Discrepancies In Delivery Research Articles

Quantifying interstitial fluid by direct osmotic pressure measurements in vivo via telemetry-enabled Nanofluidic implants

Interstitial fluid (IF) is pivotal in maintaining balance within tissues and organs, facilitating molecular transport and supporting homeostasis. Various drug delivery systems, such as long-acting depots or implants, rely on IF to distribute drugs locally before they enter the bloodstream. The volume and accessibility of this fluid directly influence how drugs diffuse and the build-up of the osmotic pressure in areas with high drug concentration, ultimately impacting the performance of the delivery systems. Consequently, differences in free fluid availability contribute to discrepancies in drug delivery in vitro versus in vivo. Accurately estimating the volume of IF in vivo would significantly improve the design of in vitro drug release experiments and enhance the outcomes of animal studies. However, accurately measuring free IF and its effect on drug delivery systems in living organisms poses challenges. In response, we developed a reservoir-membrane subcutaneous (SQ) implant similar to a long-acting drug delivery system. The implant measures fluid availability in surrounding tissues by measuring real-time osmotic pressure changes resulting from fluid permeating through a nanoporous membrane, using an integrated pressure transducer and Bluetooth connectivity. By correlating in vitro and in vivo data using a computational model of molecular transport across the membrane, we estimated a 93 % reduction in free fluid availability in the subcutaneous tissue surrounding the implant as compared to our ideal in vitro setting with implant immersed within sink fluids. Applicable to various implantation sites, our study highlights a practical approach to directly assessing free fluid availability in different tissues, enhancing in vitro drug delivery experimental design and evaluating the performance of drug delivery systems in physiological contexts.

PENGARUH PENGADAAN BAHAN MAKANAN UNTUK OPERASIONAL KITCHEN TERHADAP KINERJA PURCHASING DI HOTEL ALILA SOLO

ABSTRACT
 This research is a descriptive qualitative research. The research subject in this research is purchasing Alila Solo Hotel. Methods of data collection in this study using observation, interviews, literature and documentation. This study aims to find out how the procurement of kitchen food ingredients at the Alila Hotel Solo and how the influence of the procurement of kitchen food ingredients on purchasing performance at the Alila Solo Hotel. The results showed that the procurement of kitchen food ingredients at the Alila Solo Hotel was running properly. Starting from purchase requests, selecting suppliers, placing orders and receiving goods has been done correctly. However, there are obstacles when looking for seasonal food ingredients, when sudden requests occur, discrepancies in delivery by suppliers and order delays. Given these constraints, solutions that can be taken are replacing food ingredients or looking for similar food ingredients, returning food ingredients that are not suitable and good communication is needed between purchasing and the kitchen to avoid miscommunication. The influence of the procurement of kitchen food ingredients on purchasing performance in this study uses performance indicators according to Robbins (2016: 260), namely work quality, work quantity and timeliness. All show that the procurement of food ingredients shows a good influence on purchasing performance at the Alila Solo Hotel. If the procurement of food ingredients in the kitchen goes well, good purchasing performance will also be created.
 Keywords: Food Procurement, Performance, Purchasing

