Modeling of Normal Tissue Complications Using Imaging and Biomarkers After Radiation Therapy for Hepatocellular Carcinoma.

Modeling of Normal Tissue Complications Using Imaging and Biomarkers After Radiation Therapy for Hepatocellular Carcinoma.
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肝细胞癌后使用成像和生物标志物对正常组织并发症进行建模。

DOI:
10.1016/j.ijrobp.2017.10.005
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发表时间:
2018-02-01
期刊:
International journal of radiation oncology, biology, physics
影响因子:
--
通讯作者:
Ten Haken RK
Ten Haken RK
中科院分区:
其他
文献类型:
--
作者:
El Naqa I;Johansson A;Owen D;Cuneo K;Cao Y;Matuszak M;Bazzi L;Lawrence TS;Ten Haken RK

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为接受肝脏放射治疗的肝细胞癌(HCC)患者开发NTCP模型,并评估治疗前和治疗期间功能成像和血液循环生物标志物的潜在作用,以改善这些模型的性能。对2005-2014年间接受放射治疗的192例HCC患者进行了评价:146例接受SBRT,46例接受常规放射,中位物理肿瘤剂量分别为49.8戈伊和50.4戈伊。将物理剂量转换为EQD 2进行分析。研究了两种建模NTCP的方法:(a)广义Lyman-Kutcher-Burman(LKB)模型;(B)广义并行体系结构(PA)模型。考虑了三个临床终点:ALBI变化、Child-Pugh(C-P)评分变化和3级或以上肝酶变化。局部DCE-MRI门静脉灌注信息被用作局部肝功能的成像生物标志物。四种候选炎症细胞因子被认为是生物学标志物。将成像和细胞因子纳入NTCP建模,并使用拟合优度指标评估其作用。仅使用剂量测定信息,与3级+酶变化相比,ALBI/C-P变化的LKB模型具有更陡的响应曲线。将门静脉灌注成像信息纳入PA模型以代表功能储备,与仅使用剂量模型相比,导致相对陡峭的剂量反应曲线。与ALBI/C-P变化相比,酶变化需要更大的灌注功能损失。在两种NTCP建模方法中,TGF-β1和嗜酸性粒细胞趋化因子表达的增加增加了预期风险的趋势,但未达到统计学显著性。与仅使用剂量模型相比,将成像和生物标志物纳入肝毒性的NTCP建模中可改善预期NTCP风险的估计。此外,这种广义的NTCP模型应该有助于更好地理解HCC SBRT患者的正常组织反应,并促进个性化治疗。
To develop NTCP models for hepatocellular cancer (HCC) patients who receive liver radiotherapy and to evaluate the potential role of pre- and during treatment functional imaging and blood-based circulating biological markers to improve the performance of these models. 192 HCC patients treated with radiation between 2005–2014 were evaluated: 146 received SBRT and 46 received conventional radiation to median physical tumor doses of 49.8 Gy and 50.4 Gy, respectively. Physical doses were converted into EQD2 for analysis. Two approaches were investigated for modeling NTCP: (a) a generalized Lyman-Kutcher-Burman (LKB) model; and (b) a generalization of the parallel architecture (PA) model. Three clinical endpoints were considered: change in ALBI, change in Child-Pugh (C-P) score and grade 3 or higher liver enzymatic changes. Local DCE-MRI portal venous perfusion information was used as an imaging biomarker for local liver function. Four candidate inflammatory cytokines were considered as biological markers. Imaging and cytokines were incorporated into NTCP modeling and their role was evaluated using goodness-of-fit metrics. Using dosimetric information only, the LKB model for ALBI/C-P change had a steeper response curve compared to grade3+ enzymatic changes. Incorporating portal venous perfusion imaging information into the PA model to represent functional reserve resulted in relatively steeper dose response curves compared to using dose only models. Larger loss of perfusion function was needed for enzymatic changes compared to ALBI/C-P changes. Increased TGF-β1 and Eotaxin expression increased the trend of expected risk in both NTCP modeling approaches but did not reach statistical significance. The incorporation of imaging and biological markers into NTCP modeling of liver toxicity improves estimates of expected NTCP risk compared to using dose only models. In addition, such generalized NTCP models should contribute to better understanding of normal tissue response in HCC SBRT patients and facilitate personalized treatment.
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