Pelvis Treatment Plan Dose Comparison for Proton Therapy Using Single Energy and Dual Energy Computed Tomography Simulation Methods

PURPOSE/OBJECTIVE(S)

In proton therapy, plan robustness is ameliorated by expanding the irradiation volume beyond the target, in order to mitigate setup and proton range uncertainties (RU). A byproduct of this expansion is elevated doses to surrounding organs at risk (OARs) which reduce some of the benefits associated with proton therapy. Dual-energy CT (DECT) has been shown in multiple phantom and animal tissue studies to reduce RU without compromising plan robustness. This study quantifies dosimetric differences between single-energy CT (SECT) and DECT for pelvis patients treated with intensity modulated proton therapy (IMPT).

MATERIALS/METHODS

Under IRB approval, SECT and DECT scans from 25 IMPT pelvis patients were acquired using a CT scanner. Clinical plans were generated on the SECT images using robust optimization settings of 3.5% RU and 5 mm setup uncertainty in a treatment planning system. Subsequently, the clinical plans were recomputed on the corresponding DECT generated SPR-map images. For each patient, target coverage, mean and maximum OAR doses were compared for both image sets.

RESULTS

Comparison of two plans showed systematic differences in target minimum dose (D99%) and V100%. Variations as high as 3.1% with DECT were observed in D99% indicating target under-dosage. On average, use of SECT overestimated V100% by 2.4% when compared to DECT. Since all clinical plans were optimized robustly to meet V95% coverage, higher agreement (<1%) was achieved for V95% (99.9±0.2%), and D95% (99.6±0.3%). DECT relative to SECT indicated slightly higher OAR maximum doses for femoral heads (2.3±2.78%), penile bulb/external genital (1.33±4.00%) and large bowel (0.5±1.25%). Similarly, higher mean dose was observed to rectum (2.08±4.88%), bladder (1.41±0.25%), femoral heads (1.18±6.61%) and penile bulb/external genital (1.78±5.74%) for DECT relative to SECT.

CONCLUSION

Our results show a disparity between evaluated SECT and DECT target and OAR dosimetric parameters. Given the higher accuracies in proton range estimation associated with the use of DECT, its use can imply a potential for more conformal proton plans as well as higher TPS computed target coverage and OAR dose accuracy, both of which enhance overall treatment quality.

Split-filter dual energy computed tomography radiotherapy: From calibration to image guidance

Background and purpose

Dual-energy computed tomography (DECT) is an emerging technology in radiotherapy (RT). Here, we investigate split-filter DECT throughout the RT treatment chain as compared to single-energy CT (SECT).

Materials and methods

DECT scans were acquired with a tin-gold split-filter at 140 kV resulting in a low- and high-energy CT reconstruction (recon). Ten cancer patients (four head-and-neck (HN)​, three rectum​, two anal/pelvis and one abdomen) were DECT scanned without and with iodine administered. A cylindrical and an anthropomorphic HN phantom were scanned with DECT and 120 kV SECT. The DECT images generated were: 120 kV SECT-equivalent (CTmix), virtual monoenergetic images (VMIs), iodine map, virtual non-contrast (VNC), effective atomic number (Zeff), and relative electron density (ρe,w). The clinical utility of these recons was investigated for calibration, delineation, dose calculation and image-guided RT (IGRT).

Results

A calibration curve for 75 keV VMI had a root-mean-square-error (RMSE) of 34 HU in closest agreement with the RSME of SECT calibration. This correlated with a phantom-based dosimetric agreement to SECT of γ1%1mm > 98%. A 40 keV VMI recon was most promising to improve tumor delineation accuracy with an average evaluation score of 1.6 corresponding to "partial improvement". The dosimetric impact of iodine was in general < 2%. For this setup, VNC vs. non-contrast CTmix based dose calculations are considered equivalent. SECT- and DECT-based IGRT was in agreement within the setup uncertainty.

Conclusions

DECT-based RT could be a feasible alternative to SECT providing additional recons to support the different steps of the RT workflow.

Consensus guide on CT-based prediction of stopping-power ratio using a Hounsfield look-up table for proton therapy

BACKGROUND AND PURPOSE

Studies have shown large variations in stopping-power ratio (SPR) prediction from computed tomography (CT) across European proton centres. To standardise this process, a step-by-step guide on specifying a Hounsfield look-up table (HLUT) is presented here.

MATERIALS AND METHODS

The HLUT specification process is divided into six steps: Phantom setup, CT acquisition, CT number extraction, SPR determination, HLUT specification, and HLUT validation. Appropriate CT phantoms have a head- and body-sized part, with tissue-equivalent inserts in regard to X-ray and proton interactions. CT numbers are extracted from a region-of-interest covering the inner 70% of each insert in-plane and several axial CT slices in scan direction. For optimal HLUT specification, the SPR of phantom inserts is measured in a proton beam and the SPR of tabulated human tissues is computed stoichiometrically at 100 MeV. Including both phantom inserts and tabulated human tissues increases HLUT stability. Piecewise linear regressions are performed between CT numbers and SPRs for four tissue groups (lung, adipose, soft tissue, and bone) and then connected with straight lines. Finally, a thorough but simple validation is performed.

