Measurement of murine kidney functional biomarkers using DCE-MRI: A multi-slice TRICKS technique and semi-automated image processing algorithm

Kai Jiang, Hui Tang, Prasanna K. Mishra, Slobodan I Macura, Lilach O Lerman

Research output: Contribution to journalArticle

Abstract

Purpose: To propose a rapid multi-slice T1 measurement method using time-resolved imaging of contrast kinetics (TRICKS) and a semi-automated image processing algorithm for comprehensive assessment murine kidney function using dynamic contrast-enhanced MRI (DCE-MRI). Methods: A multi-slice TRICKS sampling scheme was implemented in an established rapid T1 measurement method. A semi-automated image-processing scheme employing basic image processing techniques and machine learning was developed to facilitate image analysis. Reliability of the multi-slice technique in measuring renal perfusion and glomerular filtration rate (GFR) was tested in normal mice (n = 7 for both techniques) by comparing to the validated single-slice technique. Utility of this method was demonstrated on mice after either sham surgery (n = 7) or induction of unilateral renal artery stenosis (RAS, n = 8). Renal functional parameters were extracted using a validated bi-compartment model. Results: The TRICKS sampling scheme achieved an acceleration factor of 2.7, allowing imaging of eight axial slices at 1.23 s/scan. With the aid of the semi-automated scheme, image analysis required under 15-min for both kidneys per mouse. The multi-slice technique yielded renal perfusion and GFR values comparable to the single-slice technique. Model-fitted renal parameters successfully differentiated control and stenotic mouse kidneys, including renal perfusion (706.5 ± 164.0 vs. 375.9 ± 277.9 mL/100 g/min, P = 0.002), blood flow (1.6 ± 0.4 vs. 0.7 ± 0.7 mL/min, P < 0.001), and GFR (142.9 ± 17.9 vs. 58.0 ± 42.8 μL/min, P < 0.001). Conclusion: The multi-slice TRICKS-based DCE-MRI technique, with a semi-automated image processing scheme, allows rapid and comprehensive measurement of murine kidney function.

Original languageEnglish (US)
Pages (from-to)226-234
Number of pages9
JournalMagnetic Resonance Imaging
Volume63
DOIs
StatePublished - Nov 1 2019

Fingerprint

Biomarkers
Magnetic resonance imaging
Image processing
Kidney
Imaging techniques
Kinetics
Image analysis
Glomerular Filtration Rate
Sampling
Perfusion
Surgery
Learning systems
Blood
Renal Artery Obstruction

Keywords

  • Dynamic contrast enhanced MRI
  • Kidney volume
  • Machine learning
  • Renal functional biomarkers
  • Time-resolved imaging of contrast kinetics

ASJC Scopus subject areas

  • Biophysics
  • Biomedical Engineering
  • Radiology Nuclear Medicine and imaging

Cite this

@article{75741c7914c1467b9dec9ec71d2a2704,
title = "Measurement of murine kidney functional biomarkers using DCE-MRI: A multi-slice TRICKS technique and semi-automated image processing algorithm",
abstract = "Purpose: To propose a rapid multi-slice T1 measurement method using time-resolved imaging of contrast kinetics (TRICKS) and a semi-automated image processing algorithm for comprehensive assessment murine kidney function using dynamic contrast-enhanced MRI (DCE-MRI). Methods: A multi-slice TRICKS sampling scheme was implemented in an established rapid T1 measurement method. A semi-automated image-processing scheme employing basic image processing techniques and machine learning was developed to facilitate image analysis. Reliability of the multi-slice technique in measuring renal perfusion and glomerular filtration rate (GFR) was tested in normal mice (n = 7 for both techniques) by comparing to the validated single-slice technique. Utility of this method was demonstrated on mice after either sham surgery (n = 7) or induction of unilateral renal artery stenosis (RAS, n = 8). Renal functional parameters were extracted using a validated bi-compartment model. Results: The TRICKS sampling scheme achieved an acceleration factor of 2.7, allowing imaging of eight axial slices at 1.23 s/scan. With the aid of the semi-automated scheme, image analysis required under 15-min for both kidneys per mouse. The multi-slice technique yielded renal perfusion and GFR values comparable to the single-slice technique. Model-fitted renal parameters successfully differentiated control and stenotic mouse kidneys, including renal perfusion (706.5 ± 164.0 vs. 375.9 ± 277.9 mL/100 g/min, P = 0.002), blood flow (1.6 ± 0.4 vs. 0.7 ± 0.7 mL/min, P < 0.001), and GFR (142.9 ± 17.9 vs. 58.0 ± 42.8 μL/min, P < 0.001). Conclusion: The multi-slice TRICKS-based DCE-MRI technique, with a semi-automated image processing scheme, allows rapid and comprehensive measurement of murine kidney function.",
keywords = "Dynamic contrast enhanced MRI, Kidney volume, Machine learning, Renal functional biomarkers, Time-resolved imaging of contrast kinetics",
author = "Kai Jiang and Hui Tang and Mishra, {Prasanna K.} and Macura, {Slobodan I} and Lerman, {Lilach O}",
year = "2019",
month = "11",
day = "1",
doi = "10.1016/j.mri.2019.08.029",
language = "English (US)",
volume = "63",
pages = "226--234",
journal = "Magnetic Resonance Imaging",
issn = "0730-725X",
publisher = "Elsevier Inc.",

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TY - JOUR

T1 - Measurement of murine kidney functional biomarkers using DCE-MRI

T2 - A multi-slice TRICKS technique and semi-automated image processing algorithm

AU - Jiang, Kai

AU - Tang, Hui

AU - Mishra, Prasanna K.

AU - Macura, Slobodan I

AU - Lerman, Lilach O

PY - 2019/11/1

Y1 - 2019/11/1

N2 - Purpose: To propose a rapid multi-slice T1 measurement method using time-resolved imaging of contrast kinetics (TRICKS) and a semi-automated image processing algorithm for comprehensive assessment murine kidney function using dynamic contrast-enhanced MRI (DCE-MRI). Methods: A multi-slice TRICKS sampling scheme was implemented in an established rapid T1 measurement method. A semi-automated image-processing scheme employing basic image processing techniques and machine learning was developed to facilitate image analysis. Reliability of the multi-slice technique in measuring renal perfusion and glomerular filtration rate (GFR) was tested in normal mice (n = 7 for both techniques) by comparing to the validated single-slice technique. Utility of this method was demonstrated on mice after either sham surgery (n = 7) or induction of unilateral renal artery stenosis (RAS, n = 8). Renal functional parameters were extracted using a validated bi-compartment model. Results: The TRICKS sampling scheme achieved an acceleration factor of 2.7, allowing imaging of eight axial slices at 1.23 s/scan. With the aid of the semi-automated scheme, image analysis required under 15-min for both kidneys per mouse. The multi-slice technique yielded renal perfusion and GFR values comparable to the single-slice technique. Model-fitted renal parameters successfully differentiated control and stenotic mouse kidneys, including renal perfusion (706.5 ± 164.0 vs. 375.9 ± 277.9 mL/100 g/min, P = 0.002), blood flow (1.6 ± 0.4 vs. 0.7 ± 0.7 mL/min, P < 0.001), and GFR (142.9 ± 17.9 vs. 58.0 ± 42.8 μL/min, P < 0.001). Conclusion: The multi-slice TRICKS-based DCE-MRI technique, with a semi-automated image processing scheme, allows rapid and comprehensive measurement of murine kidney function.

AB - Purpose: To propose a rapid multi-slice T1 measurement method using time-resolved imaging of contrast kinetics (TRICKS) and a semi-automated image processing algorithm for comprehensive assessment murine kidney function using dynamic contrast-enhanced MRI (DCE-MRI). Methods: A multi-slice TRICKS sampling scheme was implemented in an established rapid T1 measurement method. A semi-automated image-processing scheme employing basic image processing techniques and machine learning was developed to facilitate image analysis. Reliability of the multi-slice technique in measuring renal perfusion and glomerular filtration rate (GFR) was tested in normal mice (n = 7 for both techniques) by comparing to the validated single-slice technique. Utility of this method was demonstrated on mice after either sham surgery (n = 7) or induction of unilateral renal artery stenosis (RAS, n = 8). Renal functional parameters were extracted using a validated bi-compartment model. Results: The TRICKS sampling scheme achieved an acceleration factor of 2.7, allowing imaging of eight axial slices at 1.23 s/scan. With the aid of the semi-automated scheme, image analysis required under 15-min for both kidneys per mouse. The multi-slice technique yielded renal perfusion and GFR values comparable to the single-slice technique. Model-fitted renal parameters successfully differentiated control and stenotic mouse kidneys, including renal perfusion (706.5 ± 164.0 vs. 375.9 ± 277.9 mL/100 g/min, P = 0.002), blood flow (1.6 ± 0.4 vs. 0.7 ± 0.7 mL/min, P < 0.001), and GFR (142.9 ± 17.9 vs. 58.0 ± 42.8 μL/min, P < 0.001). Conclusion: The multi-slice TRICKS-based DCE-MRI technique, with a semi-automated image processing scheme, allows rapid and comprehensive measurement of murine kidney function.

KW - Dynamic contrast enhanced MRI

KW - Kidney volume

KW - Machine learning

KW - Renal functional biomarkers

KW - Time-resolved imaging of contrast kinetics

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