Literature DB >> 19940650

Diffusion-weighted magnetic resonance imaging of uterine cervical cancer.

Ying Liu1, Renju Bai, Haoran Sun, Haidong Liu, Dehua Wang.   

Abstract

PURPOSE: To determine the feasibility of diffusion-weighted magnetic resonance (MR) imaging (DWI) of uterine cervical cancer and to investigate whether the apparent diffusion coefficient (ADC) values of cervical cancer differ from those of normal cervix and whether they could indicate the histologic type and the pathologic grade of tumor.
MATERIALS AND METHODS: Forty-two female patients with histopathologically proven uterine cervical cancer and 15 female patients with uterine leiomyomas underwent preoperative MR examinations using a 1.5-T clinical scanner (GE 1.5T Twin-Speed Infinity with Excite II scanner; GE Healthcare, Waukesha, Wis). Scanning sequences included T2-weighted fast spin-echo imaging, T2-weighted fast spin-echo with fat suppression imaging, T1-weighted spin-echo imaging, and DWI with diffusion factors of 0 and 1000 s/mm2. Parameters evaluated consisted of ADC values of uterine cervical cancer and normal cervix. Histologic specimens were stained with hematoxylin and eosin. The cellular densities of 32 uterine cervical cancers were calculated, which were regarded as the ratio of the total area of tumor cell nuclei divided by the area of sample image.
RESULTS: Apparent diffusion coefficient value was statistically different (P = 0.000) between normal and cancerous tissue in the uterine cervix; the former one was (mean [SD], 1.50 [0.16]) x 10(-3) mm2/s, and the latter one was (0.88 [0.15]) x 10(-3) mm2/s. Apparent diffusion coefficient value of squamous carcinoma was statistically lower than that of adenocarcinoma (P = 0.040). The ADC value of uterine cervical cancer correlated negatively with cellular density (r = -0.711, P = 0.000) and the grading of tumor (r = -0.778, P = 0.000).
CONCLUSIONS: Diffusion-weighted MR imaging has a potential ability to differentiate between normal and cancerous tissue in the uterine cervix, and it can indicate the histologic type of uterine cervical cancer as well. The ADC value of uterine cervical cancer represents tumor cellular density, thus providing a new method for evaluating the pathologic grading of tumor.

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Year:  2009        PMID: 19940650     DOI: 10.1097/RCT.0b013e31819e93af

Source DB:  PubMed          Journal:  J Comput Assist Tomogr        ISSN: 0363-8715            Impact factor:   1.826


  41 in total

Review 1.  Diffusion-weighted (DW) and dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) for monitoring anticancer therapy.

Authors:  Anwar R Padhani; Aftab Alam Khan
Journal:  Target Oncol       Date:  2010-04-11       Impact factor: 4.493

2.  Comparison of FDG PET metabolic tumour volume versus ADC histogram: prognostic value of tumour treatment response and survival in patients with locally advanced uterine cervical cancer.

Authors:  Yoshiko Ueno; Robert Lisbona; Tsutomu Tamada; Amer Alaref; Kazuro Sugimura; Caroline Reinhold
Journal:  Br J Radiol       Date:  2017-06-16       Impact factor: 3.039

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 MR imaging in gynecologic cancers.

Authors:  Shigenobu Motoshima; Hiroyuki Irie; Takahiko Nakazono; Toshiharu Kamura; Sho Kudo
Journal:  J Gynecol Oncol       Date:  2011-12-05       Impact factor: 4.401

5.  Tumor volume and subvolume concordance between FDG-PET/CT and diffusion-weighted MRI for squamous cell carcinoma of the cervix.

Authors:  Jeffrey R Olsen; Jacqueline Esthappan; Todd DeWees; Vamsi R Narra; Farrokh Dehdashti; Barry A Siegel; Julie K Schwarz; Perry W Grigsby
Journal:  J Magn Reson Imaging       Date:  2012-09-28       Impact factor: 4.813

6.  Endometrial Cancer: Combined MR Volumetry and Diffusion-weighted Imaging for Assessment of Myometrial and Lymphovascular Invasion and Tumor Grade.

Authors:  Stephanie Nougaret; Caroline Reinhold; Shaza S Alsharif; Helen Addley; Jocelyne Arceneau; Nicolas Molinari; Boris Guiu; Evis Sala
Journal:  Radiology       Date:  2015-04-30       Impact factor: 11.105

7.  Diffusion-Weighted Magnetic Resonance Imaging as a Predictor of Outcome in Cervical Cancer After Chemoradiation.

Authors:  Jennifer C Ho; Pamela K Allen; Priya R Bhosale; Gaiane M Rauch; Clifton D Fuller; Abdallah S R Mohamed; Michael Frumovitz; Anuja Jhingran; Ann H Klopp
Journal:  Int J Radiat Oncol Biol Phys       Date:  2016-11-17       Impact factor: 7.038

8.  Diffusion-weighted MR imaging in assessing cervical tumour response to nonsurgical therapy.

Authors:  S Rizzo; P Summers; S Raimondi; M Belmonte; M Maniglio; F Landoni; N Colombo; M Bellomi
Journal:  Radiol Med       Date:  2011-03-07       Impact factor: 3.469

9.  Volume Delineation in Cervical Cancer With T2 and Diffusion-weighted MRI: Agreement on Volumes Between Observers.

Authors:  Consuelo Rosa; Andrea Delli Pizzi; Antonietta Augurio; Luciana Caravatta; Monica DI Tommaso; Erica Mincuzzi; Sebastiano Cinalli; Raffaella Basilico; Annamaria Porreca; Marta DI Nicola; Domenico Genovesi
Journal:  In Vivo       Date:  2020 Jul-Aug       Impact factor: 2.155

10.  Intratumor Heterogeneity of Perfusion and Diffusion in Clear-Cell Renal Cell Carcinoma: Correlation With Tumor Cellularity.

Authors:  Qing Yuan; Payal Kapur; Yue Zhang; Yin Xi; Ingrid Carvo; Sabina Signoretti; Ivan E Dimitrov; Jeffrey A Cadeddu; Vitaly Margulis; James Brugarolas; Ananth J Madhuranthakam; Ivan Pedrosa
Journal:  Clin Genitourin Cancer       Date:  2016-04-22       Impact factor: 2.872

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