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Using positron-emission tomography–computed tomography for predicting radiotherapy-induced tumor regression in carcinoma esophagus in an Indian population

Carcinoma esophagus is a common malignancy of the Indian subcontinent. The role of positron-emission tomography–computed tomography (PET-CT) in the assessment of response to radiotherapy has been widely studied and accepted. However, its precise use as a predictive tool for actual histopathological...

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Autores principales: Singh, Sankalp, Bisht, Niharika, Sarin, Arti, Kumar, A. V. S. Anil, Gupta, Samir, Kapoor, Amul, Mishra, Prabha Shankar
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Wolters Kluwer - Medknow 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6945352/
https://www.ncbi.nlm.nih.gov/pubmed/31933551
http://dx.doi.org/10.4103/wjnm.WJNM_114_18
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author Singh, Sankalp
Bisht, Niharika
Sarin, Arti
Kumar, A. V. S. Anil
Gupta, Samir
Kapoor, Amul
Mishra, Prabha Shankar
author_facet Singh, Sankalp
Bisht, Niharika
Sarin, Arti
Kumar, A. V. S. Anil
Gupta, Samir
Kapoor, Amul
Mishra, Prabha Shankar
author_sort Singh, Sankalp
collection PubMed
description Carcinoma esophagus is a common malignancy of the Indian subcontinent. The role of positron-emission tomography–computed tomography (PET-CT) in the assessment of response to radiotherapy has been widely studied and accepted. However, its precise use as a predictive tool for actual histopathological response to radiotherapy needs further evaluation, especially in an Indian population. The aim of this study was to identify a quantum of metabolic response on PET-CT that can also predict for a good pathological response. Forty-four patients of carcinoma esophagus treated with neoadjuvant chemoradiotherapy followed by surgery were included in the study. All patients underwent a PET-CT before starting treatment as well as at 4–6 weeks after completion of radiotherapy. The percentage change in pre and posttreatment maximum standardized uptake value (SUV(max)) value (ΔSUV%) of the primary tumor was correlated against histopathological tumor regression grade (TRG) as per the Mandard's system. Seventy-five percent of the patients with a significant metabolic response, i.e., a ΔSUV% of 60% or more, also had a good pathological response to treatment. Thus, by considering a ΔSUV% of 60%, we could predict for a good pathological response (TRG of 1 or 2) to chemoradiotherapy in our patient set with a sensitivity of 95.45% and a specificity of 72.72%.
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spelling pubmed-69453522020-01-13 Using positron-emission tomography–computed tomography for predicting radiotherapy-induced tumor regression in carcinoma esophagus in an Indian population Singh, Sankalp Bisht, Niharika Sarin, Arti Kumar, A. V. S. Anil Gupta, Samir Kapoor, Amul Mishra, Prabha Shankar World J Nucl Med Original Article Carcinoma esophagus is a common malignancy of the Indian subcontinent. The role of positron-emission tomography–computed tomography (PET-CT) in the assessment of response to radiotherapy has been widely studied and accepted. However, its precise use as a predictive tool for actual histopathological response to radiotherapy needs further evaluation, especially in an Indian population. The aim of this study was to identify a quantum of metabolic response on PET-CT that can also predict for a good pathological response. Forty-four patients of carcinoma esophagus treated with neoadjuvant chemoradiotherapy followed by surgery were included in the study. All patients underwent a PET-CT before starting treatment as well as at 4–6 weeks after completion of radiotherapy. The percentage change in pre and posttreatment maximum standardized uptake value (SUV(max)) value (ΔSUV%) of the primary tumor was correlated against histopathological tumor regression grade (TRG) as per the Mandard's system. Seventy-five percent of the patients with a significant metabolic response, i.e., a ΔSUV% of 60% or more, also had a good pathological response to treatment. Thus, by considering a ΔSUV% of 60%, we could predict for a good pathological response (TRG of 1 or 2) to chemoradiotherapy in our patient set with a sensitivity of 95.45% and a specificity of 72.72%. Wolters Kluwer - Medknow 2019-12-18 /pmc/articles/PMC6945352/ /pubmed/31933551 http://dx.doi.org/10.4103/wjnm.WJNM_114_18 Text en Copyright: © 2019 World Journal of Nuclear Medicine http://creativecommons.org/licenses/by-nc-sa/4.0 This is an open access journal, and articles are distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as appropriate credit is given and the new creations are licensed under the identical terms.
spellingShingle Original Article
Singh, Sankalp
Bisht, Niharika
Sarin, Arti
Kumar, A. V. S. Anil
Gupta, Samir
Kapoor, Amul
Mishra, Prabha Shankar
Using positron-emission tomography–computed tomography for predicting radiotherapy-induced tumor regression in carcinoma esophagus in an Indian population
title Using positron-emission tomography–computed tomography for predicting radiotherapy-induced tumor regression in carcinoma esophagus in an Indian population
title_full Using positron-emission tomography–computed tomography for predicting radiotherapy-induced tumor regression in carcinoma esophagus in an Indian population
title_fullStr Using positron-emission tomography–computed tomography for predicting radiotherapy-induced tumor regression in carcinoma esophagus in an Indian population
title_full_unstemmed Using positron-emission tomography–computed tomography for predicting radiotherapy-induced tumor regression in carcinoma esophagus in an Indian population
title_short Using positron-emission tomography–computed tomography for predicting radiotherapy-induced tumor regression in carcinoma esophagus in an Indian population
title_sort using positron-emission tomography–computed tomography for predicting radiotherapy-induced tumor regression in carcinoma esophagus in an indian population
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6945352/
https://www.ncbi.nlm.nih.gov/pubmed/31933551
http://dx.doi.org/10.4103/wjnm.WJNM_114_18
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