TY - JOUR
T1 - Use of 3D biological effective dose (BED) for optimizing multi-target liver cancer treatments
AU - Kauweloa, Kevin I.
AU - Bergamo, Angelo
AU - Gutierrez, Alonso N.
AU - Stathakis, Sotiris
AU - Papanikolaou, Nikos
AU - Mavroidis, Panayiotis
N1 - Publisher Copyright:
© 2019, Australasian College of Physical Scientists and Engineers in Medicine.
PY - 2019/9/15
Y1 - 2019/9/15
N2 - The purpose is to calculate the composite 3D biological effective dose (BED) distribution in healthy liver, when multiple lesions are treated concurrently with different hypo-fractionated schemes and stereotactic body radiation therapy, and to investigate the potential of biological based plan optimization. Two patients, each having two tumors that were treated sequentially with different treatment plans, were selected. The treatment information of both treatment plans of the patients was used and their dose matrices were exported to an in-house MATLAB software, which was used to calculate the composite BED distribution. The composite BED distributions were used to determine if the healthy liver received BED beyond tolerance. When the dose to the minimum critical volume was less than tolerance, an optimization code was used to derive the scaling factors (ScF) that should be applied to the dose matrix of each plan until the minimum critical volume of healthy liver reaches a BED close to tolerance. It was shown that for each patient, there is a margin for dose escalation regarding the doses to the individual targets. More specifically, the ScFs of the doses range between 5.6 and 99 in the first patient, whereas for the second patient, the ScFs of the optimal doses range between 12.7 and 35.6. The present study indicates that there is a significant margin for dose escalation without increasing the radiation toxicity to the healthy liver. Also, the calculation of the composite BED distribution can provide additional information that may lead to a better assessment of the liver’s tolerance to different fractionation schemes and prescribed doses as well as more clinically relevant treatment plan optimization.
AB - The purpose is to calculate the composite 3D biological effective dose (BED) distribution in healthy liver, when multiple lesions are treated concurrently with different hypo-fractionated schemes and stereotactic body radiation therapy, and to investigate the potential of biological based plan optimization. Two patients, each having two tumors that were treated sequentially with different treatment plans, were selected. The treatment information of both treatment plans of the patients was used and their dose matrices were exported to an in-house MATLAB software, which was used to calculate the composite BED distribution. The composite BED distributions were used to determine if the healthy liver received BED beyond tolerance. When the dose to the minimum critical volume was less than tolerance, an optimization code was used to derive the scaling factors (ScF) that should be applied to the dose matrix of each plan until the minimum critical volume of healthy liver reaches a BED close to tolerance. It was shown that for each patient, there is a margin for dose escalation regarding the doses to the individual targets. More specifically, the ScFs of the doses range between 5.6 and 99 in the first patient, whereas for the second patient, the ScFs of the optimal doses range between 12.7 and 35.6. The present study indicates that there is a significant margin for dose escalation without increasing the radiation toxicity to the healthy liver. Also, the calculation of the composite BED distribution can provide additional information that may lead to a better assessment of the liver’s tolerance to different fractionation schemes and prescribed doses as well as more clinically relevant treatment plan optimization.
KW - BED
KW - Biological
KW - Liver cancer radiotherapy
KW - Multi-phase treatment protocols
KW - Optimization
UR - https://www.scopus.com/pages/publications/85068863536
UR - https://www.scopus.com/pages/publications/85068863536#tab=citedBy
U2 - 10.1007/s13246-019-00771-4
DO - 10.1007/s13246-019-00771-4
M3 - Article
C2 - 31297729
AN - SCOPUS:85068863536
SN - 0158-9938
VL - 42
SP - 711
EP - 718
JO - Australasian Physical and Engineering Sciences in Medicine
JF - Australasian Physical and Engineering Sciences in Medicine
IS - 3
ER -