10 research outputs found
First-order statistical speckle models improve robustness and reproducibility of contrast-enhanced ultrasound perfusion estimates
Contrast-enhanced ultrasound (CEUS) permits the quantification and monitoring of adaptive tumor responses in the face of anti-angiogenic treatment, with the goal of informing targeted therapy. However, conventional CEUS image analysis relies on mean signal intensity as an estimate of tracer concentration in indicator-dilution modeling. This discounts additional information that may be available from the first-order speckle statistics in a CEUS image. Heterogeneous vascular networks, typical of tumor-induced angiogenesis, lead to heterogeneous contrast enhancement of the imaged tumor cross-section.
To address this, a linear (B-mode) processing approach was developed to quantify the change in the first-order speckle statistics of B-mode cine loops due to the incursion of microbubbles. The technique, named the EDoF (effective degrees of freedom) method, was developed on tumor bearing mice (MDA-MB-231LN mammary fat pad inoculation) and evaluated using nonlinear (two-pulse amplitude modulated) contrast microbubble-specific images. To improve the potential clinical applicability of the technique, a second-generation compound probability density function for the statistics of two-pulse amplitude modulated contrast-enhanced ultrasound images was developed. The compound technique was tested in an antiangiogenic drug trial (bevacizumab) on tumor bearing mice (MDA-MB-231LN), and evaluated with gold-standard histology and contrast-enhanced X-ray computed tomography. The compound statistical model could more accurately discriminate anti-VEGF treated tumors from untreated tumors than conventional CEUS image. The technique was then applied to a rapid patient-derived xenograft (PDX) model of renal cell carcinoma (RCC) in the chorioallantoic membrane (CAM) of chicken embryos. The ultimate goal of the PDX model is to screen RCC patients for de novo sunitinib resistance.
The analysis of the first-order speckle statistics of contrast-enhanced ultrasound cine loops provides more robust and reproducible estimates of tumor blood perfusion than conventional image analysis. Theoretically this form of analysis could quantify perfusion heterogeneity and provide estimates of vascular fractal dimension, but further work is required to determine what physiological features influence these measures. Treatment sensitivity matrices, which combine vascular measures from CEUS and power Doppler, may be suitable for screening of de novo sunitinib resistance in patients diagnosed with renal cell carcinoma. Further studies are required to assess whether this protocol can be predictive of patient outcome
High-level synthesis design of scalable ultrafast ultrasound beamformer with single FPGA
Ultrafast ultrasound imaging is essential for advanced ultrasound imaging
techniques such as ultrasound localization microscopy (ULM) and functional
ultrasound (fUS). Current ultrafast ultrasound imaging is challenged by the
ultrahigh data bandwidth associated with the radio frequency (RF) signal, and
by the latency of the computationally expensive beamforming process. As such,
continuous ultrafast data acquisition and beamforming remain elusive with
existing software beamformers based on CPUs or GPUs. To address these
challenges, the proposed work introduces a novel method of implementing an
ultrafast ultrasound beamformer specifically for ultrafast plane wave imaging
(PWI) on a field programmable gate array (FPGA) by using high-level synthesis.
A parallelized implementation of the beamformer on a single FPGA was proposed
by 1) utilizing a delay compression technique to reduce the delay profile size,
which enables both run-time pre-calculated delay profile loading from external
memory and delay reuse 2) vectorizing channel data fetching which is enabled by
delay reuse, and 3) using fixed summing networks to reduce consumption of logic
resources. Our proposed method presents two unique advantages over current FPGA
beamformers: 1) high scalability that allows fast adaptation to different FPGA
resources and beamforming speed demands by using Xilinx High-Level Synthesis as
the development tool, and 2) allow a compact form factor design by using a
single FPGA to complete the beamforming instead of multiple FPGAs. With the
proposed method, a sustainable average beamforming rate of 4.83 G
samples/second in terms of input raw RF sample was achieved. The resulting
image quality of the proposed beamformer was compared with the software
beamformer on the Verasonics Vantage system for both phantom imaging and in
vivo imaging of a mouse brain
Repurposing Albendazole: new potential as a chemotherapeutic agent with preferential activity against HPV-negative head and neck squamous cell cancer.
