Clinical Radiation Research Articles

Establishing the Gastroduodenal Maximum Tolerated Dose for Ablative 5-Fraction Stereotactic MR-guided Online Adaptive Radiation Therapy (SMART) in a Novel Swine Model

Daily variations in abdominal anatomy introduce significant uncertainty in estimating the maximum tolerated dose (MTD). We investigated the gastroduodenal toxicity using stereotactic MR-guided online adaptive radiotherapy (SMART) to precisely control the dose to a novel swine model that closely matches human physiology and can be maintained at 80 kg. We hypothesized for a cumulative SMART course of 50 Gy in 5 fractions to the pancreas, the duodenum MTD is significantly > 37 Gy to 0.5 cc (D0.5cc).A total of 18 WMSTM were included at 3 duodenal dose levels: 37 Gy (n = 12), 43.5 Gy (n = 3), and 50 Gy (n = 3) in 5 fractions. We defined MTD as: > 10% (≥2 of 12) WMSTM present with dose limiting toxicity (DLT). A DLT was defined as ≥ Grade 3 non-hematologic toxicity due to RT per NCI CTCAE v4.0. All WMSTM underwent SMART on a clinical MR-guided radiotherapy (MRgRT) LINAC, under ventilation at breath hold (BH). Plans were IMRT and prescribed 50 Gy/5 fractions to pancreatic head, while maintaining uniform dose level (37, 43.5, 50 Gy) to duodenal circumference at 3 cm inferior to pylorus sphincter, typical uniform irradiated range 3-9 cc based on duodenal diameter. Circumference approach was used to eliminate underestimation of cumulative D0.5cc. Duodenal hotspot was 1.03% of the dose level (37, 43.5, 50 Gy) to 2 cc, 1.05% to 0.1 cc. Gated BH delivery was performed with sagittal plane tracking of the duodenum at 4 frames per second. Toxicity monitoring occurred for 30 days post-RT. Fecal occult blood test (FOBT) was done during RT and toxicity monitoring. Endoscopy occurred 14 days post-RT. Gross pathology was obtained at time of necropsy, 30 days post-RT.For the 37 Gy level, 1 of 12 WMSTM presented with DLT-pinpoint ulcer with surface damage on gross pathology (30 days post-RT). No DLT for 2 of 3 WMSTM at the 43.5 Gy level. One WMSTM at the 43.5 Gy level perforated on endoscopy, potentially due duodenal wall degradation and unknown RT-induced DLT on gross exam of emergency necropsy. Endoscopy was eliminated for the 50 Gy level. DLT was found for 2 of 3 WMSTM at the 50 Gy level upon gross pathology at necropsy, with each subject having 2-3 visible ulcerations at level of RT. One WMSTM at the 50 Gy level had duodenal pre-ulcer erosion at necropsy. All three WMSTM at 50 Gy level had visibly damaged papilla at necropsy. Another WMSTM at the 50 Gy level had common bile duct blockage, gall bladder obstruction, and jaundice at necropsy. FOBT were negative for all 18 WMSTM at 14 days post-RT.A duodenum D0.5cc of 37 Gy in 5 fractions was found to be safe in a swine model for a 50 Gy SMART course to the pancreas, showing the duodenal MTD is > 37 Gy - an increase from the RTOG 1112 limit (i.e., 30 Gy). Our results translate to a recommended MTD in human subjects and can potentially allow for greater tumor dose escalation and survival outcomes in future pancreatic patients. We are currently pursuing an expansion cohort to evaluate the MTD at 43.5 Gy.

