The Experts below are selected from a list of 7833 Experts worldwide ranked by ideXlab platform
Salahuddin Ahmad - One of the best experts on this subject based on the ideXlab platform.
-
SU‐FF‐T‐491: Cell Survival Curve Fitting Techniques in High Dose Region for Use in Stereotactic Body Radiation Therapy (SBRT)
Medical Physics, 2009Co-Authors: F Mckenna, Salahuddin AhmadAbstract:Purpose: To select a Cell Survival Curve model that is capable of fitting Cell Survival at high dose region used in stereotactic body radiation therapy.Materials and Methods: Data from fourteen Cell lines were examined. These include a Chinese hamster Cell line, a human glioblastoma Cell line, two prostate Cell lines and ten lungcancer Cell lines. Each of these Cell lines were fitted to eight different models (4 with 2 parameters and 4 with three parameters) for Cell Survival. These models included among others the well known linear quadratic model and the single hit multi target model; and the more recent McKenna‐Ahmad repair model, Kavanagh‐Newman model and universal Survival Curve model. The χ2/df of each fit was compared to determine the model most appropriate for that Survival Curve. Results: No single model provided the best fit for all the Cell lines. For all Cell lines there were models that were superior to the linear quadratic. Two recent models (McKenna‐Ahmad repair model, Kavanagh‐Newman model) provided the best fits for many Cell lines. These models have low dose quadratic behavior which changes to linear behavior at high doses. The McKenna‐ Ahmad and Kavanagh‐Newman formulas for Cell Survival are respectively as follows: ln S = −βD 2 1 1 + β γ D ln S = −K 0 ( 1− e −K g D ) D .; Conclusion: We recommend that one of the two recent two parameter models be used for fitting Cell Survival Curves if one is primarily interested in Cell Survival into or past the shoulder region of the Cell Survival Curve.
-
su ff t 491 Cell Survival Curve fitting techniques in high dose region for use in stereotactic body radiation therapy sbrt
Medical Physics, 2009Co-Authors: F Mckenna, Salahuddin AhmadAbstract:Purpose: To select a Cell Survival Curve model that is capable of fitting Cell Survival at high dose region used in stereotactic body radiation therapy.Materials and Methods: Data from fourteen Cell lines were examined. These include a Chinese hamster Cell line, a human glioblastoma Cell line, two prostate Cell lines and ten lungcancer Cell lines. Each of these Cell lines were fitted to eight different models (4 with 2 parameters and 4 with three parameters) for Cell Survival. These models included among others the well known linear quadratic model and the single hit multi target model; and the more recent McKenna‐Ahmad repair model, Kavanagh‐Newman model and universal Survival Curve model. The χ2/df of each fit was compared to determine the model most appropriate for that Survival Curve. Results: No single model provided the best fit for all the Cell lines. For all Cell lines there were models that were superior to the linear quadratic. Two recent models (McKenna‐Ahmad repair model, Kavanagh‐Newman model) provided the best fits for many Cell lines. These models have low dose quadratic behavior which changes to linear behavior at high doses. The McKenna‐ Ahmad and Kavanagh‐Newman formulas for Cell Survival are respectively as follows: ln S = −βD 2 1 1 + β γ D ln S = −K 0 ( 1− e −K g D ) D .; Conclusion: We recommend that one of the two recent two parameter models be used for fitting Cell Survival Curves if one is primarily interested in Cell Survival into or past the shoulder region of the Cell Survival Curve.
-
SU‐FF‐T‐493: Can An Addition of a Simple Constant to Linear Quadratic Formula Improve Cell Survival Curve Fits for Some Cell Lines?
Medical Physics, 2009Co-Authors: F Mckenna, Salahuddin AhmadAbstract:Purpose: To investigate the effect of an unrecognized hyper radio‐sensitivity on radiobiological parameters α and β of the linear quadratic odel. Methods and Materials: A Chinese hamster Cell line designated “choaa8” and a lungcancer Cell line designated “ncih226” were fitted to the inear quadratic (LQ) model (lnS = −αD −βD2) and to a simple constant plus linear quadratic (CLQ) model (lnS = −c −αD −βD2). The χ2/df of each fit was compared to determine which model gives the best fit to the Cell Survival Curve. Results: The linear quadratic χ2/df for the “choaa8” and the “ncih226” are 1.55 and .095 respectively. The simple constant plus linear quadratic χ2/df for the “choaa8” and the “ncih226” are 1.18 and .075 respectively. So the addition of a simple constant to the linear quadratic formula provides greater than 20% improvement to the Survival Curve fits. The α/β _ratio for the LQ “choaa8” is 11.0, whereas the α/β _ratio for the CLQ “choaa8” is 5.4. The α/β _ratio for the LQ “ncih226” is 5.1, whereas the α/β _ratio for the CLQ “ncih226” is 0 indicating α = 0. So the addition of a simple constant in the linear quadraticformula can have a dramatic effect on the α/β _ratio._ Conclusion: CLQ provided superior fits compared to the LQ for the two data sets mentioned above. The value of the α/β _ratio was heavily dependent on whether or not an addition of a simple constant to linear quadratic formula was used. Further work is required to determine if the improved fit is due to actual physical phenomena such as hyper radio‐sensitivity or an alternative explanation like experimental error or noise in the data.
F Mckenna - One of the best experts on this subject based on the ideXlab platform.
-
SU‐FF‐T‐491: Cell Survival Curve Fitting Techniques in High Dose Region for Use in Stereotactic Body Radiation Therapy (SBRT)
Medical Physics, 2009Co-Authors: F Mckenna, Salahuddin AhmadAbstract:Purpose: To select a Cell Survival Curve model that is capable of fitting Cell Survival at high dose region used in stereotactic body radiation therapy.Materials and Methods: Data from fourteen Cell lines were examined. These include a Chinese hamster Cell line, a human glioblastoma Cell line, two prostate Cell lines and ten lungcancer Cell lines. Each of these Cell lines were fitted to eight different models (4 with 2 parameters and 4 with three parameters) for Cell Survival. These models included among others the well known linear quadratic model and the single hit multi target model; and the more recent McKenna‐Ahmad repair model, Kavanagh‐Newman model and universal Survival Curve model. The χ2/df of each fit was compared to determine the model most appropriate for that Survival Curve. Results: No single model provided the best fit for all the Cell lines. For all Cell lines there were models that were superior to the linear quadratic. Two recent models (McKenna‐Ahmad repair model, Kavanagh‐Newman model) provided the best fits for many Cell lines. These models have low dose quadratic behavior which changes to linear behavior at high doses. The McKenna‐ Ahmad and Kavanagh‐Newman formulas for Cell Survival are respectively as follows: ln S = −βD 2 1 1 + β γ D ln S = −K 0 ( 1− e −K g D ) D .; Conclusion: We recommend that one of the two recent two parameter models be used for fitting Cell Survival Curves if one is primarily interested in Cell Survival into or past the shoulder region of the Cell Survival Curve.
