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Response assessment of post-treatment head and neck cancers to determine further management using NI-RADS (Neck Imaging Reporting and Data System): a subgroup analysis of a randomized controlled trial

OBJECTIVE: Interpreting complex post-treatment changes in head and neck cancer (HNC) is challenging with further added perplexity due to variable interobserver interpretation and hence evolved the NI-RADS lexicon. We evaluated the accuracy of NI-RADS in predicting disease status on 1st post-treatmen...

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Autores principales: Mahajan, Abhishek, Unde, Himangi, Sable, Nilesh P., Shukla, Shreya, Vaish, Richa, Patil, Vijay, Agarwal, Ujjwal, Agrawal, Archi, Noronha, Vanita, Joshi, Amit, Kapoor, Akhil, Menon, Nandini, Agarwal, Jai Prakash, Laskar, Sarbani Ghosh, Dcruz, Anil Keith, Chaturvedi, Pankaj, Pai, Prathamesh, Rane, Swapnil Ulhas, Bal, Munita, Patil, Asawari, Prabhash, Kumar
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10552531/
https://www.ncbi.nlm.nih.gov/pubmed/37810970
http://dx.doi.org/10.3389/fonc.2023.1200366
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author Mahajan, Abhishek
Unde, Himangi
Sable, Nilesh P.
Shukla, Shreya
Vaish, Richa
Patil, Vijay
Agarwal, Ujjwal
Agrawal, Archi
Noronha, Vanita
Joshi, Amit
Kapoor, Akhil
Menon, Nandini
Agarwal, Jai Prakash
Laskar, Sarbani Ghosh
Dcruz, Anil Keith
Chaturvedi, Pankaj
Pai, Prathamesh
Rane, Swapnil Ulhas
Bal, Munita
Patil, Asawari
Prabhash, Kumar
author_facet Mahajan, Abhishek
Unde, Himangi
Sable, Nilesh P.
Shukla, Shreya
Vaish, Richa
Patil, Vijay
Agarwal, Ujjwal
Agrawal, Archi
Noronha, Vanita
Joshi, Amit
Kapoor, Akhil
Menon, Nandini
Agarwal, Jai Prakash
Laskar, Sarbani Ghosh
Dcruz, Anil Keith
Chaturvedi, Pankaj
Pai, Prathamesh
Rane, Swapnil Ulhas
Bal, Munita
Patil, Asawari
Prabhash, Kumar
author_sort Mahajan, Abhishek
collection PubMed
description OBJECTIVE: Interpreting complex post-treatment changes in head and neck cancer (HNC) is challenging with further added perplexity due to variable interobserver interpretation and hence evolved the NI-RADS lexicon. We evaluated the accuracy of NI-RADS in predicting disease status on 1st post-treatment follow-up CECT in a homogenous cohort of those who received only chemoradiation. METHODS: Retrospective analysis of imaging was done for LASHNC patients who received radical chemoradiation in an open-label, investigator-initiated, phase 3 randomized trial (2012-2018) randomly assigned to either radical radiotherapy with concurrent weekly cisplatin (CRT) or CRT with the same schedule plus weekly nimotuzumab (NCRT). 536 patients were accrued, and 74 patients who did not undergo PET/CECT after 8 weeks post-CRT were excluded. After assessing 462 patients for eligibility to allocate NI-RADS at primary and node sites, 435 cases fell in the Primary disease cohort and 412 cases in the Node disease cohort. We evaluated sensitivity, disease prevalence, the positive and negative predictive value of the NI-RADS lexicon, and accuracy, which were expressed as percentages. We also prepared flow charts to determine concordance with allocated NI-RADS category and established accuracy with which it can identify disease status. RESULTS: Out of 435 primary disease cohort, 92%, 55%, 48%,70% were concordant and had 100%, 72%, 70%, 82% accuracy in NI-RADS1 (n=12), NI-RADS2 (n=261), NIRADS3 (n=105), and NI-RADS 4 (n=60) respectively. Out of 412 nodes disease cohort, 95%, 90%, 48%, 70%were concordant and had 92%, 97%, 90%, 67% accuracy in NI-RADS1 (n=57), NI-RADS2 (n=255), NI-RADS3 (n=105) and NI-RADS4 (n=60) respectively. % concordance of PET/CT and CECT across all primary and node disease cohorts revealed that PET/CT was 91% concordant in primary NI-RADS2 as compared to 55% concordance of CECT whereas concordance of CECT was better with 57% in primary NI-RADS3 cohort as compared to PET/CT concordance of 41%. CONCLUSION: The accuracy with which the NI-RADS lexicon performed in our study at node sites was better than that at the primary site. There is a great scope of research to understand if CECT performs better over clinical disease status in NI-RADS 3 and 4 categories. Further research should be carried out to understand if PET/CECT can be used for close interval follow-up in stage III/IV NI-RADS 2 cases.
