Motion correction of 3D dynamic contrast-enhanced ultrasound imaging without anatomical B-Mode images: Pilot evaluation in eight patients.

BACKGROUND: Dynamic contrast-enhanced ultrasound (DCE-US) is highly susceptible to motion artifacts arising from patient movement, respiration, and operator handling and experience. Motion artifacts can be especially problematic in the context of perfusion quantification. In conventional 2D DCE-US, motion correction (MC) algorithms take advantage of accompanying side-by-side anatomical B-Mode images that contain time-stable features. However, current commercial models of 3D DCE-US do not provide side-by-side B-Mode images, which makes MC challenging. PURPOSE: This work introduces a novel MC algorithm for 3D DCE-US and assesses its efficacy when handling clinical data sets. METHODS: In brief, the algorithm uses a pyramidal approach whereby short temporal windows consisting of three consecutive frames are created to perform local registrations, which are then registered to a master reference derived from a weighted average of all frames. We applied the algorithm to imaging studies from eight patients with metastatic lesions in the liver and assessed improvements in original versus motion corrected 3D DCE-US cine using: (i) frame-to-frame volumetric overlap of segmented lesions, (ii) normalized correlation coefficient (NCC) between frames (similarity analysis), and (iii) sum of squared errors (SSE), root-mean-squared error (RMSE), and r-squared (R2 ) quality-of-fit from fitted time-intensity curves (TIC) extracted from a segmented lesion. RESULTS: We noted improvements in frame-to-frame lesion overlap across all patients, from 68% ± 13% without correction to 83% ± 3% with MC (p = 0.023). Frame-to-frame similarity as assessed by NCC also improved on two different sets of time points from 0.694 ± 0.057 (original cine) to 0.862 ± 0.049 (corresponding MC cine) and 0.723 ± 0.066 to 0.886 ± 0.036 (p ≤ 0.001 for both). TIC analysis displayed a significant decrease in RMSE (p = 0.018) and a significant increase in R2 goodness-of-fit (p = 0.029) for the patient cohort. CONCLUSIONS: Overall, results suggest decreases in 3D DCE-US motion after applying the proposed algorithm.

Characterization of spatially mapped volumetric molecular ultrasound signals for predicting response to anti-vascular therapy.

Quantitative three-dimensional molecular ultrasound is a promising technology for longitudinal imaging applications such as therapy monitoring; the risk profile is favorable compared to positron emission tomography and computed tomography. However, clinical translation of quantitative methods for this technology are limited in that they assume that tumor tissues are homogeneous, and often depend on contrast-destruction events that can produce unintended bioeffects. Here, we develop quantitative features (henceforth image features) that capture tumor spatial information, and that are extracted without contrast destruction. We compare these techniques with the contrast-destruction derived differential targeted enhancement parameter (dTE) in predicting response to therapy. We found thirty-three reproducible image features that predict response to antiangiogenic therapy, without the need for a contrast agent disruption pulse. Multiparametric analysis shows that several of these image features can differentiate treated versus control animals with comparable performance to post-destruction measurements, suggesting that these can potentially replace parameters such as the dTE. The highest performing pre-destruction image features showed strong linear correlations with conventional dTE parameters with less overall variance. Thus, our study suggests that image features obtained during the wash in of the molecular agent, pre-destruction, may replace conventional post-destruction image features or the dTE parameter.

Dynamic Contrast-Enhanced Ultrasound Modeling of an Analog to Pseudo-Diffusivity in Intravoxel Incoherent Motion Magnetic Resonance Imaging.

Tumor perfusion and vascular properties are important determinants of cancer response to therapy and thus various approaches for imaging perfusion are being explored. In particular, Intravoxel Incoherent Motion (IVIM) MRI has been actively researched as an alternative to Dynamic-Contrast-Enhanced (DCE) CT and DCE-MRI as it offers non-ionizing, non-contrast-based perfusion imaging. However, for repetitive treatment assessment in a short time period, high cost, limited access, and inability to scan at the bedside remain disadvantages of IVIM MRI. We propose an analysis framework that may enable 3D DCE Ultrasound (DCE-US) - low cost, bedside imaging with excellent safety record - as an alternative modality to IVIM MRI for the generation of DCE-US based pseudo-diffusivity maps in acoustically accessible anatomy and tumors. Modelling intravascular contrast propagation as a convective-diffusive process, we reconstruct parametric maps of pseudo-diffusivity by solving a large-scale fully coupled inverse problem without any assumptions regarding local constancy of the reconstructed parameters. In a mouse tumor model, we demonstrate that the 3D DCE-US pseudo-diffusivity is repeatable, sensitive to treatment with an antiangiogenic agent, and moderately correlated to histological measures of perfusion and angiogenesis.

