Magnetic Resonance Perfusion Imaging for Breast Cancer

Breast cancer is the most frequently diagnosed cancer among women worldwide, carrying a significant socioeconomic burden. Breast cancer is a heterogeneous disease with 4 major subtypes identified. Each subtype has unique prognostic factors, risks, treatment responses, and survival rates. Advances in targeted therapies have considerably improved the 5-year survival rates for primary breast cancer patients largely due to widespread screening programs that enable early detection and timely treatment. Imaging techniques are indispensable in diagnosing and managing breast cancer. While mammography is the primary screening tool, MRI plays a significant role when mammography results are inconclusive or in patients with dense breast tissue. MRI has become standard in breast cancer imaging, providing detailed anatomic and functional data, including tumor perfusion and cellularity. A key characteristic of breast tumors is angiogenesis, a biological process that promotes tumor development and growth. Increased angiogenesis in tumors generally indicates poor prognosis and increased risk of metastasis. Dynamic contrast-enhanced (DCE) MRI measures tumor perfusion and serves as an in vivo metric for angiogenesis. DCE-MRI has become the cornerstone of breast MRI, boasting a high negative-predictive value of 89% to 99%, although its specificity can vary. This review presents a thorough overview of magnetic resonance (MR) perfusion imaging in breast cancer, focusing on the role of DCE-MRI in clinical applications and exploring emerging MR perfusion imaging techniques.

Bilateral asymmetry of quantitative parenchymal kinetics at ultrafast DCE-MRI predict response to neoadjuvant chemotherapy in patients with HER2+ breast cancer

PURPOSE

To assess whether measurement of the bilateral asymmetry of semiquantitative and quantitative perfusion parameters from ultrafast dynamic contrast-enhanced MRI (DCE-MRI), allows early prediction of pathologic response after neoadjuvant chemotherapy (NAC) in patients with HER2+ breast cancer.

MATERIALS AND METHODS

Twenty-eight female patients with HER2+ breast cancer treated with NAC who underwent pre-NAC ultrafast DCE-MRI (3-9 s/phase) were enrolled for this study. Four semiquantitative and two quantitative parenchymal parameters were calculated for each patient. Ipsilateral/contralateral (I/C) ratio (for four parameters) and the difference between (for two parameters) ipsi- and contra-lateral parenchymal kinetic parameters (kBPE) were compared for patients with pathologic complete response (pCR) and those having residual disease. Lasso regression with leave-one-out cross validation was used to determine the optimal combination of parameters for a regression model and multivariable logistic regression was used to identify independent predictors for pCR. Chi-squared test, two-sided t-test and Kruskal-Wallis test were used.

RESULTS

The Ktrans I/C ratio cutoff value of 1.11 had a sensitivity of 83.3% and specificity of 75% for pCR. The ve I/C ratio cutoff value of 1.1 had a sensitivity of 75% and specificity of 81.3% for pCR. The area under the receiver operating characteristic curve of the three-kBPE parameter model, including initial area under the enhancement curve (AUC30) I/C ratio, KtransI/C ratio and ve I/C ratio, was 0.89 with sensitivity of 91.7% at specificity of 81.3%.

CONCLUSION

Quantitative assessment of bilateral asymmetry kBPE from pre-NAC ultrafast DCE-MRI can predict pCR in patients with HER2+ breast cancer.

Value of ultrafast and standard dynamic contrast-enhanced magnetic resonance imaging in the evaluation of the presence and extension of residual disease after neoadjuvant chemotherapy in breast cancer

PURPOSE

To evaluate the diagnostic performance of ultrafast and standard dynamic contrast-enhanced (DCE)-MRI in evaluating the residual disease after neoadjuvant chemotherapy (NAC) for breast cancer.

MATERIALS AND METHODS

Sixty-seven consecutive patients underwent MRI after NAC. Visual analysis of enhancement was performed on ultrafast and standard DCE-MRI, and compared between no residual disease and residual disease groups. The lesion diameters measured on the last phase of ultrafast DCE-MRI and early and delayed phases of standard DCE-MRI were compared with pathological diameter of entire residual cancer and residual invasive ductal carcinoma (IDC).

RESULTS

The visual analysis in the delayed phase of standard DCE-MRI exhibited the highest sensitivity (90%), whereas ultrafast DCE-MRI revealed the highest positive predictive value (92%). There were no significant differences between the diameters in the delayed phase of the standard DCE-MRI and the pathological entire residual cancer (p = 0.97), and the diameters in ultrafast DCE-MRI and the pathological residual IDC (p = 0.97).

CONCLUSION

The delayed phase of standard DCE-MRI may be effective for detecting the residual disease and evaluating the extension of entire residual cancer. Enhancement in ultrafast DCE-MRI may be strongly suggestive of the presence of residual disease, and effective for evaluating the extension of residual IDC.