Development and optimisation of a preclinical cone beam computed tomography-based radiomics workflow for radiation oncology research.

Background and purpose: Radiomics features derived from medical images have the potential to act as imaging biomarkers to improve diagnosis and predict treatment response in oncology. However, the complex relationships between radiomics features and the biological characteristics of tumours are yet to be fully determined. In this study, we developed a preclinical cone beam computed tomography (CBCT) radiomics workflow with the aim to use in vivo models to further develop radiomics signatures. Materials and methods: CBCT scans of a mouse phantom were acquired using onboard imaging from a small animal radiotherapy research platform (SARRP, Xstrahl). The repeatability and reproducibility of radiomics outputs were compared across different imaging protocols, segmentation sizes, pre-processing parameters and materials. Robust features were identified and used to compare scans of two xenograft mouse tumour models (A549 and H460). Results: Changes to the radiomics workflow significantly impact feature robustness. Preclinical CBCT radiomics analysis is feasible with 119 stable features identified from scans imaged at 60 kV, 25 bin width and 0.26 mm slice thickness. Large variation in segmentation volumes reduced the number of reliable radiomics features for analysis. Standardization in imaging and analysis parameters is essential in preclinical radiomics analysis to improve accuracy of outputs, leading to more consistent and reproducible findings. Conclusions: We present the first optimised workflow for preclinical CBCT radiomics to identify imaging biomarkers. Preclinical radiomics has the potential to maximise the quantity of data captured in in vivo experiments and could provide key information supporting the wider application of radiomics.

Development and Optimization of a Machine-Learning Prediction Model for Acute Desquamation After Breast Radiation Therapy in the Multicenter REQUITE Cohort.

Purpose: Some patients with breast cancer treated by surgery and radiation therapy experience clinically significant toxicity, which may adversely affect cosmesis and quality of life. There is a paucity of validated clinical prediction models for radiation toxicity. We used machine learning (ML) algorithms to develop and optimise a clinical prediction model for acute breast desquamation after whole breast external beam radiation therapy in the prospective multicenter REQUITE cohort study. Methods and Materials: Using demographic and treatment-related features (m = 122) from patients (n = 2058) at 26 centers, we trained 8 ML algorithms with 10-fold cross-validation in a 50:50 random-split data set with class stratification to predict acute breast desquamation. Based on performance in the validation data set, the logistic model tree, random forest, and naïve Bayes models were taken forward to cost-sensitive learning optimisation. Results: One hundred and ninety-two patients experienced acute desquamation. Resampling and cost-sensitive learning optimisation facilitated an improvement in classification performance. Based on maximising sensitivity (true positives), the "hero" model was the cost-sensitive random forest algorithm with a false-negative: false-positive misclassification penalty of 90:1 containing m = 114 predictive features. Model sensitivity and specificity were 0.77 and 0.66, respectively, with an area under the curve of 0.77 in the validation cohort. Conclusions: ML algorithms with resampling and cost-sensitive learning generated clinically valid prediction models for acute desquamation using patient demographic and treatment features. Further external validation and inclusion of genomic markers in ML prediction models are worthwhile, to identify patients at increased risk of toxicity who may benefit from supportive intervention or even a change in treatment plan.

Simultaneous integrated boost (SIB) to dominant intra-prostatic lesions during extreme hypofractionation for prostate cancer: the impact of rectal spacers.

