Long-term performance evaluation of a 1.5T MR-Linac using statistical process control techniques Article Swipe
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· 2025
· Open Access
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· DOI: https://doi.org/10.1186/s13014-025-02670-3
Background The integration of magnetic resonance imaging with linear accelerators (Linacs) enhances adaptive radiotherapy by providing real-time imaging for improved treatment precision. However, the long-term performance of MR-Linac systems, particularly in clinical settings, remains insufficiently studied. Traditional quality assurance (QA) methods, relying on binary pass/fail criteria, may overlook critical system variations. This study applies statistical process control (SPC) techniques to evaluate the long-term performance of a 1.5T MR-Linac, focusing on optimization in beam quality, MR-to-MV alignment, MR imaging, and geometric distortion. Methods A dual-phase SPC framework was applied to 1 year of daily and weekly QA data from an Elekta Unity MR-Linac. Phase I established performance benchmarks, while Phase II monitored deviations online. Evaluated parameters included beam output, symmetry, MR-to-MV alignment, signal-to-noise ratio (SNR), spatial linearity, slice profile, and geometric distortion across spherical volumes (DSVs). Stability and variability were quantified using control charts and process performance indices (Ppk). Results Beam quality was stable overall (Ppk ≥ 1.33), though output dose and transverse symmetry showed increased variability in Phase II, with dose Ppk declining from 3.13 to 1.33. MR-to-MV alignment was consistent, but Phi rotational and Z translational offsets showed variability after system upgrades. Imaging metrics, including SNR and spatial linearity, achieved A + performance (Ppk ≥ 1.67) in Phase II, while vertical spatial resolution was lower (Ppk 1.04–1.10). Geometric distortion was well-controlled, though larger DSVs (≥ 500 mm) showed increased AP-axis distortion (2.44 mm) compared to RL (1.37 mm) and FH (0.93 mm). Conclusions SPC techniques dynamically identified stable parameters and areas for improvement. Key recommendations include enhanced alignment protocols for beam quality and MR-to-MV offsets, as well as targeted strategies to address geometric distortion in larger volumes and along the AP axis.
Related Topics
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1186/s13014-025-02670-3
- https://ro-journal.biomedcentral.com/counter/pdf/10.1186/s13014-025-02670-3
- OA Status
- gold
- References
- 34
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4411118273
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4411118273Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1186/s13014-025-02670-3Digital Object Identifier
- Title
-
Long-term performance evaluation of a 1.5T MR-Linac using statistical process control techniquesWork title
- Type
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articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2025Year of publication
- Publication date
-
2025-06-07Full publication date if available
- Authors
-
Qing Xiao, Mengdie Shen, Guangjun Li, Simeng Zhu, J. He, Qiang Wang, Guyu Dai, Hang Yu, Jialu Lai, Renming Zhong, Sen BaiList of authors in order
- Landing page
-
https://doi.org/10.1186/s13014-025-02670-3Publisher landing page
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https://ro-journal.biomedcentral.com/counter/pdf/10.1186/s13014-025-02670-3Direct link to full text PDF
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://ro-journal.biomedcentral.com/counter/pdf/10.1186/s13014-025-02670-3Direct OA link when available
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Quality assurance, Linear particle accelerator, Medicine, Distortion (music), Linearity, Nuclear medicine, Medical physics, Beam (structure), Optics, Physics, Computer science, Telecommunications, Bandwidth (computing), External quality assessment, Amplifier, Quantum mechanics, PathologyTop concepts (fields/topics) attached by OpenAlex
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0Total citation count in OpenAlex
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34Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.A | 83, 202 |
| abstract_inverted_index.I | 104 |
| abstract_inverted_index.Z | 186 |
