DoRGaN: Development of Quality Assurance and Quality Control Systems for High Dose Rate Brachytherapy Based on GaN Dosimetry Probes

Background

Safe High Dose Rate Brachytherapy (HDR-BT) requires quality assurance/quality control (QA/QC) according to IPEM and ESTRO recommendations. Recent advances in real-time dosimetry and related developments of QA, QC and in vivo dosimetry (IVD) systems have offered new possibilities for effective independent treatment verification, and thus for improving the patient safety.

Guidelines and considerations for the use of system suitability and quality control samples in mass spectrometry assays applied in untargeted clinical metabolomic studies

Background

Quality assurance (QA) and quality control (QC) are two quality management processes that are integral to the success of metabolomics including their application for the acquisition of high quality data in any high-throughput analytical chemistry laboratory. QA defines all the planned and systematic activities implemented before samples are collected, to provide confidence that a subsequent analytical process will fulfil predetermined requirements for quality. QC can be defined as the operational techniques and activities used to measure and report these quality requirements after data acquisition.

Aim of review

This tutorial review will guide the reader through the use of system suitability and QC samples, why these samples should be applied and how the quality of data can be reported.

Key scientific concepts of review

System suitability samples are applied to assess the operation and lack of contamination of the analytical platform prior to sample analysis. Isotopically-labelled internal standards are applied to assess system stability for each sample analysed. Pooled QC samples are applied to condition the analytical platform, perform intra-study reproducibility measurements (QC) and to correct mathematically for systematic errors. Standard reference materials and long-term reference QC samples are applied for inter-study and inter-laboratory assessment of data.

     

Quality assurance and quality control processes: summary of a metabolomics community questionnaire

Introduction

The Metabolomics Society Data Quality Task Group (DQTG) developed a questionnaire regarding quality assurance (QA) and quality control (QC) to provide baseline information about current QA and QC practices applied in the international metabolomics community.

Objectives

The DQTG has a long-term goal of promoting robust QA and QC in the metabolomics community through increased awareness via communication, outreach and education, and through the promotion of best working practices. An assessment of current QA and QC practices will serve as a foundation for future activities and development of appropriate guidelines.

Method

QA was defined as the set of procedures that are performed in advance of analysis of samples and that are used to improve data quality. QC was defined as the set of activities that a laboratory does during or immediately after analysis that are applied to demonstrate the quality of project data. A questionnaire was developed that included 70 questions covering demographic information, QA approaches and QC approaches and allowed all respondents to answer a subset or all of the questions.

Result

The DQTG questionnaire received 97 individual responses from 84 institutions in all fields of metabolomics covering NMR, LC-MS, GC-MS, and other analytical technologies.

Conclusion

There was a vast range of responses concerning the use of QA and QC approaches that indicated the limited availability of suitable training, lack of Standard Operating Procedures (SOPs) to review and make decisions on quality, and limited use of standard reference materials (SRMs) as QC materials. The DQTG QA/QC questionnaire has for the first time demonstrated that QA and QC usage is not uniform across metabolomics laboratories. Here we present recommendations on how to address the issues concerning QA and QC measurements and reporting in metabolomics.

     

A systematic quality assurance framework for the upgrade of radiation oncology information systems

In spite of its importance, no systematic and comprehensive quality assurance (QA) program for radiation oncology information systems (ROIS) to verify clinical and treatment data integrity and mitigate against data errors/corruption and/or data loss risks is available. Based on data organization, format and purpose, data in ROISs falls into five different categories: (1) the ROIS relational database and associated files; (2) the ROIS DICOM data stream; (3) treatment machine beam data and machine configuration data; (4) electronic medical record (EMR) documents; and (5) user-generated clinical and treatment reports from the ROIS. For each data category, this framework proposes a corresponding data QA strategy to very data integrity. This approach verified every bit of data in the ROIS, including billions of data records in the ROIS SQL database, tens of millions of ROIS database-associated files, tens of thousands of DICOM data files for a group of selected patients, almost half a million EMR documents, and tens of thousands of machine configuration files and beam data files. The framework has been validated through intentional modifications with test patient data. Despite the ‘big data’ nature of ROIS, the multiprocess and multithread nature of our QA tools enabled the whole ROIS data QA process to be completed within hours without clinical interruptions. The QA framework suggested in this study proved to be robust, efficient and comprehensive without labor-intensive manual checks and has been implemented for our routine ROIS QA and ROIS upgrades.     

