PurposeTo demonstrate feasibility and toxicity of linear accelerator–based stereotactic radiation therapy boost (SBRT) for prostate cancer, mimicking a high-dose-rate brachytherapy boost.Methods and MaterialsA phase 1 sequential dose escalation study of SBRT compared 20 Gy, 22 Gy, and 24 Gy to the prostate and 25 Gy, 27.5 Gy, and 30 Gy to the gross tumor volume in 2 fractions, combined with 46 Gy in 23 fractions of external beam radiation. Feasibility of dose escalation (volume receiving 125% and 150% of the dose) while meeting organ-at-risk dose constraints, grade 2 acute and late gastrointestinal and genitourinary toxicity, and freedom from biochemical failure were secondary endpoints.ResultsThirty-six men with intermediate- and high-risk prostate cancer were enrolled with a median follow-up of 24 months. Sixty-four percent of patients had high-risk features. Nine men were enrolled to dose level 1, 6 to level 2, and 6 to level 3. Another 15 patients were treated at dose level 3 on the continuation study. Dose level 3 achieved superior 125% (23.75 Gy) and 150% (28.5 Gy) dose compared to dose levels 1 and 2, with minimal differences in organ-at-risk doses. Kaplan-Meier estimate of freedom from biochemical failure at 3 years was 93.3%. There were no late grade 2 or 3 gastrointestinal events. The late grade 2 genitourinary toxicity at 2 years was 19.3%. Prostate-specific membrane antigen positron emission tomography was performed at 2 years with no local recurrences.ConclusionsWe have shown that a linear accelerator–based SBRT boost for prostate cancer is feasible and can achieve doses comparable to high-dose-rate boost up to the 150% isodose volumes. Rectal, bladder, and urethral doses remained low, and long-term toxicity was the same as or better than previous reports from high-dose-rate or low-dose-rate boost protocols.

BackgroundNext-generation sequencing and ‘omics’ platforms are used extensively in plant biology research to unravel new genomes and study their interactions with abiotic and biotic agents in the growth environment. Despite the availability of a large and growing number of genomic data sets, there are only limited resources providing highly-curated and up-to-date metabolic and regulatory networks for plant pathways.ResultsUsing PathVisio, a pathway editor tool associated with WikiPathways, we created a gene interaction network of 430 rice (Oryza sativa) genes involved in the seed development process by curating interactions reported in the published literature. We then applied an InParanoid-based homology search to these genes and used the resulting gene clusters to identify 351 Arabidopsis thaliana genes. Using this list of homologous genes, we constructed a seed development network in Arabidopsis by processing the gene list and the rice network through a Perl utility software called Pathway GeneSWAPPER developed by us. In order to demonstrate the utility of these networks in generating testable hypotheses and preliminary analysis prior to more in-depth downstream analysis, we used the expression viewer and statistical analysis features of PathVisio to analyze publicly-available and published microarray gene expression data sets on diurnal photoperiod response and the seed development time course to discover patterns of coexpressed genes found in the rice and Arabidopsis seed development networks. These seed development networks described herein, along with other plant pathways and networks, are freely available on the plant pathways portal at WikiPathways (http://plants.wikipathways.org).ConclusionIn collaboration with the WikiPathways project we present a community curation and analysis platform for plant biologists where registered users can freely create, edit, share and monitor pathways supported by published literature. We describe the curation and annotation of a seed development network in rice, and the projection of a similar, gene homology-based network in Arabidopsis. We also demonstrate the utility of the Pathway GeneSWAPPER (PGS) application in saving valuable time and labor when a reference network in one species compiled in GPML format is used to project a similar network in another species based on gene homology.Electronic supplementary materialThe online version of this article (doi:10.1186/1939-8433-6-14) contains supplementary material, which is available to authorized users.

