Impact of factors affecting the residual tumor size diagnosed by MRI following neoadjuvant chemotherapy in comparison to pathology.

BACKGROUND AND OBJECTIVES: To investigate accuracy of magnetic resonance imaging (MRI) for measuring residual tumor size in breast cancer patients receiving neoadjuvant chemotherapy (NAC). METHODS: Ninety-eight patients were studied. Several MRI were performed during NAC for response monitoring, and the residual tumor size was measured on last MRI after completing NAC. Covariates, including age, tumor characteristics, biomarkers, NAC regimens, MRI scanners, and time from last MRI to operation, were analyzed. Univariate and Multivariate linear regression models were used to determine the predictive value of these covariates for MRI-pathology size discrepancy as the outcome measure. RESULTS: The mean (±SD) of the absolute difference between MRI and pathological residual tumor size was 1.0 ± 2.0 cm (range, 0-14 cm). Univariate regression analysis showed tumor type, morphology, HR status, HER2 status, and MRI scanner (1.5 T or 3.0 T) were significantly associated with MRI-pathology size discrepancy (all P < 0.05). Multivariate regression analyses demonstrated that only tumor type, tumor morphology, and biomarker status considering both HR and HER-2 were independent predictors (P = 0.0014, 0.0032, and 0.0286, respectively). CONCLUSION: The accuracy of MRI in evaluating residual tumor size depends on tumor type, morphology, and biomarker status. The information may be considered in surgical planning for NAC patients.

Diagnostic performance of magnetic resonance imaging for assessing tumor response in patients with HER2-negative breast cancer receiving neoadjuvant chemotherapy is associated with molecular biomarker profile.

BACKGROUND: This study aimed to evaluate the influence of hormone receptor (HR) and Ki-67 proliferation markers in predicting the accuracy of magnetic resonance imaging (MRI) for measuring residual tumor size in patients with HER2-negative (HER2(-)) breast cancer receiving neoadjuvant chemotherapy (NAC). PATIENTS AND METHODS: Fifty-four women were studied. Patients received AC (doxorubicin (Adriamycin)/cyclophosphamide) and/or taxane-based regimens. The accuracy of MR-determined clinical complete response (CCR) was compared to pathological complete response (pCR). The size of detectable residual tumor on MRI was correlated with pathologically diagnosed tumor size using the Pearson correlation. RESULTS: MRI correctly diagnosed 16 of the 17 cases of pCR. There were 8 false-negative diagnoses: 7 HR(+) and 1 HR(-). The overall sensitivity, specificity, and accuracy of MRI were 78%, 94%, and 83%, respectively. The positive predictive value was 97% and the negative predictive value was 67%. For MRI vs. pathologically determined tumor size correlation, HR(-) cancers showed a higher correlation (R = 0.79) than did HR(+) cancers (R = 0.58). A worse MRI/pathology size discrepancy was found in HR(+) cancer than in HR(-)cancer (1.6 ± 2.8 cm vs. 0.56 ± 0.9 cm; P = .05). Tumors with low Ki-67 proliferation (< 40%) showed a larger size discrepancy than did those with high Ki-67 proliferation (≥ 40%) (1.2 ± 2.0 cm vs. 0.4 ± 0.8 cm; P = .05). CONCLUSIONS: The results showed that the diagnostic performance of MRI for patients with breast cancer undergoing NAC is associated with a molecular biomarker profile. Among HER2(-)tumors, the accuracy of MRI was worse in HR(+)cancers than in HR(-)cancers and was also worse in low-proliferation tumors than in high-proliferation tumors. These findings may help in surgical planning.

Comparison of breast density measured on MR images acquired using fat-suppressed versus nonfat-suppressed sequences.

PURPOSE: To investigate the difference of MR percent breast density measured from fat-suppressed versus nonfat-suppressed imaging sequences. METHODS: Breast magnetic resonance imaging (MRI) with and without fat suppression was acquired from 38 subjects. Breasts were divided into subgroups of different morphological patterns ("central" and "intermingled" types). Breast volume, fibroglandular tissue volume, and percent density were measured. The results were compared using nonparametric statistical tests and regarded as significant at p < 0.05. RESULTS: Breast volume, fibroglandular volume, and percent density between fat-suppressed and nonfat-suppressed sequences were highly correlated. Breast volumes measured on these two sequences were almost identical. Fibroglandular tissue volume and percent density, however, had small (<5%) yet significant differences between the two sequences-they were both higher on the fat-suppressed sequence. Intraobserver variability was within 4% for both sequences and different morphological types. The fibroglandular tissue volume measured on downsampled images showed a small (<5%) yet significant difference. CONCLUSIONS: The measurement of breast density made on MRI acquired using fat-suppressed and nonfat-suppressed T1W images was about 5% difference, only slightly higher than the intraobserver variability of 3%-4%. When the density data from multiple centers were to be combined, evaluating the degree of difference is needed to take this difference into account.

