Characterization of breast lesions with CE-MR multimodal morphological and kinetic analysis: Comparison with conventional mammography and high-resolution ultrasound

Vassiou, Katherine; Kanavou, T; Vlychou, M.; Poultsidi, Antigoni; Athanasiou, Evagelos; Arvanitis, Dimitrios L.; Fezoulidis, Ioannis

doi:10.1016/j.ejrad.2008.01.012

Cited by 43 publications

(26 citation statements)

References 26 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The PIE parameter (Equation 2), calculated as in [25,26], describes the post-initial behaviour of the signal curve from the maximum peak within the first 3 min to the end of the examination (fifth minute after contrast medium administration).…”

Section: Lesion Enhancement Kinetic Parametric Mapsmentioning

confidence: 99%

Assessing heterogeneity of lesion enhancement kinetics in dynamic contrast-enhanced MRI for breast cancer diagnosis

Karahaliou¹,

Vassiou²,

Arikidis³

et al. 2010

BJR

123

117

View full text Add to dashboard Cite

ABSTRACT. The current study investigates the feasibility of using texture analysis to quantify the heterogeneity of lesion enhancement kinetics in order to discriminate malignant from benign breast lesions. A total of 82 biopsy-proven breast lesions (51 malignant, 31 benign), originating from 74 women subjected to dynamic contrastenhanced magnetic resonance imaging (DCE-MRI) were analysed. Pixel-wise analysis of DCE-MRI lesion data was performed to generate initial enhancement, post-initial enhancement and signal enhancement ratio (SER) parametric maps; these maps were subsequently subjected to co-occurrence matrix texture analysis. The discriminating ability of texture features extracted from each parametric map was investigated using a least-squares minimum distance classifier and further compared with the discriminating ability of the same texture features extracted from the first post-contrast frame. Selected texture features extracted from the SER map achieved an area under receiver operating characteristic curve of 0.922 ¡ 0.029, a performance similar to post-initial enhancement map features (0.906 ¡ 0.032) and statistically significantly higher than for initial enhancement map (0.767 ¡ 0.053) and first post-contrast frame (0.756 ¡ 0.060) features. Quantifying the heterogeneity of parametric maps that reflect lesion washout properties could contribute to the computer-aided diagnosis of breast lesions in DCE-MRI. Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) significantly complements mammography and is characterised by its high sensitivity in detecting breast cancer. However, its specificity in distinguishing malignant from benign lesions is highly varied: reported values range from 37 up to 90% [1]. This variation is mainly due to the variety of image acquisition protocols and interpretation schemes adopted in clinical practice [2].Diagnostic criteria in DCE-MRI of breast masses [3, 4] include assessment of morphological features such as lesion shape, margin and enhancement homogeneity (internal architecture), as well as analysis/assessment of signal intensity-time curves generated from manually selected regions of interest (ROIs) within the lesion area. The analysis of signal intensity-time curves can be performed qualitatively (i.e. visual inspection of the curve shape [5,6]), by means of empirical parameters (e.g. relative enhancement, time-to-peak enhancement, washout ratio [7]) or quantitatively through pharmacokinetic modelling techniques [8].The subjective selection of ROI within the lesion accounts for the increased intra-and interobserver variability in the interpretation of lesion enhancement kinetics and for the discrepancy of reported findings [9,10]. While the selection of an ROI that captures the entire lesion is less subjective [11], it provides average enhancement kinetics estimates and completely ignores the heterogeneity of tumour vascular characteristics, which is diagnostically important [12]. Pixel-wise analysis of enhancement kinetics (based either on pharmacokinetic ...

show abstract

Section: Lesion Enhancement Kinetic Parametric Mapsmentioning

confidence: 99%

Assessing heterogeneity of lesion enhancement kinetics in dynamic contrast-enhanced MRI for breast cancer diagnosis

Karahaliou¹,

Vassiou²,

Arikidis³

et al. 2010

BJR

123

117

View full text Add to dashboard Cite

show abstract

“…In this regard, breast MRI has been shown to provide a high negative predictive value (NPV) that may help safely exclude a diagnosis of malignancy. [9][10][11][12] In this study, the diagnostic value of breast MRI as well as its ability to decrease unnecessary biopsies has been examined in a group of patients with solid breast lesions who had an indication for biopsy based on ultrasound results.…”

mentioning

confidence: 99%

Additional diagnostic value of MRI in patients with suspicious breast lesions based on ultrasound

