Johan Gustafsson, Erik Larsson, Katarina Sjögreen Gleisner
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The implementation of regional voxels (r.v.), estimating mean activity concentrations in regions directly from projections, offers a promising alternative for the geometry-specification to reduce PVEs.</p>\n </section>\n \n <section>\n \n <h3> Purpose</h3>\n \n <p>This study aims to demonstrate that activity-concentration estimation with r.v. is superior to reconstruction with cuboid voxels (cu.v.) with post-reconstruction partial-volume correction (PVC) for estimation of activity concentration in <sup>177</sup>Lu peptide receptor radionuclide therapy (<sup>177</sup>Lu-PRRT).</p>\n </section>\n \n <section>\n \n <h3> Methods</h3>\n \n <p>Data originated from one patient administered [<sup>177</sup>Lu]Lu-DOTA-TOC with SPECT acquired at 1 d, 4 d and 7 d p.i. stored in list-mode format (dataset PA), and eight patients given [<sup>177</sup>Lu]Lu-DOTA-TATE with SPECT acquired 1 d p.i. (dataset PB). Activity concentration was estimated from reconstruction with cu.v. and using r.v. for both datasets, with multiple noise realizations for PA using bootstrapping. Organ delineation was performed based on CT using the AI tool TotalSegmentator, and tumor delineation made in cu.v. SPECT images. The estimated activity concentration for kidneys, spleen, and tumors from r.v. was compared to that obtained with cu.v. with and without post-reconstruction PVC. To study the accuracy of activity-concentration estimates, simulations were performed with the SIMIND Monte Carlo program with patient images used as basis. The sensitivity to misalignments between SPECT and CT was also evaluated.</p>\n </section>\n \n <section>\n \n <h3> Results</h3>\n \n <p>For both patient and simulated data, activity concentrations estimated with r.v. are higher than those from cu.v., with comparable standard deviations. Mean relative errors for simulated images from PA relative to simulation input at 1 d p.i. reconstructions with r.v. are (−4.6 <i>± </i>1.4) %, (3.0 <i>± </i>0.5) %, (0.1 <i>± </i>0.5) %, and (5.6 <i>± </i>1.2) % for tumor, left kidney, right kidney, and spleen, respectively. Corresponding results for cu.v. with post-reconstruction PVC are (−12.3 <i>± </i>2.2) %, (-4.2 <i>± </i>0.6) %, (−7.0 <i>± </i>0.5) %, and (-2.1 <i>± </i>1.1) %. For simulated images based on PB, the mean relative errors obtained for r.v. are (−3.1 <i>± </i>3.5) %, (1.2 <i>± </i>1.2) %, (−1.7 <i>± </i>1.1) %, and (2.3 <i>± </i>0.8) %, while for cu.v. with PVC they are (−7.9 <i>± </i>6.7) %, (-5.8 <i>± </i>1.9) %, (−9.0 <i>± </i>1.0) %, and (-0.7 <i>± </i>2.6) %.</p>\n </section>\n \n <section>\n \n <h3> Conclusions</h3>\n \n <p>Regional voxels are superior to cu.v. for estimation of the activity concentration in organs in <sup>177</sup>Lu-PRRT and demonstrates lower sensitivity to misregistration errors. For tumors, r.v. yields lower systematic errors than cu.v. but demonstrates a higher sensitivity to image segmentation errors for volumes below approximately 10 mL.