Breathing motion compensation in chest tomosynthesis: evaluation of the effect on image quality and presence of artifacts.

Purpose: Chest tomosynthesis (CTS) has a relatively longer acquisition time compared with chest X-ray, which may increase the risk of motion artifacts in the reconstructed images. Motion artifacts induced by breathing motion adversely impact the image quality. This study aims to reduce these artifacts by excluding projection images identified with breathing motion prior to the reconstruction of section images and to assess if motion compensation improves overall image quality. Approach: In this study, 2969 CTS examinations were analyzed to identify examinations where breathing motion has occurred using a method based on localizing the diaphragm border in each of the projection images. A trajectory over diaphragm positions was estimated from a second-order polynomial curve fit, and projection images where the diaphragm border deviated from the trajectory were removed before reconstruction. The image quality between motion-compensated and uncompensated examinations was evaluated using the image quality criteria for anatomical structures and image artifacts in a visual grading characteristic (VGC) study. The resulting rating data were statistically analyzed using the software VGC analyzer. Results: A total of 58 examinations were included in this study with breathing motion occurring either at the beginning or end ( n = 17 ) or throughout the entire acquisition ( n = 41 ). In general, no significant difference in image quality or presence of motion artifacts was shown between the motion-compensated and uncompensated examinations. However, motion compensation significantly improved the image quality and reduced the motion artifacts in cases where motion occurred at the beginning or end. In examinations where motion occurred throughout the acquisition, motion compensation led to a significant increase in ripple artifacts and noise. Conclusions: Compensation for respiratory motion in CTS by excluding projection images may improve the image quality if the motion occurs mainly at the beginning or end of the examination. However, the disadvantages of excluding projections may outweigh the benefits of motion compensation.

In-silico study of the impact of system design parameters on microcalcification detection in wide-angle digital breast tomosynthesis.

Purpose: Accurate detection of microcalcifications ( µ Calcs ) is crucial for the early detection of breast cancer. Some clinical studies have indicated that digital breast tomosynthesis (DBT) systems with a wide angular range have inferior µ Calc detectability compared with those with a narrow angular range. This study aims to (1) provide guidance for optimizing wide-angle (WA) DBT for improving µ Calcs detectability and (2) prioritize key optimization factors. Approach: An in-silico DBT pipeline was constructed to evaluate µ Calc detectability of a WA DBT system under various imaging conditions: focal spot motion (FSM), angular dose distribution (ADS), detector pixel pitch, and detector electronic noise (EN). Images were simulated using a digital anthropomorphic breast phantom inserted with 120 µ m µ Calc clusters. Evaluation metrics included the signal-to-noise ratio (SNR) of the filtered channel observer and the area under the receiver operator curve (AUC) of multiple-reader multiple-case analysis. Results: Results showed that FSM degraded µ Calcs sharpness and decreased the SNR and AUC by 5.2% and 1.8%, respectively. Non-uniform ADS increased the SNR by 62.8% and the AUC by 10.2% for filtered backprojection reconstruction with a typical clinical filter setting. When EN decreased from 2000 to 200 electrons, the SNR and AUC increased by 21.6% and 5.0%, respectively. Decreasing the detector pixel pitch from 85 to 50 µ m improved the SNR and AUC by 55.6% and 7.5%, respectively. The combined improvement of a 50 µ m pixel pitch and EN200 was 89.2% in the SNR and 12.8% in the AUC. Conclusions: Based on the magnitude of impact, the priority for enhancing µ Calc detectability in WA DBT is as follows: (1) utilizing detectors with a small pixel pitch and low EN level, (2) allocating a higher dose to central projections, and (3) reducing FSM. The results from this study can potentially provide guidance for DBT system optimization in the future.

Estimation of the absorbed dose in simultaneous digital breast tomosynthesis and mechanical imaging.

