How Accurate Are We in Estimating True Stone Volume? A Comparison of Water Displacement, Ellipsoid Formula, and a CT-Based Software Tool
To compare the accuracy and reliability of stone volume estimated by ellipsoid formula (EFv) and CT-based algorithm (CTv) to true volume (TV) by water displacement in an in vitro model. Ninety stone phantoms were created using clay (0.5-40 cm , 814 HU ±91) and scanned with CT. For each stone, TV was...
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Veröffentlicht in: | Journal of endourology 2018-06, Vol.32 (6), p.572-576 |
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Sprache: | eng |
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Zusammenfassung: | To compare the accuracy and reliability of stone volume estimated by ellipsoid formula (EFv) and CT-based algorithm (CTv) to true volume (TV) by water displacement in an in vitro model.
Ninety stone phantoms were created using clay (0.5-40 cm
, 814 HU ±91) and scanned with CT. For each stone, TV was measured by water displacement, CTv was calculated by the region-growing algorithm in the CT-based software AGFA IMPAX Volume Viewer, and EFv was calculated by the standard formula π × L × W × H × 0.167. All measurements were repeated thrice, and concordance correlation coefficient (CCC) was calculated for the whole group, as well as subgroups based on volume (6 cm
).
Mean TV, CTv, and EFv were 6.42 cm
± 6.57 (range: 0.5-39.37 cm
), 6.24 cm
± 6.15 (0.48-36.1 cm
), and 8.98 cm
± 9.96 (0.49-47.05 cm
), respectively. When comparing TV to CTv, CCC was 0.99 (95% confidence interval [CI]: 0.99-0.995), indicating excellent agreement, although TV was slightly underestimated at larger volumes. When comparing TV to EFv, CCC was 0.82 (95% CI: 0.78-0.86), indicating poor agreement. EFv tended to overestimate the TV, especially as stone volume increased beyond 1.5 cm
, and there was a significant spread between trials.
An automated CT-based algorithm more accurately and reliably estimates stone volume than does the ellipsoid formula. While further research is necessary to validate stone volume as a surrogate for stone burden, CT-based algorithmic volume measurement of urinary stones is a promising technology. |
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ISSN: | 0892-7790 1557-900X |
DOI: | 10.1089/end.2017.0937 |