A convolutional neural network for estimating cone-beam CT intensity deviations from virtual CT projections

Extending cone-beam CT (CBCT) use toward dose accumulation and adaptive radiotherapy (ART) necessitates more accurate HU reproduction since cone-beam geometries are heavily degraded by photon scatter. This study proposes a novel method which aims to demonstrate how deep learning based on phantom data can be used effectively for CBCT intensity correction in patient images. Four anthropomorphic phantoms were scanned on a CBCT and conventional fan-beam CT system. Intensity correction is performed by estimating the cone-beam intensity deviations from prior information contained in the CT. Residual projections were extracted by subtraction of raw cone-beam projections from virtual CT projections. An improved version of U-net is utilized to train on a total of 2001 projection pairs. Once trained, the network could estimate intensity deviations from input patient head and neck raw projections. The results from our novel method showed that corrected CBCT images improved the (contrast-to-noise ratio) with respect to uncorrected reconstructions by a factor of 2.08. The mean absolute error and structural similarity index improved from 318 HU to 74 HU and 0.750 to 0.812 respectively. Visual assessment based on line-profile measurements and difference image analysis indicate the proposed method reduced noise and the presence of beam-hardening artefacts compared to uncorrected and manufacturer reconstructions. Projection domain intensity correction for cone-beam acquisitions of patients was shown to be feasible using a convolutional neural network trained on phantom data. The method shows promise for further improvements which may eventually facilitate dose monitoring and ART in the clinical radiotherapy workflow.

A compact and lightweight small animal PET with uniform high-resolution for onboard PET/CT image-guided preclinical radiation oncology research

Objective: In contrast to clinical radiation therapy (RT) that ubiquitously uses PET/CT image to accurately guide RT, all current commercial animal irradiators can only provide CT image-guided preclinical RT that severely limits their capability for preclinical and compatibility for translational radiation oncology research. To address this problem, we have developed a compact and lightweight PET with uniform, high spatial resolution that is suited to be installed inside an existing animal irradiator for potential onboard PET/CT image-guided preclinical RT research. Approach: The design focused on the balance of achieving sufficient imaging performance for practical preclinical RT guidance with constrained size and weight. The detector head consists of a ring of 12 detector panels in a dodecagon configuration and 12 front-end electronics boards that are closely attached to the detector panels. The overall size and weight of the detector head are 33.0 cm diameter, 11.0 cm axial length and ∼6.5 kg weight that can be installed inside an existing irradiator. Each detector panel has a 30 × 30 array of 1 × 1 × 20 mm3 LYSO scintillators with depth-of-interaction (DOI) measurement. The front-end electronics boards process and convert detected signals to digital signals and transfer them to system electronics and data acquisition located outside the irradiator through low-voltage-differential-signaling cables. Main results: The typical energy, DOI and coincidence timing resolutions are around 22.1%, 3.1 mm, and 1.92 ns. The imaging field-of-view (FOV) is 8.0 cm diameter and 3.5 cm axial length. The performance evaluations show a 1.8% sensitivity at the center FOV, uniform ∼1.1 mm resolution within 6 cm diameter FOV, and all rods of 1.0 mm diameter can be clearly resolved from the image of an ultra-micro hot-rods phantom. Significance: Overall, this compact and lightweight PET has demonstrated its designed capability and performance sufficient for providing onboard functional/biological/molecular image to guide the preclinical RT research.

EFNet: evidence fusion network for tumor segmentation from PET-CT volumes

Precise delineation of target tumor from positron emission tomography-computed tomography (PET-CT) is a key step in clinical practice and radiation therapy. PET-CT co-segmentation actually uses the complementary information of two modalities to reduce the uncertainty of single-modal segmentation, so as to obtain more accurate segmentation results. At present, the PET-CT segmentation methods based on fully convolutional neural network (FCN) mainly adopt image fusion and feature fusion. The current fusion strategies do not consider the uncertainty of multi-modal segmentation and complex feature fusion consumes more computing resources, especially when dealing with 3D volumes. In this work, we analyze the PET-CT co-segmentation from the perspective of uncertainty, and propose evidence fusion network (EFNet). The network respectively outputs PET result and CT result containing uncertainty by proposed evidence loss, which are used as PET evidence and CT evidence. Then we use evidence fusion to reduce uncertainty of single-modal evidence. The final segmentation result is obtained based on evidence fusion of PET evidence and CT evidence. EFNet uses the basic 3D U-Net as backbone and only uses simple unidirectional feature fusion. In addition, EFNet can separately train and predict PET evidence and CT evidence, without the need for parallel training of two branch networks. We do experiments on the soft-tissue-sarcomas and lymphoma datasets. Compared with 3D U-Net, our proposed method improves the Dice by 8% and 5% respectively. Compared with the complex feature fusion method, our proposed method improves the Dice by 7% and 2% respectively. Our results show that in PET-CT segmentation methods based on FCN, by outputting uncertainty evidence and evidence fusion, the network can be simplified and the segmentation results can be improved.