Evaluating dosimetric parameters predictive of hematologic toxicity in cervical cancer patients undergoing definitive pelvic chemoradiotherapy.

PURPOSE: We performed a retrospective study of cervical cancer pelvic radiotherapy plans to explore dosimetric parameters predictive of hematologic toxicity (HT), with specific interest in evaluating metabolic parameters and identifying the best predictive model. METHODS: Active marrow was retroactively contoured as pelvic bone with SUV > mean on 18F-FDG-PET. "Highly active" marrow was contoured as the hottest 10-14% volume of active marrow. Pelvic bone contour was segmented into lumbosacral, iliac crest, and lower pelvis. Predictors of HT were evaluated using logistic regression and repeated measures modeling. RESULTS: One hundred women were evaluated from 2009 to 2020. The plurality/majority had stage IIIC1 disease (38%) and underwent IMRT (88%) with pelvic field alone (72%). The majority received weekly cisplatin (78%), and 82% completed at least five cycles. The most common HT was leukopenia (grade 2+: 68%). Predictors of grade 2+ and 3+ HT were baseline WBC (p < 0.001), and 10- and 20-Gy dosimetric parameters to the active marrow, highly active marrow, and pelvic bone. The best predictive model of leukocyte trajectory included baseline WBC (p < 0.001), highly active marrow V20 (p < 0.001), and interactions of baseline WBC with time (p < 0.001) and highly active marrow V20 (p < 0.001), such that those with low baseline WBC experienced the greatest impact of highly active marrow V20. CONCLUSION: Baseline WBC was highly predictive of HT; dosimetric predictors included dose to the active marrow, highly active marrow, and pelvic bone, with the greatest impact from V20 to the highly active marrow, particularly in women with low baseline WBC. Future studies should consider incorporating baseline WBC and limiting dose to the most highly active marrow.

Human-level comparable control volume mapping with a deep unsupervised-learning model for image-guided radiation therapy.

PURPOSE: To develop a deep unsupervised learning method with control volume (CV) mapping from patient positioning daily CT (dCT) to planning computed tomography (pCT) for precise patient positioning. METHODS: We propose an unsupervised learning framework, which maps CVs from dCT to pCT to automatically generate the couch shifts, including translation and rotation dimensions. The network inputs are dCT, pCT and CV positions in the pCT. The output is the transformation parameter of the dCT used to setup the head and neck cancer (HNC) patients. The network is trained to maximize image similarity between the CV in the pCT and the CV in the dCT. A total of 554 CT scans from 158 HNC patients were used for the evaluation of the proposed model. At different points in time, each patient had many CT scans. Couch shifts are calculated for the testing by averaging the translation and rotation from the CVs. The ground-truth of the shifts come from bone landmarks determined by an experienced radiation oncologist. RESULTS: The system positioning errors of translation and rotation are less than 0.47 mm and 0.17°, respectively. The random positioning errors of translation and rotation are less than 1.13 mm and 0.29°, respectively. The proposed method enhanced the proportion of cases registered within a preset tolerance (2.0 mm/1.0°) from 66.67% to 90.91% as compared to standard registrations. CONCLUSIONS: We proposed a deep unsupervised learning architecture for patient positioning with inclusion of CVs mapping, which weights the CVs regions differently to mitigate any potential adverse influence of image artifacts on the registration. Our experimental results show that the proposed method achieved efficient and effective HNC patient positioning.

Technical Note: Extended field-of-view (FOV) MRI distortion determination through multi-positional phantom imaging.

Comprehensive characterization of geometric distortions for MRI simulators and MRI-guided treatment delivery systems is typically performed with large phantoms that are costly and unwieldy to handle. Here we propose an easily implementable methodology for MR distortion determination of the entire imaging space of the scanner through the use of a compact commercially available distortion phantom. The MagphanRT phantom was scanned at several locations within a MR scanner. From each scan, an approximate location of the phantom was determined from a subset of the fiducial spheres. The fiducial displacements were determined, and a displacement field was fitted to the displacement data using the entire multi-scan data set. An orthogonal polynomial expansion fitting function was used that had been augmented to include independent rigid-body transformations for each scan. The rigid-body portions of the displacement field were thereafter discarded, and the resultant fit then represented the distortion field. Multi-positional scans of the phantom were used successfully to determine the distortion field with extended coverage. A single scan of the phantom covered 20 cm in its smallest dimension. By stitching together overlapping scans we extended the distortion measurements to 30 cm. No information about the absolute location or orientation of each scan was required. The method, termed the Multi-Scan Expansion (MSE) method, can be easily applied for larger field-of-views (FOVs) by using a combination of larger phantom displacements and more scans. The implementation of the MSE method allows for distortion determination beyond the physical limitations of the phantom. The method is scalable to the user's needs and does not require any specialized equipment. This approach could open up for easier determination of the distortion magnitude at distances further from the scanner's isocenter. This is especially important in the newly proposed methodologies of MR-only simulation in RT and in adaptive replanning in MR linac systems.

