A microscopic oxygen transport model for ultra-high dose rate radiotherapy in vivo: The impact of physiological conditions on FLASH effect.

BACKGROUND: Ultra-high dose rate irradiation (≥40 Gy/s, FLASH) has been shown to reduce normal tissue toxicity, while maintaining tumor control compared to conventional dose-rate radiotherapy. The radiolytic oxygen (O2) depletion (ROD) resulting from FLASH has been proposed to explain the normal tissue protection effect; however, in vivo experiments have not confirmed that FLASH induced global tissue hypoxia. Nonetheless, the experiments reported are based on volume-averaged measurement, which have inherent limitations in detecting microscopic phenomena, including the potential preservation of stem cells niches due to local FLASH-induced O2 depletion. Computational modeling offers a complementary approach to understand the ROD caused by FLASH at the microscopic level. PURPOSE: We developed a comprehensive model to describe the spatial and temporal dynamics of O2 consumption and transport in response to irradiation in vivo. The change of oxygen enhancement ratio (OER) was used to quantify and investigate the FLASH effect as a function of physiological and radiation parameters at microscopic scale. METHODS: We considered time-dependent O2 supply and consumption in a 3D cylindrical geometry, incorporating blood flow linking the O2 concentration ([O2]) in the capillary to that within the tissue through the Hill equation, radial and axial diffusion of O2, metabolic and zero-order radiolytic O2 consumption, and a pulsed radiation structure. Time-evolved distributions of [O2] were obtained by numerically solving perfusion-diffusion equations. The model enables the computation of dynamic O2 distribution and the relative change of OER (δROD) under various physiological and radiation conditions in vivo. RESULTS: Initial [O2] level and the subsequent changes during irradiation determined δROD distribution, which strongly depends on physiological parameters, i.e., intercapillary spacing, ultimately determining the tissue area with enhanced radioresistance. We observed that the δROD/FLASH effect is affected by and sensitive to the interplay effect among physiological and radiation parameters. It renders that the FLASH effect can be tissue environment dependent. The saturation of FLASH normal tissue protection upon dose and dose rate was shown. Beyond ∼60 Gy/s, no significant decrease in radiosensitivity within tissue region was observed. In turn, for a given dose rate, the change of radiosensitivity became saturated after a certain dose level. Pulse structures with the same dose and instantaneous dose rate but with different delivery times were shown to have distinguishable δROD thus tissue sparing, suggesting the average dose rate could be a metric assessing the FLASH effect and demonstrating the capability of our model to support experimental findings. CONCLUSION: On a macroscopic scale, the modeling results align with the experimental findings in terms of dose and dose rate thresholds, and it also indicates that pulse structure can vary the FLASH effect. At the microscopic level, this model enables us to examine the spatially resolved FLASH effect based on physiological and irradiation parameters. Our model thus provides a complementary approach to experimental methods for understanding the underlying mechanism of FLASH radiotherapy. Our results show that physiological conditions can potentially determine the FLASH efficacy in tissue protection. The FLASH effect may be observed under optimal combination of physiological parameters, not limited to radiation conditions alone.

In vivo bioluminescence tomography-guided system for pancreatic cancer radiotherapy research.

Recent development of radiotherapy (RT) has heightened the use of radiation in managing pancreatic cancer. Thus, there is a need to investigate pancreatic cancer in a pre-clinical setting to advance our understanding of the role of RT. Widely-used cone-beam CT (CBCT) imaging cannot provide sufficient soft tissue contrast to guide irradiation. The pancreas is also prone to motion. Large collimation is unavoidably used for irradiation, costing normal tissue toxicity. We innovated a bioluminescence tomography (BLT)-guided system to address these needs. We established an orthotopic pancreatic ductal adenocarcinoma (PDAC) mouse model to access BLT. Mice underwent multi-projection and multi-spectral bioluminescence imaging (BLI), followed by CBCT imaging in an animal irradiator for BLT reconstruction and radiation planning. With optimized absorption coefficients, BLT localized PDAC at 1.25 ± 0.19 mm accuracy. To account for BLT localization uncertainties, we expanded the BLT-reconstructed volume with margin to form planning target volume(PTVBLT) for radiation planning, covering 98.7 ± 2.2% of PDAC. The BLT-guided conformal plan can cover 100% of tumors with limited normal tissue involvement across both inter-animal and inter-fraction cases, superior to the 2D BLI-guided conventional plan. BLT offers unique opportunities to localize PDAC for conformal irradiation, minimize normal tissue involvement, and support reproducibility in RT studies.

