Literature DB >> 28301309

Value of Dynamic Contrast-enhanced and Diffusion-weighted MR Imaging in the Detection of Pathologic Complete Response in Cervical Cancer after Neoadjuvant Therapy: A Retrospective Observational Study.

Aurélie Jalaguier-Coudray1, Rim Villard-Mahjoub1, Aurélie Delouche1, Béatrice Delarbre1, Eric Lambaudie1, Gilles Houvenaeghel1, Mathieu Minsat1, Agnès Tallet1, Renaud Sabatier1, Isabelle Thomassin-Naggara1.   

Abstract

Purpose To evaluate the association between dynamic contrast material-enhanced (DCE) and diffusion-weighted (DW) magnetic resonance (MR) imaging with pathologic complete response after preoperative combined chemotherapy and radiation therapy for cervical carcinoma and evaluate the risk of local recurrence. Materials and Methods The institutional ethics committee approved the study and waived the requirement to obtain informed consent. The study comprised 52 patients with locally advanced carcinoma, treated first with combined chemotherapy and radiation therapy, who underwent MR imaging before final surgery between June 2011 and July 2015. Three radiologists evaluated conventional, DW, and DCE MR images to identify a complete response. The standard of reference was surgical-pathologic findings. Results An initial increase in signal intensity on DCE MR images that was greater in the cervical lesion than in the myometrium was defined as time-signal intensity curve type B and showed a significant association with incomplete response (P = .0004). DCE MR imaging parameters (ie, maximum slope enhancement, area under the gadolinium concentration-time curve during the first 90 seconds after gadolinium injection [AUGC90], and volume transfer constant [Ktrans]) and a low signal intensity on apparent diffusion coefficient (ADC) maps were significantly associated with an incomplete response (P = .027, P = .041, P = .037, and P = .032, respectively). A mean ADC of 0.0014 m2/sec or less (hazard ratio [HR] = 8.3), low ADC signal intensity (HR = 7.3), high signal intensity at DW imaging (HR = 7.1), and time-signal intensity curve type B (HR = 4.3) were associated with earlier recurrence (P < .05). Excellent agreement between readers was found for time-signal intensity curve analysis (κ > 0.9) and the following parameters: AUGC90, Ktrans, and maximum slope enhancement (intraclass correlation coefficient, >0.9). Conclusion DCE MR imaging parameters, especially the time-signal intensity curve, and DW imaging are associated with complete response and incomplete response and could potentially help oncologists with management decisions. Moreover, DCE and DW MR imaging could help oncologists accentuate the follow-up for patients with a high risk of local recurrence to assess for recurrence. © RSNA, 2017 Online supplemental material is available for this article.

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Year:  2017        PMID: 28301309     DOI: 10.1148/radiol.2017161299

Source DB:  PubMed          Journal:  Radiology        ISSN: 0033-8419            Impact factor:   11.105


  17 in total

1.  Staging, recurrence and follow-up of uterine cervical cancer using MRI: Updated Guidelines of the European Society of Urogenital Radiology after revised FIGO staging 2018.

Authors:  Lucia Manganaro; Yulia Lakhman; Nishat Bharwani; Benedetta Gui; Silvia Gigli; Valeria Vinci; Stefania Rizzo; Aki Kido; Teresa Margarida Cunha; Evis Sala; Andrea Rockall; Rosemarie Forstner; Stephanie Nougaret
Journal:  Eur Radiol       Date:  2021-04-14       Impact factor: 5.315

2.  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

3.  Dynamic contrast-enhanced and diffusion-weighted MR imaging in early prediction of pathologic response to neoadjuvant chemotherapy in locally advanced gastric cancer.

Authors:  Hai-Liang Li; Jin-Rong Qu; Jing Li; Liang-Liang Yan; Hong-Kai Zhang; Yi Wang; Shu-Ning Xu
Journal:  Abdom Radiol (NY)       Date:  2022-08-02

4.  Imaging Biomarkers and Liquid Biopsy in Assessment of Cervical Cancer.

Authors:  Mansur A Ghani; Joy Liau; Ramez Eskander; Loren Mell; Tahir Yusufaly; Sebastian Obrzut
Journal:  J Comput Assist Tomogr       Date:  2022-08-16       Impact factor: 2.081

5.  Deep learning for fully automated tumor segmentation and extraction of magnetic resonance radiomics features in cervical cancer.

Authors:  Yu-Chun Lin; Chia-Hung Lin; Hsin-Ying Lu; Hsin-Ju Chiang; Ho-Kai Wang; Yu-Ting Huang; Shu-Hang Ng; Ji-Hong Hong; Tzu-Chen Yen; Chyong-Huey Lai; Gigin Lin
Journal:  Eur Radiol       Date:  2019-11-11       Impact factor: 5.315

6.  A preoperative radiomics model for the identification of lymph node metastasis in patients with early-stage cervical squamous cell carcinoma.

Authors:  Lifen Yan; Huasheng Yao; Ruichun Long; Lei Wu; Haotian Xia; Jinglei Li; Zaiyi Liu; Changhong Liang
Journal:  Br J Radiol       Date:  2020-10-06       Impact factor: 3.039

Review 7.  Dynamic contrast-enhanced (DCE) imaging: state of the art and applications in whole-body imaging.

Authors:  Domenico Albano; Federico Bruno; Andrea Agostini; Salvatore Alessio Angileri; Massimo Benenati; Giulia Bicchierai; Michaela Cellina; Vito Chianca; Diletta Cozzi; Ginevra Danti; Federica De Muzio; Letizia Di Meglio; Francesco Gentili; Giuliana Giacobbe; Giulia Grazzini; Irene Grazzini; Pasquale Guerriero; Carmelo Messina; Giuseppe Micci; Pierpaolo Palumbo; Maria Paola Rocco; Roberto Grassi; Vittorio Miele; Antonio Barile
Journal:  Jpn J Radiol       Date:  2021-12-24       Impact factor: 2.374

Review 8.  Radiomics in radiation oncology for gynecological malignancies: a review of literature.

Authors:  Morgan Michalet; David Azria; Marion Tardieu; Hichem Tibermacine; Stéphanie Nougaret
Journal:  Br J Radiol       Date:  2021-05-07       Impact factor: 3.629

Review 9.  Implications of the new FIGO staging and the role of imaging in cervical cancer.

Authors:  Aki Kido; Yuji Nakamoto
Journal:  Br J Radiol       Date:  2021-05-14       Impact factor: 3.629

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
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