PURPOSE: Boosting dominant intra-prostatic lesions (DILs) has the potential to increase the therapeutic ratio in prostate cancer radiotherapy. In this study, employing 5-fraction stereotactic ablative radiotherapy (SABR) volumetric modulated arc therapy (VMAT) to deliver 40 Gy to the prostate clinical target volume (CTV) while boosting the DIL up to 50 Gy was evaluated for patients before and after rectal spacer insertion. MATERIALS AND METHODS: 24 Computed Tomography (CT) scans of 12 prostate cancer patients with unfavourable intermediate or high risk prostate cancer were employed in this study. At least two treatment plans were generated for each patient to compare pre- and post-spacer insertion plans. Plans were evaluated for target coverage, organs-at-risk doses, and the achievable boost dose level. RESULTS: The CTV coverage was significantly better in plans with a spacer, V40Gy 98.4% versus 97.0% (p = 0.012). Using spacers significantly reduced rectal dose in all 12 patients in this study. It was possible to boost DIL to 50 Gy to without violating dose constraints in 6 of 12 patients and to 47.5 Gy in 3 patients post-spacer insertion. For 3 patients (25%) it was not possible to boost DIL above 45 Gy even with a spacer in situ. Without a spacer, for 6 patient (50%) clinically acceptable plan were only achieved when the DIL dose was lowered to 45 Gy. In five of these 6 patients the dose limiting structure was the urethra (urethra planning risk volume V45Gy [cc] ≤ 0.1 cc constraint). CONCLUSIONS: Clinically acceptable plans for 5 fraction SABR, 40 Gy to the prostate CTV, with a SIB to DIL (45-50 Gy) were achieved. The boost dose achieved was DIL location dependent and primarily affected by DIL's proximity to the urethra. Compared to plans before spacer insertion, higher DIL dose were achieved with spacer in situ for 25% of the patients. Moreover, significant reduction in rectal dose and better target coverage were also achieved for all patients with spacers in situ.

Enhanced fitness of SARS-CoV-2 variant of concern Alpha but not Beta.

Emerging variants of concern (VOCs) are driving the COVID-19 pandemic1,2. Experimental assessments of replication and transmission of major VOCs and progenitors are needed to understand the mechanisms of replication and transmission of VOCs3. Here we show that the spike protein (S) from Alpha (also known as B.1.1.7) and Beta (B.1.351) VOCs had a greater affinity towards the human angiotensin-converting enzyme 2 (ACE2) receptor than that of the progenitor variant S(D614G) in vitro. Progenitor variant virus expressing S(D614G) (wt-S614G) and the Alpha variant showed similar replication kinetics in human nasal airway epithelial cultures, whereas the Beta variant was outcompeted by both. In vivo, competition experiments showed a clear fitness advantage of Alpha over wt-S614G in ferrets and two mouse models-the substitutions in S were major drivers of the fitness advantage. In hamsters, which support high viral replication levels, Alpha and wt-S614G showed similar fitness. By contrast, Beta was outcompeted by Alpha and wt-S614G in hamsters and in mice expressing human ACE2. Our study highlights the importance of using multiple models to characterize fitness of VOCs and demonstrates that Alpha is adapted for replication in the upper respiratory tract and shows enhanced transmission in vivo in restrictive models, whereas Beta does not overcome Alpha or wt-S614G in naive animals.

A data science approach for early-stage prediction of Patient's susceptibility to acute side effects of advanced radiotherapy.

The prediction by classification of side effects incidence in a given medical treatment is a common challenge in medical research. Machine Learning (ML) methods are widely used in the areas of risk prediction and classification. The primary objective of such algorithms is to use several features to predict dichotomous responses (e.g., disease positive/negative). Similar to statistical inference modelling, ML modelling is subject to the class imbalance problem and is affected by the majority class, increasing the false-negative rate. In this study, seventy-nine ML models were built and evaluated to classify approximately 2000 participants from 26 hospitals in eight different countries into two groups of radiotherapy (RT) side effects incidence based on recorded observations from the international study of RT related toxicity "REQUITE". We also examined the effect of sampling techniques and cost-sensitive learning methods on the models when dealing with class imbalance. The combinations of such techniques used had a significant impact on the classification. They resulted in an improvement in incidence status prediction by shifting classifiers' attention to the minority group. The best classification model for RT acute toxicity prediction was identified based on domain experts' success criteria. The Area Under Receiver Operator Characteristic curve of the models tested with an isolated dataset ranged from 0.50 to 0.77. The scale of improved results is promising and will guide further development of models to predict RT acute toxicities. One model was optimised and found to be beneficial to identify patients who are at risk of developing acute RT early-stage toxicities as a result of undergoing breast RT ensuring relevant treatment interventions can be appropriately targeted. The design of the approach presented in this paper resulted in producing a preclinical-valid prediction model. The study was developed by a multi-disciplinary collaboration of data scientists, medical physicists, oncologists and surgeons in the UK Radiotherapy Machine Learning Network.