Commissioning and validation of a single photon beam model in RayStation for multiple matched Elekta Linacs.

PURPOSE: A single treatment planning system (TPS) model for matched linacs provides flexible clinical workflows from patient treatment to intensity-modulated radiation therapy (IMRT) quality assurance (QA) measurement. Since general guidelines for building a single TPS model and its validation for matched linacs are not well established, we present our RayStation photon TPS modeling strategy for matched Elekta VersaHD linacs. METHOD: The four linacs installed from 2013 to 2020 were matched in terms of Percent Depth Dose (PDD), profile, output factor and wedge factors for 6-MV, 10-MV, 15-MV, and 6-MV-FFF, and maintained following TG-142 recommendations until RayStation commissioning. The RayStation single model was built to represent all four linacs within the tolerance limits recommended by MPPG-5.a. The comprehensive validation tests were performed for one linac following MPPG-5.a and TG-119 guidelines, and spot checks for the other three. Our TPS modeling/validation method was evaluated by re-analyzing the previous 103 patient-specific IMRT/volumetric modulated arc therapy (VMAT) QA measurements with the calculated planar doses by the single model in comparison with the analysis results using four individual Pinnacle TPS models. RESULTS: For all energies, our single model PDDs were within 1% agreement of the four-linac commissioning measurements. The MPPG-5.a validation tests from 5.1 through 7.5 and all TG-119 measurements passed within the recommended tolerance limits. The IMRT QA results (mean ± standard deviation) for RayStation single model versus Pinnacle individual models were 98.9% ± 1.3% and 98.0% ± 1.4% for 6-MV, 99.9% ± 0.1% and 99.1% ± 1.9% for 10-MV, and 98.2% ± 1.3% and 97.9% ± 1.8% for 6-MV-FFF, respectively. CONCLUSION: We successfully built and validated a single photon beam model in RayStation for four Elekta Linacs. The proposed new validation methods were proven to be both efficient and effective.

Characterization of a commercial bioluminescence tomography-guided system for pre-clinical radiation research.

BACKGROUND: Widely used Cone-beam computed tomography (CBCT)-guided irradiators have limitations in localizing soft tissue targets growing in a low-contrast environment. This hinders small animal irradiators achieving precise focal irradiation. PURPOSE: To advance image-guidance for soft tissue targeting, we developed a commercial-grade bioluminescence tomography-guided system (BLT, MuriGlo) for pre-clinical radiation research. We characterized the system performance and demonstrated its capability in target localization. We expect this study can provide a comprehensive guideline for the community in utilizing the BLT system for radiation studies. METHODS: MuriGlo consists of four mirrors, filters, lens, and charge-coupled device (CCD) camera, enabling a compact imaging platform and multi-projection and multi-spectral BLT. A newly developed mouse bed allows animals imaged in MuriGlo and transferred to a small animal radiation research platform (SARRP) for CBCT imaging and BLT-guided irradiation. Methods and tools were developed to evaluate the CCD response linearity, minimal detectable signal, focusing, spatial resolution, distortion, and uniformity. A transparent polycarbonate plate covering the middle of the mouse bed was used to support and image animals from underneath the bed. We investigated its effect on 2D Bioluminescence images and 3D BLT reconstruction accuracy, and studied its dosimetric impact along with the rest of mouse bed. A method based on pinhole camera model was developed to map multi-projection bioluminescence images to the object surface generated from CBCT image. The mapped bioluminescence images were used as the input data for the optical reconstruction. To account for free space light propagation from object surface to optical detector, a spectral derivative (SD) method was implemented for BLT reconstruction. We assessed the use of the SD data (ratio imaging of adjacent wavelength) in mitigating out of focusing and non-uniformity seen in the images. A mouse phantom was used to validate the data mapping. The phantom and an in vivo glioblastoma model were utilized to demonstrate the accuracy of the BLT target localization. RESULTS: The CCD response shows good linearity with < 0.6% residual from a linear fit. The minimal detectable level is 972 counts for 10 × 10 binning. The focal plane position is within the range of 13-18 mm above the mouse bed. The spatial resolution of 2D optical imaging is < 0.3 mm at Rayleigh criterion. Within the region of interest, the image uniformity is within 5% variation, and image shift due to distortion is within 0.3 mm. The transparent plate caused < 6% light attenuation. The use of the SD imaging data can effectively mitigate out of focusing, image non-uniformity, and the plate attenuation, to support accurate multi-spectral BLT reconstruction. There is < 0.5% attenuation on dose delivery caused by the bed. The accuracy of data mapping from the 2D bioluminescence images to CBCT image is within 0.7 mm. Our phantom test shows the BLT system can localize a bioluminescent target within 1 mm with an optimal threshold and only 0.2 mm deviation was observed for the case with and without a transparent plate. The same localization accuracy can be maintained for the in vivo GBM model. CONCLUSIONS: This work is the first systematic study in characterizing the commercial BLT-guided system. The information and methods developed will be useful for the community to utilize the imaging system for image-guided radiation research.

