Literature DB >> 32446129

Tumor texture parameters of invasive ductal breast carcinoma in neoadjuvant chemotherapy: early identification of non-responders on breast MRI.

Mirjan M Nadrljanski1, Zorica C Milosevic2.   

Abstract

PURPOSE: Texture analysis (TA) parameters (variance of SI, mean of gradient, variance of gradient, kurtosis of SI, and entropy) in patients with invasive ductal carcinoma (IDC) contribute to objective assessment of neoadjuvant chemotherapy (NACT) activity. The objective was to assess TA parameters in early identification of non-responders (NR) in NACT, after the 2nd cycle of NACT.
MATERIAL AND METHODS: Fifty patients (N = 50) were included in the retrospective analysis of baseline and MRI following the 2nd cycle of NACT. TA parameters were computed and correlated to the lesion size and DWI-ADC in NR (N1 = 25). Additional matched responders (R, N2 = 25) assessed for the same parameters, served as the control group.
RESULTS: Tumor size and ADC did not change significantly in NR after the 2nd cycle of NACT (2.88 ± 0.38 vs. 2.76 ± 0.36 [cm], p = 0.131; 1.01 ± 0.14 vs. 1.05 ± 0.13 [mm2/s × 10-3], p = 0.363), but TA parameters changed significantly: variance of gradient (346.5 ± 12.6 vs. 355.6 ± 16.9, p = 0.01), kurtosis of SI (1.47 ± 0.09 vs. 1.54 ± 0.11, p = 0.02), entropy LH (60.39 ± 4.34 vs. 64.42 ± 3.05, p = 0.001) and entropy HL (61.02 ± 5.51 vs. 65.63 ± 3.63, p < 0.00001). TA parameters, particularly entropy (EN LH 64.42 ± 3.05 vs. 61.59 ± 1.76, p < 0.0001; EN HL 65.63 ± 3.63 vs. 62.89 ± 2.05, p < 0.0001), significantly differ between NR and R in early response assessment.
CONCLUSION: Entropy, kurtosis of SI and variance of gradient tend to increase in NR. TA parameters significantly differ between NR and R after the 2nd cycle of NACT. TA parameters, related to morpho-functional parameters may contribute to early NR identification.
Copyright © 2020 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Breast MRI; Breast carcinoma; Invasive breast carcinoma; Texture analysis

Year:  2020        PMID: 32446129     DOI: 10.1016/j.clinimag.2020.04.016

Source DB:  PubMed          Journal:  Clin Imaging        ISSN: 0899-7071            Impact factor:   1.605


  2 in total

1.  Radiomics of Tumor Heterogeneity in Longitudinal Dynamic Contrast-Enhanced Magnetic Resonance Imaging for Predicting Response to Neoadjuvant Chemotherapy in Breast Cancer.

Authors:  Ming Fan; Hang Chen; Chao You; Li Liu; Yajia Gu; Weijun Peng; Xin Gao; Lihua Li
Journal:  Front Mol Biosci       Date:  2021-03-22

2.  Delta-Radiomics Based on Dynamic Contrast-Enhanced MRI Predicts Pathologic Complete Response in Breast Cancer Patients Treated with Neoadjuvant Chemotherapy.

Authors:  Liangcun Guo; Siyao Du; Si Gao; Ruimeng Zhao; Guoliang Huang; Feng Jin; Yuee Teng; Lina Zhang
Journal:  Cancers (Basel)       Date:  2022-07-20       Impact factor: 6.575

  2 in total

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