Computer-aided detection (CAD) system for breast MRI in assessment of local tumor extent, nodal status, and multifocality of invasive breast cancers: preliminary study
Tóm tắt
We aimed to investigate the efficacy of computer-aided detection (CAD) for MRI in the assessment of tumor extent, lymph node status, and multifocality in invasive breast cancers in comparison with other breast imaging modalities. Two radiologists measured the maximum tumor size, as well as, analyzed lymph node status and multifocality in 86 patients with invasive breast cancers using mammography, ultrasound, CT, MRI with and without CAD, and 18-fludeoxyglucose positron emission tomography (FDG-PET). The assessed data were compared with pathology. For tumor extent, there were no significant differences between pathological size and measured size using mammography, ultrasound, CT, or MRI with and without CAD (P > 0.05). For evaluation of lymph node status, ultrasound had the best kappa coefficients (0.522) for agreement between imaging and pathology, and diagnostic performance with 92.1% specificity and 90.0% positive predictive value. For multifocality, MRI with CAD had the highest area under the receiver operating characteristic curve (AUC = 0.888). CAD for MRI is feasible to assess tumor extent and multifocality in invasive breast cancer patients. However, CAD is not effective in evaluation of nodal status.
Tài liệu tham khảo
Smitt MC, Nowels KW, Zdeblick MJ, Jeffrey S, Carlson RW, Stockdale FE, et al. The importance of the lumpectomy surgical margin status in long-term results of breast conservation. Cancer. 1995;76(2):259–67.
Gage I, Schnitt SJ, Nixon AJ, Silver B, Recht A, Troyan SL, et al. Pathologic margin involvement and the risk of recurrence in patients treated with breast-conserving therapy. Cancer. 1996;78(9):1921–8.
Banerjee M, George J, Song EY, Roy A, Hryniuk W. Tree-based model for breast cancer prognostication. J Clin Oncol. 2004;22(13):2567–75.
Uematsu T, Yuen S, Kasami M, Uchida Y. Comparison of magnetic resonance imaging, multidetector row computed tomography, ultrasonography, and mammography for tumor extension of breast cancer. Breast Cancer Res Treat. 2008;112(3):461–74.
Berg WA, Gutierrez L, NessAiver MS, Carter WB, Bhargavan M, Lewis RS, et al. Diagnostic accuracy of mammography, clinical examination, US, and MR imaging in preoperative assessment of breast cancer. Radiology. 2004;233(3):830–49.
Bhooshan N, Giger ML, Jansen SA, Li H, Lan L, Newstead GM. Cancerous breast lesions on dynamic contrast-enhanced MR images: computerized characterization for image-based prognostic markers. Radiology. 2010;254(3):680–90.
Uematsu T, Kasami M, Yuen S. Comparison of FDG PET and MRI for evaluating the tumor extent of breast cancer and the impact of FDG PET on the systemic staging and prognosis of patients who are candidates for breast-conserving therapy. Breast Cancer. 2009;16(2):97–104.
Bluemke DA, Gatsonis CA, Chen MH, DeAngelis GA, DeBruhl N, Harms S, et al. Magnetic resonance imaging of the breast prior to biopsy. JAMA. 2004;292(22):2735–42.
Peters NH, Borel Rinkes IH, Zuithoff NP, Mali WP, Moons KG, Peeters PH. Meta-analysis of MR imaging in the diagnosis of breast lesions. Radiology. 2008;246(1):116–24.
Hrung JM, Sonnad SS, Schwartz JS, Langlotz CP. Accuracy of MR imaging in the work-up of suspicious breast lesions: a diagnostic meta-analysis. Acad Radiol. 1999;6(7):387–97.
Behjatnia B, Sim J, Bassett LW, Moatamed NA, Apple SK. Does size matter? Comparison study between MRI, gross, and microscopic tumor sizes in breast cancer in lumpectomy specimens. Int J Clin Exp Pathol. 2010;3(3):303–9.
Meeuwis C, van de Ven SM, Stapper G, Fernandez Gallardo AM, van den Bosch MA, Mali WP, et al. Computer-aided detection (CAD) for breast MRI: evaluation of efficacy at 3.0 T. Eur Radiol. 2010;20(3):522–8.
Lehman CD, Peacock S, DeMartini WB, Chen X. A new automated software system to evaluate breast MR examinations: improved specificity without decreased sensitivity. AJR Am J Roentgenol. 2006;187(1):51–6.
