A Novel Fast Helical 4D-CT Acquisition Technique to Generate Low-Noise Sorting Artifact–Free Images at User-Selected Breathing Phases

Thomas, D; Lamb, James; White, Benjamin; Jani, S; Gaudio, S.; Lee, Percy; Ruan, Dan; McNitt-Gray, Michael F.; Low, Daniel A.

doi:10.1016/j.ijrobp.2014.01.016

Cited by 55 publications

(83 citation statements)

References 34 publications

(38 reference statements)

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“…An initial clinical study of the 5DCT technique, described by Thomas et al, 7 achieved a mean model error of 1.19 ±0.37 mm across ten patients. The quantity reported as model error by Thomas et al 7 is referred to as model residual in this study because similarity between the original scans and corresponding 5DCT reconstructions was subsequently adopted as the primary error metric.…”

Section: Discussionmentioning

confidence: 99%

Comparison of breathing gated CT images generated using a 5DCT technique and a commercial clinical protocol in a porcine model

et al. 2015

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Purpose: To demonstrate that a "5DCT" technique which utilizes fast helical acquisition yields the same respiratory-gated images as a commercial technique for regular, mechanically produced breathing cycles. Methods: Respiratory-gated images of an anesthetized, mechanically ventilated pig were generated using a Siemens low-pitch helical protocol and 5DCT for a range of breathing rates and amplitudes and with standard and low dose imaging protocols. 5DCT reconstructions were independently evaluated by measuring the distances between tissue positions predicted by a 5D motion model and those measured using deformable registration, as well by reconstructing the originally acquired scans. Discrepancies between the 5DCT and commercial reconstructions were measured using landmark correspondences. Results:The mean distance between model predicted tissue positions and deformably registered tissue positions over the nine datasets was 0.65 ± 0.28 mm. Reconstructions of the original scans were on average accurate to 0.78 ± 0.57 mm. Mean landmark displacement between the commercial and 5DCT images was 1.76 ± 1.25 mm while the maximum lung tissue motion over the breathing cycle had a mean value of 27.2 ± 4.6 mm. An image composed of the average of 30 deformably registered images acquired with a low dose protocol had 6 HU image noise (single standard deviation) in the heart versus 31 HU for the commercial images. Conclusions: An end to end evaluation of the 5DCT technique was conducted through landmark based comparison to breathing gated images acquired with a commercial protocol under highly regular ventilation. The techniques were found to agree to within 2 mm for most respiratory phases and most points in the lung. C 2015 American Association of Physicists in Medicine.

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Section: Discussionmentioning

confidence: 99%

Comparison of breathing gated CT images generated using a 5DCT technique and a commercial clinical protocol in a porcine model

et al. 2015

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“…Techniques have been proposed for retrospective sorting-based approaches with the aim of reducing motion artifacts in 4DCT images [15, 17-23]. Of these, respiratory motion model based techniques have shown promising improvement in mitigating sorting artifacts [18, 19, 24, 25], besides the additional attractive qualities of their predictive power. In particular, Thomas et al [25] demonstrated the generation of motion artifact-free 4DCT images at user-selected breathing phases based on a fast helical CT acquisition technique and a deformable lung motion model.…”

Section: Introductionmentioning

confidence: 99%

“…Of these, respiratory motion model based techniques have shown promising improvement in mitigating sorting artifacts [18, 19, 24, 25], besides the additional attractive qualities of their predictive power. In particular, Thomas et al [25] demonstrated the generation of motion artifact-free 4DCT images at user-selected breathing phases based on a fast helical CT acquisition technique and a deformable lung motion model. The model was based on Low et al [26], employing two surrogates, breathing amplitude and rate, as independent variables.…”

Section: Introductionmentioning

confidence: 99%

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A Method for Assessing Ground-Truth Accuracy of the 5DCT Technique

