Trial reportDigestive diseases and sciences2014
Fractal analysis of contrast-enhanced CT images to predict survival of patients with hepatocellular carcinoma treated with sunitinib.
Trial report in Digestive diseases and sciences, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
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Who cites it
22 citing papers in PubMed.
- Response prediction of neoadjuvant chemoradiation therapy in locally advanced rectal cancer using CT-based fractal dimension analysis.European radiology · 2022Trial
- A radiomics nomogram for the prediction of overall survival in patients with hepatocellular carcinoma after hepatectomy.Cancer imaging : the official publication of the International Cancer Imaging Society · 2020Trial
- Texture Analysis of Non-Contrast-Enhanced Computed Tomography for Assessing Angiogenesis and Survival of Soft Tissue Sarcoma.Journal of computer assisted tomographyTrial
- 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
- Simulated deep CT characterization of liver metastases with high-resolution filtered back projection reconstruction.Visual computing for industry, biomedicine, and art · 2024Article
- Fractal nature of human gastrointestinal system: Exploring a new era.World journal of gastroenterology · 2023Review
- Chaotic fractals: Why chaos is the dynamic of carcinogenesis.Cancer innovation · 2023Article
- Computed tomography-derived biomarker for predicting the treatment response to neoadjuvant chemoradiotherapy of rectal cancer.International journal of clinical oncology · 2021Article
- Review
- Quantification of Structural Heterogeneity Using Fractal Analysis of Contrast-Enhanced CT Image to Predict Survival in Gastric Cancer Patients.Digestive diseases and sciences · 2021Article
- Development and Validation a Nomogram Incorporating CT Radiomics Signatures and Radiological Features for Differentiating Invasive Adenocarcinoma From AdenocarcinomaFrontiers in oncology · 2021Article
- Predicting the Response to FOLFOX-Based Chemotherapy Regimen from Untreated Liver Metastases on Baseline CT: a Deep Neural Network Approach.Journal of digital imaging · 2020Article
- Spatial heterogeneity of oxygenation and haemodynamics in breast cancer resolved in vivo by conical multispectral optoacoustic mesoscopy.Light, science & applications · 2020Article
- Small Cell Lung Cancer Therapeutic Responses Through Fractal Measurements: From Radiology to Mitochondrial Biology.Journal of clinical medicine · 2019Article
- 6-Gingerol stabilized the p-VEGFR2/VE-cadherin/β-catenin/actin complex promotes microvessel normalization and suppresses tumor progression.Journal of experimental & clinical cancer research : CR · 2019Article
- Imaging biomarkers for the treatment of esophageal cancer.World journal of gastroenterology · 2019Review
- MR imaging based fractal analysis for differentiating primary CNS lymphoma and glioblastoma.European radiology · 2019Article
- Use of a Radiomics Model to Predict Tumor Invasiveness of Pulmonary Adenocarcinomas Appearing as Pulmonary Ground-Glass Nodules.BioMed research international · 2018Article
- Computed Tomography Image Texture: A Noninvasive Prognostic Marker of Hepatic Recurrence After Hepatectomy for Metastatic Colorectal Cancer.Annals of surgical oncology · 2017Article
- Applications and limitations of radiomics.Physics in medicine and biology · 2016Review
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundIntratumoral heterogeneity is a well-recognized feature of malignancy.
aimsTo assess the heterogeneity of tumor using fractal analysis of contrast-enhanced computed tomography (CE-CT) images for predicting survival of hepatocellular carcinoma (HCC) patients treated with sunitinib.
methodsThe patient cohort comprised 23 patients (19 men, 4 women; mean age 61.5 years) with HCC who underwent CE-CT at baseline and after one cycle of sunitinib. Arterial-phase (AP) and portal-phase (PP) CE-CT images were analyzed using a plugin software for ImageJ (NIH, Bethesda, MD). A differential box-counting method was employed to calculate the fractal dimension (FD) of the tumor. Tumor FD, density, and size were compared with survival.
resultsMedian progression-free survival (PFS) was 4.43 months. Patients were grouped into a favorable PFS (PFS >4.43 months; 9 patients) and an unfavorable PFS group (PFS ≤ 4.43; 13 patients). The baseline FD on both the AP and PP images was lower in the favorable PFS group than in the unfavorable PFS group (both P = 0.03). There was a significant difference in the change of the FD on the AP image between the favorable and unfavorable PFS groups (P = 0.02). Tumor density and size showed no significant correlations with PFS. In the Kaplan-Meier analysis, patients with tumors showing lower FD on the AP image at baseline showed longer PFS (P = 0.002). Patients with tumors showing a greater reduction in the FD on the PP image after one cycle of the therapy showed longer overall survival (P = 0.002).
conclusionThe FD of the tumor on CE-CT images may be a useful biomarker for HCC patients treated with sunitinib.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.