Mini review: Personalization of the radiation therapy management of prostate cancer using MRI-based radiomics.

Decisions on how to treat prostate cancer with radiation therapy are guideline-based but as such guidelines have been developed for populations of patients, this invariably leads to overly aggressive treatment in some patients and insufficient treatment in others. Heterogeneity within prostate tumors and in metastatic sites, even within the same patient, is believed to be a major cause of treatment failure. Radiomics biomarkers, more commonly referred to as radiomics 'features", provide readily available, cost-effective, non-invasive tools for screening, detecting tumors and serial monitoring of patients, including assessments of response to therapy and identification of therapeutic complications. Radiomics offers the potential to analyse whole tumors in 3D, as well as sub-regions or 'habitats' within tumors. Combining quantitative information from imaging with pathology, demographic details and other biomarkers will pave the way for personalised treatment selection and monitoring in prostate cancer. The aim of this review is to consider if MRI-based radiomics can bridge the gap between population-based management and personalised management of prostate cancer.

Incidence and root causes of surgical site infections after gastrointestinal surgery at a public teaching hospital in Sudan.

BACKGROUND: Surgical site infections (SSIs) are common healthcare-associated infections and associated with prolonged hospital stays, additional financial burden, and significantly hamper the potential benefits of surgical interventions. Causes of SSIs are multi-factorials and patients undergoing gastrointestinal tract procedures carry a high risk of bacterial contamination. This study aimed to determine the prevalence, associated factors, and causing microorganisms of SSIs among patients undergoing gastrointestinal tract surgeries. METHODS: A hospital based, cross-sectional study conducted at Soba University Hospital in Khartoum, Sudan. We included all patients from all age groups attending the gastrointestinal tract surgical unit between 1st September and 31st December 2017. We collected data about the socio-demographic characteristics, risk factors of SSI, and isolated microorganisms from patients with SSIs. A Chi-square test was conducted to determine the relationship between the independent categorical variables and the occurrence of SSI. The significance level for all analyses was set at p < .05. RESULTS: A total of 80 participants were included in the study. The mean age was 51 +/- 16 years and most of the patients (67.5%) did not have any chronic illness prior to the surgical operation. Most of them (46.3%) of them underwent large bowel surgery. Twenty-two patients (27.5%) developed SSI post operatively and superficial SSI was the most common type of SSIs (81.8%). Occurrence of SSI was found to be associated with long operation time (p > .001), malignant nature of the disease (p > .001), intra-operative blood loss (p > .001), and intra-operative hypotension (p = .013). The most prevalent microorganism isolated from SSI patients was E coli (47.8%), followed by Enterococcus fecalis (13.0%) and combined Pseudomonas aeruginosa + E coli infection (13.0%). CONCLUSIONS: The results showed a high prevalence of SSIs among patients attending the gastrointestinal tract surgical unit and the most prevalent microorganism isolated from them was E coli. Measures should be taken to reduce the magnitude of SSI by mitigating the identified associated factors.

Role of LmeA, a Mycobacterial Periplasmic Protein, in Maintaining the Mannosyltransferase MptA and Its Product Lipomannan under Stress.

