Characteristics of ductal carcinoma in situ in magnetic resonance imaging
Institute of Diagnostic and Interventional Radiology, Friedrich Schiller University of Jena, Erlanger Allee 101, Jena, Germany. Clinical Imaging
(Impact Factor: 0.81).
11/2007; 31(6):394-400. DOI: 10.1016/j.clinimag.2007.04.030
The aim of this study was to evaluate typical dynamic and morphological characteristics of ductal carcinoma in situ (DCIS) in magnetic resonance imaging (MRI). An optimized diagnosis of DCIS is considered to be valuable for radiologists and clinicians, especially for early and successful treatment planning.
Magnetic resonance examinations of 74 patients with pure DCIS were evaluated. Categories were established for signal increase (C1=the same enhancement as glandular tissue; C2=slow and continuous; C3=strong initial and slow further increase; C4=strong initial increase and plateau phenomenon; and C5=strong initial increase followed by a washout phenomenon) and morphological findings (M0=no pattern observed; M1=linear or linear-branched; M2=segmental dotted or granular; M3=segmental homogenous; and M4=focal spotlike). All cases were associated with histopathological results.
Regarding the 74 DCIS lesions, 37 (50%) showed a signal increase typical of malignancy (C4 and C5). Among all cases, 33.3% of G1 lesions, 68.4% of G2 lesions, and 55.5% of G3 lesions presented a C4 or C5 enhancement. Furthermore, 55.4% (n=41) showed a segmental dotted enhancement (M2), whereas 17.6% showed a focal spotlike enhancement (M4). The morphological features of the other lesions were as follows: 12.2% homogeneous (M3) and 4.0% linear (M1). In 8 cases (10.8%), no significant pattern was observed (M0). Combining dynamic and morphological characteristics, 68.9% presented an appearance comparable with the appearance of invasive breast cancer in MRI.
Ductal CIS lesions show typical morphological and kinetic, but heterogeneous, characteristics in MRI, comparable with the histopathological variety of the disease. For detecting pure DCIS cases early and precisely, a combination of dynamic and morphological criteria seems to be important.
- "On the other hand, diagnosis of non-mass-like enhancement lesions is much more challenging. Malignant lesions such as ductal carcinoma in situ (DCIS) and invasive lobular cancer (ILC) are likely to present as non-mass-like enhancement [11, 12, 21, 22]. Benign fibrocystic changes, which also appear as non-mass-like enhancement, are a frequent finding on DCE-MRI . "
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ABSTRACT: To investigate methods developed for the characterisation of the morphology and enhancement kinetic features of both mass and non-mass lesions, and to determine their diagnostic performance to differentiate between malignant and benign lesions that present as mass versus non-mass types.
Quantitative analysis of morphological features and enhancement kinetic parameters of breast lesions were used to differentiate among four groups of lesions: 88 malignant (43 mass, 45 non-mass) and 28 benign (19 mass, 9 non-mass). The enhancement kinetics was measured and analysed to obtain transfer constant (K(trans)) and rate constant (k(ep)). For each mass eight shape/margin parameters and 10 enhancement texture features were obtained. For the lesions presenting as nonmass-like enhancement, only the texture parameters were obtained. An artificial neural network (ANN) was used to build the diagnostic model.
For lesions presenting as mass, the four selected morphological features could reach an area under the ROC curve (AUC) of 0.87 in differentiating between malignant and benign lesions. The kinetic parameter (k(ep)) analysed from the hot spot of the tumour reached a comparable AUC of 0.88. The combined morphological and kinetic features improved the AUC to 0.93, with a sensitivity of 0.97 and a specificity of 0.80. For lesions presenting as non-mass-like enhancement, four texture features were selected by the ANN and achieved an AUC of 0.76. The kinetic parameter k(ep) from the hot spot only achieved an AUC of 0.59, with a low added diagnostic value.
The results suggest that the quantitative diagnostic features can be used for developing automated breast CAD (computer-aided diagnosis) for mass lesions to achieve a high diagnostic performance, but more advanced algorithms are needed for diagnosis of lesions presenting as non-mass-like enhancement.
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ABSTRACT: A short-term cost criterion is introduced to model the productivity of an M/G/1 queuing/production system; the cost is a weighted sum of penalties associated with the work rate control, penalties associated with part waiting time, and penalties on the increase of parts in the queue, assessed during the time required to serve a single part. The distribution of the service time is of general form, parameterized by the work rate (the control variable). The decision epochs for the optimal control policy are restricted to the times when service is initiated for a part. The major advantages of this formulation are generality and mathematical tractability of the optimal solution. A simple nonlinear search routine is needed to determine the optimal work rate. For the special case of an exponential service time distribution and the special case where service is modeled by a diffusion-threshold process, analytical expressions for the optimal control policy in terms of the queue length are obtained
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ABSTRACT: The objective of this study is to compare mammography with magnetic resonance mammography (MRM) in the diagnosis of histopathologically verified subtypes of ductal carcinoma in situ (DCIS).
All patients with verified pure DCIS lesions (no signs of invasion or microinvasion) after surgery were identified between 2004 and 2006. Selection criteria were performed mammography and MRM at our institute prior to surgery resulting in a cohort of 33 patients (mean patient age, 60 years; mean lesion size, 15 mm).
Magnetic resonance mammography enabled identification of DCIS in 29 of 33 patients with histopathologically verified pure DCIS (7 G1, 13 G2, and 9 G3 subtypes), giving an overall sensitivity of 87.9% for this patient cohort. Four DCIS lesions (two G1 and two G2) up to 5 mm diameter or smaller were not detected by MRM. In mammography, 21 of the 33 patients revealed suspicious outcome (including all lesions not detected by MRM), demonstrating an overall sensitivity of 63.6%. The remaining 12 mammographically occult DCIS lesions (three G1 subtypes, four G2 subtypes, five G3 subtypes) were all identified in MRM.
Magnetic resonance mammography can diagnose mammographically visible and also occult DCIS lesions without microcalcifications. Only small DCIS foci with microcalcifications could additionally be verified by mammography supposing MRM as a diagnostic approach.
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