Proceedings Virtual Imaging Trials in Medicine 2024.

This submission comprises the proceedings of the 1st Virtual Imaging Trials in Medicine conference, organized by Duke University on April 22-24, 2024. The listed authors serve as the program directors for this conference. The VITM conference is a pioneering summit uniting experts from academia, industry and government in the fields of medical imaging and therapy to explore the transformative potential of in silico virtual trials and digital twins in revolutionizing healthcare. The proceedings are categorized by the respective days of the conference: Monday presentations, Tuesday presentations, Wednesday presentations, followed by the abstracts for the posters presented on Monday and Tuesday.

A 3D Mathematical Breast Texture Model With Parameters Automatically Inferred From Clinical Breast CT Images.

A numerical realistic 3D anthropomorphic breast model is useful for evaluating breast imaging applications. A method is proposed to model small and medium-scale fibroglandular and intra-glandular adipose tissues observed in the center part of clinical breast CT images. The method builds upon a previously proposed model formulated as stochastic geometric processes with mathematically tractable parameters. In this work, the medium-scale parameters were automatically and objectively inferred from breast CT images. We hypothesized that a set of random ellipsoids exhibiting cluster interaction is representative to model the medium-scale intra-glandular adipose compartments. The ellipsoids were reconstructed using a multiple birth, death and shift algorithm. Then, a Matérn cluster process was used to fit the reconstructed ellipsoid centers. Finally, distributions of the ellipsoid shapes and orientations were estimated using maximum likelihood estimators. Feasibility was demonstrated on 16 volumes of interests (VOI). To assess the realism of the 3D breast texture model, ß and LFE metrics computed in simulated projection images of simulated texture realizations and clinical images were compared. Visual realism was illustrated. For 12 out of 16 VOIs, our hypothesis on clustering interaction process is confirmed. The average ß values from simulated texture images (3.7 to 4.2) of the 12 different VOIs are higher than the average ß value from 2D clinical images (2.87). LFE of simulated texture images and clinical mammograms are similar. Compared to our previous model, whereby simulation parameters were based upon empirical observations, our inference method substantially augments the ability to generate textures with higher visual realism and larger morphological variety.

A biomechanical breast model evaluated with respect to MRI data collected in three different positions.

BACKGROUND: Mammography is a specific type of breast imaging that uses low-dose X-rays to detect cancer in early stage. During the exam, the women breast is compressed between two plates in order to even out the breast thickness and to spread out the soft tissues. This technique improves exam quality but can be uncomfortable for the patient. The perceived discomfort can be assessed by the means of a breast biomechanical model. Alternative breast compression techniques may be computationally investigated trough finite elements simulations. METHODS: The aim of this work is to develop and evaluate a new biomechanical Finite Element (FE) breast model. The complex breast anatomy is considered including adipose and glandular tissues, muscle, skin, suspensory ligaments and pectoral fascias. Material hyper-elasticity is modeled using the Neo-Hookean material models. The stress-free breast geometry and subject-specific constitutive models are derived using tissues deformations measurements from MR images. FINDINGS: The breast geometry in three breast configurations were computed using the breast stress-free geometry together with the estimated set of equivalent Young's modulus (Ebreastr = 0.3 kPa, Ebreastl = 0.2 kPa, Eskin = 4 kPa, Efascia = 120 kPa). The Hausdorff distance between estimated and measured breast geometries for prone, supine and supine tilted configurations is equal to 2.17 mm, 1.72 mm and 5.90 mm respectively. INTERPRETATION: A subject-specific breast model allows a better characterization of breast mechanics. However, the model presents some limitations when estimating the supine tilted breast configuration. The results show clearly the difficulties to characterize soft tissues mechanics at large strain ranges with Neo-Hookean material models.

Optimization of contrast-enhanced spectral mammography depending on clinical indication.