Purpose: Use of mechanical imaging (MI) as complementary to digital mammography (DM), or in simultaneous digital breast tomosynthesis (DBT) and MI - DBTMI, has demonstrated the potential to increase the specificity of breast cancer screening and reduce unnecessary biopsies compared with DM. The aim of this study is to investigate the increase in the radiation dose due to the presence of an MI sensor during simultaneous image acquisition when automatic exposure control is used. Approach: A radiation dose study was conducted on clinically available breast imaging systems with and without an MI sensor present. Our estimations were based on three approaches. In the first approach, exposure values were compared in paired clinical DBT and DBTMI acquisitions in 97 women. In the second approach polymethyl methacrylate (PMMA) phantoms of various thicknesses were used, and the average glandular dose (AGD) values were compared. Finally, a rectangular PMMA phantom with a 45 mm thickness was used, and the AGD values were estimated based on air kerma measurements with an electronic dosemeter. Results: The relative increase in exposure estimated from digital imaging and communications in medicine headers when using an MI sensor in clinical DBTMI was 11.9 % ± 10.4 . For the phantom measurements of various thicknesses of PMMA, the relative increases in the AGD for DM and DBT measurements were, on average, 10.7 % ± 3.1 and 11.4 % ± 3.0 , respectively. The relative increase in the AGD using the electronic dosemeter was 11.2 % ± < 0.001 in DM and 12.2 % ± < 0.001 in DBT. The average difference in dose between the methods was 11.5 % ± 3.3 . Conclusions: Our measurements suggest that the use of simultaneous breast radiography and MI increases the AGD by an average of 11.5 % ± 3.3 . The increase in dose is within the acceptable values for mammography screening recommended by European guidelines.

Digital Breast Tomosynthesis Screening Improves Early Breast Cancer Detection and Survival in Taiwan.

OBJECTIVE: Our objective was to compare the efficacy of digital breast tomosynthesis (DBT) and digital mammography (DM) in breast cancer screening and their impact on long-term overall survival (OS). METHODS: The study involved 48 549 consecutive mammography examinations between 2011 and 2015 at a medical center in Taiwan, identifying 545 women who were screened and diagnosed with breast cancer. Digital mammography and DBT examinations were alternated on different days. Patients were categorized based on mammographic modality, breast density, and American Joint Committee on Cancer (AJCC) stage. To determine the long-term outcome until August 2021, survival rates were analyzed using the Kaplan-Meier (K-M) survival analysis. RESULTS: The mean age at breast cancer diagnosis was 53.2 years. Digital breast tomosynthesis examinations were significantly associated with early breast cancer (AJCC stage 0 to 2) (P = .022). The 5- and 9-year OS rates for all patients were 96.8% and 93.0%, respectively. The 5- and 9-year OS was significantly greater in the DBT group (98.4% and 96.8%) compared with the DM group (95.0% and 90.4%) (P = .030 for all). The K-M survival analysis demonstrated a significantly higher OS in the DBT group than the DM group (P = .037). Furthermore, DBT significantly improved OS in a cohort of women with stage II and III cancer (P = .032) and heterogeneously dense breasts (P = .045). CONCLUSION: Screening with DBT is associated with early breast cancer diagnosis and higher survival rates compared with DM.

Association between the canal filling ratio and bone resorption in trabecular metal stems in reverse total shoulder arthroplasty: a radiographic analysis using tomosynthesis.

Background: Several factors affect the incidence of osteopenia with cortical narrowing (CNO) in reverse shoulder arthroplasty. This study aimed to compare the incidence of CNO with different fixation methods (cemented or cementless) using a single implant (trabecular metal humeral stem) evaluated using tomosynthesis and to analyze the factors affecting the incidence of CNO for cementless stem fixation. Methods: A total of 109 patients (cementless: 75 cases; cemented: 34 cases) who underwent reverse total shoulder arthroplasty were included in this study. The patients were divided into 2 groups (cementless or cemented), and the incidence of CNO was compared. In addition, patients in the cementless group were divided into 2 groups (canal filling ratio [CFR] of ≥ 0.7 or < 0.7), the incidence of CNO was compared, and the Cramer's coefficient of association between CNO and CFR > 0.7 (and 0.8) was calculated. Results: No significant difference was observed in the incidence of CNO between the cementless and cemented groups (7/75 vs. 3/35, P value = 1.0). The association between CNO and the CFR using Cramer's coefficient of association showed that there were few correlations (coefficient: 0.14, P value = .59). Conclusion: Cementless reverse total shoulder arthroplasty with a trabecular metal stem has a similar low incidence of CNO as cemented fixation, and the incidence of CNO with a trabecular metal stem was lower than that reported in previous studies. A CFR > 0.7 was not associated with the incidence of CNO.

