Literature DB >> 27635027

Predicting Pathologic Response of Esophageal Cancer to Neoadjuvant Chemotherapy: The Implications of Metabolic Nodal Response for Personalized Therapy.

John M Findlay1,2, Kevin M Bradley3, Lai Mun Wang2,4, James M Franklin3, Eugene J Teoh3, Fergus V Gleeson3, Nicholas D Maynard5, Richard S Gillies5, Mark R Middleton2,6.   

Abstract

Only a minority of esophageal cancers demonstrates a pathologic tumor response (pTR) to neoadjuvant chemotherapy (NAC). 18F-FDG PET/CT is often used for restaging after NAC and to assess response. Increasingly, it is used during therapy to identify unresponsive tumors and predict pTR, using avidity of the primary tumor alone. However, definitions of such metabolic tumor response (mTR) vary. We aimed to comprehensively reevaluate metabolic response assessment using accepted parameters, as well as novel concepts of metabolic nodal stage (mN) and metabolic nodal response (mNR).
METHODS: This was a single-center retrospective U.K. cohort study. All patients with esophageal cancer staged before NAC with PET/CT and after with CT or PET/CT and undergoing resection from 2006 to 2014 were identified. pTR was defined as Mandard tumor regression grade 1-3; imaging parameters included metrics of tumor avidity (SUVmax/mean/peak), composites of avidity and volume (including metabolic tumor volume), nodal SUVmax, and our new concepts of mN stage and mNR.
RESULTS: Eighty-two (27.2%) of 301 patients demonstrated pTR. No pre-NAC PET parameters predicted pTR. In 220 patients restaged by PET/CT, the optimal tumor ΔSUVmax threshold was a 77.8% reduction. This was as sensitive as the current PERCIST 30% reduction, but more specific with a higher negative predictive value (P < 0.001). ΔSUVmax and Δlength independently predicted pTR, and composite avidity/spatial metrics outperformed avidity alone. Although both mTR and mNR were associated with pTR, in 82 patients with 18F-FDG-avid nodes before NAC we observed mNR in 10 (12.2%) not demonstrating mTR.
CONCLUSION: Current definitions of metabolic response are suboptimal and too simplistic. Composite avidity/volume measures improve prediction. mNR may further improve response assessment, by specifically assessing metastatic tumor subpopulations, likely responsible for disease relapse, and should be urgently assessed when considering aborting therapy on the basis of mTR alone.
© 2017 by the Society of Nuclear Medicine and Molecular Imaging.

Entities:  

Keywords:  esophageal cancer; neoadjuvant therapy; positron-emission tomography; precision oncology

Mesh:

Substances:

Year:  2016        PMID: 27635027     DOI: 10.2967/jnumed.116.176313

Source DB:  PubMed          Journal:  J Nucl Med        ISSN: 0161-5505            Impact factor:   10.057


  11 in total

1.  Favorable versus unfavorable prognostic groups by post-chemoradiation FDG-PET imaging in node-positive esophageal squamous cell carcinoma patients treated with definitive chemoradiotherapy.

Authors:  Wing-Keen Yap; Yu-Chuan Chang; Chia-Hsun Hsieh; Yin-Kai Chao; Chien-Cheng Chen; Ming-Chieh Shih; Tsung-Min Hung
Journal:  Eur J Nucl Med Mol Imaging       Date:  2017-11-30       Impact factor: 9.236

2.  Value of early evaluation of treatment response using 18F-FDG PET/CT parameters and the Epstein-Barr virus DNA load for prediction of outcome in patients with primary nasopharyngeal carcinoma.

Authors:  Yu-Hung Chen; Kai-Ping Chang; Sung-Chao Chu; Tzu-Chen Yen; Ling-Yi Wang; Joseph Tung-Chieh Chang; Cheng-Lung Hsu; Shu-Hang Ng; Shu-Hsin Liu; Sheng-Chieh Chan
Journal:  Eur J Nucl Med Mol Imaging       Date:  2018-09-27       Impact factor: 9.236

3.  Composite metrics in response assessment-new hope in oesophageal cancer?

Authors:  Janusz Włodarczyk; Jarosław Kużdżał
Journal:  J Thorac Dis       Date:  2017-09       Impact factor: 2.895

4.  Challenges in assessing response of oesophageal cancer to neoadjuvant therapy, and the potential of composite PET-CT and multimodal metrics.

Authors:  John M Findlay; Kevin M Bradley; Richard S Gillies; Nicholas D Maynard; Mark R Middleton
Journal:  J Thorac Dis       Date:  2017-10       Impact factor: 2.895

Review 5.  Personalized therapy based on image for esophageal or gastroesophageal junction adenocarcinoma.

Authors:  Kazuto Harada; Dilsa Mizrak Kaya; Anthony Lopez; Hideo Baba; Jaffer A Ajani
Journal:  Ann Transl Med       Date:  2018-02

6.  Early Metabolic Change after Induction Chemotherapy Predicts Histologic Response and Prognosis in Patients with Esophageal Cancer: Secondary Analysis of a Randomized Trial.

Authors:  Kazuto Harada; Xuemei Wang; Yusuke Shimodaira; Tara Sagebiel; Manoop S Bhutani; Jeffrey H Lee; Brian Weston; Elena Elimova; Quan Lin; Fatemeh G Amlashi; Dilsa Mizrak Kaya; Anthony Lopez; Mariela A Blum Murphy; Jack A Roth; Stephen G Swisher; Heath D Skinner; Wayne L Hofstetter; Jane E Rogers; Irene Thomas; Dipen M Maru; Ritsuko Komaki; Garrett Walsh; Jaffer A Ajani
Journal:  Target Oncol       Date:  2018-02       Impact factor: 4.493

7.  Temporal validation of metabolic nodal response of esophageal cancer to neoadjuvant chemotherapy as an independent predictor of unresectable disease, survival, and recurrence.

Authors:  John M Findlay; Edward Dickson; Cristina Fiorani; Kevin M Bradley; Somnath Mukherjee; Richard S Gillies; Nicholas D Maynard; Mark R Middleton
Journal:  Eur Radiol       Date:  2019-07-05       Impact factor: 5.315

8.  Can Gastric Cancer Patients with High Mandard Score Benefit from Neoadjuvant Chemotherapy?

Authors:  Wen-Zhe Kang; Bing-Zhi Wang; Deng-Feng Li; Zhi-Chao Jiang; Jian-Ping Xiong; Yang Li; Peng Jin; Xin-Xin Shao; Hai-Tao Hu; Yan-Tao Tian
Journal:  Can J Gastroenterol Hepatol       Date:  2022-03-25

9.  A DNA-damage immune response assay combined with PET biomarkers predicts response to neo-adjuvant chemotherapy and survival in oesophageal adenocarcinoma.

Authors:  Kieran G Foley; Anita Lavery; Eoin Napier; David Campbell; Martin M Eatock; Richard D Kennedy; Kevin M Bradley; Richard C Turkington
Journal:  Sci Rep       Date:  2021-06-22       Impact factor: 4.379

10.  Routinely staging gastric cancer with 18F-FDG PET-CT detects additional metastases and predicts early recurrence and death after surgery.

Authors:  John M Findlay; Stefan Antonowicz; Ashvina Segaran; Jihene El Kafsi; Alexa Zhang; Kevin M Bradley; Richard S Gillies; Nicholas D Maynard; Mark R Middleton
Journal:  Eur Radiol       Date:  2019-01-14       Impact factor: 5.315

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