The mycobacterial cell envelope has a diderm structure, composed of an outer mycomembrane, an arabinogalactan-peptidoglycan cell wall, a periplasm, and an inner membrane. Lipomannan (LM) and lipoarabinomannan (LAM) are structural and immunomodulatory components of this cell envelope. LM/LAM biosynthesis involves a number of mannosyltransferases and acyltransferases, and MptA is an α1,6-mannosyltransferase involved in the final extension of the mannan chain. Recently, we reported the periplasmic protein LmeA being involved in the maturation of the mannan backbone in Mycobacterium smegmatis Here, we examined the role of LmeA under stress conditions. We found that lmeA transcription was upregulated under two stress conditions: stationary growth phase and nutrient starvation. Under both conditions, LAM was decreased, but LM was relatively stable, suggesting that maintaining the cellular level of LM under stress is important. Surprisingly, the protein levels of MptA were decreased in an lmeA deletion (ΔlmeA) mutant under both stress conditions. The transcript levels of mptA in the ΔlmeA mutant were similar to or even higher than those in the wild type, indicating that the decrease of MptA protein was a posttranscriptional event. The ΔlmeA mutant was unable to maintain the cellular level of LM under stress, consistent with the decrease in MptA. Even during active growth, overexpression of LmeA led the cells to produce more LM and become more resistant to several antibiotics. Altogether, our study reveals the roles of LmeA in the homeostasis of the MptA mannosyltransferase, particularly under stress conditions, ensuring the stable expression of LM and the maintenance of cell envelope integrity.IMPORTANCE Mycobacteria differentially regulate the cellular amounts of lipoglycans in response to environmental changes, but the molecular mechanisms of this regulation remain unknown. Here, we demonstrate that cellular lipoarabinomannan (LAM) levels rapidly decline under two stress conditions, stationary growth phase and nutrient starvation, while the levels of another related lipoglycan, lipomannan (LM), stay relatively constant. The persistence of LM under stress correlated with the maintenance of two key mannosyltransferases, MptA and MptC, in the LM biosynthetic pathway. We further showed that the stress exposures lead to the upregulation of lmeA gene expression and that the periplasmic protein LmeA plays a key role in maintaining the enzyme MptA and its product LM under stress conditions. These findings reveal new aspects of how lipoglycan biosynthesis is regulated under stress conditions in mycobacteria.

A novel tool for improving the interpretation of isotope bone scans in metastatic prostate cancer.

OBJECTIVES: The isotope bone scan (IBS) is the gold-standard imaging modality for detecting skeletal metastases as part of prostate cancer staging. However, its clinical utility for assessing skeletal metastatic burden is limited due to the need for subjective interpretation. We designed and tested a novel custom software tool, the Metastatic Bone Scan Tool (MetsBST), aimed at improving interpretation of IBSs, and compared its performance with that of an established software programme. METHODS: We used IBS images from 62 patients diagnosed with prostate cancer and suspected bone metastases to design and implement MetsBST in MATLAB by defining thresholds used to identify the texture and size of metastatic bone lesions. The results of MetsBST were compared with those of the commercially available automated Bone Scan Index (aBSI) with regression analysis. RESULTS: There was strong agreement between the MetsBST and aBSI results (R2 = 0.9189). In a subregional analysis, MetsBST quantified the extent of metastatic disease in multiple bone sites in patients receiving multimodality therapy (radium-223 and external beam radiotherapy) to illustrate the differences in bone metastatic response to different treatments. CONCLUSION: The results of MetsBST and the commercial software aBSI were highly consistent. MetsBST introduces novel clinical utility by its ability to differentiate between the responses of different bone metastases to multimodality therapies. ADVANCES IN KNOWLEDGE: MetsBST reduces the variability in assessment of tumour burden caused by subjective interpretation. Therefore, it is a useful aid to physicians reporting nuclear medicine scans, and may improve decision-making in the treatment of metastatic prostate cancer.

Fiducial markers visibility and artefacts in prostate cancer radiotherapy multi-modality imaging.

BACKGROUND: In this study, a novel pelvic phantom was developed and used to assess the visibility and presence of artefacts from different types of commercial fiducial markers (FMs) on multi-modality imaging relevant to prostate cancer. METHODS AND MATERIALS: The phantom was designed with 3D printed hollow cubes in the centre. These cubes were filled with gel to mimic the prostate gland and two parallel PVC rods were used to mimic bones in the pelvic region. Each cube was filled with gelatine and three unique FMs were positioned with a clinically-relevant spatial distribution. The FMs investigated were; Gold Marker (GM) CIVCO, GM RiverPoint, GM Gold Anchor (GA) line and ball shape, and polymer marker (PM) from CIVCO. The phantom was scanned using several imaging modalities typically used to image prostate cancer patients; MRI, CT, CBCT, planar kV-pair, ExacTrac, 6MV, 2.5MV and integrated EPID imaging. The visibility of the markers and any observed artefacts in the phantom were compared to in-vivo scans of prostate cancer patients with FMs. RESULTS: All GMs were visible in volumetric scans, however, they also had the most visible artefacts on CT and CBCT scans, with the magnitude of artefacts increasing with FM size. PM FMs had the least visible artefacts in volumetric scans but they were not visible on portal images and had poor visibility on lateral kV images. The smallest diameter GMs (GA) were the most difficult GMs to identify on lateral kV images. CONCLUSION: The choice between different FMs is also dependent on the adopted IGRT strategy. PM was found to be superior to investigated gold markers in the most commonly used modalities in the management of prostate cancer; CT, CBCT and MRI imaging.