Pre-Reconstruction Processing with the Cycle-Consist Generative Adversarial Network Combined with Attention Gate to Improve Image Quality in Digital Breast Tomosynthesis.

The current study proposed and evaluated "residual squeeze and excitation attention gate" (rSEAG), a novel network that can improve image quality by reducing distortion attributed to artifacts. This method was established by modifying the Cycle Generative Adversarial Network (cycleGAN)-based generator network using projection data for pre-reconstruction processing in digital breast tomosynthesis. Residual squeeze and excitation were installed in the bridge of the generator network, and the attention gate was installed in the skip connection between the encoder and decoder. Based on the radiation dose index (exposure index and division index) incident on the detector, the cases approved by the ethics committee and used for the study were classified as reference (675 projection images) and object (675 projection images). For the cases, unsupervised data containing a mixture of cases with and without masses were used. The cases were trained using cycleGAN with rSEAG and the conventional networks (ResUNet and U-Net). For testing, predictive processing was performed on cases (60 projection images) that were not used for learning. Images were generated using filtered backprojection reconstruction (kernel: Ramachandran and Lakshminarayanan) from projection data for testing data and without pre-reconstruction processing data (evaluation: in-focus plane). The distortion was evaluated using perception-based image quality evaluation (PIQE) analysis, texture analysis (feature: "Homogeneity" and "Contrast"), and a statistical model with a Gumbel distribution. PIQE has a low rSEAG value. Texture analysis showed that rSEAG and a network without cycleGAN were similar in terms of the "Contrast" feature. In dense breasts, ResUNet had the lowest "Contrast" feature and U-Net had differences between cases. The maximal variations in the Gumbel plot, rSEAG reduced the high-frequency ripple artifacts. In this study, rSEAG could improve distortion and reduce ripple artifacts.

AI-based strategies in breast mass ≤ 2 cm classification with mammography and tomosynthesis.

PURPOSE: To evaluate the diagnosis performance of digital mammography (DM) and digital breast tomosynthesis (DBT), DM combined DBT with AI-based strategies for breast mass ≤ 2 cm. MATERIALS AND METHODS: DM and DBT images in 483 patients including 512 breast masses were acquired from November 2018 to November 2019. Malignant and benign tumours were determined by biopsies using histological analysis and follow-up within 24 months. The radiomics and deep learning methods were employed to extract the breast mass features in images and finally for benign and malignant classification. The DM, DBT and DM combined DBT (DM + DBT) images were fed into radiomics and deep learning models to construct corresponding models, respectively. The area under the receiver operating characteristic curve (AUC) was employed to estimate model performance. An external dataset of 146 patients from March 2021 to December 2022 from another center was enrolled for external validation. RESULTS: In the internal testing dataset, compared with the DM model and the DBT model, the DM + DBT models based on radiomics and deep learning both showed statistically significant higher AUCs [0.810 (RA-DM), 0.823 (RA-DBT) and 0.869 (RA-DM + DBT), P ≤ 0.001; 0.867 (DL-DM), 0.871 (DL-DBT) and 0.908 (DL-DM + DBT), P = 0.001]. The deep learning models present superior to the radiomics models in the experiments with only DM (0.867 vs 0.810, P = 0.001), only DBT (0.871 vs 0.823, P = 0.001) and DM + DBT (0.908 vs 0.869, P = 0.003). CONCLUSIONS: DBT has a clear additional value for diagnosing breast mass less than 2 cm compared with only DM. AI-based methods, especially deep learning, can help achieve excellent performance.

Comparison of Visual and Quantra Software Mammographic Density Assessment According to BI-RADS® in 2D and 3D Images.

