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基于Tc-MAA SPECT/CT的个体化预测剂量测定在选择性内放射治疗中的临床影响:不可切除肝癌患者的单中心真实世界经验

Clinical impact of Tc-MAA SPECT/CT-based personalized predictive dosimetry in selective internal radiotherapy: a real-life single-center experience in unresectable HCC patients.

作者信息

Bucalau Ana-Maria, Collette Benoît, Tancredi Illario, Vouche Michael, Pezzullo Martina, Bouziotis Jason, Moreno-Reyes Rodrigo, Trotta Nicola, Levillain Hugo, Van Laethem Jean Luc, Verset Gontran

机构信息

Department of Gastroenterology, Hepatopancreatology and Digestive Oncology, Hôpital Erasme/Bordet Institute-Hôpital Universitaire de Bruxelles, Université Libre de Bruxelles (ULB), Brussels, Belgium.

Department of Nuclear Medicine, Hôpital Erasme/Bordet Institute-Hôpital Universitaire de Bruxelles, Université Libre de Bruxelles (ULB), Brussels, Belgium.

出版信息

Eur J Hybrid Imaging. 2023 Jul 7;7(1):12. doi: 10.1186/s41824-023-00171-8.

Abstract

BACKGROUND

Recent data demonstrated that personalized dosimetry-based selective internal radiotherapy (SIRT) is associated with better outcome for unresectable hepatocellular carcinoma (HCC).

AIM

We aim to evaluate the contribution of personalized predictive dosimetry (performed with Simplicity® software) in our population of HCC patients by comparing them to our historical cohort whose activity was determined by standard dosimetry.

METHODS

This is a retrospective, single-center study conducted between February 2016 and December 2020 that included patients with HCC who received SIRT after simulation based on either standard dosimetry (group A) or, as of December 2017, on personalized dosimetry (group B). Primary endpoints were best overall response (BOR) and objective response rate (ORR) evaluated by mRECIST at 3 months. Safety and toxicity profiles were evaluated at 1- and 3-months post-treatment. For group A we compared the activity to be administered determined a posteriori using SimplicitY® and the activity actually administered determined by the standard approach.

RESULTS

Between February 2016 and December 2020, 66 patients received 69 simulations leading to 40 treatments. The median follow-up time was equal for both groups, 21 months (range 3-55) in group A and 21 months (range 4-39) in group B. The per patient analysis revealed a significant benefit of personalized predictive dosimetry in terms of better overall response at 3 months (80% vs. 33.3%, p = 0.007) and at 6 months (77.8% vs. 22.2%, p = 0.06). This trend was found in the analysis by nodule with a response rate according to mRECIST of 87.5% for personalized dosimetry versus 68.4% for standard dosimetry at 3 months, p = 0.24. Only one grade 3 biological toxicity (hyperbilirubinemia) was noted in group A. The comparison between the administered activity and the recommended activity recalculated a posteriori using SimplicitY® showed that the vast majority of patients who progressed (83.33%) received less activity than that recommended by the personalized approach or an inadequate distribution of the administered activity.

CONCLUSIONS

Our study aligns to recent literature and confirms that the use of personalized dosimetry allows a better selection of HCC patients who can benefit from SIRT, and consequently, improves the effectiveness of this treatment.

摘要

背景

近期数据表明,基于个体化剂量测定的选择性体内放射治疗(SIRT)与不可切除肝细胞癌(HCC)的更好预后相关。

目的

我们旨在通过将接受SIRT治疗的HCC患者与采用标准剂量测定法确定活性的历史队列进行比较,评估个体化预测剂量测定法(使用Simplicity®软件进行)在我们的HCC患者群体中的作用。

方法

这是一项回顾性单中心研究,于2016年2月至2020年12月进行,纳入了基于标准剂量测定法(A组)或自2017年12月起基于个体化剂量测定法(B组)进行模拟后接受SIRT治疗的HCC患者。主要终点为3个月时根据改良RECIST(mRECIST)评估的最佳总体缓解(BOR)和客观缓解率(ORR)。在治疗后1个月和3个月评估安全性和毒性情况。对于A组,我们比较了使用SimplicitY®事后确定的待给予活性与标准方法确定的实际给予活性。

结果

2016年2月至2020年12月期间,66例患者接受了69次模拟,共进行了40次治疗。两组的中位随访时间相等,A组为21个月(范围3 - 55个月),B组为21个月(范围4 - 39个月)。按患者分析显示,个体化预测剂量测定法在3个月时总体缓解更好(80%对33.3%,p = 0.007)以及6个月时(77.8%对22.2%,p = 0.06)具有显著益处。在按结节分析中也发现了这一趋势,3个月时根据mRECIST的缓解率,个体化剂量测定法为87.5%,标准剂量测定法为68.4%,p = 0.24。A组仅记录到1例3级生物学毒性(高胆红素血症)。使用SimplicitY®事后重新计算的给予活性与推荐活性之间的比较显示,绝大多数病情进展的患者(83.33%)接受的活性低于个体化方法推荐的活性或给予活性分布不当。

结论

我们的研究与近期文献一致,证实使用个体化剂量测定法能够更好地选择可从SIRT治疗中获益的HCC患者,从而提高该治疗的有效性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/77a0/10326228/57fe2fc80281/41824_2023_171_Fig1_HTML.jpg

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