Literature DB >> 28969256

Role of Functional Magnetic Resonance Imaging Derived Parameters as Imaging Biomarkers and Correlation with Clinicopathological Features in Carcinoma of Uterine Cervix.

Ramireddy Jeba Karunya1, Putta Tharani2, Subhashini John3, Ramani Manoj Kumar4, Saikat Das5.   

Abstract

INTRODUCTION: Magnetic Resonance Imaging (MRI) is emerging as a powerful tool in the evaluation and management of cervical cancer. The role of Diffusion Weighted Imaging (DWI) with Apparent Diffusion Coefficient (ADC) as a non-invasive imaging biomarker is promising in characterization of the tumour and prediction of response. AIM: The aim of this study was to evaluate the role of conventional MRI and diffusion weighted MRI in predicting clinicopathological prognostic factors.
MATERIALS AND METHODS: This was a retrospective study. The data of 100 cervical cancer patients who had MRI with DWI was retrieved from the database and analysed. Clinico pathological details were collected from the computerized hospital information system. SPSS version 15.0 was used for statistical analysis.
RESULTS: The mean tumour dimensions on MRI in x, y and z axes were 43.04 mm (±13.93, range: 17-85), 37.05mm (±11.83, range: 9-80) and 39.63 mm (±14.81, range: 14 -76). The mean T2W MRI based tumour volume (TV) was 48.18 (±34.3, range: 7-206) and on DWI images was 36.68(±33.72, range: 2.5-200). The mean ADC value in patients with squamous cell carcinoma was 0.694 (±0.125, n=88), adenocarcinoma was 0.989 (±0.309, n=6), adenosquamous was 0.894 (±0.324, n=4). There was statistical significant difference in mean ADC between squamous vs. non squamous histology (p = 0.02). The mean ADC values of well differentiated, moderately differentiated, and poorly differentiated tumours were 0.841(±0.227, n= 26), 0.729 (±0.125, n=28), 0.648 (±0.099, n=46) respectively. There was significant statistical difference of mean ADC between well differentiated, moderately differentiated (p=0.020) and poorly differentiated tumours (p=0.0001). Difference between the mean ADC values between the node positive and node negative disease was statistically significant (p=0.0001). There was no correlation between the tumour volumes on T2W and DWI images and ADC values. Sixteen patients had residual/recurrent disease at a median follow up of 12 months (range: 3-59 months). The mean ADC values in this group was 0.71 (n=16) and was not significantly different from the disease free group (mean ADC =0.72, n=74).
CONCLUSION: Higher ADC values are associated with favourable histology and differentiation. Adenocarcinomas have higher ADC values followed by adenosquamous followed by squamous cell carcinomas. Well differentiated tumours had higher ADC values than moderately followed by poorly differentiated tumours. DWI with ADC have a potential role as an imaging biomarker for prognostication and needs further studies for routine clinical applications.

Entities:  

Keywords:  Apparent diffusion coefficient; Diffusion magnetic resonance imaging; Uterine cervical neoplasm

Year:  2017        PMID: 28969256      PMCID: PMC5620897          DOI: 10.7860/JCDR/2017/29165.10426

Source DB:  PubMed          Journal:  J Clin Diagn Res        ISSN: 0973-709X


  32 in total

1.  Role of conventional and diffusion weighted MRI in predicting treatment response after low dose radiation and chemotherapy in locally advanced carcinoma cervix.

Authors:  Saikat Das; Anuradha Chandramohan; Jeba Karunya Rami Reddy; Sramana Mukhopadhyay; Ramani Manoj Kumar; Rajesh Isiah; Subhashini John; Regi Oommen; Visalakshi Jeyaseelan
Journal:  Radiother Oncol       Date:  2015-10-20       Impact factor: 6.280

Review 2.  MRI of malignant neoplasms of the uterine corpus and cervix.

