This project developed and validated an automated pipeline for prostate treatments to accurately determine which patients could benefit from adaptive radiotherapy (ART) using synthetic CTs (sCTs) generated from on-treatment cone-beam CT (CBCT) images.

The automated pipeline converted CBCTs to sCTs utilising deep-learning, for accurate dose recalculation. Deformable image registration mapped contours from the planning CT to the sCT, with the treatment plan recalculated. A pass/fail assessment used relevant clinical goals. A fail threshold indicated ART was required. All acquired CBCTs (230 sCTs) for 31 patients (6 who had ART) were assessed for pipeline accuracy and clinical viability, comparing clinical outcomes to pipeline outcomes.

The pipeline distinguished patients requiring ART; 74·4% of sCTs for ART patients were red (failure) results, compared to 6·4% of non-ART sCTs. The receiver operator characteristic area under curve was 0·98, demonstrating high performance. The automated pipeline was statistically significantly (p < 0·05) quicker than the current clinical assessment methods (182·5s and 556·4s, respectively), and deformed contour accuracy was acceptable, with 96·6% of deformed clinical target volumes (CTVs) clinically acceptable.

The automated pipeline identified patients who required ART with high accuracy while reducing time and resource requirements. This could reduce departmental workload and increase efficiency and personalisation of patient treatments. Further work aims to apply the pipeline to other treatment sites and investigate its potential for taking into account dose accumulation.

A comprehensive analysing method has been required since long in the field of radiotherapy. The basic purpose of all techniques has been to deliver the prescribed dose safely to the target volume containing tumour and as well as to reduce dose to organs at risk (OARs). The detailed comparison between different treatment techniques is very difficult and inexplicit as well. The gradual improvement in imaging software has made easy to users to assess spatial arrangement of tumour, critical organs and isodose lines in the form of a single 3D representation that can be observed from all angles. The conformity index (CI) alone cannot provide practical information about treatment plans as it is a single isodose line quantity.

The aim of this study was to develop a new method to assess the degree of damage numerically for OARs along with CI assessment for the target.

The radiotherapy plans of 30 patients of different sites, diagnosed as cancer, were selected for this study irrespective of gender. Out of 30 cases, 8 plans were of head and neck, 2 were of glyoblastoma (GBM), 10 were of pelvis, 5 were of left breast and other 5 were of oesophagus cancer. The mean age was 42 years ranging from 31 to 72 years. Patient’s consents were taken before starting the treatment and carried out this research. Risk factor (RF) for OARs depends on volume of irradiation (VVOI), total volume of the organ (VTVO) and tolerance dose (DTDO). All radiotherapy plans (Intensity Modulated Radiotherapy (IMRT) and Volumetric Modulated Arc Therapy (VMAT)) were generated using eclipse planning system, version 11.0 (Varian Medical System, Palo Alto, California, USA).

The formula developed to assess degree of damage of OARs including CI of the target is risk factor conformity index (RFC) = CI + RF. In head and neck cases, for right parotid, the maximum value of RF is 1·50 and minimum value is observed as 0·97. Optic nerve, brainstem and spinal cord are completely safe as their RF values are found to be 0 on RF scale.

RFC is a comprehensive evaluation tool encompassing a wider range of clinically relevant parameters, isodose volumes and tolerance dose of OARs. It is an advance analysing method to check both the qualitative and quantitative nature of a conformal plan, and at the same time, it assesses the degree of damage of OARs.

If RF ≥ 1, then OAR will be completely damaged as a result of irradiation.

If RF = 0, then OAR will remain safe totally during the course of irradiation.

The focus of this study is to find the optimal clinical tumour volume (CTV) to planning tumour volume (PTV) margins for precise radiotherapy treatment of prostate cancer. The geometrical shape of the target volume posses challenges in accurately identifying the CTV to PTV margins, especially when the organ affected by cancer demonstrates anatomical variations and the surrounding organs have high radio-sensitivity, in comparison to the organ of origin of the cancer.

The geometrical margins of CTV to PTV are investigated using portal imaging, in three directions. This study is carried out on 20 patients treated by the external photon beam radiotherapy of prostate cancer using standard accelerator without stereotaxic and without prostate markers.

Based on previous studies and the findings of our work, we propose CTV to PTV margin of 5·84 mm in the lateral direction, of 5·1 mm in the cranio-spinal direction and of 7·3 mm in the antero-posterior direction for external photon beam radiotherapy of prostate cancer.

The proposed CTV to PTV margins ensure high radiotherapy treatment precision of prostate cancer.