GE Senographe 2000D Research Articles

Makna Mobile Mammography Screening Unit

Amount allocated in 2017 for this initiative RM 754,892.00 (US$ 195,353 or CHF 187,509.16) Background and context: Urbanization and its discontent have seen more urban poor in need of immediate medical intervention. Only a small percentage of women ever performed mammogram due to medical screening cost and poor knowledge pertaining to mammography screening for breast cancer. A massive health education campaign through multiple methods and agencies is necessary to upend this deep-seated perception. Aim: MAKNA's mobile mammography screening unit aims to improve lifesaving chances of people afflicted by cancer through early detection of presymptomatic cancer, using approved and fully equipped vehicle with the latest technology available. Focusing in early detection Garnering resources inter alia to help the financially-challenged cancer patients Many cases that come to MAKNA come in the late stages where help of a cure is usually less than 30% Enhancing knowledge and awareness among general public Economic-wise: cheaper to screen for diseases compared with treating patient Reducing death rate from breast cancer by conduct and deliver nationwide campaign all over Malaysia from districts to cities, rural to urban dwellings Strategy: Equipment overall specs Breast screenings with mammography using full fledge digital unit (GE SENOGRAPHE 2000D) Primary objectives: To conduct mammograms and clinical breast examinations (CBE) to public. To conduct general screening to public. Secondary objectives: To conduct cancer awareness and screening program to public. To educate staffs on early detection of cancer. To raise fund for financially challenged cancer patients via MAKNA various fundraising projects Key messages: Early detection saves lives - know the early warning signs and get screened. Care for yourself and others -help us to help the financially challenged cancer patient. (Cancer treatment is very expensive.) Get involved! -Participate in our activities Further targeted communities: Rural interior villages across Malaysia Costs and returns: A. Total 2007-2017: Total costs: RM 5,787,634 (US$ 1,497,398 or CHF 1,437,713) (RM 2,499,500 for fixed assets + RM 3,288,134 for services) Total ROI: Total screenings: 204 locations Results (by case): Normal: 20,027 Benign: 2434 Abnormal/referred: 383 Cancer diagnoses: 23 B. Year of 2017´s impacts: Costs: RM 753,109 (US$ 194,878 or CHF 187,083) ROI: 6378 screenings: 47 locations Result (by case) Normal: 5329 Benign: 956 Abnormal/referred: 93 Cancer diagnoses: 7 What was learned: Majority of cancers are the result of unhealthy lifestyle rather than inherited genetic faults. Breast cancer rate by ethnic: highest in Chinese > Malay > Indian > others. Early stage of breast cancer most detected. Patient navigation program to improve follow-up with positive cases. Overall, this is a scalable solution. Specifically in good prospect to operate in Borneo, East Malaysia with 2 more units.

Dosimetry in a mammography phantom using TLD-300 dosimeters.

The purpose of this study was to evaluate the photon field effective energy (Eeff ) distribution and percentage depth-dose (PDD) within a mammography phantom by the analysis of the CaF2 :Tm (TLD-300) thermoluminescent (TL) glow curve. The experimental procedure involves the use of TLD-300 to determine with single dosimeter exposures both the relative dose and the beam quality. TLD-300 chips were exposed to x rays from a GE Senographe 2000D mammography unit at the surface and different depths within a BR12 phantom. X-ray beams were generated with Mo/Mo, Mo/Rh, and Rh/Rh anode/filter combinations and voltages between 25 and 34kV. Glow curves were deconvoluted into component peaks and the high- to low-temperature ratio (HLTR) was evaluated. The photon field Eeff was obtained from the HLTR values using a calibration curve determined previously. PDD was established from the peak 5 TL signal (TLSP5 ) at depths between 0.0 and 3.5cm inside the phantom. Taking into account the differences in density and composition between CaF2 :Tm and breast tissue, an energy-dependent correction factor (β(E)) was applied to TLSP5 . Measurements were compared with radiation transport Monte Carlo (MC) simulations performed with PENELOPE-2008. A typical 5% change in the HLTR from the phantom top surface to 3.5cm depth was measured, which corresponds to a 2.2keV increase in photon field Eeff . Values of the β(E) correction factor were 0.33 and 0.13 for Eeff equal to 15.1 and 22.5keV, respectively. This strong energy dependence of β(E) is mostly due to the differences in fluence attenuation between CaF2 and breast tissue. According to PDD measurements, dose decreased to half the surface value at depths between 0.7 and 1.0cm for Mo/Mo/25 and Rh/Rh/34 beams, respectively. Values of PDD, less than 10% at 3.5cm depth, would have been overestimated by about 3.5% (a large relative error) if an energy-independent correction factor had been assumed. Mean differences between experiments and MC simulations were 0.8keV and 1.2% in the determination of Eeff and PDD, respectively. The TLD-300 glow curve was used to accurately measure the photon field Eeff and PDD within a mammographic phantom. This work has demonstrated that Eeff and dose can be established simultaneously by using solely TLD-300.

