Bai H, Wang L, Li W, Liu X, Xia Y, Chang L. Test the Effectiveness of Quantitative Linear-Quadratic-Based (qLQB) Model on Evaluating Irradiation-Induced Liver Injury (ILI) Against Normal Tissue Complication Probability (NTCP).
Dose Response 2020;
18:1559325820961721. [PMID:
33013252 PMCID:
PMC7513411 DOI:
10.1177/1559325820961721]
[Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2020] [Accepted: 08/31/2020] [Indexed: 11/23/2022] Open
Abstract
Objectives:
To test the effectiveness of quantitative linear-quadratic-based (qLQB) model
on evaluating irradiation-induced liver injury (ILI) and establish the
relation between the damaged ratio/percent (DRP) in qLQB model and normal
tissue complication probility (NTCP).
Materials and Methods:
We established the qLQB model to calculate the ratio/percent (RP) between
damaged cell/functional subunit (FSU) and entire cell/FSU of liver for
radiation dose response, tested the qLQB against the Lyman-Kutcher-Burman
(LKB) model, and established relation between the RP and NTCP through
analyzing the dose of 32 patients with cancer of abdominal cavity who were
treated with radiation therapy at our department. Based on varied α/β and
varied parameters for NTCP, we put the calculated results into varied arrays
for the next analysis. We named the 2 groups of RPs: RP1 (α/β = 3.0, α =
0.03) and RP2 (α/β = 8.0, α = 0.26), and named the 2 groups of NTCPs: NTCP1
(n = 0.32, m = 0.15, TD50(1) = 4000 cGy) and NTCP2 (n = 1.10, m = 0.28,
TD50(1) = 4050 cGy).
Results:
Spearman correlation analysis was used to analyze the correlations among the
groups, the results were as follows: RP1 vs NTCP1, rs = 0.83827, p <
0.0001; RP1 vs NTCP2, rs = 0.83827, p < 0.0001; RP2 vs NTCP2, rs =
0.79289, p < 0.0001; and RP2 vs NTCP1, rs = 0.79289, p < 0.0001.
Conclusions:
There is a significant correlation between RP value and NTCP for evaluating
ILI, and there is no difference between qLQB model and LKB model on
evaluating ILI.
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