Albendazole is an anti-helminthic drug that has been shown to exhibit anti-cancer properties, however its activity in head and neck squamous cell cancer (HNSCC) was unknown. Using a series of in vitro assays, we assessed the ability of albendazole to inhibit proliferation in 20 HNSCC cell lines across a range of albendazole doses (1 nM-10 μM). Cell lines that responded to treatment were further examined for cell death, inhibition of migration and cell cycle arrest. Thirteen of fourteen human papillomavirus-negative HNSCC cell lines responded to albendazole, with an average IC50 of 152 nM. In contrast, only 3 of 6 human papillomavirus-positive HNSCC cell lines responded. Albendazole treatment resulted in apoptosis, inhibition of cell migration, cell cycle arrest in the G2/M phase and altered tubulin distribution. Normal control cells were not measurably affected by any dose tested. This study indicates that albendazole acts to inhibit the proliferation of human papillomavirus-negative HNSCC cell lines and thus warrants further study as a potential chemotherapeutic agent for patients suffering from head and neck cancer
Context-aware deep learning enables high-efficacy localization of high concentration microbubbles for super-resolution ultrasound localization microscopy
Abstract Ultrasound localization microscopy (ULM) enables deep tissue microvascular imaging by localizing and tracking intravenously injected microbubbles circulating in the bloodstream. However, conventional localization techniques require spatially isolated microbubbles, resulting in prolonged imaging time to obtain detailed microvascular maps. Here, we introduce LOcalization with Context Awareness (LOCA)-ULM, a deep learning-based microbubble simulation and localization pipeline designed to enhance localization performance in high microbubble concentrations. In silico, LOCA-ULM enhanced microbubble detection accuracy to 97.8% and reduced the missing rate to 23.8%, outperforming conventional and deep learning-based localization methods up to 17.4% in accuracy and 37.6% in missing rate reduction. In in vivo rat brain imaging, LOCA-ULM revealed dense cerebrovascular networks and spatially adjacent microvessels undetected by conventional ULM. We further demonstrate the superior localization performance of LOCA-ULM in functional ULM (fULM) where LOCA-ULM significantly increased the functional imaging sensitivity of fULM to hemodynamic responses invoked by whisker stimulations in the rat brain
Three-Dimensional Shear Wave Elastography Using a 2D Row Column Addressing (RCA) Array
Objective. To develop a 3D shear wave elastography (SWE) technique using a 2D row column addressing (RCA) array, with either external vibration or acoustic radiation force (ARF) as the shear wave source. Impact Statement. The proposed method paves the way for clinical translation of 3D SWE based on the 2D RCA, providing a low-cost and high volume rate solution that is compatible with existing clinical systems. Introduction. SWE is an established ultrasound imaging modality that provides a direct and quantitative assessment of tissue stiffness, which is significant for a wide range of clinical applications including cancer and liver fibrosis. SWE requires high frame rate imaging for robust shear wave tracking. Due to the technical challenges associated with high volume rate imaging in 3D, current SWE techniques are typically confined to 2D. Advancing SWE from 2D to 3D is significant because of the heterogeneous nature of tissue, which demands 3D imaging for accurate and comprehensive evaluation. Methods. A 3D SWE method using a RCA array was developed with a volume rate up to 2000 Hz. The performance of the proposed method was systematically evaluated on tissue-mimicking elasticity phantoms and in an in vivo case study. Results. 3D shear wave motion induced by either external vibration or ARF was successfully detected with the proposed method. Robust 3D shear wave speed maps were reconstructed for phantoms and in vivo. Conclusion. The high volume rate 3D imaging provided by the 2D RCA array provides a robust and practical solution for 3D SWE with a clear pathway for future clinical translation
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Haploinsufficiency of mechanistic target of rapamycin ameliorates cardiomyopathy in adult zebrafish
The adult zebrafish is an emerging vertebrate model for studying human cardiomyopathies; however, whether the simple zebrafish heart can model different subtypes of cardiomyopathies, such as dilated cardiomyopathy (DCM), remains elusive. Here, we generated and characterized an inherited DCM model in adult zebrafish and used this model to search for therapeutic strategies. We employed transcription activator-like effector nuclease (TALEN) genome editing technology to generate frame-shift mutants for the zebrafish ortholog of human BCL2-associated athanogene 3 (BAG3), an established DCM-causative gene. As in mammals, the zebrafish bag3 homozygous mutant (bag3e2/e2 ) exhibited aberrant proteostasis, as indicated by impaired autophagy flux and elevated ubiquitinated protein aggregation. Through comprehensive phenotyping analysis of the mutant, we identified phenotypic traits that resembled DCM phenotypes in mammals, including