Ulrich Bick

Contralateral Breast Cancer Risk in BRCA1 and BRCA2 Mutation Carriers

PURPOSE To estimate the risk for contralateral breast cancer in members of BRCA1- and BRCA2-positive families and to determine predictive risk factors. PATIENTS AND METHODS A retrospective, multicenter, cohort study was performed from 1996 until 2008 and comprised 2,020 women with unilateral breast cancer (index patients, n = 978; relatives, n = 1.42) from 978 families who had a BRCA1 or BRCA2 mutation. Cox regression analysis was applied to assess the association of age at first breast cancer with time from first to contralateral breast cancer, stratified by the affected BRCA gene. RESULTS The cumulative risk for contralateral breast cancer 25 years after first breast cancer was 47.4% (95% CI, 38.8% to 56.0%) for patients from families with BRCA1 or BRCA2 mutations. Members of families with BRCA1 mutations had a 1.6-fold (95% CI, 1.2-fold to 2.3-fold) higher risk of contralateral breast cancer than members of families with BRCA2 mutations. Younger age at first breast cancer was associated with a significantly higher risk of contralateral breast cancer in patients with BRCA1 mutation, and a trend was observed in patients with BRCA2 mutation. After 25 years, 62.9% (95% CI, 50.4% to 75.4%) of patients with BRCA1 mutation who were younger than 40 years of age at first breast cancer developed contralateral breast cancer, compared with only 19.6% (95% CI, 5.3% to 33.9%) of those who were older than 50 years of age at first breast cancer. CONCLUSION Contralateral breast cancer risk depends on age at first breast cancer and on the affected BRCA gene, and this risk should be considered in treatment planning.

Volumetric texture analysis of breast lesions on contrast‐enhanced magnetic resonance images

Automated image analysis aims to extract relevant information from contrast‐enhanced magnetic resonance images (CE‐MRI) of the breast and improve the accuracy and consistency of image interpretation. In this work, we extend the traditional 2D gray‐level co‐occurrence matrix (GLCM) method to investigate a volumetric texture analysis approach and apply it for the characterization of breast MR lesions. Our database of breast MR images was obtained using a T1‐weighted 3D spoiled gradient echo sequence and consists of 121 biopsy‐proven lesions (77 malignant and 44 benign). A fuzzy c‐means clustering (FCM) based method is employed to automatically segment 3D breast lesions on CE‐MR images. For each 3D lesion, a nondirectional GLCM is then computed on the first postcontrast frame by summing 13 directional GLCMs. Texture features are extracted from the nondirectional GLCMs and the performance of each texture feature in the task of distinguishing between malignant and benign breast lesions is assessed by receiver operating characteristics (ROC) analysis. Our results show that the classification performance of volumetric texture features is significantly better than that based on 2D analysis. Our investigations of the effects of various of parameters on the diagnostic accuracy provided means for the optimal use of the approach. Magn Reson Med 58:562–571, 2007.

Automatic identification and classification of characteristic kinetic curves of breast lesions on DCE‐MRI

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) of the breast is being used increasingly in the detection and diagnosis of breast cancer as a complementary modality to mammography and sonography. Although the potential diagnostic value of kinetic curves in DCE-MRI is established, the method for generating kinetic curves is not standardized. The inherent reason that curve identification is needed is that the uptake of contrast agent in a breast lesion is often heterogeneous, especially in malignant lesions. It is accepted that manual region of interest selection in 4D breast magnetic resonance (MR) images to generate the kinetic curve is a time-consuming process and suffers from significant inter- and intraobserver variability. We investigated and developed a fuzzy c-means (FCM) clustering-based technique for automatically identifying characteristic kinetic curves from breast lesions in DCE-MRI of the breast. Dynamic contrast-enhanced MR images were obtained using a T1-weighted 3D spoiled gradient echo sequence with Gd-DTPA dose of 0.2 mmol/kg and temporal resolution of 69 s. FCM clustering was applied to automatically partition the signal-time curves in a segmented 3D breast lesion into a number of classes (i.e., prototypic curves). The prototypic curve with the highest initial enhancement was selected as the representative characteristic kinetic curve (CKC) of the lesion. Four features were then extracted from each characteristic kinetic curve to depict the maximum contrast enhancement, time to peak, uptake rate, and washout rate of the lesion kinetics. The performance of the kinetic features in the task of distinguishing between benign and malignant lesions was assessed by receiver operating characteristic analysis. With a database of 121 breast lesions (77 malignant and 44 benign cases), the classification performance of the FCM-identified CKCs was found to be better than that from the curves obtained by averaging over the entire lesion and similar to kinetic curves generated from regions drawn within the lesion by a radiologist experienced in breast MRI.

