For Full-field Digital Mammography Research Articles

Assessment of local diagnostic reference levels (LDRLS) for full-field digital mammography (FFDM) and digital breast tomosynthesis (DBT) mammography in Tamil Nadu, India.

The purpose of this study was to assess local diagnostic reference levels (LDRLs) for full-field digital mammography (FFDM) and digital breast tomosynthesis (DBT) mammography in India. Data from 1500 women were collected from five different mammography facilities in major cities in Tamil Nadu, India. The mean of mean glandular dose were used to arrive at an LDRL. The noted mean compressed breast thickness was 55.26±3.4. The recorded mean MGDs for the five centres were 3.1±0.1 and 3.8±0.2mGy for FFDM and DBT, respectively. The 75th percentile value for all five centers is 3.3 and 4.0mGy for FFDM and DBT, respectively. The LDRLs found in the current study were also compared with those from earlier studies conducted in other nations, such as the United Kingdom, Malaysia, Morocco, and Ghana. The present study is the first of its kind to determine the LDRL for the FFDM and DBT scanners operating in the Tamil Nadu region, India, and is proposed as a starting point that will allow professionals to evaluate and optimize their practice. Furthermore, similar studies in other regions of India are necessary in order to establish National DRLs.

Establishment of national diagnostic reference levels for full field digital mammography and digital breast tomosynthesis in Lebanon

This study aims to establish Lebanese national diagnostic reference levels (NDRLs) for full field digital mammography (FFDM) and digital breast tomosynthesis (DBT). Data were collected from 34% of the total number of health facilities with FFDM and/or DBT units in Lebanon. NDRLs were set as the third quartile of mammography units’ median value of average glandular dose (AGD). NDRLs for different compressed breast thickness (CBT) and age groups were also proposed. Statistical analysis were performed to test the difference of AGD between cranio caudal (CC) and medio lateral oblique (MLO) views, FFDM and DBT, and AGD across health facilities, CBT and age groups. Data from 2803 women with a total of 10462 images were included in the study. For FFDM and DBT, NDRLs for CC and MLO views were equal to 1.85 and 2.24 mGy, and 2.65 and 3.04 mGy, respectively. Lebanese NDRLs were higher than most published DRLs while remaining below the European Commission’s maximum acceptable dose level (2.5 mGy) for FFDM. AGD increased significantly (p < 0.05) with the increase in CBT for both views and techniques. This first set of mammography DRLs reveals the need for optimizing the radiation exposure in Lebanon and will serve as a national/international benchmark.

Local Diagnostic Reference Levels for Full-Field Digital Mammography and Digital Breast Tomosynthesis in a Tertiary Hospital in Malaysia.

A set of national diagnostic reference levels (DRLs) was established in Malaysia for a range of breast thicknesses in 2013, but no updates for full-field digital mammography (FFDM) and digital breast tomosynthesis (DBT). Due to the increasing number of DBTs used and concern over radiation exposure, this study aimed to explore and establish local diagnostic reference levels for FFDM and DBT in Malaysia health facilities at different compressed breast thickness (CBT) ranges. The CBT, kilovoltage peak (kVp), Entrance surface dose (ESD), and average glandular dose (AGD) were retrospectively extracted from the mammography Digital Imaging and Communications in Medicine (DICOM) header. The 75th and 95th percentile values were obtained for the AGD distribution of each mammography projection for three sets of CBT range. The difference in AGD values between FFDM and DBT at three CBT ranges was determined. The DRLs for FFDM were 1.13 mGy, 1.52 mGy, and 2.87 mGy, while DBT were 1.18 mGy, 1.88 mGy, and 2.78 mGy at CBT ranges of 20–39 mm, 40–59 mm, and 60–99 mm, respectively. The AGD of DBT was significantly higher than FFDM for both mammographic views (p < 0.005). All three CBT groups showed a significant difference in AGD values for FFDM and DBT (p < 0.005). The local DRLs from this study were lower than the national DRLs, with the AGD of FFDM significantly lower than DBT.

