewis lung carcinoma tumors were monitored. The most heterogenous structures were found in tumors treated with anti-angiogenic drug that simultaneously accumulated the highest levels of necrosis and fibrosis. The anti-angiogenic group presented the highest number of correlations between parameters related to vascular function and those related to the micro-/macrostructure of the tumor microenvironment. Results suggest how patterns of multiparametric ultrasound modifications can be related to provide a more insightful marker of changes occurring within tumors during therapy.
Subject(s)
Lung Neoplasms/diagnostic imaging , Lung Neoplasms/drug therapy , Ultrasonography/methods , Angiogenesis Inhibitors/therapeutic use , Animals , Contrast Media , Cyclophosphamide/therapeutic use , Cytotoxins/therapeutic use , Disease Models, Animal , Elasticity Imaging Techniques , Image Enhancement/methods , Lung/diagnostic imaging , Male , Mice , Mice, Inbred C57BLABSTRACT
PURPOSE: Sensitivity of contrast-enhanced ultrasound (CEUS) to microvascular flow modifications can be limited by intra-injection variability (injected dose, rate, volume). PROCEDURES: To evaluate the effect of injection variability on microvascular flow evaluation, CEUS was compared between controlled and manual injections where enhancement was assessed in vitro within a flow phantom, in normal murine kidney (N = 12) and in murine ectopic tumors (N = 10). RESULTS: For both in vitro and in vivo measurements in the renal cortex, controlled injections significantly improved reproducibility of functional parameter estimation. Their coefficient of variation (CV) in the renal cortex ranged from 4 to 19 % for controlled injection vs. 5 to 43 % for manual injections. For measurements in tumors, controlled injection only decreased the CV significantly for the mean transit time. In tumors, multiple injections of contrast agent with a 15-min delay between each were shown to strongly modify contrast uptake by facilitating penetration of microbubbles. CONCLUSION: Improved reproducibility of CEUS assessments in murine models should provide more robust quantification of flow parameters and more sensitive evaluation of tumor modifications in therapeutic models.
Subject(s)
Contrast Media/chemistry , Ultrasonics/methods , Animals , Cell Line, Tumor , Injections , Kidney Cortex/pathology , Mice , Reproducibility of ResultsABSTRACT
Recently, ultrasonic imaging of soft tissue mechanics has been increasingly studied to image otherwise undetectable pathologies. However, many underlying mechanisms of tissue stiffening remain unknown, requiring small animal studies and adapted elasticity mapping techniques. Harmonic motion imaging (HMI) assesses tissue viscoelasticity by inducing localized oscillation from a periodic acoustic radiation force. The objective of this study was to evaluate the feasibility of HMI for in vivo elasticity mapping of abdominal organs in small animals. Pathological cases, i.e. chronic pancreatitis and pancreatic cancer, were also studied in vivo to assess the capability of HMI for detection of the change in mechanical properties. A 4.5 MHz focused ultrasound transducer (FUS) generated an amplitude-modulated beam resulting in 50 Hz harmonic tissue oscillations at its focus. Axial tissue displacement was estimated using 1D-cross-correlation of RF signals acquired with a 7.8 MHz diagnostic transducer confocally aligned with the FUS. In vitro results in canine liver and kidney showed the correlation between HMI displacement and Young's moduli measured by rheometry compression testing. HMI was capable of providing reproducible elasticity maps of the mouse abdominal region in vivo allowing the identification of, from stiffest to softest, the murine kidney, pancreas, liver, and spleen. Finally, pancreata affected by pancreatitis and pancreatic cancer showed HMI displacements 1.7 and 2.2 times lower than in the control case, respectively, indicating higher stiffness. The HMI displacement amplitude was correlated with the extent of fibrosis as well as detecting the very onset of stiffening even before fibrosis could be detected on H&E. This work shows that HMI can produce reliable elasticity maps of mouse abdominal region in vivo, thus providing a potentially critical tool to assess pathologies affecting organ elasticity.