Dual energy contrast enhanced soft tissue digital mammography versus ultrasound elastography in the evaluation of breast masses

PurposeTo evaluate the value of dual energy contrast enhanced (DECE) soft tissue digital mammography and ultrasound elastography (UE) in the detection of breast lesions and discrimination between benign and malignant ones. Patients and methods32 female patients with breast lesions were prospectively evaluated at the female imaging unit of Diagnostic and Interventional Radiology Department of the National Cancer Institute, Cairo University. Routine sono-mammography was done for each patient then these patients were submitted to DECE soft tissue digital mammography as well as UE.The DECE digital mammography scans were held via GE Senographe 2000D “GE Healthcare; Chalfont St-Giles, UK” FFDM system with some specific software and hardware adaptations.The UE exams were held on ultrasound scanner with elastography unit and 7.5 Mhz linear array electronic probe (Hitachi digital, EUB- 7500; Hitachi medical, Tokyo, Japan). ResultsThis study showed that sensitivity and specificity of DECE soft tissue digital mammography and UE were 86.3%, 60% and 80.9%, 40% respectively. ConclusionDECE soft tissue digital mammography demonstrated significant increase in the sensitivity without a loss in specificity. DECE soft tissue digital mammography is fast-reproducible imaging tool without operator dependency. DECE soft tissue digital mammography and UE are valuable tools to evaluate equivocal lesions.

Pilot study demonstrating potential association between breast cancer image‐based risk phenotypes and genomic biomarkers

In this pilot study, the authors examined associations between image-based phenotypes and genomic biomarkers. The potential genetic contribution of UGT2B genes to interindividual variation in breast density and mammographic parenchymal patterns is demonstrated by performing an association study between image-based phenotypes and genomic biomarkers [single-nucleotide polymorphism (SNP) genotypes]. This candidate-gene approach study included 179 subjects for whom both mammograms and blood DNA samples had been obtained. The full-field digital mammograms were acquired using a GE Senographe 2000D FFDM system (12-bit; 0.1 mm-pixel size). Regions-of-interest, 256 × 256 pixels in size, selected from the central breast region behind the nipple underwent computerized image analysis to yield image-based phenotypes of mammographic density and parenchymal texture patterns. SNP genotyping was performed using a Sequenom MassArray System. One hundred twenty three SNPs with minor allele frequency above 5% were genotyped for the UGT2B gene clusters, and used in the study. The association between the image-based phenotypes and genomic biomarkers was assessed with the Pearson correlation coefficient via thePLINK software, and included permutation and correction for multiple SNP comparisons. From the phenotype-genotype association analysis, a parenchyma texture coarseness feature was found to be correlated with SNP rs451632 after multiple test correction for the multiple SNPs (p = 0.022). The power law β, which is used to characterize the frequency component of texture patterns, was found to be correlated with SNP rs4148298 (p = 0.035). The authors' results indicate that UGT2B gene variation may contribute to interindividual variation in mammographic parenchymal patterns and breast density. Understanding the relationship between image-based phenotypes and genomic biomarkers may help understand the biologic mechanism for image-based biomarkers and yield a future role in personalized medicine.