Increased local tumor control through nanoparticle-mediated, radiation-triggered release of nitrite, an important precursor for reactive nitrogen species.

The efficacy of dose-enhancing gold nanoparticles (AuNPs) is negatively impacted by low tumor uptake, low cell membrane penetration, limited diffusion distance, and short lifetime of radiation-induced secondary particles. To overcome these limitations, we have developed a novel AuNP system capable of radiation-triggered release of nitrite, a precursor of reactive nitrogen species, and report here on the in vivo characterization of this system. AuNPs were functionalized through PEGylation, cell-penetrating peptides (CPP; AuNP@CPP), and nitroimidazole (nIm; AuNP@nIm-CPP). Mice with subcutaneous 4T1 tumors received either AuNP@nIm-CPP or AuNP@CPP intraperitoneally. Tumor and normal tissue uptake were evaluated 24 h post AuNP administration. A separate cohort of mice was injected and irradiated to a single-fraction dose of 18 Gy in a 225 kVp small animal irradiator 24 h post NP administration. The mice were followed for two weeks to evaluate tumor response. The mean physical and hydrodynamic size of both NP systems were 5 and 13 nm, respectively. NP nIm-loading of 1 wt% was determined. Tumor accumulation of AuNP@nIm-CPP was significantly lower than that of AuNP@CPP (0.2% vs 1.2%, respectively). In contrast, AuNP@nIm-CPP showed higher accumulation compared to AuNP@CPP in liver (16.5% vs 6.6%, respectively) and spleen (10.8% vs 3.1%, respectively). With respect to tumor response, no differential response was found between non-irradiated mice receiving either saline or AuNP@nIm-CPP alone. The combination of AuNP@CPP+ radiation showed no differential response from radiation alone. In contrast, a significant delay in tumor regrowth was observed in mice receiving AuNP@nIm-CPP+ radiation compared to radiation alone. AuNP functionalized with both CPP and nIm exhibited an order of magnitude less tumor accumulation compared to the NP system without nIm yet resulted in a significantly higher therapeutic response. Our data suggest that by improving the biokinetics of AuNP@nIm-CPP, this novel NP system could be a promising radiosensitizer for enhanced therapeutic response following radiation therapy.

A deep learning framework for prostate localization in cone beam CT-guided radiotherapy.

PURPOSE: To develop a deep learning-based model for prostate planning target volume (PTV) localization on cone beam computed tomography (CBCT) to improve the workflow of CBCT-guided patient setup. METHODS: A two-step task-based residual network (T2 RN) is proposed to automatically identify inherent landmarks in prostate PTV. The input to the T2 RN is the pretreatment CBCT images of the patient, and the output is the deep learning-identified landmarks in the PTV. To ensure robust PTV localization, the T2 RN model is trained by using over thousand sets of CT images with labeled landmarks, each of the CTs corresponds to a different scenario of patient position and/or anatomy distribution generated by synthetically changing the planning CT (pCT) image. The changes, including translation, rotation, and deformation, represent vast possible clinical situations of anatomy variations during a course of radiation therapy (RT). The trained patient-specific T2 RN model is tested by using 240 CBCTs from six patients. The testing CBCTs consists of 120 original CBCTs and 120 synthetic CBCTs. The synthetic CBCTs are generated by applying rotation/translation transformations to each of the original CBCT. RESULTS: The systematic/random setup errors between the model prediction and the reference are found to be <0.25/2.46 mm and 0.14/1.41° in translation and rotation dimensions, respectively. Pearson's correlation coefficient between model prediction and the reference is higher than 0.94 in translation and rotation dimensions. The Bland-Altman plots show good agreement between the two techniques. CONCLUSIONS: A novel T2 RN deep learning technique is established to localize the prostate PTV for RT patient setup. Our results show that highly accurate marker-less prostate setup is achievable by leveraging the state-of-the-art deep learning strategy.

