Literature DB >> 27296409

Dynamic contrast-enhanced MRI for treatment response assessment in patients with oesophageal cancer receiving neoadjuvant chemoradiotherapy.

Sophie E Heethuis1, Peter S N van Rossum2, Irene M Lips3, Lucas Goense2, Francine E Voncken4, Onne Reerink3, Richard van Hillegersberg5, Jelle P Ruurda5, Marielle E Philippens3, Marco van Vulpen3, Gert J Meijer3, Jan J W Lagendijk3, Astrid L H M W van Lier3.   

Abstract

PURPOSE: To explore and evaluate the potential value of dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) for the prediction of pathologic response to neoadjuvant chemoradiotherapy (nCRT) in oesophageal cancer.
MATERIAL AND METHODS: Twenty-six patients underwent DCE-MRI before, during (week 2-3) and after nCRT, but before surgery (pre/per/post, respectively). Histopathologic tumour regression grade (TRG) was assessed after oesophagectomy. Tumour area-under-the-concentration time curve (AUC), time-to-peak (TTP) and slope were calculated. The ability of these DCE-parameters to distinguish good responders (GR, TRG 1-2) from poor responders (noGR, TRG⩾3), and pathologic complete responders (pCR) from no-pCR was assessed.
RESULTS: Twelve patients (48%) showed GR of which 8 patients (32%) pCR. Analysis of AUC change throughout treatment, AUCper-pre, was most predictive for GR, at a threshold of 22.7% resulting in a sensitivity of 92%, specificity of 77%, PPV of 79%, and a NPV of 91%. AUCpost-pre was most predictive for pCR, at a threshold of -24.6% resulting in a sensitivity of 83%, specificity of 88%, PPV of 71%, and a NPV of 93%. TTP and slope were not associated with pathologic response.
CONCLUSIONS: This study demonstrates that changes in AUC throughout treatment are promising for prediction of histopathologic response to nCRT for oesophageal cancer.
Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Entities:  

Keywords:  Chemoradiotherapy; Dynamic contrast-enhanced MRI; Neoadjuvant therapy; Oesophageal cancer; Treatment Outcome

Mesh:

Substances:

Year:  2016        PMID: 27296409     DOI: 10.1016/j.radonc.2016.05.009

Source DB:  PubMed          Journal:  Radiother Oncol        ISSN: 0167-8140            Impact factor:   6.280


  18 in total

1.  Dynamic contrast-enhanced MRI for advanced esophageal cancer response assessment after concurrent chemoradiotherapy.

Authors:  Na-Na Sun; Chang Liu; Xiao-Lin Ge; Jie Wang
Journal:  Diagn Interv Radiol       Date:  2018-07       Impact factor: 2.630

2.  Histogram analysis of DCE-MRI for chemoradiotherapy response evaluation in locally advanced esophageal squamous cell carcinoma.

Authors:  Na-Na Sun; Xiao-Lin Ge; Xi-Sheng Liu; Lu-Lu Xu
Journal:  Radiol Med       Date:  2019-10-11       Impact factor: 3.469

3.  Patient perspectives on repeated MRI and PET/CT examinations during neoadjuvant treatment of esophageal cancer.

Authors:  Lucas Goense; Alicia S Borggreve; Sophie E Heethuis; Astrid Lhmw van Lier; Richard van Hillegersberg; Stella Mook; Gert J Meijer; Peter S N van Rossum; Jelle P Ruurda
Journal:  Br J Radiol       Date:  2018-03-14       Impact factor: 3.039

4.  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

5.  Can Clinical Response Predict Pathologic Response Following Neoadjuvant Chemoradiation for Esophageal Cancer?

Authors:  Puja G Khaitan; Tyler Holliday; Austin Carroll; Wayne L Hofstetter; Erin M Bayley; Nicolas Zhou; Sameer Desale; Thomas J Watson
Journal:  J Gastrointest Surg       Date:  2022-04-12       Impact factor: 3.267

6.  Radiomic analysis in T2W and SPAIR T2W MRI: predict treatment response to chemoradiotherapy in esophageal squamous cell carcinoma.

Authors:  Zhen Hou; Shuangshuang Li; Wei Ren; Juan Liu; Jing Yan; Suiren Wan
Journal:  J Thorac Dis       Date:  2018-04       Impact factor: 2.895

7.  Preoperative Nomogram to Risk Stratify Patients for the Benefit of Trimodality Therapy in Esophageal Adenocarcinoma.

Authors:  Lucas Goense; Peter S N van Rossum; Mian Xi; Dipen M Maru; Brett W Carter; Gert J Meijer; Linus Ho; Richard van Hillegersberg; Wayne L Hofstetter; Steven H Lin
Journal:  Ann Surg Oncol       Date:  2018-03-22       Impact factor: 5.344

8.  DCE-MRI-Derived Volume Transfer Constant (Ktrans) and DWI Apparent Diffusion Coefficient as Predictive Markers of Short- and Long-Term Efficacy of Chemoradiotherapy in Patients With Esophageal Cancer.

Authors:  Zhi-Min Ye; Shu-Jun Dai; Feng-Qin Yan; Lei Wang; Jun Fang; Zhen-Fu Fu; Yue-Zhen Wang
Journal:  Technol Cancer Res Treat       Date:  2018-01-01

Review 9.  Cancer Metabolism and Tumor Heterogeneity: Imaging Perspectives Using MR Imaging and Spectroscopy.

Authors:  Gigin Lin; Kayvan R Keshari; Jae Mo Park
Journal:  Contrast Media Mol Imaging       Date:  2017-10-09       Impact factor: 3.161

10.  Preoperative image-guided identification of response to neoadjuvant chemoradiotherapy in esophageal cancer (PRIDE): a multicenter observational study.

Authors:  A S Borggreve; S Mook; M Verheij; V E M Mul; J J Bergman; A Bartels-Rutten; L C Ter Beek; R G H Beets-Tan; R J Bennink; M I van Berge Henegouwen; L A A Brosens; I L Defize; J M van Dieren; H Dijkstra; R van Hillegersberg; M C Hulshof; H W M van Laarhoven; M G E H Lam; A L H M W van Lier; C T Muijs; W B Nagengast; A J Nederveen; W Noordzij; J T M Plukker; P S N van Rossum; J P Ruurda; J W van Sandick; B L A M Weusten; F E M Voncken; D Yakar; G J Meijer
Journal:  BMC Cancer       Date:  2018-10-20       Impact factor: 4.430

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