Addressing Provider-Dependent Gaps in Sickle Cell Disease Care

Sickle cell disease (SCD) affects around 100,000 Americans and presents numerous health-related challenges thus necessitating effective management strategies. Educational initiatives on evidence-based intervention are known to play a crucial role in improving patient-related outcomes (PRO) and enhancing the quality of life (QOL) for individuals with SCD. Community-based hospitals face challenges in managing SCD patients. Patients who are unaffiliated with a comprehensive sickle cell center have increased healthcare utilization, readmissions, and patient dissatisfaction due to limited access to specialized services and discrepancies in care delivery. Addressing these disparities and expanding access to care is crucial in optimizing SCD management. The purpose of this exploratory observational study was to identify provider-related gaps in a community-based tertiary center. The survey assessed internal medicine trainees' and hospitalists' baseline knowledge and comfort level at a tertiary care center with a total of 304 yearly adult admissions related to SCD management. The survey was distributed through an online platform. Data was analyzed to identify trends and gaps in internal medicine providers. Our survey had a total of 30 respondents, the response rate was 39%. Most respondents (90%) had prior experience with SCD patients; however, many gaps were identified [Table 1]. 70-75% of physicians felt comfortable managing acute pain and chronic illnesses, yet only half of these providers were comfortable with managing SCD patients. While our study sample is small, similar results were noted in a study conducted in another community-based hospital in the Chicagoland area. Our study shows a similar provider-related gap in SCD care delivery. Dr. Kanter proposed a model of care delivery which is known as the “hub and spoke” model. It offers a promising solution, creating a networked system of care with a central hub and secondary spokes providing more limited services. Community-based hospital settings can serve as spokes, bringing specialized SCD care closer to patients in local areas. Hence, we propose that this model can be further modified to include provider education. This equips non-sickle cell specialists at various spokes with the necessary knowledge and skills through targeted education by sickle cell specialists at a centralized hub. Targeting provider gaps may significantly improve PRO. Our residency program hopes to establish an affiliation with the University of Illinois (UI) Health Sickle Cell Center (SCC) to help with educating trainees on SCD. The UI Health SCC was one of eight sites participating in the National Sickle Cell Disease Implementation Consortium (SCDIC) with the goal of helping patients access longitudinal care, increase hydroxyurea utilization when appropriate, and provide proper pain management in ED. They are also part of the Recruitment and Engagement in Care to Impact Practice Enhancement (RECIPE) project which focuses on patients with SCD that are unaffiliated with care centers and attempts to understand and eliminate their barriers to care. Future efforts should include implementing targeted provider education, within the context of a hub and spoke model. This may help bridge the gap in care delivery and ultimately enhance outcomes for SCD patients.

Visualization and Estimation of Nasal Spray Delivery to Olfactory Mucosa in an Image-Based Transparent Nasal Model.

Background: Nose-to-brain (N2B) drug delivery offers unique advantages over intravenous methods; however, the delivery efficiency to the olfactory region using conventional nasal devices and protocols is low. This study proposes a new strategy to effectively deliver high doses to the olfactory region while minimizing dose variability and drug losses in other regions of the nasal cavity. Materials and Methods: The effects of delivery variables on the dosimetry of nasal sprays were systematically evaluated in a 3D-printed anatomical model that was generated from a magnetic resonance image of the nasal airway. The nasal model comprised four parts for regional dose quantification. A transparent nasal cast and fluorescent imaging were used for visualization, enabling detailed examination of the transient liquid film translocation, real-time feedback on input effect, and prompt adjustment to delivery variables, which included the head position, nozzle angle, applied dose, inhalation flow, and solution viscosity. Results: The results showed that the conventional vertex-to-floor head position was not optimal for olfactory delivery. Instead, a head position tilting 45-60° backward from the supine position gave a higher olfactory deposition and lower variability. A two-dose application (250 mg) was necessary to mobilize the liquid film that often accumulated in the front nose following the first dose administration. The presence of an inhalation flow reduced the olfactory deposition and redistributed the sprays to the middle meatus. The recommended olfactory delivery variables include a head position ranging 45-60°, a nozzle angle ranging 5-10°, two doses, and no inhalation flow. With these variables, an olfactory deposition fraction of 22.7 ± 3.7% was achieved in this study, with insignificant discrepancies in olfactory delivery between the right and left nasal passages. Conclusions: It is feasible to deliver clinically significant doses of nasal sprays to the olfactory region by leveraging an optimized combination of delivery variables.

Comparing log file to measurement-based patient-specific quality assurance.