Dou

Thomas

O’Connell

et al. 2015

International Journal of Radiation Oncology*Biology*Physics

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Purpose To develop a technique that assesses the accuracy of the breathing phase-specific volume image generation process by patient-specific breathing motion model using the original free-breathing CT scans as ground truths. Methods 16 lung cancer patients underwent a previously published protocol in which 25 free-breathing fast helical CT scans were acquired with a simultaneous breathing surrogate. A patient-specific motion model was constructed based on the tissue displacements determined by a state-of-the-art deformable image registration. The first image was arbitrarily selected as the reference image. The motion model was used, along with the free-breathing phase information of the original 25 image datasets, to generate a set of deformation vector fields (DVF) that mapped the reference image to the 24 non-reference images. The high-pitch helically acquired original scans served as ground truths because they captured the instantaneous tissue positions during free breathing. Image similarity between the simulated and the original scans was assessed using deformable registration that evaluated the point-wise discordance throughout the lungs. Results Qualitative comparisons using image overlays showed excellent agreement between the simulated and the original images. Even large 2 cm diaphragm displacements were very well modeled, as was sliding motion across the lung-chest wall boundary. The mean error across the patient cohort was 1.15±0.37 mm, while the mean 95th percentile error was 2.47±0.78 mm. Conclusion The proposed ground truth based technique provided voxel-by-voxel accuracy analysis that could identify organ or tumor-specific motion modeling errors for treatment planning. Despite a large variety of breathing patterns and lung deformations during the free-breathing scanning session, the 5DCT technique was able to accurately reproduce the original helical CT scans, suggesting its applicability to a wide range of patients.

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“…[14][15][16] Various techniques have been proposed for retrospective sorting-based approaches with the aim of reducing irregular breathing artifacts in 4DCT images. [17][18][19][20][21] In particular, Thomas et al demonstrated the acquisition of sorting-artifact-free CT images at arbitrary user-selected breathing phases based on a lung motion model 21 first published by Low et al 22 This approach is termed 5DCT (three spatial dimensions along with the breathing amplitude and breathing rate). The 5DCT image acquisition aims at capturing the extent of lung tissue motion by performing multiple high-pitch (1.2) helical scans with a simultaneously recorded surrogate signal.…”

Section: Introductionmentioning

confidence: 99%

Technical Note: Simulation of 4DCT tumor motion measurement errors

et al. 2015

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Purpose: To determine if and by how much the commercial 4DCT protocols under-and overestimate tumor breathing motion. Methods: 1D simulations were conducted that modeled a 16-slice CT scanner and tumors moving proportionally to breathing amplitude. External breathing surrogate traces of at least 5-min duration for 50 patients were used. Breathing trace amplitudes were converted to motion by relating the nominal tumor motion to the 90th percentile breathing amplitude, reflecting motion defined by the more recent 5DCT approach. Based on clinical low-pitch helical CT acquisition, the CT detector moved according to its velocity while the tumor moved according to the breathing trace. When the CT scanner overlapped the tumor, the overlapping slices were identified as having imaged the tumor. This process was repeated starting at successive 0.1 s time bin in the breathing trace until there was insufficient breathing trace to complete the simulation. The tumor size was subtracted from the distance between the most superior and inferior tumor positions to determine the measured tumor motion for that specific simulation. The effect of the scanning parameter variation was evaluated using two commercial 4DCT protocols with different pitch values. Because clinical 4DCT scan sessions would yield a single tumor motion displacement measurement for each patient, errors in the tumor motion measurement were considered systematic. The mean of largest 5% and smallest 5% of the measured motions was selected to identify over-and underdetermined motion amplitudes, respectively. The process was repeated for tumor motions of 1-4 cm in 1 cm increments and for tumor sizes of 1-4 cm in 1 cm increments. Results: In the examined patient cohort, simulation using pitch of 0.06 showed that 30% of the patients exhibited a 5% chance of mean breathing amplitude overestimations of 47%, while 30% showed a 5% chance of mean breathing amplitude underestimations of 36%; with a separate simulation using pitch of 0.1 showing, respectively, 37% overestimation and 61% underestimation. Conclusions: The simulation indicates that commercial low-pitch helical 4DCT processes potentially yield large tumor motion measurement errors, both over-and underestimating the tumor motion. C 2015 American Association of Physicists in Medicine. [http://dx

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A Novel Fast Helical 4D-CT Acquisition Technique to Generate Low-Noise Sorting Artifact–Free Images at User-Selected Breathing Phases

Cited by 55 publications

References 34 publications

Comparison of breathing gated CT images generated using a 5DCT technique and a commercial clinical protocol in a porcine model

Comparison of breathing gated CT images generated using a 5DCT technique and a commercial clinical protocol in a porcine model

A Method for Assessing Ground-Truth Accuracy of the 5DCT Technique

Technical Note: Simulation of 4DCT tumor motion measurement errors

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