Deep learning-augmented radioluminescence imaging for radiotherapy dose verification.

We developed a novel dose verification method using a camera-based radioluminescence imaging system (CRIS) combined with a deep learning-based signal processing technique. The CRIS consists of a cylindrical chamber coated with scintillator material on the inner surface of the cylinder, coupled with a hemispherical mirror and a digital camera at the two ends. After training, the deep learning model is used for image-to-dose conversion to provide absolute dose prediction at multiple depths of a specific water phantom from a single CRIS image under the assumption of a good consistency between the TPS setting and actual beam energy. The model was trained using a set of captured radioluminescence images and the corresponding dose maps from the clinical treatment planning system (TPS) for the sake of acceptable data collection. To overcome the latent error and inconsistency that exists between the TPS calculation and the corresponding measurement, the model was trained in an unsupervised manner. Validation experiments were performed on five square fields (ranging from 2 × 2 to 10 × 10cm2 ) and three clinical intensity-modulated radiation therapy (IMRT) cases. The results were compared to the TPS calculations in terms of gamma index at 1.5, 5, and 10cm depths. The mean 2%/2mm gamma pass rates were 100% for square fields and 97.2% (range from 95.5% to 99.5%) for the IMRT fields. Further validations were performed by comparing the CRIS results with measurements on various regular fields. The results show a mean gamma pass rate of 91% (1%/1mm) for cross-profiles and a mean percentage deviation of 1.15% for percentage depth doses (PDDs). The system is capable of converting the irradiated radioluminescence image to corresponding water-based dose maps at multiple depths with a spatial resolution comparable to the TPS calculations.

Symptom Outcomes of Cancer Patients With Clival Metastases Treated With Radiotherapy: A Study of 44 Patients.

To describe clinical features, radiotherapy (RT), and symptom outcomes in cancer patients with cranial nerve palsies associated with clival metastases. This is a retrospective review of patients with primary metastatic cancers who developed clival metastases and received RT (2000-2020). Of the 44 patients with primary cancers (manly breast, prostate and multiple myeloma cancers) and distal clival metastases, 32 patients (73%) also had cervical spine metastases. Of the 23 RT-treated patients, 65% and 35% received clivus only and whole brain RT, respectively. Post-RT symptom improvement was observed in patients with diplopia (5/6; 83%), headache (8/10; 80%), chin numbness (2/4; 50%), blurry vision (2/5; 40%), lateral gaze deficit (2/6; 33%), and tongue deviation (1/4; 25%). Early detection and cranial nerve examination, in addition to RT treatment, should be considered in patients with breast, prostate, and multiple myeloma cancers, who developed cervical spine metastases.

Deep learning-enabled EPID-based 3D dosimetry for dose verification of step-and-shoot radiotherapy.

The study aims at a novel dosimetry methodology to reconstruct a 3D dose distribution as imparted to a virtual cylindrical phantom using an electronic portal imaging device (EPID). A deep learning-based signal processing strategy, referred to as 3DosiNet, is utilized to learn a mapping from an EPID image to planar dose distributions at given depths. The network was trained with the volumetric dose exported from the clinical treatment planning system (TPS). Given the latent inconsistency between measurements and corresponding TPS calculations, unsupervised learning is formulated in 3DosiNet to capture abstractive image features that are less sensitive to the potential variations. Validation experiments were performed using five regular fields and three clinical intensity-modulated radiation therapy (IMRT) cases. The measured dose profiles and percentage depth dose (PDD) curves were compared with those measured using standard tools in terms of the 1D gamma index. The mean gamma pass rates (2%/2mm) over the regular fields are 100% and 97.3% for the dose profile and PDD measurements, respectively. The measured volumetric dose was compared to the corresponding TPS calculation in terms of the 3D gamma index. The mean 2%/2mm gamma pass rates are 97.9% for square fields and 94.9% for the IMRT fields. The system promises to be a practical 3D dosimetric tool for pre-treatment patient-specific quality assurance and further developed for in-treatment patient dose monitoring.