RESULTS

The best practices and individual challenges are explained comprehensively for each step. A well-defined strategy for specifying the connection points between the individual line segments of the HLUT is presented. The guide was tested exemplarily on three CT scanners from different vendors, proving its feasibility.

CONCLUSION

The presented step-by-step guide for CT-based HLUT specification with recommendations and examples can contribute to reduce inter-centre variations in SPR prediction.

Dual- and multi-energy CT for particle stopping-power estimation: current state, challenges and potential

Range uncertainty has been a key factor preventing particle radiotherapy from reaching its full physical potential. One of the main contributing sources is the uncertainty in estimating particle stopping power (ρ_s) within patients. Currently, theρ_sdistribution in a patient is derived from a single-energy CT (SECT) scan acquired for treatment planning by converting CT number expressed in Hounsfield units (HU) of each voxel toρ_susing a Hounsfield look-up table (HLUT), also known as the CT calibration curve. HU andρ_sshare a linear relationship with electron density but differ in their additional dependence on elemental composition through different physical properties, i.e. effective atomic number and mean excitation energy, respectively. Because of that, the HLUT approach is particularly sensitive to differences in elemental composition between real human tissues and tissue surrogates as well as tissue variations within and among individual patients. The use of dual-energy CT (DECT) forρ_sprediction has been shown to be effective in reducing the uncertainty inρ_sestimation compared to SECT. The acquisition of CT data over different x-ray spectra yields additional information on the material elemental composition. Recently, multi-energy CT (MECT) has been explored to deduct material-specific information with higher dimensionality, which has the potential to further improve the accuracy ofρ_sestimation. Even though various DECT and MECT methods have been proposed and evaluated over the years, these approaches are still only scarcely implemented in routine clinical practice. In this topical review, we aim at accelerating this translation process by providing: (1) a comprehensive review of the existing DECT/MECT methods forρ_sestimation with their respective strengths and weaknesses; (2) a general review of uncertainties associated with DECT/MECT methods; (3) a general review of different aspects related to clinical implementation of DECT/MECT methods; (4) other potential advanced DECT/MECT applications beyondρ_sestimation.

Trajectories and determinants of left ventricular ejection fraction after first myocardial infarction in current era of primary coronary interventions

Background

Left ventricular ejection fraction (EF) is an independent predictor of adverse outcomes after myocardial infarction (MI). However, contemporary data from the PCI era of MI therapy on trajectories and determinants of EF are scarce.

Purpose

The present study aimed to describe the epidemiology of systolic dysfunction and EF recovery among consecutive patients hospitalized for their first MI.

Methods

Data from a single-centre prospectively-designed AMBITION registry of consecutive patients hospitalized for MI between years 2017 and 2021 at a large tertiary cardiology centre were utilized.

Results

Out of 1593 patients in the registry, 1065 were hospitalized for MI type I and had no previous history of heart failure (HF) or coronary artery disease. Revascularisation was performed in 93.5% of patients: 901 (84.6%) underwent PCI, 89 (8.4%) CABG and 6 (0.6%) both. At discharge, EF&lt;40% was present in 238 (22.3%), EF 40–50% in 326 (30.6%) and EF &gt;50% in 501 (47.0%), respectively. Patients with EF&lt;40% were more often those who suffered subacute and anterior STEMI, had higher heart rate at admission and higher maximal troponin level, and more often HF signs requiring intravenous diuretic therapy (Table 1). In the multivariate Cox analysis, EF&lt;40%, together with age, glomerular filtration rate, glycemia level, clinical signs of HF, and atrial fibrillation were associated with increased mortality risk. Among subjects with EF&lt;40%, the control follow-up EF determined on a median 153 days (IQR 101–407) after discharge was available in 166 patients. Among these, systolic function recovered to EF&gt;50% in 38 (22.9%) and improved to EF 40–50% in 45 (27.1%). Improvement in systolic function to EF&gt;40% was predicted by lower severity of coronary artery atherosclerosis (GENSINI score), by higher discharge EF, by the lower leukocyte count, the absence of atrial fibrillation during MI hospitalization and glycemia level (Table 2). Recovery of systolic function was associated with lower mortality risk (log-rank p=0.012).

Conclusion

In the current era of primary coronary intervention, only 22% of patients after the first MI have EF below 40%. Of them, EF improves in 50%, and full recovery is observed in 23% of patients. Severity or coronary atherosclerosis, inflammatory response to MI, atrial fibrillation and glucose metabolism may all affect EF recovery. These observations provide novel therapeutic targets for EF recovery.