| abstract_inverted_index.a | 66 |
| abstract_inverted_index.AP | 282 |
| abstract_inverted_index.FH | 241 |
| abstract_inverted_index.II | 110 |
| abstract_inverted_index.MR | 77 |
| abstract_inverted_index.QA | 96 |
| abstract_inverted_index.RL | 237 |
| abstract_inverted_index.an | 99 |
| abstract_inverted_index.as | 267, 269 |
| abstract_inverted_index.by | 15 |
| abstract_inverted_index.in | 31, 72, 167, 208, 276 |
| abstract_inverted_index.of | 4, 27, 65, 92 |
| abstract_inverted_index.on | 43, 70 |
| abstract_inverted_index.to | 60, 89, 176, 236, 272 |
| abstract_inverted_index.500 | 227 |
| abstract_inverted_index.II, | 169, 210 |
| abstract_inverted_index.Key | 255 |
| abstract_inverted_index.Phi | 183 |
| abstract_inverted_index.Ppk | 172 |
| abstract_inverted_index.SNR | 197 |
| abstract_inverted_index.SPC | 85, 245 |
| abstract_inverted_index.The | 2 |
| abstract_inverted_index.and | 79, 94, 129, 137, 144, 161, 185, 198, 240, 251, 264, 279 |
| abstract_inverted_index.but | 182 |
| abstract_inverted_index.for | 19, 253, 261 |
| abstract_inverted_index.may | 47 |
| abstract_inverted_index.mm) | 228, 234, 239 |
| abstract_inverted_index.the | 24, 62, 281 |
| abstract_inverted_index.was | 87, 152, 180, 215, 221 |
| abstract_inverted_index.≥ | 156, 206 |
| abstract_inverted_index.(Ppk | 155, 205, 217 |
| abstract_inverted_index.(QA) | 40 |
| abstract_inverted_index.(≥ | 226 |
| abstract_inverted_index.1.5T | 67 |
| abstract_inverted_index.3.13 | 175 |
| abstract_inverted_index.Beam | 150 |
| abstract_inverted_index.DSVs | 225 |
| abstract_inverted_index.This | 52 |
| abstract_inverted_index.beam | 73, 117, 262 |
| abstract_inverted_index.data | 97 |
| abstract_inverted_index.dose | 160, 171 |
| abstract_inverted_index.from | 98, 174 |
| abstract_inverted_index.mm). | 243 |
| abstract_inverted_index.well | 268 |
| abstract_inverted_index.were | 139 |
| abstract_inverted_index.with | 8, 170 |
| abstract_inverted_index.year | 91 |
| abstract_inverted_index.(0.93 | 242 |
| abstract_inverted_index.(1.37 | 238 |
| abstract_inverted_index.(2.44 | 233 |
| abstract_inverted_index.(SPC) | 58 |
| abstract_inverted_index.1.33. | 177 |
| abstract_inverted_index.1.67) | 207 |
| abstract_inverted_index.Phase | 103, 109, 168, 209 |
| abstract_inverted_index.Unity | 101 |
| abstract_inverted_index.after | 191 |
| abstract_inverted_index.along | 280 |
| abstract_inverted_index.areas | 252 |
| abstract_inverted_index.axis. | 283 |
| abstract_inverted_index.daily | 93 |
| abstract_inverted_index.lower | 216 |
| abstract_inverted_index.ratio | 123 |
| abstract_inverted_index.slice | 127 |
| abstract_inverted_index.study | 53 |
| abstract_inverted_index.using | 141 |
| abstract_inverted_index.while | 108, 211 |
| abstract_inverted_index.(Ppk). | 148 |
| abstract_inverted_index.(SNR), | 124 |
| abstract_inverted_index.1.33), | 157 |
| abstract_inverted_index.Elekta | 100 |
| abstract_inverted_index.across | 132 |
| abstract_inverted_index.binary | 44 |
| abstract_inverted_index.charts | 143 |
| abstract_inverted_index.larger | 224, 277 |
| abstract_inverted_index.linear | 9 |
| abstract_inverted_index.output | 159 |
| abstract_inverted_index.showed | 164, 189, 229 |
| abstract_inverted_index.stable | 153, 249 |
| abstract_inverted_index.system | 50, 192 |
| abstract_inverted_index.though | 158, 223 |
| abstract_inverted_index.weekly | 95 |
| abstract_inverted_index.(DSVs). | 135 |
| abstract_inverted_index.AP-axis | 231 |
| abstract_inverted_index.Imaging | 194 |
| abstract_inverted_index.Methods | 82 |
| abstract_inverted_index.Results | 149 |
| abstract_inverted_index.address | 273 |
| abstract_inverted_index.applied | 88 |
| abstract_inverted_index.applies | 54 |
| abstract_inverted_index.control | 57, 142 |
| abstract_inverted_index.imaging | 7, 18 |
| abstract_inverted_index.include | 257 |
| abstract_inverted_index.indices | 147 |
| abstract_inverted_index.offsets | 188 |
| abstract_inverted_index.online. | 113 |
| abstract_inverted_index.output, | 118 |
| abstract_inverted_index.overall | 154 |
| abstract_inverted_index.process | 56, 145 |
| abstract_inverted_index.quality | 38, 151, 263 |
| abstract_inverted_index.relying | 42 |
| abstract_inverted_index.remains | 34 |
| abstract_inverted_index.spatial | 125, 199, 213 |
| abstract_inverted_index.volumes | 134, 278 |