ANTP-SMACN7 fusion peptide alone induced high linear energy transfer irradiation radiosensitization in non-small cell lung cancer cell lines.

Objective:The aim of the present study was to investigate the mechanisms responsible for the radiation-sensitizing effect of antennapedia proteins, ANTP-SMACN7, on lung cancer cells treated with accelerated carbon and Fe particle irradiation.Methods:The ANTP-SMACN7 fusion peptide was synthesized and linked to fluorescein isothiocyanate to determine its ability to penetrate cells. A549 and NCI-H460 cells, human non-small cell lung cancer (NSCLC) cell lines, were irradiated with X-ray or high linear energy transfer (LET) irradiation with or without ANTP-SMACN7 treatment. Cellular survival, apoptosis, and protein expression were studied by colony formation assays, flow cytometry, and western blot analyses, respectively.Results:ANTP-SMACN7 fusion proteins entered the cells and promoted A549 and NCI-H460 cell high LET irradiation radiosensitization. High LET irradiation was more efficient for clonogenic cell killing and the induction of apoptosis (P < 0.05). Treatment with ANTP-SMACN7 significantly reduced the A549 and NCI-H460 cell clone-forming percentages and increased apoptosis through inhibition of the X-linked inhibitor of apoptosis protein and the activation of caspase-3 and caspase-9.Conclusions:Regarding pharmaceutical radiosensitization, these findings provided a way to improve high-LET clinical radiotherapy for NSCLC patients.

Radiobiology of the FLASH effect.

Radiation exposures at ultrahigh dose rates (UHDRs) at several orders of magnitude greater than in current clinical radiotherapy (RT) have been shown to manifest differential radiobiological responses compared to conventional (CONV) dose rates. This has led to studies investigating the application of UHDR for therapeutic advantage (FLASH-RT) that have gained significant interest since the initial discovery in 2014 that demonstrated reduced lung toxicity with equivalent levels of tumor control compared with conventional dose-rate RT. Many subsequent studies have demonstrated the potential protective role of FLASH-RT in normal tissues, yet the underlying molecular and cellular mechanisms of the FLASH effect remain to be fully elucidated. Here, we summarize the current evidence of the FLASH effect and review FLASH-RT studies performed in preclinical models of normal tissue response. To critically examine the underlying biological mechanisms of responses to UHDR radiation exposures, we evaluate in vitro studies performed with normal and tumor cells. Differential responses to UHDR versus CONV irradiation recurrently involve reduced inflammatory processes and differential expression of pro- and anti-inflammatory genes. In addition, frequently reduced levels of DNA damage or misrepair products are seen after UHDR irradiation. So far, it is not clear what signal elicits these differential responses, but there are indications for involvement of reactive species. Different susceptibility to FLASH effects observed between normal and tumor cells may result from altered metabolic and detoxification pathways and/or repair pathways used by tumor cells. We summarize the current theories that may explain the FLASH effect and highlight important research questions that are key to a better mechanistic understanding and, thus, the future implementation of FLASH-RT in the clinic.

