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Title: SU-G-JeP1-15: Sliding Window Prior Data Assisted Compressed Sensing for MRI Lung Tumor Tracking

Abstract

Purpose: Prior Data Assisted Compressed Sensing (PDACS) is a partial k-space acquisition and reconstruction method for mobile tumour (i.e. lung) tracking using on-line MRI in radiotherapy. PDACS partially relies on prior data acquired at the beginning of dynamic scans, and is therefore susceptible to artifacts in longer duration scan due to slow drifts in MR signal. A novel sliding window strategy is presented to mitigate this effect. Methods: MRI acceleration is simulated by retrospective removal of data from the fully sampled sets. Six lung cancer patients were scanned (clinical 3T MRI) using a balanced steady state free precession (bSSFP) sequence for 3 minutes at approximately 4 frames per second, for a total of 650 dynamics. PDACS acceleration is achieved by undersampling of k-space in a single pseudo-random pattern. Reconstruction iteratively minimizes the total variations while constraining the images to satisfy both the currently acquired data and the prior data in missing k-space. Our novel sliding window technique (SW-PDACS), uses a series of distinct pseudo-random under-sampling patterns of partial k-space – with the prior data drawn from a sliding window of the most recent data available. Under-sampled data, simulating 2 – 5x acceleration are reconstructed using PDACS and SW-PDACS. Three quantitativemore » metrics: artifact power, centroid error and Dice’s coefficient are computed for comparison. Results: Quantitively metric values from all 6 patients are averaged in 3 bins, each containing approximately one minute of dynamic data. For the first minute bin, PDACS and SW-PDACS give comparable results. Progressive decline in image quality metrics in bins 2 and 3 are observed for PDACS. No decline in image quality is observed for SW-PDACS. Conclusion: The novel approach presented (SW-PDACS) is a more robust for accelerating longer duration (>1 minute) dynamic MRI scans for tracking lung tumour motion using on-line MRI in radiotherapy. B.G. Fallone is a co-founder and CEO of MagnetTx Oncology Solutions (under discussions to license Alberta bi-planar linac MR for commercialization).« less

Authors:
; ;  [1];  [2];  [3];  [1];  [1];  [2];  [2]
  1. Department of Oncology, University of Alberta, Edmonton, AB (Canada)
  2. (Canada)
  3. Medical Physics Division, Cross Cancer Institute, Edmonton, AB (Canada)
Publication Date:
OSTI Identifier:
22649340
Resource Type:
Journal Article
Resource Relation:
Journal Name: Medical Physics; Journal Volume: 43; Journal Issue: 6; Other Information: (c) 2016 American Association of Physicists in Medicine; Country of input: International Atomic Energy Agency (IAEA)
Country of Publication:
United States
Language:
English
Subject:
60 APPLIED LIFE SCIENCES; 61 RADIATION PROTECTION AND DOSIMETRY; IMAGES; LINEAR ACCELERATORS; LUNGS; MATHEMATICAL SOLUTIONS; METRICS; NEOPLASMS; NMR IMAGING

Citation Formats

Yip, E, Wachowicz, K, Rathee, S, Medical Physics Division, Cross Cancer Institute, Edmonton, AB, Yun, J, Gabos, Z, Fallone, B, Medical Physics Division, Cross Cancer Institute, Edmonton, AB, and MagnetTx Oncology Solutions, Ltd, PO Box 52112, Edmonton AB. SU-G-JeP1-15: Sliding Window Prior Data Assisted Compressed Sensing for MRI Lung Tumor Tracking. United States: N. p., 2016. Web. doi:10.1118/1.4956990.
Yip, E, Wachowicz, K, Rathee, S, Medical Physics Division, Cross Cancer Institute, Edmonton, AB, Yun, J, Gabos, Z, Fallone, B, Medical Physics Division, Cross Cancer Institute, Edmonton, AB, & MagnetTx Oncology Solutions, Ltd, PO Box 52112, Edmonton AB. SU-G-JeP1-15: Sliding Window Prior Data Assisted Compressed Sensing for MRI Lung Tumor Tracking. United States. doi:10.1118/1.4956990.
Yip, E, Wachowicz, K, Rathee, S, Medical Physics Division, Cross Cancer Institute, Edmonton, AB, Yun, J, Gabos, Z, Fallone, B, Medical Physics Division, Cross Cancer Institute, Edmonton, AB, and MagnetTx Oncology Solutions, Ltd, PO Box 52112, Edmonton AB. Wed . "SU-G-JeP1-15: Sliding Window Prior Data Assisted Compressed Sensing for MRI Lung Tumor Tracking". United States. doi:10.1118/1.4956990.
@article{osti_22649340,
title = {SU-G-JeP1-15: Sliding Window Prior Data Assisted Compressed Sensing for MRI Lung Tumor Tracking},
author = {Yip, E and Wachowicz, K and Rathee, S and Medical Physics Division, Cross Cancer Institute, Edmonton, AB and Yun, J and Gabos, Z and Fallone, B and Medical Physics Division, Cross Cancer Institute, Edmonton, AB and MagnetTx Oncology Solutions, Ltd, PO Box 52112, Edmonton AB},
abstractNote = {Purpose: Prior Data Assisted Compressed Sensing (PDACS) is a partial k-space acquisition and reconstruction method for mobile tumour (i.e. lung) tracking using on-line MRI in radiotherapy. PDACS partially relies on prior data acquired at the beginning of dynamic scans, and is therefore susceptible to artifacts in longer duration scan due to slow drifts in MR signal. A novel sliding window strategy is presented to mitigate this effect. Methods: MRI acceleration is simulated by retrospective removal of data from the fully sampled sets. Six lung cancer patients were scanned (clinical 3T MRI) using a balanced steady state free precession (bSSFP) sequence for 3 minutes at approximately 4 frames per second, for a total of 650 dynamics. PDACS acceleration is achieved by undersampling of k-space in a single pseudo-random pattern. Reconstruction iteratively minimizes the total variations while constraining the images to satisfy both the currently acquired data and the prior data in missing k-space. Our novel sliding window technique (SW-PDACS), uses a series of distinct pseudo-random under-sampling patterns of partial k-space – with the prior data drawn from a sliding window of the most recent data available. Under-sampled data, simulating 2 – 5x acceleration are reconstructed using PDACS and SW-PDACS. Three quantitative metrics: artifact power, centroid error and Dice’s coefficient are computed for comparison. Results: Quantitively metric values from all 6 patients are averaged in 3 bins, each containing approximately one minute of dynamic data. For the first minute bin, PDACS and SW-PDACS give comparable results. Progressive decline in image quality metrics in bins 2 and 3 are observed for PDACS. No decline in image quality is observed for SW-PDACS. Conclusion: The novel approach presented (SW-PDACS) is a more robust for accelerating longer duration (>1 minute) dynamic MRI scans for tracking lung tumour motion using on-line MRI in radiotherapy. B.G. Fallone is a co-founder and CEO of MagnetTx Oncology Solutions (under discussions to license Alberta bi-planar linac MR for commercialization).},
doi = {10.1118/1.4956990},
journal = {Medical Physics},
number = 6,
volume = 43,
place = {United States},
year = {Wed Jun 15 00:00:00 EDT 2016},
month = {Wed Jun 15 00:00:00 EDT 2016}
}