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:
影响因子:
--
通讯作者:
Ten Haken RK
中科院分区:
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
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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影响因子:
3.4
作者:
ANSCHER, MS;CROCKER, IR;JIRTLE, RL
通讯作者:
JIRTLE, RL
影响因子:
51.1
作者:
Chang, Joe Y.;Senan, Suresh;Paul, Marinus A.;Mehran, Reza J.;Louie, Alexander V.;Balter, Peter;Groen, Harry J. M.;McRae, Stephen E.;Widder, Joachim;Feng, Lei;van den Borne, Ben E. E. M.;Munsell, Mark F.;Hurkmans, Coen;Berry, Donald A.;van Werkhoven, Erik;Kresl, John J.;Dingemans, Anne-Marie;Dawood, Omar;Haasbeek, Cornelis J. A.;Carpenter, Larry S.;De Jaeger, Katrien;Komaki, Ritsuko;Slotman, Ben J.;Smit, Egbert F.;Roth, Jack A.
通讯作者:
Roth, Jack A.
影响因子:
1.8
作者:
Agresti, A;Coull, BA
通讯作者:
Coull, BA
DOI:
10.1016/j.ijrobp.2008.04.035
发表时间:
2009-01-01
影响因子:
7
作者:
Lee, Ik Jae;Seong, Jinsil;Han, Kwang Hyub
通讯作者:
Han, Kwang Hyub
DOI:
10.1016/j.ijrobp.2007.05.078
发表时间:
2008-01-01
影响因子:
7
作者:
Cao, Yue;Pan, Charlie;Lawrence, Theodore S.
通讯作者:
Lawrence, Theodore S.