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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.

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.

We have previously reported the use of simultaneous emission and transmission (SET) scanning in whole body PET and the technique may also be applicable in kinetic studies. However, there are potential sources of bias, particularly at low emission count rates, which may affect the accuracy of parameter estimates. We investigated these potential sources of bias and their effect on parameter estimation in oncological PET studies. The sources of bias considered include: (i) variation in transmission spillover (into the emission window) throughout the field of view, (ii) increased scatter arising from the rod sources, and (iii) inaccurate dead time correction. Net bias was calculated as a function of emission count rate and used to predict distortion in FDG tissue curves simulating normal and metastatic liver. The distortion was characterised by spectral analysis and the effect on parameter estimates was assessed by compartmental modelling. Variation in spillover was found to be a negligible source of bias in SET measurements. Scatter and dead time errors work in opposing directions and approximately cancel during the early part of the study when count rate is maximal. The resulting distortion causes apparently decreased tracer clearance, particularly in tumours, which mainly affects estimates of k/sub 4/ and volume of distribution. Estimates of K/sub 1/-k/sub 3/ were relatively unaffected, while bias in glucose metabolic rate was +8% and +2% for normal liver and tumour respectively.

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). The authors 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 ( Delta SNR=6.3+or-3.9, p

A quantitative SPECT (single photon emission computed tomography) regime based on simultaneous acquisition of emission and transmission data has been developed and validated. Transmission data are acquired using a scanning collimated line source and incorporated into a modified convolution-subtraction scatter correction method which produces transmission-dependent scatter fractions. This method tailors scatter fraction to attenuation path length, falling to zero outside the body. Following scatter correction, emission data are reconstructed using filtered backprojection, and attenuation correction is performed in a two-step procedure using reconstructed narrow-beam attenuation data from the line source measurements. The quantitative accuracy of this regime has been assessed in heart and lung phantom distributions, as well as in a human-lung perfusion scan with /sup 99m/Tc-macroaggregates. The use of simultaneously acquired transmission data for scatter and attenuation correction yields accurate results and promises great potential for practical quantitative SPECT. >

PURPOSE We evaluated the impact of simultaneous emission and transmission (SET) measurements of quantification and noise in neurological PET studies. METHOD Bias in SET was measured as a function of emission count rate and used to predict distortion in simulated FDG tissue curves and its effect on model parameter estimates. Studies were performed on a brain phantom and a patient to verify predicted bias and examine the effect of SET on noise. RESULTS In static imaging, SET underestimated tracer concentration by approximately 2%. In kinetic studies, tracer concentration was overestimated initially and underestimated during the mid to late part of the study, but bias in measurement of glucose metabolic rate was < 5% by simulation and < 10% in the patient study. SET imaging takes 10% longer than the emission part of a conventional scan to achieve comparable statistics. CONCLUSION Accurate neurological PET studies can be performed with SET. The relatively small bias can be predicted and potentially corrected.

This chapter investigates the impact of simultaneous emission and transmission (SET) on the accuracy of quantification in tracer kinetic studies of the brain. Accurate quantification of brain function with positron emission tomography (PET) requires a separate transmission scan to correct for photon attenuation, which extends the duration of the study. Alternatively, emission and transmission measurements can be performed simultaneously, at the potential cost of bias due to increased scatter and dead time. Scatter and dead time correction errors in SET are measured as functions of the emission count rate. The effective scatter fraction for SET was –1 (11.8 vs. 10.6%), but increased with decreasing emission count rate. In contrast, dead time correction error was –5% at 30 kcounts . sec –1 and became worse with increasing count rate. The net effect was to overestimate activity at low count rates and underestimate activity at high count rates. As a result, estimates of glucose metabolic rate using SET were lower than those from conventional acquisition, and the bias was greater in gray matter than in white matter. However, in both cases, the bias was small relative to measurement noise. It has been concluded that quantitative cerebral PET studies can be performed with acceptable bias and reduced study duration using SET.

A method of compensating for head motion in neurological emission tomography based on 3-D reconstruction and dynamic monitoring of head position and orientation has been evaluated. The net movements over a 60 minute period of 26 patients undergoing clinical PET examinations with a headholder were measured. SPECT studies containing these movements as single- or multi-step motions were simulated. All simulated movements involved some motion in all six degrees of freedom. Uncorrected and corrected reconstructions were compared with the motion-free reconstruction. The sum of the squared differences between the motion free and uncorrected reconstruction improved by 30% or more after correction in 11 of the 26 simulations. We find that motion correction can improve the quantitative accuracy of SPECT studies performed with conventional head holders.

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, p0.05) resulted in an increase in whole right lung MCC (%C60, 31 +/- 4 versus 18 +/- 2%; p0.05). 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)