Optimisation of delivery efficiency in prostate intensity modulated radiotherapy planning
| dc.contributor.advisor | Muhammed, Omer Abdul-Aziz Ali | |
| dc.contributor.advisor | Rae, William Ian Duncombe | |
| dc.contributor.author | Fourie, Nicola Sieglinde | |
| dc.date.accessioned | 2016-09-09T08:31:37Z | |
| dc.date.available | 2016-09-09T08:31:37Z | |
| dc.date.issued | 2016-02 | |
| dc.description.abstract | English: Evidence that supports dose escalation for prostate cancer is growing and with Intensity Modulated Radiation Therapy (IMRT) higher conformal target doses can be delivered. With more segments and higher monitor units (MU’s), target conformity can be improved, however this results in longer delivery times, which makes it difficult to ensure accurate dose delivery, as intra-fractional as well as target movement plays an increasing role. Evidence from the literature indicates that secondary radiation-induced cancer risk is proportional to the beam-on time (thus the MU’s). Improvements in IMRT delivery efficiency while maintaining plan quality can be achieved by reducing the complexity of an IMRT plan. This can be done by changing the optimization parameters during the optimization process. Less “complex” prostate IMRT plans will require fewer MU’s by using less segments resulting in shorter delivery times and therefore reduced risk of secondary cancers. The goal of this study was to recommend a set of optimization parameter values that will improve the delivery efficiency of prostate IMRT treatment plan while maintaining plan quality. Fifteen clinical prostate IMRT plans (15 MV), already used for treatment, were re-optimized, using a XiO treatment planning system (TPS). Changes in total MU’s and segments were evaluated for changes in some of the optimization parameter values. Eleven optimization parameters (some of them used more than once with different values) were used to generate 15 new IMRT combination plans (ICP’s) for each patient for both 6 and 15 MV, resulting in 450 plans being assessed. One parameter was changed at a time while all other variables were kept constant. Plan quality was evaluated in terms of four variables: MU, number of segments, homogeneity index and conformity index while the delivery efficiency was evaluated in terms of delivery time. To our knowledge no time delivery model has been proposed for a Siemens® ARTISTETM Linear Accelerator (Linac). Using the principles given in the literature we derived such a time delivery model by adding the radio frequency wave component and Multi Leaf Collimator delay time. K-means clustering was then used to analyse the data in terms of the five variables and the top 10 ICP’s in 3 patients in terms of a faster more conformal, delivered plan were identified. To confirm the delivery efficiency and accuracy, the fluences of these top 10 ICP’s were measured on a Siemens® ARTISTETM Linac with the step and shoot method and compared to the treatment planning system’s fluences. The evaluation criteria chosen were 3% and 3 mm, distance to agreement. A 3 dimensional dose volume histogram program was used to determine the percentage pass rates on the planned target volumes and the organs at risk. The optimization parameters such as the minimum MU’s per segment, intensity level, minimum segment size and minimum segment area; demonstrated the greatest influence on the total number of segments, while the total MU’s was most greatly influenced by the filters and intensity level optimization parameter. Controversy exists regarding which energy should be used, 6 MV or 15 MV, when treating prostate cancer. Both energies were considered here during the optimization process and it was concluded that the optimization parameters are not greatly influenced by the beam energy. However, it was seen that beam arrangement has an influence on optimization parameter behaviour. A limitation of this study is that the beam angle distribution was not investigated. Thus recommendations could be made in terms of which ICP demonstrated the most improved delivery efficiency of a prostate IMRT treatment plan while maintaining plan quality. The optimisation parameter which was introduced to the optimization process was a General High filter. Gaining knowledge about the behaviour of the optimization parameters during optimization makes it easier to advise and assist treatment planners preparing complex IMRT plans. | en_ZA |