Funding Acknowledgement

Type of funding sources: Public grant(s) – National budget only. Main funding source(s): Ministry of Health, Czech Republic

Interleukin-6 predicts recovery of systolic function after myocardial infarction

Funding Acknowledgements

Type of funding sources: Public grant(s) – National budget only. Main funding source(s): Ministry of Health of the Czech Republic

Background

Interleukin (IL)-6 is an important mediator of the inflammatory response to acute myocardial infarction (MI). Increased IL-6 levels are associated with adverse outcomes after MI. However, there are only limited data on the association of IL-6 levels with recovery of systolic function after MI.

Purpose

The aim of the present study was to evaluate the independent predictive value of IL-6 level for recovery of systolic function among patients hospitalized for their first MI.

Methods

Consecutive patients without previous history of MI or cardiomyopathy with left ventricular ejection fraction (LVEF) ≤40% measured by transthoracic echocardiography upon hospital discharge and available follow-up LVEF evaluated between 3 months and one year since hospital discharge were selected from a prospective registry of MI patients (n=1323).

Results

In total, data from 183 patients (mean age 64.2±11.2, 29% female, mean EF upon discharge 32.6±5.8) were analyzed. In the multivariate linear regression, IL-6 level measured within 24 hours from the hospital admission was positively associated with NT-proBNP, maximal hs-Troponin T a glycemia level and negatively with female gender, total cholesterol and admission systolic blood pressure. During follow-up, LVEF increased by 6.1±9.0% and LVEF recovered to value &gt;50% in 43 (23.5%) patients. In the multivariate analysis, LVEF improvement was predicted by lower IL-6, lower maximal troponin level, female gender, lower heart rate at the time of hospital admission and Killip class I. In the ROC analysis (AUC 0.72, p&lt;0.001), IL-6 ≤ 15.7ng/L had 51% sensitivity and 87% specificity to predict LVEF recovery.

Conclusion

The inflammatory response to MI, as assessed by IL-6, is associated with MI size, glucose and lipid metabolism and is lower in women. IL-6 independently predicts change in LVEF among patients with moderate to severe LV dysfunction. This supports previous findings that IL-6 inhibition can increase myocardial salvage after MI and identifies possible patients that may benefit from targeted therapy.

Experimental assessment of inter-centre variation in stopping-power and range prediction in particle therapy

PURPOSE

Experimental assessment of inter-centre variation and absolute accuracy of stopping-power-ratio (SPR) prediction within 17 particle therapy centres of the European Particle Therapy Network.

MATERIAL AND METHODS

A head and body phantom with seventeen tissue-equivalent materials were scanned consecutively at the participating centres using their individual clinical CT scan protocol and translated into SPR with their in-house CT-number-to-SPR conversion. Inter-centre variation and absolute accuracy in SPR prediction were quantified for three tissue groups: lung, soft tissues and bones. The integral effect on range prediction for typical clinical beams traversing different tissues was determined for representative beam paths for the treatment of primary brain tumours as well as lung and prostate cancer.

RESULTS

An inter-centre variation in SPR prediction (2σ) of 8.7%, 6.3% and 1.5% relative to water was determined for bone, lung and soft-tissue surrogates in the head setup, respectively. Slightly smaller variations were observed in the body phantom (6.2%, 3.1%, 1.3%). This translated into inter-centre variation of integral range prediction (2σ) of 2.9%, 2.6% and 1.3% for typical beam paths of prostate-, lung- and primary brain-tumour treatments, respectively. The absolute error in range exceeded 2% in every fourth participating centre. The consideration of beam hardening and the execution of an independent HLUT validation had a positive effect, on average.

CONCLUSION

The large inter-centre variations in SPR and range prediction justify the currently clinically used margins accounting for range uncertainty, which are of the same magnitude as the inter-centre variation. This study underlines the necessity of higher standardisation in CT-number-to-SPR conversion.

First-In-Human Validation of CT-Based Proton Range Prediction Using Prompt Gamma Imaging in Prostate Cancer Treatments

PURPOSE

Uncertainty in computed tomography (CT)-based range prediction substantially impairs the accuracy of proton therapy. Direct determination of the stopping-power ratio (SPR) from dual-energy CT (DECT) has been proposed (DirectSPR), and initial validation studies in phantoms and biological tissues have proven a high accuracy. However, a thorough validation of range prediction in patients has not yet been achieved by any means. Here, we present the first systematic validation of CT-based proton range prediction in patients using prompt gamma imaging (PGI).

METHODS AND MATERIALS

A PGI slit camera system with improved positioning accuracy, using a floor-based docking station, was used. Its overall uncertainty for range prediction validation was determined experimentally with both x-ray and beam measurements. The accuracy of range prediction in patients was determined from clinical PGI measurements during hypofractionated treatment of 5 patients with prostate cancer - in total 30 fractions with in-room control-CTs. For each pencil-beam-scanning spot, the range shift was obtained by comparing the PGI measurement to a control-CT-based PGI simulation. Three different SPR prediction approaches were applied in simulations: a standard CT-number-to-SPR conversion (Hounsfield look-up table [HLUT]), an adapted HLUT (DECT optimized), and DirectSPR. The spot-wise weighted mean range shift from all spots served as a measure for the accuracy of the respective range prediction approach.

