Measurement of Kidney Volume with Multi-Detector Computed Tomography Scanning in Young Korean.
10.3349/ymj.2009.50.2.262
- Author:
Ho Sik SHIN
1
;
Byung Ha CHUNG
;
Sang Eun LEE
;
Woo Jin KIM
;
Hong Il HA
;
Chul Woo YANG
Author Information
1. Department of Internal Medicine, The Armed Forces Yang-Ju Hospital, Yangju, Korea. chungbh@catholic.ac.kr
- Publication Type:Original Article
- Keywords:
Kidney;
volume measurement;
computed tomography
- MeSH:
Adult;
Asian Continental Ancestry Group;
Glomerular Filtration Rate;
Humans;
Kidney/*radiography;
Male;
*Organ Size;
Young Adult
- From:Yonsei Medical Journal
2009;50(2):262-265
- CountryRepublic of Korea
- Language:English
-
Abstract:
PURPOSE: Kidney volume is regarded as the most precise indicator of kidney size. However, it is not widely used clinically, because its measurement is difficult due to the complex kidney shape. We attempted to evaluate the normal kidney volume in young Korean men by using multi-detector computed tomography (MDCT). MATERIALS AND METHODS: We retrospectively reviewed MDCT data of young Korean men (113 patients). After data processing, we measured the volume and length of the kidneys. Body parameters (height, body weight, body-surface area, and total body water) and laboratory data were collected. Glomerular filtration rate (GFR) was calculated using Cockcroft-Gault (CG) equation. RESULTS: The mean kidney volume was 205.29 +/- 36.81 cm3; and mean kidney length was 10.80 +/- 0.69 cm. The former correlated significantly with height, body weight, body-surface area, and total body water (p < 0.05, correlation coefficient : gamma = 0.328, 0.649, 0.640, and 0.638, respectively). The latter also correlated significantly with all body indexes, however the correlation was weaker, except with height (p < 0.05, correlation coefficient : gamma = 0.457, 0.473, 0.505, and 0.503, respectively). Only kidney volume significantly predicted estimated GFR (adjusted R2 = 0.431, F = 85.90 and p < 0.05). CONCLUSION: The kidney volume measured with MDCT is correlated well with body parameters, and is useful to predict renal function.