Subject(s)
Abdomen/diagnostic imaging , Elasticity Imaging Techniques/methods , Animals , Dogs , Elastic Modulus , Elasticity Imaging Techniques/instrumentation , Kidney/diagnostic imaging , Liver/diagnostic imaging , Lower Gastrointestinal Tract/diagnostic imaging , Mice , Motion , TransducersABSTRACT
Harmonic Motion Imaging for Focused Ultrasound (HMIFU) is a technique that can perform and monitor high-intensity focused ultrasound (HIFU) ablation. An oscillatory motion is generated at the focus of a 93-element and 4.5 MHz center frequency HIFU transducer by applying a 25 Hz amplitude-modulated signal using a function generator. A 64-element and 2.5 MHz imaging transducer with 68kPa peak pressure is confocally placed at the center of the HIFU transducer to acquire the radio-frequency (RF) channel data. In this protocol, real-time monitoring of thermal ablation using HIFU with an acoustic power of 7 W on canine livers in vitro is described. HIFU treatment is applied on the tissue during 2 min and the ablated region is imaged in real-time using diverging or plane wave imaging up to 1,000 frames/second. The matrix of RF channel data is multiplied by a sparse matrix for image reconstruction. The reconstructed field of view is of 90° for diverging wave and 20 mm for plane wave imaging and the data are sampled at 80 MHz. The reconstruction is performed on a Graphical Processing Unit (GPU) in order to image in real-time at a 4.5 display frame rate. 1-D normalized cross-correlation of the reconstructed RF data is used to estimate axial displacements in the focal region. The magnitude of the peak-to-peak displacement at the focal depth decreases during the thermal ablation which denotes stiffening of the tissue due to the formation of a lesion. The displacement signal-to-noise ratio (SNRd) at the focal area for plane wave was 1.4 times higher than for diverging wave showing that plane wave imaging appears to produce better displacement maps quality for HMIFU than diverging wave imaging.
Subject(s)
High-Intensity Focused Ultrasound Ablation/methods , Liver/surgery , Acoustics , Animals , Computer Systems , Dogs , In Vitro Techniques , Liver/diagnostic imaging , Male , Transducers , Ultrasonography, Interventional/methodsABSTRACT
The aim of this study was to evaluate the capacity of BR55, an ultrasound contrast agent specifically targeting vascular endothelial growth factor receptor 2 (VEGFR2), to distinguish the specific anti-VEGFR2 therapy effect of sunitinib from other anti-angiogenic effects of a therapy (imatinib) that does not directly inhibit VEGFR2. Sunitinib, imatinib and placebo were administered daily for 11 d (264 h) to 45 BalbC mice bearing ectopic CT26 murine colorectal carcinomas. During the course of therapy, B-mode ultrasound, contrast-enhanced ultrasound and VEGFR2-targeted contrast-enhanced ultrasound were performed to assess tumor morphology, vascularization and VEGFR2 expression, respectively. The angiogenic effects on these three aspects were characterized using tumor volume, contrast-enhanced area and differential targeted enhancement. Necrosis, microvasculature and expression of VEGFR2 were also determined by histology and immunostaining. B-Mode imaging revealed that tumor growth was significantly decreased in sunitinib-treated mice at day 11 (p < 0.05), whereas imatinib did not affect growth. Functional evaluation revealed that the contrast-enhanced area decreased significantly (p < 0.02) and by similar amounts under both anti-angiogenic treatments by day 8 (192 h): -23% for imatinib and -21% for sunitinib. No significant decrease was observed in the placebo group. Targeted contrast-enhanced imaging revealed lower differential targeted enhancement, that is, lower levels of VEGFR2 expression, in sunitinib-treated mice relative to placebo-treated mice from 24 h (p < 0.05) and relative to both placebo- and imatinib-treated mice from 48 h (p < 0.05). Histologic assessment of tumors after the final imaging indicated that necrotic area was significantly higher for the sunitinib group (21%) than for the placebo (8%, p < 0.001) and imatinib (11%, p < 0.05) groups. VEGFR2-targeted ultrasound was able to sensitively differentiate the anti-VEGFR2 effect from the reduced area of tumor with functional flow produced by both anti-angiogenic agents. BR55 molecular imaging was, thus, able both to detect early therapeutic response to sunitinib in CT26 tumors as soon as 24 h after the beginning of the treatment and to provide early discrimination (48 h) between tumor response during anti-angiogenic therapy targeting VEGFR2 expression and response during anti-angiogenic therapy not directly acting on this receptor.