Comparison of Outcomes for One-View Asymmetries Recalled From Digital Breast Tomosynthesis Versus Full-Field Digital Mammography Screening Examinations.

BACKGROUND. Recall rates are lower for digital breast tomosynthesis (DBT) than for full-field digital mammography (FFDM). This difference could have important implications with respect to one-view asymmetries given that missed cancers are often visible on one view. OBJECTIVE. The purpose of this study is to compare the outcomes of one-view asymmetries recalled from DBT versus FFDM screening examinations and to determine predictors of malignancy among recalled asymmetries. METHODS. This retrospective study first determined recall rates associated with one-view asymmetries for screening mammography performed using DBT and FFDM from July 14, 2016, through July 14, 2020. Further analyses included patients recalled for a one-view asymmetry who completed subsequent diagnostic workup and all recommended follow-up. Patient and cancer characteristics were extracted from the electronic health record. RESULTS. The recall rate associated with asymmetries was lower for DBT screening (2.5% [3169/128,755]) than for FFDM screening (3.4% [815/23,898]) (p < .001). Further analyses of patients who completed diagnostic workup and subsequent follow-up included 3119 patients (mean age, 57 years) for DBT screening and 811 patients (mean age, 56 years) for FFDM screening. Distribution of final BI-RADS categories from subsequent diagnostic workup was not different between the two modalities (p > .99). The frequency of malignancy was not different between asymmetries recalled from DBT (1.7% [54/3119]) and FFDM (1.7% [14/811]) (p > .99). Malignant asymmetries identified on FFDM versus DBT were more frequently associated with architectural distortion on diagnostic workup (35.7% [5/14] vs 9.3% [5/54]) (p < .001) and were more commonly invasive ductal carcinoma (92.9% vs 57.4%) and less commonly invasive lobular carcinoma (0.0% vs 24.1%) (p = .05). In multivariable analysis, independent predictors of malignancy among recalled asymmetries from DBT were age (for 55-69 years, odds ratio [OR] = 2.40 [p = .04]; for ≥ 70 years, OR = 7.93 [p < .001]; reference, < 55 years) and breast density (not dense, OR = 2.47 [p = .001]; reference, dense breasts). CONCLUSION. Recalled asymmetries were less frequent for DBT than for FFDM. The malignancy rate was low for both modalities (1.7%). Age 55 years old and older and lower breast density predicted malignancy for DBT-recalled asymmetries. CLINICAL IMPACT. Our results support the use of DBT to reduce unnecessary recalls without altering PPV for asymmetry-associated malignancies. Patient factors should be considered when assessing whether a potential asymmetry on DBT screening represents overlapping fibroglandular tissue or a suspicious finding that requires diagnostic workup.

Comparison between two packages for pectoral muscle removal on mammographic images

BackgroundPectoral muscle removal is a fundamental preliminary step in computer-aided diagnosis systems for full-field digital mammography (FFDM). Currently, two open-source publicly available packages (LIBRA and OpenBreast) provide algorithms for pectoral muscle removal within Matlab environment. PurposeTo compare performance of the two packages on a single database of FFDM images. MethodsOnly mediolateral oblique (MLO) FFDM was considered because of large presence of pectoral muscle on this type of projection. For obtaining ground truth, pectoral muscle has been manually segmented by two radiologists in consensus. Both LIBRA’s and OpenBreast’s removal performance with respect to ground truth were compared using Dice similarity coefficient and Cohen-kappa reliability coefficient; Wilcoxon signed-rank test has been used for assessing differences in performances; Kruskal–Wallis test has been used to verify possible dependence of the performance from the breast density or image laterality.ResultsFFDMs from 168 consecutive women at our institution have been included in the study. Both LIBRA’s Dice-index and Cohen-kappa were significantly higher than OpenBreast (Wilcoxon signed-rank test P < 0.05). No dependence on breast density or laterality has been found (Kruskal–Wallis test P > 0.05). Conclusion: Libra has a better performance than OpenBreast in pectoral muscle delineation so that, although our study has not a direct clinical application, these results are useful in the choice of packages for the development of complex systems for computer-aided breast evaluation.