Dose evaluation of inter- and intra-fraction prostate motion in extremely hypofractionated intensity-modulated proton therapy for prostate cancer.

Inter- and intra-fractional prostate motion can deteriorate the dose distribution in extremely hypofractionated intensity-modulated proton therapy. We used verification CTs and prostate motion data calculated from 1024 intra-fractional prostate motion records to develop a voxel-wise based 4-dimensional method, which had a time resolution of 1 s, to assess the dose impact of prostate motion. An example of 100 fractional simulations revealed that motion had minimal impact on planning dose, the accumulated dose in 95 % of the scenarios fulfilled the clinical goals for target coverage (D95 > 37.5 Gy). This method can serve as a complementary measure in clinical setting to guarantee plan quality.

Filter inference: A scalable nonlinear mixed effects inference approach for snapshot time series data.

Variability is an intrinsic property of biological systems and is often at the heart of their complex behaviour. Examples range from cell-to-cell variability in cell signalling pathways to variability in the response to treatment across patients. A popular approach to model and understand this variability is nonlinear mixed effects (NLME) modelling. However, estimating the parameters of NLME models from measurements quickly becomes computationally expensive as the number of measured individuals grows, making NLME inference intractable for datasets with thousands of measured individuals. This shortcoming is particularly limiting for snapshot datasets, common e.g. in cell biology, where high-throughput measurement techniques provide large numbers of single cell measurements. We introduce a novel approach for the estimation of NLME model parameters from snapshot measurements, which we call filter inference. Filter inference uses measurements of simulated individuals to define an approximate likelihood for the model parameters, avoiding the computational limitations of traditional NLME inference approaches and making efficient inferences from snapshot measurements possible. Filter inference also scales well with the number of model parameters, using state-of-the-art gradient-based MCMC algorithms such as the No-U-Turn Sampler (NUTS). We demonstrate the properties of filter inference using examples from early cancer growth modelling and from epidermal growth factor signalling pathway modelling.

Systematic mutagenesis of Polerovirus protein P0 reveals distinct and overlapping amino acid functions in Nicotiana glutinosa.

The protein P0 serves as the viral suppressor of RNA silencing (VSR) for poleroviruses, but elicits the hypersensitive response (HR) in specific Nicotiana species. We subjected P0 proteins from turnip yellows virus (P0Tu) and potato leafroll virus (P0PL) to serial deletion and performed extensive site-directed mutagenesis of P0Tu. Most deletions of the N-terminus and many substitution mutations disrupted both HR elicitation and VSR activity. Two conserved blocks of amino acid residues were found to be associated with HR. A double lysine to arginine substitution in HR-specific block 1 caused P0Tu to elicit a more robust HR. Conversely, deletion or mutation of block 2 in the C-terminus preserved VSR activity, but impaired HR elicitation, allowing virus escape from Nicotiana glutinosa resistance when expressed in the heterologous potato virus X vector. Our observations suggest that P0 residues responsible for suppressing RNA silencing and eliciting HR have overlapping, but distinct functions.

Mobile bioluminescence tomography-guided system for pre-clinical radiotherapy research.