Patient dose monitoring systems: A new way of managing patient dose and quality in the radiology department

PurposeDue to the upcoming European Directive (2013/59/EURATOM) and the increased focus on patient safety in international guidelines and regulations, Patient Dose Monitoring Systems, also called Dose Management Systems (DMS), are introduced in medical imaging departments. This article focusses on the requirements for a DMS, its benefits and the necessary implementation steps.MethodThe implementation of a DMS can be perceived as a lengthy, yet worthy, procedure: users have to select the appropriate system for their applications, prepare data collection, validate, perform configuration, and start using the results in quality improvement projects.ResultsA state of the art DMS improves the quality of service, ensures patient safety and optimizes the efficiency of the department. The gain is multifaceted: the initial goal is compliance monitoring against diagnostic reference levels. At a higher level, the user gets an overview of the performance of the devices or centers that are under his supervision. Error identification, generation of alerts and workflow analysis are additional benefits. It can also enable a more patient-centric approach with personalized dosimetry. Skin dose, size-specific dose estimates and organ doses can be calculated and evaluated per patient.ConclusionA DMS is a powerful tool and essential for improved quality and patient care in a radiology department. It can be configured to the needs of medical physicists, radiologists, technologists, even for the management of the hospital. Collaboration between all health professionals and stakeholders, input-output validation and communication of findings are key points in the process of a DMS implementation.     

Announcement—guidance document for acquiring reliable data in ecological restoration projects

The Laurentian Great Lakes are undergoing intensive ecological restoration in Canada and the United States. In the United States, an interagency committee was formed to facilitate implementation of quality practices for federally funded restoration projects in the Great Lakes basin. The Committee's responsibilities include developing a guidance document that will provide a common approach to the application of quality assurance and quality control (QA/QC) practices for restoration projects. The document will serve as a “how‐to” guide for ensuring data quality during each aspect of ecological restoration projects. In addition, the document will provide suggestions on linking QA/QC data with the routine project data and hints on creating detailed supporting documentation. Finally, the document will advocate integrating all components of the project, including QA/QC applications, into an overarching decision‐support framework. The guidance document is expected to be released by the U.S. EPA Great Lakes National Program Office in 2017.     

Cost effectiveness of magnetic resonance imaging in the neurosciences.

OBJECTIVES--To measure, in a service setting, the effect of magnetic resonance imaging on diagnosis, diagnostic certainty, and patient management in the neurosciences; to measure the cost per patient scanned; to estimate the marginal cost of imaging and compare this with its diagnostic impact; to measure changes in patients'' quality of life; and to record the diagnostic pathway leading to magnetic resonance imaging. DESIGN--Controlled observational study using questionnaires on diagnosis and patient management before and after imaging. Detailed costing study. Quality of life questionnaires at the time of imaging and six months later. Diagnostic pathways extracted from medical records for a representative sample. SETTING--Regional superconducting 1.5 T magnetic resonance service. SUBJECTS--782 consecutive neuroscience patients referred by consultants for magnetic resonance imaging during June 1988-9; diagnostic pathways recorded for 158 cases. MAIN OUTCOME MEASURES--Costs of magnetic resonance imaging and preliminary investigations; changes in planned management and resulting savings; changes in principal diagnosis and diagnostic certainty; changes in patients'' quality of life. RESULTS--Average cost of magnetic resonance imaging was estimated at 206.20/patient pounds (throughput 2250 patients/year, 1989-90 prices including contrast and upgrading). Before magnetic resonance imaging diagnostic procedures cost 164.40/patient pounds (including inpatient stays). Management changed after imaging in 208 (27%) cases; saving an estimated 80.90/patient pounds. Confidence in planned management increased in a further 226 (29%) referrals. Consultants'' principal diagnosis changed in 159 of 782 (20%) referrals; marginal cost per diagnostic change was 626 pounds. Confidence in diagnosis increased in 236 (30%) referrals. No improvement in patients'' quality of life at six month assessment. CONCLUSIONS--Any improvement in diagnosis with magnetic resonance imaging is achieved at a higher cost. Techniques for monitoring the cost effectiveness of this technology need to be developed.     

