M. Meier-Meitinger

Characterizing mammographic images by using generic texture features

IntroductionAlthough mammographic density is an established risk factor for breast cancer, its use is limited in clinical practice because of a lack of automated and standardized measurement methods. The aims of this study were to evaluate a variety of automated texture features in mammograms as risk factors for breast cancer and to compare them with the percentage mammographic density (PMD) by using a case-control study design.MethodsA case-control study including 864 cases and 418 controls was analyzed automatically. Four hundred seventy features were explored as possible risk factors for breast cancer. These included statistical features, moment-based features, spectral-energy features, and form-based features. An elaborate variable selection process using logistic regression analyses was performed to identify those features that were associated with case-control status. In addition, PMD was assessed and included in the regression model.ResultsOf the 470 image-analysis features explored, 46 remained in the final logistic regression model. An area under the curve of 0.79, with an odds ratio per standard deviation change of 2.88 (95% CI, 2.28 to 3.65), was obtained with validation data. Adding the PMD did not improve the final model.ConclusionsUsing texture features to predict the risk of breast cancer appears feasible. PMD did not show any additional value in this study. With regard to the features assessed, most of the analysis tools appeared to reflect mammographic density, although some features did not correlate with PMD. It remains to be investigated in larger case-control studies whether these features can contribute to increased prediction accuracy.

Association of mammographic density with hormone receptors in invasive breast cancers: results from a case-only study.

For many breast cancer (BC) risk factors, there is growing evidence concerning molecular subtypes for which the risk factor is specific. With regard to mammographic density (MD), there are inconsistent data concerning its association with estrogen receptor (ER) and progesterone receptor (PR) expression. The aim of our study was to analyze the association between ER and PR expression and MD. In our case‐only study, data on BC risk factors, hormone receptor expression and MD were available for 2,410 patients with incident BC. MD was assessed as percent MD (PMD) using a semiautomated method by two readers for every patient. The association of ER/PR and PMD was studied with multifactorial analyses of covariance with PMD as the target variable and including well‐known factors that are also associated with MD, such as age, parity, use of hormone replacement therapy, and body mass index (BMI). In addition to the commonly known associations between PMD and age, parity, BMI and hormone replacement therapy, a significant inverse association was found between PMD and ER expression levels. Patients with ER‐negative tumors had an average PMD of 38%, whereas patients with high ER expression had a PMD of 35%. A statistical trend toward a positive association between PMD and PR expression was also seen. PMD appears to be inversely associated with ER expression and may correlate positively with PR expression. These effects were independent of other risk factors such as age, BMI, parity, and hormone replacement therapy, possibly suggesting other pathways that mediate this effect.

New diagnostic criteria in real-time elastography for the assessment of breast lesions.

PURPOSE Elastography is a new ultrasonographic method that has been examined as a diagnostic tool for breast lesions. This study was intended to create and define new elastographic criteria allowing assessment of whether breast lesions are malignant or benign. MATERIALS AND METHODS 217 patients with a total of 245 breast lesions of unknown malignancy underwent ultrasound examination. The new eSie Touch Elasticity Imaging technology (Siemens, Erlangen, Germany) was used with a 10-MHz linear transducer (Acuson Antares). Lesions were examined using B-mode and real-time elastography (RTE). Each lesion was histologically assessed by core biopsy. Five RTE characteristics were examined: elasticity proportion (EP), different location on RTE in comparison with B-mode (MV), different contrast patterns (SOS), dorsal lesion limitation visibility and different size on RTE in comparison with B-mode. RESULTS 54 malignant lesions (54 %) appeared inelastic, in contrast to the benign control group (34.5 %; P = 0.001). A completely elastic pattern was visible in 10 malignant (10 %) and 39 benign lesions (26.9 %). MV was identified in 23 cases, with 22 of the lesions being malignant and one benign. The SOS was negative in 89 malignant lesions (89 %) and positive in 100 benign lesions. The dorsal lesion limitation was visible on RTE without B-mode in 88 malignant lesions (88 %) and 27 benign lesions (18.6 %). The size was assessed as larger in 45 malignant lesions (45 %) and seven benign lesions (4.8 %). CONCLUSION SOS and a larger tumor size on RTE are specific characteristics of malignant breast lesions. EP, MV and distal mass border are further helpful signs to assess the malignancy of tumors.