A portable NIR fluorimeter directly quantifies singlet oxygen generated by nanostructures for Photodynamic Therapy

This paper reports on the setting up and calibration of a portable NIR fluorimeter specifically developed for quantitative direct detection of the highly reactive singlet oxygen (1O2) chemical specie, of great importance in Photodynamic therapies. This quantification relies on the measurement of fluorescence emission of 1O2, which is peaked in the near-infrared (NIR) at λ=1270nm.In recent years, several nanostructures capable of generating reactive oxygen species (ROS) when activated by penetrating radiation (X-rays, NIR light) have been developed to apply Photodynamic Therapy (PDT) to tumours in deep tissue, where visible light cannot penetrate. A bottleneck in the characterization of these nanostructures is the lack of a fast and reliable technique to quantitatively assess their performances in generating ROS, and in particular 1O2. For instance, the widely used PDT “Singlet Oxygen Sensor Green” kit suffers from self-activation under X-ray irradiation.To solve this difficulty, we propose here direct detection of 1O2 by spectroscopic means, using an apparatus developed by us around a recent thermoelectrically-cooled InGaAs single photon avalanche photodiode (SPAD). The SPAD is coupled to a custom-made integrating sphere designed for use under irradiation with high-energy X-ray beams from clinical Radiotherapy sources. We determine the detection threshold for our apparatus, which turns to be ∼9·1081O2 in realistic experimental condition and for measurements extending to 1 min of integration. After calibrations on standard photosensitizers, we demonstrate the potentiality of this instrument characterizing some photosensitizing nanostructures developed by us.

VAV2 is required for DNA repair and implicated in cancer radiotherapy resistance

Radiotherapy remains the mainstay for treatment of various types of human cancer; however, the clinical efficacy is often limited by radioresistance, in which the underlying mechanism is largely unknown. Here, using esophageal squamous cell carcinoma (ESCC) as a model, we demonstrate that guanine nucleotide exchange factor 2 (VAV2), which is overexpressed in most human cancers, plays an important role in primary and secondary radioresistance. We have discovered for the first time that VAV2 is required for the Ku70/Ku80 complex formation and participates in non-homologous end joining repair of DNA damages caused by ionizing radiation. We show that VAV2 overexpression substantially upregulates signal transducer and activator of transcription 1 (STAT1) and the STAT1 inhibitor Fludarabine can significantly promote the sensitivity of radioresistant patient-derived ESCC xenografts in vivo in mice to radiotherapy. These results shed new light on the mechanism of cancer radioresistance, which may be important for improving clinical radiotherapy.

Vitamin D Receptor Protects against Radiation-Induced Intestinal Injury in Mice via Inhibition of Intestinal Crypt Stem/Progenitor Cell Apoptosis.

It is urgent to seek new potential targets for the prevention or relief of gastrointestinal syndrome in clinical radiation therapy for cancers. Vitamin D, mediated through the vitamin D receptor (VDR), has been identified as a protective nutrient against ionizing radiation (IR)-induced damage. This study investigated whether VDR could inhibit IR-induced intestinal injury and explored underlying mechanism. We first found that vitamin D induced VDR expression and inhibited IR-induced DNA damage and apoptosis in vitro. VDR was highly expressed in intestinal crypts and was critical for crypt stem/progenitor cell proliferation under physiological conditions. Next, VDR-deficient mice exposed to IR significantly increased DNA damage and crypt stem/progenitor cell apoptosis, leading to impaired intestinal regeneration as well as shorter survival time. Furthermore, VDR deficiency activated the Pmaip1-mediated apoptotic pathway of intestinal crypt stem/progenitor cells in IR-treated mice, whereas inhibition of Pmaip1 expression by siRNA transfection protected against IR-induced cell apoptosis. Therefore, VDR protects against IR-induced intestinal injury through inhibition of crypt stem/progenitor cell apoptosis via the Pmaip1-mediated pathway. Our results reveal the importance of VDR level in clinical radiation therapy, and targeting VDR may be a useful strategy for treatment of gastrointestinal syndrome.

Plastic scintillation dosimeter with a conical mirror for measuring 3D dose distribution.

