Literature DB >> 29500645

Fractal analysis of contrast-enhanced CT images for preoperative prediction of malignant potential of gastrointestinal stromal tumor.

Yoshihiro Kurata1, Koichi Hayano2, Gaku Ohira2, Kazuo Narushima2, Tomoyoshi Aoyagi2, Hisahiro Matsubara2.   

Abstract

PURPOSE: The purpose of this study is to assess the heterogeneity of tumor enhancement using fractal analysis on contrast-enhanced computed tomography (CE-CT) for predicting malignant potential of gastrointestinal stromal tumor (GIST).
METHODS: We retrospectively identified 64 patients (36 M/28 W; median age: 65) with GISTs who received CE-CT and 18F-fluorodeoxyglucose positron emission tomography (FDG-PET) followed by curative surgery. Fractal analysis was applied to CE-CT image, and fractal dimension (FD) was measured. Diagnostic value of FD for malignant potential of GIST was compared with that of FDG-PET using the risk classification and Ki67 index.
RESULTS: 14 patients were categorized as the high risk, and 50 patients were as the very low, low or intermediate risk. FD of high-risk group was significantly higher than that of the other-risk group (p < 0.05). The areas under the ROC curves of FD and SUVmax for prediction of high-risk group were 0.82 and 0.93 (accuracy: 84.4% and 98.5%). FD showed a significant positive correlation with Ki67 index (p = 0.01).
CONCLUSION: Diagnostic value of CT fractal analysis for prediction of high-risk GIST is comparable with FDG-PET. In terms of cost and availability, fractal analysis has a potential to be an optimal preoperative biomarker.

Entities:  

Keywords:  Computed tomography; Fractal analysis; GIST; Preoperative prediction

Year:  2018        PMID: 29500645     DOI: 10.1007/s00261-018-1526-z

Source DB:  PubMed          Journal:  Abdom Radiol (NY)


  3 in total

1.  Building contrast-enhanced CT-based models for preoperatively predicting malignant potential and Ki67 expression of small intestine gastrointestinal stromal tumors (GISTs).

Authors:  Miao-Ping Zhu; Qiao-Ling Ding; Jian-Xia Xu; Chun-Yan Jiang; Jing Wang; Chao Wang; Ri-Sheng Yu
Journal:  Abdom Radiol (NY)       Date:  2021-03-25

2.  Differential Diagnosis and Molecular Stratification of Gastrointestinal Stromal Tumors on CT Images Using a Radiomics Approach.

Authors:  Martijn P A Starmans; Milea J M Timbergen; Melissa Vos; Michel Renckens; Dirk J Grünhagen; Geert J L H van Leenders; Roy S Dwarkasing; François E J A Willemssen; Wiro J Niessen; Cornelis Verhoef; Stefan Sleijfer; Jacob J Visser; Stefan Klein
Journal:  J Digit Imaging       Date:  2022-01-27       Impact factor: 4.056

3.  MRI-Based Radiomics Models for Predicting Risk Classification of Gastrointestinal Stromal Tumors.

Authors:  Haijia Mao; Bingqian Zhang; Mingyue Zou; Yanan Huang; Liming Yang; Cheng Wang; PeiPei Pang; Zhenhua Zhao
Journal:  Front Oncol       Date:  2021-05-10       Impact factor: 6.244

  3 in total

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