Subject(s)
Angiogenesis Inhibitors/administration & dosage , Contrast Media/pharmacokinetics , Neoplasms, Experimental/diagnostic imaging , Neoplasms, Experimental/drug therapy , Ultrasonography/methods , Vascular Endothelial Growth Factor Receptor-2/metabolism , Animals , Cell Line, Tumor , Cell Survival/drug effects , Drug Monitoring/methods , Female , Imatinib Mesylate/administration & dosage , Indoles/administration & dosage , Mice , Mice, Inbred BALB C , Molecular Imaging/methods , Neoplasms, Experimental/metabolism , Pyrroles/administration & dosage , Reproducibility of Results , Sensitivity and Specificity , Sunitinib , Treatment Outcome , Vascular Endothelial Growth Factor Receptor-2/antagonists & inhibitorsABSTRACT
Harmonic motion imaging (HMI) is a radiationforce- based elasticity imaging technique that tracks oscillatory tissue displacements induced by sinusoidal ultrasonic radiation force to assess the resulting oscillatory displacement denoting the underlying tissue stiffness. The objective of this study was to evaluate the feasibility of HMI in pancreatic tumor detection and high-intensity focused ultrasound (HIFU) treatment monitoring. The HMI system consisted of a focused ultrasound transducer, which generated sinusoidal radiation force to induce oscillatory tissue motion at 50 Hz, and a diagnostic ultrasound transducer, which detected the axial tissue displacements based on acquired radio-frequency signals using a 1-D cross-correlation algorithm. For pancreatic tumor detection, HMI images were generated for pancreatic tumors in transgenic mice and normal pancreases in wild-type mice. The obtained HMI images showed a high contrast between normal and malignant pancreases with an average peak-to-peak HMI displacement ratio of 3.2. Histological analysis showed that no tissue damage was associated with HMI when it was used for the sole purpose of elasticity imaging. For pancreatic tumor ablation monitoring, the focused ultrasound transducer was operated at a higher acoustic power and longer pulse length than that used in tumor detection to simultaneously induce HIFU thermal ablation and oscillatory tissue displacements, allowing HMI monitoring without interrupting tumor ablation. HMI monitoring of HIFU ablation found significant decreases in the peak-to-peak HMI displacements before and after HIFU ablation with a reduction rate ranging from 15.8% to 57.0%. The formation of thermal lesions after HIFU exposure was confirmed by histological analysis. This study demonstrated the feasibility of HMI in abdominal tumor detection and HIFU ablation monitoring.