Tomosynthesis and contrast-enhanced digital mammography: recent advances in digital mammography

Digital mammography is more and more replacing conventional mammography. Initial concerns about an inferior image quality of digital mammography have been largely overcome and recent studies even show digital mammography to be superior in women with dense breasts, while at the same time reducing radiation exposure. Nevertheless, an important limitation of digital mammography remains: namely, the fact that summation may obscure lesions in dense breast tissue. However, digital mammography offers the option of so-called advanced applications, and two of these, contrast-enhanced mammography and tomosynthesis, are promising candidates for improving the detection of breast lesions otherwise obscured by the summation of dense tissue. Two techniques of contrast-enhanced mammography are available: temporal subtraction of images acquired before and after contrast administration and the so-called dual-energy technique, which means that pairs of low/high-energy images acquired after contrast administration are subtracted. Tomosynthesis on the other hand provides three-dimensional information on the breast. The images are acquired with different angulations of the X-ray tube while the object or detector is static. Various reconstruction algorithms can then be applied to the set of typically nine to 28 source images to reconstruct 1-mm slices with a reduced risk of obscuring pathology. Combinations of both advanced applications have only been investigated in individual experimental studies; more advanced software algorithms and CAD systems are still in their infancy and have only undergone preliminary clinical evaluation.

Evaluation of contrast-enhanced digital mammography.

PURPOSE The goal of this prospective study was to evaluate the possible diagnostic benefits of contrast-enhanced digital mammography (CEDM) over conventional mammography. MATERIALS AND METHODS Our analysis included data from 70 patients with a total of 80 lesions (30 malignant and 50 benign). A series of contrast-enhanced images was acquired from each patient using a modified imaging system (GE Senographe 2000D with copper filter) suitable for displaying iodine contrast medium. After the mask image had been taken, the contrast medium was administered using a dosage of 1ml/kg body weight at a rate of 4ml/s. Three contrast-enhanced images in the cranio-caudal projection plane were then captured at intervals of 60s. The mask image was logarithmically subtracted from the contrast-enhanced images. We performed a ROC analysis of diagnostic quality with three readers. RESULTS On average, 5.66 more malignant lesions were detected with the addition of digital dynamic contrast mammography versus conventional mammography alone. The sensitivity was increased from an average of 0.43 in conventional mammography to an average of 0.62 with contrast mammography. Even in dense breast parenchyma, the sensitivity increased from an average of 0.35-0.59. In the multi-reader-ROC analyses of all readers, the differences in the AUC with p=0.02 (BI-RADS) proved statistically significant in all cases. The Wilcoxon test showed that Readers I and II primarily used the CEDM to upgrade enhancing lesions to a higher BI-RADS category or a higher probability of malignancy. These two readers benefited most from the CEDM in the ROC analysis. CONCLUSION Overall, we conclude that the addition of dynamic digital subtraction mammography to conventional mammography can significantly improve diagnostic quality. The increased sensitivity is particularly pronounced in the case of dense breast tissue.

The risk of contralateral breast cancer in patients from BRCA1/2 negative high risk families as compared to patients from BRCA1 or BRCA2 positive families: a retrospective cohort study

IntroductionWhile it has been reported that the risk of contralateral breast cancer in patients from BRCA1 or BRCA2 positive families is elevated, little is known about contralateral breast cancer risk in patients from high risk families that tested negative for BRCA1/2 mutations.MethodsA retrospective, multicenter cohort study was performed from 1996 to 2011 and comprised 6,235 women with unilateral breast cancer from 6,230 high risk families that had tested positive for BRCA1 (n = 1,154) or BRCA2 (n = 575) mutations or tested negative (n = 4,501). Cumulative contralateral breast cancer risks were calculated using the Kaplan-Meier product-limit method and were compared between groups using the log-rank test. Cox regression analysis was applied to assess the impact of the age at first breast cancer and the familial history stratified by mutation status.ResultsThe cumulative risk of contralateral breast cancer 25 years after first breast cancer was 44.1% (95%CI, 37.6% to 50.6%) for patients from BRCA1 positive families, 33.5% (95%CI, 22.4% to 44.7%) for patients from BRCA2 positive families and 17.2% (95%CI, 14.5% to 19.9%) for patients from families that tested negative for BRCA1/2 mutations. Younger age at first breast cancer was associated with a higher risk of contralateral breast cancer. For women who had their first breast cancer before the age of 40 years, the cumulative risk of contralateral breast cancer after 25 years was 55.1% for BRCA1, 38.4% for BRCA2, and 28.4% for patients from BRCA1/2 negative families. If the first breast cancer was diagnosed at the age of 50 or later, 25-year cumulative risks were 21.6% for BRCA1, 15.5% for BRCA2, and 12.9% for BRCA1/2 negative families.ConclusionsContralateral breast cancer risk in patients from high risk families that tested negative for BRCA1/2 mutations is similar to the risk in patients with sporadic breast cancer. Thus, the mutation status should guide decision making for contralateral mastectomy.