Machine learning for radiomics-based multimodality and multiparametric modeling.

Due to the recent developments of both hardware and software technologies, multimodality medical imaging techniques have been increasingly applied in clinical practice and research studies. Previously, the application of multimodality imaging in oncology has been mainly related to combining anatomical and functional imaging to improve diagnostic specificity and/or target definition, such as positron emission tomography/computed tomography (PET/CT) and single-photon emission CT (SPECT)/CT. More recently, the fusion of various images, such as multiparametric magnetic resonance imaging (MRI) sequences, different PET tracer images, PET/MRI, has become more prevalent, which has enabled more comprehensive characterization of the tumor phenotype. In order to take advantage of these valuable multimodal data for clinical decision making using radiomics, we present two ways to implement the multimodal image analysis, namely radiomic (handcrafted feature) based and deep learning (machine learned feature) based methods. Applying advanced machine (deep) learning algorithms across multimodality images have shown better results compared with single modality modeling for prognostic and/or prediction of clinical outcomes. This holds great potentials for providing more personalized treatment for patients and achieve better outcomes.

Computed Tomography-based Radiomics for Risk Stratification in Prostate Cancer.

PURPOSE: To explore the role of Computed tomography (CT)-based radiomics features in prostate cancer risk stratification. METHODS AND MATERIALS: The study population consisted of 506 patients with prostate cancer collected from a clinically annotated database. After applying exclusion criteria, 342 patients were included in the final analysis. CT-based radiomics features were extracted from planning CT scans for prostate gland-only structure, and machine learning was used to train models for Gleason score (GS) and risk group (RG) classifications. Repeated cross-validation was used. The discriminatory performance of the developed models was assessed using receiver operating characteristic area under the curve (AUC) analysis. RESULTS: Classifiers using CT-based radiomics features distinguished between GS ≤ 6 versus GS ≥ 7 with AUC = 0.90 and GS 7(3 + 4) versus GS 7(4 + 3) with AUC = 0.98. Developed classifiers also showed excellent performance in distinguishing low versus high RG (AUC = 0.96) and low versus intermediate RG (AUC = 1.00), but poorer performance was observed for GS 7 versus GS > 7 (AUC = 0.69). An overall modest performance was observed for validation on holdout data sets with the highest AUC of 0.75 for classifiers of low versus high RG and an AUC of 0.70 for GS 7 versus GS > 7. CONCLUSIONS: Our results show that radiomics features from routinely acquired planning CT scans could provide insights into prostate cancer aggressiveness in a noninvasive manner. Assessing models on training data sets, the classifiers were especially accurate in discerning high-risk from low-risk patients and in classifying GS 7 versus GS > 7 and GS 7(3 + 4) versus G7(4 + 3); however, classifiers were less adept at distinguishing high RG versus intermediate RG. External validation and prospective studies are warranted to verify the presented findings. These findings could potentially guide targeted radiation therapy strategies in radical intent radiation therapy for prostate cancer.

Preclinical Evaluation of Dose-Volume Effects and Lung Toxicity Occurring In and Out-of-Field.