Parametric Response Mapping of Coregistered Positron Emission Tomography and Dynamic Contrast Enhanced Computed Tomography to Identify Radioresistant Subvolumes in Locally Advanced Cervical Cancer.

PURPOSE: To identify subvolumes that may predict treatment response to definitive concurrent chemoradiation therapy using parametric response mapping (PRM) of coregistered positron emission tomography (PET) and dynamic contrast-enhanced (DCE) computed tomography (CT) in locally advanced cervical carcinoma. METHODS AND MATERIALS: Pre- and midtreatment (after 23 ± 4 days of concurrent chemoradiation therapy) DCE CT and PET imaging were performed on 21 patients with cervical cancer who were enrolled in a pilot study to evaluate the prognostic value of CT perfusion for primary cervical cancer (NCT01805141). Three-dimensional coregistered maps of PET/CT standardized uptake value (SUV) and DCE CT blood flow (BF) were generated. PRM was performed using voxel-wise joint histogram analysis to classify voxels within the tumor as highly metabolic and perfused (SUVhiBFhi), highly metabolic and hypoxic (SUVhiBFlo), low metabolic activity and hypoxic (SUVloBFlo), or low metabolic activity and perfused (SUVloBFhi) tissue based on thresholds determined from population means of pretreatment PET SUV and DCE CT BF. Relationships between baseline pretreatment imaging metrics and relative changes in metabolic tumor volume (ΔMTV), calculated from before treatment and during treatment imaging, were determined using univariable and multivariable linear regression models. RESULTS: The relative volume of three PRM subvolumes significantly changed during treatment (SUVhiBFhi: P = .04; SUVhiBFlo: P = .0008; SUVloBFhi: P = .02), whereas SUVloBFlo did not (P = .9). Pretreatment PET SUVmax (r = -.58, P = .006), PET SUVmean (ρ = -.59, P = .005), DCE CT BFmean (r = -.50, P = .02), tumor volume (ρ = -.65, P = .001) and PRM SUVhiBFhi (ρ = -.59, P = .004) were negatively correlated with ΔMTV, whereas PRM SUVloBFlo was positively related to ΔMTV (r = .77, P < .0001). In a multivariable model that predicted ΔMTV, PRM SUVloBFlo, which combines both PET/CT and DCE CT, was the only significant variable (ß = 1.825, P = .03), dominating both imaging modalities independently. CONCLUSIONS: PRM was applied in locally advanced cervical carcinoma treated definitively with chemoradiation, and radioresistant subvolumes were identified that correlated with changes in MTV and predicted treatment response. Identification of these subvolumes may assist in clinical decision making to tailor therapies, such as brachytherapy, in an effort to improve patient outcomes.

Spatial Characterization of Tumor Perfusion Properties from 3D DCE-US Perfusion Maps are Early Predictors of Cancer Treatment Response.

There is a need for noninvasive repeatable biomarkers to detect early cancer treatment response and spare non-responders unnecessary morbidities and costs. Here, we introduce three-dimensional (3D) dynamic contrast enhanced ultrasound (DCE-US) perfusion map characterization as inexpensive, bedside and longitudinal indicator of tumor perfusion for prediction of vascular changes and therapy response. More specifically, we developed computational tools to generate perfusion maps in 3D of tumor blood flow, and identified repeatable quantitative features to use in machine-learning models to capture subtle multi-parametric perfusion properties, including heterogeneity. Models were developed and trained in mice data and tested in a separate mouse cohort, as well as early validation clinical data consisting of patients receiving therapy for liver metastases. Models had excellent (ROC-AUC > 0.9) prediction of response in pre-clinical data, as well as proof-of-concept clinical data. Significant correlations with histological assessments of tumor vasculature were noted (Spearman R > 0.70) in pre-clinical data. Our approach can identify responders based on early perfusion changes, using perfusion properties correlated to gold-standard vascular properties.

Feasibility of Image Registration for Ultrasound-Guided Prostate Radiotherapy Based on Similarity Measurement by a Convolutional Neural Network.

