Henry Rusinek1, Jeremy C Lim2, Nicole Wake3, Jas-mine Seah4, Elissa Botterill2, Shawna Farquharson5, Artem Mikheev3, Ruth P Lim2,6. 1. Center for Advanced Imaging Innovation and Research (CAI2R) and Department of Radiology, New York University School of Medicine, 660 1st Avenue, Rm413, New York, NY, 10016, USA. hr18@nyu.edu. 2. Radiology, Austin Health, Melbourne, VIC, Australia. 3. Center for Advanced Imaging Innovation and Research (CAI2R) and Department of Radiology, New York University School of Medicine, 660 1st Avenue, Rm413, New York, NY, 10016, USA. 4. Endocrinology, Austin Health, Melbourne, VIC, Australia. 5. Florey Neuroscience Institute, Melbourne, VIC, Australia. 6. The University of Melbourne, Melbourne, VIC, Australia.
Abstract
OBJECTIVE: To investigate the precision and accuracy of a new semi-automated method for kidney segmentation from single-breath-hold non-contrast MRI. MATERIALS AND METHODS: The user draws approximate kidney contours on every tenth slice, focusing on separating adjacent organs from the kidney. The program then performs a sequence of fully automatic steps: contour filling, interpolation, non-uniformity correction, sampling of representative parenchyma signal, and 3D binary morphology. Three independent observers applied the method to images of 40 kidneys ranging in volume from 94.6 to 254.5 cm(3). Manually constructed reference masks were used to assess accuracy. RESULTS: The volume errors for the three readers were: 4.4% ± 3.0%, 2.9% ± 2.3%, and 3.1% ± 2.7%. The relative discrepancy across readers was 2.5% ± 2.1%. The interactive processing time on average was 1.5 min per kidney. CONCLUSIONS: Pending further validation, the semi-automated method could be applied for monitoring of renal status using non-contrast MRI.
OBJECTIVE: To investigate the precision and accuracy of a new semi-automated method for kidney segmentation from single-breath-hold non-contrast MRI. MATERIALS AND METHODS: The user draws approximate kidney contours on every tenth slice, focusing on separating adjacent organs from the kidney. The program then performs a sequence of fully automatic steps: contour filling, interpolation, non-uniformity correction, sampling of representative parenchyma signal, and 3D binary morphology. Three independent observers applied the method to images of 40 kidneys ranging in volume from 94.6 to 254.5 cm(3). Manually constructed reference masks were used to assess accuracy. RESULTS: The volume errors for the three readers were: 4.4% ± 3.0%, 2.9% ± 2.3%, and 3.1% ± 2.7%. The relative discrepancy across readers was 2.5% ± 2.1%. The interactive processing time on average was 1.5 min per kidney. CONCLUSIONS: Pending further validation, the semi-automated method could be applied for monitoring of renal status using non-contrast MRI.
Authors: Yen Seow Benjamin Goh; Mei Wen Fiona Wu; Bee Choo Tai; King Chien Joe Lee; Lata Raman; Boon Wee Teo; Anatharaman Vathsala; Ho Yee Tiong Journal: J Urol Date: 2013-06-11 Impact factor: 7.450
Authors: Todd Woodard; Sigurdur Sigurdsson; John D Gotal; Alyssa A Torjesen; Lesley A Inker; Thor Aspelund; Gudny Eiriksdottir; Vilmundur Gudnason; Tamara B Harris; Lenore J Launer; Andrew S Levey; Gary F Mitchell Journal: Am J Kidney Dis Date: 2014-07-10 Impact factor: 8.860
Authors: Pierre-Hugues Vivier; Pippa Storey; Hersh Chandarana; Akira Yamamoto; Kristopher Tantillo; Umer Khan; Jeff L Zhang; Eric E Sigmund; Henry Rusinek; James S Babb; Michael Bubenheim; Vivian S Lee Journal: Invest Radiol Date: 2013-07 Impact factor: 6.016
Authors: Kyungsoo Bae; Bumwoo Park; Hongliang Sun; Jinhong Wang; Cheng Tao; Arlene B Chapman; Vicente E Torres; Jared J Grantham; Michal Mrug; William M Bennett; Michael F Flessner; Doug P Landsittel; Kyongtae T Bae Journal: Clin J Am Soc Nephrol Date: 2013-03-21 Impact factor: 8.237
Authors: Iosif Mendichovszky; Pim Pullens; Ilona Dekkers; Fabio Nery; Octavia Bane; Andreas Pohlmann; Anneloes de Boer; Alexandra Ljimani; Aghogho Odudu; Charlotte Buchanan; Kanishka Sharma; Christoffer Laustsen; Anita Harteveld; Xavier Golay; Ivan Pedrosa; David Alsop; Sean Fain; Anna Caroli; Pottumarthi Prasad; Susan Francis; Eric Sigmund; Maria Fernández-Seara; Steven Sourbron Journal: MAGMA Date: 2019-10-18 Impact factor: 2.310