Mammographic density (MD) assessment is subject to inter- and intra-observer variability. An automated method, such as Quantra software, could be a useful tool for an objective and reproducible MD assessment. Our purpose was to evaluate the performance of Quantra software in assessing MD, according to BI-RADS® Atlas Fifth Edition recommendations, verifying the degree of agreement with the gold standard, given by the consensus of two breast radiologists. A total of 5009 screening examinations were evaluated by two radiologists and analysed by Quantra software to assess MD. The agreement between the three assigned values was expressed as intraclass correlation coefficients (ICCs). The agreement between the software and the two readers (R1 and R2) was moderate with ICC values of 0.725 and 0.713, respectively. A better agreement was demonstrated between the software's assessment and the average score of the values assigned by the two radiologists, with an index of 0.793, which reflects a good correlation. Quantra software appears a promising tool in supporting radiologists in the MD assessment and could be part of a personalised screening protocol soon. However, some fine-tuning is needed to improve its accuracy, reduce its tendency to overestimate, and ensure it excludes high-density structures from its assessment.

SIFT-DBT: SELF-SUPERVISED INITIALIZATION AND FINE-TUNING FOR IMBALANCED DIGITAL BREAST TOMOSYNTHESIS IMAGE CLASSIFICATION.

Digital Breast Tomosynthesis (DBT) is a widely used medical imaging modality for breast cancer screening and diagnosis, offering higher spatial resolution and greater detail through its 3D-like breast volume imaging capability. However, the increased data volume also introduces pronounced data imbalance challenges, where only a small fraction of the volume contains suspicious tissue. This further exacerbates the data imbalance due to the case-level distribution in real-world data and leads to learning a trivial classification model that only predicts the majority class. To address this, we propose a novel method using view-level contrastive Self-supervised Initialization and Fine-Tuning for identifying abnormal DBT images, namely SIFT-DBT. We further introduce a patch-level multi-instance learning method to preserve spatial resolution. The proposed method achieves 92.69% volume-wise AUC on an evaluation of 970 unique studies.

Improving diagnostic strategies in bronchoscopy for peripheral pulmonary lesions.

INTRODUCTION: In the past two decades, bronchoscopy of peripheral pulmonary lesions (PPLs) has improved its diagnostic yield due to the combination of various instruments and devices. Meanwhile, the application is complex and intertwined. AREAS COVERED: This review article outlines strategies in diagnostic bronchoscopy for PPLs. We summarize the utility and evidence of key instruments and devices based on the results of clinical trials. Future perspectives of bronchoscopy for PPLs are also discussed. EXPERT OPINION: The accuracy of reaching PPLs by bronchoscopy has improved significantly with the introduction of combined instruments such as navigation, radial endobronchial ultrasound, digital tomosynthesis, and cone-beam computed tomography. It has been accelerated with the advent of approach tools such as newer ultrathin bronchoscopes and robotic-assisted bronchoscopy. In addition, needle aspiration and cryobiopsy provide further diagnostic opportunities beyond forceps biopsy. Rapid on-site evaluation may also play an important role in decision making during the procedures. As a result, the diagnostic yield of bronchoscopy for PPLs has improved to a level comparable to that of transthoracic needle biopsy. The techniques and technologies developed in the diagnosis will be carried over to the next step in the transbronchial treatment of PPLs in the future.

Improving Computer-aided Detection for Digital Breast Tomosynthesis by Incorporating Temporal Change.

Purpose To develop a deep learning algorithm that uses temporal information to improve the performance of a previously published framework of cancer lesion detection for digital breast tomosynthesis. Materials and Methods This retrospective study analyzed the current and the 1-year-prior Hologic digital breast tomosynthesis screening examinations from eight different institutions between 2016 and 2020. The dataset contained 973 cancer and 7123 noncancer cases. The front end of this algorithm was an existing deep learning framework that performed single-view lesion detection followed by ipsilateral view matching. For this study, PriorNet was implemented as a cascaded deep learning module that used the additional growth information to refine the final probability of malignancy. Data from seven of the eight sites were used for training and validation, while the eighth site was reserved for external testing. Model performance was evaluated using localization receiver operating characteristic curves. Results On the validation set, PriorNet showed an area under the receiver operating characteristic curve (AUC) of 0.931 (95% CI: 0.930, 0.931), which outperformed both baseline models using single-view detection (AUC, 0.892 [95% CI: 0.891, 0.892]; P < .001) and ipsilateral matching (AUC, 0.915 [95% CI: 0.914, 0.915]; P < .001). On the external test set, PriorNet achieved an AUC of 0.896 (95% CI: 0.885, 0.896), outperforming both baselines (AUC, 0.846 [95% CI: 0.846, 0.847]; P < .001 and AUC, 0.865 [95% CI: 0.865, 0.866]; P < .001, respectively). In the high sensitivity range of 0.9 to 1.0, the partial AUC of PriorNet was significantly higher (P < .001) relative to both baselines. Conclusion PriorNet using temporal information further improved the breast cancer detection performance of an existing digital breast tomosynthesis cancer detection framework. Keywords: Digital Breast Tomosynthesis, Computer-aided Detection, Breast Cancer, Deep Learning © RSNA, 2024 See also commentary by Lee in this issue.

