1328 poster THE EFFECT OF PHOTON BEAM ENERGY ON VMAT TREATMENT PLAN QUALITY FOR ADVANCED PROSTATE CANCER

AbstractPurpose: To evaluate composite coplanar and non-coplanar three-dimensional conformal techniques (3D-CRT) for external-beam prostate radiotherapy using a low-energy (6 MV) photon beam.Methods and Materials: For treatment-planning purposes, three different planning target volumes (PTV) were defined for ten patients with prostate cancer and as follows: PTV1 (pelvis), PTV2 (prostate + seminal vesicles + 1 cm margin) and PTV3 (prostate + 1 cm margin). Conformal techniques of 2, 3, 4, 5 (coplanar) and 6 (non-coplanar) field techniques have been considered and combined to produce five different plan combinations (i.e. techniques A, B, C, D and E). Treatment plans were generated with a prescription dose of 75 Gy to PTV3, 65 Gy to PTV2 and 45 Gy to PTV1 and were assessed on the basis of 3D dose distributions and dose-volume histograms (DVHs). Normal tissue-dose constraints for the relevant organs at risk (OARs), that is, rectum, bladder and femoral heads, were also considered.Results: Findings show that all five treatment-plan combinations result in adequate PTV coverage and acceptable OAR irradiated volumes. The greatest rectal spacing in the high-dose region is achieved by technique C; all techniques achieve this, except for technique A, and give approximately the same fraction of volume (of rectum) that receives a dose of 50 Gy (V50) and 60 Gy (V60). When considering the bladder, techniques B, D and E give the best bladder sparing with small absolute differences, whereas technique A results in the lowest dose for femoral heads. Technique E appears to give the best compromise for all three considered OARs, provided the PTV is adequately covered.Conclusions: Even though the optimum photon-beam energy for conformal prostate radiotherapy is greater than 10 MV, our study shows that a good sparing of OAR can be achieved even with a lower-energy beam (6 MV) and the appropriate plan combination and that the dose to prostate can be as high as 75 Gy.

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Predicting Advanced Prostate Cancer from Modeling Early Indications in Biopsy and Prostatectomy Samples via Transductive Semi-Supervised Survival Analysis

BioMed Research International ◽

10.1155/2018/2178645 ◽

2018 ◽

Vol 2018 ◽

pp. 1-12

Author(s):

Faisal M. Khan

Keyword(s):

Prostate Cancer ◽

Survival Analysis ◽

Cancer Progression ◽

Advanced Prostate Cancer ◽

Complex Disease ◽

Treatment Plan ◽

The United States ◽

Censored Samples ◽

Psa Recurrence ◽

Regression Techniques

Prostate cancer is the most prevalent form of cancer and the second most common cause of cancer deaths among men in the United States. Accurate prognosis is important as it is the principal factor in determining the treatment plan. Prostate cancer is a complex disease which advances in stages. While clinical failure (including metastasis) is a significant endpoint following a radical prostatectomy, it can often take years to manifest, usually too late to be optimistically treated. In practice, the earlier endpoint of PSA Recurrence is frequently used as a surrogate in prognostic modeling. The central issue in these models is managing censored observations which challenge traditional regression techniques. The true target times of a majority of instances are unknown; what is known is a censored target representing some earlier indeterminate time. In this work we apply a novel transduction approach for semi-supervised survival analysis which has previously been shown to be powerful in medical prognosis. The approach considers censored samples as semi-supervised regression targets leveraging the partial nature of unsupervised information. We explore the use of this approach in building prostate cancer progression models from multimodal characteristics extracted from both biopsy and prostatectomy tissues samples. In this work, the approach leads to a significant increase in performance for predicting advanced prostate cancer from earlier endpoints and may also be useful in other diseases for predicting advanced endpoints from earlier stages of the disease.

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