</p>\n </section>\n </div>","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"53 4","pages":""},"PeriodicalIF":3.2000,"publicationDate":"2026-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13051038/pdf/","citationCount":"0","resultStr":"{\"title\":\"Direct estimation of activity concentration in regional voxels with application to 177Lu peptide receptor radionuclide therapy\",\"authors\":\"Johan Gustafsson, Erik Larsson, Katarina Sjögreen Gleisner\",\"doi\":\"10.1002/mp.70424\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n \\n \\n <section>\\n \\n <h3> Background</h3>\\n \\n <p>Quantitative SPECT in radionuclide-therapy is limited by partial-volume effects (PVEs). The implementation of regional voxels (r.v.), estimating mean activity concentrations in regions directly from projections, offers a promising alternative for the geometry-specification to reduce PVEs.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Purpose</h3>\\n \\n <p>This study aims to demonstrate that activity-concentration estimation with r.v. is superior to reconstruction with cuboid voxels (cu.v.) with post-reconstruction partial-volume correction (PVC) for estimation of activity concentration in <sup>177</sup>Lu peptide receptor radionuclide therapy (<sup>177</sup>Lu-PRRT).</p>\\n </section>\\n \\n <section>\\n \\n <h3> Methods</h3>\\n \\n <p>Data originated from one patient administered [<sup>177</sup>Lu]Lu-DOTA-TOC with SPECT acquired at 1 d, 4 d and 7 d p.i. stored in list-mode format (dataset PA), and eight patients given [<sup>177</sup>Lu]Lu-DOTA-TATE with SPECT acquired 1 d p.i. (dataset PB). Activity concentration was estimated from reconstruction with cu.v. and using r.v. for both datasets, with multiple noise realizations for PA using bootstrapping. Organ delineation was performed based on CT using the AI tool TotalSegmentator, and tumor delineation made in cu.v. SPECT images. The estimated activity concentration for kidneys, spleen, and tumors from r.v. was compared to that obtained with cu.v. with and without post-reconstruction PVC. To study the accuracy of activity-concentration estimates, simulations were performed with the SIMIND Monte Carlo program with patient images used as basis. The sensitivity to misalignments between SPECT and CT was also evaluated.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Results</h3>\\n \\n <p>For both patient and simulated data, activity concentrations estimated with r.v. are higher than those from cu.v., with comparable standard deviations. Mean relative errors for simulated images from PA relative to simulation input at 1 d p.i. reconstructions with r.v. are (−4.6 <i>± </i>1.4) %, (3.0 <i>± </i>0.5) %, (0.1 <i>± </i>0.5) %, and (5.6 <i>± </i>1.2) % for tumor, left kidney, right kidney, and spleen, respectively. Corresponding results for cu.v. with post-reconstruction PVC are (−12.3 <i>± </i>2.2) %, (-4.2 <i>± </i>0.6) %, (−7.0 <i>± </i>0.5) %, and (-2.1 <i>± </i>1.1) %. For simulated images based on PB, the mean relative errors obtained for r.v. are (−3.1 <i>± </i>3.5) %, (1.2 <i>± </i>1.2) %, (−1.7 <i>± </i>1.1) %, and (2.3 <i>± </i>0.8) %, while for cu.v. with PVC they are (−7.9 <i>± </i>6.7) %, (-5.8 <i>± </i>1.9) %, (−9.0 <i>± </i>1.0) %, and (-0.7 <i>± </i>2.6) %.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Conclusions</h3>\\n \\n <p>Regional voxels are superior to cu.v. for estimation of the activity concentration in organs in <sup>177</sup>Lu-PRRT and demonstrates lower sensitivity to misregistration errors. 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引用次数: 0
摘要