Due to low imaging contrast, a widely-used cone-beam computed tomography-guided small animal irradiator is less adept at localizing in vivo soft tissue targets. Bioluminescence tomography (BLT), which combines a model of light propagation through tissue with an optimization algorithm, can recover a spatially resolved tomographic volume for an internal bioluminescent source. We built a novel mobile BLT system for a small animal irradiator to localize soft tissue targets for radiation guidance. In this study, we elaborate its configuration and features that are indispensable for accurate image guidance. Phantom and in vivo validations show the BLT system can localize targets with accuracy within 1 mm. With the optimal choice of threshold and margin for target volume, BLT can provide a distinctive opportunity for investigators to perform conformal biology-guided irradiation to malignancy.

A model-informed approach to assess the risk of immune checkpoint inhibitor-induced autoimmune myocarditis.

Immune checkpoint inhibitors (ICIs), as a novel immunotherapy, are designed to modulate the immune system to attack malignancies. Despite their promising benefits, immune-related adverse events (IRAEs) may occur, and incidences are bound to increase with surging demand of this class of drugs in treating cancer. Myocarditis, although rare compared to other IRAEs, has a significantly higher fatal frequency. Due to the overwhelming complexity of the immune system, this condition is not well understood, despite the significant research efforts devoted to it. To better understand the development and progression of autoimmune myocarditis and the roles of ICIs therein, we suggest a new approach: mathematical modelling. Mathematical modelling of myocarditis has enormous potential to determine which parts of the immune system are critical to the development and progression of the disease, and therefore warrant further investigation. We provide the immunological background needed to develop a mathematical model of this disease and review relevant existing models of immunology that serve as the mathematical inspiration needed to develop this field.

Quantitative molecular bioluminescence tomography.

SIGNIFICANCE: Bioluminescence imaging and tomography (BLT) are used to study biologically relevant activity, typically within a mouse model. A major limitation is that the underlying optical properties of the volume are unknown, leading to the use of a "best" estimate approach often compromising quantitative accuracy. AIM: An optimization algorithm is presented that localizes the spatial distribution of bioluminescence by simultaneously recovering the optical properties and location of bioluminescence source from the same set of surface measurements. APPROACH: Measured data, using implanted self-illuminating sources as well as an orthotopic glioblastoma mouse model, are employed to recover three-dimensional spatial distribution of the bioluminescence source using a multi-parameter optimization algorithm. RESULTS: The proposed algorithm is able to recover the size and location of the bioluminescence source while accounting for tissue attenuation. Localization accuracies of <1 mm are obtained in all cases, which is similar if not better than current "gold standard" methods that predict optical properties using a different imaging modality. CONCLUSIONS: Application of this approach, using in-vivo experimental data has shown that quantitative BLT is possible without the need for any prior knowledge about optical parameters, paving the way toward quantitative molecular imaging of exogenous and indigenous biological tumor functionality.

Deep-Tissue Activation of Photonanomedicines: An Update and Clinical Perspectives.

With the continued development of nanomaterials over the past two decades, specialized photonanomedicines (light-activable nanomedicines, PNMs) have evolved to become excitable by alternative energy sources that typically penetrate tissue deeper than visible light. These sources include electromagnetic radiation lying outside the visible near-infrared spectrum, high energy particles, and acoustic waves, amongst others. Various direct activation mechanisms have leveraged unique facets of specialized nanomaterials, such as upconversion, scintillation, and radiosensitization, as well as several others, in order to activate PNMs. Other indirect activation mechanisms have leveraged the effect of the interaction of deeply penetrating energy sources with tissue in order to activate proximal PNMs. These indirect mechanisms include sonoluminescence and Cerenkov radiation. Such direct and indirect deep-tissue activation has been explored extensively in the preclinical setting to facilitate deep-tissue anticancer photodynamic therapy (PDT); however, clinical translation of these approaches is yet to be explored. This review provides a summary of the state of the art in deep-tissue excitation of PNMs and explores the translatability of such excitation mechanisms towards their clinical adoption. A special emphasis is placed on how current clinical instrumentation can be repurposed to achieve deep-tissue PDT with the mechanisms discussed in this review, thereby further expediting the translation of these highly promising strategies.

Translating pharmacology models effectively to predict therapeutic benefit.