RESULTS

A mean range prediction accuracy of 0.0% ± 0.5%, 0.3% ± 0.4%, and 1.8% ± 0.4% was obtained for DirectSPR, adapted HLUT, and standard HLUT, respectively. The overall validation uncertainty of the second-generation PGI slit camera is about 1 mm (2σ) for all approaches, which is smaller than the range prediction uncertainty for deep-seated tumors.

CONCLUSIONS

For the first time, range prediction accuracy was assessed in clinical routine using PGI range verification in prostate cancer treatments. Both DECT-derived range prediction approaches agree well with the measured proton range from PGI verification, whereas the standard HLUT approach differs relevantly. These results endorse the recent reduction of clinical safety margins in DirectSPR-based treatment planning in our institution.

Characteristics, management, and outcome of infective endocarditis in the Czech Republic: prospective data from the ESC EORP EURO-ENDO registry

INTRODUCTION

Data describing contemporary profile of infective endocarditis (IE) in the Czech Republic are lacking. The aim of this study was to describe the current profile and outcomes of IE patients.

METHODS

Prospectively collected data on consecutive patients admitted for IE diagnosis between April 2016 and March 2018 to 11 main tertiary care cardiac centers in the Czech Republic were used for this analysis.

RESULTS

Among 208 patients, 88 patients (42.3 %) had native valve IE (NVIE), 56 patients (26.9 %) had prosthetic valve IE (PVIE), and 57 patients (27.4 %) had intracardiac device-related IE (CDRIE). The mean age was 61.66±15.54 years. Staphylococcus aureus was the most common etiological agent of IE (27.4 %), whereas Culture negative IE was present in 26.4 % patients. Surgery was performed during hospitalization in 112 (53.8 %) patients. In-hospital death occurred in 21.2 % patients, while 1-year mortality was 40.3 %. In patients, who had an indication for surgery, but the procedure was not performed, mortality was significantly higher (p=0.002).

CONCLUSION

High proportion of culture negative IE and IE related to artificial intra-cardiac materials calls for action. Furthermore, we show that cardiac surgery should be more often contemplated, especially in the presence of risk factors as septic shock and congestive heart failure (Tab. 6, Fig. 1, Ref. 32).

Higher pulsatile index in carotid arteries is associated with adverse outcomes in patients treated by left ventricular assist device

Introduction

Better understanding of vascular changes in patients after implantation of left ventricular assist devices (LVAD) is important to understand and prevent complications of this therapy. Currently, there is substantial lack of data regarding the impact of changes in carotid territory on clinical events in this population. Our aim was to analyze the association between carotid flow patterns and atherosclerotic changes with serious clinical events after LVAD implantation in a prospective single-center study.

Methods

Eighty five patients were included (Heart mate II, n=34; Heart mate 3, n=51; mean age 55±15 years; 13 women). Pulsatile and resistance indexes were calculated and atherosclerotic changes (Belcaro score) were assessed using triplex ultrasound at the 3rd and 6th month after LVAD implantation. Basic clinical and laboratory data were also included into the analyses. The median follow-up time was 982 days [IQR 472–1431].

Results

Pulsatile and resistance index significantly increased between 3rd and 6th month (p=0.036 and p=0.012, respectively). Belcaro score did not change significantly. During the follow-up, 17 patients died, 4 due to stroke. Another 4 patients suffered from non-fatal stroke. Pulsatile index measured at 3rd month was associated with an increased risk of composite outcome of stroke, GIT hemorrhage and all-cause mortality (HR 10.6, 95% CI 2.0–55.2, p=0.005) only in the group of HeartMate 3 patients, while not in patients with HeartMate II (HR 0.96, 95% CI 0.07–12.4, p=0.97), p for interaction between groups 0.04. Association between pulsatile index and the risk of adverse events in patients with HeartMate 3 remained significant after adjustments for age, cause of heart failure and INTERMACS score.

Conclusion

Among patients after LVAD implantation, assessment of carotid flow patterns, pulsatile index in particular, may identify individuals at increased risk of serious clinical complications. Future studies are needed to understand mechanisms leading to increase flow pulsatility in this population.

Funding Acknowledgement

Type of funding source: Public grant(s) – National budget only. Main funding source(s): Ministry of Health of the Czech Republic

Time trends in the relation between the achieved education and the cardiovascular risk factors prevalence and control in general population and in persons with coronary heart disease

Background

Achieved education is the most consistent and powerful socioeconomic status index and the differences in cardiovascular mortality (CV) according to achieved education in the Czech Republic are over a long period among most pronounced in Europe. Higher prevalence of CV risk factors in less educated is the major factor behind their higher CV morbidity and mortality.

Purpose

To analyse the changes in prevalence and control of CV risk factors according to achieved education in general population and in patients with stable CHD and their impact on CV mortality.