| dc.description.abstract | Afrikaans: Volgens die literatuur kan ʼn verhoogte dosis vir die behandeling van prostaat kanker voordelig wees. Dit kan bereik word met die Intensiteit Gemoduleerde Stralings Tegniek (IMRT). Met die tegniek is verhoogte gekonformeerde teiken dosisse moontlik, maar dit lei tot vermeerdering van totale monitor eenhede (ME’e) en totale segmente, wat weer langer behandelings tyd tot gevolg het. Met langer behandelings tyd begin pasiënt beweging ʼn rol speel en word die akkuraatheid van behandeling beïnvloed. Daar is ook bewyse in die literatuur dat sekondêre geïnduseerde kankers proporsioneel is aan die bundel behandelings tyd of totale ME’e. Indien totale ME’e en segmente verminder kan word vir ʼn prostaat behandelings plan, sal dit lei na verkorte behandelings tye en die risiko verlaag vir sekondêre kankers. Dus is dit moontlik om ʼn minder gekompliseerde plan te skep maar steeds plan gehalte en doeltreffendheid te behou. Volgens die literatuur is dit moontlik wanneer die optimering parameters verander word gedurende die optimerings proses. Die doel van hierdie studie was om ʼn stel optimerings parameters voor te stel wat meer doeltreffend sal wees vir prostaat behandeling, maar nie inboet op plan gehalte nie. Vyftien prostaat IMRT planne (15 MV), wat reeds behandeling ontvang het, is heroptimeer met ʼn XiO beplannings sisteem. Elf optimerings parameters, sommige meer as een keer, was gebruik om 15 nuwe IMRT planne te skep, let wel net een parameter is verander op ʼn keer. Dis gedoen vir elke pasiënt en beide energieë (6 MV en 15 MV) gevolg, 450 nuwe planne. Die veranderinge in totale ME en segmente is waargeneem tydens heroptimering. Vier veranderlikes is gekies om plan gehalte te evalueer naamlik; ME, segmente, homogene indeks en gekonformeerde indeks. Terwyl die behandelings doeltreffendheid geevalueer is deur behandelings tyd. Sover ons kennis strek was daar nog geen behandelings tyd model geskep vir ʼn Siemens® ARTISTETM versneller nie. Met die beginsels wat verskaf word in die literatuur is ʼn behandelings tyd model geskep. Die radio frekwensie golf komponent en die veelvuldige blaar kollimator se vertraagde tyd is bygevoeg. K-gemiddelde tros analise was gedoen op die vyf veranderlikes vir elke pasiënt. Die top 10 kombinasie IMRT planne wat vinniger en ʼn beter gekonformeerde teiken dosis gehad het is geïdentifiseer. Die tydvloed van die top 10 geïdentifiseerde IMRT planne is gemeet op ʼn Siemens® ARTISTETM versneller en vergelyk met die beplannings stelsel se tydvloed deur ʼn 3% en 3 mm kriteria te gebruik. ʼn Rekenaar program (3-dimensionele volume histogram) was gebruik om die tydvloed te analiseer en die dosisse op die teiken orgaan (prostaat) en risiko organe te evalueer. Die optimerings parameters soos die minimum ME’e per segment, intensiteit vlakke, minimum segment grootte en minimum segment area; het ʼn groot invloed gehad op totale segmente. Terwyl die totale ME’e meestal beïnvloed is deur filters en intensiteit vlakke. Daar heers kontroversie oor wat die beste energie is om prostaat kanker te behandel, 6 MV of 15 MV. Beide energieë was gebruik gedurende die optimerings proses en daar is bevind dat die optimerings parameters word nie deur energie beïnvloed nie. Alhoewel, bundel verdeling het wel ʼn invloed gehad op die uitkoms van die optimerings parameters. ʼn Tekortkoming van hierdie studie was om die invloed wat bundel verspreiding op optimerings parameters het, te ondersoek. Die beste kombinasie plan is wanneer die algemene hoë filter in gestel was gedurende die optimerings proses, want behandelings doeltreffendheid is verbeter terwyl plan gehalte behoue gebly het. Gedurende hierdie studie was kennis ook versamel ten opsigte van die optimering parameters se gedrag. Dus sal dit moontlik wees om advies te kan gee aan beplanners ten opsigte van ʼn gekompliseerde IMRT plan. | af |
| dc.identifier.uri | http://hdl.handle.net/11660/4064 | |
| dc.language.iso | en | en_ZA |
| dc.publisher | University of the Free State | en_ZA |
| dc.rights.holder | University of the Free State | en_ZA |
| dc.subject | Prostate treatment | en_ZA |
| dc.subject | Optimization process | en_ZA |
| dc.subject | Time delivery model | en_ZA |
| dc.subject | IMRT | en_ZA |
| dc.subject | Radiation therapy planning | en_ZA |
| dc.subject | XiO planning | en_ZA |
| dc.subject | Cluster analysis | en_ZA |
| dc.subject | Homogeneity index | en_ZA |
| dc.subject | Conformity index | en_ZA |
| dc.subject | Radiotherapy | en_ZA |
| dc.subject | Prostate cancer--Treatment | en_ZA |
| dc.subject | Dissertation (M.Med.Sc. (Medical Physics))--University of the Free State, 2016 | en_ZA |
| dc.title | Optimisation of delivery efficiency in prostate intensity modulated radiotherapy planning | en_ZA |
| dc.type | Dissertation | en_ZA |