Abstract:Immobilisation for patients undergoing brain or head and neck radiotherapy is achieved using perspex or thermoplastic devices that require direct moulding to patient anatomy. The mould room visit can be distressing for patients and the shells do not always fit perfectly. In addition the mould room process can be time consuming. With recent developments in 3D printing technologies comes the potential to generate a treatment shell directly from a computer model of a patient. Typically, a patient requiring radiotherapy treatment will have had a CT scan and if a computer model of a shell could be obtained directly from the CT data it would reduce patient distress, reduce visits, obtain a close fitting shell and possibly enable the patient to start their radiotherapy treatment more quickly. This paper focusses on the first stage of generating the front part of the shell and investigates the dosimetric properties of the materials to show the feasibility of 3D printer materials for the production of a radiotherapy treatment shell. The majority of the possible candidate 3D printing materials tested result in very similar attenuation of a therapeutic RT beam as the Orfit soft-drape masks currently in use in many UK radiotherapy centres. The costs involved Powered by Editorial Manager® and ProduXion Manager® from Aries Systems Corporationin 3d printing are reducing and the applications to medicine are becoming more widely adopted. In this paper we show that 3D printing of bespoke radiotherapy masks is feasible and warrants further investigation. Powered by Editorial Manager® and ProduXion Manager® from Aries Systems CorporationTowards the Production of Radiotherapy Treatment Shells on 3D printers using data derived from DICOM CT and MRI: preclinical feasibility studies. AbstractImmobilisation for patients undergoing brain or head and neck radiotherapy is achieved using perspex or thermoplastic devices that require direct moulding to patient anatomy. The mould room visit can be distressing for patients and the shells do not always fit perfectly. In addition the mould room process can be time consuming. With recent developments in 3D printing technologies comes the potential to generate a treatment shell directly from a computer model of a patient. Typically, a patient requiring radiotherapy treatment will have had a CT scan and if a computer model of a shell could be obtained directly from the CT data it would reduce patient distress, reduce visits, obtain a close fitting shell and possibly enable the patient to start their radiotherapy treatment more quickly. This paper focusses on the first stage of generating the front part of the shell and investigates the dosimetric properties of the materials to show the feasibility of 3D printer materials for the production of a radiotherapy treatment shell. The majority of the possible candidate 3D printing materials tested result in very similar attenuation of a therapeutic RT beam as the Orfit soft-drape masks currently in use in many UK radiotherapy centres. The costs ...

This paper presents the preclinical evaluation of a novel immobilization system for patients undergoing external beam radiation treatment of head and neck tumors. An immobilization mask is manufactured directly from a 3-D model, built using the CT data routinely acquired for treatment planning so there is no need to take plaster of Paris moulds. Research suggests that many patients find the mould room visit distressing and so rapid prototyping could potentially improve the overall patient experience. Evaluation of a computer model of the immobilization system using an anthropomorphic phantom shows that >99% of vertices are within a tolerance of ±0.2 mm. Hausdorff distance was used to analyze CT slices obtained by rescanning the phantom with a printed mask in position. These results show that for >80% of the slices the median "worse-case" tolerance is approximately 4 mm. These measurements suggest that printed masks can achieve similar levels of immobilization to those of systems currently in clinical use.

Otsu’s criteria is a popular image segmentation approach that selects a threshold to maximise the inter-class variance of the distribution of intensity levels in the image. The algorithm finds the optimum threshold by performing an exhaustive search, but this is time-consuming, particularly for medical images employing 16-bit quantisation. This paper investigates particle swarm optimisation (PSO), Darwinian PSO and Fractional Order Darwinian PSO to speed up the algorithm. We evaluate the algorithms in medical imaging applications concerned with volume reconstruction, with a particular focus on addressing artefacts due to immobilisation masks, commonly worn by patients undergoing radiotherapy treatment for head-and-neck cancer. We find that the Fractional-Order Darwinian PSO algorithm outperforms other PSO algorithms in terms of accuracy, stability and speed which makes it the favourite choice when the accuracy and time-of-execution are a concern

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