Automatic Detection of the Nipple in Screen-Film and Full-field Digital Mammograms Using a Novel Hessian-Based Method

Automatic detection of the nipple in mammograms is an important step in computerized systems that combine multiview information for accurate detection and diagnosis of breast cancer. Locating the nipple is a difficult task owing to variations in image quality, presence of noise, and distortion and displacement of the breast tissue due to compression. In this work, we propose a novel Hessian-based method to locate automatically the nipple in screen-film and full-field digital mammograms (FFDMs). The method includes detection of a plausible nipple/retroareolar area in a mammogram using geometrical constraints, analysis of the gradient vector field by mean and Gaussian curvature measurements, and local shape-based conditions. The proposed procedure was tested on 566 mammographic images consisting of 372 randomly selected scanned films from two public databases (mini-MIAS and DDSM), and 194 digital mammograms acquired with a GE Senographe 2000D FFDM system. A radiologist independently marked the centers of the nipples for evaluation of the results. The average error obtained was 6.7 mm (22 pixels) with reference to the center of the nipple as identified by the radiologist. Only two out of the 566 detected nipples (0.35 %) had an error larger than 50 mm. The method was also directly compared with two other techniques for the detection of the nipple. The results indicate that the proposed method outperforms other algorithms presented in the literature and can be used to identify accurately the nipple on various types of mammographic images.

SU‐E‐I‐93: Comparison of the AEC Thickness Tracking Using the Signal‐ Difference‐To‐Noise Ratio in 113 Flat‐Panel Digital Mammography Units

Purpose: Signal‐difference‐to‐noise ratio (SDNR) can be served as an indicator representing the sensitivity of an x‐ray system. This study aimed to evaluate the automatic exposure control (AEC) performance using the SDNR based on the national survey data in Taiwan. Methods: Measurements were made on all the 113 flat‐panel digital mammography units in Taiwan during our 2010 national survey. They included GE Senographe 2000D (38), DS (15) and Essential (3), Hologic Selenia with Mo (20) and W (24) targets, Siemens Mammomat NovationDR(8) and Inspiration (4), and IMS Giotto Image3D (1). A disk was placed on top of the 2, 4 and 6‐cm thick acrylic blocks to simulate the contrast. Clinical AEC modes were selected to acquire images and SDNR were then measured as the mean pixel value differences between the disk and the background divided by the noise using the equation defined in ACRIN DMIST recommendations. Results: AEC systems of different manufacturers/models, or even different units with the same models resulted in different target/filter combinations and techniques when performing the thickness tracking. For example, 6‐cm thickness led to 40% Mo/Mo and 60% Mo/Rh in Hologic Selenia systems with Mo target and 4‐cm thickness led to 26% for Mo/Mo and 74% for Mo/Rh in GE 2000D systems. Decreasing SDNRs were observed when thickness increased in all the eight digital models. When normalized the mean SDNR of each model to their 4‐cm‐thickness data, large deviations between 2 cm and 6 cm were observed in the GE systems (94.7%, 87.1% and 63.0% for DS, Essential and 2000D, respectively). Deviations of the other five models ranged from 36.9% to 59.6%. Conclusions: Evaluating AEC performance using SDNR showed the decreasing trend with increasing thickness in all the eight digital models. Considering the average glandular dose together, Figure of Merit will be further investigated in the future.

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 1 ml/kg body weight at a rate of 4 ml/s. Three contrast-enhanced images in the cranio-caudal projection plane were then captured at intervals of 60 s. 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.

Full field digital mammography: which equipment?

