Ziyang Wang, Jianjing Liu, Di Lu, Guoqing Sui, Yaya Wang, Lina Tong, Xueyao Liu, Yan Zhang, Jie Fu, Wengui Xu, Dong Dai
{"title":"肺癌PET/CT运动校正算法的评估：幻影验证和患者研究。","authors":"Ziyang Wang, Jianjing Liu, Di Lu, Guoqing Sui, Yaya Wang, Lina Tong, Xueyao Liu, Yan Zhang, Jie Fu, Wengui Xu, Dong Dai","doi":"10.1002/mp.17846","DOIUrl":null,"url":null,"abstract":"<div>\n \n \n <section>\n \n <h3> Background</h3>\n \n <p>Data-driven gating (DDG) is an emerging technology that can reduce the respiratory motion artifacts in positron emission tomography (PET) images.</p>\n </section>\n \n <section>\n \n <h3> Purpose</h3>\n \n <p>The aim of this study is to use phantom and patient data to validate the performance of DDG with a motion correction algorithm based on the reconstruct, register, and average (RRA) method.</p>\n </section>\n \n <section>\n \n <h3> Methods</h3>\n \n <p>A customized motion platform drove the phantom (five spheres with diameters of 10–28 mm) using a periodic motion that had a duration of 3–5 s and amplitudes of 2–4 cm. Normalized ratio of ungated and RRA PET relative to the ground-truth static PET was calculated for RSUVmax, RSUVmean, RSUVpeak, RVolume, and relative contrast-to-noise ratio (RCNR). Additionally, 30 lung cancer patients with 76 lung lesions less than 3 cm in diameter were prospectively studied. The overall image quality of patient examination was scored using a 5-point scale by two radiologists. SUVmax, SUVmean, SUVpeak, volume, and CNR of lesions measured in ungated and RRA PET were compared, and subgroup analysis was conducted.</p>\n </section>\n \n <section>\n \n <h3> Results</h3>\n \n <p>In RRA PET images, motion artifacts of the spheres in the phantom were effectively mitigated, regardless of changes in movement amplitudes or duration. For all spheres with different ranges of motion and cycles, RSUVmax, RSUVmean, RSUVpeak, and RCNR increased significantly (<i>p</i> ≤ 0.001) and RVolume decreased significantly (<i>p </i>< 0.001) in RRA PET images. The average radiologist scores of image quality were 3.90 ± 0.86 with RRA PET, and 3.03 ± 1.19 with ungated PET. In RRA PET images, the SUVmax (<i>p </i>< 0.001), SUVmean (<i>p </i>< 0.001), SUVpeak (<i>p </i>< 0.001), and CNR (<i>p </i>< 0.001) of the lesions increased, while the volume (<i>p </i>< 0.001) of the lesions decreased. Δ%SUVmax, Δ%SUVmean, Δ%SUVpeak, and Δ%CNR of the lesions increased by 3.9%, 6.5%, 5.6%, and 4.3%, respectively, while Δ%Volume of the lesions decreased by 18.4%. Subgroup analysis showed that in lesions in the upper and middle lobes, only SUVpeak (<i>p </i>< 0.001) significantly increased by 5.6% in RRA PET, while their volume (<i>p </i>< 0.001) notably decreased by 12.4% (<i>p </i>< 0.001).</p>\n </section>\n \n <section>\n \n <h3> Conclusion</h3>\n \n <p>DDG integrated with RRA motion correction algorithm can effectively mitigate motion artifacts, thus enhancing the quantification accuracy and visual quality of images in lung cancer PET/CT.</p>\n </section>\n </div>","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"52 7","pages":""},"PeriodicalIF":3.2000,"publicationDate":"2025-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Evaluation of a motion correction algorithm in lung cancer PET/CT: Phantom validation and patient studies\",\"authors\":\"Ziyang Wang, Jianjing Liu, Di Lu, Guoqing Sui, Yaya Wang, Lina Tong, Xueyao Liu, Yan Zhang, Jie Fu, Wengui Xu, Dong Dai\",\"doi\":\"10.1002/mp.17846\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n \\n \\n <section>\\n \\n <h3> Background</h3>\\n \\n <p>Data-driven gating (DDG) is an emerging technology that can reduce the respiratory motion artifacts in positron emission tomography (PET) images.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Purpose</h3>\\n \\n <p>The aim of this study is to use phantom and patient data to validate the performance of DDG with a motion correction algorithm based on the reconstruct, register, and average (RRA) method.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Methods</h3>\\n \\n <p>A customized motion platform drove the phantom (five spheres with diameters of 10–28 mm) using a periodic motion that had a duration of 3–5 s and amplitudes of 2–4 cm. Normalized ratio of ungated and RRA PET relative to the ground-truth static PET was calculated for RSUVmax, RSUVmean, RSUVpeak, RVolume, and relative contrast-to-noise ratio (RCNR). Additionally, 30 lung cancer patients with 76 lung lesions less than 3 cm in diameter were prospectively studied. The overall image quality of patient examination was scored using a 5-point scale by two radiologists. SUVmax, SUVmean, SUVpeak, volume, and CNR of lesions measured in ungated and RRA PET were compared, and subgroup analysis was conducted.