PURPOSE: The aim of this study was to define the dose and dose-volume relationship of radiation-induced pulmonary toxicities occurring in and out-of-field in mouse models of early inflammatory and late fibrotic response. MATERIALS AND METHODS: Early radiation-induced inflammation and fibrosis were investigated in C3H/NeJ and C57BL/6J mice, respectively. Animals were irradiated with 20 Gy delivered to the upper region of the right lung as a single fraction or as 3 consecutive fractions using the Small Animal Radiation Research Platform (Xstrahl Inc, Camberley, UK). Cone beam computed tomography was performed for image guidance before irradiation and to monitor late toxicity. Histologic sections were examined for neutrophil and macrophage infiltration as markers of early inflammatory response and type I collagen staining as a marker of late-occurring fibrosis. Correlation was evaluated with the dose-volume histogram parameters calculated for individual mice and changes in the observed cone beam computed tomography values. RESULTS: Mean lung dose and the volume receiving over 10 Gy (V10) showed significant correlation with late responses for single and fractionated exposures in directly targeted volumes. Responses observed outside the target volume were attributed to nontargeted effects and showed no dependence on either mean lung dose or V10. CONCLUSIONS: Quantitative assessment of normal tissue response closely correlates early and late pulmonary response with clinical parameters, demonstrating this approach as a potential tool to facilitate clinical translation of preclinical studies. Out-of-field effects were observed but did not correlate with dosimetric parameters, suggesting that nontargeted effects may have a role in driving toxicities outside the treatment field.

Deletion of PimE mannosyltransferase results in increased copper sensitivity in Mycobacterium smegmatis.

The unique cell envelope structure of Mycobacterium tuberculosis is fundamental to its pathogenesis. Phosphatidylinositol (PI)-anchored glycolipids, such as phosphatidylinositol mannosides (PIMs), lipomannan and lipoarabinomannan, are essential components of the cell envelope widely conserved among mycobacteria, but their roles in the cell envelope integrity are not fully understood. We previously identified PimE in Mycobacterium smegmatis, a nonpathogenic model organism, as a mannosyltransferase that catalyzes the fifth mannose transfer for the biosynthesis of hexamannosyl PIMs. Our analyses, reported here, further demonstrate that the growth of the pimE deletion mutant (ΔpimE) is defective in the presence of copper. We first found that the small colony phenotype of ΔpimE on a solid Middlebrook 7H10 agar surface was alleviated when grown on M63 agar. Comparative analysis of the two media led us to identify copper in Middlebrook 7H10 as the cause of growth retardation seen in ΔpimE. We further demonstrated that ΔpimE is sensitized to several antibiotics, but the increased sensitivities were independent of the presence of copper. We conclude that the deletion of the pimE gene does not cause growth defects under optimal growth conditions, but makes the cell envelope vulnerable to toxic compounds such as copper and antibiotics.

Efficacy of a rectal spacer with prostate SABR-first UK experience.

OBJECTIVE: This study assessed the use of implanted hydrogel rectal spacers for stereotactic ablative radiotherapy-volumetric modulated arc therapy (SABR-VMAT) patients, investigating practicality, dosimetric impact, normal tissue complication probability (NTCP) and early toxicity. METHODS: Data from the first 6 patients treated within a prostate SABR and rectal spacer trial were examined to determine spacer insertion tolerability, resultant changes in treatment planning and dosimetry and early toxicity effects. CT scans acquired prior to spacer insertion were used to generate SABR plans which were compared to post-insertion plans. Plans were evaluated for target coverage, conformity, and organs at risk doses with NTCPs also determined from resultant dose fluences. Early toxicity data were also collected. RESULTS: All patients had successful spacer insertion under local anaesthetic with maximal Grade 1 toxicity. All plans were highly conformal, with no significant differences in clinical target volume dose coverage between pre- and post-spacer plans. Substantial improvements in rectal dose metrics were observed in post-spacer plans, e.g. rectal volume receiving 36 Gy reduced by ≥42% for all patients. Median NTCP for Grade 2 + rectal bleeding significantly decreased from 4.9 to 0.8% with the use of a rectal spacer (p = 0.031). To date, two episodes of acute Grade 1 proctitis have been reported following treatment. CONCLUSION: The spacer resulted in clinically and statistically significant reduction in rectal doses for all patients. Advances in knowledge: This is one of the first studies to investigate the efficacy of a hydrogel spacer in prostate SABR treatments. Observed dose sparing of the rectum is predicted to result in meaningful clinical benefit.

Small field dosimetry for the small animal radiotherapy research platform (SARRP).

