Literature DB >> 25966933

Clinical Application of Diffusion-Weighted Magnetic Resonance Imaging in Uterine Cervical Cancer.

Ying Liu1, Zhaoxiang Ye, Haoran Sun, Renju Bai.   

Abstract

OBJECTIVE: This study aimed to investigate the application value of apparent diffusion coefficient (ADC) values in evaluating histological type as well as pathologic grade of uterine cervical cancer; and to investigate whether ADC values could reflect tumor cellular density.
METHODS: Ninety-eight patients with histopathologically proven uterine cervical cancer were included in this study. Mean ADC value and minimum ADC value of the tumor were measured. Tumor cellular density was counted using colored multifunction imaging analyzing system.
RESULTS: Both mean ADC value and minimum ADC value of squamous cell carcinoma were significantly lower than that of adenocarcinoma (P = 0.001; P = 0.000). Using mean ADC criteria (≤0.965 × 10⁻³ mm/s²) and minimum ADC criteria (≤0.844 × 10⁻³ mm/s²), the sensitivity and specificity for differentiating squamous cell carcinoma from adenocarcinoma were 83.5% and 76.9%, and 77.6% and 92.3%, respectively. Receiver operating characteristic analysis revealed that there was no statistically significant difference in the Az values between them (P = 0.990). Tumor cellular density, mean ADC value, and minimum ADC value of different pathological grade varied significantly (P = 0.000, P = 0.000, P = 0.000). There was a significant positive linear correlation between tumor cellular density and pathological grade of tumor (P = 0.000). Both mean ADC value and minimum ADC value correlated negatively with cellular density (P = 0.000, P = 0.000) and the pathological grade of tumor (P = 0.000, P = 0.000). Comparisons of correlation coefficients showed no significant differences (P = 0.656, P = 0.631).
CONCLUSIONS: Diffusion-weighted magnetic resonance imaging has a potential ability to indicate the histologic type of uterine cervical cancer. Apparent diffusion coefficient measurements of uterine cervical cancer can represent tumor cellular density, thus providing a new method for evaluating the pathological grade of tumor.

Entities:  

Mesh:

Year:  2015        PMID: 25966933     DOI: 10.1097/IGC.0000000000000472

Source DB:  PubMed          Journal:  Int J Gynecol Cancer        ISSN: 1048-891X            Impact factor:   3.437


  21 in total

1.  Multi-parametric MRI in cervical cancer: early prediction of response to concurrent chemoradiotherapy in combination with clinical prognostic factors.

Authors:  Wei Yang; Jin Wei Qiang; Hai Ping Tian; Bing Chen; Ai Jun Wang; Jian Guo Zhao
Journal:  Eur Radiol       Date:  2017-08-04       Impact factor: 5.315

Review 2.  Imaging of distant metastases of prostate cancer.

Authors:  Filippo Pesapane; Marcin Czarniecki; Matteo Basilio Suter; Baris Turkbey; Geert Villeirs
Journal:  Med Oncol       Date:  2018-09-14       Impact factor: 3.064

3.  Contribution of mono-exponential, bi-exponential and stretched exponential model-based diffusion-weighted MR imaging in the diagnosis and differentiation of uterine cervical carcinoma.

Authors:  Meng Lin; Xiaoduo Yu; Yan Chen; Han Ouyang; Bing Wu; Dandan Zheng; Chunwu Zhou
Journal:  Eur Radiol       Date:  2016-09-27       Impact factor: 5.315

4.  Diffusion-weighted Imaging as a Treatment Response Biomarker for Evaluating Bone Metastases in Prostate Cancer: A Pilot Study.

Authors:  Raquel Perez-Lopez; Joaquin Mateo; Helen Mossop; Matthew D Blackledge; David J Collins; Mihaela Rata; Veronica A Morgan; Alison Macdonald; Shahneen Sandhu; David Lorente; Pasquale Rescigno; Zafeiris Zafeiriou; Diletta Bianchini; Nuria Porta; Emma Hall; Martin O Leach; Johann S de Bono; Dow-Mu Koh; Nina Tunariu
Journal:  Radiology       Date:  2016-11-22       Impact factor: 11.105

5.  Multiparametric PET/MR (PET and MR-IVIM) for the evaluation of early treatment response and prediction of tumor recurrence in patients with locally advanced cervical cancer.

Authors:  Si Gao; Siyao Du; Zaiming Lu; Jun Xin; Song Gao; Hongzan Sun
Journal:  Eur Radiol       Date:  2019-09-06       Impact factor: 5.315

6.  Prognostic model based on magnetic resonance imaging, whole-tumour apparent diffusion coefficient values and HPV genotyping for stage IB-IV cervical cancer patients following chemoradiotherapy.

Authors:  Gigin Lin; Lan-Yan Yang; Yu-Chun Lin; Yu-Ting Huang; Feng-Yuan Liu; Chun-Chieh Wang; Hsin-Ying Lu; Hsin-Ju Chiang; Yu-Ruei Chen; Ren-Chin Wu; Koon-Kwan Ng; Ji-Hong Hong; Tzu-Chen Yen; Chyong-Huey Lai
Journal:  Eur Radiol       Date:  2018-07-26       Impact factor: 5.315

7.  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

8.  Feasibility of an ADC-based radiomics model for predicting pelvic lymph node metastases in patients with stage IB-IIA cervical squamous cell carcinoma.

Authors:  Yan Yan Yu; Rui Zhang; Rui Tong Dong; Qi Yun Hu; Tao Yu; Fan Liu; Ya Hong Luo; Yue Dong
Journal:  Br J Radiol       Date:  2019-04-01       Impact factor: 3.039

9.  Magnetic resonance imaging of adenoma malignum of the uterine cervix with pathologic correlation: a case report.

Authors:  Alba Castán Senar; Blanca Paño; Adela Saco; Carlos Nicolau
Journal:  Radiol Case Rep       Date:  2016-09-20

10.  Diffusion-weighted MRI-derived ADC values reflect collagen I content in PDX models of uterine cervical cancer.

Authors:  Anette Hauge; Catherine S Wegner; Jon-Vidar Gaustad; Trude G Simonsen; Lise Mari K Andersen; Einar K Rofstad
Journal:  Oncotarget       Date:  2017-11-11
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.