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Results</h3>\\n \\n <p>In RRA PET images, motion artifacts of the spheres in the phantom were effectively mitigated, regardless of changes in movement amplitudes or duration. For all spheres with different ranges of motion and cycles, RSUVmax, RSUVmean, RSUVpeak, and RCNR increased significantly (<i>p</i> ≤ 0.001) and RVolume decreased significantly (<i>p </i>< 0.001) in RRA PET images. The average radiologist scores of image quality were 3.90 ± 0.86 with RRA PET, and 3.03 ± 1.19 with ungated PET. In RRA PET images, the SUVmax (<i>p </i>< 0.001), SUVmean (<i>p </i>< 0.001), SUVpeak (<i>p </i>< 0.001), and CNR (<i>p </i>< 0.001) of the lesions increased, while the volume (<i>p </i>< 0.001) of the lesions decreased. Δ%SUVmax, Δ%SUVmean, Δ%SUVpeak, and Δ%CNR of the lesions increased by 3.9%, 6.5%, 5.6%, and 4.3%, respectively, while Δ%Volume of the lesions decreased by 18.4%. Subgroup analysis showed that in lesions in the upper and middle lobes, only SUVpeak (<i>p </i>< 0.001) significantly increased by 5.6% in RRA PET, while their volume (<i>p </i>< 0.001) notably decreased by 12.4% (<i>p </i>< 0.001).</p>\\n </section>\\n \\n <section>\\n \\n <h3> Conclusion</h3>\\n \\n <p>DDG integrated with RRA motion correction algorithm can effectively mitigate motion artifacts, thus enhancing the quantification accuracy and visual quality of images in lung cancer PET/CT.</p>\\n </section>\\n </div>\",\"PeriodicalId\":18384,\"journal\":{\"name\":\"Medical physics\",\"volume\":\"52 7\",\"pages\":\"\"},\"PeriodicalIF\":3.2000,\"publicationDate\":\"2025-04-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Medical physics\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/mp.17846\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Medical physics","FirstCategoryId":"3","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/mp.17846","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING","Score":null,"Total":0}
Evaluation of a motion correction algorithm in lung cancer PET/CT: Phantom validation and patient studies
Background
Data-driven gating (DDG) is an emerging technology that can reduce the respiratory motion artifacts in positron emission tomography (PET) images.
Purpose
The aim of this study is to use phantom and patient data to validate the performance of DDG with a motion correction algorithm based on the reconstruct, register, and average (RRA) method.
Methods
A customized motion platform drove the phantom (five spheres with diameters of 10–28 mm) using a periodic motion that had a duration of 3–5 s and amplitudes of 2–4 cm. Normalized ratio of ungated and RRA PET relative to the ground-truth static PET was calculated for RSUVmax, RSUVmean, RSUVpeak, RVolume, and relative contrast-to-noise ratio (RCNR). Additionally, 30 lung cancer patients with 76 lung lesions less than 3 cm in diameter were prospectively studied. The overall image quality of patient examination was scored using a 5-point scale by two radiologists. SUVmax, SUVmean, SUVpeak, volume, and CNR of lesions measured in ungated and RRA PET were compared, and subgroup analysis was conducted.
Results
In RRA PET images, motion artifacts of the spheres in the phantom were effectively mitigated, regardless of changes in movement amplitudes or duration. For all spheres with different ranges of motion and cycles, RSUVmax, RSUVmean, RSUVpeak, and RCNR increased significantly (p ≤ 0.001) and RVolume decreased significantly (p < 0.001) in RRA PET images. The average radiologist scores of image quality were 3.90 ± 0.86 with RRA PET, and 3.03 ± 1.19 with ungated PET. In RRA PET images, the SUVmax (p < 0.001), SUVmean (p < 0.001), SUVpeak (p < 0.001), and CNR (p < 0.001) of the lesions increased, while the volume (p < 0.001) of the lesions decreased. Δ%SUVmax, Δ%SUVmean, Δ%SUVpeak, and Δ%CNR of the lesions increased by 3.9%, 6.5%, 5.6%, and 4.3%, respectively, while Δ%Volume of the lesions decreased by 18.4%. Subgroup analysis showed that in lesions in the upper and middle lobes, only SUVpeak (p < 0.001) significantly increased by 5.6% in RRA PET, while their volume (p < 0.001) notably decreased by 12.4% (p < 0.001).
Conclusion
DDG integrated with RRA motion correction algorithm can effectively mitigate motion artifacts, thus enhancing the quantification accuracy and visual quality of images in lung cancer PET/CT.
期刊介绍：
Medical Physics publishes original, high impact physics, imaging science, and engineering research that advances patient diagnosis and therapy through contributions in 1) Basic science developments with high potential for clinical translation 2) Clinical applications of cutting edge engineering and physics innovations 3) Broadly applicable and innovative clinical physics developments
Medical Physics is a journal of global scope and reach. By publishing in Medical Physics your research will reach an international, multidisciplinary audience including practicing medical physicists as well as physics- and engineering based translational scientists. We work closely with authors of promising articles to improve their quality.
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