A scale space based algorithm for automated segmentation of single shot tagged MRI of shearing deformation.

OBJECT: This study proposes a scale space based algorithm for automated segmentation of single-shot tagged images of modest SNR. Furthermore the algorithm was designed for analysis of discontinuous or shearing types of motion, i.e. segmentation of broken tag patterns. MATERIALS AND METHODS: The proposed algorithm utilises non-linear scale space for automatic segmentation of single-shot tagged images. The algorithm's ability to automatically segment tagged shearing motion was evaluated in a numerical simulation and in vivo. A typical shearing deformation was simulated in a Shepp-Logan phantom allowing for quantitative evaluation of the algorithm's success rate as a function of both SNR and the amount of deformation. For a qualitative in vivo evaluation tagged images showing deformations in the calf muscles and eye movement in a healthy volunteer were acquired. RESULTS: Both the numerical simulation and the in vivo tagged data demonstrated the algorithm's ability for automated segmentation of single-shot tagged MR provided that SNR of the images is above 10 and the amount of deformation does not exceed the tag spacing. The latter constraint can be met by adjusting the tag delay or the tag spacing. CONCLUSION: The scale space based algorithm for automatic segmentation of single-shot tagged MR enables the application of tagged MR to complex (shearing) deformation and the processing of datasets with relatively low SNR.

Validation of continuously tagged MRI for the measurement of dynamic 3D skeletal muscle tissue deformation.

PURPOSE: Typically spatial modulation of the magnetization (SPAMM) tagged magnetic resonance imaging (MRI) requires many repeated motion cycles limiting the applicability to highly repeatable tissue motions only. This paper describes the validation of a novel SPAMM tagged MRI and post-processing framework for the measurement of complex and dynamic 3D soft tissue deformation following just three motion cycles. Techniques are applied to indentation induced deformation measurement of the upper arm and a silicone gel phantom. METHODS: A SPAMM tagged MRI methodology is presented allowing continuous (3.3-3.6 Hz) sampling of 3D dynamic soft tissue deformation using non segmented 3D acquisitions. The 3D deformation is reconstructed by the combination of three mutually orthogonal tagging directions, thus requiring only three repeated motion cycles. In addition a fully automatic post-processing framework is presented employing Gabor scale-space and filter-bank analysis for tag extrema segmentation and triangulated surface fitting aided by Gabor filter bank derived surface normals. Deformation is derived following tracking of tag surface triplet triangle intersections. The dynamic deformation measurements were validated using indentation tests (∼20 mm deep at 12 mm/s) on a silicone gel soft tissue phantom containing contrasting markers which provide a reference measure of deformation. In addition, the techniques were evaluated in vivo for dynamic skeletal muscle tissue deformation measurement during indentation of the biceps region of the upper arm in a volunteer. RESULTS: For the phantom and volunteer tag point location precision were 44 and 92 µm, respectively resulting in individual displacements precisions of 61 and 91 µm, respectively. For both the phantom and volunteer data cumulative displacement measurement accuracy could be evaluated and the difference between initial and final locations showed a mean and standard deviation of 0.44 and 0.59 mm for the phantom and 0.40 and 0.73 mm for the human data. Finally accuracy of (cumulative) displacement was evaluated using marker tracking in the silicone gel phantom. Differences between true and predicted marker locations showed a mean of 0.35 mm and a standard deviation of 0.63 mm. CONCLUSIONS: A novel SPAMM tagged MRI and fully automatic post-processing framework for the measurement of complex 3D dynamic soft tissue deformation following just three repeated motion cycles was presented. The techniques demonstrate dynamic measurement of complex 3D soft tissue deformation at subvoxel accuracy and precision and were validated for 3.3-3.6 Hz sampling of deformation speeds up to 12 mm/s.

Use of continuously MR tagged imaging for automated motion assessment in the abdomen: a feasibility study.

PURPOSE: To investigate the feasibility of measuring motion in the abdomen using a continuously tagged magnetic resonance imaging sequence. MATERIALS AND METHODS: To assess (nonperiodic) motion in the abdomen, a nontriggered, continuously tagged transient field echo (TFE) sequence was implemented that acquires one complete 3D dataset per prepulse after a fixed delay. In postprocessing, a frequency analysis approach was developed for compact reviewing of the data and noise suppression. For proof of principle, a simulation was made and one free-breathing dynamic in vivo scan was acquired in a healthy volunteer. During the dynamic scan the volunteer received glucagon intravenously. RESULTS: The simulation showed that this frequency analysis enables the extraction of motion at low signal-to-noise ratio levels. Motion information was successfully gathered from the in vivo scan. The decline in bowel motion caused by the administration of glucagon could be quantitatively measured using the continuously tagged sequence. CONCLUSION: Continuously tagged imaging in the abdomen for the purpose of automated gathering of motion information is feasible and could aid the study of bowel motion.

Validation of SPAMM tagged MRI based measurement of 3D soft tissue deformation.

PURPOSE: This study presents and validates a novel (non-ECG-triggered) MRI sequence based on spatial modulation of the magnetization (SPAMM) to noninvasively measure 3D (quasistatic) soft tissue deformations using only six acquisitions (three static and three indentations). In the current SPAMM tagged MRI approaches, data are typically constructed from many repeated motion cycles. This has so far restricted its application to the measurement of highly repeatable and periodic movements (e.g., cardiac deformation). In biomechanical applications where soft tissue deformation is artificially induced, often by indentation, significant repeatability constraints exist, and for clinical applications, discomfort and health issues generally preclude a large number of repetitions. METHODS: A novel (non-ECG-triggered) SPAMM tagged MRI sequence is presented, whereby a single 1-1 (first order) SPAMM set is acquired following a 3D transient field echo acquisition. Full 3D deformation measurement is achieved through the combination of only six acquisitions (three static and three motion cycles). The 3D deformation measurements were validated using quasistatic indentation tests and marker tracking in a silicone gel soft tissue phantom. In addition, the technique's ability to measure 3D soft tissue deformation in vivo was evaluated using indentation of the biceps region of the upper arm in a volunteer. RESULTS: Following comparison to marker tracking in the silicone gel phantom, the SPAMM tagged MRI based displacement measurement demonstrated subvoxel accuracy with a mean displacement difference of 72 microm and a standard deviation of 289 microm. In addition, precision of displacement magnitude was evaluated for both the phantom and the volunteer data. The standard deviations of the displacement magnitude with respect to the average displacement magnitude were 75 and 169 microm for the phantom and volunteer data, respectively. CONCLUSIONS: The subvoxel accuracy and precision demonstrated in the phantom in combination with the precision comparison between the phantom and the volunteer data provide confidence in the methods presented for measurement of soft tissue deformation in vivo. To the author's knowledge, since only six acquisitions are required, the presented methodology is the fastest SPAMM tagged MRI method currently available for the noninvasive measurement of quasistatic 3D soft tissue deformation.