Background/aim: Development of imaging techniques, computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography (PET), made great impact on radiotherapy treatment planning by improving the localization of target volumes. Improved localization allows better local control of tumor volumes, but also minimizes geographical misses. Mutual information is obtained by registration and fusion of images achieved manually or automatically. The aim of this study was to validate the CT-MRI image fusion method and compare delineation obtained by CT versus CT-MRI image fusion.

Methods: The image fusion software (XIO CMS 4.50.0) was applied to delineate 16 patients. The patients were scanned on CT and MRI in the treatment position within an immobilization device before the initial treatment. The gross tumor volume (GTV) and clinical target volume (CTV) were delineated on CT alone and on CT+MRI images consecutively and image fusion was obtained.

Results: Image fusion showed that CTV delineated on a CT image study set is mainly inadequate for treatment planning, in comparison with CTV delineated on CT-MRI fused image study set. Fusion of different modalities enables the most accurate target volume delineation.

Conclusion: This study shows that registration and image fusion allows precise target localization in terms of GTV and CTV and local disease control.

Download full-text PDF

Source
http://dx.doi.org/10.2298/vsp110404001dDOI Listing

Publication Analysis

Top Keywords

image fusion
20
treatment planning
12
ctv delineated
12
image
9
radiotherapy treatment
8
fusion
8
registration fusion
8
tumor volume
8
ct-mri image
8
target volume
8

Similar Publications

Purpose: The study explores the role of multimodal imaging techniques, such as [F]F-PSMA-1007 PET/CT and multiparametric MRI (mpMRI), in predicting the ISUP (International Society of Urological Pathology) grading of prostate cancer. The goal is to enhance diagnostic accuracy and improve clinical decision-making by integrating these advanced imaging modalities with clinical variables. In particular, the study investigates the application of few-shot learning to address the challenge of limited data in prostate cancer imaging, which is often a common issue in medical research.

View Article and Find Full Text PDF

With the emergence of numerous classifications, surgical treatment for adolescent idiopathic scoliosis (AIS) can be guided more effectively. However, surgical decision-making and optimal strategies still lack standardization and personalized customization. Our study aims to devise proper deep learning (DL) models that incorporate key factors influencing surgical outcomes on the coronal plane in AIS patients to facilitate surgical decision-making and predict surgical results for AIS patients.

View Article and Find Full Text PDF

Labial adhesion in a reproductive-age woman is a rare entity. A woman in her 30s presented with complaints of passage of urine and menstrual blood from the same opening since menarche. The patient underwent some corrective surgery for the same, but the symptoms did not resolve.

View Article and Find Full Text PDF

A dual-domain network with division residual connection and feature fusion for CBCT scatter correction.

Phys Med Biol

January 2025

School of Biomedical Engineering, ShanghaiTech University, No. 1 Zhongke Road, Pudong New Area, Shanghai, Shanghai, 201210, CHINA.

Objective: This study aims to propose a dual-domain network that not only reduces scatter artifacts but also retains structure details in CBCT.

Approach: The proposed network comprises a projection-domain sub-network and an image-domain sub-network. The projection-domain sub-network utilizes a division residual network to amplify the difference between scatter signals and imaging signals, facilitating the learning of scatter signals.

View Article and Find Full Text PDF

As people's material living standards continue to improve, the types and quantities of household garbage they generate rapidly increase. Therefore, it is urgent to develop a reasonable and effective method for garbage classification. This is important for resource recycling and environmental improvement and contributes to the sustainable development of production and the economy.

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!