背景:定量SPECT在放射性核素治疗中受到部分体积效应(pve)的限制。区域体素(regional voxels, r.v.)的实现,直接从投影中估计区域的平均活动浓度,为减少pve的几何规范提供了一个有希望的替代方案。目的:本研究旨在证明在177Lu肽受体放射性核素治疗(177Lu- prrt)中,用rv -v法估算活性浓度优于用重建后部分体积校正(PVC)的长方体体素(cu.v.)重建法估算活性浓度。方法:数据来源于1例给予[177Lu]Lu-DOTA-TOC并在产后1、4、7天使用SPECT采集的患者(数据集PA),以及8例给予[177Lu]Lu-DOTA-TATE并在产后1天使用SPECT采集的患者(数据集PB)。利用cu.v重建估算活性浓度。并对两个数据集使用rv,对PA使用bootstrapping实现多个噪声。采用人工智能工具TotalSegmentator在CT上进行器官圈定,用cuv进行肿瘤圈定。SPECT图像。将rv对肾脏、脾脏和肿瘤的估计活性浓度与cu.v的估计活性浓度进行比较。有和没有重建后的PVC。为了研究活动浓度估计的准确性,使用SIMIND蒙特卡罗程序以患者图像为基础进行模拟。同时还对SPECT和CT对错位的敏感性进行了评估。结果:对于患者和模拟数据,用rv估计的活性浓度高于用cuv估计的活性浓度。,具有可比的标准差。在1 d p.i.r v重建时,PA模拟图像相对于模拟输入的平均相对误差分别为肿瘤、左肾、右肾和脾脏的(-4.6±1.4)%、(3.0±0.5)%、(0.1±0.5)%和(5.6±1.2)%。cuv的对应结果。与那些PVC(-12.3±2.2)%,(-4.2±0.6)%,(-7.0±0.5)%,和(-2.1±1.1)%。对于基于PB的模拟图像,rv的平均相对误差分别为(-3.1±3.5)%、(1.2±1.2)%、(-1.7±1.1)%和(2.3±0.8)%;与PVC(-7.9±6.7)%,(-5.8±1.9)%,(-9.0±1.0)%,和(-0.7±2.6)%。结论:区域体素优于cuv。用于估计177Lu-PRRT在器官中的活性浓度,并且对错配错误的敏感性较低。对于肿瘤,rv比cuv产生更低的系统误差。但对体积低于约10 mL的图像分割错误表现出更高的灵敏度。
Direct estimation of activity concentration in regional voxels with application to 177Lu peptide receptor radionuclide therapy
Background
Quantitative SPECT in radionuclide-therapy is limited by partial-volume effects (PVEs). The implementation of regional voxels (r.v.), estimating mean activity concentrations in regions directly from projections, offers a promising alternative for the geometry-specification to reduce PVEs.
Purpose
This study aims to demonstrate that activity-concentration estimation with r.v. is superior to reconstruction with cuboid voxels (cu.v.) with post-reconstruction partial-volume correction (PVC) for estimation of activity concentration in 177Lu peptide receptor radionuclide therapy (177Lu-PRRT).
Methods
Data originated from one patient administered [177Lu]Lu-DOTA-TOC with SPECT acquired at 1 d, 4 d and 7 d p.i. stored in list-mode format (dataset PA), and eight patients given [177Lu]Lu-DOTA-TATE with SPECT acquired 1 d p.i. (dataset PB). Activity concentration was estimated from reconstruction with cu.v. and using r.v. for both datasets, with multiple noise realizations for PA using bootstrapping. Organ delineation was performed based on CT using the AI tool TotalSegmentator, and tumor delineation made in cu.v. SPECT images. The estimated activity concentration for kidneys, spleen, and tumors from r.v. was compared to that obtained with cu.v. with and without post-reconstruction PVC. To study the accuracy of activity-concentration estimates, simulations were performed with the SIMIND Monte Carlo program with patient images used as basis. The sensitivity to misalignments between SPECT and CT was also evaluated.
Results
For both patient and simulated data, activity concentrations estimated with r.v. are higher than those from cu.v., with comparable standard deviations. Mean relative errors for simulated images from PA relative to simulation input at 1 d p.i. reconstructions with r.v. are (−4.6 ± 1.4) %, (3.0 ± 0.5) %, (0.1 ± 0.5) %, and (5.6 ± 1.2) % for tumor, left kidney, right kidney, and spleen, respectively. Corresponding results for cu.v. with post-reconstruction PVC are (−12.3 ± 2.2) %, (-4.2 ± 0.6) %, (−7.0 ± 0.5) %, and (-2.1 ± 1.1) %. For simulated images based on PB, the mean relative errors obtained for r.v. are (−3.1 ± 3.5) %, (1.2 ± 1.2) %, (−1.7 ± 1.1) %, and (2.3 ± 0.8) %, while for cu.v. with PVC they are (−7.9 ± 6.7) %, (-5.8 ± 1.9) %, (−9.0 ± 1.0) %, and (-0.7 ± 2.6) %.
Conclusions
Regional voxels are superior to cu.v. for estimation of the activity concentration in organs in 177Lu-PRRT and demonstrates lower sensitivity to misregistration errors. For tumors, r.v. yields lower systematic errors than cu.v. but demonstrates a higher sensitivity to image segmentation errors for volumes below approximately 10 mL.
期刊介绍:
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