Many in vitro and in vivo models are used in pharmacological research to evaluate the role of targeted proteins in a disease. Understanding the translational relevance and limitation of these models for analyzing a drug's disposition, pharmacokinetic/pharmacodynamic (PK/PD) profile, mechanism, and efficacy, is essential when selecting the most appropriate model of the disease of interest and predicting clinically efficacious doses of the investigational drug. Selected animal models used in ophthalmology, infectious diseases, oncology, autoimmune diseases, and neuroscience are reviewed here. Each area has specific challenges around translatability and determination of an efficacious dose: new patient-specific dosing methods may help overcome these limitations.

Mathematical modelling of autoimmune myocarditis and the effects of immune checkpoint inhibitors.

Autoimmune myocarditis is a rare, but frequently fatal, side effect of immune checkpoint inhibitors (ICIs), a class of cancer therapies. Despite extensive experimental work on the causes, development and progression of this disease, much still remains unknown about the importance of the different immunological pathways involved. We present a mathematical model of autoimmune myocarditis and the effects of ICIs on its development and progression to either resolution or chronic inflammation. From this, we gain a better understanding of the role of immune cells, cytokines and other components of the immune system in driving the cardiotoxicity of ICIs. We parameterise the model using existing data from the literature, and show that qualitative model behaviour is consistent with disease characteristics seen in patients in an ICI-free context. The bifurcation structures of the model show how the presence of ICIs increases the risk of developing autoimmune myocarditis. This predictive modelling approach is a first step towards determining treatment regimens that balance the benefits of treating cancer with the risk of developing autoimmune myocarditis.

Bioluminescence tomography system for in vivo irradiation guidance.

We constructed a bioluminescence tomography(BLT) to localize soft tissue targets for preclinical radiotherapy study. With the threshold and margin designed for target volume, BLT can provide opportunity to perform conformal irradiation to malignancy.

Quantitative Bioluminescence Tomography for In Vivo Volumetric-Guided Radiotherapy.

Several groups, including ours, have initiated efforts to develop small-animal irradiators that mimic radiation therapy (RT) for human treatment. The major image modality used to guide irradiation is cone-beam computed tomography (CBCT). While CBCT provides excellent guidance capability, it is less adept at localizing soft tissue targets growing in a low image contrast environment. In contrast, bioluminescence imaging (BLI) provides strong image contrast and thus is an attractive solution for soft tissue targeting. However, commonly used 2D BLI on an animal surface is inadequate to guide irradiation, because optical transport from an internal bioluminescent tumor is highly susceptible to the effects of optical path length and tissue absorption and scattering. Recognition of these limitations led us to integrate 3D bioluminescence tomography (BLT) with the small animal radiation research platform (SARRP). In this chapter, we introduce quantitative BLT (QBLT) with the advanced capabilities of quantifying tumor volume for irradiation guidance. The detail of system components, calibration protocol, and step-by-step procedure to conduct the QBLT-guided irradiation are described.

Quantitative Bioluminescence Tomography-Guided Conformal Irradiation for Preclinical Radiation Research.

PURPOSE: Widely used cone beam computed tomography (CBCT)-guided irradiators in preclinical radiation research are limited to localize soft tissue target because of low imaging contrast. Knowledge of target volume is a fundamental need for radiation therapy (RT). Without such information to guide radiation, normal tissue can be overirradiated, introducing experimental uncertainties. This led us to develop high-contrast quantitative bioluminescence tomography (QBLT) for guidance. The use of a 3-dimensional bioluminescence signal, related to cell viability, for preclinical radiation research is one step toward biology-guided RT. METHODS AND MATERIALS: Our QBLT system enables multiprojection and multispectral bioluminescence imaging to maximize input data for the tomographic reconstruction. Accurate quantification of spectrum and dynamic change of in vivo signal were also accounted for the QBLT. A spectral-derivative method was implemented to eliminate the modeling of the light propagation from animal surface to detector. We demonstrated the QBLT capability of guiding conformal RT using a bioluminescent glioblastoma (GBM) model in vivo. A threshold was determined to delineate QBLT reconstructed gross target volume (GTVQBLT), which provides the best overlap between the GTVQBLT and CBCT contrast labeled GBM (GTV), used as the ground truth for GBM volume. To account for the uncertainty of GTVQBLT in target positioning and volume delineation, a margin was determined and added to the GTVQBLT to form a QBLT planning target volume (PTVQBLT) for guidance. RESULTS: The QBLT can reconstruct in vivo GBM with localization accuracy within 1 mm. A 0.5-mm margin was determined and added to GTVQBLT to form PTVQBLT, largely improving tumor coverage from 75.0% (0 mm margin) to 97.9% in average, while minimizing normal tissue toxicity. With the goal of prescribed dose 5 Gy covering 95% of PTVQBLT, QBLT-guided 7-field conformal RT can effectively irradiate 99.4 ± 1.0% of GTV. CONCLUSIONS: The QBLT provides a unique opportunity for investigators to use biologic information for target delineation, guiding conformal irradiation, and reducing normal tissue involvement, which is expected to increase reproducibility of scientific discovery.