The objective is to optimize low-energy (LE) and high-energy (HE) exposure parameters of contrast-enhanced spectral mammography (CESM) examinations in four different clinical applications for which different levels of average glandular dose (AGD) and ratios between LE and total doses are required. The optimization was performed on a Senographe DS with a SenoBright® upgrade. Simulations were performed to find the optima by maximizing the contrast-to-noise ratio (CNR) on the recombined CESM image using different targeted doses and LE image quality. The linearity between iodine concentration and CNR as well as the minimal detectable iodine concentration was assessed. The image quality of the LE image was assessed on the CDMAM contrast-detail phantom. Experiments confirmed the optima found on simulation. The CNR was higher for each clinical indication than for SenoBright®, including the screening indication for which the total AGD was 22% lower. Minimal iodine concentrations detectable in the case of a 3-mm-diameter round tumor were 12.5% lower than those obtained for the same dose in the clinical routine. LE image quality satisfied EUREF acceptable limits for threshold contrast. This newly optimized set of acquisition parameters allows increased contrast detectability compared to parameters currently used without a significant loss in LE image quality.

Anatomical noise in contrast-enhanced digital mammography. Part II. Dual-energy imaging.

PURPOSE: Dual-energy (DE) contrast-enhanced digital mammography (CEDM) uses an iodinated contrast agent in combination with digital mammography (DM) to evaluate lesions on the basis of tumor angiogenesis. In DE imaging, low-energy (LE) and high-energy (HE) images are acquired after contrast administration and their logarithms are subtracted to cancel the appearance of normal breast tissue. Often there is incomplete signal cancellation in the subtracted images, creating a background "clutter" that can impair lesion detection. This is the second component of a two-part report on anatomical noise in CEDM. In Part I the authors characterized the anatomical noise for single-energy (SE) temporal subtraction CEDM by a power law, with model parameters α and ß. In this work the authors quantify the anatomical noise in DE CEDM clinical images and compare this with the noise in SE CEDM. The influence on the anatomical noise of the presence of iodine in the breast, the timing of imaging postcontrast administration, and the x-ray energy used for acquisition are each evaluated. METHODS: The power law parameters, α and ß, were measured from unprocessed LE and HE images and from DE subtracted images to quantify the anatomical noise. A total of 98 DE CEDM cases acquired in a previous clinical pilot study were assessed. Conventional DM images from 75 of the women were evaluated for comparison with DE CEDM. The influence of the imaging technique on anatomical noise was determined from an analysis of differences between the power law parameters as measured in DM, LE, HE, and DE subtracted images for each subject. RESULTS: In DE CEDM, weighted image subtraction lowers ß to about 1.1 from 3.2 and 3.1 in LE and HE unprocessed images, respectively. The presence of iodine has a small but significant effect in LE images, reducing ß by about 0.07 compared to DM, with α unchanged. Increasing the x-ray energy, from that typical in DM to a HE beam, significantly decreases α by about 2×10(-5) mm2, and lowers ß by about 0.14 compared to LE images. A comparison of SE and DE CEDM at 4 min postcontrast shows equivalent power law parameters in unprocessed images, and lower α and ß by about 3×10(-5) mm2 and 0.50, respectively, in DE versus SE subtracted images. CONCLUSIONS: Image subtraction in both SE and DE CEDM reduces ß by over a factor of 2, while maintaining α below that in DM. Given the equivalent α between SE and DE unprocessed CEDM images, and the smaller anatomical noise in the DE subtracted images, the DE approach may have an advantage over SE CEDM. It will be necessary to test this potential advantage in future lesion detectability experiments, which account for realistic lesion signals. The authors' results suggest that LE images could be used in place of DM images in CEDM exam interpretation.

Anatomical noise in contrast-enhanced digital mammography. Part I. Single-energy imaging.

PURPOSE: The use of an intravenously injected iodinated contrast agent could help increase the sensitivity of digital mammography by adding information on tumor angiogenesis. Two approaches have been made for clinical implementation of contrast-enhanced digital mammography (CEDM), namely, single-energy (SE) and dual-energy (DE) imaging. In each technique, pairs of mammograms are acquired, which are then subtracted with the intent to cancel the appearance of healthy breast tissue to permit sensitive detection and specific characterization of lesions. Patterns of contrast agent uptake in the healthy parenchyma, and uncanceled signal from background tissue create a "clutter" that can mask or mimic an enhancing lesion. This type of "anatomical noise" is often the limiting factor in lesion detection tasks, and thus, noise quantification may be useful for cascaded systems analysis of CEDM and for phantom development. In this work, the authors characterize the anatomical noise in CEDM clinical images and the authors evaluate the influence of the x-ray energy used for acquisition, the presence of iodine in the breast, and the timing of imaging postcontrast administration on anatomical noise. The results are presented in a two-part report, with SE CEDM described here, and DE CEDM in Part II. METHODS: A power law is used to model anatomical noise in CEDM images. The exponent, ß, which describes the anatomical structure, and the constant α, which represents the magnitude of the noise, are determined from Wiener spectra (WS) measurements on images. A total of 42 SE CEDM cases from two previous clinical pilot studies are assessed. The parameters α and ß are measured both from unprocessed images and from subtracted images. RESULTS: Consistent results were found between the two SE CEDM pilot studies, where a significant decrease in ß from a value of approximately 3.1 in the unprocessed images to between about 1.1 and 1.8 in the subtracted images was observed. Increasing the x-ray energy from that used in conventional DM to those of typical SE CEDM spectra with mean energies above 33 keV significantly decreased α by about a factor of 19, in agreement with theory. Compared to precontrast images, in the unprocessed postcontrast images at 30 s postinjection, α was larger by about 7.4 × 10(-7) mm(2) and ß was decreased by 0.2. While α did not vary significantly with the time after contrast administration, ß from the unprocessed image WS increased linearly, and ß from subtracted image WS increased with an initial quadratic relationship that plateaued by about 5 min postinjection. CONCLUSIONS: The presence of an iodinated contrast agent in the breast produced small, but significant changes in the power law parameters of unprocessed CEDM images compared to the precontrast images. Image subtraction in SE CEDM significantly reduced anatomical noise compared to conventional DM, with a reduction in both α and ß by about a factor of 2. The data presented here, and in Part II of this work, will be useful for modeling of CEDM backgrounds, for systems characterization and for lesion detectability experiments using models that account for anatomical noise.

Development of a physical 3D anthropomorphic breast phantom.

PURPOSE: Develop a technique to fabricate a 3D anthropomorphic breast phantom with known ground truth for image quality assessment of 2D and 3D breast x-ray imaging systems. METHODS: The phantom design is based on an existing computer model that can generate breast voxel phantoms of varying composition, size, and shape. The physical phantom is produced in two steps. First, the portion of the voxel phantom consisting of the glandular tissue, skin, and Cooper's ligaments is separated into sections. These sections are then fabricated by high-resolution rapid prototyping using a single material with 50% glandular equivalence. The remaining adipose compartments are then filled using an epoxy-based resin (EBR) with 100% adipose equivalence. The phantom sections are stacked to form the physical anthropomorphic phantom. RESULTS: The authors fabricated a prototype phantom corresponding to a 450 ml breast with 45% dense tissue, deformed to a 5 cm compressed thickness. Both the rapid prototype (RP) and EBR phantom materials are radiographically uniform. The coefficient of variation (CoV) of the relative attenuation between RP and EBR phantom samples was <1% and the CoV of the signal intensity within RP and EBR phantom samples was <1.5% on average. Digital mammography and reconstructed digital breast tomosynthesis images of the authors' phantom were reviewed by two radiologists; they reported that the images are similar in appearance to clinical images, noting there are still artifacts from air bubbles in the EBR. CONCLUSIONS: The authors have developed a technique to produce 3D anthropomorphic breast phantoms with known ground truth, yielding highly realistic x-ray images. Such phantoms may serve both qualitative and quantitative performance assessments for 2D and 3D breast x-ray imaging systems.

Optimization of a dual-energy contrast-enhanced technique for a photon-counting digital breast tomosynthesis system: I. A theoretical model.