Authors:  Evis Sala; Suzanne Wakely; Emma Senior; David Lomas
Journal:  AJR Am J Roentgenol       Date:  2007-06       Impact factor: 3.959

3.  Treatment response evaluation using the mean apparent diffusion coefficient in cervical cancer patients treated with definitive chemoradiotherapy.

Authors:  Cem Onal; Gurcan Erbay; Ozan C Guler
Journal:  J Magn Reson Imaging       Date:  2016-02-27       Impact factor: 4.813

4.  Discrimination of metastatic from hyperplastic pelvic lymph nodes in patients with cervical cancer by diffusion-weighted magnetic resonance imaging.

Authors:  Yun B Chen; Jiang Liao; Rong Xie; Gui L Chen; Gang Chen
Journal:  Abdom Imaging       Date:  2011-02

5.  Predicting tumor recurrence in patients with cervical carcinoma treated with definitive chemoradiotherapy: value of quantitative histogram analysis on diffusion-weighted MR images.

Authors:  Gurcan Erbay; Cem Onal; Elif Karadeli; Ozan C Guler; Sami Arica; Zafer Koc
Journal:  Acta Radiol       Date:  2016-07-28       Impact factor: 1.990

6.  Histogram-based apparent diffusion coefficient analysis: an emerging tool for cervical cancer characterization?

Authors:  Andrew B Rosenkrantz
Journal:  AJR Am J Roentgenol       Date:  2013-02       Impact factor: 3.959

7.  Pre-treatment diffusion-weighted MR imaging for predicting tumor recurrence in uterine cervical cancer treated with concurrent chemoradiation: value of histogram analysis of apparent diffusion coefficients.

Authors:  Suk Hee Heo; Sang Soo Shin; Jin Woong Kim; Hyo Soon Lim; Yong Yeon Jeong; Woo Dae Kang; Seok Mo Kim; Heoung Keun Kang
Journal:  Korean J Radiol       Date:  2013-07-17       Impact factor: 3.500

8.  Apparent diffusion coefficient histogram shape analysis for monitoring early response in patients with advanced cervical cancers undergoing concurrent chemo-radiotherapy.

Authors:  Jie Meng; Lijing Zhu; Li Zhu; Huanhuan Wang; Song Liu; Jing Yan; Baorui Liu; Yue Guan; Yun Ge; Jian He; Zhengyang Zhou; Xiaofeng Yang
Journal:  Radiat Oncol       Date:  2016-10-22       Impact factor: 3.481

9.  Pre-treatment MRI minimum apparent diffusion coefficient value is a potential prognostic imaging biomarker in cervical cancer patients treated with definitive chemoradiation.

Authors:  Daniel Grossi Marconi; Jose Humberto Tavares Guerreiro Fregnani; Rodrigo Ribeiro Rossini; Ana Karina Borges Junqueira Netto; Fabiano Rubião Lucchesi; Audrey Tieko Tsunoda; Mitchell Kamrava
Journal:  BMC Cancer       Date:  2016-07-28       Impact factor: 4.430

10.  Relationship between imaging biomarkers of stage I cervical cancer and poor-prognosis histologic features: quantitative histogram analysis of diffusion-weighted MR images.

Authors:  Kate Downey; Sophie F Riches; Veronica A Morgan; Sharon L Giles; Ayoma D Attygalle; Tom E Ind; Desmond P J Barton; John H Shepherd; Nandita M deSouza
Journal:  AJR Am J Roentgenol       Date:  2013-02       Impact factor: 3.959

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  3 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.  Role of apparent diffusion coefficient as a biomarker in the evaluation of cervical cancer.

Authors:  Sunita Dashottar; T Preeth Pany; Nishant Lohia
Journal:  Indian J Radiol Imaging       Date:  2019 Jan-Mar

Review 3.  What Is the Role of Imaging at Primary Diagnostic Work-Up in Uterine Cervical Cancer?

Authors:  Ingfrid S Haldorsen; Njål Lura; Jan Blaakær; Daniela Fischerova; Henrica M J Werner
Journal:  Curr Oncol Rep       Date:  2019-07-29       Impact factor: 5.075

  3 in total

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