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PurposeTo develop an in-house software program that is able to calculate and generate the biological dose distribution and biological dose volume histogram by physical dose conversion using the linear-quadratic-linear (LQL) model.Material and methodsThe Isobio software was developed using MATLAB version 2014b to calculate and generate the biological dose distribution and biological dose volume histograms. The physical dose from each voxel in treatment planning was extracted through Computational Environment for Radiotherapy Research (CERR), and the accuracy was verified by the differentiation between the dose volume histogram from CERR and the treatment planning system. An equivalent dose in 2 Gy fraction (EQD2) was calculated using biological effective dose (BED) based on the LQL model. The software calculation and the manual calculation were compared for EQD2 verification with pair t-test statistical analysis using IBM SPSS Statistics version 22 (64-bit).ResultsTwo and three-dimensional biological dose distribution and biological dose volume histogram were displayed correctly by the Isobio software. Different physical doses were found between CERR and treatment planning system (TPS) in Oncentra, with 3.33% in high-risk clinical target volume (HR-CTV) determined by D90%, 0.56% in the bladder, 1.74% in the rectum when determined by D2cc, and less than 1% in Pinnacle. The difference in the EQD2 between the software calculation and the manual calculation was not significantly different with 0.00% at p-values 0.820, 0.095, and 0.593 for external beam radiation therapy (EBRT) and 0.240, 0.320, and 0.849 for brachytherapy (BT) in HR-CTV, bladder, and rectum, respectively.ConclusionsThe Isobio software is a feasible tool to generate the biological dose distribution and biological dose volume histogram for treatment plan evaluation in both EBRT and BT.

Radiation therapy is an important local cytotoxic modality for cancer treatment whose aim is to control the disease while minimising damage to normal tissue. The combination of different treatment modalities offers a more effective cure and reduction in normal tissue toxicity. However, the differences in genetic profiles can cause diverse treatment outcomes. Multidisciplinary research, where technologies and knowledge from different areas are integrated, is necessary to design the optimal regimen for individualised cancer treatment. This paper offers an overview of some new cancer treatment strategies; the impact of molecular imaging on radiation oncology; and a computer simulation model to optimise treatment planning based on patient information. It briefly discusses molecular targeted therapy, tumour microenvironment and bioreductive agents, and evidence for making individualised medicine a reality. Using DNA microarrays and proteomic technologies, information on defined molecular targets and genetic profiling for individual patients can be obtained and new algorithms for radiation oncology-related diagnosis, treatment response and prognosis can be developed.

Severe combined immunodeficiency (SCID) cells are hypersensitive to killing by ionizing radiation because of deregulation of DNA-dependent protein kinase (DNA-PK) and a concomitant deficiency in the repair of DNA double-strand breaks. The effect of this condition on the neoplastic transformation of SCID fibroblasts, designated SCID 3T1, has been investigated. The spontaneous transformation rate was approximately 2 x 10(-5) at early passages and increased up to approximately 7 x l0(-3) at later passages. The radiation survival curves of transformed cells had thresholds and therefore appeared to be qualitatively similar to the survival curves of C3H 10T(1/2) mouse fibroblast cells, but the initial slopes were steeper. In contrast, per unit dose, SCID cells were more sensitive to transformation than 10T(1/2) cells. Eight transformed clones were tested for tumorigenicity, and all produced fibrosarcomas in athymic nude mice. Properties associated with the tumor suppressor Trp53 (formerly known as p53) were examined in three of the clones. In these clones, although Trp53 protein was overexpressed, a lower expression of Cdkn1a (formerly known as p21, Cip1) protein was observed compared to parental cells. The expression of Trp53 and Cdkn1a and the G(1)-phase arrest (one set of data on G(1)-phase delay is included as an example) was not induced by ionizing radiation in these transformed clones; each clone carried a point mutation in Trp53. This suggests that the deficiency in the repair of DNA double-strand breaks increased the tumorigenicity and the genomic instability of transformed SCID cells.

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