PURPOSE: Dual-energy (DE) iodine contrast-enhanced x-ray imaging of the breast has been shown to identify cancers that would otherwise be mammographically occult. In this article, theoretical modeling was performed to obtain optimally enhanced iodine images for a photon-counting digital breast tomosynthesis (DBT) system using a DE acquisition technique. METHODS: In the system examined, the breast is scanned with a multislit prepatient collimator aligned with a multidetector camera. Each detector collects a projection image at a unique angle during the scan. Low-energy (LE) and high-energy (HE) projection images are acquired simultaneously in a single scan by covering alternate collimator slits with Sn and Cu filters, respectively. Sn filters ranging from 0.08 to 0.22 mm thickness and Cu filters from 0.11 to 0.27 mm thickness were investigated. A tube voltage of 49 kV was selected. Tomographic images, hereafter referred to as DBT images, were reconstructed using a shift-and-add algorithm. Iodine-enhanced DBT images were acquired by performing a weighted logarithmic subtraction of the HE and LE DBT images, The DE technique was evaluated for 20-80 mm thick breasts. Weighting factors, w(t) that optimally cancel breast tissue were computed. Signal-difference-to-noise ratios (SDNRs) between iodine-enhanced and nonenhanced breast tissue normalized to the square root of the mean glandular dose (MGD) were computed as a function of the fraction of the MGD allocated to the HE images. Peak SDNR/ mean square root of MGD and optimal dose allocations were identified. SDNR/ mean square root of MGD and dose allocations were computed for several practical feasible system configurations (i.e., determined by the number of collimator slits covered by Sn and Cu). A practicalsystem configuration an d Sn-Cu filterpair that accounts for the trade-off between SDNR, tube-output, and MGD were selected. RESULTS: w(t) depends on the Sn-Cu filter combination used, as well as on the breast thickness; to optimally cancel 0% with 50% glandular breast tissue, w(t) values were found to range from 0.46 to 0.72 for all breast thicknesses and Sn-Cu filter pairs studied. The optimal w(t) values needed to cancel all possible breast tissue glandularites vary by less than 1% for 20 mm thick breasts and 18% for 80 mm breasts. The system configuration where one collimator slit covered by Sn is alternated with two collimator slits covered by Cu delivers SDNR/ mean square root of MGD nearest to the peak value. A reasonable compromise is a 0.16 mm Sn-0.23 mm Cu filter pair, resulting in SDNR values between 1.64 and 0.61 and MGD between 0.70 and 0.53 mGy for 20-80 mm thick breasts at the maximum tube current. CONCLUSIONS: A DE acquisition technique for a photon-counting DBT imaging system has been developed and optimized.

Optimization of a dual-energy contrast-enhanced technique for a photon-counting digital breast tomosynthesis system: II. An experimental validation.

PURPOSE: Previously, the authors developed a dual-energy (DE) acquisition technique for a photon-counting digital breast tomosynthesis (DBT) imaging system. Low-energy (LE) and high-energy (HE) images are acquired in a single scan by covering alternate slits of a multislit prepatient collimator with Sn and Cu, respectively. A theoretical model was used to optimize the technique. In this article, an experimental validation of this technique is presented. METHODS: Experiments were performed on a prototype DBT system. LE and HE projection images were acquired sequentially; either a Sn or a Cu filter was positioned in the filter holder at the exit window of the x-ray tube. Sn filters from 0.113 to 0.242 mm thick and Cu filters from 0.103 to 0.267 mm were used. The images were acquired with a W target at 49 kV. Tomographic images, hereafter referred to as DBT images, were reconstructed using a shift-and-add algorithm. DE-DBT images were obtained by weighted logarithmic subtraction of the LE and HE images. Weighting factors w(t) that optimally cancel breast tissues with two different glandularities were assessed for 20-80 mm thick phantoms with 0%, 50%, and 100% glandularity. The mean and standard deviation in the per-pixel signal intensity (SI) were calculated in the DBT images. These data were used to calculate signal-difference-to-noise ratios (SDNRs) between iodine enhanced and nonenhanced polymethyl methacrylate backgrounds. To illustrate the feasibility of the technique, DE-DBT images of a structured phantom containing iodine disks were assessed. The experimental results were compared against the values obtained from a theoretical model of the imaging system. RESULTS: The average difference between theoretical and experimental w(t) was found to range from 8% to 21%. Experimental w(t) values increase with phantom thickness and Cu thickness, depend somewhat on Sn thickness, and vary more as a function of breast composition in thick breasts than in thin breasts. Theoretical and experimental mean and standard deviation in the per-pixel SI differ by -7% to 10% and by -3% to 4%. Theoretical and experimental SDNR values differ, on average, by 1.5%. Iodine concentrations can be predicted from SDNR; the relationship can be accurately fit to a quadratic. In the images of the structured phantom, iodine concentrations of 1 mg/cm2 and larger are discernable. CONCLUSIONS: The strong agreement between experimental and theoretical results in this article indicates that the authors' computer model is accurate.