Local diagnostic reference levels (LDRLs) for full-field digital mammography (FFDM) and digital breast tomosynthesis (DBT) procedures in Morocco

IntroductionThe objective of this study was to establish local diagnostic reference levels (LDRLs) for the full-field digital mammography (FFDM) and tomosynthesis (DBT) in Moroccan health facilities. MethodsData from 146 women were collected from three facilities. The proposed DRLs were defined as the 75th percentile of the mean average glandular dose (AGD) distribution. ResultsThe mean AGD recorded in this study for the three centers was 1.47 mGy for all centers, and 1.42 mGy and 1.64 mGy for the CC and MLO projections, respectively. The mean compressed breast thickness (CBT) values recorded in this current study were 55 mm, the LDRLs reported for all centers was 1.7 mGy, the CC projection was 1.6 mGy, and the MLO projection was 1.8 mGy. In addition, the LDRLs reported in the current study were compared with those from previous studies for other countries, including the United Kingdom, Japan, Ghana, and Sri Lanka. ConclusionThis work provides an assessment of local DRLs for mammography in Morocco and is suggested as a starting point that will allow professionals to evaluate and optimize their practice. Furthermore, the definition of national DRLs is a necessary process in optimizing Moroccan medical exposures.

Comparison of Mean Glandular Dose between Full-Field Digital Mammography and Digital Breast Tomosynthesis.

Early detection of breast cancer is diagnosed using mammography, the gold standard in breast screening. However, its increased use also provokes radiation-induced breast malignancy. Thus, monitoring and regulating the mean glandular dose (MGD) is essential. The purpose of this study was to determine MGD for full-field digital mammography (FFDM) and digital breast tomosynthesis (DBT) in the radiology department of a single centre. We also analysed the exposure factors as a function of breast thickness. A total of 436 patients underwent both FFDM and DBT. MGD was auto calculated by the mammographic machine for each projection. Patients’ data included compressed breast thickness (CBT), peak kilovoltage (kVp), milliampere-seconds (mAs) and MGD (mGy). Result analysis showed that there is a significant difference in MGD between the two systems, namely FFDM and DBT. However, the MGD values in our centre were comparable to other centres, as well as the European guideline (<2.5 mGy) for a standard breast. Although DBT improves the clinical outcome and quality of diagnosis, the risk of radiation-induced carcinogenesis should not be neglected. Regular quality control testing on mammography equipment must be performed for dose monitoring in women following a screening mammography in the future.

Synthesis of Mammogram From Digital Breast Tomosynthesis Using Deep Convolutional Neural Network With Gradient Guided cGANs.

Synthetic digital mammography (SDM), a 2D image generated from digital breast tomosynthesis (DBT), is used as a potential substitute for full-field digital mammography (FFDM) in clinic to reduce the radiation dose for breast cancer screening. Previous studies exploited projection geometry and fused projection data and DBT volume, with different post-processing techniques applied on re-projection data which may generate different image appearance compared to FFDM. To alleviate this issue, one possible solution to generate an SDM image is using a learning-based method to model the transformation from the DBT volume to the FFDM image using current DBT/FFDM combo images. In this study, we proposed to use a deep convolutional neural network (DCNN) to learn the transformation to generate SDM using current DBT/FFDM combo images. Gradient guided conditional generative adversarial networks (GGGAN) objective function was designed to preserve subtle MCs and the perceptual loss was exploited to improve the performance of the proposed DCNN on perceptual quality. We used various image quality criteria for evaluation, including preserving masses and MCs which are important in mammogram. Experiment results demonstrated progressive performance improvement of network using different objective functions in terms of those image quality criteria. The methodology we exploited in the SDM generation task to analyze and progressively improve image quality by designing objective functions may be helpful to other image generation tasks.

Computational reader design and statistical performance evaluation of an in-silico imaging clinical trial comparing digital breast tomosynthesis with full-field digital mammography.