Breast cancer: evaluation of response to neoadjuvant chemotherapy with 3.0-T MR imaging.

PURPOSE: To assess how the molecular biomarker status of a breast cancer, including human epidermal growth factor receptor 2 (HER2), hormone receptors, and the proliferation marker Ki-67 status, affects the diagnosis at 3.0-T magnetic resonance (MR) imaging. MATERIALS AND METHODS: This study was approved by the institutional review board and was HIPAA compliant. Fifty patients (age range, 28-82 years; mean age, 49 years) receiving neoadjuvant chemotherapy were monitored with 3.0-T MR imaging. The longest dimension of the residual cancer was measured at MR imaging and correlated with pathologic findings. Patients were further divided into subgroups on the basis of HER2, hormone receptor, and Ki-67 status. Pathologic complete response (pCR) was defined as when there were no residual invasive cancer cells. The Pearson correlation was used to correlate MR imaging-determined and pathologic tumor size, and the unpaired t test was used to compare MR imaging-pathologic size discrepancies. RESULTS: Of the 50 women, 14 achieved pCR. There were seven false-negative diagnoses at MR imaging. The overall sensitivity, specificity, and accuracy for diagnosing invasive residual disease at MR imaging were 81%, 93%, and 84%, respectively. The mean MR imaging-pathologic size discrepancy was 0.5 cm ± 0.9 (standard deviation) for HER2-positive cancer and 2.3 cm ± 3.5 for HER2-negative cancer (P = .009). In the HER2-negative group, the size discrepancy was smaller for hormone receptor-negative than for hormone receptor-positive cancers (1.0 cm ± 1.1 vs 3.0 cm ± 4.0, P = .04). The size discrepancy was smaller in patients with 40% or greater Ki-67 expression (0.8 cm ± 1.1) than in patients with 10% or less Ki-67 expression (3.9 cm ± 5.1, P = .06). CONCLUSION: The diagnostic accuracy of breast MR imaging is better in more aggressive than in less aggressive cancers. When MR imaging is used for surgical planning, caution should be taken with HER2-negative hormone receptor-positive cancers.

Impact of MRI-evaluated neoadjuvant chemotherapy response on change of surgical recommendation in breast cancer.

OBJECTIVE: To investigate how MRI imaging of neoadjuvant chemotherapy (NAC) tumor response affects the recommendation for optimal breast cancer surgery, both before and after NAC. SUMMARY BACKGROUND DATA: Understanding how imaging findings are incorporated into surgeons' decision-making processes will help establish appropriate imaging guidelines for recommending breast conservation surgery (BCS) after the NAC. METHODS: Seventy-six breast cancer patients undergoing NAC with MRI follow-up studies were analyzed. Two experienced breast surgeons reviewed all cases. An initial surgical recommendation was made based on the pre-NAC lesion presentation; a subsequent surgical recommendation was made based on the post-NAC tumor response. Finally, the pathology results were disclosed and the surgeons were asked to decide on the optimal definitive surgical procedure. MRI findings throughout the entire course of the NAC were analyzed to understand how they affected different recommendations. RESULTS: Before the NAC, a large tumor size or extent of disease were the primary determinant factors for mastectomy. In this study, the mean tumor size was 5.3 +/- 3.4 cm (RECIST) in the mastectomy group and 3.2 +/- 1.6 cm in the lumpectomy group (P = 0.0001). After the NAC, based on consensus recommendations, 21 mastectomy candidates remained for mastectomy, with tumor size decreasing from 7.4 +/- 4.5 to 1.5 +/- 2.5 cm, and 22 mastectomy candidates were changed to lumpectomy, with tumor size decreasing from 4.2 +/- 2.1 to 0.4 +/- 0.6 cm. When the final pathology revealed pCR or minimal residual disease, the surgeons agreed that BCS is the optimal procedure. On the other hand, for a large extent of residual disease, mastectomy should be performed. CONCLUSION: In patients who had more extensive pretreatment disease, despite an excellent response to NAC, the surgeons still tended to apply an aggressive approach and recommended mastectomy. Given that the confirmation of pCR or minimal residual disease would change surgeons' recommendations for less aggressive, conservation surgery, the maturity of MRI for NAC response prediction may provide reliable staging information to aid in the recommendation of the optimal surgical procedure.