Assessment of breast cancer tumour size using six different methods

ObjectivesTumour size estimates using mammography (MG), conventional ultrasound (US), compound imaging (CI) and real-time elastography (RTE) were compared with histopathological specimen sizes.MethodsThe largest diameters of 97 malignant breast lesions were measured. Two US and CI measurements were made: US1/CI1 (hypoechoic nucleus only) and US2/CI2 (hypoechoic nucleus plus hyperechoic halo). Measurements were compared with histopathological tumour sizes using linear regression and Bland–Altman plots.ResultsSize prediction was best with ultrasound (US/CI/RTE: R2 0.31–0.36); mammography was poorer (R2 = 0.19). The most accurate method was US2, while US1 and CI1 were poorest. Bland–Altman plots showed better size estimation with US2, CI2 and RTE, with low variation, while mammography showed greatest variability. Smaller tumours were better assessed than larger ones. CI2 and US2 performed best for ductal tumours and RTE for lobular cancers. Tumour size prediction accuracy did not correlate significantly with breast density, but on MG tumours were more difficult to detect in high-density tissue.ConclusionsThe size of ductal tumours is best predicted with US2 and CI2, while for lobular cancers RTE is best. Hyperechoic tumour surroundings should be included in US and CI measurements and RTE used as an additional technique in the clinical staging process.

Mammographic density is the main correlate of tumors detected on ultrasound but not on mammography.

Although mammography screening programs do not include ultrasound examinations, some diagnostic units do provide women with both mammography and ultrasonography. This article is concerned with estimating the risk of a breast cancer patient diagnosed in a hospital‐based mammography unit having a tumor that is visible on ultrasound but not on mammography. A total of 1,399 women with invasive breast cancer from a hospital‐based diagnostic mammography unit were included in this retrospective study. For inclusion, mammograms from the time of the primary diagnosis had to be available for computer‐assisted assessment of percentage mammographic density (PMD), as well as Breast Imaging Reporting and Data System (BIRADS) assessment of mammography. In addition, ultrasound findings were available for the complete cohort as part of routine diagnostic procedures, regardless of any patient or imaging characteristics. Logistic regression analyses were conducted to identify predictors of mammography failure, defined as BIRADS assessment 1 or 2. The probability that the visibility of a tumor might be masked at diagnosis was estimated using a regression model with the identified predictors. Tumors were only visible on ultrasound in 107 cases (7.6%). PMD was the strongest predictor for mammography failure, but age, body mass index and previous breast surgery also influenced the risk, independently of the PMD. Risk probabilities ranged from 1% for a defined low‐risk group up to 40% for a high‐risk group. These findings might help identify women who should be offered ultrasound examinations in addition to mammography.

Zukunft mammographiebasierter Bildgebung

Mammography is the central diagnostic method for clinical diagnostics of breast cancer and the breast cancer screening program. In the clinical routine complementary methods, such as ultrasound, tomosynthesis and optional magnetic resonance imaging (MRI) are already combined for the diagnostic procedure. Future developments will utilize investigative procedures either as a hybrid (combination of several different imaging modalities in one instrument) or as a fusion method (the technical fusion of two or more of these methods) to implement fusion imaging into diagnostic algorithms. For screening there are reasonable hypotheses to aim for studies that individualize the diagnostic process within the screening procedure. Individual breast cancer risk prediction and individualized knowledge about sensitivity and specificity for certain diagnostic methods could be tested. The clinical implementation of these algorithms is not yet in sight.ZusammenfassungDie Mammographie ist die zentrale diagnostische Methode der klinischen symptombezogenen Abklärung von Brusterkrankungen und des Brustkrebsscreenings. In der klinischen Diagnostik wird sie heute schon oft durch zusätzliche Untersuchungsmethoden wie dem Ultraschall, der Tomosynthese und ggf. auch der MRT-Bildgebung unterstützt. Zukünftige Entwicklungen gehen in die Richtung, dass diese Kombination aus 2 oder mehr Untersuchungsverfahren entweder in Hybrid- (Aufnahme mehrerer unterschiedlicher Bildmodalitäten in einem einzigen Gerät) oder in Fusionsmethoden (Zusammenführung und Registrierung von Bilddaten aus verschiedenen Modalitäten) technisch professionalisiert werden. Des Weiteren könnten an subgruppenbezogene Erkrankungsrisiken und individuelle Sensitivitäten und Spezifitäten angepasste Diagnostikkombinationen für eine Screeningdiagnostik Gegenstand künftiger Studien sein. Wir stellen die aktuellen Entwicklungen auf diesen Gebieten und deren momentane Relevanz für die klinische Praxis und Entwicklungspotenzial für die Zukunft dar.AbstractMammography is the central diagnostic method for clinical diagnostics of breast cancer and the breast cancer screening program. In the clinical routine complementary methods, such as ultrasound, tomosynthesis and optional magnetic resonance imaging (MRI) are already combined for the diagnostic procedure. Future developments will utilize investigative procedures either as a hybrid (combination of several different imaging modalities in one instrument) or as a fusion method (the technical fusion of two or more of these methods) to implement fusion imaging into diagnostic algorithms. For screening there are reasonable hypotheses to aim for studies that individualize the diagnostic process within the screening procedure. Individual breast cancer risk prediction and individualized knowledge about sensitivity and specificity for certain diagnostic methods could be tested. The clinical implementation of these algorithms is not yet in sight.

