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Diffusion kurtosis imaging: correlation analysis of quantitative model parameters with molecular features in advanced lung adenocarcinoma
BACKGROUND: Due to development of magnetic resonance-based functional imaging, it is easier to detect micro-structural alterations of tumor tissues. The aim of this study was to conduct a preliminary evaluation of the correlation of non-Gaussian diffusion kurtosis imaging (DKI) parameters with expre...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Lippincott Williams & Wilkins
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7575189/ https://www.ncbi.nlm.nih.gov/pubmed/32960838 http://dx.doi.org/10.1097/CM9.0000000000001074 |
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author | Peng, Qin Tang, Wei Huang, Yao Wu, Ning Yang, Lin Li, Ni |
author_facet | Peng, Qin Tang, Wei Huang, Yao Wu, Ning Yang, Lin Li, Ni |
author_sort | Peng, Qin |
collection | PubMed |
description | BACKGROUND: Due to development of magnetic resonance-based functional imaging, it is easier to detect micro-structural alterations of tumor tissues. The aim of this study was to conduct a preliminary evaluation of the correlation of non-Gaussian diffusion kurtosis imaging (DKI) parameters with expression of molecular markers (epidermal growth factor receptor [EGFR]; anaplastic lymphoma kinase [ALK]; Ki-67 protein) in patients with advanced lung adenocarcinoma, using routine diffusion-weighted imaging as the reference standard. METHODS: Data from patients with primary lung adenocarcinoma diagnosed at Cancer Hospital, Chinese Academy of Medical Sciences (CHCAMS) from 2016 to 2019 were collected for retrospective analysis. The pathologic and magnetic resonance imaging data of 96 patients who met the inclusion criteria were included in this study. Specifically, the K(app) and D(app) parameters measured from the DKI model; apparent diffusion coefficient (ADC) value from the diffusion-weighted imaging model; and the EGFR, ALK, and Ki-67 biomarkers detected by immunohistochemistry and/or molecular biology techniques after biopsy or surgery were evaluated. The relations between quantitative parameters (ADC, K(app), D(app)) and pathologic outcomes (EGFR, ALK, and Ki-67 expression) were analyzed by Spearman correlation test. RESULTS: Of the 96 lung adenocarcinoma lesions (from 96 patients), the number of EGFR- and ALK-positive and high Ki-67 expressing lesions were 53, 12, and 83, respectively. The K(app) values were significantly higher among patients with EGFR-positive mutations (0.81 ± 0.12 vs. 0.66 ± 0.10, t = 6.41, P < 0.001), ALK rearrangement-negative (0.76 ± 0.12 vs. 0.60 ± 0.15, t = 4.09, P < 0.001), and high Ki-67 proliferative index (PI) (0.76 ± 0.12 vs. 0.58 ± 0.13, t = 4.88, P < 0.001). The D(app) values were significantly lower among patients with high Ki-67 PI (3.19 ± 0.69 μm(2)/ms vs. 4.20 ± 0.83 μm(2)/ms, t = 4.80, P < 0.001) and EGFR-positive mutations (3.11 ± 0.73 μm(2)/ms vs. 3.59 ± 0.77 μm(2)/ms, t = 3.12, P = 0.002). The differences in mean D(app) (3.73 ± 1.26 μm(2)/ms vs. 3.26 ± 0.68 μm(2)/ms, t = 1.96, P = 0.053) or ADC values ([1.34 ± 0.81] × 10(−3) mm(2)/s vs. [1.33 ± 0.41] × 10(−3) mm(2)/s, t = 0.07, P = 0.941) between the groups with or without ALK rearrangements were not statistically significant. The ADC values were significantly lower among patients with EGFR-positive mutation ([1.19 ± 0.37] × 10(−3) mm(2)/s vs. [1.50 ± 0.53] × 10(−3) mm(2)/s, t = 3.38, P = 0.001) and high Ki-67 PI ([1.28 ± 0.39] × 10(−3) mm(2)/s vs. [1.67 ± 0.77] × 10(−3) mm(2)/s, t = 2.88, P = 0.005). K(app) was strongly positively correlated with EGFR mutations (r = 0.844, P = 0.008), strongly positively correlated with Ki-67 PI (r = 0.882, P = 0.001), and strongly negatively correlated with ALK rearrangements (r = −0.772, P = 0.001). D(app) was moderately correlated with EGFR mutations (r = −0.650, P = 0.024) or Ki-67 PI (r = −0.734, P = 0.012). ADC was moderately correlated with Ki-67 PI (r = −0.679, P = 0.033). CONCLUSIONS: The K(app) value of DKI parameters was strongly correlated with different expression of EGFR, ALK, and Ki-67 in advanced lung adenocarcinoma. The results potentially indicate a surrogate measure of the status of different molecular markers assessed by non-invasive imaging tools. |
format | Online Article Text |
id | pubmed-7575189 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Lippincott Williams & Wilkins |
record_format | MEDLINE/PubMed |