BACKGROUND: Preclinical radiation biology has become increasingly sophisticated due to the implementation of advanced small animal image guided radiation platforms into laboratory investigation. These small animal radiotherapy devices enable state-of-the-art image guided therapy (IGRT) research to be performed by combining high-resolution cone beam computed tomography (CBCT) imaging with an isocentric irradiation system. Such platforms are capable of replicating modern clinical systems similar to those that integrate a linear accelerator with on-board CBCT image guidance. METHODS: In this study, we present a dosimetric evaluation of the small animal radiotherapy research platform (SARRP, Xstrahl Inc.) focusing on small field dosimetry. Physical dosimetry was assessed using ion chamber for calibration and radiochromic film, investigating the impact of beam focus size on the dose rate output as well as beam characteristics (beam shape and penumbra). Two film analysis tools) have been used to assess the dose output using the 0.5 mm diameter aperture. RESULTS: Good agreement (between 1.7-3%) was found between the measured physical doses and the data provided by Xstrahl for all apertures used. Furthermore, all small field dosimetry data are in good agreement for both film reading methods and with our Monte Carlo simulations for both focal spot sizes. Furthermore, the small focal spot has been shown to produce a more homogenous beam with more stable penumbra over time. CONCLUSIONS: FilmQA Pro is a suitable tool for small field dosimetry, with a sufficiently small sampling area (0.1 mm) to ensure an accurate measurement. The electron beam focus should be chosen with care as this can potentially impact on beam stability and reproducibility.

A novel CBCT-based method for derivation of CTV-PTV margins for prostate and pelvic lymph nodes treated with stereotactic ablative radiotherapy.

BACKGROUND: Traditional CTV-PTV margin recipes are not generally applicable in the situation of stereotactic ablative radiotherapy (SABR) treatments of multiple target volumes with a single isocentre. In this work, we present a novel geometric method of margin derivation based on CBCT-derived anatomical data. METHODS: Twenty patients with high-risk localized prostate cancer were selected for retrospective review. Individual volumes of interest (prostate, prostate and seminal vesicles and pelvic lymph nodes) were delineated on five representative CBCTs and registered to the planning CT using two registration protocols: bone match or prostate-based soft tissue match. Margins were incrementally expanded around composite CTV structures until 95% overlap was achieved. RESULTS: CTV-PTV margins of 5.2, 6.5 and 7.6 mm were required for prostate, prostate and seminal vesicles and pelvic lymph nodes respectively using a prostate matching protocol. For the prostate and seminal vesicle structures, margins calculated using our method displayed good agreement with a conventional margin recipe (within ±1.0 mm). CONCLUSIONS: We have presented an alternative method of CTV-PTV margin derivation that is applicable to SABR treatments with more than one isocentric target. These results have informed an institutional trial of prostate and pelvic nodal SABR in men with high-risk localized prostate cancer.

Inhibition of ataxia telangiectasia related-3 (ATR) improves therapeutic index in preclinical models of non-small cell lung cancer (NSCLC) radiotherapy.

BACKGROUND AND PURPOSE: To evaluate the impact of ATR inhibition using AZD6738 in combination with radiotherapy on the response of non-small cell lung cancer (NSCLC) tumour models and a murine model of radiation induced fibrosis. MATERIALS AND METHODS: AZD6738 was evaluated as a monotherapy and in combination with radiation in vitro and in vivo using A549 and H460 NSCLC models. Radiation induced pulmonary fibrosis was evaluated by cone beam computed tomography (CBCT) and histological staining. RESULTS: AZD6738 specifically inhibits ATR kinase and enhanced radiobiological response in NSCLC models but not in human bronchial epithelial cells (HBECs) in vitro. Significant tumour growth delay was observed in cell line derived xenografts (CDXs) of H460 cells (p<0.05) which were less significant in A549 cells. Combination of AZD6738 with radiotherapy showed no significant change in lung tissue density by CBCT (p>0.5) and histological scoring of radiation induced fibrosis (p>0.5). CONCLUSION: Inhibition of ATR with AZD6738 in combination with radiotherapy increases tumour growth delay without observable augmentation of late radiation induced toxicity further underpinning translation towards clinical evaluation in NSCLC.