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spelling pubmed-105525312023-10-06 Response assessment of post-treatment head and neck cancers to determine further management using NI-RADS (Neck Imaging Reporting and Data System): a subgroup analysis of a randomized controlled trial Mahajan, Abhishek Unde, Himangi Sable, Nilesh P. Shukla, Shreya Vaish, Richa Patil, Vijay Agarwal, Ujjwal Agrawal, Archi Noronha, Vanita Joshi, Amit Kapoor, Akhil Menon, Nandini Agarwal, Jai Prakash Laskar, Sarbani Ghosh Dcruz, Anil Keith Chaturvedi, Pankaj Pai, Prathamesh Rane, Swapnil Ulhas Bal, Munita Patil, Asawari Prabhash, Kumar Front Oncol Oncology OBJECTIVE: Interpreting complex post-treatment changes in head and neck cancer (HNC) is challenging with further added perplexity due to variable interobserver interpretation and hence evolved the NI-RADS lexicon. We evaluated the accuracy of NI-RADS in predicting disease status on 1st post-treatment follow-up CECT in a homogenous cohort of those who received only chemoradiation. METHODS: Retrospective analysis of imaging was done for LASHNC patients who received radical chemoradiation in an open-label, investigator-initiated, phase 3 randomized trial (2012-2018) randomly assigned to either radical radiotherapy with concurrent weekly cisplatin (CRT) or CRT with the same schedule plus weekly nimotuzumab (NCRT). 536 patients were accrued, and 74 patients who did not undergo PET/CECT after 8 weeks post-CRT were excluded. After assessing 462 patients for eligibility to allocate NI-RADS at primary and node sites, 435 cases fell in the Primary disease cohort and 412 cases in the Node disease cohort. We evaluated sensitivity, disease prevalence, the positive and negative predictive value of the NI-RADS lexicon, and accuracy, which were expressed as percentages. We also prepared flow charts to determine concordance with allocated NI-RADS category and established accuracy with which it can identify disease status. RESULTS: Out of 435 primary disease cohort, 92%, 55%, 48%,70% were concordant and had 100%, 72%, 70%, 82% accuracy in NI-RADS1 (n=12), NI-RADS2 (n=261), NIRADS3 (n=105), and NI-RADS 4 (n=60) respectively. Out of 412 nodes disease cohort, 95%, 90%, 48%, 70%were concordant and had 92%, 97%, 90%, 67% accuracy in NI-RADS1 (n=57), NI-RADS2 (n=255), NI-RADS3 (n=105) and NI-RADS4 (n=60) respectively. % concordance of PET/CT and CECT across all primary and node disease cohorts revealed that PET/CT was 91% concordant in primary NI-RADS2 as compared to 55% concordance of CECT whereas concordance of CECT was better with 57% in primary NI-RADS3 cohort as compared to PET/CT concordance of 41%. CONCLUSION: The accuracy with which the NI-RADS lexicon performed in our study at node sites was better than that at the primary site. There is a great scope of research to understand if CECT performs better over clinical disease status in NI-RADS 3 and 4 categories. Further research should be carried out to understand if PET/CECT can be used for close interval follow-up in stage III/IV NI-RADS 2 cases. Frontiers Media S.A. 2023-09-21 /pmc/articles/PMC10552531/ /pubmed/37810970 http://dx.doi.org/10.3389/fonc.2023.1200366 Text en Copyright © 2023 Mahajan, Unde, Sable, Shukla, Vaish, Patil, Agarwal, Agrawal, Noronha, Joshi, Kapoor, Menon, Agarwal, Laskar, Dcruz, Chaturvedi, Pai, Rane, Bal, Patil and Prabhash https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Oncology
Mahajan, Abhishek
Unde, Himangi
Sable, Nilesh P.
Shukla, Shreya
Vaish, Richa
Patil, Vijay
Agarwal, Ujjwal
Agrawal, Archi
Noronha, Vanita
Joshi, Amit
Kapoor, Akhil
Menon, Nandini
Agarwal, Jai Prakash
Laskar, Sarbani Ghosh
Dcruz, Anil Keith
Chaturvedi, Pankaj
Pai, Prathamesh
Rane, Swapnil Ulhas
Bal, Munita
Patil, Asawari
Prabhash, Kumar
Response assessment of post-treatment head and neck cancers to determine further management using NI-RADS (Neck Imaging Reporting and Data System): a subgroup analysis of a randomized controlled trial
title Response assessment of post-treatment head and neck cancers to determine further management using NI-RADS (Neck Imaging Reporting and Data System): a subgroup analysis of a randomized controlled trial
title_full Response assessment of post-treatment head and neck cancers to determine further management using NI-RADS (Neck Imaging Reporting and Data System): a subgroup analysis of a randomized controlled trial
title_fullStr Response assessment of post-treatment head and neck cancers to determine further management using NI-RADS (Neck Imaging Reporting and Data System): a subgroup analysis of a randomized controlled trial
title_full_unstemmed Response assessment of post-treatment head and neck cancers to determine further management using NI-RADS (Neck Imaging Reporting and Data System): a subgroup analysis of a randomized controlled trial
title_short Response assessment of post-treatment head and neck cancers to determine further management using NI-RADS (Neck Imaging Reporting and Data System): a subgroup analysis of a randomized controlled trial
title_sort response assessment of post-treatment head and neck cancers to determine further management using ni-rads (neck imaging reporting and data system): a subgroup analysis of a randomized controlled trial
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10552531/
https://www.ncbi.nlm.nih.gov/pubmed/37810970
http://dx.doi.org/10.3389/fonc.2023.1200366
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