MétaCan
Menu
Back to cohort
Record W4308682682 · doi:10.1002/acm2.13826

System‐dependent image distortion related to gantry positions of a 0.35 T MRgRT: Characterization and the corresponding correction

2022· article· en· W4308682682 on OpenAlexaff
Shanti Marasini, Benjamin Quinn, Mike Cole, Rocco Flores, Taeho Kim

Bibliographic record

VenueJournal of Applied Clinical Medical Physics · 2022
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Radiotherapy Techniques
Canadian institutionsMarch of Dimes Canada
FundersNational Cancer Institute
KeywordsIsocenterImaging phantomDistortion (music)Medical imagingImage-guided radiation therapyComputer scienceNuclear medicinePhysicsArtificial intelligenceComputer visionOpticsMedicine

Abstract

fetched live from OpenAlex

Abstract Purpose MR‐guided radiotherapy with high accuracy treatment planning requires addressing MR imaging artifacts that originate from system imperfections. This work presents the characterization and corresponding correction of gantry‐related imaging distortions including geometric distortion and isocenter shift in a 0.35 T magnetic resonance imaging (MRI)‐guided radiotherapy (MRgRT) system using distortion vector fields (DVFs). Methods Two phantoms, the magnetic resonance imaging distortion in 3D (MRID 3D ) phantom and the Fluke phantom, along with a human volunteer were imaged at different gantry angles on a 0.35 T MR‐Linac. The geometric distortion and isocenter shift were characterized for both phantom images. DVFs with a field of view extended beyond the physical boundary of the MRID 3D phantom were extracted from images taken at 30° gantry angle increments, with vendor‐provided distortion correction turned on and off (DstOff). These extended DVFs were then applied to the relevant phantom images to correct their geometric distortions and isocenter shift at the respective gantry angles. The extended DVFs produced from the MRID 3D phantom were also applied to Fluke phantom and human MR images at their respective gantry angles. The resampled images were evaluated using structural similarity index measure (SSIM) comparison with the vendor corrected images from the MRgRT system. Results Geometric distortion with “mean (± SD) distortion” of 3.2 ± 0.02, 2.9 ± 0.02, and 1.8 ± 0.01 mm and isocenter shift (±SD) of 0.49 ± 0.3, 0.05 ± 0.2, and 0.01 ± 0.03 mm were present in the DstOff MRID 3D phantom images in right–left (RL), anterior–posterior (AP), and superior–inferior (SI) directions, respectively. After resampling the originally acquired images by applying extended DVFs, the distortion was corrected to 0.18 ± 0.02, 0.09 ± 0.01, 0.15 ± 0.01 mm, and isocenter shift was corrected to 0.14 ± 0.05, −0.02 ± 0.04, and −0.07 ± 0.05 mm in RL, AP, and SI directions, respectively. The Fluke phantom average geometric distortion with “mean (± SD) distortion” of 2.7 ± 0.1 mm was corrected to 0.2 ± 0. 1 mm and the average isocenter shift (± SD) of 0.51 ± 0.2 mm, and 0.05 ± 0.03 was corrected to −0.08 ± 0.03 mm, and −0.05 ± 0.01 in RL and AP directions, respectively. SSIM (mean ± SD) of the original images to resampled images was increased from 0.49 ± 0.02 to 0.78 ± 0.01, 0.45 ± 0.02 to 0.75 ± 0.01, and 0.86 ± 0.25 to 0.98 ± 0.08 for MRID 3D phantom, Fluke phantom, and human MR images, respectively, for all the gantry angles compared to the vendor corrected images. Conclusion The gantry‐related MR imaging distortion including geometric distortion and isocenter shift was characterized and a corresponding correction was demonstrated using extended DVFs on 0.35 T MRgRT system. The characterized gantry‐related isocenter shift can be combined with geometric distortion correction to provide a technique for the correction of the full system‐dependent distortion in an MRgRT system.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.752
Threshold uncertainty score0.328

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.007
GPT teacher head0.306
Teacher spread0.299 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations6
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Applied Clinical Medical PhysicsSame topicAdvanced Radiotherapy TechniquesFrench-language works237,207