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DOI: 10.4103/wjnm.WJNM_114_18
Using positron-emission tomography–computed tomography for predicting radiotherapy-induced tumor regression in carcinoma esophagus in an Indian population
Abstract
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 (SUVmax) 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%.
Financial support and sponsorship
Nil.
Publikationsverlauf
Eingereicht: 14. Dezember 2018
Angenommen: 11. April 2019
Artikel online veröffentlicht:
22. April 2022
© 2019. Sociedade Brasileira de Neurocirurgia. This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commecial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/)
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