X-ray induced formation of γ-H2AX foci after full-field digital mammography and digital breast-tomosynthesis.

Purpose To determine in-vivo formation of x-ray induced γ-H2AX foci in systemic blood lymphocytes of patients undergoing full-field digital mammography (FFDM) and to estimate foci after FFDM and digital breast-tomosynthesis (DBT) using a biological phantom model. Materials and Methods The study complies with the Declaration of Helsinki and was performed following approval by the ethic committee of the University of Erlangen-Nuremberg. Written informed consent was obtained from every patient. For in-vivo tests, systemic blood lymphocytes were obtained from 20 patients before and after FFDM. In order to compare in-vivo post-exposure with pre-exposure foci levels, the Wilcoxon matched pairs test was used. For in-vitro experiments, isolated blood lymphocytes from healthy volunteers were irradiated at skin and glandular level of a porcine breast using FFDM and DBT. Cells were stained against the phosphorylated histone variant γ-H2AX, and foci representing distinct DNA damages were quantified. Results Median in-vivo foci level/cell was 0.086 (range 0.067–0.116) before and 0.094 (0.076–0.126) after FFDM (p = 0.0004). In the in-vitro model, the median x-ray induced foci level/cell after FFDM was 0.120 (range 0.086–0.140) at skin level and 0.035 (range 0.030–0.050) at glandular level. After DBT, the median x-ray induced foci level/cell was 0.061 (range 0.040–0.081) at skin level and 0.015 (range 0.006–0.020) at glandular level. Conclusion In patients, mammography induces a slight but significant increase of γ-H2AX foci in systemic blood lymphocytes. The introduced biological phantom model is suitable for the estimation of x-ray induced DNA damages in breast tissue in different breast imaging techniques.

Correlates of mammographic density in B-mode ultrasound and real time elastography.

The aim of our study involved the assessment of B-mode imaging and elastography with regard to their ability to predict mammographic density (MD) without X-rays. Women, who underwent routine mammography, were prospectively examined with additional B-mode ultrasound and elastography. MD was assessed quantitatively with a computer-assisted method (Madena). The B-mode and elastography images were assessed by histograms with equally sized gray-level intervals. Regression models were built and cross validated to examine the ability to predict MD. The results of this study showed that B-mode imaging and elastography were able to predict MD. B-mode seemed to give a more accurate prediction. R2 for B-mode image and elastography were 0.67 and 0.44, respectively. Areas in the B-mode images that correlated with mammographic dense areas were either dark gray or of intermediate gray levels. Concerning elastography only the gray levels that represent extremely stiff tissue correlated positively with MD. In conclusion, ultrasound seems to be able to predict MD. Easy and cheap utilization of regular breast ultrasound machines encourages the use of ultrasound in larger case–control studies to validate this method as a breast cancer risk predictor. Furthermore, the application of ultrasound for breast tissue characterization could enable comprehensive research concerning breast cancer risk and breast density in young and pregnant women.

CT-Guided Biopsies of Pancreatic Lesions: Impact of Contrast Application Prior to versus Following Needle Placement

RATIONALE AND OBJECTIVES Pancreatic lesions are frequently detected in pancreatic phase only, which may lead to false negative findings in CT-guided biopsies. We evaluated the accuracy and complication rate of CT guided biopsies of pancreatic lesions with i.v.-contrast application following needle placement in comparison to biopsy after contrast enhanced CT. MATERIALS AND METHODS In 30 patients planning and needle placement was performed on the basis of a native planning CT and prior diagnostic CT or MRT. After needle placement contrast enhanced CT was performed to confirm needle course and adjusted if necessary (group 1). In 30 additional patients biopsy was planned based on contrast enhanced CT and needle was placed in the lesion. Control scans confirmed correct needle position (group 2). An 18G coaxial system was used for both groups. Statistical analysis was performed with Students t and Fishers exact test for comparison of lesion size, location as well as accuracy and complication rates. RESULTS Mean lesion size was significantly smaller in group 1 (31 mm vs. 39 mm; p = 0.02). Diagnostic accuracy and sensitivity for malignancy in group 1 was 93% and 92% versus 80% and 77% in group 2. Complications related to the procedure, i.e. haematoma (n = 5, group 1/n = 2, group 2) and pain (n = 0, group 1/n = 2, group 2) did not statistically differ. CONCLUSION CT-guided biopsy of pancreatic lesions with i.v.-contrast application following needle placement is a reliable method and provides superior accuracy compared to biopsies performed after contrast enhanced planning CT.

[Future of mammography-based imaging].

Mammography is the central diagnostic method for clinical diagnostics of breast cancer and the breast cancer screening program. In the clinical routine complementary methods, such as ultrasound, tomosynthesis and optional magnetic resonance imaging (MRI) are already combined for the diagnostic procedure. Future developments will utilize investigative procedures either as a hybrid (combination of several different imaging modalities in one instrument) or as a fusion method (the technical fusion of two or more of these methods) to implement fusion imaging into diagnostic algorithms. For screening there are reasonable hypotheses to aim for studies that individualize the diagnostic process within the screening procedure. Individual breast cancer risk prediction and individualized knowledge about sensitivity and specificity for certain diagnostic methods could be tested. The clinical implementation of these algorithms is not yet in sight.ZusammenfassungDie Mammographie ist die zentrale diagnostische Methode der klinischen symptombezogenen Abklärung von Brusterkrankungen und des Brustkrebsscreenings. In der klinischen Diagnostik wird sie heute schon oft durch zusätzliche Untersuchungsmethoden wie dem Ultraschall, der Tomosynthese und ggf. auch der MRT-Bildgebung unterstützt. Zukünftige Entwicklungen gehen in die Richtung, dass diese Kombination aus 2 oder mehr Untersuchungsverfahren entweder in Hybrid- (Aufnahme mehrerer unterschiedlicher Bildmodalitäten in einem einzigen Gerät) oder in Fusionsmethoden (Zusammenführung und Registrierung von Bilddaten aus verschiedenen Modalitäten) technisch professionalisiert werden. Des Weiteren könnten an subgruppenbezogene Erkrankungsrisiken und individuelle Sensitivitäten und Spezifitäten angepasste Diagnostikkombinationen für eine Screeningdiagnostik Gegenstand künftiger Studien sein. Wir stellen die aktuellen Entwicklungen auf diesen Gebieten und deren momentane Relevanz für die klinische Praxis und Entwicklungspotenzial für die Zukunft dar.AbstractMammography is the central diagnostic method for clinical diagnostics of breast cancer and the breast cancer screening program. In the clinical routine complementary methods, such as ultrasound, tomosynthesis and optional magnetic resonance imaging (MRI) are already combined for the diagnostic procedure. Future developments will utilize investigative procedures either as a hybrid (combination of several different imaging modalities in one instrument) or as a fusion method (the technical fusion of two or more of these methods) to implement fusion imaging into diagnostic algorithms. For screening there are reasonable hypotheses to aim for studies that individualize the diagnostic process within the screening procedure. Individual breast cancer risk prediction and individualized knowledge about sensitivity and specificity for certain diagnostic methods could be tested. The clinical implementation of these algorithms is not yet in sight.