A recent study reported on an in-silico imaging trial that evaluated the performance of digital breast tomosynthesis (DBT) as a replacement for full-field digital mammography (FFDM) for breast cancer screening. In this in-silico trial, the whole imaging chain was simulated, including the breast phantom generation, the x-ray transport process, and computational readers for image interpretation. We focus on the design and performance characteristics of the computational reader in the above-mentioned trial. Location-known lesion (spiculated mass and clustered microcalcifications) detection tasks were used to evaluate the imaging system performance. The computational readers were designed based on the mechanism of a channelized Hotelling observer (CHO), and the reader models were selected to trend human performance. Parameters were tuned to ensure stable lesion detectability. A convolutional CHO that can adapt a round channel function to irregular lesion shapes was compared with the original CHO and was found to be suitable for detecting clustered microcalcifications but was less optimal in detecting spiculated masses. A three-dimensional CHO that operated on the multiple slices was compared with a two-dimensional (2-D) CHO that operated on three versions of 2-D slabs converted from the multiple slices and was found to be optimal in detecting lesions in DBT. Multireader multicase reader output analysis was used to analyze the performance difference between FFDM and DBT for various breast and lesion types. The results showed that DBT was more beneficial in detecting masses than detecting clustered microcalcifications compared with FFDM, consistent with the finding in a clinical imaging trial. Statistical uncertainty smaller than 0.01 standard error for the estimated performance differences was achieved with a dataset containing approximately 3000 breast phantoms. The computational reader design methodology presented provides evidence that model observers can be useful in-silico tools for supporting the performance comparison of breast imaging systems.

Technical challenges in generalizing calibration techniques for breast density measurements.

PurposeWe are developing a calibration methodology for full‐field digital mammography (FFDM). Calibration compensates for image acquisition technique influences on the pixel representation, ideally producing improved inter‐image breast density estimates. This approach relies on establishing references with rigid breast tissue‐equivalent phantoms (BTEs) and requires an accurate estimate of the compressed breast thickness because the system readout is nominal. There is also an attenuation mismatch between adipose breast tissue and the adipose BTE that was noted in our previous work. It is referred to as the “attenuation anomaly” and addressed in this report. The objectives are to evaluate methods to correct for the compressed breast thickness and compensate for the attenuation anomaly.MethodsThickness correction surfaces were established with a deformable phantom (DP) using both image and physical measurements for three direct x‐ray conversion FFDM units. The Cumulative Sum serial quality control procedure was established to ensure the thickness correction measurements were stable over time by imaging and calibrating DPs biweekly in lieu of physical measurements. The attenuation anomaly was addressed by evaluating adipose image regions coupled with an optimization technique to adjust the adipose calibration data. We compared calibration consistency across matched left and right cranial caudal (CC) mammographic views (n = 199) with and without corrections using Bland–Altman plots. These plots were complemented by comparing the right and left breast calibrated average (μa) and population distribution mean (ma) with 95% confidence intervals and difference distribution variances with the F‐test for uncorrected and corrected data.ResultsThickness correction surfaces were well approximated as tilted planes and were dependent upon compression force. A correction was developed for the attenuation anomaly. All paddles (large and small paddles for all units) exhibited similar tilt as a function of force. Without correction, ma = 0.92 (−1.77, 3.62) was not significantly different from zero with many negative μa samples. The thickness correction produced a significant shift in the μa distribution in the positive direction with ma = 13.99 (11.17, 16.80) and reduced the difference distribution variance significantly (P < 0.0001). Applying both corrections in tandem gave ma = 22.83 (20.32, 25.34), representing another significant positive shift in comparison with the thickness correction in isolation. Thickness corrections were stable over approximately a 2‐year timeframe for all units.ConclusionThese correction techniques are valid approaches for addressing technical problems with calibration that relies on reference phantoms. The efficacy of the calibration methodology will require validation with clinical endpoints in future studies.

