Karpavičienė, Greta

Image-guided radiotherapy (IGRT) has enhanced the precision of cancer treatment by integrating imaging modalities such as computed tomography (CT), magnetic resonance imaging (MRI) and cone-beam computed tomography (CBCT) into daily radiotherapy workflows. In head and neck cancer, where anatomical changes are common, accurate image registration between planning and treatment scans is essential to ensure dose accuracy. However, geometric distortions in CBCT (such as translation, rotation, and scaling resulting from patient positioning variations observed in daily CBCT images) can affect tumour targeting and dose delivery. This pilot study assesses a MATLAB-based image correction algorithm that uses rigid bony landmarks and point cloud registration together with spatial transformation to align CBCT with planning CT. Two head and neck cancer patients were retrospectively analysed, selected for their contrasting anatomical responses: one with substantial tumour regression and one with minimal change. Imaging was performed on the Halcyon V3.1 linear accelerator (Varian Medical Systems), with 25 daily CBCT scans per patient (85–96 slices per scan), resulting in 50 datasets for analysis. Spatial deviations were measured along the X, Y, and Z axes, and dose recalculations were performed for each treatment fraction. The correction method significantly improved spatial congruence and reduced geometric discrepancies caused by voxel spacing and acquisition parameters. Uncorrected scans showed dose deviations of up to ± 12% in organs at risk, notably the spinal cord and parotid glands. These findings demonstrate the feasibility and dosimetric relevance of automated CBCT correction in daily head and neck radiotherapy. Although limited in sample size, the study provides a detailed technical and dosimetric analysis of spatial distortions and supports future validation in larger patient cohorts.

Patient positioning, together with physical changes in soft tissues during the course of radiotherapy, significantly affects the irradiation of targeted tissues and adjacent structures. This leads to a high risk of under-dosage of the tumour and/or over-dosage of critical normal structures during the late sessions of treatment. Accurate and timely identification of irradiation-affected tissue regions is highly valuable for adaptive radiotherapy planning. We propose a method for the identification and evaluation of specific computed tomography (CT) attenuation changes that can reveal the affected tissue regions. The search for correlated CT attenuation changes in the tumour and surrounding tissues, based on principal component analysis of series of intensity values in each fixed voxel, can reveal the actual three-dimensional region of irradiation-affected tissues for radiotherapy control and replanning.

Ensuring selective irradiation of target tissues is one of the biggest challenges in radiotherapy. Methods and devices of Image-Guided Radiotherapy (IGRT) are elaborated with the aim of ensuring that the prescribed radiation dose is delivered accurately to the tumour while minimising exposure to surrounding healthy tissues. Technical solutions ensure a few-millimetre, or even sub-millimetre precision of the irradiation beam, while with currently used mechanical means of patient positioning, we can expect much bigger positioning deviations, reaching even centimetre range. Patient positioning deviation to a certain extent is related to changes in soft tissue density and volume, which change during the period of treatment. Therefore, the discovery of reliable reference structures in routinely performed daily Cone-Beam Computed Tomograms (CBCT) was one of the aims of this study. Having the reliable reference structures, we carried out the retrospective estimation of patient position deviation during the whole treatment cycle and evaluated possible dynamics of unwanted irradiation of tumour-surrounding critical organs. The study was conducted in patients with head and neck cancer treated in the Lithuanian University of Health Sciences Kaunas Clinics Affiliated Hospital of Oncology, Department of Radiotherapy. Patients’ positioning was evaluated using volumetric images obtained by the CBCT machine integrated into the Halcyon V3.1 linear accelerator (Varian Medical Systems, Palo Alto, CA, USA). Custom-made algorithms of hard tissue segmentation and actual patient position estimation were elaborated in MATLAB (MathWorks, USA) environment. The hard tissue structures in volumetric images, in particular the mandible and part of the skull, were segmented and adjusted using mathematical morphology algorithms. We found these structures as reliable reference landmarks for patient position estimation. We found the deviation of actual patient position ranging from 1 to 3,5 mm, which resulted in changes in irradiation ranging from 0,016 to 0,057 Gy/fraction in the planned target volume and in critical surrounding organs (e.g. larynx, parotid, etc.) as well. The values indicate that it can cause significant damage to the surrounding organs. In conclusion, we state that specially selected hard tissue structures can serve as reliable landmarks of patient position, while soft tissues eventually change. The development of more precise image-guided radiotherapy methods can significantly reduce the damage to tumour-surrounding organs.

Maximisation of irradiation accuracy of malignant tissues is a key challenge on the way to optimal radiotherapy. Strategies to improve irradiation accuracy should balance the expected clinical benefit against the feasibility and procedural demands of the method used. This pilot study marks an initial step toward retrospectively evaluating patient positioning accuracy, analysing CBCT images in relation to clinical outcomes, and estimating actual irradiation of target and surrounding tissues. The CBCT images were acquired from head and neck patients treated with the Halcyon V3.1 linear accelerator. The algorithms for precise alignment of images, which made it possible to estimate the detailed changes in tumour tissue density during treatment sessions were developed in the MATLAB. The recalculation of the actual dose showed that even small positioning errors can lead to significant changes in the delivered dose, especially in areas where critical organs are affected.