ArticleDigestive diseases and sciences2021
Quantification of Structural Heterogeneity Using Fractal Analysis of Contrast-Enhanced CT Image to Predict Survival in Gastric Cancer Patients.
Article in Digestive diseases and sciences, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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9 citing papers in PubMed, 19 citations in OpenAlex.
- Diagnostic efficacy of dual-energy computed tomography-based fractal analysis for assessing extramural venous invasion/tumor deposits and peripheral nerve invasion in rectal cancer.Quantitative imaging in medicine and surgery · 2026Article
- Predicting pathological complete response to chemoradiotherapy using artificial intelligence-based magnetic resonance imaging radiomics in esophageal squamous cell carcinoma.World journal of gastroenterology · 2025Article
- Texture analysis of CT colonography to develop a novel imaging biomarker for the management of colorectal cancer.Annals of gastroenterological surgery · 2025Article
- Fractal nature of human gastrointestinal system: Exploring a new era.World journal of gastroenterology · 2023Review
- The predictive potential of contrast-enhanced computed tomography based radiomics in the preoperative staging of cT4 gastric cancer.Quantitative imaging in medicine and surgery · 2022Article
- Fractal Analysis of a Non-Newtonian Fluid Flow in a Rough-Walled Pipe.Materials (Basel, Switzerland) · 2022Article
- The seen and the unseen: Molecular classification and image based-analysis of gastrointestinal cancers.Computational and structural biotechnology journal · 2022Review
- Computed tomography-derived biomarker for predicting the treatment response to neoadjuvant chemoradiotherapy of rectal cancer.International journal of clinical oncology · 2021Article
- Endoscopic Ultrasound vs. Computed Tomography for Gastric Cancer Staging: A Network Meta-Analysis.Diagnostics (Basel, Switzerland) · 2021Review
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8 authors at 1 institution in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundMalignant tumor essentially implies structural heterogeneity. Fractal analysis of medical imaging has a potential to quantify this structural heterogeneity in the tumor
aimsThe purpose of this study is to quantify this structural abnormality in the tumor applying fractal analysis to contrast-enhanced computed tomography (CE-CT) image and to evaluate its biomarker value for predicting survival of surgically treated gastric cancer patients.
methodsA total of 108 gastric cancer patients (77 men and 31 women; mean age: 69.1 years), who received curative surgery without any neoadjuvant therapy, were retrospectively investigated. Portal-phase CE-CT images were analyzed with use of a plug-in tool for ImageJ (NIH, Bethesda, USA), and the fractal dimension (FD) in the tumor was calculated using a differential box-counting method to quantify structural heterogeneity in the tumor. Tumor FD was compared with clinicopathologic features and disease-specific survival (DSS).
resultsHigh FD value of the tumor significantly associated with high T stage and high pathological stage (P = 0.009, 0.007, respectively). In Kaplan-Meier analysis, patients with higher FD tumors (FD > 0.9746) showed a significantly worse DSS (P = 0.009, log rank). Multivariate analysis demonstrated that tumor FD, T stage, and N stage were independent prognostic factors for DSS. In subset analysis of lymph-node positive gastric cancers, only tumor FD was an independent prognostic factor for DSS.
conclusionCT fractal analysis can be a useful biomarker for gastric cancer patients, reflecting survival and clinicopathologic features.
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