A wide variety of digital mammography systems are now commercially available. These include digital radiography (DR) systems such as the CSi/amorphous silicon detector (for example, GE Senographe 2000D, DS and Essential models), amorphous selenium (for example, LoRad Selenia, Siemens Novation and Inspiration models, IMS Giotto, Planmed Nuance) and a scanning system with silicon detectors (for example, Sectra Micro Dose Mammography). A variety of computerised radiography (CR) systems for mammography are also available (for example, Fuji Profect, Kodak DirectView, Konica Regius 190, Agfa CR 85-X). Recently the CR manufacturers have introduced new designs of phosphor plates. Such a wide variety of systems raises the question of how the performances of these systems compare with each other and with film-screen technology. Another factor to be considered is the radiation dose required by each system to reach an acceptable level of image quality. To help answer these questions, the National Health Service Breast Screening Programme and European Guidelines specify minimum and achievable standards for dose and image quality. The minimum standard is designed to ensure that new digital systems are at least as good as the previous film-screen systems. This lecture compares the measurements on a wide range of digital systems against the standards in the European Guidelines. The overall conclusion is that the DR systems can generally meet the achievable image quality standards for a dose lower than that used for film-screen systems. While the new designs of CR plate have brought about measurable improvements, most CR systems still require doses higher than film-screen systems to meet the minimum standards for image quality.

SU‐GG‐I‐50: Breast Tissue Classification in Digital Breast Tomosynthesis Images Using Texture Features

Purpose: Breast density is a known breast cancer risk factor. Digital breast tomosynthesis (DBT) is a tomographic x‐ray breast imaging modality with superior breast tissue visualization in comparison to mammography. The goal of our on‐going study is to evaluate the performance of DBT texture features in distinguishing between dense and fatty breast tissue regions. Our hypothesis is that DBT texture analysis could result in more discriminative features to characterize breast density in comparison to mammography, and ultimately yield more accurate measures of risk. Method and Materials: DBT images and digital mammograms (DM) from 39 women were analyzed. DBT and DM acquisition was performed with a GE Senographe 2000D FFDM system modified to allow positioning of the x‐ray tube at 9 locations by varying the angle from −25° to +25° in increments of 6.25°. Filtered‐backprojection was used to reconstruct DBT tomographic planes in 1 mm increments. The dense tissue area was delineated within each breast image using a widely validated thresholding technique (Cumulus Ver. 4.0, University of Toronto). Two regions of interest (ROIs) were manually selected in each breast image: one within the dense tissue region and another within the fatty region. Texture features of skewness, coarseness, contrast, fractal dimension, energy and homogeneity were computed from all available ROIs. Two‐tailed paired Student's t‐test was applied to compare the means of the texture feature distributions from the dense versus the fatty ROIs. Results: Coarseness, contrast, energy and homogeneity were statistically significantly different (p⩽0.001) between dense and fatty ROIs. Dense ROIs have lower coarseness, higher contrast, higher energy and lower homogeneity. Conclusion: X‐ray image texture differs between dense and fatty breast tissue regions. Further work is underway to fully compare the relative performance of texture features in classifying dense versus fatty tissue regions using DM, DBT source projections, and reconstructed DBT images.

Evaluation of the potential in radiation dose reduction for full-field digital mammography

Evaluation of the potential in radiation dose reduction for full-field digital mammography This study evaluates the image quality for different radiation doses in full-field digital mammography (FFDM). The potential of dose reductions is evaluated for both, the transition from screen-film mammography (SFM) to FFDM as well as within FFDM due to the optimization of exposure parameters. Exposures of a 4.5 cm breast phantom rendering different contrasts as well as bar patterns were made using a FFDM system (GE Senographe 2000D). For different kVp and mAs settings as well as different target/filter combinations chosen for the above exposures, average glandular dose (AGD), signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR) and modulation transfer function (MTF) were determined. To benchmark the results, relative change of AGD was evaluated against SNR, CNR and MTF. Eventually, the results were normalized to AGD's rendered by settings typically used in today's clinical routine. For standard settings (automatic mode), both FFDM and SFM deliver approximately the same AGD of about 2.2 mGy. From that, AGD reduction can be substantial in FFDM if only SNR and high contrast CNR are considered. In this case, reduction of up to 40% can be achieved in a wide kVp range if switching from the standard target/filter combination Mo/Rh to Rh/Rh. However, if low contrast CNR is to remain unchanged, dose reduction is practically impossible. The change of peak voltage and target/filter material had no influence on MTF. Assuming current CNR requirements as standards, significant dose reduction in FFDM cannot be achieved. Only by compromising low contrast CNR levels AGD of up to 40% can be saved at current standards of SNR and high contrast CNR.

