Comparison of CT and MR-CT fusion for prostate post-implant dosimetry.

Int J Radiat Oncol Biol Phys

Department of Radiation Oncology, St. Luke's-Roosevelt Hospital Center, Beth Israel Medical Center, Continuum Health Partners, New York, NY, USA.

Published: April 2012

Purpose: The use of T2 MR for postimplant dosimetry (PID) after prostate brachytherapy allows more anatomically accurate and precise contouring but does not readily permit seed identification. We developed a reproducible technique for performing MR-CT fusion and compared the resulting dosimetry to standard CT-based PID.

Methods And Materials: CT and T1-weighted MR images for 45 patients were fused and aligned based on seed distribution. The T2-weighted MR image was then fused to the aligned T1. Reproducibility of the fusion technique was tested by inter- and intraobserver variability for 13 patients. Dosimetry was computed for the prostate as a whole and for the prostate divided into anterior and posterior sectors of the base, mid-prostate, and apex.

Results: Inter- and intraobserver variability for the fusion technique showed less than 1% variation in D90. MR-CT fusion D90 and CT D90 were nearly equivalent for the whole prostate, but differed depending on the identification of superior extent of the base (p = 0.007) and on MR/CT prostate volume ratio (p = 0.03). Sector analysis showed a decrease in MR-CT fusion D90 in the anterior base (ratio 0.93 ±0.25, p < 0.05) and an increase in MR-CT fusion D90 in the apex (p < 0.05). The volume of extraprostatic tissue encompassed by the V100 is greater on MR than CT. Factors associated with this difference are the MR/CT volume ratio (p < 0.001) and the difference in identification of the inferior extent of the apex (p = 0.03).

Conclusions: We developed a reproducible MR-CT fusion technique that allows MR-based dosimetry. Comparing the resulting postimplant dosimetry with standard CT dosimetry shows several differences, including adequacy of coverage of the base and conformity of the dosimetry around the apex. Given the advantage of MR-based tissue definition, further study of MR-based dosimetry is warranted.

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.ijrobp.2011.01.064DOI Listing

Publication Analysis

Top Keywords

mr-ct fusion
24
fusion technique
12
fusion d90
12
dosimetry
9
fusion
8
postimplant dosimetry
8
developed reproducible
8
dosimetry standard
8
fused aligned
8
inter- intraobserver
8

Similar Publications

Complicated image registration is a key issue in medical image analysis, and deep learning-based methods have achieved better results than traditional methods. The methods include ConvNet-based and Transformer-based methods. Although ConvNets can effectively utilize local information to reduce redundancy via small neighborhood convolution, the limited receptive field results in the inability to capture global dependencies.

View Article and Find Full Text PDF

This paper presents an innovative automatic fusion imaging system that combines 3D CT/MR images with real-time ultrasound acquisition. The system eliminates the need for external physical markers and complex training, making image fusion feasible for physicians with different experience levels. The integrated system involves a portable 3D camera for patient-specific surface acquisition, an electromagnetic tracking system, and US components.

View Article and Find Full Text PDF

Background: Information complementarity can be achieved by fusing MR and CT images, and fusion images have abundant soft tissue and bone information, facilitating accurate auxiliary diagnosis and tumor target delineation.

Purpose: The purpose of this study was to construct high-quality fusion images based on the MR and CT images of intracranial tumors by using the Residual-Residual Network (Res2Net) method.

Methods: This paper proposes an MR and CT image fusion method based on Res2Net.

View Article and Find Full Text PDF

Medical image segmentation and registration are two fundamental and highly related tasks. However, current works focus on the mutual promotion between the two at the loss function level, ignoring the feature information generated by the encoder-decoder network during the task-specific feature mapping process and the potential inter-task feature relationship. This paper proposes a unified multi-task joint learning framework based on bi-fusion of structure and deformation at multi-scale, called BFM-Net, which simultaneously achieves the segmentation results and deformation field in a single-step estimation.

View Article and Find Full Text PDF
Article Synopsis
  • A study evaluated the effectiveness of no-touch radiofrequency ablation (NT-RFA) with twin cooled wet electrodes in patients with recurrent hepatocellular carcinoma (HCC) after prior treatments, involving 102 patients and 112 tumors.
  • The study found that 21.4% of cases needed to switch to conventional RFA, but overall treatment success was high at 99.1%, with no major complications reported.
  • Mid-term analyses showed low rates of local tumor progression (LTP), with significant predictive factors identified, including the number of prior treatments and certain patient health indicators.
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!