View-sharing for 4D magnetic resonance imaging with randomized projection-encoding enables improvements of respiratory motion imaging for treatment planning in abdominothoracic radiotherapy Journal Article

   

Authors:	Subashi, E.; Feng, L.; Liu, Y.; Robertson, S.; Segars, P.; Driehuys, B.; Kelsey, C. R.; Yin, F. F.; Otazo, R.; Cai, J.
Article Title:	View-sharing for 4D magnetic resonance imaging with randomized projection-encoding enables improvements of respiratory motion imaging for treatment planning in abdominothoracic radiotherapy
Abstract:	Background and Purpose: The accuracy and precision of radiation therapy are dependent on the characterization of organ-at-risk and target motion. This work aims to demonstrate a 4D magnetic resonance imaging (MRI) method for improving spatial and temporal resolution in respiratory motion imaging for treatment planning in abdominothoracic radiotherapy. Materials and Methods: The spatial and temporal resolution of phase-resolved respiratory imaging is improved by considering a novel sampling function based on quasi-random projection-encoding and peripheral k-space view-sharing. The respiratory signal is determined directly from k-space, obviating the need for an external surrogate marker. The average breathing curve is used to optimize spatial resolution and temporal blurring by limiting the extent of data sharing in the Fourier domain. Improvements in image quality are characterized by evaluating changes in signal-to-noise ratio (SNR), resolution, target detection, and level of artifact. The method is validated in simulations, in a dynamic phantom, and in-vivo imaging. Results: Sharing of high-frequency k-space data, driven by the average breathing curve, improves spatial resolution and reduces artifacts. Although equal sharing of k-space data improves resolution and SNR in stationary features, phases with large temporal changes accumulate significant artifacts due to averaging of high frequency features. In the absence of view-sharing, no averaging and detection artifacts are observed while spatial resolution is degraded. Conclusions: The use of a quasi-random sampling function, with view-sharing driven by the average breathing curve, provides a feasible method for self-navigated 4D-MRI at improved spatial resolution. © 2023 The Authors
Keywords:	controlled study; treatment planning; disease marker; nuclear magnetic resonance imaging; diagnostic accuracy; accuracy; radiotherapy; signal noise ratio; in vivo study; abdomen; image quality; nuclear magnetic resonance; breathing pattern; lung blood vessel; thorax; principal component analysis; organs at risk; modulation transfer function; fourier transform; human; article; lesion volume; four-dimensional imaging; 4d-mri; projection-encoding; respiratory imaging; view-sharing
Journal Title:	Physics and Imaging in Radiation Oncology
Volume:	25
ISSN:	2405-6316
Publisher:	Elsevier B.V.
Date Published:	2023-01-01
Start Page:	100409
Language:	English
DOI:	10.1016/j.phro.2022.12.006
PROVIDER:	scopus
PMCID:	PMC9841273
PUBMED:	36655213
DOI/URL:	https://www.scopus.com/inward/record.uri?eid=2-s2.0-85145740794&doi=10.1016%2fj.phro.2022.12.006&partnerID=40&md5=80b2314f89de721769f5843de639ed9e
Notes:	Article -- MSK Cancer Center Support Grant (P30 CA008748) acknowledged in PDF -- MSK corresponding author is Ergys Subashi -- Export Date: 1 February 2023 -- Source: Scopus

https://synapse.mskcc.org/synapse/works/has_related_data_chk/202603