Madhusudan A Savaikar, Timothy Whitehead, Sudipta Roy, Lori Strong, Nicole Fettig, Tina Prmeau, Jingqin Luo, Shunqiang Li, Richard L Wahl, Kooresh I Shoghi
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We characterized the reproducibility of standardized uptake value (SUV) metrics to assess response to therapy, and we optimized a preclinical PERCIST paradigm to complement clinical standards. Considerations in this effort included variability in tumor growth rate and tumor size, solid tumors versus tumor heterogeneity and a necrotic phenotype, and optimal selection of tumor slices versus whole tumor. <b>Methods:</b> A test-retest protocol was implemented to optimize the reproducibility of <sup>18</sup>F-FDG PET SUV thresholds, SUV<sub>peak</sub> metrics, and preclinical PERCIST parameters. In assessing response to therapy, <sup>18</sup>F-FDG PET imaging was performed at baseline and 4 d after therapy. The reproducibility, accuracy, variability, and performance of imaging metrics to assess response to therapy were determined. We defined an index called the Quantitative Response Assessment Score to integrate parameters of prediction and precision and thus aid in selecting the optimal image metric to assess response to therapy. <b>Results:</b> Our data suggest that a threshold of 25% of SUV<sub>max</sub> (SUV<sub>25</sub>) was highly reproducible (<9% variability). The concordance and reproducibility of preclinical PERCIST were maximized at α = 0.7 and β = 2.8 and exhibited a high correlation with SUV<sub>25</sub> measures of tumor uptake, which in turn correlated with the SUV of metabolic tumor. <b>Conclusion:</b> The Quantitative Response Assessment Score favors SUV<sub>25</sub> followed by SUV<sub>peak</sub> for a sphere with a volume of 14 mm<sup>3</sup> (SUV<sub>P14</sub>) as optimal metrics of response to therapy. Additional studies are warranted to fully characterize the utility of SUV<sub>25</sub> and preclinical PERCIST SUV<sub>P14</sub> as image metrics for response to therapy across a wide range of therapeutic regimens and PDX models.</p>","PeriodicalId":50832,"journal":{"name":"Aktuelle Neurologie","volume":"32 1","pages":"842-849"},"PeriodicalIF":0.0000,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7262224/pdf/","citationCount":"0","resultStr":"{\"title\":\"Preclinical PERCIST and 25% of SUV<sub>max</sub> Threshold: Precision Imaging of Response to Therapy in Co-clinical <sup>18</sup>F-FDG PET Imaging of Triple-Negative Breast Cancer Patient-Derived Tumor Xenografts.\",\"authors\":\"Madhusudan A Savaikar, Timothy Whitehead, Sudipta Roy, Lori Strong, Nicole Fettig, Tina Prmeau, Jingqin Luo, Shunqiang Li, Richard L Wahl, Kooresh I Shoghi\",\"doi\":\"10.2967/jnumed.119.234286\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Numerous recent works highlight the limited utility of established tumor cell lines in recapitulating the heterogeneity of tumors in patients. More realistic preclinical cancer models are thought to be provided by transplantable, patient-derived xenografts (PDXs). The inter- and intratumor heterogeneity of PDXs, however, presents several challenges in developing optimal quantitative pipelines to assess response to therapy. The objective of this work was to develop and optimize image metrics for <sup>18</sup>F-FDG PET to assess response to combination docetaxel and carboplatin therapy in a co-clinical trial involving triple-negative breast cancer PDXs. We characterized the reproducibility of standardized uptake value (SUV) metrics to assess response to therapy, and we optimized a preclinical PERCIST paradigm to complement clinical standards. Considerations in this effort included variability in tumor growth rate and tumor size, solid tumors versus tumor heterogeneity and a necrotic phenotype, and optimal selection of tumor slices versus whole tumor. <b>Methods:</b> A test-retest protocol was implemented to optimize the reproducibility of <sup>18</sup>F-FDG PET SUV thresholds, SUV<sub>peak</sub> metrics, and preclinical PERCIST parameters. In assessing response to therapy, <sup>18</sup>F-FDG PET imaging was performed at baseline and 4 d after therapy. The reproducibility, accuracy, variability, and performance of imaging metrics to assess response to therapy were determined. We defined an index called the Quantitative Response Assessment Score to integrate parameters of prediction and precision and thus aid in selecting the optimal image metric to assess response to therapy. <b>Results:</b> Our data suggest that a threshold of 25% of SUV<sub>max</sub> (SUV<sub>25</sub>) was highly reproducible (<9% variability). The concordance and reproducibility of preclinical PERCIST were maximized at α = 0.7 and β = 2.8 and exhibited a high correlation with SUV<sub>25</sub> measures of tumor uptake, which in turn correlated with the SUV of metabolic tumor. <b>Conclusion:</b> The Quantitative Response Assessment Score favors SUV<sub>25</sub> followed by SUV<sub>peak</sub> for a sphere with a volume of 14 mm<sup>3</sup> (SUV<sub>P14</sub>) as optimal metrics of response to therapy. Additional studies are warranted to fully characterize the utility of SUV<sub>25</sub> and preclinical PERCIST SUV<sub>P14</sub> as image metrics for response to therapy across a wide range of therapeutic regimens and PDX models.