PURPOSE: Registration of 3-dimensional ultrasound images poses a challenge for ultrasound-guided radiation therapy of the prostate since ultrasound image content changes significantly with anatomic motion and ultrasound probe position. The purpose of this work is to investigate the feasibility of using a pretrained deep convolutional neural network for similarity measurement in image registration of 3-dimensional transperineal ultrasound prostate images. METHODS: We propose convolutional neural network-based registration that maximizes a similarity score between 2 identical in size 3-dimensional regions of interest: one encompassing the prostate within a simulation (reference) 3-dimensional ultrasound image and another that sweeps different spatial locations around the expected prostate position within a pretreatment 3-dimensional ultrasound image. The similarity score is calculated by (1) extracting pairs of corresponding 2-dimensional slices (patches) from the regions of interest, (2) providing these pairs as an input to a pretrained convolutional neural network which assigns a similarity score to each pair, and (3) calculating an overall similarity by summing all pairwise scores. The convolutional neural network method was evaluated against ground truth registrations determined by matching implanted fiducial markers visualized in a pretreatment orthogonal pair of x-ray images. The convolutional neural network method was further compared to manual registration and a standard commonly used intensity-based automatic registration approach based on advanced normalized correlation. RESULTS: For 83 image pairs from 5 patients, convolutional neural network registration errors were smaller than 5 mm in 81% of the cases. In comparison, manual registration errors were smaller than 5 mm in 61% of the cases and advanced normalized correlation registration errors were smaller than 5 mm only in 25% of the cases. CONCLUSION: Convolutional neural network evaluation against manual registration and an advanced normalized correlation -based registration demonstrated better accuracy and reliability of the convolutional neural network. This suggests that with training on a large data set of transperineal ultrasound prostate images, the convolutional neural network method has potential for robust ultrasound-to-ultrasound registration.

Evaluation of transperineal ultrasound imaging as a potential solution for target tracking during hypofractionated radiotherapy for prostate cancer.

BACKGROUND: Emerging hypofractionated prostate radiotherapy regimens require solutions for accurate target tracking during beam delivery. The goal of this study is to evaluate the performance of the Clarity ultrasound monitoring system for prostate motion tracking. METHODS: Five prostate patients underwent continuous perineum ultrasound imaging during their daily treatments. Initial absolute 3D positions of fiducials implanted in the prostate were estimated from the KV images. Fiducial positions in MV images acquired during beam delivery were compared with predicted positions based on Clarity 3D tracking. The uncertainty in the comparison results was evaluated in a phantom validation study. RESULTS: Continuous real-time ultrasound motion tracking was recorded in 5 patients and 167 fractions for overall of 39.7 h. Phantom validation of the proposed procedure demonstrated that predicted and observed fiducial positions agree within 1.1 mm. In patients agreement between predicted and actual fiducial positions varied between 1.3 mm and 3.3 mm. On average ultrasound tracking reduced the maximum localization error in patients by 20% on average. With the motion corrected, the duration prostate beyond 1 mm from its initial treatment position can be reduced from 37 to 22% of the total treatment time. CONCLUSION: Real-time ultrasound tracking reduces uncertainty in prostate position due to intra-fractional motion. TRIAL REGISTRATION: IRB Protocol #27372 . Date of registration of trial: 12/17/2013.

Pilot study of combined FDG-PET and dynamic contrast-enhanced CT of locally advanced cervical carcinoma before and during concurrent chemoradiotherapy suggests association between changes in tumor blood volume and treatment response.

Modern PET/CT radiotherapy simulators offer FDG-PET and dynamic contrast-enhanced (DCE) CT imaging for combined volumetric assessment of tumor metabolism and perfusion. However, the clinical utility of such assessment has not been clearly defined. Thus, in a prospective longitudinal study of primary cervical tumors treated with concurrent chemoradiotherapy (CCRT) we evaluated: (1) whether PET and perfusion parameters correlate or provide complementary information; (2) what imaging changes occur during CCRT; and (3) whether any parameters are predictive of treatment response as assessed by PET/CT 3 months posttherapy. FDG-PET/CT and DCE-CT scans were performed on 21 patients prior to and during CCRT. Coregistered volumetric parametric maps of standardized uptake value (SUV) measures and perfusion parameters blood flow (BF), blood volume (BV), and permeability were generated. Summary statistics for these parameters and their changes were calculated within the metabolic tumor volume (MTV). Correlations between SUV and BF/BV/permeability on local and global bases were assessed with Pearson's coefficient r. MTV, maximum SUV, and mean SUV decreased significantly between the pre- and during-treatment time points, while mean BV and permeability increased significantly. Global correlations between mean BF/BV/permeability and mean SUV values (-.15 < r < .29) were at most moderate. An increase in mean tumor BV during treatment was significantly correlated with complete metabolic response on 3-month posttreatment PET/CT. Weak correlations of SUV and perfusion parameters suggest a complementary role of FDG-PET and DCE-CT for tumor characterization. The association between relative change in mean BV and outcome suggests a potential role for DCE-CT in early evaluation of cervical tumor response to chemoradiotherapy.

Quantitative Three-Dimensional Dynamic Contrast-Enhanced Ultrasound Imaging: First-In-Human Pilot Study in Patients with Liver Metastases.