Strategies for Decreasing Screening Mammography Recall Rates While Maintaining Performance Metrics

This study aimed to determine the impact of interventions designed to reduce screening mammography recall rates on screening performance metrics. We assessed baseline performance for full-field digital mammography (FFDM) and digital breast tomosynthesis mammography (DBT) for a 3-year period before intervention. The first intervention sought to increase awareness of recalls from screening mammography. Breast imagers discussed their perceptions regarding screening recalls and were required to review their own recalled cases, including outcomes of diagnostic evaluation and biopsy. The second intervention implemented consensus double reading of all recalls, requiring two radiologists to agree if recall was necessary. Recall rates, cancer detection rates, and positive predictive value 1 (PPV1) were compared before and after each intervention. The baseline recall rate, cancer detection rate, and PPV1 were 11.1%, 3.8/1000, and 3.4%, respectively, for FFDM, and 7.6%, 4.8/1000, and 6.0%, respectively, for DBT. Recall rates decreased significantly to 9.2% for FFDM and to 6.6% for DBT after the first intervention promoting awareness, as well as to 9.9% for FFDM after the second intervention implementing group consensus. PPV1 increased significantly to 5.7% for FFDM and to 9.0% for DBT after the second intervention. Cancer detection rate did not significantly change with the implementation of these interventions. An average of 2.3 minutes was spent consulting for each recall. Reduction in recall rates is desirable, provided performance metrics remain favorable. Our interventions improved performance and could be implemented in other breast imaging settings.

Compression forces used in the Norwegian Breast Cancer Screening Program.

Compression is used in mammography to reduce breast thickness, which is claimed to improve image quality and reduce radiation dose. In the Norwegian Breast Cancer Screening Program (NBCSP), the recommended range of compression force for full-field digital mammography (FFDM) is 11-18 kg (108-177 N). This is the first study to investigate the compression force used in the programme. The study included information from 17,951 randomly selected females screened with FFDM at 14 breast centres in the NBCSP, during January-March 2014. We investigated the applied compression force on the left breast in craniocaudal and mediolateral oblique views for breast centres, mammography machines within the breast centres and for the radiographers. The mean compression force for all mammograms in the study was 116 N and ranged from 91 N to 147 N between the breast centres. The variation in compression force was wider between the breast centres than that between mammography machines (range 137-155 N) and radiographers (95-143 N) within one breast centre. Approximately 59% of the mammograms in the study complied with the recommended range of compression force. A wide variation in applied compression force was observed between the breast centres in the NBCSP. This variation indicates a need for evidence-based recommendations for compression force aimed at optimizing the image quality and individualizing breast compression. Advances in knowledge: There was a wide variation in applied compression force between the breast centres in the NBCSP. The variation was wider between the breast centres than that between mammography machines and radiographers within one breast centre.

Clinical utility of the radiation dose management system for full field digital mammography (FFDM): In Asian women with dense breast tissue.

70 Background: In the perspectives on radiation dose, there are consensus of importance on radiation dose management for patient safety and trends to reduce radiation dose for patient safety. Radiation dose management system like Radimetrics helps radiologists optimize protocols and reduce radiation dose. There is no previous data applying the radiation dose management system in mammography.We investigated the clinical usefulness of the radiation dose management system in full field digital mammography (FFDM) using commercial Radiation dose management system. Methods: We did radiation dose tracking, monitoring, and statistics through the existed radiation dose management system (Radimetrics). The utilization data, parameter, and dose report were sent to the conventional picture archiving and communication system (PACS) and the Radimetrics enterprise flat form. And we could review the data including age, kVp, mAs, breast thickness, and compression force under the web base. We analyzed the breast composition depending on the BI-RADS assessment categories. We evaluated the correlation of the age, kVp, mAs, breast thickness, compression force, and breast composition with organ dose of breast. Additionally, in patients with above diagnostic reference level ( ≥ 75%) of radiation dose, the causes were analyzed. Results: From February to May 2015, 3076 sets of FFDM were performed and sent to PACS and the radiation dose management system (Radimetrics). In total 3076 sets, 2520 were routine bilateral FFDM with 4 views. The mean glandular dose was 6.59± 2.87 mGy (2.63-18.46). In the correlation analysis, the age had moderate negative linear relationship with organ dose. The mAs and breast composition had moderate positive linear relationship with organ dose. The kVp, breast thickness, and compression force had weak positive linear relationship with organ dose. Patients with above diagnostic reference level ( ≥ 75%) of radiation dose showed dense breast composition and thicker breast. Conclusions: The radiation dose management system is useful in FFDM. Especially in Asian women with thick and dense breasts, radiation dose should be carefully managed.

