FRoG: a fast robust analytical dose engine on GPU for p, 4He, 12C and 16O particle therapy

Radiotherapy with protons and heavier ions landmarks a novel era in the field of highprecision cancer therapy. To identify patients most benefiting from this technologically demanding therapy, fast assessment of comparative treatment plans utilizing different ion species is urgently needed. Moreover, to overcome uncertainties of actual in-vivo physical dose distribution and biological effects elicited by different radiation qualities, development of a reliable high-throughput algorithm is required. To this end, we engineered a unique graphics processing unit (GPU) based software architecture allowing rapid and robust dose calculation. Fast dose Recalculation on GPU (FRoG) currently operates with four particle beams, i.e., raster-scanning proton, helium, carbon and oxygen ions. Designed to perform fast and accurate calculations for both physical and biophysical quantities, FRoG operates an advanced analytical pencil beam algorithm using parallelized procedures on a GPU. Clinicians and medical physicists can assess both dose and dose-averaged linear energy transfer (LET) distributions for proton therapy (and in turn effective dose by applying variable RBE schemes) to further scrutinize plans for acceptance or potential re-planning purposes within minutes. In addition, various biological model predictions are readily accessible for heavy ion therapy, such as the local effect model (LEM) and microdosimetric kinetic model (MKM). FRoG has been extensively benchmarked against gold standard Monte Carlo simulations and experimental data. Evaluating against commercial treatment planning systems demonstrates the strength of FRoG in better predicting dose distributions in complex clinical settings. In preparation for the upcoming translation of novel ions, case-/disease-specific ion-beam selection and advanced multi-particle treatment modalities at the Heidelberg Ion-beam Therapy Center (HIT), we quantified the accuracy limits in particle therapy treatment planning under complex heterogeneous conditions for the four ions (p, 4He, 12C, 16O) for various dose engines, both analytical algorithms and Monte Carlo code. Devised in-house, FRoG landmarks the first GPU-based treatment planning system (non commercial) for raster-scanning 4He ion beams, with an official treatment program set for early 2020. Since its inception, FRoG has been installed and is currently in operation clinically at four centers across Europe: HIT (Heidelberg, Germany), CNAO (Pavia, Italy) , Aarhus (Denmark) and the Normandy Proton Therapy Center (Caen, France). Here, the development and validation of FRoG as well as clinical investigations and advanced topics in particle therapy dose calculation are covered. The thesis is presented in cumulative format and comprises four peer reviewed publications

Development and benchmarking of a dose rate engine for raster‐scanned FLASH helium ions

Background:Radiotherapy with charged particles at high dose and ultra-highdose rate (uHDR) is a promising technique to further increase the therapeuticindex of patient treatments. Dose rate is a key quantity to predict the so-calledFLASH effect at uHDR settings. However, recent works introduced varying cal-culation models to report dose rate,which is susceptible to the delivery method,scanning path (in active beam delivery) and beam intensity.Purpose:This work introduces an analytical dose rate calculation engine forraster scanned charged particle beams that is able to predict dose rate from theirradiation plan and recorded beam intensity. The importance of standardizeddose rate calculation methods is explored here.Methods:Dose is obtained with an analytical pencil beam algorithm, usingpre-calculated databases for integrated depth dose distributions and lateralpenumbra. Dose rate is then calculated by combining dose information withthe respective particle fluence (i.e., time information) using three dose-rate-calculation models (mean, instantaneous, and threshold-based). Dose ratepredictions for all three models are compared to uHDR helium ion beam (145.7MeV/u, range in water of approximatively 14.6 cm) measurements performe

Overcoming hypoxia-induced tumor radioresistance in non-small cell lung cancer by targeting DNA-dependent protein kinase in combination with carbon ion irradiation

Background: Hypoxia-induced radioresistance constitutes a major obstacle for a curative treatment of cancer. The aim of this study was to investigate effects of photon and carbon ion irradiation in combination with inhibitors of DNA-Damage Response (DDR) on tumor cell radiosensitivity under hypoxic conditions. Methods: Human non-small cell lung cancer (NSCLC) models, A549 and H1437, were irradiated with dose series of photon and carbon ions under hypoxia (1% O2) vs. normoxic conditions (21% O2). Clonogenic survival was studied after dual combinations of radiotherapy with inhibitors of DNA-dependent Protein Kinase (DNAPKi, M3814) and ATM serine/threonine kinase (ATMi). Results: The OER at 30% survival for photon irradiation of A549 cells was 1.4. The maximal oxygen effect measured as survival ratio was 2.34 at 8 Gy photon irradiation of A549 cells. In contrast, no significant oxygen effect was found after carbon ion irradiation. Accordingly, the relative effect of 6 Gy carbon ions was determined as 3.8 under normoxia and. 4.11 under hypoxia. ATM and DNA-PK inhibitors dose dependently sensitized tumor cells for both radiation qualities. For 100 nM DNAPKi the survival ratio at 4 Gy more than doubled from 1.59 under normoxia to 3.3 under hypoxia revealing a strong radiosensitizing effect under hypoxic conditions. In contrast, this ratio only moderately increased after photon irradiation and ATMi under hypoxia. The most effective treatment was combined carbon ion irradiation and DNA damage repair inhibition. Conclusions: Carbon ions efficiently eradicate hypoxic tumor cells. Both, ATMi and DNAPKi elicit radiosensitizing effects. DNAPKi preferentially sensitizes hypoxic cells to radiotherapy

