Retrospektive Analyse eines computerassistierten Detektions-Systems (CAD) in der digitalen Vollfeldmammographie in Abhängigkeit von der Histologie

[Quantitative parametric analysis of contrast-enhanced lesions in dynamic MR mammography]

PURPOSE

The aim of the study was an evaluation of the quantitative parametric analysis of contrast-enhanced lesions in dynamic MR mammography.

MATERIAL AND METHODS

In 137 patients, 183 contrast-enhanced lesions were identified in dynamic MR mammography. In 82 lesions histopathology was performed and in 101 lesions follow-up MR mammography was carried out. The contrast kinetics of lesions was analyzed quantitatively, on a pixel-by-pixel basis. The initial signal enhancement was coded by color intensity (bright, medium, dark), the post-initial signal enhancement was coded by color hue (blue, green, red). ROC analysis and logistic regression were performed.

RESULTS

Malignant lesions showed a significantly higher number of bright red, medium red and dark red, bright green and medium green pixels than benign lesions. Benign lesions showed a significantly higher number of bright blue, medium blue and dark blue pixels than malignant lesions. The highest areas under the ROC curves (AUC) were found for medium red (AUC = 0.782) and medium green pixels (AUC = 0.733). A regression model with medium red and medium green pixels allows diagnosis of malignant lesions with a sensitivity of 60.7% and a specificity of 83.6%.

CONCLUSIONS

The quantification of contrast-enhanced lesions allows objective analysis of the signal intensities in malignant and benign lesions. Therefore, this method might increase the specificity of MR mammography. Further developments are necessary before this method can be used for routine analysis of contrast-enhancing lesions in MR mammography.

Quantitative 2- and 3-dimensional analysis of pharmacokinetic model-derived variables for breast lesions in dynamic, contrast-enhanced MR mammography

PURPOSE

2- and 3-dimensional evaluation of quantitative pharmacokinetic parameters derived from the Tofts model modeling dynamic contrast enhancement of lesions in MR mammography.

MATERIALS AND METHODS

In 95 patients, MR mammography revealed 127 suspicious lesions. The initial rate of enhancement was coded by color intensity, the post-initial enhancement change is coded by color hue. 2D and 3D analysis of distribution of color hue and intensity, vascular permeability and extracellular volume were performed.

RESULTS

In 2D, malignant lesions showed significant higher number of bright red, medium red, dark red, bright green, medium green, dark green and bright blue pixels than benign lesions. In 3D, statistical significant differences between malignant and benign lesions was found for all this parameters. Vascular permeability was significant higher in malignant lesions than in benign lesions. Regression model using the 3D data found that the best discriminator between malignant and benign lesions was combined number of voxels and medium green pixels, with a sensitivity of 79.4% and a specificity of 83.1%.

CONCLUSIONS

Quantitative analysis of pharmacokinetic variables of contrast kinetics showed significant differences between malignant and benign lesions. 3D analysis showed superior diagnostic differentiation between malignant and benign lesions than 2D analysis. The parametric analysis using a pharmacokinetic model allows objective analysis of contrast enhancement in breast lesions.

Real-time sonoelastography of the cervix: tissue elasticity of the normal and abnormal cervix

RATIONALE AND OBJECTIVES

First study to investigate the basic tissue elastic properties of the cervix in pre- and postmenopausal healthy women and to compare these normal findings with the results in a group of patients with focal pathology of the cervix.

MATERIALS AND METHODS

A total of 113 patients underwent transvaginal ultrasound, among them 24 with cervical pathology. The real-time elastography (Hitachi) information was color-coded and superimposed on the B-mode scan. The elastography images were analyzed by means of a software tool to identify thresholds for the colors red (soft), blue (hard), and green (medium hard), and the percentages of the three colors of the total area were determined. The results were correlated with age. In addition, scans were evaluated subjectively on an analogue scale from 1 (definitely normal) to 5 (definitely abnormal). Statistical analysis was performed using Anova, Wilcoxon's test, and Pearson's correlation.

RESULTS

Computer-assisted generation of the color spectrum showed green to be predominant in both the normal group (67+/-13 %) and in the group with cervical pathology (64+/-15 %) without a significant difference between both groups (p=>0.05). Significant differences (p<0.05) in the blue color spectrum (hard tissue) were found between the 13 cervical tumor patients (34+/-15 %) and the normal group (26+/-13 %) but not between the CIN patients and normal women (19+/-12 %) (p>0.05). Subjective tumor characterization also showed significant differences (p<0.05) among the groups and good correlation with the histologic diagnosis (r2=0.744). There were no significant changes in color distribution with patient age (p>0.05).

CONCLUSION

Computer-assisted and subjective evaluation of cervical elastography allows differentiation of malignancy from normal findings. CIN cannot be identified with this modality. Elastographically, cervical tissue is of medium hardness and does not change with age.