Breast percent density: estimation on digital mammograms and central tomosynthesis projections.

PURPOSE: To evaluate inter- and intrareader agreement in breast percent density (PD) estimation on clinical digital mammograms and central digital breast tomosynthesis (DBT) projection images. MATERIALS AND METHODS: This HIPAA-compliant study had institutional review board approval; all patients provided informed consent. Breast PD estimation was performed on the basis of anonymized digital mammograms and central DBT projections in 39 women (mean age, 51 years; range, 31-80 years). All women had recently detected abnormalities or biopsy-proved cancers. PD was estimated by three experienced readers on the mediolateral oblique views of the contralateral breasts by using software; each reader repeated the estimation after 2 months. Spearman correlations of inter- and intrareader and intermodality PD estimates, as well as kappa statistics between categoric PD estimates, were computed. RESULTS: High correlation (rho = 0.91) was observed between PD estimates on digital mammograms and those on central DBT projections, averaged over all estimations; the corresponding kappa coefficient (0.79) indicated substantial agreement. Mean interreader agreement for PD estimation on central DBT projections (rho = 0.85 +/- 0.05 [standard deviation]) was significantly higher (P < .01) than that for PD estimation on digital mammograms (rho = 0.75 +/- 0.05); the corresponding kappa coefficients indicated substantial (kappa = 0.65 +/- 0.12) and moderate (kappa = 0.55 +/- 0.14) agreement for central DBT projections and digital mammograms, respectively. CONCLUSION: High correlation between PD estimates on digital mammograms and those on central DBT projections suggests the latter could be used until a method for PD estimation based on three-dimensional reconstructed images is introduced. Moreover, clinical PD estimation is possible with reduced radiation dose, as each DBT projection was acquired by using about 22% of the dose for a single mammographic projection.

The effect of scatter and glare on image quality in contrast-enhanced breast imaging using an a-Si/CsI(TI) full-field flat panel detector.

The purpose of this study is to evaluate the performance of an antiscatter grid and its potential benefit on image quality for a full-field digital mammography (FFDM) detector geometry at energies typical for temporal subtraction contrast-enhanced (CE) breast imaging. The signal intensities from primary, scatter, and glare were quantified in images acquired with an a-Si/CsI(T1) FFDM detector using a Rh target and a 0.27 mm Cu filter at tube voltages ranging from 35 to 49 kV. Measurements were obtained at the center of the irradiation region of 20-80 mm thick breast-equivalent phantoms. The phantoms were imaged with and without an antiscatter grid. Based on these data, the performance of the antiscatter grid was determined by calculating the primary and scatter transmission factors (T(P) and T(S)) and Bucky factors (Bf). In addition, glare-to-primary ratios (GPRs) and scatter-to-primary ratios (SPRs) were quantified. The effect of the antiscatter grid on the signal-difference-to-noise ratio (SDNR) was also assessed. It was found that T(P) increases with kV but does not depend on the phantom thickness; T(P) values between 0.81 and 0.84 were measured. T(S) increases with kV and phantom thickness; T(S) values between 0.13 and 0.21 were measured. Bf decreases with kV and increases with phantom thickness; Bf ranges from 1.4 to 2.1. GPR is nearly constant, varying from 0.10 to 0.11. SPR without an antiscatter grid (SPR-) ranges from 0.35 to 1.34. SPR- decreases by approximately 9% from 35 to 49 kV for a given phantom thickness and is 3.5 times larger for an 80 mm thick breast-equivalent phantom than for a 20 mm thick breast-equivalent phantom. SPR with an antiscatter grid (SPR+) ranges from 0.06 to 0.31. SPR+ increases by approximately 23% from 35 to 49 kV for a given phantom thickness; SPR+ is four times larger for an 80 mm breast-equivalent phantom than for a 20 mm breast-equivalent phantom. When imaging a 25 mm PMMA plate at the same mean glandular dose with and without an antiscatter grid, the SDNR is 4% greater with a grid than without. For an 75 mm PMMA plate, the SDNR is 20% greater with a grid. In conclusion, at the higher x-ray energy range used for CE-DM and CE-DBT, an antiscatter grid significantly reduces SPR and improves SDNR. These effects are most pronounced for thick breasts.