Cytokine Release Syndrome By T-cell-Redirecting Therapies: Can We Predict and Modulate Patient Risk?

T-cell-redirecting therapies are promising new therapeutic options in the field of cancer immunotherapy, but the development of these modalities is challenging. A commonly observed adverse event in patients treated with T-cell-redirecting therapies is cytokine release syndrome (CRS). Its clinical manifestation is a burden on patients, and continues to be a big hurdle in the clinical development of this class of therapeutics. We review different T-cell-redirecting therapies, discuss key factors related to cytokine release and potentially leading to CRS, and present clinical mitigation strategies applied for those modalities. We propose to dissect those risk factors into drug-target-disease-related factors and individual patient risk factors. Aiming to optimize the therapeutic intervention of these modalities, we illustrate how the knowledge on drug-target-disease-related factors, such as target expression, binding affinity, and target accessibility, can be leveraged in a model-based framework and highlight with case examples how modeling and simulation is applied to guide drug discovery and development. We draw attention to the current gaps in predicting the individual patient's risk towards a high-grade CRS, which requires further considerations of risk factors related, but not limited to, the patient's demographics, genetics, underlying pathologies, treatment history, and environmental exposures. The drug-target-disease-related factors together with the individual patient's risk factors can be regarded as the patient's propensity for developing CRS in response to therapy. As an outlook, we suggest implementing a risk scoring system combined with mechanistic modeling to enable the prediction of an individual patient's risk of CRS for a given therapeutic intervention.

Geometric Reproducibility of Fiducial Markers and Efficacy of a Patient-Specific Margin Design Using Deep Inspiration Breath Hold for Stereotactic Body Radiation Therapy for Pancreatic Cancer.

PURPOSE: In patients undergoing stereotactic body radiation therapy (SBRT) for pancreatic adenocarcinoma, the reproducibility of tumor positioning between deep-inspiration breath holds is unclear. We characterized this variation with fiducials at simulation and treatment and investigated whether a patient-specific breath-hold (PSBH) margin would help account for intrafraction variation at treatment. METHODS AND MATERIALS: We analyzed 20 consecutive patients with pancreatic cancer who underwent SBRT with deep-inspiration breath holds. At simulation, 3 additional breath-hold scans were acquired immediately after the contrast-enhanced planning computed tomography (CT) scan and used to quantify the mean and maximum variations in the simulation fiducial position (Sim_Var avg and Sim_Var max ), as well as to design the internal target volume (ITV) incorporating a PSBH margin. RESULTS: At treatment, a mean of 5 breath-hold cone beam CT (CBCT) scans were acquired per fraction for each patient to quantify the mean and maximum variations in the treatment fiducial position (Tx_Var avg and Tx_Var max ). Various planning target volume (PTV) margins on the gross tumor volume (GTV) versus ITV were evaluated using CBCT scans, with the goal of >95% of fiducials being covered at treatment. The Sim_Var avg and Sim_Var max were 0.9 ± 0.5 mm and 1.5 ± 0.8 mm in the left-right (LR) direction, 0.9 ± 0.4 mm and 1.4 ± 0.4 mm in the anteroposterior (AP) direction, and 1.5 ± 0.9 mm and 2.1 ± 1.0 mm in the superoinferior (SI) direction, respectively. The Tx_Var avg and Tx_Var max were 1.2 ± 0.4 mm and 2.0 ± 0.7 mm in the LR direction, 1.1 ± 0.4 mm and 1.8 ± 0.6 mm in the AP direction, and 1.9 ± 1.0 mm and 3.1 ± 1.4 mm in the SI direction, respectively. The ITV was increased by 21.0% ± 8.6% compared with the GTV alone. The PTV margin necessary to encompass >95% of the fiducial locations was 2 mm versus 4 mm in both LR and AP and 4 mm versus 6 mm in SI for the ITV and the GTV, respectively. CONCLUSIONS: The interbreath-hold variation is not insignificant, especially in the SI direction. Acquiring multiple breath-hold CT scans at simulation can help quantify the reproducibility of the interbreath hold and design a PSBH margin for treatment.