cardiac chamber enlargement, reduced ejection fraction characterized by increased end-systolic volume/body weight (ESV/BW), and reduced contractile myofibril activation kinetics. Nonbiased transcriptome analysis identified the hyperactivation of the mechanistic target of rapamycin (mTOR) signaling in bag3e2/e2 mutant hearts. Further genetic studies showed that mtorxu015/+ , an mTOR haploinsufficiency mutant, repaired abnormal proteostasis, improved cardiac function and rescued the survival of the bag3e2/e2 mutant. This study established the bag3e2/e2 mutant as a DCM model in adult zebrafish and suggested mtor as a candidate therapeutic target gene for BAG3 cardiomyopathy.This work was supported in part by the Scientist Development Grant from the American Heart Association (14SDG18160021) to Y.D., the Ted and Loretta Rogers Cardiovascular Career Development Award Honoring Hugh C. Smith (from the Mayo Clinic) to Y.D., the National Institutes of Health (HL81753, HL107304, HL111437 and GM63904) to X.X., and the Mayo Foundation for Medical Education and Research to X.X.Open access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]
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Y-box binding protein-1 is crucial in acquired drug resistance development in metastatic clear-cell renal cell carcinoma
Background:
Renal cell carcinoma (RCC) is a highly vascular tumor and patients with low risk metastatic RCC of clear-cell histological sub-type (mccRCC) are treated with tyrosine-kinase inhibitors (TKIs), sunitinib, as the first-line of treatment. Unfortunately, TKI resistance eventually develops, and the underlying molecular mechanism is not well understood.
Methods:
RCC cell-line with metastatic clear-cell histology (Caki-1), and patient samples were analysed to identify the role of Y-box binding protein 1 (YB-1) and ATP-binding cassette sub-family B member 1 (ABCB-1) in acquired sunitinib-resistance development. Caki-1 was conditioned with increasing sunitinib doses to recapitulate acquired resistance development in clinics. Sunitinib-conditioned and wild-type Caki-1 were subjected to cell viability assay, scratch assay, chicken embryo chorioallantoic membrane engraftment and proteomics analysis. Classical biochemical assays like flow cytometry, immunofluorescent staining, immunohistochemical staining, optical coherence tomography imaging, Western Blot and RT-PCR assays were applied to determine the possible mechanism of sunitinib-resistance development and the effect of drug treatments. Publicly available data was also used to determine the role of YB-1 upregulation in ccRCC and the patients’ overall survival.
Results:
We demonstrate that YB-1 and ABCB-1 are upregulated in sunitinib-resistant in vitro, ex vivo, in vivo and patient samples compared to the sensitive samples. This provides evidence to a mechanism of acquired sunitinib-resistance development in mccRCC. Furthermore, our results establish that inhibiting ABCB-1 with elacridar, in addition to sunitinib, has a positive impact on reverting sunitinib-resistance development in in vitro, ex vivo and in vivo models.
Conclusion:
This work proposes a targeted therapy (elacridar and sunitinib) to re-sensitize sunitinib-resistant mccRCC and, possibly, slow disease progression.Medicine, Faculty ofOther UBCNon UBCUrologic Sciences, Department ofReviewedFacult
ULTRA-SR Challenge: Assessment of Ultrasound Localization and TRacking Algorithms for Super-Resolution Imaging
With the widespread interest and uptake of super-resolution ultrasound (SRUS) through localization and tracking of microbubbles, also known as ultrasound localization microscopy (ULM), many localization and tracking algorithms have been developed. ULM can image many centimeters into tissue in-vivo and track microvascular flow non-invasively with sub-diffraction resolution. In a significant community effort, we organized a challenge, Ultrasound Localization and TRacking Algorithms for Super-Resolution (ULTRA-SR). The aims of this paper are threefold: to describe the challenge organization, data generation, and winning algorithms; to present the metrics and methods for evaluating challenge entrants; and to report results and findings of the evaluation. Realistic ultrasound datasets containing microvascular flow for different clinical ultrasound frequencies were simulated, using vascular flow physics, acoustic field simulation and nonlinear bubble dynamics simulation. Based on these datasets, 38 submissions from 24 research groups were evaluated against ground truth using an evaluation framework with six metrics, three for localization and three for tracking. In-vivo mouse brain and human lymph node data were also provided, and performance assessed by an expert panel. Winning algorithms are described and discussed. The publicly available data with ground truth and the defined metrics for both localization and tracking present a valuable resource for researchers to benchmark algorithms and software, identify optimized methods/software for their data, and provide insight into the current limits of the field. In conclusion, Ultra-SR challenge has provided benchmarking data and tools as well as direct comparison and insights for a number of the state-of-the art localization and tracking algorithms