Literature DB >> 25208287

Diffusion-weighted imaging of gynecologic tumors: diagnostic pearls and potential pitfalls.

Sunita Dhanda1, Meenakshi Thakur, Rajendra Kerkar, Pooja Jagmohan.   

Abstract

Conventional magnetic resonance (MR) imaging has an established role in gynecologic imaging. However, increasing clinical demand for improved lesion characterization and disease mapping to optimize patient management has resulted in the incorporation of newer sequences, such as diffusion-weighted (DW) imaging, into routine protocols for pelvic MR imaging. DW imaging provides functional information about the microenvironment of water in tissues, hence augmenting the morphologic information derived from conventional MR images. It can depict shifts of water from extracellular to intracellular compartments, altered cell membrane permeability, disruption of cell membrane depolarization, and increased cellular density. Such changes may be associated with tumors. DW imaging has emerged as an important cancer biomarker and takes the role of the radiologist from the level of mere macroscopic diagnosis to more active participation in determining patient prognosis and management through a better understanding of the tumor microenvironment. With the growing acknowledgment of DW imaging as a pivotal tool in the radiologist's armamentarium, radiologists must be familiar with the appearances of various gynecologic tumors at DW imaging and understand the implications of this sequence for improving diagnostic accuracy and predicting and monitoring treatment response. Although positron emission tomography/computed tomography is extremely useful for detecting tumor recurrence in cervical and ovarian carcinomas, it has a limited specificity in the immediate posttreatment setting. DW imaging may aid in detection of residual or recurrent tumors in such situations. DW imaging is a potentially useful adjunct to conventional MR imaging for evaluation of gynecologic tumors, thus improving overall diagnostic accuracy, tumor staging, prediction of response to therapy, and treatment follow-up. ©RSNA, 2014.

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Year:  2014        PMID: 25208287     DOI: 10.1148/rg.345130131

Source DB:  PubMed          Journal:  Radiographics        ISSN: 0271-5333            Impact factor:   5.333


  16 in total

1.  Diffusion-weighted MR imaging of mediastinal lymphadenopathy.

Authors:  Ali Kemal Sivrioglu
Journal:  Jpn J Radiol       Date:  2015-11-03       Impact factor: 2.374

2.  Radiolabeled pertuzumab for imaging of human epidermal growth factor receptor 2 expression in ovarian cancer.

Authors:  Dawei Jiang; Hyung-Jun Im; Haiyan Sun; Hector F Valdovinos; Christopher G England; Emily B Ehlerding; Robert J Nickles; Dong Soo Lee; Steve Y Cho; Peng Huang; Weibo Cai
Journal:  Eur J Nucl Med Mol Imaging       Date:  2017-03-06       Impact factor: 9.236

3.  A prospective comparative dosimetric study between diffusion weighted MRI (DWI) & T2-weighted MRI (T2W) for target delineation and planning in cervical cancer brachytherapy.

Authors:  Rishabh Kumar; Geeta S Narayanan; Bhaskar Vishwanthan; Sowmya Narayanan; Sanjeet Mandal
Journal:  Rep Pract Oncol Radiother       Date:  2020-10-28

4.  The feasibility of reduced field-of-view diffusion-weighted imaging in evaluating bladder invasion of uterine cervical cancer.

Authors:  Mayumi Takeuchi; Kenji Matsuzaki; Masafumi Harada
Journal:  Br J Radiol       Date:  2021-10-27       Impact factor: 3.039

Review 5.  Restriction spectrum imaging: An evolving imaging biomarker in prostate MRI.

Authors:  Ryan L Brunsing; Natalie M Schenker-Ahmed; Nathan S White; J Kellogg Parsons; Christopher Kane; Joshua Kuperman; Hauke Bartsch; Andrew Karim Kader; Rebecca Rakow-Penner; Tyler M Seibert; Daniel Margolis; Steven S Raman; Carrie R McDonald; Nikdokht Farid; Santosh Kesari; Donna Hansel; Ahmed Shabaik; Anders M Dale; David S Karow
Journal:  J Magn Reson Imaging       Date:  2016-08-16       Impact factor: 4.813

6.  Pathological characteristics and risk stratification in patients with stage I endometrial cancer: utility of apparent diffusion coefficient histogram analysis.

Authors:  Taein An; Chan Kyo Kim
Journal:  Br J Radiol       Date:  2021-07-08       Impact factor: 3.629

7.  Value of Minimum Apparent Diffusion Coefficient on Magnetic Resonance Imaging as a Biomarker for Predicting Progression of Disease Following Surgery and Radiotherapy in Glial Tumors from a Tertiary Care Center in Northern India.

Authors:  Pramod Kumar Gupta; Rishi Awasthi; Shalini Singh; Sanjay Behari; K J Maria Das; Rakesh Kumar Gupta; Shaleen Kumar
Journal:  J Neurosci Rural Pract       Date:  2017 Apr-Jun

8.  Value of diffusion-weighted imaging combined with conventional magnetic resonance imaging in the diagnosis of thecomas/fibrothecomas and their differential diagnosis with malignant pelvic solid tumors.

Authors:  Bing Yin; Wenhua Li; Yanfen Cui; Caiting Chu; Ming Ding; Jian Chen; Ping Zhang; Xiangru Wu
Journal:  World J Surg Oncol       Date:  2016-01-08       Impact factor: 2.754

9.  Evaluating Myometrial Invasion in Endometrial Cancer: Comparison of Reduced Field-of-view Diffusion-weighted Imaging and Dynamic Contrast-enhanced MR Imaging.

Authors:  Mayumi Takeuchi; Kenji Matsuzaki; Masafumi Harada
Journal:  Magn Reson Med Sci       Date:  2017-05-18       Impact factor: 2.471

10.  Whole-lesion ADC histogram and texture analysis in predicting recurrence of cervical cancer treated with CCRT.

Authors:  Jie Meng; Lijing Zhu; Li Zhu; Li Xie; Huanhuan Wang; Song Liu; Jing Yan; Baorui Liu; Yue Guan; Jian He; Yun Ge; Zhengyang Zhou; Xiaofeng Yang
Journal:  Oncotarget       Date:  2017-09-28
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