Budget impact analysis of introducing digital breast tomosynthesis in breast cancer screening in Italy.

PURPOSE: This study quantifies the impact on budget and cost per health benefit of implementing digital breast tomosynthesis (DBT) in place of digital mammography (DM) for breast cancer screening among asymptomatic women in Italy. METHODS: A budget impact analysis and a cost consequence analysis were conducted using parameters from the MAITA project and literature. The study considered four scenarios for DBT implementation, i.e., DBT for all women, DBT for women aged 45-49 years, DBT based on breast density (BI-RADS C + D or D only), and compared these to the current DM screening. Healthcare provider's perspective was adopted, including screening, diagnosis, and cancer treatment costs. RESULTS: Introducing DBT for all women would increase overall screening costs by 20%. Targeting DBT to women aged 45-49 years or with dense breasts would result in smaller cost increases (3.2% for age-based and 1.4-10.7% for density-based scenarios). The cost per avoided interval cancer was significantly higher when DBT was applied to all women compared to targeted approaches. The cost per gained early-detected cancer slightly increases in targeted approaches, while the assumptions on the clinical significance and overdiagnosis of cancers detected by DBT and not by DM have a strong impact. CONCLUSIONS: Implementing DBT as a primary breast cancer test in screening programs in Italy would lead to a substantial increase in costs. Tailoring DBT use to women aged 45-49 or with dense breasts could enhance the feasibility and sustainability of the intervention. Further research is needed to clarify the impact of DBT on overdiagnosis and the long-term outcomes.

Digital breast tomosynthesis in breast cancer screening: an ethical perspective.

Although digital breast tomosynthesis has higher sensitivity than digital mammography and at least as high specificity, digital mammography remains the most common method for conducting mammographic screening. At the same time, mammography systems are now delivered "DBT-ready" and can be used for either digital mammography or digital breast tomosynthesis. In this paper, we ask whether it is ethically permissible to use such equipment for digital mammography, given its lower sensitivity. We argue it is not, and that clinics are ethically required to use their DBT-ready equipment to screen with digital breast tomosynthesis whenever this is practically possible. Our argument relies on a comparison between digital breast tomosynthesis and a hypothesized improvement in the image quality of digital mammography. CRITICAL RELEVANCE STATEMENT: Women may lose out on the benefits of screening with digital breast tomosynthesis when DBT-ready equipment is used to screen with digital mammography; we argue that this practice is ethically problematic. KEY POINTS: Digital breast tomosynthesis finds more cases of breast cancer than digital mammography. Mammography equipment can often be used to screen with both digital breast tomosynthesis and digital mammography. When they can, clinics are ethically required to use existing equipment to screen with digital breast tomosynthesis instead of digital mammography.

Survey on Current Utilization and Perception of Synthesized Mammography.

