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Introduction of a breast apparent diffusion coefficient category system (ADC-B) derived from a large multicenter MRI database
OBJECTIVES: To develop an intuitive and generally applicable system for the reporting, assessment, and documentation of ADC to complement standard BI-RADS criteria. METHODS: This was a multicentric, retrospective analysis of 11 independently conducted institutional review board–approved studies from...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10326122/ https://www.ncbi.nlm.nih.gov/pubmed/37166495 http://dx.doi.org/10.1007/s00330-023-09675-0 |
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author | Bickel, Hubert Clauser, Paola Pinker, Katja Helbich, Thomas Biondic, Iva Brkljacic, Boris Dietzel, Matthias Ivanac, Gordana Krug, Barbara Moschetta, Marco Neuhaus, Victor Preidler, Klaus Baltzer, Pascal |
author_facet | Bickel, Hubert Clauser, Paola Pinker, Katja Helbich, Thomas Biondic, Iva Brkljacic, Boris Dietzel, Matthias Ivanac, Gordana Krug, Barbara Moschetta, Marco Neuhaus, Victor Preidler, Klaus Baltzer, Pascal |
author_sort | Bickel, Hubert |
collection | PubMed |
description | OBJECTIVES: To develop an intuitive and generally applicable system for the reporting, assessment, and documentation of ADC to complement standard BI-RADS criteria. METHODS: This was a multicentric, retrospective analysis of 11 independently conducted institutional review board–approved studies from seven institutions performed between 2007 and 2019. Breast Apparent Diffusion coefficient (ADC-B) categories comprised ADC-B0 (ADC non-diagnostic), ADC-B1 (no enhancing lesion), and ADC-B2-5. The latter was defined by plotting ADC versus cumulative malignancy rates. Statistics comprised ANOVA with post hoc testing and ROC analysis. p values ≤ 0.05 were considered statistically significant. RESULTS: A total of 1625 patients (age: 55.9 years (± 13.8)) with 1736 pathologically verified breast lesions were included. The mean ADC (× 10(−3) mm(2)/s) differed significantly between benign (1.45, SD .40) and malignant lesions (.95, SD .39), and between invasive (.92, SD .22) and in situ carcinomas (1.18, SD .30) (p < .001). The following ADC-B categories were identified: ADC-B0—ADC cannot be assessed; ADC-B1—no contrast-enhancing lesion; ADC-B2—ADC ≥ 1.9 (cumulative malignancy rate < 0.1%); ADC-B3—ADC 1.5 to < 1.9 (0.1–1.7%); ADC-B4—ADC 1.0 to < 1.5 (10–24.5%); and ADC-B5—ADC < 1.0 (> 24.5%). At the latter threshold, a positive predictive value of 95.8% (95% CI 0.94–0.97) for invasive versus non-invasive breast carcinomas was reached. CONCLUSIONS: The breast apparent diffusion coefficient system (ADC-B) provides a simple and widely applicable categorization scheme for assessment, documentation, and reporting of apparent diffusion coefficient values in contrast-enhancing breast lesions on MRI. CLINICAL RELEVANCE STATEMENT: The ADC-B system, based on diverse MRI examinations, is clinically relevant for stratifying breast cancer risk via apparent diffusion coefficient measurements, and complements BI-RADS for improved clinical decision-making and patient outcomes. KEY POINTS: • The breast apparent diffusion coefficient category system (ADC-B) is a simple tool for the assessment, documentation, and reporting of ADC values in contrast-enhancing breast lesions on MRI. • The categories comprise ADC-B0 for non-diagnostic examinations, ADC-B1 for examinations without an enhancing lesion, and ADC-B2-5 for enhancing lesions with an increasing malignancy rate. • The breast apparent diffusion coefficient category system may be used to complement BI-RADS in clinical decision-making. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00330-023-09675-0. |
format | Online Article Text |