Purpose: To perform a clinical assessment of quantitative three-dimensional (3D) dynamic contrast-enhanced ultrasound (DCE-US) feasibility and repeatability in patients with liver metastasis, and to evaluate the extent of quantitative perfusion parameter sampling errors in 2D compared to 3D DCE-US imaging. Materials and Methods: Twenty consecutive 3D DCE-US scans of liver metastases were performed in 11 patients (45% women; mean age, 54.5 years; range, 48-60 years; 55% men; mean age, 57.6 years; range, 47-68 years). Pairs of repeated disruption-replenishment and bolus DCE-US images were acquired to determine repeatability of parameters. Disruption-replenishment was carried out by infusing 0.9 mL of microbubbles (Definity; Latheus Medical Imaging) diluted in 35.1 mL of saline over 8 min. Bolus consisted of intravenous injection of 0.2 mL microbubbles. Volumes-of-interest (VOI) and regions-or-interest (ROI) were segmented by two different readers in images to extract 3D and 2D perfusion parameters, respectively. Disruption-replenishment parameters were: relative blood volume (rBV), relative blood flow (rBF). Bolus parameters included: time-to-peak (TP), peak enhancement (PE), area-under-the-curve (AUC), and mean-transit-time (MTT). Results: Clinical feasibility and repeatability of 3D DCE-US using both the destruction-replenishment and bolus technique was demonstrated. The repeatability of 3D measurements between pairs of repeated acquisitions was assessed with the concordance correlation coefficient (CCC), and found to be excellent for all parameters (CCC > 0.80), except for the TP (0.74) and MTT (0.30) parameters. The CCC between readers was found to be excellent (CCC > 0.80) for all parameters except for TP (0.71) and MTT (0.52). There was a large Coefficient of Variation (COV) in intra-tumor measurements for 2D parameters (0.18-0.52). Same-tumor measurements made in 3D were significantly different (P = 0.001) than measurements made in 2D; a percent difference of up to 86% was observed between measurements made in 2D compared to 3D in the same tumor. Conclusions: 3D DCE-US imaging of liver metastases with a matrix array transducer is feasible and repeatable in the clinic. Results support 3D instead of 2D DCE US imaging to minimize sampling errors due to tumor heterogeneity.

X-Ray responsive nanoparticles with triggered release of nitrite, a precursor of reactive nitrogen species, for enhanced cancer radiosensitization.

Remotely and locally triggered release of therapeutic species by X-ray irradiation is highly desired to enhance the efficacy of radiotherapy. However, the development of such X-ray responsive nanosystems remains a challenge, especially in response to high energy clinically relevant X-ray radiation. Herein, we report novel nitroimidazole ligated gold nanoparticles (AuNPs) that synergistically function to release nitrite, an important precursor for nitric oxide and reactive nitrogen species that sensitize cancer cells, upon radiation with clinically used 6 MeV X-rays, while no release was detected without radiation. These functional AuNPs were prepared with surface-grafted nitroimidazole as the nitrite-releasing agent, cell-penetrating peptide (CPP) to induce nucleus localization, and poly(ethylene glycol) for water solubility. In vitro radiotherapy using such nanoparticles showed enhanced sensitivity of hypoxic cancer cells to X-ray radiation, presumably due to the generation of both reactive oxygen and nitrogen species. The dose modifying factor (DMF) was found to be 0.71 for the dual-functionalized nanoparticle, which indicates that significant lower X-ray doses are required to achieve the same therapeutic effects. Thus, X-ray triggered nitrite release from gold-nitroimidazole nanosystems offers a novel strategy to sensitize cancer cells for improved radiotherapy.

Early prediction of tumor response to bevacizumab treatment in murine colon cancer models using three-dimensional dynamic contrast-enhanced ultrasound imaging.

