ArticleMedical physics2017
Respiratory motion prediction and prospective correction for free-breathing arterial spin-labeled perfusion MRI of the kidneys.
Article in Medical physics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 13 citations in OpenAlex.
- Investigation of Endogenous Renal CEST Contrast and the Influence of Respiratory Motion on a Clinical 3 Tesla MRI: An In Vivo and In Vitro Study.Magnetic resonance in medicine · 2026Article
- Non-contrast myocardial perfusion in rest and exercise stress using systolic flow-sensitive alternating inversion recovery.Magma (New York, N.Y.) · 2022Article
- Consensus-based technical recommendations for clinical translation of renal ASL MRI.Magma (New York, N.Y.) · 2020Article
- Motion prediction enables simulated MR-imaging of freely moving model organisms.PLoS computational biology · 2019Article
- In vivo measurements of kidney glomerular number and size in healthy and OsAmerican journal of physiology. Renal physiology · 2019Article
- Enabling free-breathing background suppressed renal pCASL using fat imaging and retrospective motion correction.Magnetic resonance in medicine · 2019Article
- CAPTURE: Consistently Acquired Projections for Tuned and Robust Estimation: A Self-Navigated Respiratory Motion Correction Approach.Investigative radiology · 2018Article
- Non-Invasive Renal Perfusion Imaging Using Arterial Spin Labeling MRI: Challenges and Opportunities.Diagnostics (Basel, Switzerland) · 2018Review
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Authors and funding
13 authors at 9 institutions in 4 countries.
Funding
Abstract
purposeRespiratory motion prediction using an artificial neural network (ANN) was integrated with pseudocontinuous arterial spin labeling (pCASL) MRI to allow free-breathing perfusion measurements in the kidney. In this study, we evaluated the performance of the ANN to accurately predict the location of the kidneys during image acquisition.
methodsA pencil-beam navigator was integrated with a pCASL sequence to measure lung/diaphragm motion during ANN training and the pCASL transit delay. The ANN algorithm ran concurrently in the background to predict organ location during the 0.7-s 15-slice acquisition based on the navigator data. The predictions were supplied to the pulse sequence to prospectively adjust the axial slice acquisition to match the predicted organ location. Additional navigators were acquired immediately after the multislice acquisition to assess the performance and accuracy of the ANN. The technique was tested in eight healthy volunteers.
resultsThe root-mean-square error (RMSE) and mean absolute error (MAE) for the eight volunteers were 1.91 ± 0.17 mm and 1.43 ± 0.17 mm, respectively, for the ANN. The RMSE increased with transit delay. The MAE typically increased from the first to last prediction in the image acquisition. The overshoot was 23.58% ± 3.05% using the target prediction accuracy of ± 1 mm.
conclusionRespiratory motion prediction with prospective motion correction was successfully demonstrated for free-breathing perfusion MRI of the kidney. The method serves as an alternative to multiple breathholds and requires minimal effort from the patient.
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