Computer-aided detection in breast MRI: a systematic review and meta-analysis

To evaluate the additional value of computer-aided detection (CAD) in breast MRI by assessing radiologists' accuracy in discriminating benign from malignant breast lesions. A literature search was performed with inclusion of relevant studies using a commercially available CAD system with automatic colour mapping. Two independent researchers assessed the quality of the studies. The accuracy of the radiologists' performance with and without CAD was presented as pooled sensitivity and specificity. Of 587 articles, 10 met the inclusion criteria, all of good methodological quality. Experienced radiologists reached comparable pooled sensitivity and specificity before and after using CAD (sensitivity: without CAD: 89%; 95% CI: 78-94%, with CAD: 89%; 95%CI: 81-94%) (specificity: without CAD: 86%; 95% CI: 79-91%, with CAD: 82%; 95% CI: 76-87%). For residents the pooled sensitivity increased from 72% (95% CI: 62-81%) without CAD to 89% (95% CI: 80-94%) with CAD, however, not significantly. Concerning specificity, the results were similar (without CAD: 79%; 95% CI: 69-86%, with CAD: 78%; 95% CI: 69-84%). CAD in breast MRI has little influence on the sensitivity and specificity of experienced radiologists and therefore their interpretation remains essential. However, residents or inexperienced radiologists seem to benefit from CAD concerning breast MRI evaluation

Breast MRI: guidelines from the European Society of Breast Imaging

The aim of breast MRI is to obtain a reliable evaluation of any lesion within the breast. It is currently always used as an adjunct to the standard diagnostic procedures of the breast, i.e., clinical examination, mammography and ultrasound. Whereas the sensitivity of breast MRI is usually very high, specificity—as in all breast imaging modalities—depends on many factors such as reader expertise, use of adequate techniques and composition of the patient cohorts. Since breast MRI will always yield MR-only visible questionable lesions that require an MR-guided intervention for clarification, MRI should only be offered by institutions that can also offer a MRI-guided breast biopsy or that are in close contact with a site that can perform this type of biopsy for them. Radiologists involved in breast imaging should ensure that they have a thorough knowledge of the MRI techniques that are necessary for breast imaging, that they know how to evaluate a breast MRI using the ACR BI-RADS MRI lexicon, and most important, when to perform breast MRI. This manuscript provides guidelines on the current best practice for the use of breast MRI, and the methods to be used, from the European Society of Breast Imaging (EUSOBI)

Improvement in breast lesion characterization with dynamic contrast-enhanced MRI using pharmacokinetic modeling and bookend T-1 measurements

Dynamic contrast-enhanced breast MR imaging was performed on 14 patients (five cancerous lesions, nine benign) with slice-selective spoiled gradient-recalled echo (2D SPGR) imaging. Adiabatic saturation recovery T-1 measurements were performed before (T-1pre) and after (T-1post) 2D SPGR imaging. These two "book-end" T-1 measurements were used to calibrate the equations which were employed to convert the time course of the 2D SPGR signal strength to T-1-vs.-time, which in turn was used to compute the gadolinium concentration-vs.-time ([C](t)) in the lesion. The extraction-flow product (EF) was computed for each lesion by pharmacokinetic modeling of [C](t). For this study, EF provided a sensitivity and specificity for cancer of 100% and 78%, respectively. When only T-1pre was used to estimate [C](t) (which assumes a priori knowledge of the shape and amplitude of the slice profile), the sensitivity and specificity fell to 80% and 56%, respectively. This is presumably due to unexpected variations in the shape and/or amplitude of the slice profile, which could be caused by factors such as patient-to-patient variations in breast geometry or inconsistently set transmit gains. Therefore, both T-1pre and T-1post measurements are necessary for optimum sensitivity and specificity using pharmacokinetic analysis. (C) 2004 Wiley-Liss, Inc

A comparison of T-2(*)-weighted magnitude and phase imaging for measuring the arterial input function in the rat aorta following intravenous injection of gadolinium contrast agent

The arterial input function (AIF) is important for quantitative MR imaging perfusion experiments employing Gd contrast agents. This study compared the accuracy of T-2*-weighted magnitude and phase imaging for noninvasive measurement of the AIF in the rat aorta. Twenty-eight in vivo experiments were performed involving simultaneous arterial blood sampling and MR imaging following Gd injection. In vitro experiments were also performed to confirm the in vivo results. At 1.89 T and TE = 3 ms, the relationship between changes in 1/T-2* in blood (estimated from MR signal magnitude) and Gd concentration ([Gd]) was measured to be similar to 19 s(-1) mM(-1), while that between phase and [Gd] was similar to 0.19 rad mM(-1). Both of these values are consistent with previously published results. The in vivo phase data had approximately half as much scatter with respect to [Gd] than the in vivo magnitude data (r(2) = .34 vs. r(2)= .17, respectively). This is likely due to the fact that the estimated change in 1/T2* is more sensitive than the phase to a variety of factors such as partial volume effects and T, weighting. Therefore, this study indicates that phase imaging may be a preferred method for measuring the AIF in the rat aorta compared to T2*-weighted magnitude imaging. (c) 2005 Elsevier Inc. All rights reserved

Computer-aided Diagnosis in Breast MRI: Do Adjunct Features Derived from T2-weighted Images Improve Classification of Breast Masses?

Abstract. In the field of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) of breast cancer, current research efforts in computer-aided diagnosis (CADx) are mainly focused on the temporal series of T1-weighted images acquired during uptake of a contrast agent, processing morphological and kinetic information. Although static T2weighted images are usually part of DCE-MRI protocols, they are seldom used in CADx systems. The aim of this work was to evaluate to what extent T2-weighted images provide complementary information to a CADx system, improving its performance for the task of discriminating benign breast masses from life-threatening carcinomas. In a preliminary study considering 64 masses, inclusion of lesion features derived from T2weighted images increased the classification performance from Az=0.94 to Az=0.99.

ISOLLE: Locally linear embedding with geodesic distance

Varini C, Degenhard A, Nattkemper TW. ISOLLE: Locally linear embedding with geodesic distance. In: Jorge A, ed. KNOWLEDGE DISCOVERY IN DATABASES: PKDD 2005. Lecture notes in computer science ; 3721 : Lecture notes in artificial intelligence. Vol 3721. Berlin, Heidelberg: SPRINGER-VERLAG BERLIN; 2005: 331-342.Locally Linear Embedding (LLE) has recently been proposed as a method for dimensional reduction of high-dimensional nonlinear data sets. In LLE each data point is reconstructed from a linear combination of its n nearest neighbors, which are typically found using the Euclidean Distance. We propose an extension of LLE which consists in performing the search for the neighbors with respect to the geodesic distance (ISOLLE). In this study we show that the usage of this metric can lead to a more accurate preservation of the data structure. The proposed approach is validated on both real-world and synthetic data