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Time-resolved magnetic resonance fingerprinting for radiotherapy motion management.

Publication ,  Journal Article
Li, T; Cui, D; Hui, ES; Cai, J
Published in: Med Phys
December 2020

PURPOSE: This study aims to develop a novel time-resolved magnetic resonance fingerprinting (TR-MRF) technique for respiratory motion imaging applications. MATERIALS AND METHODS: The TR-MRF technique consists of repeated MRF acquisitions using an unbalanced steady-state free precession sequence with spiral-in-spiral-out trajectory. Time-resolved magnetic resonance fingerprinting was first tested via computer simulation using a four-dimensional (4D) extended cardiac-torso (XCAT) phantom for both regular and irregular breathing profiles, and was tested in three healthy volunteers. Parametric TR-MRF maps at different respiratory phases were subsequently estimated using our TR-MRF sorting and reconstruction techniques. The resulting TR-MRF maps were evaluated using a set of metrices related to radiotherapy applications, including absolute difference in motion amplitude, error in the amplitude of diaphragm motion (ADM), tumor volume error (TVE), signal-to-noise ratio (SNR), and tumor contrast. RESULTS: TR-MRF maps with regular and irregular breathing were successfully generated in XCAT phantom. Numerical simulations showed that the TVE were 1.6 ± 2.7% and 1.3 ± 2.2%, the average absolute differences in tumor motion amplitude were 0.3 ± 0.7 mm and 0.3 ± 0.6 mm, and the ADM were 4.1 ± 0.9% and 3.5 ± 0.9% for irregular and regular breathing, respectively. The SNR of the T1 and T2 maps of the liver and the tumor were generally higher for regular breathing compared to irregular breathing, whereas tumor-to-liver contrast is similar between the two breathing patterns. The proposed technique was successfully implemented on the healthy volunteers. CONCLUSION: We have successfully demonstrated in both digital phantom and healthy subjects a novel TR-MRF technique capable of imaging respiratory motions with simultaneous quantification of MR multiparametric maps.

Duke Scholars

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Published In

Med Phys

DOI

EISSN

2473-4209

Publication Date

December 2020

Volume

47

Issue

12

Start / End Page

6286 / 6293

Location

United States

Related Subject Headings

  • Phantoms, Imaging
  • Nuclear Medicine & Medical Imaging
  • Motion
  • Magnetic Resonance Spectroscopy
  • Magnetic Resonance Imaging
  • Image Processing, Computer-Assisted
  • Humans
  • Computer Simulation
  • 5105 Medical and biological physics
  • 4003 Biomedical engineering
 

Citation

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Li, T., Cui, D., Hui, E. S., & Cai, J. (2020). Time-resolved magnetic resonance fingerprinting for radiotherapy motion management. Med Phys, 47(12), 6286–6293. https://doi.org/10.1002/mp.14513
Li, Tian, Di Cui, Edward S. Hui, and Jing Cai. “Time-resolved magnetic resonance fingerprinting for radiotherapy motion management.Med Phys 47, no. 12 (December 2020): 6286–93. https://doi.org/10.1002/mp.14513.
Li T, Cui D, Hui ES, Cai J. Time-resolved magnetic resonance fingerprinting for radiotherapy motion management. Med Phys. 2020 Dec;47(12):6286–93.
Li, Tian, et al. “Time-resolved magnetic resonance fingerprinting for radiotherapy motion management.Med Phys, vol. 47, no. 12, Dec. 2020, pp. 6286–93. Pubmed, doi:10.1002/mp.14513.
Li T, Cui D, Hui ES, Cai J. Time-resolved magnetic resonance fingerprinting for radiotherapy motion management. Med Phys. 2020 Dec;47(12):6286–6293.

Published In

Med Phys

DOI

EISSN

2473-4209

Publication Date

December 2020

Volume

47

Issue

12

Start / End Page

6286 / 6293

Location

United States

Related Subject Headings

  • Phantoms, Imaging
  • Nuclear Medicine & Medical Imaging
  • Motion
  • Magnetic Resonance Spectroscopy
  • Magnetic Resonance Imaging
  • Image Processing, Computer-Assisted
  • Humans
  • Computer Simulation
  • 5105 Medical and biological physics
  • 4003 Biomedical engineering