JBiSE  Vol.6 No.3 A , March 2013
Can semi-quantitative evaluation of uncertain (type II) time-intensity curves improve diagnosis in breast DCE-MRI?
ABSTRACT

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 histological-cytological 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.


Cite this paper
Fusco, R. , Filice, S. , Granata, V. , Mandato, Y. , Porto, A. , D’Aiuto, M. , Rinaldo, M. , Bonito, M. , Sansone, M. , Sansone, C. , Rotondo, A. and Petrillo, A. (2013) Can semi-quantitative evaluation of uncertain (type II) time-intensity curves improve diagnosis in breast DCE-MRI?. Journal of Biomedical Science and Engineering, 6, 418-425. doi: 10.4236/jbise.2013.63A052.
References
[1]   Ojeda-Fournier, H., Choe, K.A. and Mahoney, M.C. (2007) Recognizing and interpreting artifacts and pitfalls in MR imaging of the breast. Radiographics, 27, S147-S164. doi:10.1148/rg.27si075516

[2]   Moon, M., Cornfeld, D. and Weinreb, J. (2009) Dynamic contrast-enhanced breast MR imaging. Magnetic Resonance Imaging Clinics of North America, 17, 351-362. doi:10.1016/j.mric.2009.01.010

[3]   Orel, S. (2008) Who should have breast magnetic resonance imaging evaluation? Journal of Clinical Oncology, 26, 703-711. doi:10.1200/JCO.2007.14.3594

[4]   Kuhl, C.K., et al. (1999) Dynamic breast MR imaging: Are signal intensity time course data useful for differential diagnosis of enhancing lesions? Radiology, 211, 101- 110.

[5]   Macura, K.F., Ouwerkerk, R., Jacobs, M.A. and Bluemke, D.A. (2006) Patterns of enhancement on breast MR images: Interpretation and imaging pitfalls. Radiographics, 26, 1719-1734. doi:10.1148/rg.266065025

[6]   Evelhoch, J.L. (1999) Key factors in the acquisition of contrast kinetic data for oncology. Journal of Magnetic Resonance Imaging, 10, 254-259. doi:10.1002/(SICI)1522-2586(199909)10:3<254::AID-JMRI5>3.0.CO;2-9

[7]   Goto, M., et al. (2007) Diagnosis of breast tumors by contrast-enhanced MR Imaging: comparison between the diagnostic performance of dynamic enhancement patterns and morphologic features. Journal of Magnetic Resonance Imaging, 25, 104-112. doi:10.1002/jmri.20812

[8]   Siegmann, K.C., et al. (2002) MR Imaging-detected breast lesions: Histopathologic correlation of lesion characteristics and signal intensity data. American Journal of Roentgenology, 178, 1403-1409. doi:10.2214/ajr.178.6.1781403

[9]   Hara, M., Watanabe, T., Okumura, A., et al. (2009) Angle between 1 and 4 min gives the most significant difference in time-intensity curves between benign disease and breast cancer: Analysis of dynamic magnetic resonance imaging in 103 patients with breast lesions. Clinical Imaging, 33, 335-342. doi:10.1016/j.clinimag.2008.12.001

[10]   Pediconi, F., et al. (2010) Role of breast MR imaging for predicting malignancy of histologically borderline lesions diagnosed at core needle biopsy: Prospective evaluation. Radiology, 257, 653-661. doi:10.1148/radiol.10100732

[11]   Baltzer, P.A.T., Renz, D.M., Kullnig, P.E., et al. (2009) Application of computer-aided diagnosis (CAD) in MR-mammography (MRM): Do we really need whole lesion time curve distribution analysis? Academic Radiology, 16, 435-442. doi:10.1016/j.acra.2008.10.007

[12]   Vassiou, K., Kanavou, T., Vlychou, M., et al. (2009) Characterization of breast lesions with CE-MR multimodal morphological and kinetic analysis: Comparison with conventional mammography and high-resolution ultra- sound. European Journal of Radiology, 70, 69-76. doi:10.1016/j.ejrad.2008.01.012

[13]   Leinsinger, G., et al. (2006) Cluster analysis of signalintensity time course in dynamic breast MRI: Does unsupervised vector quantization help to evaluate small mammographic lesions? European Radiology, 16, 1138-1146. doi:10.1007/s00330-005-0053-9