PACS: the silent revolution.

Abstract. More than 15 years ago the idea of a Picture Archiving and Communication System (PACS) and a filmless hospital was created. In a PACS environment images are acquired, read, communicated and stored digitally. After many years of unsuccessful attempts and prototype installations, the necessary hardware components for a successful PACS installation are now readily available. However, software development is still lagging behind. Only very recently, software developers have realized that it is not sufficient for PACS software to store, communicate and display images, but that PACS software should effectively support the radiologist in the task of interpreting and communicating imaging findings through context-dependent default display arrangements, work-flow management, radiological and hospital information systems integration, and computer-assisted diagnosis. This review examines hard- and software requirements for efficient PACS operation, analyses costs and benefits, and discusses future developments.

Detection and classification of contrast-enhancing masses by a fully automatic computer-assisted diagnosis system for breast MRI

To evaluate a fully automatic computer‐assisted diagnosis (CAD) method for breast magnetic resonance imaging (MRI), which considered dynamic as well as morphologic parameters and linked those to descriptions laid down in the Breast Imaging Reporting and Data System (BI‐RADS) MRI atlas.

Breast Cancer in Young Women After Treatment for Hodgkin’s Disease During Childhood or Adolescence: An Observational Study With up to 33-Year Follow-up

BACKGROUND The treatment of Hodgkins disease (HD; also called Hodgkins lymphoma) in children and adolescents with radiotherapy and chemotherapy leads to high survival rates but has a number of late effects. The most serious one is the development of a secondary malignant tumor, usually in the field that was irradiated. In women, breast cancer can arise in this way. METHOD Data on the occurrence of secondary breast cancer (sBC) were collected from 590 women who were treated in five consecutive pediatric HD treatment studies in the years 1978-1995 and then re-evaluated in a late follow-up study after a median interval of 17.8 years (maximum, 33.7 years). Information was obtained from 1999 onward by written inquiry to the participants and their treating physicians. The cumulative incidence of sBC was calculated by the Gooley method. RESULTS By July 2012, sBC had been diagnosed in 26 of 590 female HD patients; the breast cancer was in the irradiated field in 25 of these 26 patients. Their age at the time of treatment for HD was 9.9 to 16.2 years (the pubertal phase), and sBC was discovered with a median latency of 20.7 years after HD treatment (shortest latency, 14.3 years) and at a median age of 35.3 years (youngest age, 26.8 years). The radiation dose to the supradiaphragmatic fields ranged from 20 to 45 Gy. The cumulative incidence for sBC 30 years after treatment for HD was 19% (95% confidence interval, 12% to 29%). For women aged 25 to 45 in this series, the frequency of breast cancer was 24 times as high as in the corresponding normal population. CONCLUSION Women who were treated for HD in childhood or adolescence have an increased risk of developing breast cancer as young adults. The risk is associated with prior radiotherapy and with the age at which it was administered (the pubertal phase). Because of these findings, a structured breast cancer screening project for this high-risk group has been initiated in collaboration with the German Consortium for Hereditary Breast and Ovarian Cancer (Deutsches Konsortium für familiären Brust- und Eierstockkrebs).

Near-infrared laser computed tomography of the breast first clinical experience.

RATIONALE AND OBJECTIVES The purpose of the present study was to evaluate a near-infrared (NIR) laser breast imaging system (Computed Tomography Laser Mammography [CTLM]) as an adjunct to mammography by means of receiver-operating characteristic (ROC) analysis. The NIR technique used in this study is based on the absorption of NIR light by hemoglobin. Malignant tumors can be detected by imaging their neovascularization. MATERIALS AND METHODS Eighty-two patients were examined by both CTLM and mammography. Seventy-nine of the 82 patients underwent biopsies, and three patients had 2-year follow up. Three-dimensional scans were acquired with an NIR laser computed tomographic scanner (the CTLM system) at a slice thickness of 4 mm. Mammograms were analyzed alone and together with CTLM images. RESULTS Histology revealed 37 benign and 42 malignant lesions. For the combination of mammography and CTLM, the area under the ROC curve was significantly larger than for mammography alone. In addition, it was shown that the difference in area under the ROC curve between the combination of both methods and mammography alone was considerably larger for dense breasts than for radiolucent breasts, although these differences were not statistically significant. CONCLUSION CTLM, used as an adjunct, may serve as a feasible tool to improve the diagnostic capabilities of mammography.