Recent technological advances have allowed the possibility of performing patient-specific quality assurance (QA) without time-intensive measurements. The objectives of this study are to: (1) compare how well the log file-based Mobius QA system agrees with measurement-based QA methods (ArcCHECK and portal dosimetry, PD) in passing and failing plans, and; (2) evaluate their error sensitivities. To these ends, ten phantom plans and 100 patient plans were measured with ArcCHECK and PD on VitalBeam, while log files were sent to Mobius for dose recalculation. Gamma evaluation was performed using criteria 3%/2mm, per TG218 recommendations, and non-inferiority of the Mobius recalculation was determined with statistical testing. Ten random plans were edited to include systematic errors, then subjected to QA. Receiver operating characteristic curves were constructed to compare error sensitivities across the QA systems, and clinical significance of the errors was determined by recalculating dose to patients. We found no significant difference between Mobius, ArcCHECK, and PD in passing plans at the TG218 action limit. Mobius showed good sensitivity to collimator and gantry errors but not MLC bank shift errors, but could flag discrepancies in treatment delivery. Systematic errors were clinically significant only at large magnitudes; such unacceptable plans did not pass QA checks at the TG218 tolerance limit. Our results show that Mobius is not inferior to existing measurement-based QA systems, and can supplement existing QA practice by detecting real-time delivery discrepancies. However, it is still important to maintain rigorous routine machine QA to ensure reliability of machine log files.

A measurement validation of improved plan deliverability with monitor unit objective tool for spine stereotactic ablative radiotherapy.

Spine stereotactic body radiation therapy (SBRT) uses high dose per fraction for palliative pain control. The treatment plans are often heavily modulated due to close proximity to spinal cord and this can lead to poor plan quality which are susceptible to dose delivery discrepancy. Therefore, we aim to assess the effectiveness of the monitor unit (MU) objective tool in Eclipse treatment planning systems in modulating the plan complexity to improve the plan quality in spine SBRT. Seven retrospective spine SBRT plans are re-optimized using the MU objective tool in Eclipse TPS v13.6 and were compared with the original plans. The dose metrics of the tumor PTV were compared using D1cc. D99%, D95%, D0.03cc, D0.1cc, D0.35cc and D1cc, and that of cord PRV were compared using D0.03cc, D0.1cc, D0.35cc. Four different plan complexities were also calculated for the original and re-optimized plans to quantify the impact of the tool on the modulation. Patient specific quality assurance measurements were performed with Stereophan and SRS MapCheck, and analyzed using the 1%/1-mm and 2%/2-mm criteria with gamma analysis. The dose metrics of the PTV and cord PRV of the re-optimized and original plans are similar and still meet the planning dose constraints. In particular, the PTV dose coverage has a small percentage difference of (0.15 ± 1.33)% and (0.01 ± 1.04)% for D99% and D95%, respectively. The 4 calculated plan complexity metrics consistently show that the re-optimized plans are quantitatively less complex than the original plan. The gamma passing rate of the re-optimized plans improved from (92.2 ± 2.0)% to (94.2 ± 1.6)% with the 1%/1-mm criterion, and (98.7 ± 1.0)% to (99.5 ± 0.3)% with the 2%/2-mm criterion. Overall, the re-optimized plans achieve at least a 10% MU reduction (11.7% to 24.6%). Our study shows that optimization with the MU objective tool can reduce plan complexity and improves dose delivery accuracy, while not compromising the dose distribution.

Dosimetry audit for megavoltage photon beams applied in non-reference conditions

PurposeWe have conducted for the first time a Malaysian postal dosimetry audit of external beam under non-reference conditions by evaluating the output performance while screening for systematic errors within the dosimetry chain. The potential use from the choice of detector were investigated along with the search for other sources of discrepancies. MethodsTen radiotherapy centres were audited, encompassing 16 megavoltage photon beam arrangements, adopting the IAEA postal dosimetry protocol for non-reference conditions, with a holder modified to accommodate three TLD types: Ge-doped cylindrical silica fibres (CF), Ge-doped flat silica fibres (FF), and TLD-100 powder. ResultsEight of the centres operated within ± 5% of stated dose, one other exceeding tolerance for all measured points, and one did not return any dosimeters for analysis after failing the initial irradiations. Post remedial measures, the mean relative response for CF, FF, and TLD-100 was 1.00, 0.99, and 0.98 respectively, with associated coefficients of variation 6.87%, 6.45%, and 5.06%. ConclusionHigh quality radiotherapy clinical practice postal dosimetry audits that are based on sensitive TLDs are seen to be particularly effective in identifying and resolving dose delivery discrepancies.

Virtual patient-specific QA with DVH-based metrics.

We demonstrate a virtual pretreatment patient-specific QA (PSQA) procedure that is capable of quantifying dosimetric effect on patient anatomy for both intensity modulated radiotherapy (IMRT) and volumetric modulated arc therapy (VMAT). A machine learning prediction model was developed to use linear accelerator parameters derived from the DICOM-RT plan to predict delivery discrepancies at treatment delivery (defined as the difference between trajectory log file and DICOM-RT) and was coupled with an independent Monte Carlo dose calculation algorithm for dosimetric analysis. Machine learning models for IMRT and VMAT were trained and validated using 120 IMRT and 206 VMAT fields of prior patients, with 80% assigned for iterative training and testing, and 20% for post-training validation. Various prediction models were trained and validated, with the final models selected for clinical implementation being a boosted tree and bagged tree for IMRT and VMAT, respectively. After validation, these models were then applied clinically to predict the machine parameters at treatment delivery for 7 IMRT plans from various sites (61 fields) and 10 VMAT multi-target intracranial radiosurgery plans (35 arcs) and compared to the dosimetric effect calculated directly from trajectory log files. Dose indices tracked for targets and organs at risk included dose received by 99%, 95%, and 1% of the volume, mean dose, percent of volume receiving 25%-100% of the prescription dose. The average coefficient of determination (r2 ) when comparing intra-field predicted and actual delivery error was 0.987±0.012 for IMRT and 0.895±0.095 for VMAT, whereas r2 when comparing inter-field predicted versus actual delivery error was 0.982 for IMRT and 0.989 for VMAT. Regarding dosimetric analysis, r2 when comparing predicted versus actual dosimetric changes for all dose indices was 0.966 for IMRT and 0.907 for VMAT. Prediction models can be used to anticipate the dosimetric effect calculated from trajectory files and have potential as a "delivery-free" pretreatment analysis to enhance PSQA.

Advancing Health Equity for Medicaid Beneficiaries by Adding Colorectal Cancer Screening to the Centers for Medicare and Medicaid Services Adult Core Set

Advancing Health Equity for Medicaid Beneficiaries by Adding Colorectal Cancer Screening to the Centers for Medicare and Medicaid Services Adult Core Set

A tool for patient-specific prediction of delivery discrepancies in machine parameters using trajectory log files.

Multileaf collimator (MLC) delivery discrepancy between planned and actual (delivered) positions have detrimental effect on the accuracy of dose distributions for both IMRT and VMAT. In this study, we evaluated the consistency of MLC delivery discrepancies over the course of treatment and over time to verify that a predictive machine learning model would be applicable throughout the course of treatment. Next, the MLC and gantry positions recorded in prior trajectory log files were analyzed to build a machine learning algorithm to predict MLC positional discrepancies during delivery for a new treatment plan. An open source tool was developed and released to predict the MLC positional discrepancies at treatment delivery for any given plan. Trajectory log files of 142 IMRT plans and 125 VMAT plans from 9 Varian TrueBeam linear accelerators were collected and analyzed. The consistency of delivery discrepancy over patient-specific quality assurance (QA) and patient treatment deliveries was evaluated. Data were binned by treatment site and machine type to determine their relationship with MLC and gantry angle discrepancies. Motion-related parameters including MLC velocity, MLC acceleration, control point, dose rate, and gravity vector, gantry velocity and gantry acceleration, where applicable, were analyzed to evaluate correlations with MLC and gantry discrepancies. Several regression models, such as simple/multiple linear regression, decision tree, and ensemble method (boosted tree and bagged tree model) were used to develop a machine learning algorithm to predict MLC discrepancy based on MLC motion parameters. MLC discrepancies at patient-specific QA differed from those at patient treatment deliveries by a small (mean=0.0021±0.0036mm, P=0.0089 for IMRT; mean=0.0010±0.0016mm, P=0.0003 for VMAT) but statistically significant amount, likely due to setting the gantry angle to zero for QA in IMRT. MLC motion parameters, MLC velocity and gravity vector, showed significant correlation (P<0.001) with MLC discrepancy, especially MLC velocity, which had an approximately linear relationship (slope = -0.0027, P<0.001, R2 =0.79). Incorporating MLC motion parameters, the final generalized model trained by data from all linear accelerators can predict MLC discrepancy to a high degree of accuracy with high correlation (R2 =0.86) between predicted and actual MLC discrepancies. The same prediction results were found across different treatment sites and linear accelerators. We have developed a machine learning model using trajectory log files to predict the MLC discrepancies during delivery. This model has been a released as a research tool in which a DICOM-RT with predicted MLC positions can be generated using the original DICOM-RT file as input. This tool can be used to simulate radiotherapy treatment delivery and may be useful for studies evaluating plan robustness and dosimetric uncertainties from treatment delivery.

