Purpose: To analyze changes in parotid gland dose resulting from anatomic changes throughout a course of radiotherapy in a cohort of head-and-neck cancer patients.

Methods And Materials: The study population consisted of 10 head-and-neck cancer patients treated definitively with intensity-modulated radiotherapy on a helical tomotherapy unit. A total of 330 daily megavoltage computed tomography images were retrospectively processed through a deformable image registration algorithm to be registered to the planning kilovoltage computed tomography images. The process resulted in deformed parotid contours and voxel mappings for both daily and accumulated dose-volume histogram calculations. The daily and cumulative dose deviations from the original treatment plan were analyzed. Correlations between dosimetric variations and anatomic changes were investigated.

Results: The daily parotid mean dose of the 10 patients differed from the plan dose by an average of 15%. At the end of the treatment, 3 of the 10 patients were estimated to have received a greater than 10% higher mean parotid dose than in the original plan (range, 13-42%), whereas the remaining 7 patients received doses that differed by less than 10% (range, -6-8%). The dose difference was correlated with a migration of the parotids toward the high-dose region.

Conclusions: The use of deformable image registration techniques and daily megavoltage computed tomography imaging makes it possible to calculate daily and accumulated dose-volume histograms. Significant dose variations were observed as result of interfractional anatomic changes. These techniques enable the implementation of dose-adaptive radiotherapy.

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.ijrobp.2008.04.013DOI Listing

Publication Analysis

Top Keywords

computed tomography
16
daily megavoltage
12
megavoltage computed
12
deformable image
12
image registration
12
anatomic changes
12
parotid gland
8
dose
8
gland dose
8
head-and-neck cancer
8

Similar Publications

Background: Computed tomography (CT)-derived low muscle mass is associated with adverse outcomes in critically ill patients. Muscle ultrasound is a promising strategy for quantitating muscle mass. We evaluated the association between baseline ultrasound rectus femoris cross-sectional area (RF-CSA) and intensive care unit (ICU) mortality.

View Article and Find Full Text PDF

Low-cost male urogenital simulator for penile implant surgery training: a 3D printing approach.

3D Print Med

January 2025

Department of Surgical & Interventional Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.

Background: Penile implant surgery is the standard surgical treatment for end-stage erectile dysfunction. However, the growing complexity of modern high-tech penile prostheses has increased the demand for more practical training opportunities. The most advanced contemporary training methods involve simulation training using cadavers, with costs exceeding $5,000 per cadaver, inclusive of biohazard fees.

View Article and Find Full Text PDF

To investigate if progression of coronary artery calcification (CAC) in patients with systemic lupus erythematosus (SLE) is associated with renal and traditional cardiovascular risk factors as well as incidence of myocardial infarctions. CAC progression was evaluated by cardiac computed tomography (CT) at baseline and after 5 years. Multivariable Poisson regression was applied to investigate associations between CAC progression and baseline values for traditional cardiovascular risk factors, CAC, SLE disease duration, lupus nephritis, and renal function.

View Article and Find Full Text PDF

Coronary artery calcification (CAC) is a key marker of coronary artery disease (CAD) but is often underreported in cancer patients undergoing non-gated CT or PET/CT scans. Traditional CAC assessment requires gated CT scans, leading to increased radiation exposure and the need for specialized personnel. This study aims to develop an artificial intelligence (AI) method to automatically detect CAC from non-gated, freely-breathing, low-dose CT images obtained from positron emission tomography/computed tomography scans.

View Article and Find Full Text PDF

Objectives: To investigate the performance of a deep learning (DL) model for segmenting cone-beam computed tomography (CBCT) scans taken before and after mandibular horizontal guided bone regeneration (GBR) to evaluate hard tissue changes.

Materials And Methods: The proposed SegResNet-based DL model was trained on 70 CBCT scans. It was tested on 10 pairs of pre- and post-operative CBCT scans of patients who underwent mandibular horizontal GBR.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!