Kinetic characteristics of ductal carcinoma in situ (DCIS) in dynamic breast MRI using computer-assisted analysis

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.

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.

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.

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.

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.