To test the measurement technique of the three-dimensional (3D) dose distribution measured image by capturing the scintillation light generated using a plastic scintillator and a scintillating screen. Our imaging system constituted a column shaped plastic scintillator covered by a Gd2 O2 S:Tb scintillating screen, a conical mirror and a cooled CCD camera. The scintillator was irradiated with 6 MV photon beams. Meanwhile, the irradiated plan was prepared for the static field plans, two-field plan (2F plan) and the conformal arc plan (CA plan). The 2F plan contained 16 mm2 and 10 mm2 fields irradiated from gantry angles of 0° and 25°, respectively. The gantry was rotated counterclockwise from 45° to 315° for the CA plan. The field size was then obtained as 10 mm2 . A Monte Carlo simulation was performed in the experimental geometry to obtain the calculated 3D dose distribution as the reference data. Dose response was acquired by comparing between the reference and the measurement. The dose rate dependence was verified by irradiating the same MU value at different dose rates ranging from 100 to 600 MU/min. Deconvolution processing was applied to the measured images for the correction of light blurring. The measured 3D dose distribution was reconstructed from each measured image. Gamma analysis was performed to these 3D dose distributions. The gamma criteria were 3% for the dose difference, 2mm for the distance-to-agreement and 10% for the threshold. Dose response for the scintillation light was linear. The variation in the light intensity for the dose rate ranging from 100 to 600 MU/min was less than 0.5%, while our system presents dose rate independence. For the 3D dose measurement, blurring of light through deconvolution processing worked well. The 3D gamma passing rate (3D GPR) for the 10 × 10 mm2 , 16 × 16 mm2 , and 20 × 20 mm2 fields were observed to be 99.3%, 98.8%, and 97.8%, respectively. Reproducibility of measurement was verified. The 3D GPR results for the 2F plan and the CA plan were 99.7% and 100%, respectively. We developed a plastic scintillation dosimeter and demonstrated that our system concept can act as a suitable technique for measuring the 3D dose distribution from the gamma results. In the future, we will attempt to measure the 4D dose distribution for clinical volumetric modulated arc radiation therapy (VMAT)-SBRTplans.

Artificial Intelligence: Guidance for clinical imaging and therapeutic radiography professionals, a summary by the Society of Radiographers AI working group

IntroductionArtificial intelligence (AI) has started to be increasingly adopted in medical imaging and radiotherapy clinical practice, however research, education and partnerships have not really caught up yet to facilitate a safe and effective transition. The aim of the document is to provide baseline guidance for radiographers working in the field of AI in education, research, clinical practice and stakeholder partnerships. The guideline is intended for use by the multi-professional clinical imaging and radiotherapy teams, including all staff, volunteers, students and learners. MethodsThe format mirrored similar publications from other SCoR working groups in the past. The recommendations have been subject to a rapid period of peer, professional and patient assessment and review. Feedback was sought from a range of SoR members and advisory groups, as well as from the SoR director of professional policy, as well as from external experts. Amendments were then made in line with feedback received and a final consensus was reached. ResultsAI is an innovative tool radiographers will need to engage with to ensure a safe and efficient clinical service in imaging and radiotherapy. Educational provisions will need to be proportionately adjusted by Higher Education Institutions (HEIs) to offer the necessary knowledge, skills and competences for diagnostic and therapeutic radiographers, to enable them to navigate a future where AI will be central to patient diagnosis and treatment pathways. Radiography-led research in AI should address key clinical challenges and enable radiographers co-design, implement and validate AI solutions. Partnerships are key in ensuring the contribution of radiographers is integrated into healthcare AI ecosystems for the benefit of the patients and service users. ConclusionRadiography is starting to work towards a future with AI-enabled healthcare. This guidance offers some recommendations for different areas of radiography practice. There is a need to update our educational curricula, rethink our research priorities, forge new strong clinical-academic-industry partnerships to optimise clinical practice.Specific recommendations in relation to clinical practice, education, research and the forging of partnerships with key stakeholders are discussed, with potential impact on policy and practice in all these domains. These recommendations aim to serve as baseline guidance for UK radiographers. Implications for practiceThis review offers the most up-to-date recommendations for clinical practitioners, researchers, academics and service users of clinical imaging and therapeutic radiography services. Radiography practice, education and research must gradually adjust to AI-enabled healthcare systems to ensure gains of AI technologies are maximised and challenges and risks are minimised. This guidance will need to be updated regularly given the fast-changing pace of AI development and innovation.

