Yujin Eom, Yong-Jin Park, Sumin Lee, Su-Jin Lee, Young-Sil An, Bok-Nam Park, Joon-Kee Yoon
{"title":"18f -氟脱氧葡萄糖正电子发射断层扫描/计算机断层扫描自动测量有效辐射剂量。","authors":"Yujin Eom, Yong-Jin Park, Sumin Lee, Su-Jin Lee, Young-Sil An, Bok-Nam Park, Joon-Kee Yoon","doi":"10.3390/tomography10120151","DOIUrl":null,"url":null,"abstract":"<p><strong>Background/objectives: </strong>Calculating the radiation dose from CT in <sup>18</sup>F-PET/CT examinations poses a significant challenge. The objective of this study is to develop a deep learning-based automated program that standardizes the measurement of radiation doses.</p><p><strong>Methods: </strong>The torso CT was segmented into six distinct regions using TotalSegmentator. An automated program was employed to extract the necessary information and calculate the effective dose (ED) of PET/CT. The accuracy of our automated program was verified by comparing the EDs calculated by the program with those determined by a nuclear medicine physician (n = 30). Additionally, we compared the EDs obtained from an older PET/CT scanner with those from a newer PET/CT scanner (n = 42).</p><p><strong>Results: </strong>The CT ED calculated by the automated program was not significantly different from that calculated by the nuclear medicine physician (3.67 ± 0.61 mSv and 3.62 ± 0.60 mSv, respectively, <i>p</i> = 0.7623). Similarly, the total ED showed no significant difference between the two calculation methods (8.10 ± 1.40 mSv and 8.05 ± 1.39 mSv, respectively, <i>p</i> = 0.8957). A very strong correlation was observed in both the CT ED and total ED between the two measurements (r<sup>2</sup> = 0.9981 and 0.9996, respectively). The automated program showed excellent repeatability and reproducibility. When comparing the older and newer PET/CT scanners, the PET ED was significantly lower in the newer scanner than in the older scanner (4.39 ± 0.91 mSv and 6.00 ± 1.17 mSv, respectively, <i>p</i> < 0.0001). Consequently, the total ED was significantly lower in the newer scanner than in the older scanner (8.22 ± 1.53 mSv and 9.65 ± 1.34 mSv, respectively, <i>p</i> < 0.0001).</p><p><strong>Conclusions: </strong>We successfully developed an automated program for calculating the ED of torso <sup>18</sup>F-PET/CT. By integrating a deep learning model, the program effectively eliminated inter-operator variability.</p>","PeriodicalId":51330,"journal":{"name":"Tomography","volume":"10 12","pages":"2144-2157"},"PeriodicalIF":2.2000,"publicationDate":"2024-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11679132/pdf/","citationCount":"0","resultStr":"{\"title\":\"Automated Measurement of Effective Radiation Dose by <sup>18</sup>F-Fluorodeoxyglucose Positron Emission Tomography/Computed Tomography.\",\"authors\":\"Yujin Eom, Yong-Jin Park, Sumin Lee, Su-Jin Lee, Young-Sil An, Bok-Nam Park, Joon-Kee Yoon\",\"doi\":\"10.3390/tomography10120151\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background/objectives: </strong>Calculating the radiation dose from CT in <sup>18</sup>F-PET/CT examinations poses a significant challenge. The objective of this study is to develop a deep learning-based automated program that standardizes the measurement of radiation doses.</p><p><strong>Methods: </strong>The torso CT was segmented into six distinct regions using TotalSegmentator. An automated program was employed to extract the necessary information and calculate the effective dose (ED) of PET/CT. The accuracy of our automated program was verified by comparing the EDs calculated by the program with those determined by a nuclear medicine physician (n = 30). Additionally, we compared the EDs obtained from an older PET/CT scanner with those from a newer PET/CT scanner (n = 42).</p><p><strong>Results: </strong>The CT ED calculated by the automated program was not significantly different from that calculated by the nuclear medicine physician (3.67 ± 0.61 mSv and 3.62 ± 0.60 mSv, respectively, <i>p</i> = 0.7623). Similarly, the total ED showed no significant difference between the two calculation methods (8.10 ± 1.40 mSv and 8.05 ± 1.39 mSv, respectively, <i>p</i> = 0.8957). A very strong correlation was observed in both the CT ED and total ED between the two measurements (r<sup>2</sup> = 0.9981 and 0.9996, respectively). The automated program showed excellent repeatability and reproducibility. When comparing the older and newer PET/CT scanners, the PET ED was significantly lower in the newer scanner than in the older scanner (4.39 ± 0.91 mSv and 6.00 ± 1.17 mSv, respectively, <i>p</i> < 0.0001). Consequently, the total ED was significantly lower in the newer scanner than in the older scanner (8.22 ± 1.53 mSv and 9.65 ± 1.34 mSv, respectively, <i>p</i> < 0.0001).</p><p><strong>Conclusions: </strong>We successfully developed an automated program for calculating the ED of torso <sup>18</sup>F-PET/CT. By integrating a deep learning model, the program effectively eliminated inter-operator variability.</p>\",\"PeriodicalId\":51330,\"journal\":{\"name\":\"Tomography\",\"volume\":\"10 12\",\"pages\":\"2144-2157\"},\"PeriodicalIF\":2.2000,\"publicationDate\":\"2024-12-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11679132/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Tomography\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.3390/tomography10120151\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Tomography","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.3390/tomography10120151","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING","Score":null,"Total":0}
