Predicting Axillary Metastasis of Breast Cancer Patients with MRI Relaxometry

<b>Background:</b> Breast cancer is a leading cause of cancer-related mortality among women worldwide. Accurate staging, including the detection of axillary metastases, is vital for treatment planning. This study evaluates the efficacy of MRI relaxometry as a diagnostic tool for axillary...

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Main Authors: Roxana Pintican, Radu Fechete, Delia Ioana Radutiu, Manuela Lenghel, Ioana Bene, Carolina Solomon, Cristiana Ciortea, Anca Ciurea
Format: Article
Language:English
Published: MDPI AG 2025-01-01
Series:Diagnostics
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Online Access:https://www.mdpi.com/2075-4418/15/2/188
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author Roxana Pintican
Radu Fechete
Delia Ioana Radutiu
Manuela Lenghel
Ioana Bene
Carolina Solomon
Cristiana Ciortea
Anca Ciurea
author_facet Roxana Pintican
Radu Fechete
Delia Ioana Radutiu
Manuela Lenghel
Ioana Bene
Carolina Solomon
Cristiana Ciortea
Anca Ciurea
author_sort Roxana Pintican
collection DOAJ
description <b>Background:</b> Breast cancer is a leading cause of cancer-related mortality among women worldwide. Accurate staging, including the detection of axillary metastases, is vital for treatment planning. This study evaluates the efficacy of MRI relaxometry as a diagnostic tool for axillary lymph node metastases in breast cancer patients. <b>Methods:</b> A prospective study was conducted on 67 consecutive breast cancer patients. Relaxometry parameters, including T2Max, T2Min, and 1HAv, were assessed using 1.5 Tesla MRI. All axillary metastases were histologically confirmed using core-needle biopsy or surgical specimens. Statistical analyses included ROC curves, chi-square tests, and multivariate analysis to determine correlations between imaging findings and pathological results. <b>Results:</b> Significant associations were found between T2Min-ipsilateral (<i>p</i> = 0.018), 1HAv-ipsilateral (<i>p</i> = 0.003), and axillary metastases. ROC analysis demonstrated that T2Min-ipsilateral and 1HAv-ipsilateral have modest to acceptable discriminatory abilities (AUC = 0.681 and AUC = 0.740, respectively). Combined clinical and imaging models enhanced diagnostic accuracy (AUC = 0.749). <b>Conclusions:</b> MRI relaxometry improves the detection of axillary metastases in breast cancer, particularly when integrated with clinical and pathological evaluations.
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spelling doaj-art-cc255f31b172488097a055c202d1a8832025-01-24T13:29:02ZengMDPI AGDiagnostics2075-44182025-01-0115218810.3390/diagnostics15020188Predicting Axillary Metastasis of Breast Cancer Patients with MRI RelaxometryRoxana Pintican0Radu Fechete1Delia Ioana Radutiu2Manuela Lenghel3Ioana Bene4Carolina Solomon5Cristiana Ciortea6Anca Ciurea7Department of Radiology, “Iuliu Hatieganu” University of Medicine and Pharmacy, 400347 Cluj-Napoca, RomaniaInstitute for Interdisciplinary Research in Bio-Nano-Science, Babes-Bolyai University, INSPIRE Platform, 400347 Cluj-Napoca, RomaniaDepartment of Radiology, “Iuliu Hatieganu” University of Medicine and Pharmacy, 400347 Cluj-Napoca, RomaniaDepartment of Radiology, “Iuliu Hatieganu” University of Medicine and Pharmacy, 400347 Cluj-Napoca, RomaniaDepartment of Radiology, “Iuliu Hatieganu” University of Medicine and Pharmacy, 400347 Cluj-Napoca, RomaniaDepartment of Radiology, “Iuliu Hatieganu” University of Medicine and Pharmacy, 400347 Cluj-Napoca, RomaniaDepartment of Radiology, “Iuliu Hatieganu” University of Medicine and Pharmacy, 400347 Cluj-Napoca, RomaniaDepartment of Radiology, “Iuliu Hatieganu” University of Medicine and Pharmacy, 400347 Cluj-Napoca, Romania<b>Background:</b> Breast cancer is a leading cause of cancer-related mortality among women worldwide. Accurate staging, including the detection of axillary metastases, is vital for treatment planning. This study evaluates the efficacy of MRI relaxometry as a diagnostic tool for axillary lymph node metastases in breast cancer patients. <b>Methods:</b> A prospective study was conducted on 67 consecutive breast cancer patients. Relaxometry parameters, including T2Max, T2Min, and 1HAv, were assessed using 1.5 Tesla MRI. All axillary metastases were histologically confirmed using core-needle biopsy or surgical specimens. Statistical analyses included ROC curves, chi-square tests, and multivariate analysis to determine correlations between imaging findings and pathological results. <b>Results:</b> Significant associations were found between T2Min-ipsilateral (<i>p</i> = 0.018), 1HAv-ipsilateral (<i>p</i> = 0.003), and axillary metastases. ROC analysis demonstrated that T2Min-ipsilateral and 1HAv-ipsilateral have modest to acceptable discriminatory abilities (AUC = 0.681 and AUC = 0.740, respectively). Combined clinical and imaging models enhanced diagnostic accuracy (AUC = 0.749). <b>Conclusions:</b> MRI relaxometry improves the detection of axillary metastases in breast cancer, particularly when integrated with clinical and pathological evaluations.https://www.mdpi.com/2075-4418/15/2/188axillary metastasisbreast cancerN stagerelaxometryaxillary MRI
spellingShingle Roxana Pintican
Radu Fechete
Delia Ioana Radutiu
Manuela Lenghel
Ioana Bene
Carolina Solomon
Cristiana Ciortea
Anca Ciurea
Predicting Axillary Metastasis of Breast Cancer Patients with MRI Relaxometry
Diagnostics
axillary metastasis
breast cancer
N stage
relaxometry
axillary MRI
title Predicting Axillary Metastasis of Breast Cancer Patients with MRI Relaxometry
title_full Predicting Axillary Metastasis of Breast Cancer Patients with MRI Relaxometry
title_fullStr Predicting Axillary Metastasis of Breast Cancer Patients with MRI Relaxometry
title_full_unstemmed Predicting Axillary Metastasis of Breast Cancer Patients with MRI Relaxometry
title_short Predicting Axillary Metastasis of Breast Cancer Patients with MRI Relaxometry
title_sort predicting axillary metastasis of breast cancer patients with mri relaxometry
topic axillary metastasis
breast cancer
N stage
relaxometry
axillary MRI
url https://www.mdpi.com/2075-4418/15/2/188
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