Cluster analysis of signal-intensity time course in dynamic breast MRI: does unsupervised vector quantization help to evaluate small mammographic lesions?

Abstract

We examined whether neural network clustering could support the characterization of diagnostically challenging breast lesions in dynamic magnetic resonance imaging (MRI). We examined 88 patients with 92 breast lesions (51 malignant, 41 benign). Lesions were detected by mammography and classified Breast Imaging and Reporting Data System (BIRADS) III (median diameter 14 mm). MRI was performed with a dynamic T1-weighted gradient echo sequence (one precontrast and five postcontrast series). Lesions with an initial contrast enhancement >or=50% were selected with semiautomatic segmentation. For conventional analysis, we calculated the mean initial signal increase and postinitial course of all voxels included in a lesion. Secondly, all voxels within the lesions were divided into four clusters using minimal-free-energy vector quantization (VQ). With conventional analysis, maximum accuracy in detecting breast cancer was 71%. With VQ, a maximum accuracy of 75% was observed. The slight improvement using VQ was mainly achieved by an increase of sensitivity, especially in invasive lobular carcinoma and ductal carcinoma in situ (DCIS). For lesion size, a high correlation between different observers was found (R(2) = 0.98). VQ slightly improved the discrimination between malignant and benign indeterminate lesions (BIRADS III) in comparison with a standard evaluation method.

Can semi-quantitative evaluation of uncertain (type II) time-intensity curves improve diagnosis in breast DCE-MRI?

“…ILC with a diffuse growth pattern appearing as a non mass-like enhancement may exhibit low-magnitude and persistent-enhancement kinetics possibly associated with weak angiogenic activity. Similarly, the patterns of enhancement kinetics are unreliable for diagnosis of DCIS; only about 70% of DCIS exhibit fast, initial enhancement, with variable delayed-phase enhancement patterns [13,14].…”

“…They were affected by: Invasive Lobular Carcinoma (ILC) (6 subjects), Lobular Carcinoma in Situ (LCIS) (2), Invasive Ductal Carcinoma (IDC) (12), Ductal Carcinoma in Situ (DCIS) (6), phyllodes giant tumor (1), fibroadenomas (13), focalatypical forms of hyperplasia (10). They were all cytological or histological proven.…”

“…The vascularisation of the malignant lesions resulting from neo-vessels, that are the basis of exponential tumour growth, is one of the major reasons that dynamic features of MRI have played a crucial role in breast cancer for a decade [7][8][9][10][11][12][13][14][15][16][17][18][19].…”

“…Kinetic curve analysis can be performed qualitatively (visual inspection of the curve shape), semi-quantitatively (by means of empirical parameters of signal intensity changes as gradient of the upslope of enhancement curves, maximum signal intensity and wash-out gradient) or quantitatively through pharmacokinetic modelling techniques [5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23][24].…”

Classification of Small Contrast Enhancing Breast Lesions in Dynamic Magnetic Resonance Imaging Using a Combination of Morphological Criteria and Dynamic Analysis Based on Unsupervised Vector-Quantization

“…So, the 3-dimensional extension of the lesion was taken into account. 19 Lesion segmentation as a preparative step for dynamic analysis was performed by only 1 observer. To test the stability of the method, the interobserver-variability was analyzed in a sample of 20 lesions.…”