Digital mammographic density and breast cancer risk: a case–control study of six alternative density assessment methods

IntroductionMammographic density is a strong breast cancer risk factor and a major determinant of screening sensitivity. However, there is currently no validated estimation method for full-field digital mammography (FFDM).MethodsThe performance of three area-based approaches (BI-RADS, the semi-automated Cumulus, and the fully-automated ImageJ-based approach) and three fully-automated volumetric methods (Volpara, Quantra and single energy x-ray absorptiometry (SXA)) were assessed in 3168 FFDM images from 414 cases and 685 controls. Linear regression models were used to assess associations between breast cancer risk factors and density among controls, and logistic regression models to assess density-breast cancer risk associations, adjusting for age, body mass index (BMI) and reproductive variables.ResultsQuantra and the ImageJ-based approach failed to produce readings for 4% and 11% of the participants. All six density assessment methods showed that percent density (PD) was inversely associated with age, BMI, being parous and postmenopausal at mammography. PD was positively associated with breast cancer for all methods, but with the increase in risk per standard deviation increment in PD being highest for Volpara (1.83; 95% CI: 1.51 to 2.21) and Cumulus (1.58; 1.33 to 1.88) and lower for the ImageJ-based method (1.45; 1.21 to 1.74), Quantra (1.40; 1.19 to 1.66) and SXA (1.37; 1.16 to 1.63). Women in the top PD quintile (or BI-RADS 4) had 8.26 (4.28 to 15.96), 3.94 (2.26 to 6.86), 3.38 (2.00 to 5.72), 2.99 (1.76 to 5.09), 2.55 (1.46 to 4.43) and 2.96 (0.50 to 17.5) times the risk of those in the bottom one (or BI-RADS 1), respectively, for Volpara, Quantra, Cumulus, SXA, ImageJ-based method, and BI-RADS (P for trend <0.0001 for all). The ImageJ-based method had a slightly higher ability to discriminate between cases and controls (area under the curve (AUC) for PD = 0.68, P = 0.05), and Quantra slightly lower (AUC = 0.63; P = 0.06), than Cumulus (AUC = 0.65).ConclusionsFully-automated methods are valid alternatives to the labour-intensive "gold standard" Cumulus for quantifying density in FFDM. The choice of a particular method will depend on the aims and setting but the same approach will be required for longitudinal density assessments.Electronic supplementary materialThe online version of this article (doi:10.1186/s13058-014-0439-1) contains supplementary material, which is available to authorized users.

Automated Percentage of Breast Density Measurements for Full-field Digital Mammography Applications