Beresford MJ, Padhani AR, Taylor NJ, Ah-See ML, Stirling JJ, Makris A, et al. Inter- and intraobserver variability in the evaluation of dynamic breast cancer MRI. J Magn Reson Imaging. 2006;24(6):1316–25.
Levrini G, Sghedoni R, Mori C, Botti A, Vacondio R, Nitrosi A, et al. Size assessment of breast lesions by means of a computer-aided detection (CAD) system for magnetic resonance mammography. Radiol Med. 2011;116(7):1039–49.
American College of Radiology. ACR BI-RADS breast imaging and reporting data system: breast imaging atlas. 4th ed. Reston, VA: American College of Radiology; 2003.
Seo BK, Pisano ED, Cho KR, Cho PK, Lee JY, Kim SJ. Low-dose multidetector dynamic CT in the breast: preliminary study. Clin Imaging. 2005;29(3):172–8.
Duchesne N, Jaffey J, Florack P, Duchesne S. Redefining ultrasound appearance criteria of positive axillary lymph nodes. Can Assoc Radiol J. 2005;56(5):289–96.
Damera A, Evans AJ, Cornford EJ, Wilson AR, Burrell HC, James JJ, et al. Diagnosis of axillary nodal metastases by ultrasound-guided core biopsy in primary operable breast cancer. Br J Cancer. 2003;89(7):1310–3.
Partridge SC, Gibbs JE, Lu Y, Esserman LJ, Tripathy D, Wolverton DS, et al. MRI measurements of breast tumor volume predict response to neoadjuvant chemotherapy and recurrence-free survival. AJR Am J Roentgenol. 2005;184(6):1774–81.
Williams TC, DeMartini WB, Partridge SC, Peacock S, Lehman CD. Breast MR imaging: computer-aided evaluation program for discriminating benign from malignant lesions. Radiology. 2007;244(1):94–103.
Levman JE, Causer P, Warner E, Martel AL. Effect of the enhancement threshold on the computer-aided detection of breast cancer using MRI. Acad Radiol. 2009;16(9):1064–9.
Egan RL. Multicentric breast carcinomas: clinical-radiographic-pathologic whole organ studies and 10-year survival. Cancer. 1982;49(6):1123–30.
Chmura Kraemer H, Periyakoil VS, Noda A. Kappa coefficients in medical research. Stat Med. 2002;21(14):2109–29.
Hylton NM. Vascularity assessment of breast lesions with gadolinium-enhanced MR imaging. Magn Reson Imaging Clin N Am. 1999;7(2):411–20.
Hylton N. Dynamic contrast-enhanced magnetic resonance imaging as an imaging biomarker. J Clin Oncol. 2006;24(20):3293–8.
Arasu VA, Chen RC, Newitt DN, Chang CB, Tso H, Hylton NM, et al. Can signal enhancement ratio (SER) reduce the number of recommended biopsies without affecting cancer yield in occult MRI-detected lesions? Acad Radiol. 2011;18(6):716–21.
Dorrius MD, Jansen-van der Weide MC, van Ooijen PM, Pijnappel RM, Oudkerk M. Computer-aided detection in breast MRI: a systematic review and meta-analysis. Eur Radiol. 2011;21(8):1600–8.
Elston CW, Ellis IO. The Breast. Edinburgh: Churchill Livingstone; 1998.
Heusner TA, Kuemmel S, Umutlu L, Koeninger A, Freudenberg LS, Hauth EA, et al. Breast cancer staging in a single session: whole-body PET/CT mammography. J Nucl Med. 2008;49(8):1215–22.
Demartini WB, Lehman CD, Peacock S, Russell MT. Computer-aided detection applied to breast MRI: assessment of CAD-generated enhancement and tumor sizes in breast cancers before and after neoadjuvant chemotherapy. Acad Radiol. 2005;12(7):806–14.
Ahn JH, Son EJ, Kim JA, Youk JH, Kim EK, Kwak JY, et al. The role of ultrasonography and FDG-PET in axillary lymph node staging of breast cancer. Acta Radiol. 2010;51(8):859–65.
Lumachi F, Tregnaghi A, Ferretti G, Povolato M, Marzola MC, Zucchetta P, et al. Accuracy of ultrasonography and 99mTc-sestamibi scintimammography for assessing axillary lymph node status in breast cancer patients. A prospective study. Eur J Surg Oncol. 2006;32(9):933–6.
Alvarez S, Anorbe E, Alcorta P, Lopez F, Alonso I, Cortes J. Role of sonography in the diagnosis of axillary lymph node metastases in breast cancer: a systematic review. AJR Am J Roentgenol. 2006;186(5):1342–8.