Federica Zanca

Two-View and Single-View Tomosynthesis versus Full-Field Digital Mammography: High-Resolution X-Ray Imaging Observer Study

PURPOSE To compare the diagnostic accuracy of two-dimensional (2D) full-field digital mammography with that of two-view (mediolateral and craniocaudal) and single-view (mediolateral oblique) tomosynthesis in an observer study involving two institutions. MATERIALS AND METHODS Ethical committee approval was obtained. All participating women gave informed consent. Two hundred twenty women (mean age, 56.3; range, 40-80 years) with breast density of 2-4 according to American College of Radiology criteria were recruited between November 2008 and September 2009 and underwent standard treatment plus tomosynthesis with a prototype photon-counting machine. After exclusion criteria were met, this resulted in a final test set of 130 women. Ten accredited readers classified the 130 cases (40 cancers, 24 benign lesions, and 66 normal images) using 2D mammography and two-view tomosynthesis. Another 10 readers reviewed the same cases using 2D mammography but single-view tomosynthesis. The multireader, multicase receiver operating characteristic (ROC) method was applied. The significance of the observed difference in accuracy between 2D mammography and tomosynthesis was calculated. RESULTS For diagnostic accuracy, 2D mammography performed significantly worse than two-view tomosynthesis (average area under ROC curve [AUC] = 0.772 for 2D, AUC = 0.851 for tomosynthesis, P = .021). Significant differences were found for both masses and microcalcification (P = .037 and .049). The difference in AUC between the two modalities of -0.110 was significant (P = .03) only for the five readers with the least experience (<10 years of reading); with AUC of -0.047 for the five readers with 10 years or more experience (P = .25). No significant difference (P = .79) in reader performance was seen when 2D mammography (average AUC = 0.774) was compared with single-view tomosynthesis (average AUC = 0.775). CONCLUSION Two-view tomosynthesis outperforms 2D mammography but only for readers with the least experience. The benefits were seen for both masses and microcalcification. No differences in classification accuracy was seen between and 2D mammography and single-view tomosynthesis.

Evaluation of clinical image processing algorithms used in digital mammography

Screening is the only proven approach to reduce the mortality of breast cancer, but significant numbers of breast cancers remain undetected even when all quality assurance guidelines are implemented. With the increasing adoption of digital mammography systems, image processing may be a key factor in the imaging chain. Although to our knowledge statistically significant effects of manufacturer-recommended image processings have not been previously demonstrated, the subjective experience of our radiologists, that the apparent image quality can vary considerably between different algorithms, motivated this study. This article addresses the impact of five such algorithms on the detection of clusters of microcalcifications. A database of unprocessed (raw) images of 200 normal digital mammograms, acquired with the Siemens Novation DR, was collected retrospectively. Realistic simulated microcalcification clusters were inserted in half of the unprocessed images. All unprocessed images were subsequently processed with five manufacturer-recommended image processing algorithms (Agfa Musica 1, IMS Raffaello Mammo 1.2, Sectra Mamea AB Sigmoid, Siemens OPVIEW v2, and Siemens OPVIEW v1). Four breast imaging radiologists were asked to locate and score the clusters in each image on a five point rating scale. The free-response data were analyzed by the jackknife free-response receiver operating characteristic (JAFROC) method and, for comparison, also with the receiver operating characteristic (ROC) method. JAFROC analysis revealed highly significant differences between the image processings (F = 8.51, p < 0.0001), suggesting that image processing strongly impacts the detectability of clusters. Siemens OPVIEW2 and Siemens OPVIEW1 yielded the highest and lowest performances, respectively. ROC analysis of the data also revealed significant differences between the processing but at lower significance (F = 3.47, p = 0.0305) than JAFROC. Both statistical analysis methods revealed that the same six pairs of modalities were significantly different, but the JAFROC confidence intervals were about 32% smaller than ROC confidence intervals. This study shows that image processing has a significant impact on the detection of microcalcifications in digital mammograms. Objective measurements, such as described here, should be used by the manufacturers to select the optimal image processing algorithm.

An improved method for simulating microcalcifications in digital mammograms

The assessment of the performance of a digital mammography system requires an observer study with a relatively large number of cases with known truth which is often difficult to assemble. Several investigators have developed methods for generating hybrid abnormal images containing simulated microcalcifications. This article addresses some of the limitations of earlier methods. The new method is based on digital images of needle biopsy specimens. Since the specimens are imaged separately from the breast, the microcalcification attenuation profile scan is deduced without the effects of over and underlying tissues. The resulting templates are normalized for image acquisition specific parameters and reprocessed to simulate microcalcifications appropriate to other imaging systems, with different x-ray, detector and image processing parameters than the original acquisition system. This capability is not shared by previous simulation methods that have relied on extracting microcalcifications from breast images. The method was validated by five experienced mammographers who compared 59 pairs of simulated and real microcalcifications in a two-alternative forced choice task designed to test if they could distinguish the real from the simulated lesions. They also classified the shapes of the microcalcifications according to a standardized clinical lexicon. The observed probability of correct choice was 0.415, 95% confidence interval (0.284, 0.546), showing that the radiologists were unable to distinguish the lesions. The shape classification revealed substantial agreement with the truth (mean kappa = 0.70), showing that we were able to accurately simulate the lesion morphology. While currently limited to single microcalcifications, the method is extensible to more complex clusters of microcalcifications and to three-dimensional images. It can be used to objectively assess an imaging technology, especially with respect to its ability to adequately visualize the morphology of the lesions, which is a critical factor in the benign versus malignant classification of a lesion detected in screening mammography.

Does digital mammography in a decentralized breast cancer screening program lead to screening performance parameters comparable with film-screen mammography?

Objective:To evaluate if the screening performance parameters of digital mammography (DM) in a decentralized screening organization were comparable with film-screen mammography (FSM).Methods:A nationwide screening program was launched in 2001, and since 2005 screening with DM has been allowed. Firstly, the parameters of the three regional screening units (RSUs) that first switched to DM (11,355 women) were compared with the FSM period of the same three RSUs (23,325 women). Secondly, they were compared with the results of the whole central breast unit (CBU).Results:The recall rate (RR) of the DM group in the initial round was 2.64% [2.40% for FSM (p = 0.43)] and in the subsequent round 1.20% [1.58% for FSM (p = 0.03)]. The cancer detection rate (CDR) was 0.59% for DM and 0.64% for FSM (p = 0.56). The percentage of ductal carcinoma in situ was 0.07% for DM and 0.16% for FSM (p = 0.02). The positive predictive value was high in the subsequent rounds (DM 48.00%, FSM 45.93%) and lower in the initial round (DM 24.05%, FSM 24.86%). Compared with the results of the whole CBU, DM showed no significant difference.Conclusion:DM can be introduced in a decentralized screening organization with a high CDR without increasing the RR.

Simulation of 3D objects into breast tomosynthesis images.

Digital breast tomosynthesis is a new three-dimensional (3D) breast-imaging modality that produces images of cross-sectional planes parallel to the detector plane from a limited number of X-ray projections over a limited angular range. Several technical and clinical parameters have not yet been completely optimised. Some of the open questions could be addressed experimentally; other parameter settings cannot be easily realised in practice and the associated optimisation process requires therefore a theoretical approach. Rather than simulating the complete 3D imaging chain, it is hypothesised that the simulation of small lesions into clinical (or test object) images can be of help in the optimisation process. In the present study, small 3D objects have been simulated into real projection images. Subsequently, these hybrid projection images are reconstructed using the routine clinical reconstruction tools. In this study, the validation of this simulation framework is reported through the comparison between simulated and real objects in reconstructed planes. The results confirm that there is no statistically significant difference between the simulated and the real objects. This suggests that other small mathematical or physiological objects could be simulated with the same approach.

Correlation of free-response and receiver-operating-characteristic area-under-the-curve estimates: Results from independently conducted FROC/ROC studies in mammography

PURPOSE From independently conducted free-response receiver operating characteristic (FROC) and receiver operating characteristic (ROC) experiments, to study fixed-reader associations between three estimators: the area under the alternative FROC (AFROC) curve computed from FROC data, the area under the ROC curve computed from FROC highest rating data, and the area under the ROC curve computed from confidence-of-disease ratings. METHODS Two hundred mammograms, 100 of which were abnormal, were processed by two image-processing algorithms and interpreted by four radiologists under the FROC paradigm. From the FROC data, inferred-ROC data were derived, using the highest rating assumption. Eighteen months afterwards, the images were interpreted by the same radiologists under the conventional ROC paradigm; conventional-ROC data (in contrast to inferred-ROC data) were obtained. FROC and ROC (inferred, conventional) data were analyzed using the nonparametric area-under-the-curve (AUC), (AFROC and ROC curve, respectively). Pearson correlation was used to quantify the degree of association between the modality-specific AUC indices and standard errors were computed using the bootstrap-after-bootstrap method. The magnitude of the correlations was assessed by comparison with computed Obuchowski-Rockette fixed reader correlations. RESULTS Average Pearson correlations (with 95% confidence intervals in square brackets) were: Corr(FROC, inferred ROC) = 0.76[0.64, 0.84] > Corr(inferred ROC, conventional ROC) = 0.40[0.18, 0.58] > Corr (FROC, conventional ROC) = 0.32[0.16, 0.46]. CONCLUSIONS Correlation between FROC and inferred-ROC data AUC estimates was high. Correlation between inferred- and conventional-ROC AUC was similar to the correlation between two modalities for a single reader using one estimation method, suggesting that the highest rating assumption might be questionable.

Comparison of visual grading and free-response ROC analyses for assessment of image processing algorithms in digital mammography

OBJECTIVE To compare two methods for assessment of image-processing algorithms in digital mammography: free-response receiver operating characteristic (FROC) for the specific task of microcalcification detection and visual grading analysis (VGA). METHODS The FROC study was conducted prior to the VGA study reported here. 200 raw data files of low breast density (Breast Imaging-Reporting and Data System I-II) mammograms (Novation DR, Siemens, Germany)-100 of which abnormal-were processed by four image-processing algorithms: Raffaello (IMS, Bologna, Italy), Sigmoid (Sectra, Linköping, Sweden), and OpView v. 2 and v. 1 (Siemens, Erlangen, Germany). Four radiologists assessed the mammograms for the detection of microcalcifications. 8 months after the FROC study, a subset (200) of the 800 images was reinterpreted by the same radiologists, using the VGA methodology in a side-by-side approach. The VGA grading was based on noise, saturation, contrast, sharpness and confidence with the image in terms of normal structures. Ordinal logistic regression was applied; OpView v. 1 was the reference processing algorithm. RESULTS In the FROC study all algorithms performed better than OpView v. 1. From the current VGA study and for confidence with the image, Sigmoid and Raffaello were significantly worse (p<0.001) than OpView v. 1; OpView v. 2 was significantly better (p=0.01). For the image quality criteria, results were mixed; Raffaello and Sigmoid for example were better than OpView v. 1 for sharpness and contrast (although not always significantly). CONCLUSION VGA and FROC discordant results should be attributed to the different clinical task addressed. ADVANCES IN KNOWLEDGE The method to use for image-processing assessment depends on the clinical task tested.

The relationship between the attenuation properties of breast microcalcifications and aluminum