Subject(s)
High-Intensity Focused Ultrasound Ablation/methods , Image Processing, Computer-Assisted/methods , Pancreatic Neoplasms/diagnostic imaging , Pancreatic Neoplasms/therapy , Animals , Feasibility Studies , Mice , Mice, Transgenic , Signal Processing, Computer-Assisted , UltrasonographyABSTRACT
Perfusion parameter estimation from dynamic contrast-enhanced ultrasound (DCE-US) data relies on fitting parametric models of flow to curves describing linear echo power as a function of time. The least squares criterion is generally used to fit these models to data. This criterion is optimal in the sense of maximum likelihood under the assumption of an additive white Gaussian noise. In the current work, it is demonstrated that this assumption is not held for DCEUS. A better-adapted maximum likelihood criterion based on a multiplicative model is proposed. It is tested on simulated bolus perfusion data and on 11 sequences acquired in vivo during bolus perfusion of contrast agent in the cortex of healthy murine kidney, an area where the perfusion is expected to be approximately homogeneous. Results on simulated data show a significant improvement (p < 0.05) of the precision and the accuracy for the estimations of perfusion parameters time to peak (TTP), wash-in rate (WiR), and mean transit time (MTT). On the 11 in vivo sequences, the new method leads to a significant reduction (p < 0.05) in the variation of parametric maps for 9 sequences for TTP and 10 sequences for WiR and MTT. The mean percent decreases of the coefficient of variation are 40%, 25%, and 59% for TTP, WiR, and MTT, respectively. This method should contribute to a more robust and accurate estimation of perfusion parameters and an improved resolution of parametric imaging.
Subject(s)
Contrast Media/chemistry , Image Processing, Computer-Assisted/methods , Ultrasonography/methods , Animals , Computer Simulation , Kidney/diagnostic imaging , Least-Squares Analysis , Mice , Phospholipids/chemistry , Reproducibility of Results , Sulfur Hexafluoride/chemistryABSTRACT
Ultrasound (US) scanners typically apply lossy, non-linear modifications to the US data for visualization purposes. The resulting images are then stored as compressed video data. Some system manufacturers provide dedicated software for quantification purposes to eliminate such processing distortions, at least partially. This is currently the recommended approach for quantitatively assessing changes in contrast-agent concentration from clinical data. However, the machine-specific access to US data and the limited set of analysis functionalities offered by each dedicated-software package make it difficult to perform comparable analyses with different US systems. The objective of this work was to establish if linearization of compressed video images obtained with an arbitrary US system can provide an alternative to dedicated-software analysis of machine-specific files for the estimation of echo-power. For this purpose, an Aplio 50 system (Toshiba Medical Systems, Tochigi, Japan), coupled with dedicated CHI-Q (Contrast Harmonic Imaging Quantification) software by Toshiba Medical Systems, was used. Results were compared with two approaches that apply algorithms to estimate relative echo-power from compressed video images: commercially available VueBox software by Bracco Suisse SA (Geneva, Switzerland) and in-laboratory software called PixPower. The echo-power estimated by CHI-Q analysis indicated a strong linear relationship versus agent concentration in vitro (R(2) ≥ 0.9996) for dynamic range (DR) settings of DR60 and DR80, with slopes between 9.22 and 9.57 dB/decade (p = 0.05). These values approach the theoretically predicted dependence of 10.0 dB/decade (equivalent to 3 dB for each concentration doubling). Echo-power estimations obtained from compressed video images with VueBox and PixPower also exhibited strong linear proportionality with concentration (R(2) ≥ 0.9996), with slopes between 9.30 and 9.68 dB/decade (p = 0.05). On an independent in vivo data set (N = 24), the difference in echo-power estimation between CHI-Q and each of the other two approaches was calculated after excluding regions that contain pixels affected by saturated or thresholded pixel values. The mean difference in estimates (expressed in decibels) was -0.25 dB between VueBox and CHI-Q (95% confidence interval: -0.75 to 0.26 dB) and -0.17 dB between PixPower and CHI-Q (95% confidence interval: -0.67 to 0.13 dB). To achieve linearization of data, one of the approaches (VueBox) requires calibration files provided by the software manufacturer for each machine type and setting. The other (PixPower) requires empirical correction of the imaging dynamic range based on ground truth data. These requirements could potentially be removed if US system manufacturers were willing to make relevant information on the applied processing publically available. Reliable echo-power estimation from linearized data would facilitate inclusion of different US systems in multicentric studies and more widespread implementation of emerging techniques for quantitative analysis of contrast ultrasound.