The diverse pathology and kinetics of mass, nonmass, and focus enhancement on MR imaging of the breast

Abstract

Purpose To compare the pathology and kinetic characteristics of breast lesions with focus, mass and nonmass-like enhancement. Materials and Methods 852 MRI detected breast lesions in 697 patients were selected for an IRB approved review. Patients underwent dynamic contrast enhanced MRI using one pre and three to six post-contrast T1 weighted images. The ‘type’ of enhancement was classified as mass, non-mass or focus, and kinetic curves quantified by the initial enhancement percentage (E1), time to peak enhancement (Tpeak) and signal enhancement ratio (SER). These kinetic parameters were compared between malignant and benign lesions within each morphologic type. Results 552 lesions were classified as mass (396 malignant, 156 benign), 261 as nonmass (212 malignant,49 benign) and 39 as focus (9 malignant,30 benign). The most common pathology of malignant/benign lesions by morphology: for mass, invasive ductal carcinoma/fibroadenoma; for nonmass, ductal carcinoma in situ (DCIS)/fibrocystic change(FCC); for focus, DCIS/FCC. Benign mass lesions exhibited significantly lower E1, longer Tpeak and lower SER compared with malignant mass lesions (p < 0.0001). Benign nonmass lesions exhibited only a lower SER compared to malignant nonmass lesions (p<0.01). Conclusions By considering the diverse pathology and kinetic characteristics of different lesion morphologies, diagnostic accuracy may be improved.

Morphological Distribution and Internal Enhancement Architecture of Contrast-Enhanced Magnetic Resonance Imaging in the Diagnosis of Non-Mass-Like Breast Lesions: A Meta-Analysis

“…Recent studies evaluated the diagnostic performance of MR imaging on non-mass-like breast lesions (5)(6)(7)(8)(9)(10)(11)(12)(13)(14)(15)(16)(17)(18)(19). No significant difference was found in kinetic enhancement curve assessment between non-mass-like benign and malignant lesions (7,9,12,13,(15)(16)(17)(18)20,21). However, among lesions showing non-mass-like enhancement on DCE-MRI, .4% of the segmental enhancements and 44-100% of clustered ring enhancements were found malignant (7,8,10,16,19,22), respectively.…”

Segmentation and Kinetic Analysis of Breast Lesions in DCE-MR Imaging Using ICA

“…Enhancement curves representing the change in blood flow are obtained from DCE-MRI and help to differentiate between malignant and benign lesions. Research has demonstrated the high relevance of enhancement curves for mass-like lesions [17,11]. However, this method has not yet proven successful for the assessment of non-mass-like lesions [10].…”

“…where evaluated by a receiver operating characteristic (ROC) which showed an area under the curve (AUC) of .88 for mass-like lesions, but for non-mass-like lesions only a AUC of .59, hardly better than the random decision of an AUC of .5. Another approach is done by Jansen et al [11]. They extracted and analyzed qualitative and quantitative features from DCE-MRI enhancement curves for mass-like, non-mass-like and focus enhancements.…”

Automated analysis of non-mass-enhancing lesions in breast MRI based on morphological, kinetic, and spatio-temporal moments and joint segmentation-motion compensation technique

“…While mass-enhancing lesions exhibit a typical kinetic behavior that is distinctive for malignant and benign lesions, non-mass-enhancing lesions have kinetic characteristics that are far less well characterized and of limited accuracy in discriminating between malignant and benign behavior [26]. As a dynamical feature, the slope of the relative signal intensity enhancement (RSIE) is used in most current CAD systems.…”

“…Research initiatives have been focused on automated analysis of mass lesions [18][19][20][21][22][23][24], while very few studies investigated the characterization of the morphology and/or enhancement kinetic features of non-mass lesions [17,[25][26][27]. The studies showed a much lower sensitivity and specificity for non-mass-like enhancement lesions compared with masses and suggested the need for more advanced algorithms for the diagnosis of non-mass-like enhancement.…”