Abstract
Background: Enhancement characteristics of breast lesions are regarded as a major criterion for their differential diagnosis in dynamic breast MRI (bMRI). However, ductal carcinoma in situ (DCIS) exhibits a highly heterogeneous enhancement pattern when kinetic analysis is performed conventionally by manual placement of region of interest (ROI) and therefore its diagnosis remains challenging.
Purpose: To compare enhancement characteristics of DCIS lesions on dynamic bMRI using manual ROI placement with computer-aided analysis and to evaluate whether the latter might increase the detection rate of kinetic features suspicious for malignancy.
Material and Methods: The enhancement patterns of 47 histopathologically verified pure DCIS lesions were evaluated on bMRI images using manual ROI placement as well as a commercially available computer analysis software. The latter is able to automatically assess enhancement characteristics of a whole lesion pixelwise. Kinetic features evaluated included classification of lesion enhancement pattern into washout, plateau or persistent curve type. A washout and plateau enhancement pattern are regarded as suggestive for malignancy.
Results: Morphological classification revealed focus-like enhancement in 2 lesions, mass enhancement in 11, and non-mass enhancement in 34. Manual placement of ROI demonstrated a suspicious enhancement pattern in 51.1% of the DCIS lesions, which could not be significantly increased using computer-aided analysis. Of the mass and non-mass-enhancing DCIS lesions, 90.9% and 38.3%, respectively, demonstrated suspicious kinetic curves. After application of the automated analysis software, the detection rate of suspicious enhancement patterns was unchanged in mass DCIS lesions and increased to 52.9% in non-mass DCIS lesions (P=0.33). However, the increase in the detection of washout curves alone was significant (P=0.02). In all, 40% of G1, 41.1% of G2, and 60% of G3 lesions demonstrated a suspicious curve type with manual evaluation. Computer analysis increased the detection of suspicious enhancement patterns in a non-significant manner to 50%, 58.8%, and 70%, respectively.
Conclusion: The detection of suspicious enhancement curves could not be significantly increased in DCIS lesions when using computer-aided analysis despite a significantly higher detection rate of washout curves alone.
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Acknowledgment
We would like to thank Dr Nalinda Pallawela for editing the manuscript.
Declaration of interest: The authors report no conflicts of interest. The authors alone are responsible for the content and writing of the paper.