ArticleEuropean journal of nuclear medicine and molecular imaging2017
[18]Fluorodeoxyglucose Positron Emission Tomography for the Textural Features of Cervical Cancer Associated with Lymph Node Metastasis and Histological Type.
Article in European journal of nuclear medicine and molecular imaging, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.
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Who cites it
32 citing papers in PubMed.
- Article
- Differentiation of cervical cancer subtypes using machine learning models on MRI images.Polish journal of radiology · 2026Article
- [Diagnostics (Basel, Switzerland) · 2024Review
- Can we skip invasive biopsy of sentinel lymph nodes? A preliminary investigation to predict sentinel lymph node status using PET/CT-based radiomics.BMC cancer · 2024Article
- Respective contribution of baseline clinical data, tumour metabolism and tumour blood-flow in predicting pCR after neoadjuvant chemotherapy in HER2 and Triple Negative breast cancer.EJNMMI research · 2024Article
- Predictive value and potential association of PET/CT radiomics on lymph node metastasis of cervical cancer.Annals of medicine and surgery (2012) · 2024Article
- Radiomics-based machine learning models for differentiating pathological subtypes in cervical cancer: a multicenter study.Frontiers in oncology · 2024Article
- Network Evolution Model-based prediction of tumor mutation burden from radiomic-clinical features in endometrial cancers.BMC cancer · 2023Article
- Intra- and peri-tumoral MRI radiomics features for preoperative lymph node metastasis prediction in early-stage cervical cancer.Insights into imaging · 2023Article
- Automatic tumor segmentation and metachronous single-organ metastasis prediction of nasopharyngeal carcinoma patients based on multi-sequence magnetic resonance imaging.Frontiers in oncology · 2023Article
- Prognostic Value of Pre-Treatment [18F]FDG PET/CT Texture Analysis in Undifferentiated Soft-Tissue Sarcoma.Journal of clinical medicine · 2022Article
- The value of metabolic parameters and textural analysis in predicting prognosis in locally advanced cervical cancer treated with chemoradiotherapy.Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al] · 2022Article
- Radiomics in Oncological PET Imaging: A Systematic Review-Part 2, Infradiaphragmatic Cancers, Blood Malignancies, Melanoma and Musculoskeletal Cancers.Diagnostics (Basel, Switzerland) · 2022Review
- Post treatment imaging in patients with local advanced cervical carcinoma.Frontiers in oncology · 2022Review
- Application and Clinical Value of Machine Learning-Based Cervical Cancer Diagnosis and Prediction Model in Adjuvant Chemotherapy for Cervical Cancer: A Single-Center, Controlled, Non-Arbitrary Size Case-Control Study.Contrast media & molecular imaging · 2022Article
- Exploratory analysis of radiomic as prognostic biomarkers inFrontiers in medicine · 2022Article
- Radiomics in cervical and endometrial cancer.The British journal of radiology · 2021Review
- A Systematic Review of PET Textural Analysis and Radiomics in Cancer.Diagnostics (Basel, Switzerland) · 2021Review
- Radiomic Score as a Potential Imaging Biomarker for Predicting Survival in Patients With Cervical Cancer.Frontiers in oncology · 2021Article
- Effect of grey-level discretization on texture feature on different weighted MRI images of diverse disease groups.PloS one · 2021Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundIn this study, we investigated the correlation between the lymph node (LN) status or histological types and textural features of cervical cancers on
methodsWe retrospectively reviewed the imaging records of 170 patients with International Federation of Gynecology and Obstetrics stage IB-IVA cervical cancer. Four groups of textural features were studied in addition to the maximum standardized uptake value (SUV
resultsAmong all the significant indices related to pelvic LN metastasis, homogeneity derived from the gray-level co-occurrence matrix (GLCM) was the sole independent predictor. By combining SUV
conclusionThis study revealed that in patients with cervical cancer, pelvic or para-aortic LN metastases can be predicted by using textural feature of homogeneity from the GLCM and TLG
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