Impact of breast magnetic resonance imaging on the locoregional staging and management of breast cancer

The impact of preoperative breast MRI on the therapeutic management of breast cancer patients

BACKGROUND

The role of preoperative breast MRI to evaluate the extent of disease in breast cancer patients is considered controversial. We aimed at assessing the effect of breast MRI on the management of newly diagnosed breast cancer.

MATERIALS

A retrospective review of 202 consecutively seen patients who were newly diagnosed with breast cancer and who underwent preoperative breast MRIs at Assuta Ashdod between June 1, 2017, and June 1, 2020. Data included discovering suspicious lesions by conventional imaging, MRI findings, and surgical pathology results. This was analyzed to determine whether the MRI changed the management and whether it had a justified or unjustified effect on the treatment.

RESULTS

The mean age was 54.51 (standard deviation, 11.34 years). Breast MRI revealed additional findings in 56 % of patients and modified therapeutic management in 32 % of the cases evaluated, having a justified effect in 87.6 %. Patients with changed management had a statistically significantly higher mastectomy rate (36 %) than those who did not (14 %). No statistically significant association was found between independent variables such as breast density, tumor location on the breast, type of tumor, patient's demographic information, etc. And whether MRI findings changed the initial treatment plan.

CONCLUSIONS

MRI played an essential role in the preoperative staging of breast cancer in our study, modifying therapeutic planning in approximately one-third of the cases and having a justified effect on most of them. We, therefore, support preoperative breast MRI in newly diagnosed breast cancer patients.

Artificial Intelligence-Enhanced Breast MRI: Applications in Breast Cancer Primary Treatment Response Assessment and Prediction

ABSTRACT

Primary systemic therapy (PST) is the treatment of choice in patients with locally advanced breast cancer and is nowadays also often used in patients with early-stage breast cancer. Although imaging remains pivotal to assess response to PST accurately, the use of imaging to predict response to PST has the potential to not only better prognostication but also allow the de-escalation or omission of potentially toxic treatment with undesirable adverse effects, the accelerated implementation of new targeted therapies, and the mitigation of surgical delays in selected patients. In response to the limited ability of radiologists to predict response to PST via qualitative, subjective assessments of tumors on magnetic resonance imaging (MRI), artificial intelligence-enhanced MRI with classical machine learning, and in more recent times, deep learning, have been used with promising results to predict response, both before the start of PST and in the early stages of treatment. This review provides an overview of the current applications of artificial intelligence to MRI in assessing and predicting response to PST, and discusses the challenges and limitations of their clinical implementation.

Multifocality and Multicentrality in Breast Cancer: Comparison of the Efficiency of Mammography, Contrast-Enhanced Spectral Mammography, and Magnetic Resonance Imaging in a Group of Patients with Primarily Operable Breast Cancer

BACKGROUND

The multifocality and multicentrality of breast cancer (MFMCC) are the significant aspects that determine a specialist's choice between applying breast-conserving therapy (BCT) or performing a mastectomy. This study aimed to assess the usefulness of mammography (MG), contrast-enhanced spectral mammography (CESM), and magnetic resonance imaging (MRI) in women diagnosed with breast cancer before qualifying for surgical intervention to visualize other (additional) cancer foci.

METHODS

The study included 60 breast cancer cases out of 630 patients initially who underwent surgery due to breast cancer from January 2015 to April 2019. MG, CESM, and MRI were compared with each other in terms of the presence of MFMCC and assessed for compliance with the postoperative histopathological examination (HP).

RESULTS

Histopathological examination confirmed the presence of MFMCC in 33/60 (55%) patients. The sensitivity of MG in detecting MFMCC was 50%, and its specificity was 95.83%. For CESM, the sensitivity was 85.29%, and the specificity was 96.15%. For MRI, all the above-mentioned parameters were higher as follows: sensitivity-91.18%; specificity-92.31%.

CONCLUSIONS

In patients with MFMCC, both CESM and MRI are highly sensitive in the detection of additional cancer foci. Both CESM and MRI change the extent of surgical intervention in every fourth patient.