Increased mammographic breast density is a significant risk factor for breast cancer. A reproducible, accurate, and automated breast density measurement is required for full-field digital mammography (FFDM) to support clinical applications. We evaluated a novel automated percentage of breast density measure (PDa) and made comparisons with the standard operator-assisted measure (PD) using FFDM data. We used a nested breast cancer case-control study matched on age, year of mammogram and diagnosis with images acquired from a specific direct x-ray conversion FFDM technology. PDa was applied to the raw and clinical display (or processed) representation images. We evaluated the transformation (pixel mapping) of the raw image, giving a third representation (raw-transformed), to improve the PDa performance using differential evolution optimization. We applied PD to the raw and clinical display images as a standard for measurement comparison. Conditional logistic regression was used to estimate the odd ratios (ORs) for breast cancer with 95% confidence intervals (CI) for all measurements; analyses were adjusted for body mass index. PDa operates by evaluating signal-dependent noise (SDN), captured as local signal variation. Therefore, we characterized the SDN relationship to understand the PDa performance as a function of data representation and investigated a variation analysis of the transformation. The associations of the quartiles of operator-assisted PD with breast cancer were similar for the raw (OR: 1.00 [ref.]; 1.59 [95% CI, 0.93-2.70]; 1.70 [95% CI, 0.95-3.04]; 2.04 [95% CI, 1.13-3.67]) and clinical display (OR: 1.00 [ref.]; 1.31 [95% CI, 0.79-2.18]; 1.14 [95% CI, 0.65-1.98]; 1.95 [95% CI, 1.09-3.47]) images. PDa could not be assessed on the raw images without preprocessing. However, PDa had similar associations with breast cancer when assessed on 1) raw-transformed (OR: 1.00 [ref.]; 1.27 [95% CI, 0.74-2.19]; 1.86 [95% CI, 1.05-3.28]; 3.00 [95% CI, 1.67-5.38]) and 2) clinical display (OR: 1.00 [ref.]; 1.79 [95% CI, 1.04-3.11]; 1.61 [95% CI, 0.90-2.88]; 2.94 [95% CI, 1.66-5.19]) images. The SDN analysis showed that a nonlinear relationship between the mammographic signal and its variation (ie, the biomarker for the breast density) is required for PDa. Although variability in the transform influenced the respective PDa distribution, it did not affect the measurement's association with breast cancer. PDa assessed on either raw-transformed or clinical display images is a valid automated breast density measurement for a specific FFDM technology and compares well against PD. Further work is required for measurement generalization.

Full-field digital mammography image data storage reduction using a crop tool.

The storage requirements for full-field digital mammography (FFDM) in a picture archiving and communication system are significant, so methods to reduce the data set size are needed. A FFDM crop tool for this purpose was designed, implemented, and tested. A total of 1,651 screening mammography cases with bilateral FFDMs were included in this study. The images were cropped using a DICOM editor while maintaining image quality. The cases were evaluated according to the breast volume (1/4, 2/4, 3/4, and 4/4) in the craniocaudal view. The image sizes between the cropped image group and the uncropped image group were compared. The overall image quality and reader's preference were independently evaluated by the consensus of two radiologists. Digital storage requirements for sets of four uncropped to cropped FFDM images were reduced by 3.8 to 82.9 %. The mean reduction rates according to the 1/4-4/4 breast volumes were 74.7, 61.1, 38, and 24 %, indicating that the lower the breast volume, the smaller the size of the cropped data set. The total image data set size was reduced from 87 to 36.7 GB, or a 57.7 % reduction. The overall image quality and the reader's preference for the cropped images were higher than those of the uncropped images. FFDM mammography data storage requirements can be significantly reduced using a crop tool.

Comparison of dry laser printer versus paper printer in full-field digital mammography

Paper printers have been used to document radiological findings in some hospitals. It is critical to establish whether paper printers can achieve the same efficacy and quality as dry laser printers for full-field digital mammography (FFDM). To compare the image quality and detection rate of dry laser printers and paper printers for FFDM. Fifty-five cases (25 with single clustered microcalcifications and 30 controls) were selected by a radiologist not participating in the image review. All images were printed on film and paper by one experienced mammography technologist using the processing algorithm routinely used for our mammograms. Two radiologists evaluated hard copies from dry laser printers and paper printers for image quality and detectability of clustered microcalcifications. For the image quality comparisons, agreement between the reviewers was evaluated by means of kappa statistics. The significance of differences between both of the printers was determined using Wilcoxon's signed-rank test. The detection rate of two printing systems was evaluated using receiver operating characteristic (ROC) analysis. From 110 scores (55 patients, two readers) per printer system, the following quality results were achieved for dry laser printer images: 70 (63.6%) were rated as good and 40 (36.4%) as moderate. By contrast, for the paper printer images, 25 scores (22.7%) were rated as good and 85 (77.3%) as moderate. Therefore, the image quality of the dry laser printer was superior to that achieved by the paper printer (P=0.00). The average area-under-the-curve (Az) values for the dry laser printer and the paper printer were 0.991 and 0.805, respectively. The difference was 0.186. Results of ROC analysis showed significant difference in observer performance between the dry laser printer and paper printer (P=0.0015). The performance of dry laser printers is superior to that of paper printers. Paper printers should not be used in FFDM.

