Predictive value of 3D quantitative shape features based on CT for disease-free survival of primary gastrointestinal stromal tumors

ObjectiveTo explore the predictive value of 3D quantitative shape features based on enhanced CT for disease-free survival (DFS) of primary gastric gastrointestinal stromal tumors (GIST) patients receiving curative resection. MethodsFrom January 2010 to December 2016, a total of 154 patients with primary gastric GIST who received curative resection in Zhongshan Hospital, Fudan University were retrospectively collected. The conventional CT imaging features and 3D quantitative shape features of tumors were evaluated, and the influencing factors of DFS were analyzed by univariate and multivariate Cox regression. Cut-off values were extracted, and Kaplan-Meier curves were used for survival analysis. ResultsMaximum 3D diameter (HR=1.829, 95%CI 1.389-2.408, P<0.001) and spherical disproportion (HR=2.153, 95%CI 1.474-3.146, P<0.001) were independent risk factors for DFS in primary gastric GIST. Kaplan-Meier curves showed that patients with maximum 3D diameter>90.5 mm and spherical disproportion>1.5 showed shorter DFS after curative resection (P<0.001). ConclusionMaximum 3D diameter and spherical disproportion based on preoperative enhanced CT are valuable in the diagnosis of postoperative DFS in primary gastric GIST.

Publication Details

Journal
SHILAP Revista de lepidopterología
Published
2024-10-01
DOI
https://doi.org/10.12025/j.issn.1008-6358.2024.20240850
Primary Topic
Gastrointestinal Tumor Research and Treatment
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Predictive value of 3D quantitative shape features based on CT for disease-free survival of primary gastrointestinal stromal tumors

SHILAP Revista de lepidopterología
Gastrointestinal Tumor Research and Treatment
article

Predictive value of 3D quantitative shape features based on CT for disease-free survival of primary gastrointestinal stromal tumors

article en

Abstract

ObjectiveTo explore the predictive value of 3D quantitative shape features based on enhanced CT for disease-free survival (DFS) of primary gastric gastrointestinal stromal tumors (GIST) patients receiving curative resection. MethodsFrom January 2010 to December 2016, a total of 154 patients with primary gastric GIST who received curative resection in Zhongshan Hospital, Fudan University were retrospectively collected. The conventional CT imaging features and 3D quantitative shape features of tumors were evaluated, and the influencing factors of DFS were analyzed by univariate and multivariate Cox regression. Cut-off values were extracted, and Kaplan-Meier curves were used for survival analysis. ResultsMaximum 3D diameter (HR=1.829, 95%CI 1.389-2.408, P<0.001) and spherical disproportion (HR=2.153, 95%CI 1.474-3.146, P<0.001) were independent risk factors for DFS in primary gastric GIST. Kaplan-Meier curves showed that patients with maximum 3D diameter>90.5 mm and spherical disproportion>1.5 showed shorter DFS after curative resection (P<0.001). ConclusionMaximum 3D diameter and spherical disproportion based on preoperative enhanced CT are valuable in the diagnosis of postoperative DFS in primary gastric GIST.

SHILAP Revista de lepidopterología
Good health and well-being
Openalex Percentile: Top 49%
Gastrointestinal Tumor Research and Treatment
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Predictive value of 3D quantitative shape features based on CT for disease-free survival of primary gastrointestinal stromal tumors · SHILAP Revista de lepidopterología (2024) | TGRS Research Map | TGRS