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A new method for determining the optimal CT threshold for extracting the upper airway.

ABSTRACT: OBJECTIVES: The purpose of this study was to evaluate the optimal upper threshold levels of a number of individuals and determine the most suitable upper threshold. METHODS: A phantom model and ten patients were used in this study. The phantom was made of acrylic resin and urethane resin and had nine pillar-shaped air spaces. The subjects were ten female patients with jaw deformities who were not affected by respiratory disease. The optimal threshold levels were determined using the "calculation of CT value disparities" (CCTD) technique, which we devised. In other words, the mean CT values along two lines (air space and soft tissue) were calculated and the optimal threshold level was determined as the level that produced the maximum difference between the CT values measured inside and outside of the air-space border. RESULTS: The optimal upper threshold levels of the nine phantom holes calculated using the CCTD technique in the front-on standing position and side-on standing position were -434 HU and -456 HU, respectively. The optimal upper threshold level of the ten patients calculated using the CCTD technique was -472 HU. The true threshold level of each patient was defined as the optimal threshold level calculated using the CCTD technique. The mean threshold level was defined as -472 HU. The absolute differences between the volume measurements obtained with these two measures were considered. Therefore, the no error values were -460 HU and -470 HU. CONCLUSIONS: We consider that the most suitable upper threshold level for extracting the airway is from -460 HU to -470 HU.

SUBMITTER: Nakano H

PROVIDER: S-EPMC3667543 | biostudies-other | 2013

REPOSITORIES: biostudies-other

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Project description:BackgroundFor neonates and children requiring decompression of tension pneumothorax, specific recommendations for the choice of needle type and size are missing. The aim of this retrospective study was to determine optimal length and diameter of needles for decompression of tension pneumothorax in paediatric patients.MethodsUtilizing computed tomography, we determined optimal length and diameter of needles to enable successful decompression and at the same time minimize risk of injury to intrathoracic structures and the intercostal vessels and nerve. Preexisting computed tomography scans of the chest were reviewed in children aged 0, 5 and 10?years. Chest wall thickness and width of the intercostal space were measured at the 4th intercostal space at the anterior axillary line (AAL) on both sides of the thorax. In each age group, three needles different in bore and length were evaluated regarding sufficient length for decompression and risk of injury to intrathoracic organs and the intercostal vessels and nerve.Results197 CT-scans were reviewed, of which 58 were excluded, resulting in a study population of 139 children and 278 measurements. Width of the intercostal space was small at 4th ICS AAL (0?years: 0.44?±?0.13?cm; 5?years: 0.78?±?0.22?cm; 10?years: 1.12?±?0.36?cm). The ratio of decompression failure to risk of injury at 4th ICS AAL was most favourable for a 22G/2.5?cm catheter in infants (Decompression failure: right: 2%, left: 4%, Risk of injury: right: 14%, left: 24%), a 22G/2.5?cm or a 20G/3.2?cm catheter in 5-year-old children (20G/3.2?cm: Decompression failure: right: 2.1%, left: 0%, Risk of injury: right: 2.1%, left: 17%) and a 18G/4.5?cm needle in 10-year-old children (Decompression failure: right: 9.5%, left: 9.5%, Risk of injury: right: 7.1%, left: 11.9%).ConclusionsIn children aged 0, 5 and 10?years presenting with a tension pneumothorax, we recommend 22G/2.5?cm, 20G/3.2?cm and 18G/4.5?cm needles, respectively, for acute decompression.

Project description:BackgroundDTI is sensitive to white matter (WM) microstructural damage and has been suggested as a surrogate marker for phase 2 clinical trials in cerebral small vessel disease (SVD). The study's objective is to establish the best way to analyse the diffusion-weighted imaging data in SVD for this purpose. The ideal method would be sensitive to change and predict dementia conversion, but also straightforward to implement and ideally automated. As part of the OPTIMAL collaboration, we evaluated five different DTI analysis strategies across six different cohorts with differing SVD severity.MethodsThose 5 strategies were: (1) conventional mean diffusivity WM histogram measure (MD median), (2) a principal component-derived measure based on conventional WM histogram measures (PC1), (3) peak width skeletonized mean diffusivity (PSMD), (4) diffusion tensor image segmentation θ (DSEG θ) and (5) a WM measure of global network efficiency (Geff). The association between each measure and cognitive function was tested using a linear regression model adjusted by clinical markers. Changes in the imaging measures over time were determined. In three cohort studies, repeated imaging data together with data on incident dementia were available. The association between the baseline measure, change measure and incident dementia conversion was examined using Cox proportional-hazard regression or logistic regression models. Sample size estimates for a hypothetical clinical trial were furthermore computed for each DTI analysis strategy.ResultsThere was a consistent cross-sectional association between the imaging measures and impaired cognitive function across all cohorts. All baseline measures predicted dementia conversion in severe SVD. In mild SVD, PC1, PSMD and Geff predicted dementia conversion. In MCI, all markers except Geff predicted dementia conversion. Baseline DTI was significantly different in patients converting to vascular dementia than to Alzheimer' s disease. Significant change in all measures was associated with dementia conversion in severe but not in mild SVD. The automatic and semi-automatic measures PSMD and DSEG θ required the lowest minimum sample sizes for a hypothetical clinical trial in single-centre sporadic SVD cohorts.ConclusionDTI parameters obtained from all analysis methods predicted dementia, and there was no clear winner amongst the different analysis strategies. The fully automated analysis provided by PSMD offers advantages particularly for large datasets.

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A new method for determining the optimal CT threshold for extracting the upper airway.

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