G. Iacoviello

Performance of commercially available deformable image registration platforms for contour propagation using patient‐based computational phantoms: A multi‐institutional study

PURPOSEnTo investigate the performance of various algorithms for deformable image registration (DIR) to propagate regions of interest (ROIs) using multiple commercial platforms.nnnMETHODS AND MATERIALSnThirteen institutions participated in the study with six commercial platforms: RayStation (RaySearch Laboratories, Stockholm, Sweden), MIM (Cleveland, OH, USA), VelocityAI and Smart Adapt (Varian Medical Systems, Palo Alto, CA, USA), Mirada XD (Mirada Medical Ltd, Oxford, UK), and ABAS (Elekta AB, Stockholm, Sweden). The DIR algorithms were tested on synthetic images generated with the ImSimQA package (Oncology Systems Limited, Shrewsbury, UK) by applying two specific Deformation Vector Fields (DVF) to real patient data-sets. Head-and-neck (HN), thorax, and pelvis sites were included. The accuracy of the algorithms was assessed by comparing the DIR-mapped ROIs from each center with those of reference, using the Dice Similarity Coefficient (DSC) and Mean Distance to Conformity (MDC) metrics. Statistical inference on validation results was carried out in order to identify the prognostic factors of DIR performances.nnnRESULTSnDVF intensity, anatomic site and participating center were significant prognostic factors of DIR performances. Sub-voxel accuracy was obtained in the HN by all algorithms. Large errors, with MDC ranging up to 6 mm, were observed in low-contrast regions that underwent significant deformation, such as in the pelvis, or large DVF with strong contrast, such as the clinical tumor volume (CTV) in the lung. Under these conditions, the hybrid DIR algorithms performed significantly better than the free-form intensity based algorithms and resulted robust against intercenter variability.nnnCONCLUSIONSnThe performances of the systems proved to be site specific, depending on the DVF type and the platforms and the procedures used at the various centers. The pelvis was the most challenging site for most of the algorithms, which failed to achieve sub-voxel accuracy. Improved reproducibility was observed among the centers using the same hybrid registration algorithm.

Characterization of phenolic pellets for ESR dosimetry in photon beam radiotherapy

This work deals with the dosimetric features of a particular phenolic compound (IRGANOX 1076®) for dosimetry of clinical photon beams by using electron spin resonance (ESR) spectroscopy. After the optimization of the ESR readout parameters (namely modulation amplitude and microwave power) to maximise the signal without excessive spectrum distortions, basic dosimetric properties of laboratory-made phenolic dosimeters in pellet form, such as reproducibility, dose–response, sensitivity, linearity and dose rate dependence were investigated. The dosimeters were tested by measuring the depth dose profile of a 6xa0MV photon beam. A satisfactory intra-batch reproducibility of the ESR signal of the manufactured dosimeters was obtained. The ESR signal proved to increase linearly with increasing dose in the investigated dose range 1–13xa0Gy. The presence of an intrinsic background signal limits the minimum detectable dose to a value of approximately 0.6xa0Gy. Reliable and accurate assessment of the dose was achieved, independently of the dose rate. Such characteristics, together with the fact that IRGANOX 1076® is almost tissue-equivalent, and the stability of the ESR signal, make these dosimeters promising materials for ESR dosimetric applications in radiotherapy.