Prostate cancer treated with brachytherapy; an exploratory study of dose-dependent biomarkers and quality of life.

BACKGROUND: Low-dose-rate permanent prostate brachytherapy (PPB) is an attractive treatment option for patients with localised prostate cancer with excellent outcomes. As standard CT-based post-implant dosimetry often correlates poorly with late treatment-related toxicity, this exploratory (proof of concept) study was conducted to investigate correlations between radiation - induced DNA damage biomarker levels, and acute and late bowel, urinary, and sexual toxicity. METHODS: Twelve patients treated with 125I PPB monotherapy (145Gy) for prostate cancer were included in this prospective study. Post-implant CT based dosimetry assessed the minimum dose encompassing 90% (D90%) of the whole prostate volume (global), sub-regions of the prostate (12 sectors) and the near maximum doses (D0.1cc, D2cc) for the rectum and bladder. Six blood samples were collected from each patient; pre-treatment, 1 h (h), 4 h, 24 h post-implant, at 4 weeks (w) and at 3 months (m). DNA double strand breaks were investigated by staining the blood samples with immunofluorescence antibodies to γH2AX and 53BP1 proteins (γH2AX/53BP1). Patient self-scored quality of life from the Expanded Prostate Cancer Index Composite (EPIC) were obtained at baseline, 1 m, 3 m, 6 m, 9 m, 1 year (y), 2y and 3y post-treatment. Spearman's correlation coefficients were used to evaluate correlations between temporal changes in γH2AX/53BP1, dose and toxicity. RESULTS: The minimum follow up was 2 years. Population mean prostate D90% was 144.6 ± 12.1 Gy and rectal near maximum dose D0.1cc = 153.0 ± 30.8 Gy and D2cc = 62.7 ± 12.1 Gy and for the bladder D0.1cc = 123.1 ± 27.0 Gy and D2cc = 70.9 ± 11.9 Gy. Changes in EPIC scores from baseline showed high positive correlation between acute toxicity and late toxicity for both urinary and bowel symptoms. Increased production of γH2AX/53BP1 at 24 h relative to baseline positively correlated with late bowel symptoms. Overall, no correlations were observed between dose metrics (prostate global or sector doses) and γH2AX/53BP1 foci counts. CONCLUSIONS: Our results show that a prompt increase in γH2AX/53BP1foci at 24 h post-implant relative to baseline may be a useful measure to assess elevated risk of late RT - related toxicities for PPB patients. A subsequent investigation recruiting a larger cohort of patients is warranted to verify our findings.

Class solutions for SABR-VMAT for high-risk prostate cancer with and without elective nodal irradiation.

BACKGROUND: The purpose of this study is to find the optimal planning settings for prostate SABR-VMAT for high-risk prostate cancer patients irradiated to prostate only (PO) or prostate and pelvic lymph nodes (PPLN). METHODS: For 10 patients, plans using 6MV flattened, flattening-filter-free (FFF) 6MV (6 F) and FFF 10MV (10 F) photon beams with full and partial arc arrangements were generated and compared. The prescribed dose was 40Gy to the prostate with 25Gy to the PLN in 5 fractions. Plans were then evaluated for PTV coverage, dose fall-off, and OAR doses. The number of monitor units and the treatment delivery times were also compared. Statistical differences were evaluated using a paired sample Wilcoxon signed rank test with a significance level of 0.05%. RESULTS: A total of 150 plans were generated for this study. Acceptable PO plans were obtained using single arcs, while two arcs were necessary for PPLN. All plans were highly conformal (CI ≥1.3 and CN ≥0.90) with no significant differences in the PTV dose coverage. 6MV plans required significantly longer treatment time and had higher dose spillage compared to FFF plans. Superior plans were obtained using 10 F 300° partial arcs for PO with the lowest rectal dose, dose spillage and the shortest treatment times. For PPLN, 6 F and 10 F plans were equivalent. CONCLUSIONS: SABR-VMAT with FFF photon beams offers a clear benefit with respect to shorter treatment delivery times and reduced dose spillage. Class solutions using a single 10 F 300° arc for PO and two 10 F or 6 F partial 300° arcs for PPLN are proposed.