Physical characteristics of five clinical systems for digital mammography

The purpose of this study was to evaluate and compare the physical characteristics of five clinical systems for digital mammography (GE Senographe 2000D, Lorad Selenia M-IV, Fischer Senoscan, Agfa DM 1000, and IMS Giotto) currently in clinical use. The basic performances of the mammography systems tested were assessed on the basis of response curve, modulation transfer function (MTF), noise power spectrum, noise equivalent quanta (NEQ), and detective quantum efficiency (DQE) in an experimental setting closely resembling the clinical one. As expected, all the full field digital mammography systems show a linear response curve over a dynamic range from 3.5 to 500 microGy (0.998<R2< 1). The presampling MTFs at 2, 3, and 5 lp/mm were found to be respectively 0.78, 0.64, and 0.37 for GE Senographe 2000D; 0.92, 0.85, and 0.69 for Lorad Selenia and Agfa DM1000; 0.75, 0.63, and 0.42 for Fischer Senoscan; and 0.91, 0.82, and 0.61 for the IMS Giotto. According to the pixel size of each digital system, the presampling MTF was calculated within a range up to the Nyquist frequency (5 lp/mm for GE Senographe 2000D, 7.1 lp/mm for Lorad Selenia, 9.3 lp/mm for Fischer Senoscan, and 5.88 lp/mm for IMS Giotto detector). The NEQ becomes related to the exposure in a linear behavior starting from about 40.3 microGy for GE Senographe 2000D, 42.9 microGy for Lorad Selenia, 41.2 microGy for Agfa DM1000, <87.6 microGy for Fischer Senoscan, and 61.3 microGy for the IMS Giotto. Above those values, the systems can be considered "quantum noise limited," that is the electronic noise is negligible if compared to the quantum noise. The DQE, for several emitted x-ray spectra for each system, i.e., 28 kV p Mo-Mo, Mo-Rh, Rh-Rh, W-Al anode-filter combination, hardened by 40 mm poly(methylmethacrylate) (PMMA) was evaluated. For the five different systems, the DQE at close to zero spatial frequency ranges between 0.25 and 0.63 at 131 microGy entrance surface air kerma to the detectors. The results of our quantitative analysis demonstrated a higher DQE for direct conversion technology when compared to that of the indirect conversion. The NEQ behavior of each system can be exploited to select the optimum exposure level set in clinical practice to ensure minimum patient dose though adequate image quality. The detailed results of the physical characterization of the digital systems reported in this work allow the quantitative comparison of different technologies as well as the definition of reference values for subsequent quality control tests. The method developed in this work is suitable to be reproduced in any medical physics department for the previously described goals.

