Literature DB >> 28728757

Value of whole-lesion apparent diffusion coefficient (ADC) first-order statistics and texture features in clinical staging of cervical cancers.

Y Guan1, W Li1, Z Jiang1, B Zhang1, Y Chen1, X Huang1, J Zhang1, S Liu2, J He3, Z Zhou4, Y Ge5.   

Abstract

AIM: To explore the value of whole-lesion apparent diffusion coefficient (ADC) first-order statistics and texture features in clinical staging of cervical cancers.
MATERIALS AND METHODS: Fifty-six women (mean age, 51 years) with histopathologically confirmed cervical cancers underwent 3 T pelvic magnetic resonance imaging including diffusion-weighted imaging (b=0, 800 s/mm2) prospectively. The ADC first-order statistics and texture features derived from the whole volume of cervical cancers were correlated with International Federation of Gynecology and Obstetrics (FIGO) stages (i.e., stages I, II, III, and IV).
RESULTS: The first-order statistics of skewness, kurtosis, and entropy, and the texture features of entropy(H) and homogeneity correlated positively, while the texture feature of energy correlated negatively with FIGO stages (all p<0.05). Skewness, kurtosis, entropy, entropy(H), and homogeneity were significantly higher, while energy was significantly lower in cervical cancers at higher (IIB-IVA) than lower (IB-IIA) FIGO stages (all p<0.05). Kurtosis and energy had the largest areas under the receiver operating characteristic (ROC) curve of 0.749 and 0.746 in differentiating cervical cancers at lower (IB-IIA) from higher (IIB-IVA) FIGO stages.
CONCLUSION: Whole-lesion ADC first-order statistics and texture features proved relevant and meaningful in the clinical staging of cervical cancers.
Copyright © 2017 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.

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Year:  2017        PMID: 28728757     DOI: 10.1016/j.crad.2017.06.115

Source DB:  PubMed          Journal:  Clin Radiol        ISSN: 0009-9260            Impact factor:   2.350


  5 in total

1.  Diagnosis of Cervical Cancer With Parametrial Invasion on Whole-Tumor Dynamic Contrast-Enhanced Magnetic Resonance Imaging Combined With Whole-Lesion Texture Analysis Based on T2- Weighted Images.

Authors:  Xin-Xiang Li; Ting-Ting Lin; Bin Liu; Wei Wei
Journal:  Front Bioeng Biotechnol       Date:  2020-06-11

2.  Cervical Cancer: Associations between Metabolic Parameters and Whole Lesion Histogram Analysis Derived from Simultaneous 18F-FDG-PET/MRI.

Authors:  Hans-Jonas Meyer; Sandra Purz; Osama Sabri; Alexey Surov
Journal:  Contrast Media Mol Imaging       Date:  2018-07-30       Impact factor: 3.161

3.  Radiomic features of cervical cancer on T2-and diffusion-weighted MRI: Prognostic value in low-volume tumors suitable for trachelectomy.

Authors:  Benjamin W Wormald; Simon J Doran; Thomas Ej Ind; James D'Arcy; James Petts; Nandita M deSouza
Journal:  Gynecol Oncol       Date:  2019-11-02       Impact factor: 5.482

4.  Radiomics Analysis of Multi-Sequence MR Images For Predicting Microsatellite Instability Status Preoperatively in Rectal Cancer.

Authors:  Zongbao Li; Hui Dai; Yunxia Liu; Feng Pan; Yanyan Yang; Mengchao Zhang
Journal:  Front Oncol       Date:  2021-07-07       Impact factor: 6.244

Review 5.  Radiomics in cervical and endometrial cancer.

Authors:  Lucia Manganaro; Gabriele Maria Nicolino; Miriam Dolciami; Federica Martorana; Anastasios Stathis; Ilaria Colombo; Stefania Rizzo
Journal:  Br J Radiol       Date:  2021-07-08       Impact factor: 3.629

  5 in total

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