Parenchymal texture analysis in digital breast tomosynthesis for breast cancer risk estimation: a preliminary study.

RATIONALE AND OBJECTIVES: Studies have demonstrated a relationship between mammographic parenchymal texture and breast cancer risk. Although promising, texture analysis in mammograms is limited by tissue superposition. Digital breast tomosynthesis (DBT) is a novel tomographic x-ray breast imaging modality that alleviates the effect of tissue superposition, offering superior parenchymal texture visualization compared to mammography. The aim of this study was to investigate the potential advantages of DBT parenchymal texture analysis for breast cancer risk estimation. MATERIALS AND METHODS: DBT and digital mammographic (DM) images of 39 women were analyzed. Texture features, shown in previous studies with mammograms to correlate with cancer risk, were computed from the retroareolar breast region. The relative performances of the DBT and DM texture features were compared in correlating with two measures of breast cancer risk: (1) the Gail and Claus risk estimates and (2) mammographic breast density. Linear regression was performed to model the association between texture features and increasing levels of risk. RESULTS: No significant correlation was detected between parenchymal texture and the Gail and Claus risk estimates. Significant correlations were observed between texture features and breast density. Overall, the DBT texture features demonstrated stronger correlations with breast percent density than DM features (P < or = .05). When dividing the study population into groups of increasing breast percent density, the DBT texture features appeared to be more discriminative, having regression lines with overall lower P values, steeper slopes, and higher R(2) estimates. CONCLUSION: Although preliminary, the results of this study suggest that DBT parenchymal texture analysis could provide more accurate characterization of breast density patterns, which could ultimately improve breast cancer risk estimation.

Initial clinical experience with contrast-enhanced digital breast tomosynthesis.

RATIONALE AND OBJECTIVES: 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). MATERIALS AND METHODS: 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. RESULTS: Initial experience suggests that CE-DBT provides morphologic and vascular characteristics of breast lesions qualitatively concordant with that of digital mammography and MR. CONCLUSION: As an adjunct to digital mammography, CE-DBT may be a potential alternative tool for breast lesion morphologic and vascular characterization.

Validation of MTF measurement for digital mammography quality control.

The modulation transfer function (MTF) describes the spatial resolution properties of imaging systems. In this work, the accuracy of our implementation of the edge method for calculating the presampled MTF was examined. Synthetic edge images with known MTF were used as gold standards for determining the robustness of the edge method. These images simulated realistic data from clinical digital mammography systems, and contained intrinsic system factors that could affect the MTF accuracy, such as noise, scatter, and flat-field nonuniformities. Our algorithm is not influenced by detector dose variations for MTF accuracy up to 1/2 the sampling frequency. We investigated several methods for noise reduction, including truncating the supersampled line spread function (LSF), windowing the LSF, applying a local exponential fit to the LSF, and applying a monotonic constraint to the supersampled edge spread function. Only the monotonic constraint did not introduce a systematic error; the other methods could result in MTF underestimation. Overall, our edge method consistently computed MTFs which were in good agreement with the true MTF. The edge method was then applied to images from a commercial storage-phosphor based digital mammography system. The calculated MTF was affected by the size (sides of 2.5, 5, or 10 cm) and the composition (lead or tungsten) of the edge device. However, the effects on the MTF were observed only with regard to the low frequency drop (LFD). Scatter nonuniformity was dependent on edge size, and could lead to slight underestimation of LFD. Nevertheless, this negative effect could be minimized by using an edge of 5 cm or larger. An edge composed of lead is susceptible to L-fluorescence, which causes overestimation of the LFD. The results of this work are intended to underline the need for clear guidelines if the MTF is to be given a more crucial role in acceptance tests and routine assessment of digital mammography systems: the MTF algorithm and edge object test tool need to be publicly validated.

