Mechanistic formulation of a lineal‐quadratic‐linear (LQL) model: Split‐dose experiments and exponentially decaying sources

Guerrero, Mariana; Carlone, Marco

doi:10.1118/1.3456927

Cited by 50 publications

(45 citation statements)

References 26 publications

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“…The biological parameters in this software were modified from LQL_equiv that were collected from seven radiotherapy treatment centers in France [6]. Before using this software to predict the treatment outcome, the user should understand and check the biological parameters carefully by considering the biological effect end point.…”

Section: Discussionmentioning

confidence: 99%

“…An increase in the overall treatment time affects the radiation tolerance of the early reacting tissues by repopulation. The survival fraction in the LQL model is described in Equation 1 where G (δ D )is the reduction in the survival due to interaction between lesions [6]. The LQL survival curve in the large dose region undergoes a change from the continuous bending of the LQ survival curve to the linear curve described in Equation 2 [6].…”

Section: Methodsmentioning

confidence: 99%

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Isobio software: biological dose distribution and biological dose volume histogram from physical dose conversion using linear-quadratic-linear model

Jaikuna¹,

Khadsiri²,

Chawapun³

et al. 2017

jcb

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PurposeTo develop an in-house software program that is able to calculate and generate the biological dose distribution and biological dose volume histogram by physical dose conversion using the linear-quadratic-linear (LQL) model.Material and methodsThe Isobio software was developed using MATLAB version 2014b to calculate and generate the biological dose distribution and biological dose volume histograms. The physical dose from each voxel in treatment planning was extracted through Computational Environment for Radiotherapy Research (CERR), and the accuracy was verified by the differentiation between the dose volume histogram from CERR and the treatment planning system. An equivalent dose in 2 Gy fraction (EQD2) was calculated using biological effective dose (BED) based on the LQL model. The software calculation and the manual calculation were compared for EQD2 verification with pair t-test statistical analysis using IBM SPSS Statistics version 22 (64-bit).ResultsTwo and three-dimensional biological dose distribution and biological dose volume histogram were displayed correctly by the Isobio software. Different physical doses were found between CERR and treatment planning system (TPS) in Oncentra, with 3.33% in high-risk clinical target volume (HR-CTV) determined by D90%, 0.56% in the bladder, 1.74% in the rectum when determined by D2cc, and less than 1% in Pinnacle. The difference in the EQD2 between the software calculation and the manual calculation was not significantly different with 0.00% at p-values 0.820, 0.095, and 0.593 for external beam radiation therapy (EBRT) and 0.240, 0.320, and 0.849 for brachytherapy (BT) in HR-CTV, bladder, and rectum, respectively.ConclusionsThe Isobio software is a feasible tool to generate the biological dose distribution and biological dose volume histogram for treatment plan evaluation in both EBRT and BT.

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Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Isobio software: biological dose distribution and biological dose volume histogram from physical dose conversion using linear-quadratic-linear model

Jaikuna¹,

Khadsiri²,

Chawapun³

et al. 2017

jcb

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“…It may be noted that models such as LQL, USC and PLQ assume homogeneous tumor sensitivity [29][30][31][32], though they are all amenable to extension including heterogeneous radiosensitivity. In the Results section we briefly describe results for heterogeneous versions of these models.…”

Section: Radiobiological Modelsmentioning

confidence: 99%

“…As examples of models which have been developed to describe the proposed and as yet not fully specified distinct tumoricidal mechanisms at high radiation doses, we used the Linear Quadratic Linear (LQL) [29,30], Universal Survival Curve (USC) [31], the Pade Linear Quadratic (PLQ) [32] formalisms (details are given in Appendix A).…”

Section: Radiobiological Modelsmentioning

confidence: 99%

“…The Linear Quadratic Linear (LQL) [29,30] model was developed to modify the LQ model through the replacement of the continuously bending terminal part of the dose response curve for the logarithm of cell survival by the corresponding exponential cell inactivation mode. This was accomplished by modification of the ''G-factor'' which represents damage repair between radiation dose fractions.…”

Section: Linear Quadratic Linear (Lql) Modelmentioning

confidence: 99%

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High-dose and fractionation effects in stereotactic radiation therapy: Analysis of tumor control data from 2965 patients

Shuryak¹,

Carlson²,

Brown³

et al. 2015

Radiotherapy and Oncology

117

107

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Volumetric reduction of brain metastases after stereotactic radiotherapy: Prognostic factors and effect on local control

Kanayama

Ikawa

2022

Cancer Medicine

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Background and Purpose Few reports include volumetric measurements as endpoints after stereotactic radiotherapy (SRT) despite the importance of such measurements. This study aimed to (1) investigate the impact of the volumetric response (specifically, an over 65% and over 90% volume reduction in brain metastases) at 6 months post‐SRT on local control and (2) identify the predictive factors for a volumetric response of over 65% and over 90%. Materials and Methods This study included 250 unresected brain metastases (>0.3 cc) treated with SRT. Doses were stratified according to the biological effective dose (BED). The BED was calculated using four models: linear‐quadratic (LQ): α/β = 10; LQ: α/β = 20; LQ cubic: α/β = 12; and LQ linear: α/β = 10. The median prescription dose was 30 Gy/3 fractions (BED20, 45). The median follow‐up time after SRT was 18.6 months (range, 6.4–81.8 months). Results In the multivariate analysis, over 65% volume reduction and over 90% volume reduction were prognostic factors for local control (hazard ratio: 2.370, p = 0.011 and hazard ratio: 3.161, p = 0.014, respectively). A dose of 80% of the gross tumor volume (GTV) D80 > BED20 58 was a predictive factor for over 65% and over 90% volume reductions (odds ratio: 1.975, p = 0.023; odds ratio: 3.204, p < 0.001, respectively). Conclusion Robust volume reduction of brain metastases at 6 months post‐SRT can predict local control. GTV D80 in the LQ model: α/β = 20 may be warranted for good volume reduction.

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Mechanistic formulation of a lineal‐quadratic‐linear (LQL) model: Split‐dose experiments and exponentially decaying sources

Cited by 50 publications

References 26 publications

Isobio software: biological dose distribution and biological dose volume histogram from physical dose conversion using linear-quadratic-linear model

Isobio software: biological dose distribution and biological dose volume histogram from physical dose conversion using linear-quadratic-linear model

High-dose and fractionation effects in stereotactic radiation therapy: Analysis of tumor control data from 2965 patients

Volumetric reduction of brain metastases after stereotactic radiotherapy: Prognostic factors and effect on local control

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