Applications of Monte Carlo methods to special radiotherapeutic techniques

Monte Carlo (MC) methods are considered one of the most powerful and precise approaches to study and solve medical physics issues. They, indeed, can be applied in all the situations where to use deterministic algorithms is infeasible or impossible. Surprising improvements in computer technology have promoted a wide diffusion of this technique, giving rise to the born of several Monte Carlo codes, such as the GEANT4 toolkit. In this paper we show some of the applications we developed using GEANT4. In particular, the simulation of two different radiotherapy techniques, such as proton/ion therapy and stereotactic radiosurgery will be discussed. In the first case we show the main features of our last public version of the GEANT4 Hadrontherapy program, also discussing the issues related to the nuclear fragmentation. In the second case, we show the procedures followed for the simulation of a Gamma Knife device, in order to validate the Treatment Planning System (TPS) used for the dose computation

Use of an electronic administrative database to identify older community dwelling adults at high-risk for hospitalization or emergency department visits: The elders risk assessment index

<p>Abstract</p> <p>Background</p> <p>The prevention of recurrent hospitalizations in the frail elderly requires the implementation of high-intensity interventions such as case management. In order to be practically and financially sustainable, these programs require a method of identifying those patients most at risk for hospitalization, and therefore most likely to benefit from an intervention. The goal of this study is to demonstrate the use of an electronic medical record to create an administrative index which is able to risk-stratify this heterogeneous population.</p> <p>Methods</p> <p>We conducted a retrospective cohort study at a single tertiary care facility in Rochester, Minnesota. Patients included all 12,650 community-dwelling adults age 60 and older assigned to a primary care internal medicine provider on January 1, 2005. Patient risk factors over the previous two years, including demographic characteristics, comorbid diseases, and hospitalizations, were evaluated for significance in a logistic regression model. The primary outcome was the total number of emergency room visits and hospitalizations in the subsequent two years. Risk factors were assigned a score based on their regression coefficient estimate and a total risk score created. This score was evaluated for sensitivity and specificity.</p> <p>Results</p> <p>The final model had an AUC of 0.678 for the primary outcome. Patients in the highest 10% of the risk group had a relative risk of 9.5 for either hospitalization or emergency room visits, and a relative risk of 13.3 for hospitalization in the subsequent two year period.</p> <p>Conclusions</p> <p>It is possible to create a screening tool which identifies an elderly population at high risk for hospital and emergency room admission using clinical and administrative data readily available within an electronic medical record.</p

Data acquisition system for a proton imaging apparatus

New developments in the proton-therapy field for cancer treatments, leaded Italian physics researchers to realize a proton imaging apparatus consisting of a silicon microstrip tracker to reconstruct the proton trajectories and a calorimeter to measure their residual energy. For clinical requirements, the detectors used and the data acquisition system should be able to sustain about 1 MHz proton rate. The tracker read-out, using an ASICs developed by the collaboration, acquires the signals detector and sends data in parallel to an FPGA. The YAG:Ce calorimeter generates also the global trigger. The data acquisition system and the results obtained in the calibration phase are presented and discussed

A Monte Carlo study for the calculation of the average linear energy transfer (LET) distributions for a clinical proton beam line and a radiobiological carbon ion beam line

Fluence, depth absorbed dose and linear energy transfer (LET) distributions of proton and carbon ion beams have been investigated using the Monte Carlo code Geant4 (GEometry ANd Tracking). An open source application was developed with the aim to simulate two typical transport beam lines, one used for ocular therapy and cell irradiations with protons and the other for cell irradiations with carbon ions. This tool allows evaluation of the primary and total dose averaged LET and predict their spatial distribution in voxelized or sliced geometries. In order to reproduce the LET distributions in a realistic way, and also the secondary particles contributions due to nuclear interactions were considered in the computations. Pristine and spread-out Bragg peaks were taken into account both for proton and carbon ion beams, with the maximum energy of 62 MeV/n. Depth dose distributions were compared with experimental data, showing good agreement. Primary and total LET distributions were analysed in order to study the influence of contributions of secondary particles in regions at different depths. A non-negligible influence of high-LET components was found in the entrance channel for proton beams, determining the total dose averaged LET by the factor 3 higher than the primary one. A completely different situation was obtained for carbon ions. In this case, secondary particles mainly contributed in the tail that is after the peak. The results showed how the weight of light and heavy secondary ions can considerably influence the computation of LET depth distributions. This has an important role in the interpretation of results coming from radiobiological experiments and, therefore, in hadron treatment planning procedures

Utility of electronic patient records in primary care for stroke secondary prevention trials

BACKGROUND: This study aimed to inform the design of a pragmatic trial of stroke prevention in primary care by evaluating data recorded in electronic patient records (EPRs) as potential outcome measures. The study also evaluated achievement of recommended standards of care; variation between family practices; and changes in risk factor values from before to after stroke.METHODS: Data from the UK General Practice Research Database (GPRD) were analysed for 22,730 participants with an index first stroke between 2003 and 2006 from 414 family practices. For each subject, the EPR was evaluated for the 12 months before and after stroke. Measures relevant to stroke secondary prevention were analysed including blood pressure (BP), cholesterol, smoking, alcohol use, body mass index (BMI), atrial fibrillation, utilisation of antihypertensive, antiplatelet and cholesterol lowering drugs. Intraclass correlation coefficients (ICC) were estimated by family practice. Random effects models were fitted to evaluate changes in risk factor values over time.RESULTS: In the 12 months following stroke, BP was recorded for 90%, cholesterol for 70% and body mass index (BMI) for 47%. ICCs by family practice ranged from 0.02 for BP and BMI to 0.05 for LDL and HDL cholesterol. For subjects with records available both before and after stroke, the mean reductions from before to after stroke were: mean systolic BP, 6.02 mm Hg; diastolic BP, 2.78 mm Hg; total cholesterol, 0.60 mmol/l; BMI, 0.34 Kg/m2. There was an absolute reduction in smokers of 5% and heavy drinkers of 4%. The proportion of stroke patients within the recommended guidelines varied from less than a third (29%) for systolic BP, just over half for BMI (54%), and over 90% (92%) on alcohol consumption.CONCLUSIONS: Electronic patient records have potential for evaluation of outcomes in pragmatic trials of stroke secondary prevention. Stroke prevention interventions in primary care remain suboptimal but important reductions in vascular risk factor values were observed following stroke. Better recording of lifestyle factors in the GPRD has the potential to expand the scope of the GPRD for health care research and practice

Efficacy of a brief multifactorial adherence-based intervention on reducing the blood pressure of patients with poor adherence: protocol for a randomized clinical trial

<p>Abstract</p> <p>Background</p> <p>Lowering of blood pressure by antihypertensive drugs reduces the risks of cardiovascular events, stroke, and total mortality. However, poor adherence to antihypertensive medications reduces their effectiveness and increases the risk of adverse events. In terms of relative risk reduction, an improvement in medication adherence could be as effective as the development of a new drug.</p> <p>Methods/Design</p> <p>The proposed randomized controlled trial will include patients with a low adherence to medication and uncontrolled blood pressure. The intervention group will receive a multifactorial intervention during the first, third, and ninth months, to improve adherence. This intervention will include motivational interviews, pill reminders, family support, blood pressure self-recording, and simplification of the dosing regimen.</p> <p>Measurement</p> <p>The primary outcome is systolic blood pressure. The secondary outcomes are diastolic blood pressure, proportion of patients with adequately controlled blood pressure, and total cost.</p> <p>Discussion</p> <p>The trial will evaluate the impact of a multifactorial adherence intervention in routine clinical practice. Ethical approval was given by the Ethical Committee on Human Research of Balearic islands, Spain (approval number IB 969/08 PI).</p> <p>Trial registration</p> <p>Current controlled trials ISRCTN21229328</p

Cost effectiveness of support for people starting a new medication for a long term condition through community pharmacies: an economic evaluation of the New Medicine Service (NMS) compared with normal practice

Background: The English community pharmacy New Medicine Service (NMS) significantly increases patient adherence to medicines, compared with normal practice. We examined the cost-effectiveness of NMS compared with normal practice by combining adherence improvement and intervention costs with the effect of increased adherence on patient outcomes and healthcare costs. Methods: We developed Markov models for diseases targeted by the NMS (hypertension, type 2 diabetes, chronic obstructive pulmonary disease, asthma and antiplatelet regimens) to assess the impact of patients’ non-adherence. Clinical event probability, treatment pathway, resource-use and costs were extracted from literature and costing tariffs. Incremental costs and outcomes associated with each disease were incorporated additively into a composite probabilistic model and combined with adherence rates and intervention costs from the trial. Costs per extra quality-adjusted-life-year(QALY) were calculated from the perspective of NHS England, using a lifetime horizon. Results: NMS generated a mean of 0.05 (95%CI: 0.00, 0.13) more QALYs per patient, at a mean reduced cost of -£144 (95%CI: -769, 73). The NMS dominates normal practice with probability of 0.78 (ICER: - £3166 per QALY). NMS has a 96.7% probability of cost-effectiveness compared with normal practice at a willingness-to-pay of £20000 per QALY. Sensitivity analysis demonstrated that targeting each disease with NMS has a probability over 0.90 of cost-effectiveness compared with normal practice at a willingness-to-pay of £20000 per QALY. Conclusions: Our study suggests that the New Medicine Service increased patient medicine adherence compared with normal practice, which translated into increased health gain at reduced overall cost