Publication

A rapid high-performance semi-automated tool to measure total kidney volume from MRI in autosomal dominant polycystic kidney disease

Simms, R. J., Doshi, T., Metherall, P., Ryan, D., Wright, P., Gruel, N., van Gastel, M. D. A., Gansevoort, R. T., Tindale, W. & Ong, A. C. M., Aug-2019, In : European Radiology. 29, 8, p. 4188-4197 10 p.

Research output: Contribution to journalArticleAcademicpeer-review

APA

Simms, R. J., Doshi, T., Metherall, P., Ryan, D., Wright, P., Gruel, N., ... Ong, A. C. M. (2019). A rapid high-performance semi-automated tool to measure total kidney volume from MRI in autosomal dominant polycystic kidney disease. European Radiology, 29(8), 4188-4197. https://doi.org/10.1007/s00330-018-5918-9

Author

Simms, Roslyn J ; Doshi, Trushali ; Metherall, Peter ; Ryan, Desmond ; Wright, Peter ; Gruel, Nicolas ; van Gastel, Maatje D A ; Gansevoort, Ron T ; Tindale, Wendy ; Ong, Albert C M. / A rapid high-performance semi-automated tool to measure total kidney volume from MRI in autosomal dominant polycystic kidney disease. In: European Radiology. 2019 ; Vol. 29, No. 8. pp. 4188-4197.

Harvard

Simms, RJ, Doshi, T, Metherall, P, Ryan, D, Wright, P, Gruel, N, van Gastel, MDA, Gansevoort, RT, Tindale, W & Ong, ACM 2019, 'A rapid high-performance semi-automated tool to measure total kidney volume from MRI in autosomal dominant polycystic kidney disease', European Radiology, vol. 29, no. 8, pp. 4188-4197. https://doi.org/10.1007/s00330-018-5918-9

Standard

A rapid high-performance semi-automated tool to measure total kidney volume from MRI in autosomal dominant polycystic kidney disease. / Simms, Roslyn J; Doshi, Trushali; Metherall, Peter; Ryan, Desmond; Wright, Peter; Gruel, Nicolas; van Gastel, Maatje D A; Gansevoort, Ron T; Tindale, Wendy; Ong, Albert C M.

In: European Radiology, Vol. 29, No. 8, 08.2019, p. 4188-4197.

Research output: Contribution to journalArticleAcademicpeer-review

Vancouver

Simms RJ, Doshi T, Metherall P, Ryan D, Wright P, Gruel N et al. A rapid high-performance semi-automated tool to measure total kidney volume from MRI in autosomal dominant polycystic kidney disease. European Radiology. 2019 Aug;29(8):4188-4197. https://doi.org/10.1007/s00330-018-5918-9


BibTeX

@article{bf62a429c2504e61b76a52eea0e82077,
title = "A rapid high-performance semi-automated tool to measure total kidney volume from MRI in autosomal dominant polycystic kidney disease",
abstract = "ObjectivesTo develop a high-performance, rapid semi-automated method (Sheffield TKV Tool) for measuring total kidney volume (TKV) from magnetic resonance images (MRI) in patients with autosomal dominant polycystic kidney disease (ADPKD).MethodsTKV was initially measured in 61 patients with ADPKD using the Sheffield TKV Tool and its performance compared to manual segmentation and other published methods (ellipsoidal, mid-slice, MIROS). It was then validated using an external dataset of MRI scans from 65 patients with ADPKD.ResultsSixty-one patients (mean age 4514years, baseline eGFR 7632ml/min/1.73m(2)) with ADPKD had a wide range of TKV (258-3680ml) measured manually. The Sheffield TKV Tool was highly accurate (mean volume error 0.55.3{\%} for right kidney, -0.75.5{\%} for left kidney), reproducible (intra-operator variability -0.2 +/- 1.3{\%}; inter-operator variability 1.1 +/- 2.9{\%}) and outperformed published methods. It took less than 6min to execute and performed consistently with high accuracy in an external MRI dataset of T2-weighted sequences with TKV acquired using three different scanners and measured using a different segmentation methodology (mean volume error was 3.45 +/- 3.96{\%}, n=65).Conclusions The Sheffield TKV Tool is operator friendly, requiring minimal user interaction to rapidly, accurately and reproducibly measure TKV in this, the largest reported unselected European patient cohort with ADPKD. It is more accurate than estimating equations and its accuracy is maintained at larger kidney volumes than previously reported with other semi-automated methods. It is free to use, can run as an independent executable and will accelerate the application of TKV as a prognostic biomarker for ADPKD into clinical practice.Key Points center dot This new semi-automated method (Sheffield TKV Tool) to measure total kidney volume (TKV) will facilitate the routine clinical assessment of patients with ADPKD.center dot Measuring TKV manually is time consuming and laborious.center dot TKV is a prognostic indicator in ADPKD and the only imaging biomarker approved by the FDA and EMA.",
keywords = "Polycystic kidney diseases, Autosomal dominant polycystic kidney disease, Magnetic resonance imaging, Kidneys, MAGNETIC-RESONANCE IMAGES, AUTOMATED SEGMENTATION, RENAL CYSTS, PROGRESSION, TOLVAPTAN",
author = "Simms, {Roslyn J} and Trushali Doshi and Peter Metherall and Desmond Ryan and Peter Wright and Nicolas Gruel and {van Gastel}, {Maatje D A} and Gansevoort, {Ron T} and Wendy Tindale and Ong, {Albert C M}",
year = "2019",
month = "8",
doi = "10.1007/s00330-018-5918-9",
language = "English",
volume = "29",
pages = "4188--4197",
journal = "European Radiology",
issn = "0938-7994",
publisher = "SPRINGER",
number = "8",