Are gamma passing rate and dose-volume histogram QA metrics correlated?

The quality of a measured distribution of dose delivered against its corresponding radiotherapy plan is routinely assessed by gamma index (GI) and dose-volume histogram (DVH) metrics. Any correlation between error detection rates, as based on either of these approaches, while argued, has never been convincingly demonstrated. The dependence of the strength of correlation between the GI passing rate ( ) and DVH quality assurance (QA) metrics on various elements of the therapy plan has not been systematically investigated. A formal analysis of the relation between and DVH metrics has been undertaken, leading to a relationship which may partly approximate with respect to the DVH. This relationship was further validated by studying examples of simulated clinical radiotherapy plans and by studying the correlation between and the derived relationship using a simple two-dimensional representations of the planning target volume (PTV) and organs at risk (OAR), where penumbra regions, distance-to-agreement tolerances and dose delivery errors were systematically varied. It is shown formally that there cannot be any correlation between and other commonly applied DVH-derived QA measures. However, may be partly approximated given the planned and measured DVH. The derived approximation (the " -slope indicator") may be clinically useful in some practical cases of radiotherapy plan QA. In formal terms, there cannot be any correlation between and any common DVH-calculated patient-specific measures, with respect to PTV or OAR. However, as demonstrated analytically and further confirmed in our simulation studies, the approximation derived in this study (the " -slope indicator") may in some cases offer a degree of correlation between and the PTV and OAR DVH QA metrics in measured and planned patient-specific dose distributions-which may be potentially useful in clinical practice.

Radiation-Responsive Amino Acid Nanosensor Gel (RANG) for Radiotherapy Monitoring and Trauma Care.

Accurate detection of doses is critical for the development of effective countermeasures and patient stratification strategies in cases of accidental exposure to ionizing radiation. Existing detection devices are limited by high fabrication costs, long processing times, need for sophisticated detection systems, and/or loss of readout signal over time, particularly in complex environments. Here, we describe fundamental studies on amino acid-facilitated templating of gold nanoparticles following exposure to ionizing radiation as a new colorimetric approach for radiation detection. Tryptophan demonstrated spontaneous nanoparticle formation, and parallel screening of a library of amino acids and related compounds led to the identification of lead candidates, including phenylalanine, which demonstrated an increase in absorbance at wavelengths typical of gold nanoparticles in the presence of ionizing radiation (X-rays). Evaluation of screening, i.e., absorbance data, in concert with chemical informatics modeling led to the elucidation of physicochemical properties, particularly polarizable regions and partial charges, that governed nanoparticle formation propensities upon exposure of amino acids to ionizing radiation. NMR spectroscopy revealed key roles of amino and carboxy moieties in determining the nanoparticle formation propensity of phenylalanine, a lead amino acid from the screen. These findings were employed for fabricating radiation-responsive amino acid nanosensor gels (RANGs) based on phenylalanine and tryptophan, and efficacy of RANGs was demonstrated for predicting clinical doses of ionizing radiation in anthropomorphic thorax phantoms and in live canine patients undergoing radiotherapy. The use of biocompatible templating ligands (amino acids), rapid response, simplicity of fabrication, efficacy, ease of operation and detection, and long-lasting readout indicate several advantages of the RANG over existing detection systems for monitoring radiation in clinical radiotherapy, radiological emergencies, and trauma care.

An updating approach for knowledge-based planning models to improve plan quality and variability in volumetric-modulated arc therapy for prostate cancer.