Healthcare delivery for HIV-positive people with tuberculosis in Europe.

In a 2013 survey, we reported distinct discrepancies in delivery of tuberculosis (TB) and HIV services in eastern Europe (EE) vs. western Europe (WE). To verify the differences in TB and HIV services in EE vs. WE. Twenty-three sites completed a survey in 2018 (EE, 14; WE, nine; 88% response rate). Results were compared across as well as within the two regions. When possible, results were compared with the 2013 survey. Delivery of healthcare was significantly less integrated in EE: provision of TB and HIV services at one site (36% in EE vs. 89% in WE; P=0.034), and continued TB follow-up in one location (42% vs. 100%; P=0.007). Although access to TB diagnostics, standard TB and HIV drugs was generally good, fewer sites in EE reported unlimited access to rifabutin/multi-drug-resistant TB (MDR-TB) drugs, HIV integrase inhibitors and opioid substitution therapy (OST). Compared with 2013, routine usage of GeneXpert was more common in EE in 2018 (54% vs. 92%; P=0.073), as was access to moxifloxacin (46% vs. 91%; P=0.033), linezolid (31% vs. 64%; P=0.217), and bedaquiline (0% vs. 25%; P=0.217). Integration of TB and HIV services (46% vs. 39%; P=1.000) and provision of OST to patients with opioid dependency (54% vs. 46%; P=0.695) remained unchanged. Delivery of TB and HIV healthcare, including integration of TB and HIV care and access to MDR-TB drugs, still differs between WE and EE, as well as between individual EE sites.

Barriers to Evidence-Based Treatment of Serious Burns: The Impact of Implicit Bias on Clinician Perceptions of Patient Adherence.

The underlying assumption of modern evidence-based practice is that treatment decisions made by healthcare providers are based solely on the best available scientific data. However, the connection between evidence informed care guidelines and the provision of care remains ambiguous. In reality, a number of contextual and nonclinical factors can also play a role, among which is the implicit bias that affects the way in which we approach or treat others based on irrelevant, individual characteristics despite conscious efforts to treat everyone equally. Influenced by the social and demographic characteristics of patients, this bias and its associated perceptions have been shown to affect clinical decision making and access to care across multiple conditions and settings. This summary article offers an introduction to how the phenomenon of implicit bias can impact on treatment compliance in multiple care contexts, its potential presence and impact in burns care and describes some of the strategies which offer possible solutions to reducing the disconnect between the conscious attempts to deliver equitable care and the discrepancies in care delivery that remain.

Do rurally focussed dental programs produce regional and rural dentists? An exploratory cross-sectional survey examining Australian dental graduates of 2015.

