Organ doses and effective doses in pediatric radiography: patient-dose survey in Finland.

BACKGROUND: Use of the effective dose in diagnostic radiology permits the radiation exposure of diverse diagnostic procedures to be quantified. Fundamental knowledge of patient doses enhances the implementation of the "as low as reasonably achievable" (ALARA) principle. PURPOSE: To provide comparative information on pediatric examination protocols and patient doses in skull, sinus, chest, abdominal, and pelvic radiography examinations. MATERIAL AND METHODS: 24 Finnish hospitals were asked to register pediatric examination data, including patient information and examination parameters and specifications. The total number of examinations in the study was 1916 (1426 chest, 228 sinus, 96 abdominal, 94 skull, and 72 pelvic examinations). Entrance surface dose (ESD) and dose-area products (DAP) were calculated retrospectively or DAP meters were used. Organ doses and effective doses were determined using a Monte Carlo program (PCXMC). RESULTS: There was considerable variation in examination protocols between different hospitals, indicating large variations in patient doses. Mean effective doses of different age groups ranged from 5 microSv to 14 microSv in skull and sinus examinations, from 25 microSv to 483 microSv in abdominal examinations, and from 6 microSv to 48 microSv in chest examinations. CONCLUSION: In chest and sinus examinations, the amount of data was extensive, allowing national pediatric diagnostic reference levels to be defined. Parameter selection in pediatric examination protocols should be harmonized in order to reduce patient doses and improve optimization.

Bayesian inference of physiologically meaningful parameters from body sway measurements.

The control of the human body sway by the central nervous system, muscles, and conscious brain is of interest since body sway carries information about the physiological status of a person. Several models have been proposed to describe body sway in an upright standing position, however, due to the statistical intractability of the more realistic models, no formal parameter inference has previously been conducted and the expressive power of such models for real human subjects remains unknown. Using the latest advances in Bayesian statistical inference for intractable models, we fitted a nonlinear control model to posturographic measurements, and we showed that it can accurately predict the sway characteristics of both simulated and real subjects. Our method provides a full statistical characterization of the uncertainty related to all model parameters as quantified by posterior probability density functions, which is useful for comparisons across subjects and test settings. The ability to infer intractable control models from sensor data opens new possibilities for monitoring and predicting body status in health applications.

Baseline adjustment increases accurate interpretation of posturographic sway scores.

Postural steadiness may be quantified using posturographic sway measures. These measures are commonly used to differentiate between a person's baseline balance and balance related to some physiological condition. However, the difference in sway scores between the two conditions may be difficult to detect due to large inter-subject variation. We compared detection accuracy provided by three models that linearly regress a sway measure (mean distance, velocity, or frequency) on the effect of eye closure on balance (eyes open (EO) vs. eyes closed (EC)). In Model 1 the dependent variable is a single sway score (EO or EC), whereas in Models 2 and 3 it is a change score (EO-EO or EC-EO). The independent variable is always the group (group=0: EO or group=1: EC). Model 3 also accounts for the regression to the mean effect (RTM), by considering the baseline value (EO) as a covariate. When differentiating between EO and EC conditions, 94% accuracy can be achieved when using mean velocity as sway measure and either Model 2 or 3. Thus by adjusting for baseline score one increases the accurate interpretation of posturographic sway scores.

Evaluation of postural steadiness before and after sedation: comparison of four nonlinear and three conventional measures.

Sedative drugs decrease postural steadiness and increase the risk of injury from falls and accidents. The recovery rate is individual, making it hard to predict the patient's steadiness and hence safe discharge time. 103 outpatients sedated with midazolam and fentanyl were measured posturographically, before (PRE) and after (POST) endoscopy. The ability of conventional and nonlinear sway measures to separate the PRE and POST conditions were compared, and the area under the receiver operating characteristics curve (AUC) was used to quantify the significance of the separation. A nonlinear measure, fuzzy sample entropy, scored the largest AUC (AUCFSE = 0.83, p < 0.0001). While the AUCFSE was not significantly larger than the AUCs of conventional sway measures which offer easy quantification of postural steadiness, nonlinear measures provide more insight into the structure of postural control, which may help understand the effect of sedation on postural steadiness. This study is a step toward developing a tester that indicates a safe discharge time.

Quantifying time awake posturographically.

Although sleepiness is a major risk factor in traffic and occupational accidents, convenient, quantitative, and commercial sleepiness testing is lacking. The issue is relevant to policymakers concerned with legislation for, and surveillance of, traffic- and occupational safety. This work suggested and examined posturographic sleepiness testing for instrumentation purposes. In 63 subjects--for whom we tested balance with a force platform during sustained waking for maximum 36 h--sustained waking impaired the balance. The sustained waking explained 60% of the diurnal balance variations, whereas the time of day explained 40% of the balance variations. The first finding -that balance depends on the subject's time awake (TA)- allowed to posturographically estimate the subjects' TA with 86% accuracy and 97% precision. Results also show that balance scores tested at 13:30 hours serve as a threshold to detect excessive sleepiness. This work provides guidelines for a posturographic sleepiness tester.

Model-based posturographic sleepiness monitor tested on 20 subjects.

A previous posturographic force platform study verified that human balance deteriorates as a function of time awake (TA). It found that TA can be estimated with +/-2.5 h accuracy using 30 s trial length. For a fast, reliable and convenient sleepiness monitor even better TA estimation accuracy and shorter trial length is needed. We continued this quest by modeling the quiet stance test situation with a single-link inverted pendulum model (SLIPM). The center-of-mass (COM) trace in the AP (anterior-posterior) direction was calculated from the measured center-of-pressure (COP) trace. The sway angle theta, ankle torque tau and the horizontal force F acting on the COM were calculated from the SLIP equations--each analyzed with 13 different sway measures, i.e. variables that correlate with TA. The effect of circadian rhythm was separated from the sway measures. Twenty subjects' sway measures were analyzed. The SLIPM-based posturographic averaged TA estimation accuracy improved to +/-2.3 h. The trial length could be shortened to 21 s.