Contrast-to-Noise Ratios of Different Elements in Digital Mammography

To determine the contrast-to-noise ratios (CNRs) of different elements at different energies using various anode/filter combinations currently employed in digital mammography. The elements investigated included not only elements already used in conventional contrast agents such as gadolinium and iodine but also other elements to investigate their potential as mammographic contrast agents. The CNRs of 20 mmol/L bismuth (Bi), gadolinium (Gd), ytterbium (Yb), dysprosium (Dy), and iodine (I) were determined at different slice thicknesses (0.25, 0.5, and 1 cm) of the element solution with an additional 4-cm Plexiglas in relation to water (to simulate dense glandular tissue), oil, and air. The following anode/filter combinations were used: Mo/Mo in the range of 22-34 kVp, Mo/Rh in the range of 36-40 kVp, Rh/Rh in the range of 42-46 kVp, and Mo/Cu in the range of 47-49 kVp. In the range of 22-46 kVp, the mAs were chosen to achieve a fairly uniform dose range (of 4.38-4.71 mGy). Doses were measured using the PTW DIADOS diagnostic dosimeter. The element solutions were examined with a GE Senographe 2000D. Bismuth showed the best CNR for all energies investigated and in relation to both water and oil. In the energy range below 46 kVp, bismuth (CNR at 30 kVp/50 mAs and 1/0.5/0.25 cm slice thickness: 9.9/6.1/3.4) was followed by Yb (5.9/3.5/2.0), Dy (5.3/3.2/1.9), Gd (4.2/2.5/1.6), and iodine (2.4/1.8/1.5). Bismuth had the best CNR relative to both water (values given above) and oil (Bi: 20.7/11.2/5; Yb: 16.9/8.6/3.6; Dy: 16.6/8.4/3.5; Gd: 15.21/7.5/3.2; I: 13.8/6.3/3.2). The CNR of Bi was also superior to that of the other elements investigated at high energy in combination with copper filters (eg, CNR at 49 kVp Mo/Cu at slice thicknesses of 1/0.5/0.25 cm, relative to water: 9.6/6.0/4.0) but now followed by iodine (7.9/5.3/3.5), Yb (5.8/4.0/2.9), Dy (5.4/3.7/2.8), and Gd (4.7/3.2/2.7). Iodine was the only element of those investigated whose contrast-to-noise ratio was improved with the use of a copper filter at high energies based on its K-edge (increase in CNR from 2.9 to 7.9 from 40 to 49 kVp at 1-cm slice thickness). Nevertheless, the improved CNR of iodine was below that of Bi at low energies and for Mo/Mo or Mo/Rh filters. The contrast of water/fat tended to decrease slightly at higher energies (CNR of water/air at 42 kVp: 33.9, at 48 kVp: 25.6; CNR of oil/air at 42 kVp: 23.8, at 48 kVp: 21.9). Copper filters and higher energies are useful for visualizing iodine-based contrast agents in contrast-enhanced mammography because they markedly improve the CNR relative to water. This technique further benefits from the fact that the CNR of water and fat relative to air markedly decreases at higher energies and with the use of copper filters. Bismuth was found to have a much better CNR than iodine for all energies investigated including the low energy ranges typically used in mammography. These results suggest that bismuth is a potential candidate for a specific mammographic contrast agent.

Initial Clinical Experience With Contrast-Enhanced Digital Breast Tomosynthesis

Contrast-enhanced digital mammography and digital breast tomosynthesis are two imaging techniques that attempt to increase malignant breast lesion conspicuity. The combination of these into a single technique, contrast-enhanced digital breast tomosynthesis (CE-DBT), could potentially integrate the strengths of both. The objectives of this study were to assess the clinical feasibility of CE-DBT as an adjunct to digital mammography, and to correlate lesion enhancement characteristics and morphology obtained with CE-DBT to digital mammography, ultrasound, and magnetic resonance (MR). CE-DBT (GE Senographe 2000D; Milwaukee, WI) was performed as a pilot study in an ongoing National Cancer Institute-funded grant (P01-CA85484) studying multimodality breast imaging. Thirteen patients with ACR BI-RADS category 4 or 5 breast lesions underwent imaging with digital mammography, ultrasound, MR, and CE-DBT. CE-DBT was performed at 49 kVp with a rhodium target and a 0.27-mm copper (Alfa Aesar, Ward Hill, MA) filter. Preinjection and postinjection DBT image sets were acquired in the medial lateral oblique projection with slight compression. Each image set consists of nine images acquired over a 50-degree arc and was obtained with a mean glandular x-ray dose comparable to two conventional mammographic views. Between the precontrast and postcontrast DBT image sets, a single bolus of iodinated contrast agent (1 ml/kg at 2 ml/s, Omnipaque-300; Amersham Health Inc., Princeton, NJ) was administered. Images were reconstructed using filtered-backprojection in 1-mm increments and transmitted to a clinical PACS workstation. Initial experience suggests that CE-DBT provides morphologic and vascular characteristics of breast lesions qualitatively concordant with that of digital mammography and MR. As an adjunct to digital mammography, CE-DBT may be a potential alternative tool for breast lesion morphologic and vascular characterization.