[14]   Pediconi, F., Catalano, C., Padula, S., Roselli, A., Dominelli, V., Cagioli, S., Kirchin, M.A., Pirovano, G. and Passariello, R. (2008) Contrast-enhanced MR mammography: Improved lesion detection and differentiation with gado-benate dimeglumine. American Journal of Roentgenology, 191, 1339-1346. doi:10.2214/AJR.07.3533

[15]   Jansen, S.A., Fan, X., Karczmar, G.S., et al. (2008) DCEMRI of breast lesions: It kinetic analysis equally effective for both mass and nonmass-like enhancement? Medical Physics, 35, 3102-3109. doi:10.1118/1.2936220

[16]   Karahaliou, A., Vassiou, K., Arikidis, N.S., Skiadopoulos, S., Kanavou, T. and Costaridou, L. (2010) Assessing heterogeneity of lesion enhancement kinetics in dynamic contrast-enhanced MRI for breast cancer diagnosis. British Journal of Radiology, 83, 296-309. doi:10.1259/bjr/50743919

[17]   Yoo, J.L., Woo, O.H., Kim, Y.K., Cho, K.R., Yong, H.S., Seo, B.K., Kim, A. and Kang, E.Y. (2010) Can MR imaging contribute in characterizing well-circumscribed breast carcinomas? Radiographics, 30, 1689-1702. doi:10.1148/rg.306105511

[18]   Agrawal, G., Su, M.Y., Nalcioglu, O., Feig, S.A. and Chen, J.H. (2009) Significance of breast lesion descriptor in the ACR BI-RADS MRI lexicon. Cancer, 115, 1363- 1380. doi:10.1002/cncr.24156

[19]   El Khouli, R.H., Macura, K.J., Jacobs, M.A., Khalil, T.H., Kamel, I.R., Dwyer, A. and Bluemke, D.A. (2009) Dynamic contrast-enhanced MRI of the breast: Quantitative method for kinetic curve type assessment. American Journal of Roentgenology, 193, W295-W300. doi:10.2214/AJR.09.2483

[20]   Sansone, M., Fusco, R., Petrillo, A., Petrillo, M. and Bracale, M. (2011) An expectation-maximisation approach for simultaneous pixel classification and tracer kinetic modelling in dynamic contrast enhanced-magnetic resonance imaging. Medical & Biological Engineering & Com- puting, 49, 485-495. doi:10.1007/s11517-010-0695-x

[21]   Fusco, R., Sansone, M., Petrillo, M. and Petrillo, A. (2012) Influence of parameterization on tracer kinetic modeling in DCE-MRI. Journal of Medical and Biological Engineering, in press.

[22]   Fusco, R., Sansone, M., Maffei, S. and Petrillo, A. (2012) Dynamic contrast-enhanced MRI in breast cancer: A comparison between distributed and compartmental tracer kinetic models. Journal of Biomedical Graphics and Com- puting, 2, 23-36. doi:10.5430/jbgc.v2n2p23

[23]   Fusco, R., Sansone, M., Sansone, C. and Petrillo, A. (2012) Segmentation and classification of breast lesions using dynamic and textural features in dynamic contrast enhanced-magnetic resonance imaging. 25th International Symposium on Computer-Based Medical Systems (CBMS), Naples, 20-22 June 2012, 1-4.

[24]   Fusco, R., Sansone, M., Petrillo, A. and Sansone, C. (2012) A multiple classifier system for classification of breast lesions using dynamic and morphological features in DCE-MRI. Structural, Syntactic, and Statistical Pattern Recognition. Lecture Notes in Computer Science, 7626, 684-692. doi:10.1007/978-3-642-34166-3_75

[25]   Schisterman, E.F., Perkins, N.J., Liu, A. and Bondell, H. (2005) Optimal cut-point and its corresponding Youden Index to discriminate individuals using pooled blood samples. Epidemiology, 16, 73-81. doi:10.1097/01.ede.0000147512.81966.ba

[26]   Obuchowski, N.A. (2005) ROC analysis. American Journal of Roentgenology, 184, 364-372. doi:10.2214/ajr.184.2.01840364

[27]   Joseph, L. and Reinhold, C. (2005) Statistical inference for proportions. American Journal of Roentgenology, 184, 1057-1064. doi:10.2214/ajr.184.4.01841057

[28]   Hawass, N.E. (1997) Comparing the sensitivities and specificities of two diagnostic procedures performed on the same group of patients. British Journal of Radiology, 70, 360-366.

