Added value of preoperative MRI in primary surgery for breast cancer

Abstract Introduction The use of magnetic resonance imaging (MRI) in preoperative staging of breast cancer remains arbitrary. The high sensitivity together with the somewhat lower specificity of MRI provides a unique balance between finding true extent/new lesions and overdiagnostics/overtreatment. This study aims to assess a cohort of breast cancer patients examined with preoperative MRI and estimate the potential benefits and negative effects. Method This retrospective, single center cohort study included patients examined with preoperative MRI before primary surgery for breast cancer between 2019 and 2022. Result In total, 94 patients were included. Median age was 54 years, 37.2% were premenopausal and 35.1% had invasive lobular carcinoma. The detection rate of occult contralateral breast cancer was 9.6%. Reoperation rate due to positive margins was 6.4%. Bland-Altman statistics showed higher agreement between estimated extent by MRI and postoperative histopathological extent, compared to estimation by ultrasound or mammography. MRI contributed to correct change of operation method in 18.1%, but also less favorable choice of surgery in 5.3% of patients (such as unnecessary mastectomy). The total mastectomy rate was 54.3%. Unnecessary biopsies of benign lesions after MRI were performed in 11.7% of patients. Discussion In this cohort, breast MRI had a clear impact on the surgical treatment of breast cancer, affecting choice of operation method. About a fifth of patients examined with MRI received a benefit with a better management of their breast cancer, however an equally large part received less optimal diagnostics and treatment.

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Publication Details

Journal
British journal of surgery
Published
2025-08-01
DOI
https://doi.org/10.1093/bjs/znaf149.030
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
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article

Added value of preoperative MRI in primary surgery for breast cancer

Kristina Åhsberg, Anna Gardfjell, Björn Brännström Breitholtz
British journal of surgery
Radiomics and Machine Learning in Medical Imaging
article

Added value of preoperative MRI in primary surgery for breast cancer

Kristina Åhsberg, Anna Gardfjell, Björn Brännström Breitholtz
article en

Abstract

Abstract Introduction The use of magnetic resonance imaging (MRI) in preoperative staging of breast cancer remains arbitrary. The high sensitivity together with the somewhat lower specificity of MRI provides a unique balance between finding true extent/new lesions and overdiagnostics/overtreatment. This study aims to assess a cohort of breast cancer patients examined with preoperative MRI and estimate the potential benefits and negative effects. Method This retrospective, single center cohort study included patients examined with preoperative MRI before primary surgery for breast cancer between 2019 and 2022. Result In total, 94 patients were included. Median age was 54 years, 37.2% were premenopausal and 35.1% had invasive lobular carcinoma. The detection rate of occult contralateral breast cancer was 9.6%. Reoperation rate due to positive margins was 6.4%. Bland-Altman statistics showed higher agreement between estimated extent by MRI and postoperative histopathological extent, compared to estimation by ultrasound or mammography. MRI contributed to correct change of operation method in 18.1%, but also less favorable choice of surgery in 5.3% of patients (such as unnecessary mastectomy). The total mastectomy rate was 54.3%. Unnecessary biopsies of benign lesions after MRI were performed in 11.7% of patients. Discussion In this cohort, breast MRI had a clear impact on the surgical treatment of breast cancer, affecting choice of operation method. About a fifth of patients examined with MRI received a benefit with a better management of their breast cancer, however an equally large part received less optimal diagnostics and treatment.

British journal of surgeryVol. 112(Supplement_11)
Lund University (SE), Skåne University Hospital (SE), Hallands sjukhus Halmstad (SE)
Openalex Percentile: Top 70%
Radiomics and Machine Learning in Medical Imaging
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