PURPOSE:The detectability with magnetic resonance mammography (MR-M) of non-invasive ductal carcinoma in situ (DCIS), its morphology, and patterns of contrast enhancement were studied. MATERIAL AND METHODS:A total of 849 MR-M examinations were performed in 741 patients using a dynamic, contrast-enhanced FLASH 3D sequence at 1.0 T. Surgical breast biopsies were obtained in 332 cases. Histological work-up confirmed 164 carcinomas, including 20 DCIS. RESULTS:Of 20 DCIS, 14 were correctly diagnosed by MR-M on the basis of focal increase of signal intensity. In two cases (10%), no increase of signal intensity was observed. In another three cases (15%), multifocal enhancement lead to a false-negative diagnosis. In one case (5%), DCIS was a random finding in a patient diagnosed and treated for adjacent phylloides tumour. The sensitivity of MR-M was 70%. 4 (20%) of the DCIS did not show microcalcifications at conventional mammography and were only detected at MR-M. The sensitivity of conventional mammography also amounted to 70%. However, the combination of both imaging methods increased sensitivity to 90%. CONCLUSION:Ductal carcinoma in situ is not reliably detectable by MR-mammography alone due to lack of a uniform pattern of enhancement.

UNLABELLED:Preceding studies have shown that a second independent reviewer of conventional mammographies increases the detection rate of features typical for malignancy by up to 15%.METHODS:In order to test a computer-aided diagnostic (CAD) system (ImageChecker, R2 Technology, USA) for the detection of pathologic criteria in conventional mammography, 96 mammographies were retrospectively evaluated using ImageChecker. Thirty-five of these mammographies had been diagnosed as not showing pathologies, and 61 had depicted histologically confirmed malignancy.RESULTS:Detecting 41 of 61 breast malignancies, ImageChecker showed a diagnostic sensitivity of 70.5%. All malignancies accompanied by microcalcifications were identified by ImageChecker, whereas 18 cases characterized by parenchymal opacity without microcalcifications were not marked. On the average, 1.95 markers per image were set, giving a total of 187 markers in this study. 63% of all markers showed normal tissue and were thus false positive.CONCLUSIONS:Pathologic parenchymal opacities in mammography are a well-known problem for all CAD systems in use. Despite this major drawback, even now ImageChecker can provide tremendous support in routine interpretation of conventional mammographies.

Purpose: The detectability with magnetic resonance mammography (MR-M) of non-invasive ductal carcinoma in situ (DCIS), its morphology, and patterns of contrast enhancement were studied. Material and methods: A total of 849 MR-M examinations were performed in 741 patients using a dynamic, contrast-enhanced FLASH 3D sequence at 1.0 T. Surgical breast biopsies were obtained in 332 cases. Histological work-up confirmed 164 carcinomas, including 20 DCIS. Results: Of 20 DCIS, 14 were correctly diagnosed by MR-M on the basis of focal increase of signal intensity. In two cases (10%), no increase of signal intensity was observed. In another three cases (15%), multifocal enhancement lead to a false-negative diagnosis. In one case (5%), DCIS was a random finding in a patient diagnosed and treated for adjacent phylloides tumour. The sensitivity of MR-M was 70%. 4 (20%) of the DCIS did not show microcalcifications at conventional mammography and were only detected at MR-M. The sensitivity of conventional mammography also amounted to 70%. However, the combination of both imaging methods increased sensitivity to 90%. Conclusion: Ductal carcinoma in situ is not reliably detectable by MR-mammography alone due to lack of a uniform pattern of enhancement.

A method for a three-dimensional surface reconstruction of the retina in the area of the papilla is presented. The surface reconstruction is based on a sequence of discrete gray-level images of the retina recorded by a scanning laser ophthalmoscope (SLO). The underlying assumption of the surface reconstruction algorithm developed here is that the depth information is also encoded in the brightness values of the single pixels in addition to the ordinary spatial 2D information. The brightness of an image position depends on the degree of reflection of a confocal laser beam. Only those surface structures located directly in the focus plane of the confocal laser beam produce a high response to the laser light. The displacements between the single images of a sequence are considered to be approximately linear and are corrected by applying the cepstrum technique. The depth is estimated from the volumetric representation of the image sequence by searching for the maximal value of the brightness within a computed depth profile, at every image position. In the resulting images, disturbances occurring during the recording cause incorrect local estimations of the depth. These local disturbances are corrected by applying specially developed surface improvement processes. The work is concluded with a comparison of several different approaches to reduce the noise and disturbances in SLO image data.

A method of a three-dimensional surface reconstruction of the retina in the area of the papilla is presented. The surface reconstruction is based on a sequence of discrete gray-level images of the retina recorded by a scanning laser ophthalmoscope (SLO). The underlying assumption of the developed surface reconstruction algorithm is that the depth information is also encoded in the brightness values of the single pixels beside the ordinary spatial 2D information. The brightness of an image position depends also on the degree of reflection of a confocal laser beam. Only these surface structures produce a high response of the focused laser light, which are located directly in the focus plane of the confocal laser beam. The occurring disparities between the single images of a sequence are considered to be approximately linear and are corrected by applying the cepstrum technique. The depth information is estimated out of the volumetric representation of the image sequence by searching the maximal value of the brightness within a computed depth profile at every image position. In the resulting range images disturbances which occur during the recording cause wrong local estimations of the depth information. These local disturbances are corrected by applying especially developed surface improvement processes. The work is completed by investigating several different approaches to reduce the noise and disturbances of SLO image data.