Validation of dose distribution computation on sCT images generated from MRI scans by Philips MRCAT.
MRCAT
Prostate cancer
Radiotherapy
sCT
Journal
Reports of practical oncology and radiotherapy : journal of Greatpoland Cancer Center in Poznan and Polish Society of Radiation Oncology
ISSN: 1507-1367
Titre abrégé: Rep Pract Oncol Radiother
Pays: Poland
ID NLM: 100885761
Informations de publication
Date de publication:
Historique:
received:
14
09
2018
revised:
26
11
2018
accepted:
07
02
2019
entrez:
13
3
2019
pubmed:
13
3
2019
medline:
13
3
2019
Statut:
ppublish
Résumé
To evaluate calculation of treatment plans based on synthetic-CT (sCT) images generated from MRI. Because of better soft tissue contrast, MR images are used in addition to CT images for radiotherapy planning. However, registration of CT and MR images or repositioning between scanning sessions introduce systematic errors, hence suggestions for MRI-only therapy. The lack of information on electron density necessary for dose calculation leads to sCT (synthetic CT) generation. This work presents a comparison of dose distribution calculated on standard CT and sCT. 10 prostate patients were included in this study. CT and MR images were collected for each patient and then water equivalent (WE) and MRCAT images were generated. The radiation plans were optimized on CT and then recalculated on MRCAT and WE data. 2D gamma analysis was also performed. The mean differences in the majority of investigated DVH points were in order of 1% up to 10%, including both MRCAT and WE dose distributions. Mean gamma pass for acceptance criteria 1%/1 mm were greater than 82.5%. Prescribed doses for target volumes and acceptable doses for organs at risk were met in almost all cases. The dose calculation accuracy on MRCAT was not significantly compromised in the majority of clinical relevant DVH points. The introduction of MRCAT into practise would eliminate systematic errors, increase patients' comfort and reduce treatment expenses. Institutions interested in MRCAT commissioning must, however, consider changes to established workflow.
Sections du résumé
AIM
OBJECTIVE
To evaluate calculation of treatment plans based on synthetic-CT (sCT) images generated from MRI.
BACKGROUND
BACKGROUND
Because of better soft tissue contrast, MR images are used in addition to CT images for radiotherapy planning. However, registration of CT and MR images or repositioning between scanning sessions introduce systematic errors, hence suggestions for MRI-only therapy. The lack of information on electron density necessary for dose calculation leads to sCT (synthetic CT) generation. This work presents a comparison of dose distribution calculated on standard CT and sCT.
MATERIALS AND METHODS
METHODS
10 prostate patients were included in this study. CT and MR images were collected for each patient and then water equivalent (WE) and MRCAT images were generated. The radiation plans were optimized on CT and then recalculated on MRCAT and WE data. 2D gamma analysis was also performed.
RESULTS
RESULTS
The mean differences in the majority of investigated DVH points were in order of 1% up to 10%, including both MRCAT and WE dose distributions. Mean gamma pass for acceptance criteria 1%/1 mm were greater than 82.5%. Prescribed doses for target volumes and acceptable doses for organs at risk were met in almost all cases.
CONCLUSIONS
CONCLUSIONS
The dose calculation accuracy on MRCAT was not significantly compromised in the majority of clinical relevant DVH points. The introduction of MRCAT into practise would eliminate systematic errors, increase patients' comfort and reduce treatment expenses. Institutions interested in MRCAT commissioning must, however, consider changes to established workflow.
Identifiants
pubmed: 30858769
doi: 10.1016/j.rpor.2019.02.001
pii: S1507-1367(19)30016-1
pmc: PMC6396091
doi:
Types de publication
Journal Article
Langues
eng
Pagination
245-250Références
Med Phys. 2005 Feb;32(2):473-82
pubmed: 15789594
Int J Radiat Oncol Biol Phys. 2005 Jun 1;62(2):406-17
pubmed: 15890582
Med Phys. 2012 Nov;39(11):6701-11
pubmed: 23127064
Radiat Oncol. 2014 Jan 09;9:16
pubmed: 24405515
Int J Radiat Oncol Biol Phys. 2015 Dec 1;93(5):1144-53
pubmed: 26581150
Phys Med Biol. 2017 Apr 21;62(8):2961-2975
pubmed: 27983520
Phys Med Biol. 2017 Feb 7;62(3):948-965
pubmed: 28076338
Radiat Oncol. 2017 Jan 26;12(1):28
pubmed: 28126030
Med Phys. 2017 Apr;44(4):1408-1419
pubmed: 28192624
Acta Oncol. 2017 Jun;56(6):792-798
pubmed: 28270011
Acta Oncol. 2017 Jun;56(6):787-791
pubmed: 28464739
Int J Radiat Oncol Biol Phys. 2018 Jan 1;100(1):199-217
pubmed: 29254773
Rep Pract Oncol Radiother. 2019 Jan-Feb;24(1):28-34
pubmed: 30337845