Objectives The development of new techniques in radiotherapy (RT) provides a better planned target volume (PTV) dose distribution while further improving the protection of organs at risk (OARs). The study aims to present the dosimetric results of studies using hybrid techniques in whole-breast radiotherapy (WBRT). Methods: This systematic literature review was conducted by scanning the relevant literature in PubMed, Scopus, and Web of Science following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines. Among the parameters are dose values for PTV and OARs beam contribute ratios, the value of monitors, and treatment times for different RT techniques. Initially, 586 articles were identified; 196 duplicate articles were removed leaving 391 articles for screening. Three-hundred and thirty-seven irrelevant articles were excluded, leaving 54 studies assessed for eligibility. A total of 22 articles met the search criteria to evaluate dosimetric results of hybrid and other RT techniques in WBRT. Results: According to the dosimetric data of the studies, hybrid intensity-modulated RT (H-IMRT) and hybrid volumetric-modulated arc therapy (H-VMAT) techniques give dosimetrically advantageous results in WBRT compared to other RT techniques. Conclusion: Hybrid techniques using appropriate beams contribute value and show great promise in improving dosimetric results in WBRT. However, there is a need for new studies showing the long-term clinical results of hybrid RT.

The use of Hybrid Techniques in Whole-Breast Radiotherapy: A Systematic Review

To reduce liver and lung dose during right breast irradiation while maintaining optimal dose to the target volume. This dose reduction has the potential to decrease acute side effects and long-term toxicity.16 patients treated with radiation therapy for localized carcinoma of the right breast were included retrospectively. For the planning CT, each patient was immobilised on an indexed board with the arms placed above the head. CT scans were acquired in free-breathing (FB) as well as with deep inspiration breath hold (DIBH). Both scans were acquired with the same length. Planning target volumes (PTV's) were created with a 5 mm margin from the respective clinical target volumes (CTV's) on both CT datasets. The liver was outlined as scanned. Dose metrics evaluated were as follows: differences in PTV coverage, dose to the liver (max, mean, V90%, V50%, V30%), dose to lung (mean, V20Gy, relative electron density) and dose to heart (Dmax). The p-values were calculated using Wilcoxon signed-rank tests. A p-value was significant when <0.05.Differences in PTV coverage between plans using FB and DIBH were less than 2 %. Maximum liver dose was significantly less using DIBH: 17.5 Gy versus FB: 40.3 Gy (p < 0.001). The volume of the liver receiving 10 % of the dose was significantly less using DIBH with 1.88 cm3 versus 72.2 cm3 under FB (p < 0.001). The absolute volume receiving 20 Gy in the right lung was larger using DIBH: 291 cm3 versus 230 cm3 under FB (p < 0.001) and the relative volume of lung receiving dose greater than 20 Gy was smaller with DIBH: 11.5 % versus 14 % in FB (p = 0.007). The relative electron density of lung was significantly less with DIBH: 0.59 versus 0.62 with FB, (p < 0.001). This suggests that the lung receives less dose due to its lower density when using DIBH.Radiation of the right breast using DIBH spares liver and lung tissue significantly and thus carries the potential of best practice for right sided breast cancer. 

Deep inspirational breast hold (DIBH) for right breast irradiation: Improved sparing of liver and lung tissue

Stochastic differential equation mixed effects models (SDEMEMs) are increasingly used in biomedical and pharmacokinetic/pharmacodynamic research. However, the complexity of these models means that previous research has focussed on approximate parameter estimation methods. This thesis develops three novel Bayesian parameter estimation methods for SDEMEMs. The new methods can produce parameter estimates that are more accurate and provide more reliable uncertainty quantification. The new methods are applied to both real and simulated data from a tumour xenography study on mice.

Bayesian inference for stochastic differential equation mixed effects models

Abstract Objective In left breast radiotherapy (RT) desired heart doses may be achieved without heart-sparing RT techniques in some patients. We aimed to examine the existence of predictive factors and cutoff points to determine which patients are the main candidates for heart-sparing RT techniques. Material and method Dosimetric data for left breast cancer was examined. RT plans were made at conventional doses to the breast and peripheral lymph nodes. Statistical analyses were performed using SPSS 22.0 (SPSS Inc., IBM Corp., Armonk, NY). Result 114 cases were evaluated by ROC (Receiver operating characteristic) analysis in the breast-conserving surgery (BCS) and mastectomy groups. While only left lung volume (AUC: 0.74, 95% CI 0.61–0.87, p = 0.002) was significant in BCS cases, in cases with mastectomy, left lung volume (AUC: 0.81, 95% CI 0.69–0.94, p = 0.002) and lung/heart volume ratio (AUC: 0.83, 95% CI 0.70–0.96, p = 0.001) had a significant relationship with the relevance of heart doses. The cutoff point of 1.92 was selected for the lung/heart volume ratio for the mastectomized patients. Moreover, the cutoff point 1154 cc and 1208 cc was determined for the left lung volume for the BCS and mastectomized patients, respectively. Conclusion Various cutoff points in left breast RT can be used to predict whether RT plans will meet QUANTEC (Quantitative Analysis of Normal Tissue Effects in the Clinic) heart dose limits. Evaluating only these few cutoff points before planning makes it possible to eliminate 70% of patients with BCS and 40% of patients with mastectomy from respiratory-controlled methods, which require time and effort. Patients with lung volume and lung/heart volume ratio smaller than the cutoff values can be considered primary candidates for heart-sparing techniques. 

Cardiac protective techniques in left breast radiotherapy: rapid selection criteria for routine clinical decision making

Abstract Objective: In left breast radiotherapy (RT) desired heart doses may be achieved without heart-sparing RT techniques in some patients. We aimed to examine the existence of predictive factors and cut-off points to determine which patients are the main candidates for heart-sparing RT techniques. Material and method: Dosimetric data for left breast cancer was examined. RT plans were made at conventional doses to the breast and peripheral lymph nodes. Statistical analyzes were performed using SPSS 22.0 (SPSS Inc.,IBM Corp.,Armonk, NY). Results: 114 cases were evaluated by ROC analysis in the breast conserving surgery (BCS) and mastectomy groups. While only left lung volume (AUC:0.74, 95%CI:0.61-0.87, p=0.002) was significant in BCS cases, in cases with mastectomy, left lung volume (AUC:0.81, 95%CI:0.69-0.94, p=0.002) and lung/heart volume ratio (AUC:0.83,95%CI:0.70-0.96, p=0.001) had a significant relationship with the relevance of heart doses. The cut-off point of 1.92 was selected for the lung/heart volume ratio for the mastectomized patients. Moreover, the cut-off point 1154 cc and 1208 cc was determined for the left lung volume for the BCS and mastectomized patients, respectively. Conclusion: Various cut-off points in left breast RT can be used to predict whether RT plans will meet QUANTEC heart dose limits. Evaluating only these few cut-off points before planning makes it possible to eliminate 70% of patients with BCS and 40% of patients with mastectomy from respiratory-controlled methods, which require time and effort. Patients with lung volume and lung/heart volume ratio smaller than the cut-off values can be considered primary candidates for heart-sparing techniques. 

Cardiac Protective Techniques in Left Breast Radiotherapy: Rapid selection criteria for routine clinical decision making