Biophysical modeling and experimental validation of relative biological effectiveness (RBE) for 4He ion beam therapy

Background: Helium (4He) ion beam therapy provides favorable biophysical characteristics compared to currently administered particle therapies, i.e., reduced lateral scattering and enhanced biological damage to deep-seated tumors like heavier ions, while simultaneously lessened particle fragmentation in distal healthy tissues as observed with lighter protons. Despite these biophysical advantages, raster-scanning 4He ion therapy remains poorly explored e.g., clinical translational is hampered by the lack of reliable and robust estimation of physical and radiobiological uncertainties. Therefore, prior to the upcoming 4He ion therapy program at the Heidelberg Ion-beam Therapy Center (HIT), we aimed to characterize the biophysical phenomena of 4He ion beams and various aspects of the associated models for clinical integration. Methods: Characterization of biological effect for 4He ion beams was performed in both homogenous and patient-like treatment scenarios using innovative models for estimation of relative biological effectiveness (RBE) in silico and their experimental validation using clonogenic cell survival as the gold-standard surrogate. Towards translation of RBE models in patients, the first GPU-based treatment planning system (non-commercial) for raster-scanning 4He ion beams was devised in-house (FRoG). Results: Our data indicate clinically relevant uncertainty of ±5–10% across different model simulations, highlighting their distinct biological and computational methodologies. The in vitro surrogate for highly radio-resistant tissues presented large RBE variability and uncertainty within the clinical dose range. Conclusions: Existing phenomenological and mechanistic/biophysical models were successfully integrated and validated in both Monte Carlo and GPU-accelerated analytical platforms against in vitro experiments, and tested using pristine peaks and clinical fields in highly radio-resistant tissues where models exhibit the greatest RBE uncertainty. Together, these efforts mark an important step towards clinical translation of raster-scanning 4He ion beam therapy to the clinic

Surgery for rheumatic heart disease in the Northern Territory, Australia, 1997-2016: what have we gained?

Background: Between 1964 and 1996, the 10-year survival of patients having valve replacement surgery for rheumatic heart disease (RHD) in the Northern Territory, Australia, was 68%. As medical care has evolved since then, this study aimed to determine whether there has been a corresponding improvement in survival. Methods: A retrospective study of Aboriginal patients with RHD in the Northern Territory, Australia, having their first valve surgery between 1997 and 2016. Survival was examined using Kaplan-Meier and Cox regression analysis. Findings: The cohort included 281 adults and 61 children. The median (IQR) age at first surgery was 31 (18-42) years; 173/342 (51%) had a valve replacement, 113/342 (33%) had a valve repair and 56/342 (16%) had a commissurotomy. There were 93/342 (27%) deaths during a median (IQR) follow-up of 8 (4-12) years. The overall 10-year survival was 70% (95% CI: 64% to 76%). It was 62% (95% CI: 53% to 70%) in those having valve replacement. There were 204/281 (73%) adults with at least 1 preoperative comorbidity. Preoperative comorbidity was associated with earlier death, the risk of death increasing with each comorbidity (HR: 1.3 (95% CI: 1.2 to 1.5), p50 mm Hg before surgery (HR 1.9 (95% CI: 1.2 to 3.1) p=0.007) were independently associated with death. Interpretation: Survival after valve replacement for RHD in this region of Australia has not improved. Although the patients were young, many had multiple comorbidities, which influenced long-term outcomes. The increasing prevalence of complex comorbidity in the region is a barrier to achieving optimal health outcomes

Health and Employment after Fifty (HEAF):A new prospective cohort study

BackgroundDemographic trends in developed countries have prompted governmental policies aimed at extending working lives. However, working beyond the traditional retirement age may not be feasible for those with major health problems of ageing, and depending on occupational and personal circumstances, might be either good or bad for health. To address these uncertainties, we have initiated a new longitudinal study.Methods/designWe recruited some 8000 adults aged 50–64 years from 24 British general practices contributing to the Clinical Practice Research Datalink (CPRD). Participants have completed questionnaires about their work and home circumstances at baseline, and will do so regularly over follow-up, initially for a 5-year period. With their permission, we will access their primary care health records via the CPRD. The inter-relation of changes in employment (with reasons) and changes in health (e.g., major new illnesses, new treatments, mortality) will be examined.DiscussionCPRD linkage allows cost-effective frequent capture of detailed objective health data with which to examine the impact of health on work at older ages and of work on health. Findings will inform government policy and also the design of work for older people and the measures needed to support employment in later life, especially for those with health limitations