| abstract_inverted_index.(Linacs) | 11 |
| abstract_inverted_index.Abstract | 0 |
| abstract_inverted_index.However, | 23 |
| abstract_inverted_index.MR-Linac | 28 |
| abstract_inverted_index.MR-to-MV | 75, 120, 178, 265 |
| abstract_inverted_index.achieved | 201 |
| abstract_inverted_index.adaptive | 13 |
| abstract_inverted_index.clinical | 32 |
| abstract_inverted_index.compared | 235 |
| abstract_inverted_index.critical | 49 |
| abstract_inverted_index.enhanced | 258 |
| abstract_inverted_index.enhances | 12 |
| abstract_inverted_index.evaluate | 61 |
| abstract_inverted_index.focusing | 69 |
| abstract_inverted_index.imaging, | 78 |
| abstract_inverted_index.improved | 20 |
| abstract_inverted_index.included | 116 |
| abstract_inverted_index.magnetic | 5 |
| abstract_inverted_index.methods, | 41 |
| abstract_inverted_index.metrics, | 195 |
| abstract_inverted_index.offsets, | 266 |
| abstract_inverted_index.overlook | 48 |
| abstract_inverted_index.profile, | 128 |
| abstract_inverted_index.quality, | 74 |
| abstract_inverted_index.studied. | 36 |
| abstract_inverted_index.symmetry | 163 |
| abstract_inverted_index.systems, | 29 |
| abstract_inverted_index.targeted | 270 |
| abstract_inverted_index.vertical | 212 |
| abstract_inverted_index.Evaluated | 114 |
| abstract_inverted_index.Geometric | 219 |
| abstract_inverted_index.MR-Linac, | 68 |
| abstract_inverted_index.MR-Linac. | 102 |
| abstract_inverted_index.Stability | 136 |
| abstract_inverted_index.alignment | 179, 259 |
| abstract_inverted_index.assurance | 39 |
| abstract_inverted_index.criteria, | 46 |
| abstract_inverted_index.declining | 173 |
| abstract_inverted_index.framework | 86 |
| abstract_inverted_index.geometric | 80, 130, 274 |
| abstract_inverted_index.including | 196 |
| abstract_inverted_index.increased | 165, 230 |
| abstract_inverted_index.long-term | 25, 63 |
| abstract_inverted_index.monitored | 111 |
| abstract_inverted_index.pass/fail | 45 |
| abstract_inverted_index.protocols | 260 |
| abstract_inverted_index.providing | 16 |
| abstract_inverted_index.real-time | 17 |
| abstract_inverted_index.resonance | 6 |
| abstract_inverted_index.settings, | 33 |
| abstract_inverted_index.spherical | 133 |
| abstract_inverted_index.symmetry, | 119 |
| abstract_inverted_index.treatment | 21 |
| abstract_inverted_index.upgrades. | 193 |
| abstract_inverted_index.Background | 1 |
| abstract_inverted_index.alignment, | 76, 121 |
| abstract_inverted_index.deviations | 112 |
| abstract_inverted_index.distortion | 131, 220, 232, 275 |
| abstract_inverted_index.dual-phase | 84 |
| abstract_inverted_index.identified | 248 |
| abstract_inverted_index.linearity, | 126, 200 |
| abstract_inverted_index.parameters | 115, 250 |
| abstract_inverted_index.precision. | 22 |
| abstract_inverted_index.quantified | 140 |
| abstract_inverted_index.resolution | 214 |
| abstract_inverted_index.rotational | 184 |
| abstract_inverted_index.strategies | 271 |
| abstract_inverted_index.techniques | 59, 246 |
| abstract_inverted_index.transverse | 162 |
| abstract_inverted_index.Conclusions | 244 |
| abstract_inverted_index.Traditional | 37 |
| abstract_inverted_index.benchmarks, | 107 |
| abstract_inverted_index.consistent, | 181 |
| abstract_inverted_index.distortion. | 81 |
| abstract_inverted_index.dynamically | 247 |
| abstract_inverted_index.established | 105 |
| abstract_inverted_index.integration | 3 |
| abstract_inverted_index.performance | 26, 64, 106, 146, 204 |
| abstract_inverted_index.statistical | 55 |
| abstract_inverted_index.variability | 138, 166, 190 |
| abstract_inverted_index.variations. | 51 |
| abstract_inverted_index.accelerators | 10 |
| abstract_inverted_index.improvement. | 254 |
| abstract_inverted_index.optimization | 71 |
| abstract_inverted_index.particularly | 30 |
| abstract_inverted_index.radiotherapy | 14 |
| abstract_inverted_index.1.04–1.10). | 218 |
| abstract_inverted_index.translational | 187 |
| abstract_inverted_index.insufficiently | 35 |
| abstract_inverted_index.recommendations | 256 |
| abstract_inverted_index.signal-to-noise | 122 |
| abstract_inverted_index.well-controlled, | 222 |
| cited_by_percentile_year | |
| countries_distinct_count | 1 |
| institutions_distinct_count | 11 |
| citation_normalized_percentile.value | 0.28574309 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |