Literature DB >> 31324577

Diffusion Kurtosis Imaging in the Assessment of Cervical Carcinoma.

Mandi Wang1, Jose A U Perucho1, Queenie Chan2, Jianqing Sun3, Philip Ip4, Ka Yu Tse5, Elaine Y P Lee6.   

Abstract

RATIONALE AND
OBJECTIVES: To evaluate the additional value of diffusion kurtosis imaging (DKI) in the characterization of cervical carcinoma.
MATERIALS AND METHODS: Seventy-five patients (56.9 ± 13.4 years) with histologic-confirmed cervical carcinoma were included. Diffusion-weighted imaging (DWI) was acquired on a 3T MRI with five b values (0, 500, 800, 1000, and 1500 s/mm2). Data were analyzed based on DKI model (5 b values) and conventional DWI (0 and 1000 s/mm2). Largest single-slice region of interest (ROI) and volume of interest (VOI) were drawn around the tumor. Mean diffusivity (MD), mean kurtosis (MK), and apparent diffusion coefficient (ADC) of cervical carcinoma and normal myometrium were measured and compared. MD, MK, and ADC of cervical carcinoma were compared among histologic subtypes, tumor grades, and FIGO stages.
RESULTS: ROI- and VOI-derived DKI parameters and ADC were all in excellent consistency (intraclass correlation coefficient, ICC > 0.90, respectively). Cervical carcinoma had significantly lower MD, ADC, and higher MK than normal myometrium (p < 0.001). MD and ADC showed significant differences between histologic subtypes and FIGO stages, lower in squamous cell carcinoma than adenocarcinoma and higher in FIGO I-II than FIGO III-IV (p < 0.050), but not with tumor grade. No difference was observed in MK for different clinicopathologic features tested.
CONCLUSION: ROI and VOI analyses were in excellent consistency. MD and ADC were able to distinguish histologic subtypes and separating FIGO stages, MK could not. DKI showed no clear added value over conventional DWI in the characterization of cervical carcinoma.
Copyright © 2019 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Cervical carcinoma; Diffusion kurtosis imaging; Diffusion-weighted imaging; Histologic subtypes, FIGO

Year:  2019        PMID: 31324577     DOI: 10.1016/j.acra.2019.06.022

Source DB:  PubMed          Journal:  Acad Radiol        ISSN: 1076-6332            Impact factor:   3.173


  2 in total

1.  Cervical Carcinoma: Evaluation Using Diffusion MRI With a Fractional Order Calculus Model and its Correlation With Histopathologic Findings.

Authors:  Xian Shao; Li An; Hui Liu; Hui Feng; Liyun Zheng; Yongming Dai; Bin Yu; Jin Zhang
Journal:  Front Oncol       Date:  2022-04-05       Impact factor: 5.738

2.  Analysis of quantitative and semi-quantitative parameters of DCE-MRI in differential diagnosis of benign and malignant cervical tumors.

Authors:  Jun Song; Yong Gu; Tingting Du; Qiyu Liu
Journal:  Am J Transl Res       Date:  2021-11-15       Impact factor: 4.060

  2 in total

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