Quality control issues in point of care testing

* Quality Control (QC) in Point of Care Testing (PoCT) is often thought of as a complex issue; however intelligent system analysis can simplify matters and greatly increase the chances of a well controlled system. What we want to achieve is a QC program which adequately controls the PoCT system, but does not excessively contribute to the operating costs or complexity of maintaining a PoCT instrument, or network of instruments. * Don't neglect effective pre-analytical work: good documentation, operator training, monitoring, and analyser maintenance programs are essential, as for any analyser. * Look closely at your analyser: Is it a "laboratory type" instrument or cartridge or strip based? Can it perform multiple test types or a single test only? How is it calibrated? Does it have built in self-check capabilities or an electronic check cartridge? Is the sample in contact with the instrument? What are the cartridge/strip/reagent storage requirements? * Establish where the analysis is taking place and which system component is involved. * Tailor your QC program to target this component, but still check the system as a whole. * A common approach is to check cartridges/strips on delivery and run a QA sample at least monthly to check storage conditions and operator performance. If there is no independent electronic instrument check, daily QC checks are also recommended. * Don't be afraid to stray beyond conventional QC models if necessary. Some PoCT systems are not adequately controlled by the application of conventional QC alone.     

A 3-year experience of quality control and quality assurance in the multisite delivery of a lymphocyte-based cellular therapy for renal cell carcinoma

Autolymphocyte therapy (ALT) is outpatient-based adoptive immunotherapy using ex vivo-activated memory T-cells. To support the safe and reproducible delivery of ALT at three cell processing facilities (Boston, MA; Atlanta, GA; Orange, CA) we created a comprehensive quality assurance/quality control program compliant with recent FDA guidance relevant to activated lymphocytes and somatic cell therapies. Each facility performed extensive QC testing to ensure sterility, viability, and proper cell yield. Additonally, several QC tests were performed at Cellocr's centralized reference laboratory to monitor cell potency and identity of the ex vivo-processed lymphocytes. We report here the successful implementation of this QA/QC program for ALT which has resulted in the safe preparation and delivery of cell infusion products amounting to over 3600 treatments at seven clinical sites nationwide. We believe this program will serve as a model for other cellular therapies.     

Quality Controls in Digital Mammography protocol of the EFOMP Mammo Working group

This article aims to present the protocol on Quality Controls in Digital Mammography published online in 2015 by the European Federation of Organisations for Medical Physics (EFOMP) which was developed by a Task Force under the Mammo Working Group. The main objective of this protocol was to define a minimum set of easily implemented quality control tests on digital mammography systems that can be used to assure the performance of a system within a set and acceptable range. Detailed step-by-step instructions have been provided, limiting as much as possible any misinterpretations or variations by the person performing. It is intended that these tests be implemented as part of the daily routine of medical physicists and system users throughout Europe in a harmonised way so allowing results to be compared. In this paper the main characteristics of the protocol are illustrated, including examples, together with a brief summary of the contents of each chapter. Finally, instructions for the download of the full protocol and of the related software tools are provided.     