[extract] The Australian dental workforce has increased significantly over the past decade; however, severe geographical maldistribution currently disadvantages those living in rural areas. Thus, recruiting and retaining dentists is a critical challenge for rural community health services. To strategically address the rural Australian workforce deficit with an educational intervention, three rurally focussed dental schools have been established since 2007, each with curricula providing students with additional education and training experiences informed by health delivery discrepancies between metropolitan and rural communities. However, while these new rurally focused dental schools have been operating for almost a decade, little has been done to investigate whether they are actually producing more rural dentists than their metropolitan counterparts. This study investigates the practice location of Australian dental graduates who completed their degrees from three rurally focussed and three metropolitan dental programs in 2015.

A correlation study between clinical dose distribution and gamma passing rates in pre-treatment Tomotherapy quality assurance

Introduction: we focused on Tomotherapy patient-specific Quality Assurance (QA) in prostate cancer cases. Conventionally it is possible to accomplish QA with the calculation of in-phantom gamma passing rate (GPR). However, GPR, although widely used, is not a good predictor of the agreement between calculated and delivered dose to the patient and recent studies suggest the use of clinical metrics. To our best knowledge, there are no similar studies in Tomotherapy. In this work, we used 3DVH software and ArcCheck matrix (SunNuclear Corporation, Melbourne, FL) and we looked for the correlation between clinical metrics results and phantom GPRs. 3DVH applies perturbations to the in-patient TPS planned dose to account for discrepancies in dose delivery. Materials and methods: we retrospectively selected patients between those treated in our centre for prostatic cancer with Tomotherapy between April 2017 and August 2018. We submitted all plans to a specific QA; for data acquisition, we used the ArcCheck matrix and SNC patient software. We compared delivered and calculated volumetric dose distributions via the GPR and evaluated the clinical metrics using the 3DVH software. Unlike what previous authors have done, we did not investigate DVH clinical endpoints (e.g. rectum v70) agreement, but the complete dose distributions agreement applying gamma metric to the comparison of in-patient calculated and delivered dose distribution. For statistical analysis, we made both two tails Pearson’s correlation coefficient calculation and a linear regression evaluation. Results: from our results do not emerge any significant correlation between GPR and 3DVH results for every DTA and %D values used in gamma analysis. Conclusions: from this study, the need for employing clinical patient metrics instead of the simple gamma analysis, already suggested for conventional Linacs treatments, is extended to Tomotherapy treatments. Further studies are necessary to extend this result to Tomotherapy pre-treatment QA to other anatomical districts.

CLO19-026: Determining the Treatment Decision of Tumors With Mixed Response

Introduction: Individuals receiving systemic anticancer therapies for advanced solid tumors routinely undergo imaging studies to assess the efficacy of the treatment. Mixed response (MR) to cancer therapy is a common but poorly described phenomenon. There is a paucity of data regarding both the incidence and possible mechanisms of this clinical quandary. Potential etiologies include tumor heterogeneity, differences in tumor microenvironment, and discrepancies in drug delivery to different tumor deposits. It is also possible that MR simply reflects differences in the rate of resistance emerging. MR represents a therapeutic dilemma for the clinician. Methods: Mixed tumor response was defined as: One tumor decreasing in size; one tumor increasing in size (classified as RECIST response/progressions), One tumor stable; another tumor progressing, One tumor stable; another tumor responding, New tumor; another tumor responding or remaining stable. Between 2015 and 2017, 120 restaging CT scans were reviewed of patients who had received at least 1 line of therapy for advanced cancer diagnosis which showed MR; hematologic malignancies were excluded. Charts were reviewed to determine the clinical decision that was made at the time of the MR. Results: A total of 120 scans with MR were reviewed from various solid tumor diagnoses. 38 scans were excluded due to loss of follow-up or death. Of the remaining 82 scans, therapy was switched in 30, the same therapy was continued in 50, and an additional agent was added to the current treatment in 2 cases (Table). Of the patients in which treatment was switched, 20% (6/30) showed response to treatment on the following scan. Of the cases that were kept on current treatment, none showed response on the following restaging scan which was done 6–8 weeks later. There were 4 (10%) deaths prior to the next scan in the group that had treatment switched and similarly 5 deaths (10%) prior to the next scan in the group in which treatment remained the same. Conclusion: MR is associated with a poor prognosis, irrespective of treatment decisions. These data are retrospective and our sample size is small, so definitive conclusions cannot be drawn. However, changing therapy when a MR is observed may be of benefit to some patients. A prospective evaluation to more accurately describe and understand the MR phenomenon is warranted.

