Literature DB >> 29861348

Using synthetic CT for partial brain radiation therapy: Impact on image guidance.

Eric D Morris1, Ryan G Price2, Joshua Kim3, Lonni Schultz4, M Salim Siddiqui3, Indrin Chetty1, Carri Glide-Hurst5.   

Abstract

PURPOSE: Recent advancements in synthetic computed tomography (synCT) from magnetic resonance (MR) imaging data have made MRI-only treatment planning feasible in the brain, although synCT performance for image guided radiation therapy (IGRT) is not well understood. This work compares geometric equivalence of digitally reconstructed radiographs (DRRs) from CTs and synCTs for brain cancer patients and quantifies performance for partial brain IGRT. METHODS AND MATERIALS: Ten brain cancer patients (12 lesions, 7 postsurgical) underwent MR-SIM and CT-SIM. SynCTs were generated by combining ultra-short echo time, T1, T2, and fluid attenuation inversion recovery datasets using voxel-based weighted summation. SynCT and CT DRRs were compared using patient-specific thresholding and assessed via overlap index, Dice similarity coefficient, and Jaccard index. Planar IGRT images for 22 fractions were evaluated to quantify differences between CT-generated DRRs and synCT-generated DRRs in 6 quadrants. Previously validated software was implemented to perform 2-dimensional (2D)-2D rigid registrations using normalized mutual information. Absolute (planar image/DRR registration) and relative (differences between synCT and CT DRR registrations) shifts were calculated for each axis and 3-dimensional vector difference. A total of 1490 rigid registrations were assessed.
RESULTS: DRR agreements in anteroposterior and lateral views for overlap index, Dice similarity coefficient, and Jaccard index were >0.95. Normalized mutual information results were equivalent in 75% of quadrants. Rotational registration results were negligible (<0.07°). Statistically significant differences between CT and synCT registrations were observed in 9/18 matched quadrants/axes (P < .05). The population average absolute shifts were 0.77 ± 0.58 and 0.76 ± 0.59 mm for CT and synCT, respectively, for all axes/quadrants. Three-dimensional vectors were <2 mm in 77.7 ± 10.8% and 76.5 ± 7.2% of CT and synCT registrations, respectively. SynCT DRRs were sensitive in postsurgical cases (vector displacements >2 mm in affected quadrants).
CONCLUSIONS: DRR synCT geometry was robust. Although statistically significant differences were observed between CT and synCT registrations, results were not clinically significant. Future work will address synCT generation in postsurgical settings.
Copyright © 2018 American Society for Radiation Oncology. Published by Elsevier Inc. All rights reserved.

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Year:  2018        PMID: 29861348      PMCID: PMC6123249          DOI: 10.1016/j.prro.2018.04.001

Source DB:  PubMed          Journal:  Pract Radiat Oncol        ISSN: 1879-8500


  30 in total

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Journal:  J Clin Oncol       Date:  2006-12-20       Impact factor: 44.544

4.  Evaluation of similarity measures for use in the intensity-based rigid 2D-3D registration for patient positioning in radiotherapy.

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5.  Registration of 2D x-ray images to 3D MRI by generating pseudo-CT data.

Authors:  M J van der Bom; J P W Pluim; M J Gounis; E B van de Kraats; S M Sprinkhuizen; J Timmer; R Homan; L W Bartels
Journal:  Phys Med Biol       Date:  2011-01-21       Impact factor: 3.609

6.  The intraclass correlation coefficient as a measure of reliability.

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7.  Dosimetric characterization of MRI-only treatment planning for brain tumors in atlas-based pseudo-CT images generated from standard T1-weighted MR images.

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Review 8.  Target definition in prostate, head, and neck.

Authors:  Coen Rasch; Roel Steenbakkers; Marcel van Herk
Journal:  Semin Radiat Oncol       Date:  2005-07       Impact factor: 5.934

9.  Using networks to measure similarity between genes: association index selection.

Authors:  Juan I Fuxman Bass; Alos Diallo; Justin Nelson; Juan M Soto; Chad L Myers; Albertha J M Walhout
Journal:  Nat Methods       Date:  2013-12       Impact factor: 28.547

10.  Validation for 2D/3D registration. I: A new gold standard data set.

Authors:  S A Pawiro; P Markelj; F Pernus; C Gendrin; M Figl; C Weber; F Kainberger; I Nöbauer-Huhmann; H Bergmeister; M Stock; D Georg; H Bergmann; W Birkfellner
Journal:  Med Phys       Date:  2011-03       Impact factor: 4.071

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  3 in total

1.  Artificial Intelligence in Radiation Therapy.

Authors:  Yabo Fu; Hao Zhang; Eric D Morris; Carri K Glide-Hurst; Suraj Pai; Alberto Traverso; Leonard Wee; Ibrahim Hadzic; Per-Ivar Lønne; Chenyang Shen; Tian Liu; Xiaofeng Yang
Journal:  IEEE Trans Radiat Plasma Med Sci       Date:  2021-08-24

Review 2.  "Après Mois, Le Déluge": Preparing for the Coming Data Flood in the MRI-Guided Radiotherapy Era.

Authors:  Kendall J Kiser; Benjamin D Smith; Jihong Wang; Clifton D Fuller
Journal:  Front Oncol       Date:  2019-09-30       Impact factor: 6.244

3.  Performance of deep learning synthetic CTs for MR-only brain radiation therapy.

Authors:  Xiaoning Liu; Hajar Emami; Siamak P Nejad-Davarani; Eric Morris; Lonni Schultz; Ming Dong; Carri K Glide-Hurst
Journal:  J Appl Clin Med Phys       Date:  2021-01-07       Impact factor: 2.102

  3 in total

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