Quantification of Al-equivalent thickness of just visible microcalcifications in full field digital mammograms.

Characterization of digital mammography systems is often performed by means of contrast-detail curves using a homogeneous phantom with inserts of different sizes and thicknesses. In this article, a more direct measure of the threshold contrast-detail characteristics of microcalcifications in clinical mammograms is proposed, which also takes into account routine processing and display. The proposed method scores the detectability of simulated microcalcifications with known size and aluminum-equivalent thickness. Thickness estimates, based on x-ray transmission coefficients, were first validated for Al particles. The same approach was then applied to associate Al-equivalent thickness with simulated microcalcifications. Thirty-five mammograms of patients were acquired using a full field digital mammography (FFDM) system operating under standard exposure conditions. Different microcalcifications were simulated using templates of real microcalcifications as described in Med. Phys. 30, 2234-2240 (2003). These templates were first modified such that they simulated a template of the same microcalcification for an ideally sharp detector. They were then adjusted for the imaging characteristics of the FFDM, beam quality, and breast thickness. Microcalcification sizes in the image plane ranged from 200 to 800 microm. Their peak Al-equivalent thickness varied between 70 and 1000 microm. Software phantoms were created. They consisted of 0-10 simulated microcalcifications randomly distributed in 2 cm by 2 cm frames embedded within digital mammograms. Routine processing and printing followed. Three experienced radiologists recorded the locations of the microcalcifications, and confidence ratings were given. Free response receiver operating characteristics (FROC) analysis was performed. Using a binary score, the fractions of detected microcalcifications were plotted as a function of equivalent diameter for the different Al-equivalent thicknesses. Pair-wise agreement of the detected microcalcifications was calculated for the different Al-equivalent thickness groups. The FROC curves of each radiologist indicated similar true positive fractions for a given number of false positives per image. One radiologist applied a more conservative scoring. Detected fractions for the different sizes of the microcalcifications showed the same trend for all observers. In addition, the observer with the least FP also detected less microcalcifications. The pair-wise agreement of the detected microcalcifications was good. The average detected fractions were >0.5 for microcalcifications with equivalent diameter >400 microm and Al-equivalent thickness >400 microm. An average detected fraction >0.5 was also seen for microcalcifications with equivalent diameter <400 microm and equivalent thickness >800 microm. The detected fractions of smaller microcalcifications were <0.5. The results obtained with this method indicate that it may be possible to quantify the performance of a digital mammography detector including processing and viewing for the detection of microcalcifications. We hypothesize that the FROC curves and detected fractions of simulated microcalcifications of different sizes reflect the clinical reality.

Development and validation of a simulation procedure to study the visibility of micro calcifications in digital mammograms.

The visibility of micro calcifications is a determining factor for digital mammography. To address the problem of quantification, we developed a procedure to simulate micro calcifications into real mammograms. First, the shapes, sizes and x-ray transmission coefficients of real micro calcifications were derived from the appearance of biopsy specimens in the raw data of magnified, digital images acquired at 27 kVp and Mo/Mo anode-filter combination. This allowed us to create "ideal templates" of micro calcifications. The x-ray transmissions of the real micro calcifications values were expressed in Al-equivalent thickness. This made it possible to recalculate the x-ray transmission characteristics of a particular ideal template for other x-ray beam qualities. Extra corrections for differences in spatial resolution were based on the presampled two-dimensional modulation transfer functions and on the difference in pixel size. Three radiologists compared the appearance of real and simulated micro calcifications in a two-alternative forced choice (2AFC) evaluation. They perceived no differences between real and simulated lesions. Preliminary results show that it is possible to simulate micro calcifications with well defined characteristics that are indistinguishable from real ones. It should be noted, however, that the full potential of the approach has not been proven. In future work, these templates may be useful to evaluate particular aspects of digital mammograms, such as the effects of processing and of viewing conditions on the visibility of micro calcifications.