8. Analysis of dose variations and sources of error in VMAT treatments with an EPID-based in vivo dosimetry system

Purpose To evaluate the daily dose delivery discrepancies catching sources of errors in VMAT treatments with a 3D EPID-based in vivo dosimetry (IVD) system. Methods and materials The IVD software PerFRACTION (Sun Nuclear Corporation) was used. PerFRACTION is based on the information concerning MLC and collimator positions obtained by EPID images and on the information of log files, such as MUs and the gantry angles. From these informations, a collapsed-cone/superposition algorithm (SDC) is used to calculate the dose distribution on daily CBCT images [1] . It also uses the SDC to produce an entire dose volume to check against that from the TPS. First of all, we calculated the dose discrepancies ( Δ D%) at the isocenter (ID) and the 3D gamma passing rate (%GP) between our reference (AAA) and SDC algorithm, for 81 plans. About IVD, 3D dose distributions were reconstructed for 405 fractions of 53 patients, including prostates (21%), lungs (15%), Head & Neck (17%), PBI (10%), and palliatives (38%). We evaluated Δ D% between reference and daily dose distribution in terms of dose to 95% of the volume ( D 95 % ) , dose to 2% of the volume ( D 2 % ) and average dose of the target. Results We obtained for ID an average Δ D% equal to (1.8 ± 0.8)% and an average %GP equal to (99 ± 2)%. For IVD, the mean Δ D% was equal to (−0.3 ± 2.2)% for D 95 % , (0.9 ± 1.4)% for D 2 % , and (0.5 ± 1.2)% for average dose. 75% of fractions showed Δ D% inferior to 2%. For 74 (18%) of the analyzed dose points, Δ D% was greater than the 3%. For the fractions that exceed 3%, the errors are due to setup (28.4%), patient anatomy (40.5%), setup + anatomy (27%) and bolus positioning (4%). No machine-based errors were observed for these patients. Conclusion 3D EPID-based IVD is a powerful method to cacht and quantify delivery discrepancies during radiotherapy process.

In vivo Portal Imaging Dosimetry Identifies Delivery Errors in Rectal Cancer Radiotherapy on the Belly Board Device.

Purpose:We recently developed a novel, open-source in vivo dosimetry that uses the electronic portal imaging device to detect dose delivery discrepancies. We applied our method on patients with rectal cancer treated on a belly board device.Methods: In vivo dosimetry was performed on 10 patients with rectal cancer treated prone on the belly board with a 4-field box arrangement. Portal images were acquired approximately once per week from each treatment beam. Our dosimetry method used these images along with the planning CT to reconstruct patient planar dose at isocenter depth.Results:Our algorithm proved sensitive to dose discrepancies and detected discordances in 7 patients. The majority of these were due to soft tissue differences between planning and treatment, present despite matching to bony anatomy. As a result of this work, quality assurance procedures have been implemented for our immobilization devices.Conclusion: In vivo dosimetry is a powerful quality assurance tool that can detect delivery discrepancies, including changes in patient setup and position. The added information on actual dose delivery may be used to evaluate equipment and process quality and to guide for adaptive radiotherapy.

