Till Örebro universitet

The workflow in radiology departments has changed dramatically with the transition to digital PACS, especially with the shift from tile mode to stack mode display of volumetric images. With the increasing number of images in routinely captured datasets, the standard user interface devices (UIDs) become inadequate. One basic approach to improve the navigation of the stack mode datasets is to take advantage of alternative UIDs developed for other domains, such as the computer game industry. We evaluated three UIDs both in clinical practice and in a task-based experiment. After using the devices in the daily image interpretation work, the readers reported that both of the tested alternative UIDs were better in terms of ergonomics compared to the standard mouse and that both alternatives were more efficient when reviewing large CT datasets. In the task-based experiment, one of the tested devices was faster than the standard mouse, while the other alternative was not significantly faster. One of the tested alternative devices showed a larger number of traversed images during the task. The results indicate that alternative user interface devices can improve the navigation of stack mode datasets and that radiologists should consider the potential benefits of alternatives to the standard mouse.

Objectives The objectives of this study were to quantify the impact of image post-processing parameters on the apparent renal stone size, and to quantify the intra- and inter-reader variability in renal stone size estimation. Methods Fifty CT datasets including a renal or ureteral stone were included retrospectively during a prospective inclusion period. Each of the CT datasets was post-processed in different ways regarding slice thickness, slice increment and window setting. In the first part of the study a single reader repeated size estimations for the renal stones using different post-processing parameters. In the intra-reader variability experiment one reader reported size estimations for the same images with a one-week interval. The inter-reader variability data were obtained from 11 readers reporting size estimations for the same renal stones. Results The apparent stone size differed according to image post-processing parameters with the largest mean differences seen with regard to the window settings experiment (1.5 mm, p < 0.001) and slice thickness (0.8 mm, p < 0.001). Changes in parameters introduced a bias and a pseudo-random variability. The inter-reader variability was considerably larger than the intra-reader variability. Conclusion Our results indicate a need for the standardisation of making measurements on CT images.

The size estimation in CT images of an obstructing ureteral calculus is important for the clinical management of a patient presenting with renal colic. The objective of the present study was to develop a reader independent urinary calculus segmentation algorithm using well-known digital image processing steps and to validate the method against size estimations by several readers. Fifty clinical CT examinations demonstrating urinary calculi were included. Each calculus was measured independently by 11 readers. The mean value of their size estimations was used as validation data for each calculus. The segmentation algorithm consisted of interpolated zoom, binary thresholding and morphological operations. Ten examinations were used for algorithm optimisation and 40 for validation. Based on the optimisation results three segmentation method candidates were identified. Between the primary segmentation algorithm using cubic spline interpolation and the mean estimation by 11 readers, the bias was 0.0 mm, the standard deviation of the difference 0.26 mm and the Bland-Altman limits of agreement 0.0 +/- 0.5 mm. The validation showed good agreement between the suggested algorithm and the mean estimation by a large number of readers. The limit of agreement was narrower than the inter-reader limit of agreement previously reported for the same data. The size of kidney stones is usually estimated manually by the radiologist. An algorithm for computer-aided size estimation is introduced. The variability between readers can be reduced. A reduced variability can give better information for treatment decisions.

The standard imaging procedure for a patient presenting with renal colic is unenhanced CT. The CT measured size has a close correlation to the estimated prognosis for spontaneous passage of a ureteral calculus. Size estimations of urinary calculi in CT images are still based on 2d-reformats. In the present study we developed and validated a calculus oriented 3dmethod for measurements of length and width of urinary calculi and compared those with corresponding 2d measurements in axial and coronal reformats.

Methods: Fifty unenhanced CT examinations demonstrating urinary calculi were included. A 3d-symmetric segmentation algorithm was validated against reader size estimations. The calculus-oriented size from the segmentation was then compared to the size in axial and coronal reformats.

Results: The validation showed 0.1±0.7 mm agreement against reference measure. There was a 0.4 mm median bias for 3d-estimated calculus length compared to 2d (p<0.001), but no significant bias for 3d-width compared to 2d.

Conclusion: The size of the urinary calculus becomes underestimated if its orientation is not aligned to the axial or coronal image plane. Future studies aiming to correlate calculus size with patient outcome should use a calculus oriented size estimation.