Due to spatial tumor heterogeneity and consecutive sampling errors, it is critically important to assess treatment response following antiangiogenic therapy in three dimensions as two-dimensional assessment has been shown to substantially over- and underestimate treatment response. In this study, we evaluated whether three-dimensional (3D) dynamic contrast-enhanced ultrasound (DCE-US) imaging allows assessing early changes in tumor perfusion following antiangiogenic treatment (bevacizumab administered at a dose of 10 mg/kg b.w.), and whether these changes could predict treatment response in colon cancer tumors that either are responsive (LS174T tumors) or none responsive (CT26) to the proposed treatment. Our results showed that the perfusion parameters of 3D DCE-US including peak enhancement (PE) and area under curve (AUC) significantly decreased by up to 69 and 77%, respectively, in LS174T tumors within 1 day after antiangiogenic treatment (P = 0.005), but not in CT26 tumors (P > 0.05). Similarly, the percentage area of neovasculature significantly decreased in treated versus control LS174T tumors (P < 0.001), but not in treated versus control CT26 tumors (P = 0.796). Early decrease in both PE and AUC by 45-50% was predictive of treatment response in 100% (95% CI 69.2, 100%) of responding tumors, and in 100% (95% CI 88.4, 100%) and 86.7% (95% CI 69.3, 96.2%), respectively, of nonresponding tumors. In conclusion, 3D DCE-US provides clinically relevant information on the variability of tumor response to antiangiogenic therapy and may be further developed as biomarker for predicting treatment outcomes.

Molecular Contrast-Enhanced Ultrasound Imaging of Radiation-Induced P-Selectin Expression in Healthy Mice Colon.

PURPOSE: To evaluate the feasibility of using molecular contrast-enhanced ultrasound (mCEUS) to image radiation (XRT)-induced expression of cell adhesion molecules that mediate inflammatory response to XRT in healthy mouse colon tissue. METHODS AND MATERIALS: The colons of male BALB/c mice (aged 6-8 weeks, n=9) were irradiated with 14 Gy using a Kimtron IC-225 x-ray irradiator operating at 225 kV/13.0 mA at a dose rate of 0.985 Gy/min. The head and thorax regions were shielded during irradiation. A second control cohort of mice was left untreated (n=6). Molecular CEUS was carried out before and 24 hours after irradiation using a VEVO2100 system and MS250 21-MHz center frequency transducer. Each imaging session comprised mCEUS imaging with P-selectin targeted microbubbles and control microbubbles targeted with an isotype control IgG. Quantification of mCEUS was carried out by measuring the differential targeted enhancement (dTE) parameter. The perfusion parameters peak enhancement and area under the curve were also extracted from the initial injection bolus. Animals were sacrificed at 24 hours and the colon was resected for immunohistochemistry analysis (P-selectin/CD31-stained vessel). RESULTS: For P-selectin targeted microbubble, a significant increase (40 a.u.; P=.013) in dTE (P-dTE) was observed in irradiated mice over 24 hours. In contrast, a nonsignificant change in P-selectin dTE was observed in control mice. For control microbubbles, no significant difference in the IgG dTE parameter was noted in treated and control animals over 24 hours. A nonsignificant increase in the peak enhancement and area under the curve perfusion parameters associated with blood volume was noted in animals treated with radiation. Quantitative histology indicated significantly elevated P-selectin expression per blood vessel (36% in treated; 14% in control). CONCLUSION: Our results confirm the feasibility of using mCEUS for imaging of XRT-induced expression of P-selectin as a potential approach to monitoring healthy tissue inflammatory damage during radiation therapy.

Intrafractional Tracking Accuracy of a Transperineal Ultrasound Image Guidance System for Prostate Radiotherapy.

PURPOSE: The aim of this study is to evaluate the tracking accuracy of a commercial ultrasound system under relevant treatment conditions and demonstrate its clinical utility for detecting significant treatment deviations arising from inadvertent intrafractional target motion. METHODS: A multimodality male pelvic phantom was used to simulate prostate image-guided radiotherapy with the system under evaluation. Target motion was simulated by placing the phantom on a motion platform. The tracking accuracy of the ultrasound system was evaluated using an independent optical tracking system under the conditions of beam-on, beam-off, poor image quality with an acoustic shadow introduced, and different phantom motion cycles. The time delay between the ultrasound-detected and actual phantom motion was investigated. A clinical case example of prostate treatment is presented as a demonstration of the utility of the system in practice. RESULTS: Time delay between the motion phantom and ultrasound tracking system is 223 ± 45.2 milliseconds including video and optical tracking system frame rates. The tracking accuracy and precision were better with a longer period. The precision of ultrasound tracking performance in the axial (superior-inferior) direction was better than that in the lateral (left-right) direction (root mean square errors are 0.18 and 0.25 mm, respectively). The accuracy of ultrasound tracking performance in the lateral direction was better than that in the axial direction (the mean position errors are 0.23 and 0.45 mm, respectively). Interference by radiation and image quality do not affect tracking ability significantly. Further, utilizing the tracking system as part of a clinical study for prostate treatment further verified the accuracy and clinical appropriateness. CONCLUSIONS: It is feasible to use transperineal ultrasound daily to monitor prostate motion during treatment. Our results verify the accuracy and precision of an ultrasound system under typical external beam treatment conditions and further demonstrate that the tracking system was able to identify important prostate shifts in a clinical case.