SU‐D‐BRC‐03: Development and Validation of an Online 2D Dose Verification System for Daily Patient Plan Delivery Accuracy Check

Purpose:All plan verification systems for particle therapy are designed to do plan verification before treatment. However, the actual dose distributions during patient treatment are not known. This study develops an online 2D dose verification tool to check the daily dose delivery accuracy.Methods:A Siemens particle treatment system with a modulated scanning spot beam is used in our center. In order to do online dose verification, we made a program to reconstruct the delivered 2D dose distributions based on the daily treatment log files and depth dose distributions. In the log files we can get the focus size, position and particle number for each spot. A gamma analysis is used to compare the reconstructed dose distributions with the dose distributions from the TPS to assess the daily dose delivery accuracy. To verify the dose reconstruction algorithm, we compared the reconstructed dose distributions to dose distributions measured using PTW 729XDR ion chamber matrix for 13 real patient plans. Then we analyzed 100 treatment beams (58 carbon and 42 proton) for prostate, lung, ACC, NPC and chordoma patients.Results:For algorithm verification, the gamma passing rate was 97.95% for the 3%/3mm and 92.36% for the 2%/2mm criteria. For patient treatment analysis,the results were 97.7%±1.1% and 91.7%±2.5% for carbon and 89.9%±4.8% and 79.7%±7.7% for proton using 3%/3mm and 2%/2mm criteria, respectively. The reason for the lower passing rate for the proton beam is that the focus size deviations were larger than for the carbon beam. The average focus size deviations were −14.27% and −6.73% for proton and −5.26% and −0.93% for carbon in the x and y direction respectively.Conclusion:The verification software meets our requirements to check for daily dose delivery discrepancies. Such tools can enhance the current treatment plan and delivery verification processes and improve safety of clinical treatments.

Government reports versus offenders' experiences: toward the resolution of discrepancies in healthcare and healthcare delivery.

- Canadian literature on federal correctional institutions and prison living indicate a shortage inadequate and available healthcare services to meet the needs of the prison population, despite prisoners higher rates of health challenges (e.g. mental health, addictions, HIV/AIDS) in comparison to the general population. With fewer resources, concerns arise about the delivery, quantity, and quality of penal healthcare provision. Thus, the authors examines former prisoners' experiences of, in comparison to government reports on, wait-times, and request processes for healthcare services, as well as issues of access, quality of interactions with healthcare professionals and the regulations and policies governing healthcare provision. The paper aims to discuss these issues. - The authors compare data gathered from interviews with 56 former-federal prisoners with publicly available Correctional Services Canada reports on healthcare delivery, staff-prisoner interactions, programmes and services, and overall physical and mental health to identify consistencies and inconsistencies between the government's and former prisoners' understandings of penal healthcare. - Discrepancies exist between prisoners reported experiences of healthcare provision and government reports. Prisoners are dissatisfied with healthcare provision in more secure facilities or when they feel their healthcare needs are not met yet become more satisfied in less secure institutions or when their needs are eventually met. - Theories of administrative control frame the analyses, including discrepancies between parolee experiences and Correctional Service Canada reports. Policy recommendations to improve healthcare provision are highlighted.

Comparison of planned and measured rectal dose in-vivo during high dose rate Cobalt-60 brachytherapy of cervical cancer

Cobalt-60 (Co-60) is a relatively new source for the application of high-dose rate (HDR) brachytherapy. Radiation dose to the rectum is often a limiting factor in achieving the full prescribed dose to the target during brachytherapy of cervical cancer. The aim of this study was to measure radiation doses to the rectum in-vivo during HDR Co-60 brachytherapy. A total of eleven HDR brachytherapy treatments of cervical cancer were recruited in this study. A series of diodes incorporated in a rectal probe was inserted into the patient's rectum during each brachytherapy procedure. Real-time measured rectal doses were compared to calculated doses by the treatment planning system (TPS). The differences between calculated and measured dose ranged from 8.5% to 41.2%. This corresponds to absolute dose differences ranging from 0.3 Gy to 1.5 Gy. A linear relationship was observed between calculated and measured doses with linear regression R2 value of 0.88, indicating close association between the measured and calculated doses. In general, absorbed doses for the rectum as calculated by TPS were observed to be higher than the doses measured using the diode probe. In-vivo dosimetry is an important quality assurance method for HDR brachytherapy of cervical cancer. It provides information that can contribute to the reduction of errors and discrepancies in dose delivery. Our study has shown that in-vivo dosimetry is feasible and can be performed to estimate the dose to the rectum during HDR brachytherapy using Co-60.