The aim of this study was to examine baseline mucociliary clearance (MCC) in patients with cystic fibrosis (n = 30; mean +/- SEM age, 23 +/- 1 yr; FEV1, 68 +/- 5% pred; range, 14 to 126%) and a group of normal subjects (n = 12; mean age, 27 +/- 1 yr) after an aerosol deposition of 99mTc-sulphur colloid (mass median diameter, 4.8 microns; geometric standard deviation, 1.6). Dynamic geometric mean images were formed from gamma camera data, and the percent clearance of activity after 60 min (%C60) was calculated for the whole right lung. Initial deposition of the aerosol was determined in terms of the penetration index, the ratio of peripheral to central activity. For normal subjects, an increase in mean inspiratory flow rate (MIFR) (49 +/- 5 versus 21 +/- 3 L/min, p < 0.05) resulted in an increase in whole right lung MCC (%C60, 31 +/- 4 versus 18 +/- 2%; p < 0.05). When aerosol delivery was controlled (MIFR, 34 +/- 5 versus 36 +/- 5 L/min), there was excellent reproducibility between studies (whole lung %C60, 34 +/- 8 versus 31 +/- 7; NS). The measurement of MCC was highly reproducible in six patients studied on four occasions with a mean coefficient of variation of 3.3 +/- 1%. A breathing pattern to accentuate central deposition was utilized in the patient studies (MIFR, 49 +/- 4 L/min).(ABSTRACT TRUNCATED AT 250 WORDS)

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The conventional measurement of the regional cerebral metabolic rate of glucose (rCMRGlc) with fluorodeoxyglucose (FDG) and positron emission tomography (PET) requires arterial or arterialised-venous (a-v) blood sampling at frequent intervals to obtain the plasma input function (IF). We evaluated the accuracy of rCMR-Glc measurements using population-based IFs that were calibrated with two a-v blood samples. Population-based IFs were derived from: (1) the average of a-v IFs from 26 patients (Standard IF) and (2) a published model of FDG plasma concentration (Feng IF). Values for rCMRGlc calculated from the population-based IFs were compared with values obtained with IFs derived from frequent a-v blood sampling in 20 non-diabetic and six diabetic patients. Values for rCMRGlc calculated with the different IFs were highly correlated for both patient groups (r > or = 0.992) and root mean square residuals about the regression line were less than 0.24 mg/min/100 g. The Feng IF tended to underestimate high rCMRGlc. Both population-based IFs simplify the measurement of rCMRGlc with minimal loss in accuracy and require only two a-v blood samples for calibration. The reduced blood sampling requirements markedly reduce radiation exposure to the blood sampler.

Total-body positron emission tomography (PET) is a useful diagnostic tool for evaluating malignant disease. However, tumour detection is limited by image artefacts due to the lack of attenuation correction and noise. Attenuation correction may be possible using transmission data acquired after or simultaneously with emission data. Despite the elimination of attenuation artefacts, however, tumour detection is still hampered by noise, which is amplified during image reconstruction by filtered backprojection (FBP). We have investigated, as an alternative to FBP, an accelerated expectation maximization (EM) algorithm for its potential to improve tumour detectability in total-body PET. Signal to noise ratio (SNR), calculated for a tumour with respect to the surrounding background, is used as a figure of merit. A software tumour phantom, with conditions typical of those encountered in a total-body PET study using simultaneous acquisition, is used to optimize and compare various reconstruction approaches. Accelerated EM reconstruction followed by two-dimensional filtering is shown to yield significantly higher SNR than FBP for a range of tumour sizes, concentrations and counting statistics (deltaSNR = 6.3 +/- 3.9, p < 0.001). The methods developed are illustrated by examples derived from physical phantom and patient data.

Background Despite growing evidence that deprescribing can improve clinical outcomes, quality of life and reduce the likelihood of adverse drug events, the practice is not widespread, particularly in hospital settings. Clinical risk assessment tools, like the Drug Burden Index (DBI), can help prioritise patients for medication review and prioritise medications to deprescribe, but are not integrated within routine care. The aim of this study was to conduct formative usability testing of a computerised decision support (CDS) tool, based on DBI, to identify modifications required to the tool prior to trialling in practice. Methods Our CDS tool comprised a DBI MPage in the electronic medical record (clinical workspace) that facilitated review of a patient’s DBI and medication list, access to deprescribing resources, and the ability to deprescribe. Two rounds of scenario-based formative usability testing with think-aloud protocol were used. Seventeen end-users participated in the testing, including junior and senior doctors, and pharmacists. Results Participants expressed positive views about the DBI CDS tool but testing revealed a number of clear areas for improvement. These primarily related to terminology used (i.e. what is a DBI and how is it calculated?), and consistency of functionality and display. A key finding was that users wanted the CDS tool to look and function in a similar way to other decision support tools in the electronic medical record. Modifications were made to the CDS tool in response to user feedback. Conclusion Usability testing proved extremely useful for identifying components of our CDS tool that were confusing, difficult to locate or to understand. We recommend usability testing be adopted prior to implementation of any digital health intervention. We hope our revised CDS tool equips clinicians with the knowledge and confidence to consider discontinuation of inappropriate medications in routine care of hospitalised patients. In the next phase of our project, we plan to pilot test the tool in practice to evaluate its uptake and effectiveness in supporting deprescribing in routine hospital care.