[29]   Kuhl, C. (2007) The current status of breast MR imaging. Part I. Choice of technique, image interpretation, diag- nostic accuracy, and transfer to clinical practice. Radiology, 244, 356-378. doi:10.1148/radiol.2442051620

[30]   Meyer-Baese, A., et al. (2008) Computer-aided diagnosis and visualization based on clustering and independent component analysis for breast MRI. International Conference on Image Processing, 12, 3000-3003.

[31]   El Khouri, C., Tardivon, A., Thibault, F., Barreau, B. and Neuenshwander, S. (2007) Comment je fais une IRM mammaire? Journal de Radiologie, 88, 694-700. doi:10.1016/S0221-0363(07)89880-5

[32]   Molleran, V. and Mahoney, M. (2010) The BI-RADS breast magnetic resonance imaging lexicon. Magnetic Resonance Imaging Clinics of North America, 18, 171-185. doi:10.1016/j.mric.2010.02.001

[33]   Eby, P.R., et al. (2009) Characteristics of probably benign breast MRI lesions. American Journal of Roentgenology, 193, 861-867. doi:10.2214/AJR.08.2096

[34]   Jansen, S.A., Fan, X., Medved, M., et al. (2010) Characterizing early contrast uptake of ductal carcinoma in situ with high temporal resolution dynamic contrast-enhanced MRI of the breast: A pilot study. Physics in Medicine and Biology, 55, 473-485. doi:10.1088/0031-9155/55/19/N02

[35]   Nishiura, M., Tamaki, Y. and Murase, K. (2010) Differentiation between ductal carcinoma in situ and mastopathy using contrast-enhanced magnetic resonance imaging and a model of contrast enhancement. European Journal of Radiology, 80, 740-743. doi:10.1016/j.ejrad.2010.09.039

[36]   Fernández-Guinea, O., Andicoechea, A., González, L.O., González-Reyes, S., Merino, A.M., Hernández, L.C., López- Mu?iz, A., García-Pravia, P. and Vizoso, F.J. (2010) Relationship between morphological features and kinetic patterns of enhancement of the dynamic breast magnetic resonance imaging and clinico-pathological and biological factors in invasive breast cancer. BMC Cancer, 10, 8. doi:10.1186/1471-2407-10-8

[37]   Jansen, S.A., Shimauchi, A., Zak, L., Fan, X., Wood, A.M., Karczmar, G.S. and Newstead, G.M. (2009) Ki- netic curves of malignant lesions are not consistent across MRI systems: Need for improved standardization of breast dynamic contrast-enhanced MRI acquisition. American Journal of Roentgenology, 193, 832-839. doi:10.2214/AJR.08.2025

[38]   Schnall, M.D., Blume, J., Bluemke, D.A., DeAngelis, G.A., DeBruhl, N., Harms, S., Heywang-K?brunner, S.H., Hylton, N., Kuhl, C.K., Pisano, E.D., Causer, P., Schnitt, S.J., Thickman, D., Stelling, C.B., Weatherall, P.T., Lehman, C. and Gatsonis, C.A. (2006) Diagnostic architectural and dynamic features at breast MR imaging: Multicenter study. Radiology, 238, 42-53. doi:10.1148/radiol.2381042117

[39]   Bhooshan, N., Giger, M.L., Jansen, S.A., Li, H., Lan, L. and New-stead, G.M. (2010) Cancerous breast lesions on dynamic contrast-enhanced MR images: Computerized characterization for image-based prognostic markers. Radiology, 254, 680-690. doi:10.1148/radiol.09090838

[40]   Santamaría, G., Velasco, M., Bargalló, X., Caparrós, X., Farrús, B. and Luis Fernández, P. (2010) Radiologic and pathologic findings in breast tumors with high signal intensity on T2-weighted MR images. Radiographics, 30, 533-548. doi:10.1148/rg.302095044

[41]   Peters, N.H., Borel Rinkes, I.H., Zuithoff, N.P., Mali, W.P., Moons, K.G. and Peeters, P.H. (2008) Meta-analysis of MR imaging in the diagnosis of breast lesions. Radiology, 246, 116-124. doi:10.1148/radiol.2461061298

 
 
Top