A tomographic reconstruction algorithm for cross-sectional imaging of IMRT beams from six projections Article Swipe
Odran Pivot
,
Patrick Pittet
,
Rolf Clackdoyle
,
Laurent Desbat
,
Simon Rit
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1088/1361-6560/acc925
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1088/1361-6560/acc925
Objective . Patient-specific Quality Assurance (QA) measurements are of key importance in radiotherapy for safe and efficient treatment delivery and allow early detection of clinically relevant errors. Such QA processes remain challenging to implement for complex Intensity Modulated Radiation Therapy (IMRT) radiotherapy fields delivered using a multileaf collimator (MLC) which often feature small open segments and raise QA issues similar to those encountered in small field dosimetry. Recently, detectors based on long scintillating fibers have been proposed to measure a few parallel projections of the irradiation field with good performance for small field dosimetry. The purpose of this work is to develop and validate a novel approach to reconstruct MLC-shaped small irradiation fields from six projections. Approach . The proposed field reconstruction method uses a limited number of geometric parameters to model the irradiation field. These parameters are iteratively estimated with a steepest descent algorithm. The reconstruction method was first validated on simulated data. Real data were measured with a water-equivalent slab phantom equipped with a detector made of 6 scintillating-fiber ribbons placed at 1 m from the source. A radiochromic film was used to acquire a reference measurement of a first dose distribution in the slab phantom at the same source-to-detector distance and the treatment planning system (TPS) provided the reference for another dose distribution. In addition, simulated errors introduced on the delivered dose, field location and field shape were used to evaluate the ability of the proposed method to efficiently identify a deviation between the planned and delivered treatments. Main results . For a first small IMRT segment, 3%/3 mm, 2%/2 mm and 2%/1 mm gamma analysis conducted between the reconstructed dose distribution and the dose measured with radiochromic film exhibited pass rates of 100%, 99.9% and 95.7%, respectively. For a second and smaller IMRT segment, the same gamma analysis performed between the reconstructed dose distribution and the reference provided by the TPS showed pass rates of 100%, 99.4% and 92.6% for the 3%/3 mm, 2%/2 mm and 2%/1 mm gamma criteria, respectively. Gamma analysis of the simulated treatment delivery errors showed the ability of the reconstruction algorithm to detect a 3% deviation between the planned and delivered doses, as well as shifts lower than 7 mm and 3 mm when considering an individual leaf and a whole field shift, respectively. Significance . The proposed method allows accurate tomographic reconstruction of IMRT segments by processing projections measured with six scintillating-fiber ribbons and is suitable for water-equivalent real-time small IMRT segments QA.
Related Topics
Concepts
Multileaf collimator
Imaging phantom
Quality assurance
Dosimetry
Detector
Collimator
Computer science
Radiation treatment planning
Algorithm
Reconstruction algorithm
Nuclear medicine
Medical physics
Artificial intelligence
Optics
Iterative reconstruction
Physics
Beam (structure)
Radiation therapy
Linear particle accelerator
Medicine
External quality assessment
Internal medicine
Pathology
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1088/1361-6560/acc925
- OA Status
- hybrid
- Cited By
- 1
- References
- 34
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4361247630
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4361247630Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1088/1361-6560/acc925Digital Object Identifier
- Title
-
A tomographic reconstruction algorithm for cross-sectional imaging of IMRT beams from six projectionsWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2023Year of publication
- Publication date
-
2023-03-30Full publication date if available
- Authors
-
Odran Pivot, Patrick Pittet, Rolf Clackdoyle, Laurent Desbat, Simon RitList of authors in order
- Landing page
-
https://doi.org/10.1088/1361-6560/acc925Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
hybridOpen access status per OpenAlex
- OA URL
-
https://doi.org/10.1088/1361-6560/acc925Direct OA link when available
- Concepts
-
Multileaf collimator, Imaging phantom, Quality assurance, Dosimetry, Detector, Collimator, Computer science, Radiation treatment planning, Algorithm, Reconstruction algorithm, Nuclear medicine, Medical physics, Artificial intelligence, Optics, Iterative reconstruction, Physics, Beam (structure), Radiation therapy, Linear particle accelerator, Medicine, External quality assessment, Internal medicine, PathologyTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
1Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 1Per-year citation counts (last 5 years)
- References (count)
-
34Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.delivered | 44, 224, 250, 360 |
| abstract_inverted_index.detection | 23 |
| abstract_inverted_index.detectors | 69 |
| abstract_inverted_index.deviation | 245, 355 |
| abstract_inverted_index.efficient | 17 |
| abstract_inverted_index.estimated | 140 |
| abstract_inverted_index.exhibited | 283 |
| abstract_inverted_index.geometric | 129 |
| abstract_inverted_index.implement | 34 |
| abstract_inverted_index.multileaf | 47 |
| abstract_inverted_index.performed | 303 |
| abstract_inverted_index.processes | 30 |
| abstract_inverted_index.real-time | 409 |
| abstract_inverted_index.reference | 188, 212, 311 |
| abstract_inverted_index.simulated | 153, 219, 340 |
| abstract_inverted_index.treatment | 18, 206, 341 |
| abstract_inverted_index.validated | 151 |
| abstract_inverted_index.MLC-shaped | 110 |
| abstract_inverted_index.algorithm. | 145 |
| abstract_inverted_index.clinically | 25 |
| abstract_inverted_index.collimator | 48 |
| abstract_inverted_index.dosimetry. | 67, 94 |
| abstract_inverted_index.importance | 11 |
| abstract_inverted_index.individual | 376 |
| abstract_inverted_index.introduced | 221 |
| abstract_inverted_index.parameters | 130, 137 |
| abstract_inverted_index.processing | 397 |
| abstract_inverted_index.challenging | 32 |
| abstract_inverted_index.considering | 374 |
| abstract_inverted_index.efficiently | 242 |
| abstract_inverted_index.encountered | 63 |
| abstract_inverted_index.irradiation | 86, 112, 134 |
| abstract_inverted_index.iteratively | 139 |
| abstract_inverted_index.measurement | 189 |
| abstract_inverted_index.performance | 90 |
| abstract_inverted_index.projections | 83, 398 |
| abstract_inverted_index.reconstruct | 109 |
| abstract_inverted_index.tomographic | 391 |
| abstract_inverted_index.treatments. | 251 |
| abstract_inverted_index.Significance | 384 |
| abstract_inverted_index.distribution | 194, 275, 308 |
| abstract_inverted_index.measurements | 7 |
| abstract_inverted_index.projections. | 116 |
| abstract_inverted_index.radiochromic | 181, 281 |
| abstract_inverted_index.radiotherapy | 13, 42 |
| abstract_inverted_index.distribution. | 216 |
| abstract_inverted_index.reconstructed | 273, 306 |
| abstract_inverted_index.respectively. | 291, 335, 383 |
| abstract_inverted_index.scintillating | 73 |
| abstract_inverted_index.reconstruction | 122, 147, 349, 392 |
| abstract_inverted_index.Patient-specific | 3 |
| abstract_inverted_index.water-equivalent | 161, 408 |
| abstract_inverted_index.source-to-detector | 202 |
| abstract_inverted_index.scintillating-fiber | 171, 402 |
| cited_by_percentile_year.max | 95 |
| cited_by_percentile_year.min | 91 |
| corresponding_author_ids | https://openalex.org/A5009944691 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 5 |
| corresponding_institution_ids | https://openalex.org/I899635006 |
| citation_normalized_percentile.value | 0.58954663 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |