The accuracy of incremental pre-operative breast MRI findings – Concordance with histopathology in the Swedish randomized multicenter POMB trial

Effects of preoperative magnetic resonance image on survival rates and surgical planning in breast cancer conservative surgery: randomized controlled trial (BREAST-MRI trial)

BACKGROUND

Breast magnetic resonance imaging (MRI) has high sensitivity in detecting invasive neoplasms. Controversy remains about its impact on the preoperative staging of breast cancer surgery. This study evaluated survival and surgical outcomes of preoperative MRI in conservative breast cancer surgery.

METHODS

A phase III, randomized, open-label, single-center trial including female breast cancer participants, stage 0-III disease, and eligible for breast-conserving surgery. We compared the role of including MRI in preoperative evaluation versus radiologic exam routine with mammography and ultrasound in breast cancer conservative candidates. The primary outcome was local relapse-free survival (LRFS), and secondary outcomes were overall survival (OS), mastectomy rate, and reoperation rate.

RESULTS

524 were randomized to preoperative MRI group (n = 257) or control group (n = 267). The survival analysis showed a 5.9-years LRFS of 99.2% in MRI group versus 98.9% in control group (HR = 0.72; 95% CI 0.12-4.28; p = 0.7) and an OS of 95.3% in the MRI group versus 96.3% in the control group (HR = 1.37 95% CI 0.59-3.19; p = 0.8). Surgical management changed in 21 ipsilateral breasts in the MRI group; 21 (8.3%) had mastectomies versus one in the control group. No difference was found in reoperation rates, 22 (8.7%) in the MRI group versus 23 (8.7%) in the control group (RR = 1.002; 95% CI 0.57-1.75; p = 0.85).

CONCLUSION

Preoperative MRI increased the mastectomy rates by 8%. The use of preoperative MRI did not influence local relapse-free survival, overall survival, or reoperation rates.

Impact of Preoperative Magnetic Resonance Imaging on Surgical Outcomes in Women with Invasive Breast Cancer: A Systematic Review and Meta-Analysis

BACKGROUND

Currently, whether magnetic resonance imaging (MRI) should be routinely applied to patients with breast cancer before surgery remains controversial. A pooled analysis of the association between preoperative MRI and surgical outcomes in female patients with newly diagnosed invasive breast cancer was conducted to provide evidence-based medicine for clinical practice.

METHODS

Three independent researchers searched the following databases: PubMed, Medline, Embase, Ovid, Cochrane Library, and Web of Science from inception to April 2022. Literature was included and excluded according to Cochrane's principles. The basic information from eligible documents was extracted. Systematic evaluation and meta-analysis were performed, and the odds ratio (OR) was analyzed by the random-effect model. The quality of the literature was assessed using the modified Jadad scale and the Newcastle-Ottawa (NOS) mean scale.

RESULTS

A total of 19 studies were included, including 4 randomized controlled trials and 15 observational comparative studies. Among them, most studies were not limited to a specific pathological type, with the exception of 3 that were limited to invasive lobular carcinoma. The results showed that preoperative MRI examination would significantly reduce the reoperation rate (OR = 0.77, P=0.02) and increase the mastectomy rate (OR = 1.36, P=0.001). In comparison, preoperative MRI did not significantly affect the rate of secondary mastectomy (OR = 0.77, P=0.02), the rate of positive margin (OR = 1.08, P=0.66), the rate of mastectomy (OR = 1.00, P < 0.05), and reoperations (OR = 0.65, P=0.19) in the subgroup analysis of patients with invasive lobular carcinoma.

CONCLUSION

Available evidence suggests that preoperative MRI examination increases the rate of mastectomy and reduces the rate of reoperations. The results indicate that preoperative MRI examination has the potential to benefit patients with breast cancer, but more high-quality studies are needed for confirmation.

Breast imaging: Beyond the detection

Breast cancer is a heterogeneous disease nowadays, including different biological subtypes with a variety of possible treatments, which aim to achieve the best outcome in terms of response to therapy and overall survival. In recent years breast imaging has evolved considerably, and the ultimate goal is to predict these strong phenotypic differences noninvasively. Indeed, breast cancer multiparametric studies can highlight not only qualitative imaging parameters, as the presence/absence of a likely malignant finding, but also quantitative parameters, suggesting clinical-pathological features through the evaluation of imaging biomarkers. A further step has been the introduction of artificial intelligence and in particular radiogenomics, that investigates the relationship between breast cancer imaging characteristics and tumor molecular, genomic and proliferation features. In this review, we discuss the main techniques currently in use for breast imaging, their respective fields of use and their technological and diagnostic innovations.

Impact of preoperative breast MRI on 10-year survival of patients included in the Swedish randomized multicentre POMB trial

Background

The value of preoperative breast MRI as an adjunct technique regarding its effect on re-excision rates has been a subject of discussion. No survival data regarding preoperative breast MRI are available from randomized studies.

Methods

Ten-year follow-up of the POMB randomized multicentre study was analysed, evaluating MRI and its effect on disease-free survival (DFS) and overall survival (OS). Patients with newly diagnosed breast cancer were randomized to either preoperative MRI or conventional imaging. Kaplan–Meier plots were used to analyse DFS and OS, and Cox regression to estimate hazard ratios (HRs).

Results

A total of 440 patients, aged 56 years or less, with newly diagnosed breast cancer were randomized to either preoperative MRI (220) or conventional imaging (220; control). Median follow-up for each group was 10 years. DFS rates were 85.5 and 80.0 per cent for the MRI and control groups respectively (P = 0.099). The risk of relapse or death was 46 per cent higher in the control group (HR 1.46, 95 per cent c.i. 0.93 to 2.29). OS rates after 10 years were 90.9 and 88.6 per cent in the MRI and control groups respectively (P = 0.427). The risk of death was 27 per cent higher in the control group (HR 1.27, 0.71 to 2.29). Locoregional, distant, and contralateral recurrence outcomes combined were increased in the control group (P = 0.048). A subgroup analysis of patients with breast cancer stages I–III showed that preoperative MRI improved DFS compared with conventional imaging, but this did not reach statistical significance (P = 0.057).

Conclusion

After 10 years of follow-up, preoperative breast MRI as an adjunct to conventional imaging resulted in slightly, but non-significantly, improved DFS and OS. Registration number: NCT01859936 (http://www.clinicaltrials.gov).

Preoperative Staging in Breast Cancer: Intraindividual Comparison of Unenhanced MRI Combined With Digital Breast Tomosynthesis and Dynamic Contrast Enhanced-MRI

Objectives

To evaluate the accuracy in lesion detection and size assessment of Unenhanced Magnetic Resonance Imaging combined with Digital Breast Tomosynthesis (UE-MRI+DBT) and Dynamic Contrast Enhanced Magnetic Resonance Imaging (DCE-MRI), in women with known breast cancer.

Methods

A retrospective analysis was performed on 84 patients with histological diagnosis of breast cancer, who underwent MRI on a 3T scanner and DBT over 2018-2019, in our Institution. Two radiologists, with 15 and 7 years of experience in breast imaging respectively, reviewed DCE-MRI and UE-MRI (including DWI and T2-w) + DBT images in separate reading sections, unaware of the final histological examination. DCE-MRI and UE-MRI+DBT sensitivity, positive predictive value (PPV) and accuracy were calculated, using histology as the gold standard. Spearman correlation and regression analyses were performed to evaluate lesion size agreement between DCE-MRI vs Histology, UE-MRI+DBT vs Histology, and DCE-MRI vs UE-MRI+DBT. Inter-reader agreement was evaluated using Cohen’s κ coefficient. McNemar test was used to identify differences in terms of detection rate between the two methodological approaches. Spearman’s correlation analysis was also performed to evaluate the correlation between ADC values and histological features.

Results

109 lesions were confirmed on histological examination. DCE-MRI showed high sensitivity (100% Reader 1, 98% Reader 2), good PPV (89% Reader 1, 90% Reader 2) and accuracy (90% for both readers). UE-MRI+DBT showed 97% sensitivity, 91% PPV and 92% accuracy, for both readers. Lesion size Spearman coefficient were 0.94 (Reader 1) and 0.91 (Reader 2) for DCE-MRI vs Histology; 0.91 (Reader 1) and 0.90 (Reader 2) for UE-MRI+DBT vs Histology (p-value <0.001). DCE-MRI vs UE-MRI+DBT regression coefficient was 0.96 for Reader 1 and 0.94 for Reader 2. Inter-reader agreement was 0.79 for DCE-MRI and 0.94 for UE-MRI+DBT. McNemar test did not show a statistically significant difference between DCE-MRI and UE-MRI+DBT (McNemar test p-value >0.05). Spearman analyses showed an inverse correlation between ADC values and histological grade (p-value <0.001).

Conclusions

DCE-MRI was the most sensitive imaging technique in breast cancer preoperative staging. However, UE-MRI+DBT demonstrated good sensitivity and accuracy in lesion detection and tumor size assessment. Thus, UE-MRI could be a valid alternative when patients have already performed DBT.

Preoperative Prediction of Axillary Lymph Node Metastasis in Breast Carcinoma Using Radiomics Features Based on the Fat-Suppressed T2 Sequence

RATIONALE AND OBJECTIVES

To investigate the value of radiomics method based on the fat-suppressed T2 sequence for preoperative predicting axillary lymph node (ALN) metastasis in breast carcinoma.

MATERIALS AND METHODS

The data of 329 invasive breast cancer patients were divided into the primary cohort (n = 269) and validation cohort (n = 60). Radiomics features were extracted from the fat-suppressed T2-weighted images on breast MRI, and ALN metastasis-related radiomics feature selection was performed using Mann-Whitney U-test and support vector machines with recursive feature elimination; then a radiomics signature was constructed by linear support vector machine. The predictive models were constructed using a linear regression model based on the clinicopathologic factors and radiomics signature, and nomogram was used for a visual prediction of the combined model. The predictive performances are evaluated with the sensitivity, specificity, accuracy, and area under the receiver operating characteristic curve.

RESULTS

A total of 647 radiomics features were extracted from each patient. About 23 ALN metastasis-related radiomics features were selected to construct the radiomics signature, including 17 texture features, 5 first-order statistical features, and one shape feature; patient age, tumor size, HER2 status, and vascular cancer thrombus accompanied or not were selected to construct the cilinicopathologic feature model. The sensitivity, specificity, accuracy, and are under the curve value of radiomics signature, clinicopathologic feature model, and the nomogram were 65.22%, 81.08%, 75.00%, and 0.819 (95% confidence interval [CI]: 0.776-0.861), 30.44%, 81.08%, 61.67%, and 0.605 (95% CI: 0.571-0.624) and 60.87%, 89.19%, 78.33%, and 0.810 (95% CI: 0.761-0.855), respectively.

CONCLUSION

Radiomics methods based on the fat-suppressed T2 sequence and the nomogram are helpful for preoperative accurate predicting ALN metastasis.