Dataset Information

Image fusion for computer-assisted bone tumor surgery.

ABSTRACT: The fusion of computed tomography and magnetic resonance images is a software-dependent processing technique that enables one to integrate and analyze preoperative images for planning complex musculoskeletal tumor resections. By integrating various imaging modalities into one imaging data set we may facilitate preoperative image analysis and planning of navigation computer-assisted bone tumor resection and reconstruction. We performed image fusion for computer-assisted tumor surgery in 13 consecutive patients, seven males and six females, with a mean age of 35.8 years (range, 6-80 years). Visual verification of fused images was accurate in all patients. The mean time for image fusion was 30.6 minutes (range, 8-80 minutes). After intraoperative registration, all tumor resections were performed as planned preoperatively under navigation image guidance. Resections achieved after navigation resection planning were validated by postoperative CT or resected specimens in seven patients. Histologic examination of all resected specimens showed tumor-free margins in patients with bone sarcoma. The fusion of computed tomography and magnetic resonance imaging has the potential to enhance computer-assisted bone tumor surgery. The fusion image, when combined with surgical navigation, helps surgeons reproduce a preoperative plan reliably and may offer substantial clinical benefits.

SUBMITTER: Wong KC

PROVIDER: S-EPMC2584299 | biostudies-literature | 2008 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Image fusion for computer-assisted bone tumor surgery.

Wong Kwok Chuen KC Kumta Shekhar Madhuker SM Antonio Gregory Ernest GE Tse Lung Fung LF

Clinical orthopaedics and related research 20080722 10

The fusion of computed tomography and magnetic resonance images is a software-dependent processing technique that enables one to integrate and analyze preoperative images for planning complex musculoskeletal tumor resections. By integrating various imaging modalities into one imaging data set we may facilitate preoperative image analysis and planning of navigation computer-assisted bone tumor resection and reconstruction. We performed image fusion for computer-assisted tumor surgery in 13 consec ...[more]

PMID: 18648902

Similar Datasets

Project description:Oral tongue squamous cell carcinoma (OTSCC) displays variable levels of immune cells within the tumor microenvironment. The quantity and localization of tumor infiltrating lymphocytes (TILs), specific functional TIL subsets (e.g., CD8+), and biomarker-expressing cells (e.g., PD-L1+) may have prognostic and predictive value. The purpose of this study was to evaluate the robustness and utility of computer-assisted image analysis tools to quantify and localize immunohistochemistry-based biomarkers within the tumor microenvironment on a tissue microarray (TMA). We stained a 91-patient OTSCC TMA with antibodies targeting CD3, CD4, CD8, FOXP3, IDO, and PD-L1. Cell populations were segmented into epithelial (tumor) or stromal compartments according to a mask derived from a pan-cytokeratin stain. Definiens Tissue Studio was used to enumerate marker-positive cells or to quantify the staining intensity. Automated methods were validated against manual tissue segmentation, cell count, and stain intensity quantification. Univariate associations of cell count and stain intensity with smoking status, stage, overall survival (OS), and disease-free survival (DFS) were determined. Our results revealed that the accuracy of automated tissue segmentation was dependent on the distance of the tissue section from the cytokeratin mask and the proportion of the tissue containing tumor vs. stroma. Automated and manual cell counts and stain intensities were highly correlated (Pearson coefficient range: 0.46-0.90; p?<?0.001). Within this OTSCC cohort, smokers had significantly stronger PD-L1 stain intensity and higher numbers of CD3+, CD4+ and FOXP3+ TILs. In the subset of patients who had received adjuvant radiotherapy, a higher number of CD8+ TILs was associated with inferior OS and DFS. Taken together, this proof-of-principle study demonstrates the robustness and utility of computer-assisted image analysis for high-throughput assessment of multiple IHC markers on TMAs, with potential implications for studies on prognostic and predictive biomarkers.

Dataset Information

Image fusion for computer-assisted bone tumor surgery.

Publications

Image fusion for computer-assisted bone tumor surgery.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets