Feasibility of artificial-intelligence-based synthetic computed tomography in a magnetic resonance-only radiotherapy workflow for brain radiotherapy: Two-way dose validation and 2D/2D kV-image-based positioning. (October 2022)
- Record Type:
- Journal Article
- Title:
- Feasibility of artificial-intelligence-based synthetic computed tomography in a magnetic resonance-only radiotherapy workflow for brain radiotherapy: Two-way dose validation and 2D/2D kV-image-based positioning. (October 2022)
- Main Title:
- Feasibility of artificial-intelligence-based synthetic computed tomography in a magnetic resonance-only radiotherapy workflow for brain radiotherapy: Two-way dose validation and 2D/2D kV-image-based positioning
- Authors:
- Masitho, Siti
Szkitsak, Juliane
Grigo, Johanna
Fietkau, Rainer
Putz, Florian
Bert, Christoph - Abstract:
- Abstract: Background and purpose: Magnetic Resonance Imaging (MRI)-only workflow eliminates the MRI-computed tomography (CT) registration inaccuracy, which degrades radiotherapy (RT) treatment accuracy. For an MRI-only workflow MRI sequences need to be converted to synthetic-CT (sCT). The purpose of this study was to evaluate a commercially available artificial intelligence (AI)-based sCT generation for dose calculation and 2D/2D kV-image daily positioning for brain RT workflow. Materials and methods: T1-VIBE DIXON was acquired at the 1.5 T MRI for 26 patients in RT setup for sCTs generation. For each patient, a volumetric modulated arc therapy (VMAT) plan was optimized on the CT, then recalculated on the sCT; and vice versa. sCT-based digitally reconstructed radiographs (DRRs) were fused with stereoscopic X-ray images recorded as image guidance for clinical treatments. Dosimetric differences between planned/recalculated doses and the differences between the calculated and recorded clinical couch shift/rotation were evaluated. Results: Mean ΔD50 between planned/recalculated doses for target volumes ranged between −0.2 % and 0.2 %; mean ΔD50 and ΔD0.01ccm were −0.6 % and 1.6 % and −1.4 % and 1.0 % for organ-at-risks, respectively. Differences were tested for clinical equivalence using intervals ±2 % (dose), ±1mm (translation), and ±1° (rotation). Dose equivalence was found using ±2 % interval ( p < 0.001). The median differences between lat./long./vert. couch shift betweenAbstract: Background and purpose: Magnetic Resonance Imaging (MRI)-only workflow eliminates the MRI-computed tomography (CT) registration inaccuracy, which degrades radiotherapy (RT) treatment accuracy. For an MRI-only workflow MRI sequences need to be converted to synthetic-CT (sCT). The purpose of this study was to evaluate a commercially available artificial intelligence (AI)-based sCT generation for dose calculation and 2D/2D kV-image daily positioning for brain RT workflow. Materials and methods: T1-VIBE DIXON was acquired at the 1.5 T MRI for 26 patients in RT setup for sCTs generation. For each patient, a volumetric modulated arc therapy (VMAT) plan was optimized on the CT, then recalculated on the sCT; and vice versa. sCT-based digitally reconstructed radiographs (DRRs) were fused with stereoscopic X-ray images recorded as image guidance for clinical treatments. Dosimetric differences between planned/recalculated doses and the differences between the calculated and recorded clinical couch shift/rotation were evaluated. Results: Mean ΔD50 between planned/recalculated doses for target volumes ranged between −0.2 % and 0.2 %; mean ΔD50 and ΔD0.01ccm were −0.6 % and 1.6 % and −1.4 % and 1.0 % for organ-at-risks, respectively. Differences were tested for clinical equivalence using intervals ±2 % (dose), ±1mm (translation), and ±1° (rotation). Dose equivalence was found using ±2 % interval ( p < 0.001). The median differences between lat./long./vert. couch shift between CT-based/sCT-based DRRs were 0.3 mm/0.2 mm/0.3 mm ( p < 0.05); median differences between lat./long./vert. couch rotation were −1.5°/0.1°/0.1° (after improvement of RT setup: −0.4°/−0.1°/−0.4°, p < 0.05). Conclusions: This in-silico study showed that the AI-based sCT provided equivalent results to the CT for dose calculation and daily stereoscopic X-ray positioning when using an optimal RT setup during MRI acquisition. … (more)
- Is Part Of:
- Physics and imaging in radiation oncology. Volume 24(2022)
- Journal:
- Physics and imaging in radiation oncology
- Issue:
- Volume 24(2022)
- Issue Display:
- Volume 24, Issue 2022 (2022)
- Year:
- 2022
- Volume:
- 24
- Issue:
- 2022
- Issue Sort Value:
- 2022-0024-2022-0000
- Page Start:
- 111
- Page End:
- 117
- Publication Date:
- 2022-10
- Subjects:
- Brain radiotherapy -- Synthetic CT -- MRI-only workflow -- Artificial intelligence -- kV-image-based positioning
Radiotherapy -- Periodicals
Radiation dosimetry -- Periodicals
Cancer -- Imaging -- Periodicals
Oncology -- Periodicals
615.842 - Journal URLs:
- http://www.sciencedirect.com/ ↗
https://www.journals.elsevier.com/physics-and-imaging-in-radiation-oncology/ ↗ - DOI:
- 10.1016/j.phro.2022.10.002 ↗
- Languages:
- English
- ISSNs:
- 2405-6316
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 24702.xml