-
su ff t 491 Cell Survival Curve fitting techniques in high dose region for use in stereotactic body radiation therapy sbrt
Medical Physics, 2009Co-Authors: F Mckenna, Salahuddin AhmadAbstract:Purpose: To select a Cell Survival Curve model that is capable of fitting Cell Survival at high dose region used in stereotactic body radiation therapy.Materials and Methods: Data from fourteen Cell lines were examined. These include a Chinese hamster Cell line, a human glioblastoma Cell line, two prostate Cell lines and ten lungcancer Cell lines. Each of these Cell lines were fitted to eight different models (4 with 2 parameters and 4 with three parameters) for Cell Survival. These models included among others the well known linear quadratic model and the single hit multi target model; and the more recent McKenna‐Ahmad repair model, Kavanagh‐Newman model and universal Survival Curve model. The χ2/df of each fit was compared to determine the model most appropriate for that Survival Curve. Results: No single model provided the best fit for all the Cell lines. For all Cell lines there were models that were superior to the linear quadratic. Two recent models (McKenna‐Ahmad repair model, Kavanagh‐Newman model) provided the best fits for many Cell lines. These models have low dose quadratic behavior which changes to linear behavior at high doses. The McKenna‐ Ahmad and Kavanagh‐Newman formulas for Cell Survival are respectively as follows: ln S = −βD 2 1 1 + β γ D ln S = −K 0 ( 1− e −K g D ) D .; Conclusion: We recommend that one of the two recent two parameter models be used for fitting Cell Survival Curves if one is primarily interested in Cell Survival into or past the shoulder region of the Cell Survival Curve.
-
SU‐FF‐T‐493: Can An Addition of a Simple Constant to Linear Quadratic Formula Improve Cell Survival Curve Fits for Some Cell Lines?
Medical Physics, 2009Co-Authors: F Mckenna, Salahuddin AhmadAbstract:Purpose: To investigate the effect of an unrecognized hyper radio‐sensitivity on radiobiological parameters α and β of the linear quadratic odel. Methods and Materials: A Chinese hamster Cell line designated “choaa8” and a lungcancer Cell line designated “ncih226” were fitted to the inear quadratic (LQ) model (lnS = −αD −βD2) and to a simple constant plus linear quadratic (CLQ) model (lnS = −c −αD −βD2). The χ2/df of each fit was compared to determine which model gives the best fit to the Cell Survival Curve. Results: The linear quadratic χ2/df for the “choaa8” and the “ncih226” are 1.55 and .095 respectively. The simple constant plus linear quadratic χ2/df for the “choaa8” and the “ncih226” are 1.18 and .075 respectively. So the addition of a simple constant to the linear quadratic formula provides greater than 20% improvement to the Survival Curve fits. The α/β _ratio for the LQ “choaa8” is 11.0, whereas the α/β _ratio for the CLQ “choaa8” is 5.4. The α/β _ratio for the LQ “ncih226” is 5.1, whereas the α/β _ratio for the CLQ “ncih226” is 0 indicating α = 0. So the addition of a simple constant in the linear quadraticformula can have a dramatic effect on the α/β _ratio._ Conclusion: CLQ provided superior fits compared to the LQ for the two data sets mentioned above. The value of the α/β _ratio was heavily dependent on whether or not an addition of a simple constant to linear quadratic formula was used. Further work is required to determine if the improved fit is due to actual physical phenomena such as hyper radio‐sensitivity or an alternative explanation like experimental error or noise in the data.
-
su ff t 493 can an addition of a simple constant to linear quadratic formula improve Cell Survival Curve fits for some Cell lines
Medical Physics, 2009Co-Authors: F Mckenna, S AhmadAbstract:Purpose: To investigate the effect of an unrecognized hyper radio‐sensitivity on radiobiological parameters α and β of the linear quadratic odel. Methods and Materials: A Chinese hamster Cell line designated “choaa8” and a lungcancer Cell line designated “ncih226” were fitted to the inear quadratic (LQ) model (lnS = −αD −βD2) and to a simple constant plus linear quadratic (CLQ) model (lnS = −c −αD −βD2). The χ2/df of each fit was compared to determine which model gives the best fit to the Cell Survival Curve. Results: The linear quadratic χ2/df for the “choaa8” and the “ncih226” are 1.55 and .095 respectively. The simple constant plus linear quadratic χ2/df for the “choaa8” and the “ncih226” are 1.18 and .075 respectively. So the addition of a simple constant to the linear quadratic formula provides greater than 20% improvement to the Survival Curve fits. The α/β _ratio for the LQ “choaa8” is 11.0, whereas the α/β _ratio for the CLQ “choaa8” is 5.4. The α/β _ratio for the LQ “ncih226” is 5.1, whereas the α/β _ratio for the CLQ “ncih226” is 0 indicating α = 0. So the addition of a simple constant in the linear quadraticformula can have a dramatic effect on the α/β _ratio._ Conclusion: CLQ provided superior fits compared to the LQ for the two data sets mentioned above. The value of the α/β _ratio was heavily dependent on whether or not an addition of a simple constant to linear quadratic formula was used. Further work is required to determine if the improved fit is due to actual physical phenomena such as hyper radio‐sensitivity or an alternative explanation like experimental error or noise in the data.
