PURPOSE: Several image-based retrospective sorting methods of 4D magnetic
resonance imaging (4D MRI) have been proposed for respiratory motion
reconstruction in external beam radiotherapy. However, the optimal strategy for
providing accurate and artifact-free 4D MRI, ideally corresponding to an average
breathing cycle, is not yet defined. This study presents a proactive comparison
of three published image-based sorting methods, to define a groundwork for
benchmarking in 4D MRI.
METHODS: Three published 4D MRI methods were selected for image retrospective
sorting: body area, mutual information, and navigator slice. The three
image-based methods were compared against a conventional retrospective sorting
method based on an external surrogate. Comparisons were performed by means of an
MRI digital phantom, derived from the XCAT CT phantom generated with different
patient-derived signals, for a total of 12 cases. Specific multislice MRI
acquisitions were simulated for slice sorting and sagittal, coronal, and axial
orientations were tested. An average 4D cycle was generated as ground truth.
RESULTS: Individual and grouped patient analyses showed better performance of the
navigator slice and mutual information in amplitude binning with respect to the
body area strategy. Binning artifacts were reduced on the diaphragm with the
slice navigator method due to the acquired internal information. Tumor motion
description accurately matched the ground truth in the mutual information
strategy with amplitude binning. The body area method followed the performance of
the external surrogate and presented larger errors, since was not correlated with
the internal anatomy. Sagittal and coronal orientations reported lower errors
than axial slicing. Individual analysis showed the need of a patient-specific
evaluation for the selection of the best method.
CONCLUSIONS: A comparison between three different image-based retrospective
sorting methods for 4D MRI is proposed, providing guidelines for benchmark
definition in MRI-guided radiotherapy.