Optimal beam quality selection in digital mammography

An experimental method of determining the optimal beam quality for digital mammography systems was applied to two systems (Fuji Profect and GE Senographe 2000D). The mean glandular dose (MGD) and contrast-to-noise ratio (CNR) were measured using Perspex breast phantoms simulating breasts from 20 mm to 90 mm thick. For each thickness, four combinations of tube voltage and target/filter were tested. Optimal beam quality was defined as giving a target CNR for the lowest MGD and was similar for the two systems. For breasts with a thickness of 21 mm or 32 mm, a tube voltage of either 25 kV or 28 kV and a Mo/Mo target/filter combination was optimal. For breast thicknesses of 45 mm and greater, the combination that had the highest X-ray energy (34 kV Rh/Rh) was optimal. Optimization using the higher energy beam quality required greater detector dose to compensate for the lower contrast. Thus for a 75 mm thick breast the 34 kV Rh/Rh combination required about a 90% greater detector dose than 28 kV Mo/Mo to achieve the same CNR because of the 25% reduction in contrast. Nonetheless, the MGD was reduced by 32% by choosing the higher energy spectra and achieving the same CNR. Current automatic exposure control (AEC) designs that aim for a fixed detector dose are not optimal and greater use of higher energy spectra should be accompanied by higher detector doses at all breast thicknesses which are average or above. This may result in slightly higher doses, but better image quality for these breasts.

A simple method to estimate coordinate resolution and MTF for pixelized detectors

A simple method to estimate the coordinate resolution of pixelized detectors, using non-single photon counting readout is proposed. This method can be useful particularly for testing detectors used in digital imaging systems. The proposal is based on the determination of the statistical correlation between detector neighbor pixels, by means of the statistical noise measurement of isolated pixels, and the linear combination of neighbor pixels. Distributions of differences between neighbor pixels are constructed for pixels sharing an edge or only having one common vertex. The method is validated using images from a GE Senographe 2000D mammographic unit. The pixelized detector has been irradiated by X-rays along its entire surface. The correlation asymmetry between perpendicular directions has been studied to estimate the possible existence of a hardware asymmetry. The coordinate resolution of the studied detector, pixel size 100 μm, is of the order of 50–55 μm, that is, almost twice as large as the value determined by geometry. A small asymmetry between the mutually perpendicular X and Y directions has been detected. The modulation transfer function (MTF) can be estimated from the correlation data, and the reconstructed MTF is in good agreement with measurements.

The Dutch experience of digital mammography in screening

In The Netherlands a number of (screening) trials with digital mammography have started. The first trial began in 1999, in which the applicability of digital mammography was tested in a clinical environment. For this purpose a GE Senographe 2000D was installed in the Radboud University Nijmegen Medical Centre. The outcome of this trial was positive. Therefore in 2002 a second trial started at a static screening site in Utrecht with a Lorad Selenia system. In this trial, digital mammography was evaluated in a screening environment with its specific demands regarding workflow. In 2004 two more trials were started with mobile digital screening units. In these trials, a Fuji FCR Profect and an Agfa DM 1000 system were installed in the screening units. This summer a new trial will start at a static screening unit in Nijmegen in which digital mammography equipment from different vendors (General Electric, IMS, Sectra, Planmed) will be installed to test connectivity. Results of all trials will be presented with emphasis on physical and technical aspects and workflow issues. Problems with the mammography systems in the trials will be discussed. Besides this, some experiences with digital mammography equipment in Dutch hospitals will be discussed with emphasis on possible pitfalls.

SU‐FF‐I‐47: A Method of the Pixelized Detectors Coordinate Resolution and MTF Estimation

Purpose: We propose a simple method to estimate MTF and coordinate resolution of pixelized detectors used in digital imaging systems. Method and Materials: The traditional determination of coordinate resolution for pixelized detectors is mainly based on the use of line spread function measurements. The proposed method is based on the determination of the statistical correlation between neighbour elements in the detector. The correlation is evaluated by means of statistical noise measurement of the isolated elements and the linear combination of neighbour elements. To suppress the possible contribution of the beam spatial variation, the difference between values of neighbour elements is used. The distribution of differences between the detector neighbour pixels is constructed for the pixels sharing an edge (either in X or Y directions), or having one common vertex (U or V). For the validation of the method, we have studied the GE Senographe 2000D mammography unit digital detector. The detector has been irradiated by X‐rays across its entire surface. The dependence of the resolution on the photon intensity value and the pixel coordinate has been studied. The resolution function has been considered as a result of convolution of Gaussian and uniform distributions. Results: The coordinate resolution of the studied detector, having pixel size of 100 μ, is of the order of 50 –55 μ, that is, almost twice the value conditioned by pixel geometrical size. A small asymmetry between the X and Y directions has been detected. The reconstructed modulation transfer function agrees with MTF measurements of the studied detector, within a few percent. Conclusion: The proposed method can be useful for the estimation of coordinate resolution, line spread function and modulation transfer function of the detectors used in the systems of medical digital imaging.