Assessing accuracy and precision for field and laboratory data: a perspective in ecosystem restoration

Unlike most laboratory studies, rigorous quality assurance/quality control (QA/QC) procedures may be lacking in ecosystem restoration (“ecorestoration”) projects, despite legislative mandates in the United States. This is due, in part, to ecorestoration specialists making the false assumption that some types of data (e.g. discrete variables such as species identification and abundance classes) are not subject to evaluations of data quality. Moreover, emergent behavior manifested by complex, adapting, and nonlinear organizations responsible for monitoring the success of ecorestoration projects tend to unconsciously minimize disorder, QA/QC being an activity perceived as creating disorder. We discuss similarities and differences in assessing precision and accuracy for field and laboratory data. Although the concepts for assessing precision and accuracy of ecorestoration field data are conceptually the same as laboratory data, the manner in which these data quality attributes are assessed is different. From a sample analysis perspective, a field crew is comparable to a laboratory instrument that requires regular “recalibration,” with results obtained by experts at the same plot treated as laboratory calibration standards. Unlike laboratory standards and reference materials, the “true” value for many field variables is commonly unknown. In the laboratory, specific QA/QC samples assess error for each aspect of the measurement process, whereas field revisits assess precision and accuracy of the entire data collection process following initial calibration. Rigorous QA/QC data in an ecorestoration project are essential for evaluating the success of a project, and they provide the only objective “legacy” of the dataset for potential legal challenges and future uses.     

Mise en place d’une équipe d’experts en physique médicale au Luxembourg : organisation, résultats qualité et radioprotection en médecine nucléaire (2002–2011)

Implementations of the statutory UE requirements concerning ionizing radiation in the medical domain (96/29/Euratom, 13th May 1996; 97/43/Euratom, 30th June 1997) have changed quality control in medical imaging departments. In Luxembourg, the Ministry of Health and the “Union of Luxembourg Hospitals” have thus created a “Medical Physics Cell” (five Medical Physics experts). It is in charge of implementing a standardized program of Quality Assurance (QA) and radiation protection relative to patients as well as staffs, on a coordinated national basis, in all five in-hospital nuclear medicine departments of the country. The program distributes QA controls between three levels, various periodicities and degrees of expertise. It sensitizes staff and medical doctors by trainings and facilitates ISO accreditation. From 2002 to 2011, in all five in-hospital departments of nuclear medicine of a small country, image quality, radiation protection and reference values of each medical equipment were defined and implemented in a standard way. In 2011, the medical physics cell, the driving force leading to the institutionalization of the discipline within the nuclear medicine departments, is considered as a partner rather than as a control body by the teams in charge of the nuclear medicine departments.     

AIAP: A Quality Control and Integrative Analysis Package to Improve ATAC-seq Data Analysis

Assay for transposase-accessible chromatin with high-throughput sequencing (ATAC-seq) is a technique widely used to investigate genome-wide chromatin accessibility. The recently published Omni-ATAC-seq protocol substantially improves the signal/noise ratio and reduces the input cell number. High-quality data are critical to ensure accurate analysis. Several tools have been developed for assessing sequencing quality and insertion size distribution for ATAC-seq data; however, key quality control (QC) metrics have not yet been established to accurately determine the quality of ATAC-seq data. Here, we optimized the analysis strategy for ATAC-seq and defined a series of QC metrics for ATAC-seq data, including reads under peak ratio (RUPr), background (BG), promoter enrichment (ProEn), subsampling enrichment (SubEn), and other measurements. We incorporated these QC tests into our recently developed ATAC-seq Integrative Analysis Package (AIAP) to provide a complete ATAC-seq analysis system, including quality assurance, improved peak calling, and downstream differential analysis. We demonstrated a significant improvement of sensitivity (20%–60%) in both peak calling and differential analysis by processing paired-end ATAC-seq datasets using AIAP. AIAP is compiled into Docker/Singularity, and it can be executed by one command line to generate a comprehensive QC report. We used ENCODE ATAC-seq data to benchmark and generate QC recommendations, and developed qATACViewer for the user-friendly interaction with the QC report. The software, source code, and documentation of AIAP are freely available at https://github.com/Zhang-lab/ATAC-seq_QC_analysis.     

