BACKGROUNDTumor perfusion through the microvascular network can be imaged noninvasively by dynamic contrast‐enhanced magnetic resonance imaging (DCE‐MRI). The objective of the current study was to quantify the microvascular perfusion parameters in various human breast lesions and to determine whether they varied between benign lesions and malignancy and whether they were altered with increased invasiveness.METHODSPerfusion parameters in 22 benign fibrocystic changes, 15 ductal carcinomas in situ (DCIS), 30 infiltrating ductal carcinomas (IDC), and 22 fibroadenomas were measured using high‐resolution DCE‐MRI. Pixel‐by‐pixel image analysis yielded parametric images of two perfusion indicators: the influx transcapillary transfer constant (ktrans) and the efflux transcapillary rate constant (kep). Correlations of lesion type and perfusion parameters were calculated using Spearman correlation. Logistic regression analysis evaluated the best predictors of the kinetic parameters that differentiate between IDC and benign lesions.RESULTSThe perfusion parameters exhibited a progressive increase from benign fibrocystic changes to DCIS and IDC, with a significant correlation between lesion type and the parameters' values (range of correlation coefficients, 0.56–0.76; P < 0.0001). In addition, ktrans increased from low‐grade DCIS to high‐grade DCIS. Fibroadenomas were characterized uniquely by high ktrans but low kep. Stepwise logistic regression selected ktrans as the best predictor for distinguishing benign fibrocystic changes from IDC, yielding 93% sensitivity and 96% specificity.CONCLUSIONSThe microvascular perfusion parameters in breast lesions were elevated with invasiveness. Quantification of these parameters using high‐resolution DCE‐MRI was helpful for differentiating between breast lesions and should improve breast carcinoma diagnosis. Cancer 2005. © 2005 American Cancer Society.

The data appear to support the use of a quantitative D-dimer assay as a first-line test in evaluation for pulmonary embolism when the clinical probability of the presence of pulmonary embolism is low or intermediate. The sensitivity and negative predictive value were 100% for these cases. More than 26% of CT angiographic examinations might have been avoided if the D-dimer assay had been used as a first-line test in the care of patients at low or intermediate risk. Because of the small sample size, the D-dimer assay is not recommended as a first-line test in the evaluation of patients at high risk.

Purpose: To investigate a fast, objective, and standardized method for analyzing breast dynamic contrastenhanced magnetic resonance imaging (DCE-MRI) applying principal component analysis (PCA) adjusted with a model-based method.Materials and Methods: 3D gradient-echo DCE breast images of 31 malignant and 38 benign lesions, recorded on a 1.5T scanner, were retrospectively analyzed by PCA and by the model-based three-timepoints (3TP) method.Results: Intensity-scaled (IS) and enhancement-scaled (ES) datasets were reduced by PCA yielding a first IS-eigenvector that captured the signal variation between fat and fibroglandular tissue; two IS-eigenvectors and the two first ES-eigenvectors captured contrast-enhanced changes, whereas the remaining eigenvectors captured predominantly noise changes. Rotation of the two contrast-related eigenvectors led to a high congruence between the projection coefficients and the 3TP parameters. The ES-eigenvectors and the rotation angle were highly reproducible across malignant lesions, enabling calculation of a general rotated eigenvector base. Receiver operating characteristic (ROC) curve analysis of the projection coefficients of the two eigenvectors indicated high sensitivity of the first rotated eigenvector to detect lesions (area under the curve [AUC] > 0.97) and of the second rotated eigenvector to differentiate malignancy from benignancy (AUC ¼ 0.87). Conclusion:PCA adjusted with a model-based method provided a fast and objective computer-aided diagnostic tool for breast DCE-MRI.

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To reassess the minimum number of specimens required for an accurate diagnosis compared to the standard acquisition of five specimens. A total of 190 consecutive breast mass biopsies were performed using a 14-gauge core biopsy needle under ultrasound guidance. Two to six specimens were obtained from each mass and placed in sequential containers. Each specimen was evaluated by a pathologist in the order it was obtained and was labeled as "diagnostic' or 'non-diagnostic'. During the biopsy procedure, the radiologist indicated after which number biopsy he was confident that an adequate diagnostic specimen had been obtained. This was based upon real-time visualization of the needle passing through the lesion and whether the specimen sank or floated in formalin. These observations were compared with the pathologic diagnostic yield according to specimen number. Fifty-eight lesions (30.5%) were malignant, four (2.1%) were atypical, and 128 (67.4%) were benign. Histologic diagnosis was obtained after the first specimen in 157 (82.6%) lesions, the second specimen in 172 (90.5%) lesions, the third specimen in 186 (97.9%) lesions, the fourth specimen in 188 (98.9%) lesions, and the fifth specimen in 190 (100%) lesions. A histologic diagnosis was made in 90% of the malignant lesions after the first biopsy pass, 95% after the second pass, 98% after the third pass, and 100% after the fourth and fifth passes. Nine (4.7%) lesions showed discrepancy between the radiologist's confidence of diagnosis and pathologic diagnostic yield. Of these lesions, seven were benign and two were malignant. A diagnostic yield of 95% was obtained based on operator estimate of the minimum number of required core biopsies. A high diagnostic yield of 98% was achieved after three biopsy passes and 100% after five passes.