Dose comparison between screen/film and full-field digital mammography

The study purpose was the comparison between doses delivered by a full-field digital mammography system and a screen/film mammography unit, both using the same type of X-ray tube. Exposure parameters and breast thickness were collected for 300 screen/film (GE Senographe DMR) and 296 digital mammograms (GE Senographe 2000D). The entrance surface air kerma (ESAK) was calculated from anode/filter combination, kV(p) and mAs values and breast thickness, by simulating spectra through a program based on a catalogue of experimental X-ray spectra. The average glandular dose (AGD) was also computed. Results showed an overall reduction of average glandular dose by 27% of digital over screen/film mammography. The dose saving was about 15% for thin and thick breasts, while it was between 30% and 40% for intermediate thicknesses. Full-field digital mammography dose reduction is allowed by wider dynamic range and higher efficiency of digital detector, which can be exposed at higher energy spectra than screen/film mammography, and by the separation between acquisition and displaying processes.

Volumetric breast density estimation from full-field digital mammograms

A method is presented for estimation of dense breast tissue volume from mammograms obtained with full-field digital mammography (FFDM). The thickness of dense tissue mapping to a pixel is determined by using a physical model of image acquisition. This model is based on the assumption that the breast is composed of two types of tissue, fat and parenchyma. Effective linear attenuation coefficients of these tissues are derived from empirical data as a function of tube voltage (kVp), anode material, filtration, and compressed breast thickness. By employing these, tissue composition at a given pixel is computed after performing breast thickness compensation, using a reference value for fatty tissue determined by the maximum pixel value in the breast tissue projection. Validation has been performed using 22 FFDM cases acquired with a GE Senographe 2000D by comparing the volume estimates with volumes obtained by semi-automatic segmentation of breast magnetic resonance imaging (MRI) data. The correlation between MRI and mammography volumes was 0.94 on a per image basis and 0.97 on a per patient basis. Using the dense tissue volumes from MRI data as the gold standard, the average relative error of the volume estimates was 13.6%.

Computer‐aided detection of breast masses on full field digital mammograms

We are developing a computer-aided detection (CAD) system for breast masses on full field digital mammographic (FFDM) images. To develop a CAD system that is independent of the FFDM manufacturer's proprietary preprocessing methods, we used the raw FFDM image as input and developed a multiresolution preprocessing scheme for image enhancement. A two-stage prescreening method that combines gradient field analysis with gray level information was developed to identify mass candidates on the processed images. The suspicious structure in each identified region was extracted by clustering-based region growing. Morphological and spatial gray-level dependence texture features were extracted for each suspicious object. Stepwise linear discriminant analysis (LDA) with simplex optimization was used to select the most useful features. Finally, rule-based and LDA classifiers were designed to differentiate masses from normal tissues. Two data sets were collected: a mass data set containing 110 cases of two-view mammograms with a total of 220 images, and a no-mass data set containing 90 cases of two-view mammograms with a total of 180 images. All cases were acquired with a GE Senographe 2000D FFDM system. The true locations of the masses were identified by an experienced radiologist. Free-response receiver operating characteristic analysis was used to evaluate the performance of the CAD system. It was found that our CAD system achieved a case-based sensitivity of 70%, 80%, and 90% at 0.72, 1.08, and 1.82 false positive (FP) marks/image on the mass data set. The FP rates on the no-mass data set were 0.85, 1.31, and 2.14 FP marks/image, respectively, at the corresponding sensitivities. This study demonstrated the usefulness of our CAD techniques for automated detection of masses on FFDM images.