An integrated fuzzy QFD framework for new product development

An important source of competitive advantage, survival and renewal for firms is the successful new product development (NPD). Quality function deployment (QFD) aims to facilitate the NPD process from product conceptualization to production requirements; however, conventional QFD has its shortcomings. Even though modified QFD models have been proposed in literature, a comprehensive model is necessary. In this paper, factors in each phase of the QFD is prepared first through literature review and interview with domain experts. Fuzzy Delphi method is adopted to select the critical factors, and fuzzy interpretive structural modeling is applied to determine the relationships among the critical factors. The results are then used to construct houses of quality for QFD, which is incorporated by fuzzy analytic network process. A case study of a thin film transistor liquid crystal display firm is carried out to verify the practicality of the proposed framework.     

An audit of a hospital-based Doppler ultrasound quality control protocol using a commercial string Doppler phantom

Results from a four-year audit of a Doppler quality assurance (QA) program using a commercially available Doppler string phantom are presented. The suitability of the phantom was firstly determined and modifications were made to improve the reliability and quality of the measurements. QA of Doppler ultrasound equipment is very important as data obtained from these systems is used in patient management. It was found that if the braided-silk filament of the Doppler phantom was exchanged with an O-ring rubber filament and the velocity range below 50 cm/s was avoided for Doppler quality control (QC) measurements, then the maximum velocity accuracy (MVA) error and intrinsic spectral broadening (ISB) results obtained using this device had a repeatability of 18 ± 3.3% and 19 ± 3.5%, respectively. A consistent overestimation of the MVA of between 12% and 56% was found for each of the tested ultrasound systems. Of more concern was the variation of the overestimation within each respective transducer category: MVA errors of the linear, curvilinear and phased array probes were in the range 12.3–20.8%, 32.3–53.8% and 27–40.7%, respectively. There is a dearth of QA data for Doppler ultrasound; it would be beneficial if a multicentre longitudinal study was carried out using the same Doppler ultrasound test object to evaluate sensitivity to deterioration in performance measurements.     

How to measure CT image quality: Variations in CT-numbers,uniformity and low contrast resolution for a CT quality assurance phantom

PurposeQuality assurance (QA) phantoms for testing different image quality parameters in computed tomography (CT) are commercially available. Such phantoms are also used as reference for acceptance in the specifications of CT-scanners. The aim of this study was to analyze the characteristics of the most commonly used QA phantom in CT: Catphan 500/504/600.MethodsNine different phantoms were scanned on the same day, on one CT-scanner with the same parameter settings. Interphantom variations in CT-number values, image uniformity and low contrast resolution were evaluated for the phantoms. Comparisons between manual image analysis and results obtained from the automatic evaluation software QAlite were performed.ResultsSome interphantom variations were observed in the low contrast resolution and the CT-number modules of the phantoms. Depending on the chosen regulatory framework, the variations in CT-numbers can be interpreted as substantial. The homogenous modules were found more invariable. However, the automatic image analysis software QAlite measures image uniformity differently than recommended in international standards, and will not necessarily give results in agreement with these standards.ConclusionsIt is important to consider the interphantom variations in relation to ones framework, and to be aware of which phantom is used to study CT-numbers and low contrast resolution for a specific scanner. Comparisons with predicted values from manual and acceptance values should be performed with care and consideration. If automatic software-based evaluations are to be used, users should be aware that large differences can exist for the image uniformity testing.     

