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Can diffusion-weighted imaging predict tumor grade and expression of Ki-67 in breast cancer? A multicenter analysis

BACKGROUND: Numerous studies have analyzed associations between apparent diffusion coefficient (ADC) and histopathological features such as Ki-67 proliferation index in breast cancer (BC), with mixed results. The purpose of this study was to perform a multicenter analysis to determine relationships...

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Autores principales: Surov, Alexey, Clauser, Paola, Chang, Yun-Woo, Li, Lihua, Martincich, Laura, Partridge, Savannah C., Kim, Jin You, Meyer, Hans Jonas, Wienke, Andreas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6011203/
https://www.ncbi.nlm.nih.gov/pubmed/29921323
http://dx.doi.org/10.1186/s13058-018-0991-1
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author Surov, Alexey
Clauser, Paola
Chang, Yun-Woo
Li, Lihua
Martincich, Laura
Partridge, Savannah C.
Kim, Jin You
Meyer, Hans Jonas
Wienke, Andreas
author_facet Surov, Alexey
Clauser, Paola
Chang, Yun-Woo
Li, Lihua
Martincich, Laura
Partridge, Savannah C.
Kim, Jin You
Meyer, Hans Jonas
Wienke, Andreas
author_sort Surov, Alexey
collection PubMed
description BACKGROUND: Numerous studies have analyzed associations between apparent diffusion coefficient (ADC) and histopathological features such as Ki-67 proliferation index in breast cancer (BC), with mixed results. The purpose of this study was to perform a multicenter analysis to determine relationships between ADC and expression of Ki-67 and tumor grade in BC. METHODS: For this study, data from six centers were acquired. The sample comprises 870 patients (all female; mean age, 52.6 ± 10.8 years). In every case, breast magnetic resonance imaging with diffusion-weighted imaging was performed. The comparison of ADC values in groups was performed by Mann-Whitney U test where the p values are adjusted for multiple testing (Bonferroni correction). The association between ADC and Ki-67 values was calculated by Spearman’s rank correlation coefficient. Sensitivity, specificity, negative and positive predictive values, accuracy, and AUC were calculated for the diagnostic procedures. ADC thresholds were chosen to maximize the Youden index. RESULTS: Overall, data of 870 patients were acquired for this study. The mean ADC value of the tumors was 0.98 ± 0.22 × 10(− 3) mm(2) s(− 1). ROC analysis showed that it is impossible to differentiate high/moderate grade tumors from grade 1 lesions using ADC values. Youden index identified a threshold ADC value of 1.03 with a sensitivity of 56.2% and specificity of 67.9%. The positive predictive value was 18.2%, and the negative predictive value was 92.4%. The level of the Ki-67 proliferation index was available for 845 patients. The mean value was 12.33 ± 21.77%. ADC correlated with weak statistical significant with expression of Ki-67 (p = − 0.202, p < 0.001). ROC analysis was performed to distinguish tumors with high proliferative potential from tumors with low expression of Ki-67 using ADC values. Youden index identified a threshold ADC value of 0.91 (sensitivity 64%, specificity 50%, positive predictive value 67.7%, negative predictive value 45.0%). CONCLUSIONS: ADC cannot be used as a surrogate marker for proliferation activity and/or for tumor grade in breast cancer.
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spelling pubmed-60112032018-06-27 Can diffusion-weighted imaging predict tumor grade and expression of Ki-67 in breast cancer? A multicenter analysis Surov, Alexey Clauser, Paola Chang, Yun-Woo Li, Lihua Martincich, Laura Partridge, Savannah C. Kim, Jin You Meyer, Hans Jonas Wienke, Andreas Breast Cancer Res Research Article BACKGROUND: Numerous studies have analyzed associations between apparent diffusion coefficient (ADC) and histopathological features such as Ki-67 proliferation index in breast cancer (BC), with mixed results. The purpose of this study was to perform a multicenter analysis to determine relationships between ADC and expression of Ki-67 and tumor grade in BC. METHODS: For this study, data from six centers were acquired. The sample comprises 870 patients (all female; mean age, 52.6 ± 10.8 years). In every case, breast magnetic resonance imaging with diffusion-weighted imaging was performed. The comparison of ADC values in groups was performed by Mann-Whitney U test where the p values are adjusted for multiple testing (Bonferroni correction). The association between ADC and Ki-67 values was calculated by Spearman’s rank correlation coefficient. Sensitivity, specificity, negative and positive predictive values, accuracy, and AUC were calculated for the diagnostic procedures. ADC thresholds were chosen to maximize the Youden index. RESULTS: Overall, data of 870 patients were acquired for this study. The mean ADC value of the tumors was 0.98 ± 0.22 × 10(− 3) mm(2) s(− 1). ROC analysis showed that it is impossible to differentiate high/moderate grade tumors from grade 1 lesions using ADC values. Youden index identified a threshold ADC value of 1.03 with a sensitivity of 56.2% and specificity of 67.9%. The positive predictive value was 18.2%, and the negative predictive value was 92.4%. The level of the Ki-67 proliferation index was available for 845 patients. The mean value was 12.33 ± 21.77%. ADC correlated with weak statistical significant with expression of Ki-67 (p = − 0.202, p < 0.001). ROC analysis was performed to distinguish tumors with high proliferative potential from tumors with low expression of Ki-67 using ADC values. Youden index identified a threshold ADC value of 0.91 (sensitivity 64%, specificity 50%, positive predictive value 67.7%, negative predictive value 45.0%). CONCLUSIONS: ADC cannot be used as a surrogate marker for proliferation activity and/or for tumor grade in breast cancer. BioMed Central 2018-06-19 2018 /pmc/articles/PMC6011203/ /pubmed/29921323 http://dx.doi.org/10.1186/s13058-018-0991-1 Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Surov, Alexey
Clauser, Paola
Chang, Yun-Woo
Li, Lihua
Martincich, Laura
Partridge, Savannah C.
Kim, Jin You
Meyer, Hans Jonas
Wienke, Andreas
Can diffusion-weighted imaging predict tumor grade and expression of Ki-67 in breast cancer? A multicenter analysis
title Can diffusion-weighted imaging predict tumor grade and expression of Ki-67 in breast cancer? A multicenter analysis
title_full Can diffusion-weighted imaging predict tumor grade and expression of Ki-67 in breast cancer? A multicenter analysis
title_fullStr Can diffusion-weighted imaging predict tumor grade and expression of Ki-67 in breast cancer? A multicenter analysis
title_full_unstemmed Can diffusion-weighted imaging predict tumor grade and expression of Ki-67 in breast cancer? A multicenter analysis
title_short Can diffusion-weighted imaging predict tumor grade and expression of Ki-67 in breast cancer? A multicenter analysis
title_sort can diffusion-weighted imaging predict tumor grade and expression of ki-67 in breast cancer? a multicenter analysis
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6011203/
https://www.ncbi.nlm.nih.gov/pubmed/29921323
http://dx.doi.org/10.1186/s13058-018-0991-1
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