Intra-Animal Comparison between Three-dimensional Molecularly Targeted US and Three-dimensional Dynamic Contrast-enhanced US for Early Antiangiogenic Treatment Assessment in Colon Cancer.

Purpose To perform an intra-animal comparison between (a) three-dimensional (3D) molecularly targeted ultrasonography (US) by using clinical-grade vascular endothelial growth factor receptor 2 (VEGFR2)-targeted microbubbles and (b) 3D dynamic contrast material-enhanced (DCE) US by using nontargeted microbubbles for assessment of antiangiogenic treatment effects in a murine model of human colon cancer. Materials and Methods Twenty-three mice with human colon cancer xenografts were randomized to receive either single-dose antiangiogenic treatment (bevacizumab, n = 14) or control treatment (saline, n = 9). At baseline and 24 hours after treatment, animals were imaged with a clinical US system equipped with a clinical matrix array transducer by using the following techniques: (a) molecularly targeted US with VEGFR2-targeted microbubbles, (b) bolus DCE US with nontargeted microbubbles, and (c) destruction-replenishment DCE US with nontargeted microbubbles. VEGFR2-targeted US signal, peak enhancement, area under the time-intensity curve, time to peak, relative blood volume (rBV), relative blood flow, and blood flow velocity were quantified. VEGFR2 expression and percentage area of blood vessels were assessed ex vivo with quantitative immunofluorescence and correlated with corresponding in vivo US parameters. Statistical analysis was performed with Wilcoxon signed rank tests and rank sum tests, as well as Pearson correlation analysis. Results Molecularly targeted US signal with VEGFR2-targeted microbubbles, peak enhancement, and rBV significantly decreased (P ≤ .03) after a single antiangiogenic treatment compared with those in the control group; similarly, ex vivo VEGFR2 expression (P = .03) and percentage area of blood vessels (P = .03) significantly decreased after antiangiogenic treatment. Three-dimensional molecularly targeted US signal correlated well with VEGFR2 expression (r = 0.86, P = .001), and rBV (r = 0.71, P = .01) and relative blood flow (r = 0.78, P = .005) correlated well with percentage area of blood vessels, while other US perfusion parameters did not. Conclusion Three-dimensional molecularly targeted US and destruction-replenishment 3D DCE US provide complementary molecular and functional in vivo imaging information on antiangiogenic treatment effects in human colon cancer xenografts compared with ex vivo reference standards. © RSNA, 2016 Online supplemental material is available for this article.

Robotic intrafractional US guidance for liver SABR: System design, beam avoidance, and clinical imaging.

PURPOSE: To present a system for robotic 4D ultrasound (US) imaging concurrent with radiotherapy beam delivery and estimate the proportion of liver stereotactic ablative body radiotherapy (SABR) cases in which robotic US image guidance can be deployed without interfering with clinically used VMAT beam configurations. METHODS: The image guidance hardware comprises a 4D US machine, an optical tracking system for measuring US probe pose, and a custom-designed robot for acquiring hands-free US volumes. In software, a simulation environment incorporating the LINAC, couch, planning CT, and robotic US guidance hardware was developed. Placement of the robotic US hardware was guided by a target visibility map rendered on the CT surface by using the planning CT to simulate US propagation. The visibility map was validated in a prostate phantom and evaluated in patients by capturing live US from imaging positions suggested by the visibility map. In 20 liver SABR patients treated with VMAT, the simulation environment was used to virtually place the robotic hardware and US probe. Imaging targets were either planning target volumes (PTVs, range 5.9-679.5 ml) or gross tumor volumes (GTVs, range 0.9-343.4 ml). Presence or absence of mechanical interference with LINAC, couch, and patient body as well as interferences with treated beams was recorded. RESULTS: For PTV targets, robotic US guidance without mechanical interference was possible in 80% of the cases and guidance without beam interference was possible in 60% of the cases. For the smaller GTV targets, these proportions were 95% and 85%, respectively. GTV size (1/20), elongated shape (1/20), and depth (1/20) were the main factors limiting the availability of noninterfering imaging positions. The robotic US imaging system was deployed in two liver SABR patients during CT simulation with successful acquisition of 4D US sequences in different imaging positions. CONCLUSIONS: This study indicates that for VMAT liver SABR, robotic US imaging of a relevant internal target may be possible in 85% of the cases while using treatment plans currently deployed in the clinic. With beam replanning to account for the presence of robotic US guidance, intrafractional US may be an option for 95% of the liver SABR cases.