BACKGROUND/AIMS: Total renal volume (TRV) is an important index to evaluate the progression of autosomal-dominant polycystic kidney disease (ADPKD). TRV has been assessed by manually tracing renal contours from CT or MR scans, often employing contrast medium (CM). We developed a fast and nearly automated technique based on the analysis of MR images acquired without CM injection for TRV quantification. METHODS: 30 ADPKD patients underwent MRI. After the selection of one point inside each kidney for the entire volume, the automatic extraction of kidney contours was performed on each acquired slice; the segmentation procedure was based on region growing and on the application of morphological operators and curvature-based motion. The area inside each contour was calculated and TRV was derived. Volume measurements were validated by comparison with measurements obtained by stereology. RESULTS: TRV estimated in patients was 768 ± 545 ml (range 161-3,111 ml). The automatic measurements were in excellent correlation with the manual ones (r = 0.99, y = x - 0.7), with a small bias and narrow limits of agreement in both absolute (-5 ± 37 ml) and percentage (-0.6 ± 9.6%) terms. CONCLUSION: This preliminary study showed the feasibility of a fast and nearly automated method for determining TRV; importantly it does not require the use of potentially nephrotoxic CM.
BACKGROUND/AIMS: Total renal volume (TRV) is an important index to evaluate the progression of autosomal-dominant polycystic kidney disease (ADPKD). TRV has been assessed by manually tracing renal contours from CT or MR scans, often employing contrast medium (CM). We developed a fast and nearly automated technique based on the analysis of MR images acquired without CM injection for TRV quantification. METHODS: 30 ADPKDpatients underwent MRI. After the selection of one point inside each kidney for the entire volume, the automatic extraction of kidney contours was performed on each acquired slice; the segmentation procedure was based on region growing and on the application of morphological operators and curvature-based motion. The area inside each contour was calculated and TRV was derived. Volume measurements were validated by comparison with measurements obtained by stereology. RESULTS: TRV estimated in patients was 768 ± 545 ml (range 161-3,111 ml). The automatic measurements were in excellent correlation with the manual ones (r = 0.99, y = x - 0.7), with a small bias and narrow limits of agreement in both absolute (-5 ± 37 ml) and percentage (-0.6 ± 9.6%) terms. CONCLUSION: This preliminary study showed the feasibility of a fast and nearly automated method for determining TRV; importantly it does not require the use of potentially nephrotoxic CM.
Authors: Timothy L Kline; Panagiotis Korfiatis; Marie E Edwards; Kyongtae T Bae; Alan Yu; Arlene B Chapman; Michal Mrug; Jared J Grantham; Douglas Landsittel; William M Bennett; Bernard F King; Peter C Harris; Vicente E Torres; Bradley J Erickson Journal: Kidney Int Date: 2017-05-20 Impact factor: 10.612
Authors: Youngwoo Kim; Yinghui Ge; Cheng Tao; Jianbing Zhu; Arlene B Chapman; Vicente E Torres; Alan S L Yu; Michal Mrug; William M Bennett; Michael F Flessner; Doug P Landsittel; Kyongtae T Bae Journal: Clin J Am Soc Nephrol Date: 2016-01-21 Impact factor: 8.237
Authors: Kanishka Sharma; Anna Caroli; Le Van Quach; Katja Petzold; Michela Bozzetto; Andreas L Serra; Giuseppe Remuzzi; Andrea Remuzzi Journal: PLoS One Date: 2017-05-30 Impact factor: 3.240
Authors: Kanishka Sharma; Christian Rupprecht; Anna Caroli; Maria Carolina Aparicio; Andrea Remuzzi; Maximilian Baust; Nassir Navab Journal: Sci Rep Date: 2017-05-17 Impact factor: 4.379