Screening mammography is one of the most challenging radiological techniques and this is partly due to the difficulty in detecting microcalcifications (MCs) against an anatomical background of varying mammographic tissue density. Further complicating factors in the detection of MCs include the small size and their resemblance to other bright structures in the breast. A number of different microcalcification simulating materials are available and these are often incorporated in test objects used to study some aspects of an imaging system, for example, optimal beam quality selection in digital mammography. Aluminum (Al) has similar x-ray attenuation properties to MCs and therefore Al is extensively used in test objects. However, to the best of our knowledge, the suitability of Al as a substitute material for MCs has not been studied explicitly. The aim of this study was therefore to demonstrate that spectral optimization studies for MCs can be performed with Al sheets. The approach used was twofold. First, contrasts generated by Al and MCs at several exposure settings were compared, and secondly an optimization study was performed with both Al and MCs as the contrasting target using an amorphous selenium (a-Se) based digital mammography unit. Specimens from stereotactic vacuum-assisted breast biopsies of non-palpable lesions with mammographic evidence of MCs were obtained from clinical routine patients. Contrasts generated by these MCs and by Al sheets were measured for Mo/Mo, Mo/Rh and W/Rh anode/filter combinations, for different polymethylmethacrylate (PMMA) thicknesses at the extremes of the x-ray tube voltages used clinically. A linear regression was then applied between the two measurements of contrast; the ratio of the angular coefficient q obtained from the fitted regression lines for Al and MCs ranged from 0.96 to 0.99 for Mo/Mo and Mo/Rh combinations at 2 and 4 cm PMMA, respectively, and from 0.83 at 4 cm PMMA to 1.14 at 7 cm PMMA for the W/Rh combination. For the optimization study, the signal-difference-to-noise ratio (SDNR) measured using the MCs was plotted as a function of mean glandular dose (MGD) for 4 cm PMMA, for the three different anode/filter combinations. The W/Rh combination always gave the highest SDNR for a given MGD. The SDNR and MGD were then used to define the common figure of merit SNR(2)/MGD; the setting that maximized this measure at 4 cm PMMA was 27 kV and a W/Rh combination. These results demonstrate a close correspondence between the attenuation properties of Al and extracted MC material over the energy range studied for the Mo/Mo, Mo/Rh and W/Rh anode/filter combinations. Furthermore, it was found that the exposure parameters that maximized the figure of merit for the MC specimen agree with results found in studies that used Al sheets as a substitute for the MC.

Computed Tomography Characteristics Predictive for Radial EBUS-Miniprobe-Guided Diagnosis of Pulmonary Lesions

Introduction: Radial endobronchial ultrasonography miniprobe (rEBUS-MP) is a technique that has increased the diagnostic yield of bronchoscopic occult pulmonary lesions. The purpose of this study was to identify computed tomography (CT) characteristics affecting the success rate of rEBUS-MP in the evaluation of these pulmonary lesions. Methods: Our study encompassed a retrospective review of all consecutive patients who underwent a rEBUS-MP examination between January 2011 and December 2013. CT characteristics including lesion size, lesion location, and bronchus sign were analyzed against two defined outcomes (visualization yield and diagnostic yield). Univariate analysis was employed to examine the individual effects of each CT parameter on visualization yield and diagnostic yield. Multivariate logistic regression was performed to identify significant predictors of diagnostic yield. Results: Seven hundred and sixty lesions (760 patients) were included. The mean ± SD longest lesion diameter was 43 ± 2 mm. rEBUS-MP could visualize 83% and a definitive diagnosis was established in 62%. In a multivariate analysis, longest lesion diameter greater than 20 mm (odds ratio [OR]: 1.97 and p = 0.036), distance lesion to secondary or tertiary carina greater than 40 mm (OR: 0.60 and p=0.016), and lobar segment (1, 3, or 6, respectively) were determined to be significant factors predicting diagnostic yield. Bronchus sign was the only parameter that indirectly influenced the diagnostic yield through enhancing visualization yield (p < 0.001). Conclusion: Multivariate analysis revealed that lesion size, distance to carina, and segment were predictors of diagnostic yield. The presence of a bronchus sign substantially increased the diagnostic yield through the visualization yield.

Implementing the complete beam hardening effect of the bowtie filter versus scaling beam intensities: effects on dosimetric applications in computed tomography

Abstract. The bowtie filter is an essential element of computed tomography scanners. Implementation of this filter in a Monte Carlo dosimetry platform can be based on Turner’s method, which describes how to measure the filter thickness and relate the x-ray beam as a function of bowtie angle to the central beam. In that application, the beam hardening is accounted for by means of weighting factors that are associated to the photons according to their position (fan angle) and energy. We assessed an alternative approximation in which the photon spectrum is given a fan angle-dependent scaling factor. The aim of our investigation was to evaluate the effects on dose accuracy estimation when using the gold standard bowtie filter method versus a beam scaling approximation method. In particular, we wanted to assess the percentage dose differences between the two methods for several water thicknesses representative for different patients of different body mass index. The largest percentage differences were found for the thickest part of the bowtie filter and increased with patient size.