Comparison of reading time between screen-film mammography and soft-copied, full-field digital mammography

To compare the reading time for full-field digital mammography (FFDM) and screen-film mammography (SFM) using a recommended reading method and to provide data regarding the reading time required to establish the optimal conditions for digital mammography. Reading time was measured during image interpretation by two expert radiologists. FFDM images were taken for screening, and readers A and B read images obtained for 79 and 82 patients, respectively. The mammograms read by both readers were similar with regard to patients' backgrounds. Further, 100 SFM mammograms were read to perform comparative analyses. The reading times were compared. Reader A recorded mean reading times of 31 and 56 s, respectively, for the SFM and FFDM images with no comparative mammograms, and means of 45 and 62 s for those with comparative mammograms. Reader B recorded mean reading times of 43 and 74 s, respectively, for SFM and FFDM images with no comparative mammograms, and 53 and 66 s for those with comparative mammograms. The reading time is prolonged in FFDM performed according to a recommended method. Post-processing is thought to affect the reading time.

Image Quality of a Wet Laser Printer Versus a Paper Printer for Full-Field Digital Mammograms

The purpose of our study was to compare the image quality of a wet laser printer with that of a paper printer for full-field digital mammography (FFDM). For both a wet laser printer and a paper printer connected to an FFDM system, image quality parameters were evaluated using a standardized printer test image (luminance density, dynamic range). The detectability of standardized objects on a phantom was also evaluated. Furthermore, 640 mammograms of 80 patients with different breast tissue composition patterns were imaged with both printers. Subjective image quality parameters (brightness, contrast, and detection of details of anatomic structures-that is, skin, subcutis, musculature, glandular tissue, and fat), the detectability of breast lesions (mass, calcifications), and the diagnostic performance according to the BI-RADS classification were evaluated. Both the luminance density and the dynamic range were superior for the wet laser printer. More standardized objects were visible on the phantom imaged with the wet laser printer than with the paper printer (13/16 vs 11/16). Each subjective image quality parameter of the mammograms from the wet laser printer was rated superior to those of the paper printer. Significantly more breast lesions were detected on the wet laser printer images than on the paper printer images (masses, 13 vs 10; calcifications, 65 vs 48; p < 0.05). With the paper printer images, BI-RADS 4 and 5 categories were underestimated for 10 (43.5%) of 23 patients. For FFDM, images obtained from a wet laser printer show superior objective and subjective image quality compared with a paper printer. As a consequence, the paper printer should not be used for FFDM.

Comparison of full-field digital mammography and film–screen mammography: image quality and lesion detection

The objective of this study is to compare image quality and lesion detection for full field digital mammography (FFDM) and film-screen mammography (FSM). In 200 women we performed digital mammography of one breast and film-screen mammography of the other breast. Imaging parameters were set automatically. Image quality, visualization of calcifications and masses were rated by three readers independently. Mean glandular dose was calculated for both systems. We found no significant difference in mean glandular dose. Image quality was rated by reader A/B/C as excellent for FFDM in 153/155/167 cases and for FSM in 139/116/114 cases (p<0.03/0.001/0.001). Microcalcifications were detected by FFDM in 103/89/98 and by FSM in 76/76/76 cases (p<0.01/0.06/0.01). Detection of masses did not differ significantly. FFDM provided significantly better visibility of skin and nipple-areola region (p<0.01). FFDM demonstrated improved image quality compared with film-screen mammography. Microcalcification detection was also significantly better with the digital mammography system for two of the three readers.