Fiducial-based image-guided SBRT for pancreatic adenocarcinoma: Does inter-and intra-fraction treatment variation warrant adaptive therapy?

PURPOSE: Variation in target positioning represents a challenge to set-up reproducibility and reliability of dose delivery with stereotactic body radiation therapy (SBRT) for pancreatic adenocarcinoma (PDAC). While on-board imaging for fiducial matching allows for daily shifts to optimize target positioning, the magnitude of the shift as a result of inter- and intra-fraction variation may directly impact target coverage and dose to organs-at-risk. Herein, we characterize the variation patterns for PDAC patients treated at a high-volume institution with SBRT. METHODS: We reviewed 30 consecutive patients who received SBRT using active breathing coordination (ABC). Patients were aligned to bone and then subsequently shifted to fiducials. Inter-fraction and intra-fraction scans were reviewed to quantify the mean and maximum shift along each axis, and the shift magnitude. A linear regression model was conducted to investigate the relationship between the inter- and intra-fraction shifts. RESULTS: The mean inter-fraction shift in the LR, AP, and SI axes was 3.1 ± 1.8 mm, 2.9 ± 1.7 mm, and 3.5 ± 2.2 mm, respectively, and the mean vector shift was 6.4 ± 2.3 mm. The mean intra-fraction shift in the LR, AP, and SI directions were 2.0 ± 0.9 mm, 2.0 ± 1.3 mm, and 2.3 ± 1.4 mm, respectively, and the mean vector shift was 4.3 ± 1.8 mm. A linear regression model showed a significant relationship between the inter- and intra-fraction shift in the AP and SI axis and the shift magnitude. CONCLUSIONS: Clinically significant inter- and intra-fraction variation occurs during treatment of PDAC with SBRT even with a comprehensive motion management strategy that utilizes ABC. Future studies to investigate how these variations could lead to variation in the dose to the target and OAR should be investigated. Strategies to mitigate the dosimetric impact, including real time imaging and adaptive therapy, in select cases should be considered.

In vivo bioluminescence tomography-guided radiation research platform for pancreatic cancer: an initial study using subcutaneous and orthotopic pancreatic tumor models.

Genetically engineered mouse model(GEMM) that develops pancreatic ductal adenocarcinoma(PDAC) offers an experimental system to advance our understanding of radiotherapy(RT) for pancreatic cancer. Cone beam CT(CBCT)-guided small animal radiation research platform(SARRP) has been developed to mimic the RT used for human. However, we recognized that CBCT is inadequate to localize the PDAC growing in low image contrast environment. We innovated bioluminescence tomography(BLT) to guide SARRP irradiation for in vivo PDAC. Before working on the complex PDAC-GEMM, we first validated our BLT target localization using subcutaneous and orthotopic pancreatic tumor models. Our BLT process involves the animal transport between the BLT system and SARRP. We inserted a titanium wire into the orthotopic tumor as the fiducial marker to track the tumor location and to validate the BLT reconstruction accuracy. Our data shows that with careful animal handling, minimum disturbance for target position was introduced during our BLT imaging procedure(<0.5mm). However, from longitudinal 2D bioluminescence image(BLI) study, the day-to-day location variation for an abdominal tumor can be significant. We also showed that the 2D BLI in single projection setting cannot accurately capture the abdominal tumor location. It renders that 3D BLT with multiple-projection is needed to quantify the tumor volume and location for precise radiation research. Our initial results show the BLT can retrieve the location at 2mm accuracy for both tumor models, and the tumor volume can be delineated within 25% accuracy. The study for the subcutaneous and orthotopic models will provide us valuable knowledge for BLT-guided PDAC-GEMM radiation research.