}

RIS

TY - JOUR

T1 - A rapid high-performance semi-automated tool to measure total kidney volume from MRI in autosomal dominant polycystic kidney disease

AU - Simms, Roslyn J

AU - Doshi, Trushali

AU - Metherall, Peter

AU - Ryan, Desmond

AU - Wright, Peter

AU - Gruel, Nicolas

AU - van Gastel, Maatje D A

AU - Gansevoort, Ron T

AU - Tindale, Wendy

AU - Ong, Albert C M

PY - 2019/8

Y1 - 2019/8

N2 - ObjectivesTo develop a high-performance, rapid semi-automated method (Sheffield TKV Tool) for measuring total kidney volume (TKV) from magnetic resonance images (MRI) in patients with autosomal dominant polycystic kidney disease (ADPKD).MethodsTKV was initially measured in 61 patients with ADPKD using the Sheffield TKV Tool and its performance compared to manual segmentation and other published methods (ellipsoidal, mid-slice, MIROS). It was then validated using an external dataset of MRI scans from 65 patients with ADPKD.ResultsSixty-one patients (mean age 4514years, baseline eGFR 7632ml/min/1.73m(2)) with ADPKD had a wide range of TKV (258-3680ml) measured manually. The Sheffield TKV Tool was highly accurate (mean volume error 0.55.3% for right kidney, -0.75.5% for left kidney), reproducible (intra-operator variability -0.2 +/- 1.3%; inter-operator variability 1.1 +/- 2.9%) and outperformed published methods. It took less than 6min to execute and performed consistently with high accuracy in an external MRI dataset of T2-weighted sequences with TKV acquired using three different scanners and measured using a different segmentation methodology (mean volume error was 3.45 +/- 3.96%, n=65).Conclusions The Sheffield TKV Tool is operator friendly, requiring minimal user interaction to rapidly, accurately and reproducibly measure TKV in this, the largest reported unselected European patient cohort with ADPKD. It is more accurate than estimating equations and its accuracy is maintained at larger kidney volumes than previously reported with other semi-automated methods. It is free to use, can run as an independent executable and will accelerate the application of TKV as a prognostic biomarker for ADPKD into clinical practice.Key Points center dot This new semi-automated method (Sheffield TKV Tool) to measure total kidney volume (TKV) will facilitate the routine clinical assessment of patients with ADPKD.center dot Measuring TKV manually is time consuming and laborious.center dot TKV is a prognostic indicator in ADPKD and the only imaging biomarker approved by the FDA and EMA.

AB - ObjectivesTo develop a high-performance, rapid semi-automated method (Sheffield TKV Tool) for measuring total kidney volume (TKV) from magnetic resonance images (MRI) in patients with autosomal dominant polycystic kidney disease (ADPKD).MethodsTKV was initially measured in 61 patients with ADPKD using the Sheffield TKV Tool and its performance compared to manual segmentation and other published methods (ellipsoidal, mid-slice, MIROS). It was then validated using an external dataset of MRI scans from 65 patients with ADPKD.ResultsSixty-one patients (mean age 4514years, baseline eGFR 7632ml/min/1.73m(2)) with ADPKD had a wide range of TKV (258-3680ml) measured manually. The Sheffield TKV Tool was highly accurate (mean volume error 0.55.3% for right kidney, -0.75.5% for left kidney), reproducible (intra-operator variability -0.2 +/- 1.3%; inter-operator variability 1.1 +/- 2.9%) and outperformed published methods. It took less than 6min to execute and performed consistently with high accuracy in an external MRI dataset of T2-weighted sequences with TKV acquired using three different scanners and measured using a different segmentation methodology (mean volume error was 3.45 +/- 3.96%, n=65).Conclusions The Sheffield TKV Tool is operator friendly, requiring minimal user interaction to rapidly, accurately and reproducibly measure TKV in this, the largest reported unselected European patient cohort with ADPKD. It is more accurate than estimating equations and its accuracy is maintained at larger kidney volumes than previously reported with other semi-automated methods. It is free to use, can run as an independent executable and will accelerate the application of TKV as a prognostic biomarker for ADPKD into clinical practice.Key Points center dot This new semi-automated method (Sheffield TKV Tool) to measure total kidney volume (TKV) will facilitate the routine clinical assessment of patients with ADPKD.center dot Measuring TKV manually is time consuming and laborious.center dot TKV is a prognostic indicator in ADPKD and the only imaging biomarker approved by the FDA and EMA.

KW - Polycystic kidney diseases

KW - Autosomal dominant polycystic kidney disease

KW - Magnetic resonance imaging

KW - Kidneys

KW - MAGNETIC-RESONANCE IMAGES

KW - AUTOMATED SEGMENTATION

KW - RENAL CYSTS

KW - PROGRESSION

KW - TOLVAPTAN

U2 - 10.1007/s00330-018-5918-9

DO - 10.1007/s00330-018-5918-9

M3 - Article

VL - 29

SP - 4188

EP - 4197

JO - European Radiology

JF - European Radiology

SN - 0938-7994

IS - 8

ER -

ID: 75969167