Practical radiation dosimetry across a variety of CBCT devices in Radiology

Cone beam technology is becoming more prominent in Radiology. In our hospital we have an extremity CT, an O-arm and a number of C-arms offering 3D capabilities. Each of these modalities use cone beam CT (CBCT) technology to image the area of interest in one single rotation. Traditional CTDI metrics for radiation dosimetry in CT depend on narrow beam geometry. The relevance of the CTDI as a dose indicator for cone beam scanning is contentious due to underestimation of dose lying outside the standard 100 mm chamber length and CTDI phantoms being of insufficient length.In an attempt to better quantify dose from cone beam scanning, alternative methodologies have been developed which attempt to counter the limitations of CTDI methodologies. In this comparison study we utilised the CBCT methodologies outlined in (i) IAEA Report 5, (ii) EFOMP’s protocol on QC in CBCT and (iii) conventional CTDI measurement and tested them on various CBCT systems used in Radiology. These methods were chosen as they use equipment that is typically available to a diagnostic imaging physicist.We determine that the EFOMP protocol and the conventional CTDI method produce the best estimate of the radiation output for quality control purposes. Our conclusion is that the EFOMP protocol is the fastest and easiest method to measure a CBCT metric but it is not always accessible. For the systems in our hospital we will adopt the EFOMP protocol for open systems (C-arms) and perform CTDI_Vol measurements using conventional techniques on enclosed systems (O-arm and extremity CT).     

Overview of a quality assurance/quality control compliance program consistent with FDA regulations and policies for somatic cell and gene therapies: a four year experience

Somatic cell and gene therapy involve the application of biological technologies to an individual patient through the use of living cells which provide a therapeutic benefit (Aliski, 1991). Various forms of cellular and gene therapies are being developed and evaluated in an increasing number of clinical trials for congential and acquired disorders. The potential and progress of these therapeutic applications have resulted in an increasing effort by the Food and Drug Administration (FDA) to develop the regulatory framework under which these therapeutic approaches would insure safety and efficacy, the primary mandate of the FDA.Over five years ago Cellcor began to define the parameters, specifications, and conditions relevant to a Quality Assurance/Quality Control (QA/QC) program that has evolved to insure safety and maximize the efficacy of applications of the company'sex vivo technology, autolymphocyte therapy. Autolymphocyte therapy is an outpatient form of somatic cell immunotherapy based upon the infusion of T cells that have been activatedex vivo using a combination of previously generated autologous cytokines and an anti-CD3 monoclonal antibody.We have been able to demonstrate the feasibility for the safe, controlled, and consistent preparation and delivery of a cellular therapy by application of relevant GMP regulations. This presentation reviews aspects of this program and chronicles our experience which at present amounts to over 4400 infusions for over 700 patients. This program provides a high degree of assurance that a cellular therapy program can be carried out in a multisite mode involving hundreds of patients through the strict adherence to cGMP as set forth in existing regulations. It would be prudent that developers of cellular andex vivo gene therapies establish a similar cell processing and QA/QC infrastructure at an early developmental stage to optimize safety and reproducibility and facilitate regulatory review.     

Quality attributes of recombinant therapeutic proteins: an assessment of impact on safety and efficacy as part of a quality by design development approach

Quality by Design (QbD) is a new approach to the development of recombinant therapeutic protein products that promotes a better understanding of the product and its manufacturing process. The first step in the QbD approach consists in identifying the critical quality attributes (CQA), i.e., those quality attributes of the product that have an impact on its clinical efficacy or safety. CQAs are identified through a science-based risk assessment taking into consideration a combination of clinical and nonclinical data obtained with the molecule or other similar molecules or platform products, as well as the published literature. The purpose of this article is to perform a comprehensive review of the published literature, supporting an assessment of the impact on safety and efficacy of the quality attributes commonly encountered in recombinant therapeutic proteins, more specifically those produced in mammalian cell expression systems. Quality attributes generally observed in biopharmaceutical proteins including product-related impurities and substances, process-related impurities, product attributes, and contaminants are evaluated one by one for their impact on biological activity, pharmacokinetics and pharmacodynamics, immunogenicity, and overall safety/toxicity.