Kenneth E. Ekstrand - One of the best experts on this subject based on the ideXlab platform.
-
The Hug–Kellerer equation as the universal Cell Survival Curve
Physics in Medicine and Biology, 2010Co-Authors: Kenneth E. EkstrandAbstract:The Hug–Kellerer (H-K) equation is one of the earliest proposed radiation Cell Survival Curves. We examine this equation in view of the recent perceived need for a universal Cell Survival Curve which would be applicable to single radiation fractions at high doses. We derive relationships between the three parameters of the H-K equation and the parameters α and β of the linear-quadratic equation. Using these relationships we show how the H-K equation can be used to determine single-fraction doses which are equivalent in theory to the dose in a conventional multi-fraction course of radiation therapy.
-
The Hug-Kellerer equation as the universal Cell Survival Curve.
Physics in medicine and biology, 2010Co-Authors: Kenneth E. EkstrandAbstract:The Hug–Kellerer (H-K) equation is one of the earliest proposed radiation Cell Survival Curves. We examine this equation in view of the recent perceived need for a universal Cell Survival Curve which would be applicable to single radiation fractions at high doses. We derive relationships between the three parameters of the H-K equation and the parameters α and β of the linear-quadratic equation. Using these relationships we show how the H-K equation can be used to determine single-fraction doses which are equivalent in theory to the dose in a conventional multi-fraction course of radiation therapy.
T Toda - One of the best experts on this subject based on the ideXlab platform.
-
WE‐A‐BRA‐05: Proton Ultra High Dose‐Rate Effect on HSG Cell Survival Curve
Medical Physics, 2010Co-Authors: Taeko Matsuura, Y Egashira, Teiji Nishio, R Kohno, Satoru Kameoka, R Ohta, K Matsumura, H Suzuki, T Taniyama, T TodaAbstract:Purpose: One of the important issues that we are facing in the current radiation process is the long treatment time for irradiating protons to the tumor moving with respiration. In order to improve this problem, we are currently developing the highly precise and very short time protonIGRT using the high intensity beam from cyclotron and the real‐time images acquired by two flat panel detectors attached to the gantry. The dose‐rate by using this method will reach 10 to 100 times of the present one. The purpose of this study is to investigate the relative biological effectiveness (RBE) of HSG Cell in such an ultra high dose‐rate regime and its LET dependence by using the colony assay method. Material and method: We attached the HSG Cells at the bottom of the plastic chamber, and irradiated the spatially and temporally homogeneous proton beam. We used 235MeV proton beams with the different beam current of 10nA and 300nA in order to study the dose‐rate effect. The chamber was molded in a Polyethylene block with a hole which fits tightly to the chamber. It was placed at plateau(1.75, 114Gy/min, yD=0.56keV/ m), then at Bragg‐peak(8, 325Gy/min, yD=3.19keV/ m) to see the LET dependence of RBE at high dose‐rate.Result: There were no significant splits observed in Survival Curves of HSG Cell over the protondose‐rate. The ratio of RBE at lower dose‐rate to that at higher dose‐rate was 0.98−+0.08 at Bragg‐peak and was 0.96−+0.11 at plateau. On the other hand, the RBE ratio at Bragg‐peak to plateau was 1.13–1.20, which suggests that the position dependence of RBE cannot be neglected. Conclusion: We conclude that in the therapeutic planning of high dose‐rateradiation, the present RBE can be consistently used. Instead, the RBE enhancement toward the Bragg‐peak and beyond should be reconsidered.