PurposeThe purpose of this study was to compare the dose–volume parameters and regression scatter plots of the iteratively improved RapidPlan (RP) models, specific knowledge‐based planning (KBP) models, in volumetric‐modulated arc therapy (VMAT) for prostate cancer over three periods.MethodsA RP1 model was created from 47 clinical intensity‐modulated radiation therapy (IMRT)/VMAT plans. A RP2 model was created to exceed dosimetric goals which set as the mean values +1SD of the dose–volume parameters of RP1 (50 consecutive new clinical VMAT plans). A RP3 model was created with more strict dose constraints for organs at risks (OARs) than RP1 and RP2 models (50 consecutive anew clinical VMAT plans). Each RP model was validated against 30 validation plans (RP1, RP2, and RP3) that were not used for model configuration, and the dose–volume parameters were compared. The Cook's distances of regression scatterplots of each model were also evaluated.ResultsSignificant differences (p < 0.05) between RP1 and RP2 were found in Dmean (101.5% vs. 101.9%), homogeneity index (3.90 vs. 4.44), 95% isodose conformity index (1.22 vs. 1.20) for the target, V40Gy (47.3% vs. 45.7%), V60Gy (27.9% vs. 27.1%), V70Gy (16.4% vs. 15.2%), and V78Gy (0.4% vs. 0.2%) for the rectal wall, and V40Gy (43.8% vs. 41.8%) and V70Gy (21.3% vs. 20.5%) for the bladder wall, whereas only V70Gy (15.2% vs. 15.8%) of the rectal wall differed significantly between RP2 and RP3. The proportions of cases with a Cook's distance of <1.0 (RP1, RP2, and RP3 models) were 55%, 78%, and 84% for the rectal wall, and 77%, 68%, and 76% for the bladder wall, respectively.ConclusionsThe iteratively improved RP models, reflecting the clear dosimetric goals based on the RP feedback (dose–volume parameters) and more strict dose constraints for the OARs, generated superior dose–volume parameters and the regression scatterplots in the model converged. This approach could be used to standardize the inverse planning strategies.

PH-0491 Clinical stereotactic ablative body radiotherapy on patients with early-stage inoperable lung cancer

PH-0491 Clinical stereotactic ablative body radiotherapy on patients with early-stage inoperable lung cancer

PO-1736 Using the DcmCollab Audit Tool to support quality assurance of clinical radiotherapy trials

PO-1736 Using the DcmCollab Audit Tool to support quality assurance of clinical radiotherapy trials

Fractionated Low-Dose Radiation Induces Long-Lasting Inflammatory Responses in the Hippocampal Stem Cell Niche

Despite major technical advances in hippocampus-sparing radiation therapy, radiation-induced injury to the neural stem cell compartment may affect neurocognitive functions. In the brain, glial cells modulate neuronal functions and are major mediators of neuroinflammation. In a preclinical mouse model with fractionated low-dose radiation (LDR), the complex response to radiation-induced injury was analyzed in the hippocampal stem cell compartment over a period of 6 months. Adult and juvenile C57BL/6NCrl mice were exposed to low doses of ionizing radiation (IR; 20 fractions of 0.1 Gy, for up to 4 weeks) daily. At 72 hours and 1, 3, and 6 months after fractionated LDR, magnetic resonance imaging (9.4 T) was conducted to detect structural and functional abnormalities in the hippocampal region. Using immunofluorescence and histologic studies, neuroglia cells (astrocytes, microglia, oligodendrocytes) were quantified and neuroinflammatory responses were characterized in the hippocampal dentate gyrus. Using in vivo bromodeoxyuridine labeling, the cell fate of newly generated progenitor cells was tracked in the subgranular zone of the dentate gyrus during fractionated LDR. Low doses of IR induced long-lasting inflammatory responses with local increases of activated microglia and reactive astrocytes, which were most pronounced in the juvenile hippocampus within the first months after LDR. Glial activation with the consequent release of proinflammatory mediators increased local blood flow and vascular permeability in the hippocampal region. Cell fate mapping of progenitors located in the subgranular zone revealed a transient shift from neurogenesis to gliogenesis. Glial cell activation and transient neuroinflammation may reflect radiation-induced neuronal damage in the hippocampal stem cell niche. The increased proliferative capacity of the developing brain may explain the enhanced hippocampal radiosensitivity, with stronger inflammatory reactions in the juvenile hippocampus. Thus, limiting the radiation dose to the hippocampal region is an important issue of clinical radiation therapy at all ages to preserve neurocognitive functions.