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Lookup NU author(s): Dr Jiabao He
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
Copyright © 2023 Cheung, Wu, Senn, Sharma, McGoldrick, Gagliardi, Husain, Masannat and He. Introduction: The early identification of good responders to neoadjuvant chemotherapy (NACT) holds a significant potential in the optimal treatment of breast cancer. A recent Bayesian approach has been postulated to improve the accuracy of the intravoxel incoherent motion (IVIM) model for clinical translation. This study examined the prediction and early sensitivity of Bayesian IVIM to NACT response. Materials and methods: Seventeen female patients with breast cancer were scanned at baseline and 16 patients were scanned after Cycle 1. Tissue diffusion and perfusion from Bayesian IVIM were calculated at baseline with percentage change at Cycle 1 computed with reference to baseline. Cellular proliferative activity marker Ki-67 was obtained semi-quantitatively with percentage change at excision computed with reference to core biopsy. Results: The perfusion fraction showed a significant difference (p = 0.042) in percentage change between responder groups at Cycle 1, with a decrease in good responders [−7.98% (−19.47–1.73), n = 7] and an increase in poor responders [10.04% (5.09–28.93), n = 9]. There was a significant correlation between percentage change in perfusion fraction and percentage change in Ki-67 (p = 0.042). Tissue diffusion and pseudodiffusion showed no significant difference in percentage change between groups at Cycle 1, nor was there a significant correlation against percentage change in Ki-67. Perfusion fraction, tissue diffusion, and pseudodiffusion showed no significant difference between groups at baseline, nor was there a significant correlation against Ki-67 from core biopsy. Conclusion: The alteration in tumour perfusion fraction from the Bayesian IVIM model, in association with cellular proliferation, showed early sensitivity to good responders in NACT. Clinical trial registration: https://clinicaltrials.gov/ct2/show/NCT03501394, identifier NCT03501394.
Author(s): Cheung SM, Wu W-S, Senn N, Sharma R, McGoldrick T, Gagliardi T, Husain E, Masannat Y, He J
Publication type: Article
Publication status: Published
Journal: Frontiers in Oncology
Year: 2023
Volume: 13
Online publication date: 06/12/2023
Acceptance date: 21/11/2023
Date deposited: 04/03/2024
ISSN (electronic): 2234-943X
Publisher: Frontiers Media SA
URL: https://doi.org/10.3389/fonc.2023.1277556
DOI: 10.3389/fonc.2023.1277556
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