-
we a bra 05 proton ultra high dose rate effect on hsg Cell Survival Curve
Medical Physics, 2010Co-Authors: Taeko Matsuura, Y Egashira, Teiji Nishio, R Kohno, Satoru Kameoka, R Ohta, K Matsumura, H Suzuki, T Taniyama, T TodaAbstract:Purpose: One of the important issues that we are facing in the current radiation process is the long treatment time for irradiating protons to the tumor moving with respiration. In order to improve this problem, we are currently developing the highly precise and very short time protonIGRT using the high intensity beam from cyclotron and the real‐time images acquired by two flat panel detectors attached to the gantry. The dose‐rate by using this method will reach 10 to 100 times of the present one. The purpose of this study is to investigate the relative biological effectiveness (RBE) of HSG Cell in such an ultra high dose‐rate regime and its LET dependence by using the colony assay method. Material and method: We attached the HSG Cells at the bottom of the plastic chamber, and irradiated the spatially and temporally homogeneous proton beam. We used 235MeV proton beams with the different beam current of 10nA and 300nA in order to study the dose‐rate effect. The chamber was molded in a Polyethylene block with a hole which fits tightly to the chamber. It was placed at plateau(1.75, 114Gy/min, yD=0.56keV/ m), then at Bragg‐peak(8, 325Gy/min, yD=3.19keV/ m) to see the LET dependence of RBE at high dose‐rate.Result: There were no significant splits observed in Survival Curves of HSG Cell over the protondose‐rate. The ratio of RBE at lower dose‐rate to that at higher dose‐rate was 0.98−+0.08 at Bragg‐peak and was 0.96−+0.11 at plateau. On the other hand, the RBE ratio at Bragg‐peak to plateau was 1.13–1.20, which suggests that the position dependence of RBE cannot be neglected. Conclusion: We conclude that in the therapeutic planning of high dose‐rateradiation, the present RBE can be consistently used. Instead, the RBE enhancement toward the Bragg‐peak and beyond should be reconsidered.
Meinhard Nevinnystickel - One of the best experts on this subject based on the ideXlab platform.
-
applicability of the linear quadratic formalism for modeling local tumor control probability in high dose per fraction stereotactic body radiotherapy for early stage non small Cell lung cancer
Radiotherapy and Oncology, 2013Co-Authors: Matthias Guckenberger, Rainer J Klement, Michael Allgauer, Steffen Appold, Karin Dieckmann, Iris Ernst, Ute Ganswindt, Richard Holy, U Nestle, Meinhard NevinnystickelAbstract:Background and purpose: To compare the linear-quadratic (LQ) and the LQ-L formalism (linear Cell Survival Curve beyond a threshold dose dT) for modeling local tumor control probability (TCP) in stereotactic body radiotherapy (SBRT) for stage I non-small Cell lung cancer (NSCLC). Materials and methods: This study is based on 395 patients from 13 German and Austrian centers treated with SBRT for stage I NSCLC. The median number of SBRT fractions was 3 (range 1–8) and median single fraction dose was 12.5 Gy (2.9–33 Gy); dose was prescribed to the median 65% PTV encompassing isodose (60–100%). Assuming an a/b-value of 10 Gy, we modeled TCP as a sigmoid-shaped function of the biologically effective dose (BED). Models were compared using maximum likelihood ratio tests as well as Bayes factors (BFs). Results: There was strong evidence for a dose–response relationship in the total patient cohort (BFs > 20), which was lacking in single-fraction SBRT (BFs 20). Conclusion: Our data suggest accurate modeling of local tumor control in fractionated SBRT for stage I NSCLC with the traditional LQ formalism.