Sarıca¹,

Uluc²

2014

BJR

View full text Add to dashboard Cite

Objective: Biopsy has long been the standard approach in Breast Imaging Reporting and Data System® (BI-RADS) 4 or BI-RADS 5 (American College of Radiology, Reston, VA) lesions despite a wide variation in reported incidence of malignancy in BI-RADS 4 lesions. This study examined the diagnostic value of breast MRI as well as its ability to decrease unnecessary biopsies in patients with solid breast lesions who had an indication for biopsy. Methods: In this retrospective study, 277 breast lesions with a documented histological diagnosis as established by ultrasound-guided biopsy were included. All patients were female, and biopsy was performed owing to a BI-RADS score of 4 or 5 on ultrasonography. In addition, all patients had undergone MRI before biopsy. Sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of MRI in predicting malignancy were calculated.Results: When all lesions were analysed, sensitivity, specificity, NPV and PPV of MRI in detecting malignancy were 94.2%, 56.1%, 90.7% and 68.1%, respectively. When only ultrasonographic BI-RADS 4 lesions are considered, the corresponding figures were as follows: 90.9%, 56.7%, 93.8% and 46.4%, respectively. False-negative rate of MRI for the latter group of lesions was 2.6%. 42% of unnecessary biopsies were avoided in sonographic BI-RADS 4 lesions. Conclusion: Despite promising results obtained in this study, dynamic MRI currently does not seem to be effective in ruling out the need for biopsy in the assessment of sonographic BI-RADS 4 lesions. However, advanced MRI techniques may assist in improving possible benefits of MRI in this patient group.

show abstract

“…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.…”

Section: Patients and Protocolmentioning

confidence: 99%

“…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].…”

Section: Introductionmentioning

confidence: 99%

“…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].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

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

Fusco¹,

Filice²,

Granata³

et al. 2013

JBiSE

View full text Add to dashboard Cite

Objective/Background: Qualitative assessment of uncertain (type II) time-intensity curves (TICs) in breast DCE-MRI is problematic and operator dependent. The aim of this work is to evaluate if a semi-quantitative assessment of uncertain TICs could improve overall diagnostic performance. Methods: In this study 49 lesions from 44 patients were retrospectively analysed. Per each lesion one region-of-interest (ROI)-averaged TIC was qualitatively evaluated by two radiologists in consensus: all the ROIs resulted in type II (uncertain) TIC. The same TICs were semi-quantitatively re-classified on the basis of the difference between the signal intensities of the last-time-point and of the peak: this difference was classified according to two different cut-off ranges (±5% and ±3%). All patients were cytological or histological biopsy proven. Fisher test and McNemar test were performed to evaluate if results were statistically significant (p < 0.05). Results: Using ±5% cut-off 16 TICs were reclassified as type III and 12 as type I while 21 were reclassified again as type II. Using ±3% 22 TICs were reclassified as type III and 16 as type I while 11 were reclassified again as type II. The semi-quantitative classification was compared to the histologicalcytological results: the sensitivity, specificity, positive and negative predictive values obtained with ±3% were 77%, 91%, 91% and 78% respectively while using ±5% were 58%, 96%, 94% and 68% respectively. Using the ±5% cut-off 26/28 (93%) TICs were correctly reclassified while using the ±3% cut-off 34/38 (90%) TICs were correctly reclassified (p < 0.05). Conclusions: Semi-quantitative methods in kinetic curve assessment on DCE-MRI could improve classification of qualitatively uncertain TICs, leading to a more accurate classification of suspicious breast lesions.

show abstract

Characterization of breast lesions with CE-MR multimodal morphological and kinetic analysis: Comparison with conventional mammography and high-resolution ultrasound

Cited by 43 publications

References 26 publications

Assessing heterogeneity of lesion enhancement kinetics in dynamic contrast-enhanced MRI for breast cancer diagnosis

Assessing heterogeneity of lesion enhancement kinetics in dynamic contrast-enhanced MRI for breast cancer diagnosis

Additional diagnostic value of MRI in patients with suspicious breast lesions based on ultrasound

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

Contact Info

Product

Resources

About