引用次数: 0
摘要
背景/目的：在18F-PET/CT检查中计算CT的辐射剂量是一个重大挑战。本研究的目的是开发一种基于深度学习的自动化程序，使辐射剂量的测量标准化。方法：利用TotalSegmentator将躯干CT分割成6个不同的区域。采用自动程序提取必要信息并计算PET/CT有效剂量（ED）。通过将程序计算的ed与核医学医师确定的ed进行比较（n = 30），验证了我们自动化程序的准确性。此外，我们比较了老式PET/CT扫描仪与新型PET/CT扫描仪的EDs （n = 42）。结果：自动程序计算的CT ED与核医学医师计算的CT ED差异无统计学意义（分别为3.67±0.61 mSv和3.62±0.60 mSv, p = 0.7623）。同样，两种计算方法的总ED也无显著差异（分别为8.10±1.40 mSv和8.05±1.39 mSv, p = 0.8957）。在CT ED和总ED两个测量值之间观察到非常强的相关性（r2分别= 0.9981和0.9996）。该自动化程序具有良好的重复性和再现性。当比较旧的和新的PET/CT扫描仪时，新扫描仪的PET ED明显低于旧扫描仪（分别为4.39±0.91 mSv和6.00±1.17 mSv, p < 0.0001）。因此，新扫描仪的总ED明显低于旧扫描仪（分别为8.22±1.53 mSv和9.65±1.34 mSv, p < 0.0001）。结论：我们成功开发了一个计算躯干18F-PET/CT ED的自动程序。通过集成深度学习模型，该程序有效地消除了操作员之间的可变性。
Automated Measurement of Effective Radiation Dose by 18F-Fluorodeoxyglucose Positron Emission Tomography/Computed Tomography.
Background/objectives: Calculating the radiation dose from CT in 18F-PET/CT examinations poses a significant challenge. The objective of this study is to develop a deep learning-based automated program that standardizes the measurement of radiation doses.
Methods: The torso CT was segmented into six distinct regions using TotalSegmentator. An automated program was employed to extract the necessary information and calculate the effective dose (ED) of PET/CT. The accuracy of our automated program was verified by comparing the EDs calculated by the program with those determined by a nuclear medicine physician (n = 30). Additionally, we compared the EDs obtained from an older PET/CT scanner with those from a newer PET/CT scanner (n = 42).
Results: The CT ED calculated by the automated program was not significantly different from that calculated by the nuclear medicine physician (3.67 ± 0.61 mSv and 3.62 ± 0.60 mSv, respectively, p = 0.7623). Similarly, the total ED showed no significant difference between the two calculation methods (8.10 ± 1.40 mSv and 8.05 ± 1.39 mSv, respectively, p = 0.8957). A very strong correlation was observed in both the CT ED and total ED between the two measurements (r2 = 0.9981 and 0.9996, respectively). The automated program showed excellent repeatability and reproducibility. When comparing the older and newer PET/CT scanners, the PET ED was significantly lower in the newer scanner than in the older scanner (4.39 ± 0.91 mSv and 6.00 ± 1.17 mSv, respectively, p < 0.0001). Consequently, the total ED was significantly lower in the newer scanner than in the older scanner (8.22 ± 1.53 mSv and 9.65 ± 1.34 mSv, respectively, p < 0.0001).
Conclusions: We successfully developed an automated program for calculating the ED of torso 18F-PET/CT. By integrating a deep learning model, the program effectively eliminated inter-operator variability.
TomographyMedicine-Radiology, Nuclear Medicine and Imaging
CiteScore
2.70
自引率
10.50%
发文量
222
期刊介绍：
TomographyTM publishes basic (technical and pre-clinical) and clinical scientific articles which involve the advancement of imaging technologies. Tomography encompasses studies that use single or multiple imaging modalities including for example CT, US, PET, SPECT, MR and hyperpolarization technologies, as well as optical modalities (i.e. bioluminescence, photoacoustic, endomicroscopy, fiber optic imaging and optical computed tomography) in basic sciences, engineering, preclinical and clinical medicine.
Tomography also welcomes studies involving exploration and refinement of contrast mechanisms and image-derived metrics within and across modalities toward the development of novel imaging probes for image-based feedback and intervention. The use of imaging in biology and medicine provides unparalleled opportunities to noninvasively interrogate tissues to obtain real-time dynamic and quantitative information required for diagnosis and response to interventions and to follow evolving pathological conditions. As multi-modal studies and the complexities of imaging technologies themselves are ever increasing to provide advanced information to scientists and clinicians.
Tomography provides a unique publication venue allowing investigators the opportunity to more precisely communicate integrated findings related to the diverse and heterogeneous features associated with underlying anatomical, physiological, functional, metabolic and molecular genetic activities of normal and diseased tissue. Thus Tomography publishes peer-reviewed articles which involve the broad use of imaging of any tissue and disease type including both preclinical and clinical investigations. In addition, hardware/software along with chemical and molecular probe advances are welcome as they are deemed to significantly contribute towards the long-term goal of improving the overall impact of imaging on scientific and clinical discovery.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