Background The current standard of care (SOC) for whole breast radiotherapy (WBRT) in the US is conventional tangential photon fields. Advanced WBRT techniques may provide similar tumor control and better normal tissue sparing, but it is controversial whether the medical benefits of an advanced technology are significant enough to justify its higher cost. Objective To analyze the cost-effectiveness of six advanced WBRT techniques compared with SOC. Methods We developed a Markov model to simulate health states for one cohort of women (65-year-old) with early-stage breast cancer over 15 years after WBRT. The cost effectiveness analyses of field-in-field (FIF), hybrid intensity modulated radiotherapy (IMRT), full IMRT, standard volumetric modulated arc therapy (STD-VMAT), multiple arc VMAT (MA-VMAT), non-coplanar VMAT (NC-VMAT) compared with SOC were performed with both tumor control and radiogenic side effects considered. Transition probabilities and utilities for each health state were obtained from literature. Costs incurred by payers were adopted from literature and Medicare data. Quality-adjusted life years (QALYs) and incremental cost-effectiveness ratio (ICER) were calculated. One-way sensitivity analyses and probabilistic sensitivity analyses (PSA) were performed to evaluate the impact of uncertainties on the final results. Results FIF has the lowest ICER value of 1,511 $/QALY. The one-way analyses show that the cost-effectiveness of advanced WBRT techniques is most sensitive to the probability of developing contralateral breast cancer. PSAs show that SOC is more cost effective than almost all advanced WBRT techniques at a willingness-to-pay (WTP) threshold of 50,000 $/QALY, while FIF, hybrid IMRT and MA-VMAT are more cost-effective than SOC with a probability of 59.2%, 72.3% and 72.6% at a WTP threshold of 100,000 $/QALY, respectively. Conclusions FIF might be the most cost-effective option for WBRT patients at a WTP threshold of 50,000 $/QALY, while hybrid IMRT and MA-VMAT might be the most cost-effective options at a WTP threshold of 100,000 $/QALY.

/pdf/cost-effectiveness-analysis-of-radiotherapy-techniques-for-3rs51j8syv.pdf

Cost-effectiveness analysis of radiotherapy techniques for whole breast irradiation

Current estimates of the HIV epidemic indicate a decrease in the incidence of the disease in the undiagnosed subpopulation over the past 10 years. However, a lack of access to care has not been considered when modeling the population. Populations at high risk for contracting HIV are twice as likely to lack access to reliable medical care. In this paper, we consider three contributors to the HIV population dynamics: at-risk population exhaustion, lack of access to care, and usage of anti-retroviral therapy (ART) by diagnosed individuals. An extant problem in the mathematical study of this system is deriving parameter estimates due to a portion of the population being unobserved. We approach this problem by looking at the proportional change in the infected subpopulations. We obtain conservative estimates for the proportional change of the infected subpopulations using hierarchical Bayesian statistics. The estimated proportional change is used to derive epidemic parameter estimates for a system of stochastic differential equations (SDEs). Model fit is quantified to determine the best parametric explanation for the observed dynamics in the infected subpopulations. Parameter estimates derived using these methods produce simulations that closely follow the dynamics observed in the data, as well as values that are generally in agreement with prior understanding of transmission and diagnosis rates. Simulations suggest that the undiagnosed population may be larger than currently estimated without significantly affecting the population dynamics.

/pdf/estimating-epidemiological-parameters-of-a-stochastic-4sv169jyw9.pdf

Estimating epidemiological parameters of a stochastic differential model of HIV dynamics using hierarchical Bayesian statistics

Current estimates of the HIV epidemic indicate a decrease in the incidence of the disease in the undiagnosed subpopulation over the past 10 years. However, a lack of access to care has not been considered when modeling the population. Populations at high risk for contracting HIV are twice as likely to lack access to reliable medical care. In this paper, we consider three contributors to the HIV population dynamics: susceptible pool exhaustion, lack of access to care, and usage of anti-retroviral therapy (ART) by diagnosed individuals. We consider the change in the proportion of undiagnosed individuals as the parameter in a simple Markov model. We obtain conservative estimates for the proportional change of the infected subpopulations using hierarchical Bayesian statistics. The estimated proportional change is used to derive epidemic parameter estimates for a system of stochastic differential equations (SDEs). Epidemic parameters are modified to capture the dynamics of each of the three contributors, as well as all their possible combinations. Model fit is quantified to determine the best explanation for the observed dynamics in the infected subpopulations.

/pdf/is-the-hiv-epidemic-over-investigating-population-dynamics-gbnu1fcsw0.pdf

Is the HIV epidemic over? Investigating population dynamics using Bayesian methodology to estimate epidemiological parameters for a system of stochastic differential equations

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Cost-effectiveness analysis of radiotherapy techniques for whole breast irradiation

Estimating epidemiological parameters of a stochastic differential model of HIV dynamics using hierarchical Bayesian statistics

Is the HIV epidemic over? Investigating population dynamics using Bayesian methodology to estimate epidemiological parameters for a system of stochastic differential equations