spelling | pubmed-75751892020-10-29 Diffusion kurtosis imaging: correlation analysis of quantitative model parameters with molecular features in advanced lung adenocarcinoma Peng, Qin Tang, Wei Huang, Yao Wu, Ning Yang, Lin Li, Ni Chin Med J (Engl) Original Articles BACKGROUND: Due to development of magnetic resonance-based functional imaging, it is easier to detect micro-structural alterations of tumor tissues. The aim of this study was to conduct a preliminary evaluation of the correlation of non-Gaussian diffusion kurtosis imaging (DKI) parameters with expression of molecular markers (epidermal growth factor receptor [EGFR]; anaplastic lymphoma kinase [ALK]; Ki-67 protein) in patients with advanced lung adenocarcinoma, using routine diffusion-weighted imaging as the reference standard. METHODS: Data from patients with primary lung adenocarcinoma diagnosed at Cancer Hospital, Chinese Academy of Medical Sciences (CHCAMS) from 2016 to 2019 were collected for retrospective analysis. The pathologic and magnetic resonance imaging data of 96 patients who met the inclusion criteria were included in this study. Specifically, the K(app) and D(app) parameters measured from the DKI model; apparent diffusion coefficient (ADC) value from the diffusion-weighted imaging model; and the EGFR, ALK, and Ki-67 biomarkers detected by immunohistochemistry and/or molecular biology techniques after biopsy or surgery were evaluated. The relations between quantitative parameters (ADC, K(app), D(app)) and pathologic outcomes (EGFR, ALK, and Ki-67 expression) were analyzed by Spearman correlation test. RESULTS: Of the 96 lung adenocarcinoma lesions (from 96 patients), the number of EGFR- and ALK-positive and high Ki-67 expressing lesions were 53, 12, and 83, respectively. The K(app) values were significantly higher among patients with EGFR-positive mutations (0.81 ± 0.12 vs. 0.66 ± 0.10, t = 6.41, P < 0.001), ALK rearrangement-negative (0.76 ± 0.12 vs. 0.60 ± 0.15, t = 4.09, P < 0.001), and high Ki-67 proliferative index (PI) (0.76 ± 0.12 vs. 0.58 ± 0.13, t = 4.88, P < 0.001). The D(app) values were significantly lower among patients with high Ki-67 PI (3.19 ± 0.69 μm(2)/ms vs. 4.20 ± 0.83 μm(2)/ms, t = 4.80, P < 0.001) and EGFR-positive mutations (3.11 ± 0.73 μm(2)/ms vs. 3.59 ± 0.77 μm(2)/ms, t = 3.12, P = 0.002). The differences in mean D(app) (3.73 ± 1.26 μm(2)/ms vs. 3.26 ± 0.68 μm(2)/ms, t = 1.96, P = 0.053) or ADC values ([1.34 ± 0.81] × 10(−3) mm(2)/s vs. [1.33 ± 0.41] × 10(−3) mm(2)/s, t = 0.07, P = 0.941) between the groups with or without ALK rearrangements were not statistically significant. The ADC values were significantly lower among patients with EGFR-positive mutation ([1.19 ± 0.37] × 10(−3) mm(2)/s vs. [1.50 ± 0.53] × 10(−3) mm(2)/s, t = 3.38, P = 0.001) and high Ki-67 PI ([1.28 ± 0.39] × 10(−3) mm(2)/s vs. [1.67 ± 0.77] × 10(−3) mm(2)/s, t = 2.88, P = 0.005). K(app) was strongly positively correlated with EGFR mutations (r = 0.844, P = 0.008), strongly positively correlated with Ki-67 PI (r = 0.882, P = 0.001), and strongly negatively correlated with ALK rearrangements (r = −0.772, P = 0.001). D(app) was moderately correlated with EGFR mutations (r = −0.650, P = 0.024) or Ki-67 PI (r = −0.734, P = 0.012). ADC was moderately correlated with Ki-67 PI (r = −0.679, P = 0.033). CONCLUSIONS: The K(app) value of DKI parameters was strongly correlated with different expression of EGFR, ALK, and Ki-67 in advanced lung adenocarcinoma. The results potentially indicate a surrogate measure of the status of different molecular markers assessed by non-invasive imaging tools. Lippincott Williams & Wilkins 2020-10-20 2020-09-21 /pmc/articles/PMC7575189/ /pubmed/32960838 http://dx.doi.org/10.1097/CM9.0000000000001074 Text en Copyright © 2020 The Chinese Medical Association, produced by Wolters Kluwer, Inc. under the CC-BY-NC-ND license. http://creativecommons.org/licenses/by-nc-nd/4.0 This is an open access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND), where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal. http://creativecommons.org/licenses/by-nc-nd/4.0 |
spellingShingle | Original Articles Peng, Qin Tang, Wei Huang, Yao Wu, Ning Yang, Lin Li, Ni Diffusion kurtosis imaging: correlation analysis of quantitative model parameters with molecular features in advanced lung adenocarcinoma |
title | Diffusion kurtosis imaging: correlation analysis of quantitative model parameters with molecular features in advanced lung adenocarcinoma |
title_full | Diffusion kurtosis imaging: correlation analysis of quantitative model parameters with molecular features in advanced lung adenocarcinoma |
title_fullStr | Diffusion kurtosis imaging: correlation analysis of quantitative model parameters with molecular features in advanced lung adenocarcinoma |
title_full_unstemmed | Diffusion kurtosis imaging: correlation analysis of quantitative model parameters with molecular features in advanced lung adenocarcinoma |
title_short | Diffusion kurtosis imaging: correlation analysis of quantitative model parameters with molecular features in advanced lung adenocarcinoma |
title_sort | diffusion kurtosis imaging: correlation analysis of quantitative model parameters with molecular features in advanced lung adenocarcinoma |
topic | Original Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7575189/ https://www.ncbi.nlm.nih.gov/pubmed/32960838 http://dx.doi.org/10.1097/CM9.0000000000001074 |
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