AI-based automatic patient positioning in a digital-BGO PET/CT scanner: efficacy and impact
Abstract Background A recently released digital solid-state positron emission tomography/x-ray CT (PET/CT) scanner with bismuth germanate (BGO) scintillators provides an artificial intelligence (AI) based system for automatic patient positioning. The efficacy of this digital-BGO system in patient pl...
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SpringerOpen
2025-01-01
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| Series: | EJNMMI Physics |
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| Online Access: | https://doi.org/10.1186/s40658-025-00715-w |
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| author | John A. Kennedy Tala Palchan-Hazan Zohar Keidar |
| author_facet | John A. Kennedy Tala Palchan-Hazan Zohar Keidar |
| author_sort | John A. Kennedy |
| collection | DOAJ |
| description | Abstract Background A recently released digital solid-state positron emission tomography/x-ray CT (PET/CT) scanner with bismuth germanate (BGO) scintillators provides an artificial intelligence (AI) based system for automatic patient positioning. The efficacy of this digital-BGO system in patient placement at the isocenter and its impact on image quality and radiation exposure was evaluated. Method The digital-BGO PET/CT with AI-based auto-positioning was compared (χ2, Mann–Whitney tests) to a solid-state lutetium-yttrium oxyorthosilicate (digital-LYSO) PET/CT with manual patient positioning (n = 432 and 343 studies each, respectively), with results split into groups before and after the date of a recalibration of the digital-BGO auto-positioning camera. To measure the transverse displacement of the patient center from the scanner isocenter (off-centering), CT slices were retrospectively selected and automatically analyzed using in-house software. Noise was measured as the coefficient of variation within the liver of absolute Hounsfield units referenced to air. Radiation exposure was recorded as dose-length product (DLP). Off-centering measurements were validated by a phantom study. Results The phantom validation study gave < 1.6 mm error in 15 off-centering measurements. Patient off-centering was biased 1.92 ± 1.79 cm (mean ± standard deviation) in the posterior direction which was significantly different from the 0.22 ± 1.21 cm bias in the left lateral direction (p < 0.0001, Wilcoxon). After recalibration, 27% (38/140) of the studies had off-centering results > 2.5cm for the digital-BGO, which was significantly better than the 49% (143/292, p < 0.001) before recalibration and better than for the digital-LYSO: 54% (119/222, p < 0.001) before and 55% (66/121, p < 0.001) after. On average, CT image quality was superior for non-obese patients who were most closely aligned with the isocenter: noise increased by 3.2 ± 0.1% for every 1 cm increase in off-centering. DLP increased by 144 ± 22 Gy cm for every 1 cm increase in anterior off-centering. Conclusion AI-based automatic patient positioning in a digital-BGO PET/CT scanner significantly reduces patient off-centering, thereby improving image quality and ensuring proper radiation exposure. |
| format | Article |
| id | doaj-art-c0b7518feceb499bbb04437dee7dc8c7 |
| institution | Kabale University |
| issn | 2197-7364 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | EJNMMI Physics |
| spelling | doaj-art-c0b7518feceb499bbb04437dee7dc8c72025-01-26T12:53:08ZengSpringerOpenEJNMMI Physics2197-73642025-01-0112111310.1186/s40658-025-00715-wAI-based automatic patient positioning in a digital-BGO PET/CT scanner: efficacy and impactJohn A. Kennedy0Tala Palchan-Hazan1Zohar Keidar2Department of Nuclear Medicine, Rambam Health Care CampusDepartment of Nuclear Medicine, Rambam Health Care CampusDepartment of Nuclear Medicine, Rambam Health Care CampusAbstract Background A recently released digital solid-state positron emission tomography/x-ray CT (PET/CT) scanner with bismuth germanate (BGO) scintillators provides an artificial intelligence (AI) based system for automatic patient positioning. The efficacy of this digital-BGO system in patient placement at the isocenter and its impact on image quality and radiation exposure was evaluated. Method The digital-BGO PET/CT with AI-based auto-positioning was compared (χ2, Mann–Whitney tests) to a solid-state lutetium-yttrium oxyorthosilicate (digital-LYSO) PET/CT with manual patient positioning (n = 432 and 343 studies each, respectively), with results split into groups before and after the date of a recalibration of the digital-BGO auto-positioning camera. To measure the transverse displacement of the patient center from the scanner isocenter (off-centering), CT slices were retrospectively selected and automatically analyzed using in-house software. Noise was measured as the coefficient of variation within the liver of absolute Hounsfield units referenced to air. Radiation exposure was recorded as dose-length product (DLP). Off-centering measurements were validated by a phantom study. Results The phantom validation study gave < 1.6 mm error in 15 off-centering measurements. Patient off-centering was biased 1.92 ± 1.79 cm (mean ± standard deviation) in the posterior direction which was significantly different from the 0.22 ± 1.21 cm bias in the left lateral direction (p < 0.0001, Wilcoxon). After recalibration, 27% (38/140) of the studies had off-centering results > 2.5cm for the digital-BGO, which was significantly better than the 49% (143/292, p < 0.001) before recalibration and better than for the digital-LYSO: 54% (119/222, p < 0.001) before and 55% (66/121, p < 0.001) after. On average, CT image quality was superior for non-obese patients who were most closely aligned with the isocenter: noise increased by 3.2 ± 0.1% for every 1 cm increase in off-centering. DLP increased by 144 ± 22 Gy cm for every 1 cm increase in anterior off-centering. Conclusion AI-based automatic patient positioning in a digital-BGO PET/CT scanner significantly reduces patient off-centering, thereby improving image quality and ensuring proper radiation exposure.https://doi.org/10.1186/s40658-025-00715-wPET/CTPatient off-centeringImage qualityRadiation exposure |
| spellingShingle | John A. Kennedy Tala Palchan-Hazan Zohar Keidar AI-based automatic patient positioning in a digital-BGO PET/CT scanner: efficacy and impact EJNMMI Physics PET/CT Patient off-centering Image quality Radiation exposure |
| title | AI-based automatic patient positioning in a digital-BGO PET/CT scanner: efficacy and impact |
| title_full | AI-based automatic patient positioning in a digital-BGO PET/CT scanner: efficacy and impact |
| title_fullStr | AI-based automatic patient positioning in a digital-BGO PET/CT scanner: efficacy and impact |
| title_full_unstemmed | AI-based automatic patient positioning in a digital-BGO PET/CT scanner: efficacy and impact |
| title_short | AI-based automatic patient positioning in a digital-BGO PET/CT scanner: efficacy and impact |
| title_sort | ai based automatic patient positioning in a digital bgo pet ct scanner efficacy and impact |
| topic | PET/CT Patient off-centering Image quality Radiation exposure |
| url | https://doi.org/10.1186/s40658-025-00715-w |
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