Methods

Based on data of 15 590 persons from 7 cross sectional epidemiological surveys carried through the Czech MONICA and post-MONICA project in 1985–2018 in identical 6 districts of the Czech Republic (general population) and on data of 2129 patients from 5 independent descriptive surveys of the Czech EUROASPIRE study in 1995–2018 (patients with stable CHD) time trends of major CV risk factors and their control in respondents with basic, secondary and university education were compared.

Results

The persons from general population as well as patients with CHD with higher education had consistently lower BMI and lower prevalence of obesity, the differences increased in due time (p&lt;0,001), the prevalence of obesity increased in all educational strata (p&lt;0,001). The total and non-HDL cholesterol were higher in lower educational population strata (p&lt;0,01), but not in CHD patients, there was a very pronounced continuous decrease in all educational strata (p&lt;0,001 for trend). Population systolic and diastolic blood pressures and prevalence of hypertension were higher in men and women with basic education (p&lt;0,01) and decreased during the analysed period (p&lt;0,001). In CHD patients the blood pressure was higher only in women. The prevalence of smoking was higher in men with basic education and decreased in all educational strata (p&lt;0,0001), in women the prevalence of smoking increased in women with basic and decreased in women with secondary and university education (p&lt;0,0001), in CHD patients the prevalence of smoking was lower and did not differ according to education. Prevalence of diabetes and of sedentary life style increased and was more prevalent in general as well as in CHD population in persons with lower education.

Conclusion

CV risk gradient in general population and in CHD patients decreased with level of education achieved, was present during the whole analysed period and became more pronounced in the 2016–18 survey. The education based differences were more pronounced in factors influenced by lifestyle (BMI, smoking) and less in factors influenced also by medical therapies (blood pressure, cholesterol levels). The impact on CV mortality is to be expected more pronounced in general CV prevention and less in already treated population. Observation of healthy life style remains a basic problem in CV prevention, particularly in persons with elementary education.

Funding Acknowledgement

Type of funding source: Public grant(s) – National budget only. Main funding source(s): Agency for Medical Research, Ministry of Health of the Czech Republic

Impact of range uncertainty on clinical distributions of linear energy transfer and biological effectiveness in proton therapy

PURPOSE

Increased radiation response after proton irradiation, such as late radiation-induced toxicity, is determined by high dose and elevated linear energy transfer (LET). Steep dose-averaged LET (LET_d ) gradients and elevated LET_d occur at the end of proton range and might be particularly sensitive to uncertainties in range prediction. Therefore, this study quantified LET_d distributions and the impact of range uncertainty in robust dose-optimized proton treatment plans and assessed the biological effect in normal tissues and tumors of patients.

METHODS

For each of six cancer patients (two brain, head-and-neck, and prostate), two nominal treatment plans were robustly dose optimized using single- and multi-field optimization, respectively. For each plan, two additional scenarios with ±3.5% range deviation relative to the nominal plan were derived by global rescaling of stopping-power ratios. Dose and LET_d distributions were calculated for each scenario using the beam parameters of the corresponding nominal plan. The variability in relative biological effectiveness (RBE) and probability of late radiation-induced brain toxicity (P_IC ) was assessed.

RESULTS

The optimization technique (single- vs multi-field) had a negligible impact on the LET_d distributions in the clinical target volume (CTV) and in most organs at risk (OARs). LET_d distributions in the CTV were rather homogeneous with arithmetic mean of LET_d below 3.2 keV/µm and robust against range deviations. The RBE variability within the CTV induced by range uncertainty was small (≤0.05, 95% confidence interval). In OARs, LET_d hotspots (>7 keV/µm) occurred and LET_d distributions were inhomogeneous and sensitive to range deviations. LET_d hotspots and the impact of range deviations were most prominent in OARs of brain tumor patients which translated in RBE values exceeding 1.1 in all brain OARs. The near-maximum predicted P_IC in healthy brain tissue of brain tumor patients was smaller than 5% and occurred adjacent to the CTV. Range deviations induced absolute differences in P_IC up to 1.2%.

CONCLUSIONS

Robust dose optimization generates LET_d distributions in the target volume robust against range deviations. The current findings support using a constant RBE within the CTV. The impact of range deviations on the considered probability of late radiation-induced toxicity in brain tissue was limited for robust dose-optimized treatment plans. Incorporation of LET_d in robust optimization frameworks may further reduce uncertainty related to the RBE-weighted dose estimation in normal tissues.

An open-source platform for interactive collision prevention in photon and particle beam therapy treatment planning

We present an open-source platform to aid medical dosimetrists in preventing collisions between gantry head and patient or couch during photon or particle beam therapy treatment planning. This generic framework uses the native scripting interface of the particular planning software to import STL files of the treatment machine elements. These are visualized in 3D together with the contoured or scanned patient surface. A graphical dialog with sliders allows the interactive rotation of the gantry and couch, with real-time feedback. To prevent a future replanning, treatment planners can assess in advance and exclude beam angles resulting in a potential risk of collision. The software platform is publicly available on GitHub and has been validated for RayStation with actual patient plans. Furthermore, the incorporation of the complete patient geometry was tested with a 3D surface scan of a full-body phantom performed with a handheld smartphone. With this study, we aim at minimizing the risk of replanning due to collisions and thus of treatment delays and unscheduled consumption of manpower. The clinical workflow can be streamlined at no cost already at the treatment planning stage. By ensuring a real-time verification of the plan feasibility, the script might boost the use of optimal couch angles that a planner might shy away from otherwise.

Status and innovations in pre-treatment CT imaging for proton therapy

Pre-treatment CT imaging is a topic of growing importance in particle therapy. Improvements in the accuracy of stopping-power prediction are demanded to allow for a dose conformality that is not inferior to state-of-the-art image-guided photon therapy. Although range uncertainty has been kept practically constant over the last decades, recent technological and methodological developments, like the clinical application of dual-energy CT, have been introduced or arise at least on the horizon to improve the accuracy and precision of range prediction. This review gives an overview of the current status, summarizes the innovations in dual-energy CT and its potential impact on the field as well as potential alternative technologies for stopping-power prediction.

A Monte Carlo based radiation response modelling framework to assess variability of clinical RBE in proton therapy

The clinical implementation of a variable relative biological effectiveness (RBE) in proton therapy is currently controversially discussed. Initial clinical evidence indicates a variable proton RBE, which needs to be verified. In this study, a radiation response modelling framework for assessing clinical RBE variability is established. It was applied to four selected glioma patients (grade III) treated with adjuvant radio(chemo)therapy and who developed late morphological image changes on T1-weighted contrast-enhanced (T1w-CE) magnetic resonance (MR) images within approximately two years of recurrence-free follow-up. The image changes were correlated voxelwise with dose and linear energy transfer (LET) values using univariable and multivariable logistic regression analysis. The regression models were evaluated by the area-under-the-curve (AUC) method performing a leave-one-out cross validation. The tolerance dose TD₅₀ at which 50% of patient voxels experienced toxicity was interpolated from the models. A Monte Carlo (MC) model was developed to simulate dose and LET distributions, which includes variance reduction (VR) techniques to decrease computation time. Its reliability and accuracy were evaluated based on dose calculations of the clinical treatment planning system (TPS) as well as absolute dose measurements performed in the patient specific quality assurance. Morphological image changes were related to a combination of dose and LET. The multivariable models revealed cross-validated AUC values of up to 0.88. The interpolated TD₅₀ curves decreased with increasing LET indicating an increase in biological effectiveness. The MC model reliably predicted average TPS dose within the clinical target volume as well as absolute water phantom dose measurements within 2% accuracy using dedicated VR settings. The observed correlation of dose and LET with late brain tissue damage suggests considering RBE variability for predicting chronic radiation-induced brain toxicities. The MC model simulates radiation fields in patients precisely and time-efficiently. Hence, this study encourages and enables in-depth patient evaluation to assess the variability of clinical proton RBE.

P6230Gender disparities in serum uric acid levels associated increased cardiovascular risk. The Czech Post-MONICA study

Background

Recent European Society of Hypertension (ESH) guidelines have implemented serum uric acid (SUA) levels as cardiovascular (CV) risk factor and recommend routine SUA levels measurement in hypertensive patients. However, what is the appropriate SUA level threshold and whether all patients with so called asymptomatic hyperuricemia should be treated remain unclear.

Objective

To evaluate longitudinal trends and determinants of mean serum uric acid (SUA) levels in two representative Czech population surveys (2006–09 and 2015–18) and to determine the SUA levels associated with increased 10-year risk of cardiovascular (CV) death.

Methods

Two independent cross-sectional surveys of major CV risk factors were performed in the Czech Republic in 2006–09 and 2015–18; 1% percent random samples aged 25–64 years stratified by age and gender were examined. The number of participants was 3612 in 2006–09, and 2621 in 2015–18. Ten-year risk of CV death was categorized using the SCORE algorithm as low (<1%), intermediate (1% to <5%), high (≥5% to 10%), and very high (≥10%).

Results

Final analyses included 3542 individuals (48.2% men; mean age 47.1±11.3) in 2006–09, and 2304 individuals (47.4% men; mean age 47.9±10.9) in 2015–18. Over the past decade, there was a highly significant increase in SUA levels (μmol/l) from 344.6±81.1 to 374.4±73.3 in men, and from 250.1±73.8 to 278.9±66.1 in women. In gender-specific multivariate linear regression analyses conducted in the 2015–18 survey, SUA levels increased with use of diuretics, an increase in waist-to-height ratio, serum triglycerides, and aspartate aminotransferase, and a decrease in estimated glomerular filtration rate in both genders, whereas in men SUA levels increased also with an increase in quartiles of alcohol intake and gamma-glutamyl transferase, and a decrease in glycated haemoglobin. When analysing pooled data of the two surveys, mean SUA levels increased with each increase in 10-year CV risk category in women (P<0.001), but not in men (P=0.21). In receiver operating characteristic (ROC) curve analysis, the cut-off value of SUA levels discriminating between low/intermediate and high/very high CV risk category in women was 306 μmol/l (sensitivity 53%; specificity 82%; area under the ROC curve 0.713 [95% CI 0.683–0.743]).

Conclusions

Over the past decade, there was a significant increase in uricemia in the Czech adult population. However, increasing SUA levels were associated with increased 10-year CV death risk only in women. The SUA levels associated with high/very high CV risk were substantially lower in Czech women than the currently used cut-off values for hyperuricemia.

Acknowledgement/Funding

Grant number 15-27109A from Czech health research council

Clinical Feasibility of Single-Source Dual-spiral 4D Dual-Energy CT for Proton Treatment Planning Within the Thoracic Region

PURPOSE

Single-source dual-spiral dual-energy computed tomography (DECT) provides additional patient information but is prone to motion between the 2 consecutively acquired computed tomography (CT) scans. Here, the clinical applicability of dual-spiral time-resolved DECT (4D-DECT) for proton treatment planning within the thoracic region was evaluated.

METHODS AND MATERIALS

Dual-spiral 4D-DECT scans of 3 patients with lung cancer were acquired. For time-averaged datasets and 4 breathing phases, the geometric conformity of 80 kVp and 140 kVp 4D-DECT scans before image post-processing was assessed by normalized cross correlation (NCC). Additionally, the conformity of the corresponding DECT-derived 58 keV and 79 keV pseudo-monoenergetic CT datasets after image post-processing, including deformable image registration (DIR), was determined. To analyze the reliability of proton dose calculation, clinical (Plan_Clin) and artificial worst-case (Plan_WorstCase, targeting the diaphragm) treatment plans were calculated on 140 kVp and 79 keV datasets and compared with gamma analyses (0.1% dose-difference and 1 mm distance-to-agreement criterion). The applicability of a patient-specific DECT-based prediction of stopping-power ratio (SPR) was investigated and proton range shifts compared with the clinical heuristic CT-number-to-SPR conversion were assessed. Finally, the delineation variability of an experienced radiation oncologist was quantified.

RESULTS

Dual-spiral 4D-DECT scans without DIR showed a high geometric conformity, with an average NCC ± standard deviation of 98.7% ± 1.0% when including all patient voxels or 88.2% ± 7.8% when considering only lung. DIR improved the conformity, leading to an average NCC of 99.9% ± 0.1% and 99.6% ± 0.5%, respectively. Plan_Clin dose distributions on 140 kVp and 79 keV datasets were similar, with an average gamma passing rate of 99.9% (99.2%-100%). The worst-case evaluation still revealed high passing rates (99.3% on average, 92.4% as minimum). Clinically relevant mean range shifts of 2.2% ± 1.2% were determined between patient-specific DECT-based SPR prediction and clinical heuristic CT-number-to-SPR conversion. The intra-observer delineation variability was slightly reduced using additional DECT-derived datasets.

CONCLUSIONS

The 79 keV pseudo-monoenergetic CT datasets can be consistently obtained from dual-spiral 4D-DECT and are applicable for dose calculation. Patient-specific DECT-based SPR prediction performed well and potentially reduces range uncertainty in proton therapy of patients with lung cancer.

Inter-centre variability of CT-based stopping-power prediction in particle therapy: Survey-based evaluation

Background and purpose

Stopping-power ratios (SPRs) are used in particle therapy to calculate particle range in patients. The heuristic CT-to-SPR conversion (Hounsfield Look-Up-Table, HLUT), needed for treatment planning, depends on CT-scan and reconstruction parameters as well as the specific HLUT definition. To assess inter-centre differences in these parameters, we performed a survey-based qualitative evaluation, as a first step towards better standardisation of CT-based SPR derivation.

Materials and methods

A questionnaire was sent to twelve particle therapy centres (ten from Europe and two from USA). It asked for details on CT scanners, image acquisition and reconstruction, definition of the HLUT, body-region specific HLUT selection, investigations of beam-hardening and experimental validations of the HLUT. Technological improvements were rated regarding their potential to improve SPR accuracy.

Results

Scan parameters and HLUT definition varied widely. Either the stoichiometric method (eight centres) or a tissue-substitute-only HLUT definition (three centres) was used. One centre combined both methods. The number of HLUT line segments varied widely between two and eleven. Nine centres had investigated influence of beam-hardening, often including patient-size dependence. Ten centres had validated their HLUT experimentally, with very different validation schemes. Most centres deemed dual-energy CT promising for improving SPR accuracy.

Conclusions

Large inter-centre variability was found in implementation of CT scans, image reconstruction and especially in specification of the CT-to-SPR conversion. A future standardisation would reduce time-intensive institution-specific efforts and variations in treatment quality. Due to the interdependency of multiple parameters, no conclusion can be drawn on the derived SPR accuracy and its inter-centre variability.

On the equivalence of image-based dual-energy CT methods for the determination of electron density and effective atomic number in radiotherapy

Dual-energy computed tomography enables the determination of relative electron density and effective atomic number. As this can increase accuracy in radiotherapy treatment planning, a substantial number of algorithms for the determination of the two quantities has been suggested – most of them based on reconstructed CT images. We show that many of these methods share a common theoretical framework. Equations can be transformed from one method to the other by re-definition of the calibration parameters. We suggest that further work should be spent on practical calibration and the reliability of CT numbers rather than on the theoretical framework.

Experimental verification of stopping-power prediction from single- and dual-energy computed tomography in biological tissues

An experimental setup for consecutive measurement of ion and x-ray absorption in tissue or other materials is introduced. With this setup using a 3D-printed sample container, the reference stopping-power ratio (SPR) of materials can be measured with an uncertainty of below 0.1%. A total of 65 porcine and bovine tissue samples were prepared for measurement, comprising five samples each of 13 tissue types representing about 80% of the total body mass (three different muscle and fatty tissues, liver, kidney, brain, heart, blood, lung and bone). Using a standard stoichiometric calibration for single-energy CT (SECT) as well as a state-of-the-art dual-energy CT (DECT) approach, SPR was predicted for all tissues and then compared to the measured reference. With the SECT approach, the SPRs of all tissues were predicted with a mean error of (-0.84  ±  0.12)% and a mean absolute error of (1.27  ±  0.12)%. In contrast, the DECT-based SPR predictions were overall consistent with the measured reference with a mean error of (-0.02  ±  0.15)% and a mean absolute error of (0.10  ±  0.15)%. Thus, in this study, the potential of DECT to decrease range uncertainty could be confirmed in biological tissue.

Dual-energy CT based proton range prediction in head and pelvic tumor patients

BACKGROUND AND PURPOSE

To reduce range uncertainty in particle therapy, an accurate computation of stopping-power ratios (SPRs) based on computed tomography (CT) is crucial. Here, we assess range differences between the state-of-the-art CT-number-to-SPR conversion using a generic Hounsfield look-up table (HLUT) and a direct patient-specific SPR prediction (RhoSigma) based on dual-energy CT (DECT) in 100 proton treatment fields.

MATERIAL AND METHODS

For 25 head-tumor and 25 prostate-cancer patients, the clinically applied treatment plan, optimized using a HLUT, was recalculated with RhoSigma as CT-number-to-SPR conversion. Depth-dose curves in beam direction were extracted for both dose distributions in a regular grid and range deviations were determined and correlated to SPR differences within the irradiated volume.

RESULTS

Absolute (relative) mean water-equivalent range shifts of 1.1mm (1.2%) and 4.1mm (1.7%) were observed in the head-tumor and prostate-cancer cohort, respectively. Due to the case dependency of a generic HLUT, range deviations within treatment fields strongly depend on the tissues traversed leading to a larger variation within one patient than between patients.

CONCLUSIONS

The magnitude of patient-specific range deviations between HLUT and the more accurate DECT-based SPR prediction is clinically relevant. A clinical application of the latter seems feasible as demonstrated in this study using medically approved systems from CT acquisition to treatment planning.

Methodological accuracy of image-based electron density assessment using dual-energy computed tomography

PURPOSE

Electron density is the most important tissue property influencing photon and ion dose distributions in radiotherapy patients. Dual-energy computed tomography (DECT) enables the determination of electron density by combining the information on photon attenuation obtained at two different effective x-ray energy spectra. Most algorithms suggested so far use the CT numbers provided after image reconstruction as input parameters, i.e., are imaged-based. To explore the accuracy that can be achieved with these approaches, we quantify the intrinsic methodological and calibration uncertainty of the seemingly simplest approach.

METHODS

In the studied approach, electron density is calculated with a one-parametric linear superposition ('alpha blending') of the two DECT images, which is shown to be equivalent to an affine relation between the photon attenuation cross sections of the two x-ray energy spectra. We propose to use the latter relation for empirical calibration of the spectrum-dependent blending parameter. For a conclusive assessment of the electron density uncertainty, we chose to isolate the purely methodological uncertainty component from CT-related effects such as noise and beam hardening.

RESULTS

Analyzing calculated spectrally weighted attenuation coefficients, we find universal applicability of the investigated approach to arbitrary mixtures of human tissue with an upper limit of the methodological uncertainty component of 0.2%, excluding high-Z elements such as iodine. The proposed calibration procedure is bias-free and straightforward to perform using standard equipment. Testing the calibration on five published data sets, we obtain very small differences in the calibration result in spite of different experimental setups and CT protocols used. Employing a general calibration per scanner type and voltage combination is thus conceivable.

CONCLUSION

Given the high suitability for clinical application of the alpha-blending approach in combination with a very small methodological uncertainty, we conclude that further refinement of image-based DECT-algorithms for electron density assessment is not advisable.