</p>\",\"PeriodicalId\":50832,\"journal\":{\"name\":\"Aktuelle Neurologie\",\"volume\":\"32 1\",\"pages\":\"842-849\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7262224/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Aktuelle Neurologie\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2967/jnumed.119.234286\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2019/11/22 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q4\",\"JCRName\":\"Medicine\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Aktuelle Neurologie","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2967/jnumed.119.234286","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2019/11/22 0:00:00","PubModel":"Epub","JCR":"Q4","JCRName":"Medicine","Score":null,"Total":0}
引用次数: 0
摘要
最近的许多研究都强调,已建立的肿瘤细胞系在再现患者肿瘤的异质性方面作用有限。可移植的患者来源异种移植物(PDXs)被认为能提供更真实的临床前癌症模型。然而,PDXs 的肿瘤间和肿瘤内异质性给开发评估治疗反应的最佳定量管道带来了一些挑战。这项工作的目的是开发和优化 18F-FDG PET 图像指标,以评估三阴性乳腺癌 PDXs 共同临床试验中多西他赛和卡铂联合疗法的反应。我们确定了评估治疗反应的标准化摄取值 (SUV) 指标的可重复性,并优化了临床前 PERCIST 范例,以补充临床标准。这项工作的考虑因素包括肿瘤生长速度和肿瘤大小的可变性、实体瘤与肿瘤异质性和坏死表型的对比,以及肿瘤切片与整个肿瘤的最佳选择。方法采用重复测试方案来优化 18F-FDG PET SUV 阈值、SUV 峰值指标和临床前 PERCIST 参数的可重复性。在评估治疗反应时,分别在基线和治疗后 4 d 进行了 18F-FDG PET 成像检查。我们确定了评估治疗反应的成像指标的再现性、准确性、可变性和性能。我们定义了一个名为 "定量反应评估评分 "的指数,以整合预测参数和精确度参数,从而帮助选择评估治疗反应的最佳影像指标。结果我们的数据表明,SUVmax 的 25% 临界值(SUV25)具有很高的可重复性(25 个肿瘤摄取测量值,反过来又与代谢肿瘤的 SUV 值相关)。结论:定量反应评估评分倾向于将 SUV25 和体积为 14 立方毫米的球体的 SUV 峰值(SUVP14)作为治疗反应的最佳指标。还需要进行更多的研究,以全面确定 SUV25 和临床前 PERCIST SUVP14 作为图像指标在各种治疗方案和 PDX 模型中对治疗反应的效用。
Preclinical PERCIST and 25% of SUVmax Threshold: Precision Imaging of Response to Therapy in Co-clinical 18F-FDG PET Imaging of Triple-Negative Breast Cancer Patient-Derived Tumor Xenografts.
Numerous recent works highlight the limited utility of established tumor cell lines in recapitulating the heterogeneity of tumors in patients. More realistic preclinical cancer models are thought to be provided by transplantable, patient-derived xenografts (PDXs). The inter- and intratumor heterogeneity of PDXs, however, presents several challenges in developing optimal quantitative pipelines to assess response to therapy. The objective of this work was to develop and optimize image metrics for 18F-FDG PET to assess response to combination docetaxel and carboplatin therapy in a co-clinical trial involving triple-negative breast cancer PDXs. We characterized the reproducibility of standardized uptake value (SUV) metrics to assess response to therapy, and we optimized a preclinical PERCIST paradigm to complement clinical standards. Considerations in this effort included variability in tumor growth rate and tumor size, solid tumors versus tumor heterogeneity and a necrotic phenotype, and optimal selection of tumor slices versus whole tumor. Methods: A test-retest protocol was implemented to optimize the reproducibility of 18F-FDG PET SUV thresholds, SUVpeak metrics, and preclinical PERCIST parameters. In assessing response to therapy, 18F-FDG PET imaging was performed at baseline and 4 d after therapy. The reproducibility, accuracy, variability, and performance of imaging metrics to assess response to therapy were determined. We defined an index called the Quantitative Response Assessment Score to integrate parameters of prediction and precision and thus aid in selecting the optimal image metric to assess response to therapy. Results: Our data suggest that a threshold of 25% of SUVmax (SUV25) was highly reproducible (<9% variability). The concordance and reproducibility of preclinical PERCIST were maximized at α = 0.7 and β = 2.8 and exhibited a high correlation with SUV25 measures of tumor uptake, which in turn correlated with the SUV of metabolic tumor. Conclusion: The Quantitative Response Assessment Score favors SUV25 followed by SUVpeak for a sphere with a volume of 14 mm3 (SUVP14) as optimal metrics of response to therapy. Additional studies are warranted to fully characterize the utility of SUV25 and preclinical PERCIST SUVP14 as image metrics for response to therapy across a wide range of therapeutic regimens and PDX models.