Introduction Aimed to develop a simple and robust volumetric modulated arc radiotherapy (VMAT) solution for comprehensive lymph node (CLN) breast cancer without increase in low‐dose wash. Methods Forty CLN‐breast patient data sets were utilised to develop a knowledge‐based planning (KBP) VMAT model, which limits low‐dose wash using iterative learning and base‐tangential methods as benchmark. Another twenty data sets were employed to validate the model comparing KBP‐generated ipsilateral VMAT (ipsi‐VMAT) plans against the benchmarked hybrid (h)‐VMAT (departmental standard) and bowtie‐VMAT (published best practice) methods. Planning target volume (PTV), conformity/homogeneity index (CI/HI), organ‐at‐risk (OAR), remaining‐volume‐at‐risk (RVR) and blinded radiation oncologist (RO) plan preference were evaluated. Results Ipsi‐ and bowtie‐VMAT plans were dosimetrically equivalent, achieving greater nodal target coverage (P < 0.05) compared to h‐VMAT with minor reduction in breast coverage. CI was enhanced for a small reduction in breast HI with improved dose sparing to ipsilateral‐lung and humeral head (P < 0.05) at immaterial expense to spinal cord. Significantly, low‐dose wash to OARs and RVR were comparable between all plan types demonstrating a simple VMAT class solution robust to patient‐specific anatomic variation can be applied to CLN breast without need for complex beam modification (hybrid plans, avoidance sectors or other). This result was supported by blinded RO review. Conclusions A simple and robust ipsilateral VMAT class solution for CLN breast generated using iterative KBP modelling can achieve clinically acceptable target coverage and OAR sparing without unwanted increase in low‐dose wash associated with increased second malignancy risk.

Introduction: RapidPlan (RP), a knowledge-based planning system, aims to consistently improve plan quality and efficiency in radiotherapy. During the early stages of implementation, some of the challenges include knowing how to optimally train a model and how to integrate RP into a department. We discuss our experience with the implementation of RP into our institution. Methods: We reviewed all patients planned using RP over a 7-month period following inception in our department. Our primary outcome was clinically acceptable plans (used for treatment) with secondary outcomes including model performance and a comparison of efficiency and plan quality between RP and manual planning (MP). Results: Between November 2017 and May 2018, 496 patients were simulated, of which 217 (43.8%) had an available model. RP successfully created a clinically acceptable plan in 87.2% of eligible patients. The individual success of the 24 models ranged from 50% to 100%, with more than 90% success in 15 (62.5%) of the models. In 40% of plans, success was achieved on the 1st optimisation. The overall planning time with RP was reduced by up to 95% compared with MP times. The quality of the RP plans was at least equivalent to historical MP plans in terms of target coverage and organ at risk constraints. Conclusion: While initially time-consuming and resource-intensive to implement, plans optimised with RP demonstrate clinically acceptable plan quality, while significantly improving the efficiency of a department, suggesting RP and its application is a highly effective tool in clinical practice.

Introduction: This study aimed to develop a single-isocentre volumetric modulated arc therapy (si-VMAT) technique for multiple brain metastases using knowledge-based planning software, comparing it with a multipleisocentre stereotactic radiosurgery (mi-SRS) planning approach. Methods: Twenty-six si-VMAT plans were created and uploaded into RapidPlan TM (RP) to create a si-VMAT model. Ten patients, with 2 to 6 metastases (mets), were planned with a si-VMAT technique utilising RP, and a mi-SRS technique on Brainlab iPlan. Paddick Conformity Index (PCI) was used to compare conformity. The volumes of the brain receiving 15Gy, 12Gy, 10Gy, 7.5Gy and 3Gy were also compared. Retrospective treatment times from the last eight patients treated were averaged for pre-imaging and beam on time to calculate treatment times for both techniques. Results: There was a significant difference in the PCI scores for the mi-SRS plans (M = 0.667, SD = 0.114) and si-VMAT plans (M = 0.728, SD = 0.088), with PCI values suggesting better prescription dose conformity with the si-VMAT technique (P = 0.014). Percentage of total brain volume receiving low-dose wash at four of the five different dose levels was significantly less (P < 0.05) with mi-SRS. Average time to treat a single met with current mi-SRS technique is 25.7 min, with each additional met requiring this same amount of time. The average time to treat 2-3 mets using si-VMAT would be 25.3 min and 4+ metastases 33.5 min. Conclusion: A knowledge-based si-VMAT approach was efficient in planning and treating multi metastases while achieving clinically acceptable dosimetry with respect to dose conformity and low-dose fall off.