id | pubmed-10326122 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-103261222023-07-08 Introduction of a breast apparent diffusion coefficient category system (ADC-B) derived from a large multicenter MRI database Bickel, Hubert Clauser, Paola Pinker, Katja Helbich, Thomas Biondic, Iva Brkljacic, Boris Dietzel, Matthias Ivanac, Gordana Krug, Barbara Moschetta, Marco Neuhaus, Victor Preidler, Klaus Baltzer, Pascal Eur Radiol Breast OBJECTIVES: To develop an intuitive and generally applicable system for the reporting, assessment, and documentation of ADC to complement standard BI-RADS criteria. METHODS: This was a multicentric, retrospective analysis of 11 independently conducted institutional review board–approved studies from seven institutions performed between 2007 and 2019. Breast Apparent Diffusion coefficient (ADC-B) categories comprised ADC-B0 (ADC non-diagnostic), ADC-B1 (no enhancing lesion), and ADC-B2-5. The latter was defined by plotting ADC versus cumulative malignancy rates. Statistics comprised ANOVA with post hoc testing and ROC analysis. p values ≤ 0.05 were considered statistically significant. RESULTS: A total of 1625 patients (age: 55.9 years (± 13.8)) with 1736 pathologically verified breast lesions were included. The mean ADC (× 10(−3) mm(2)/s) differed significantly between benign (1.45, SD .40) and malignant lesions (.95, SD .39), and between invasive (.92, SD .22) and in situ carcinomas (1.18, SD .30) (p < .001). The following ADC-B categories were identified: ADC-B0—ADC cannot be assessed; ADC-B1—no contrast-enhancing lesion; ADC-B2—ADC ≥ 1.9 (cumulative malignancy rate < 0.1%); ADC-B3—ADC 1.5 to < 1.9 (0.1–1.7%); ADC-B4—ADC 1.0 to < 1.5 (10–24.5%); and ADC-B5—ADC < 1.0 (> 24.5%). At the latter threshold, a positive predictive value of 95.8% (95% CI 0.94–0.97) for invasive versus non-invasive breast carcinomas was reached. CONCLUSIONS: The breast apparent diffusion coefficient system (ADC-B) provides a simple and widely applicable categorization scheme for assessment, documentation, and reporting of apparent diffusion coefficient values in contrast-enhancing breast lesions on MRI. CLINICAL RELEVANCE STATEMENT: The ADC-B system, based on diverse MRI examinations, is clinically relevant for stratifying breast cancer risk via apparent diffusion coefficient measurements, and complements BI-RADS for improved clinical decision-making and patient outcomes. KEY POINTS: • The breast apparent diffusion coefficient category system (ADC-B) is a simple tool for the assessment, documentation, and reporting of ADC values in contrast-enhancing breast lesions on MRI. • The categories comprise ADC-B0 for non-diagnostic examinations, ADC-B1 for examinations without an enhancing lesion, and ADC-B2-5 for enhancing lesions with an increasing malignancy rate. • The breast apparent diffusion coefficient category system may be used to complement BI-RADS in clinical decision-making. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00330-023-09675-0. Springer Berlin Heidelberg 2023-05-11 2023 /pmc/articles/PMC10326122/ /pubmed/37166495 http://dx.doi.org/10.1007/s00330-023-09675-0 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Breast Bickel, Hubert Clauser, Paola Pinker, Katja Helbich, Thomas Biondic, Iva Brkljacic, Boris Dietzel, Matthias Ivanac, Gordana Krug, Barbara Moschetta, Marco Neuhaus, Victor Preidler, Klaus Baltzer, Pascal Introduction of a breast apparent diffusion coefficient category system (ADC-B) derived from a large multicenter MRI database |
title | Introduction of a breast apparent diffusion coefficient category system (ADC-B) derived from a large multicenter MRI database |
title_full | Introduction of a breast apparent diffusion coefficient category system (ADC-B) derived from a large multicenter MRI database |
title_fullStr | Introduction of a breast apparent diffusion coefficient category system (ADC-B) derived from a large multicenter MRI database |
title_full_unstemmed | Introduction of a breast apparent diffusion coefficient category system (ADC-B) derived from a large multicenter MRI database |
title_short | Introduction of a breast apparent diffusion coefficient category system (ADC-B) derived from a large multicenter MRI database |
title_sort | introduction of a breast apparent diffusion coefficient category system (adc-b) derived from a large multicenter mri database |
topic | Breast |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10326122/ https://www.ncbi.nlm.nih.gov/pubmed/37166495 http://dx.doi.org/10.1007/s00330-023-09675-0 |
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