Optimization of Radiation Dose and Image Quality in Musculoskeletal CT: Emphasis on Iterative Reconstruction Techniques (Part 1).

Computed tomography (CT) is a modality of choice for the study of the musculoskeletal system for various indications including the study of bone, calcifications, internal derangements of joints (with CT arthrography), as well as periprosthetic complications. However, CT remains intrinsically limited by the fact that it exposes patients to ionizing radiation. Scanning protocols need to be optimized to achieve diagnostic image quality at the lowest radiation dose possible. In this optimization process, the radiologist needs to be familiar with the parameters used to quantify radiation dose and image quality. CT imaging of the musculoskeletal system has certain specificities including the focus on high-contrast objects (i.e., in CT of bone or CT arthrography). These characteristics need to be taken into account when defining a strategy to optimize dose and when choosing the best combination of scanning parameters. In the first part of this review, we present the parameters used for the evaluation and quantification of radiation dose and image quality. In the second part, we discuss different strategies to optimize radiation dose and image quality at CT, with a focus on the musculoskeletal system and the use of novel iterative reconstruction techniques.

Optimization of Radiation Dose and Image Quality in Musculoskeletal CT: Emphasis on Iterative Reconstruction Techniques (Part 2).

Computed tomography (CT) is a modality of choice for the study of the musculoskeletal system for various indications including the study of bone, calcifications, internal derangements of joints (with CT arthrography), as well as periprosthetic complications. However, CT remains intrinsically limited by the fact that it exposes patients to ionizing radiation. Scanning protocols need to be optimized to achieve diagnostic image quality at the lowest radiation dose possible. In this optimization process, the radiologist needs to be familiar with the parameters used to quantify radiation dose and image quality. CT imaging of the musculoskeletal system has certain specificities including the focus on high-contrast objects (i.e., in CT of bone or CT arthrography). These characteristics need to be taken into account when defining a strategy to optimize dose and when choosing the best combination of scanning parameters. In the first part of this review, we present the parameters used for the evaluation and quantification of radiation dose and image quality. In the second part, we discuss different strategies to optimize radiation dose and image quality of CT, with a focus on the musculoskeletal system and the use of novel iterative reconstruction techniques.

Streamlining the medication process improves safety in the intensive care unit.

BACKGROUND: Multiple interventions were made to optimize the medication process in our intensive care unit (ICU). 1 Transcriptions from the medical order form to the administration plan were eliminated by merging both into a single document; 2 the new form was built in a logical sequence and was highly structured to promote completeness and standardization of information; 3 frequently used drug names, approved units, and fixed routes were pre-printed; 4 physicians and nurses were trained with regard to the correct use of the new form. This study was aimed at evaluating the impact of these interventions on clinically significant types of medication errors. METHODS: Eight types of medication errors were measured by a prospective chart review before and after the interventions in the ICU of a public tertiary care hospital. We used an interrupted time-series design to control the secular trends. RESULTS: Over 85 days, 9298 lines of drug prescription and/or administration to 294 patients, corresponding to 754 patient-days were collected and analysed for the three series before and three series following the intervention. Global error rate decreased from 4.95 to 2.14% (-56.8%, P < 0.001). CONCLUSIONS: The safety of the medication process in our ICU was improved by simple and inexpensive interventions. In addition to the optimization of the prescription writing process, the documentation of intravenous preparation, and the scheduling of administration, the elimination of the transcription in combination with the training of users contributed to reducing errors and carried an interesting potential to increase safety.

Optimization of the piggyBac Transposon Using mRNA and Insulators: Toward a More Reliable Gene Delivery System.

Integrating and expressing stably a transgene into the cellular genome remain major challenges for gene-based therapies and for bioproduction purposes. While transposon vectors mediate efficient transgene integration, expression may be limited by epigenetic silencing, and persistent transposase expression may mediate multiple transposition cycles. Here, we evaluated the delivery of the piggyBac transposase messenger RNA combined with genetically insulated transposons to isolate the transgene from neighboring regulatory elements and stabilize expression. A comparison of piggyBac transposase expression from messenger RNA and DNA vectors was carried out in terms of expression levels, transposition efficiency, transgene expression and genotoxic effects, in order to calibrate and secure the transposition-based delivery system. Messenger RNA reduced the persistence of the transposase to a narrow window, thus decreasing side effects such as superfluous genomic DNA cleavage. Both the CTF/NF1 and the D4Z4 insulators were found to mediate more efficient expression from a few transposition events. We conclude that the use of engineered piggyBac transposase mRNA and insulated transposons offer promising ways of improving the quality of the integration process and sustaining the expression of transposon vectors.

A hierarchical approach to model parameter optimization for developmental systems.

In the context of Systems Biology, computer simulations of gene regulatory networks provide a powerful tool to validate hypotheses and to explore possible system behaviors. Nevertheless, modeling a system poses some challenges of its own: especially the step of model calibration is often difficult due to insufficient data. For example when considering developmental systems, mostly qualitative data describing the developmental trajectory is available while common calibration techniques rely on high-resolution quantitative data. Focusing on the calibration of differential equation models for developmental systems, this study investigates different approaches to utilize the available data to overcome these difficulties. More specifically, the fact that developmental processes are hierarchically organized is exploited to increase convergence rates of the calibration process as well as to save computation time. Using a gene regulatory network model for stem cell homeostasis in Arabidopsis thaliana the performance of the different investigated approaches is evaluated, documenting considerable gains provided by the proposed hierarchical approach.