OBJECTIVE: To assess utilization and perceptions of 2D synthesized mammography (SM) for digital breast tomosynthesis (DBT) among practicing U.S. breast radiologists. METHODS: An IRB-exempt 23-question anonymized survey was developed by the Society of Breast Imaging (SBI) Patient Care and Delivery Committee and emailed to practicing U.S. radiologist SBI members on October 9, 2023. Questions assessed respondents' demographics, current mammographic screening protocol, confidence interpreting SM for mammographic findings, and perceived advantages and disadvantages of SM. RESULTS: Response rate was 13.4% (371/2771). Of 371 respondents, 208 were currently screening with DBT/SM (56.1%), 98 with DBT/SM/digital mammography (DM) (26.4%), 61 with DBT/DM (16.4%), and 4 with DM (1.1%). Most respondents felt confident using DBT/SM to evaluate masses (254/319, 79.6%), asymmetries (247/319, 77.4%), and distortions (265/318, 83.3%); however, confidence was mixed for calcifications (agreement 130/320, 40.6%; disagreement 156/320, 48.8%; neutral 34/320, 10.6%). The most frequently cited disadvantage and advantage of SM were reconstruction algorithm false-positive results (199/347, 57.4%) and lower radiation dose (281/346, 81.2%), respectively. Higher confidence and fewer disadvantages were reported by radiologists who had more SM experience, screened with DBT/SM, or exclusively used Hologic vendor (all P <.05). CONCLUSION: For most survey respondents (56.1%), SM has replaced DM in DBT screening. Radiologists currently screening with DBT/SM or with more SM experience reported greater confidence in SM with fewer perceived disadvantages.

Diagnostic accuracy of digital breast tomosynthesis and digital mammography in women with dense or non-dense breast tissue: A systematic review and meta-analysis.

BACKGROUND: Despite its excellent screening effectiveness and sensitivity for breast cancer (BC), digital breast tomosynthesis (DBT) is controversial due to its high radiation exposure and long reading time. This study examines the diagnostic accuracy of DBT and digital mammography (DM) for BC screening and diagnosis in women with dense or non-dense breast tissue. MATERIAL AND METHODS: PRISMA-compliant searches were performed on Medline, Embase, PubMed, Web of Science, and the Cochrane databases for articles comparing DBT and DM for BC screening until March 2023. Meta-analysis was performed using RevMan sofware, and the Cochrane Risk of Bias Assessment Tool was employed to assess study quality. RESULTS: This meta-analysis included 11 trials with a total of 2,124,018 individuals. Screening with DBT resulted in a greater cancer detection rate, as demonstrated by a risk ratio (RR) of 1.27 (95% confidence interval (95% CI): 1.14-1.41). Digital breast tomosynthesis also had a reduced recall rate, with a RR of 0.88 (95% CI: 0.78-0.99), higher sensitivity and specificity values (pooled sensitivity of 0.91 (95% CI: 0.59-0.99)) and pooled specificity of 0.90 (95% CI: 0.42-1.0)) than DM (pooled sensitivity of 0.86 (95% CI: 0.52-1.0) and pooled specificity of 0.81 (95% CI: 0.12-1.0)). All acquired data exhibited reliability, lack of bias and statistical significance (p < 0.05). CONCLUSION: Digital breast tomosynthesis is a more effective screening and diagnostic assessment tool for women with dense or non-dense breasts than DM in terms of incremental cancer detection, sensitivity and recall rate.

Stationary prospective cardiac gated computed tomography-dynamic study in phantoms andin vivo.

Objective.This study explores the feasibility of a stationary gantry cardiac gated computed tomography (CT) with carbon nanotube (CNT) linear x-ray source arrays.Approach.We developed a stationary gantry CT system utilizing multipixel CNT x-ray sources. Given the advantages of straightforward x-ray pulse control with these sources, we investigated the potential for gated prospective imaging. We implemented prospective respiratory and cardiac gating control and evaluated the system through dynamic phantom imaging studies followed by imaging of a porcine model.Main Results.The findings revealed minimal anatomical motion artifacts in the heart and lungs, confirming successful physiologic gated acquisition in stationary gantry cardiac CT. This indicates the potential of this imaging approach for reducing artifacts and improving image quality.Significance.This study demonstrates the feasibility of prospective physiological gating with CNT x-ray sources in a stationary gantry setup for cardiac imaging. This approach could potentially alleviate the need for beta blocker administration during cardiac CT scans, thereby increasing the flexibility of the imaging system and enabling the imaging of a wider variety of patient cardiac conditions.

Role of contrast-enhanced mammogram as an adjunct to tomosynthesis in evaluation of circumscribed breast lesions.

OBJECTIVES: We evaluated the role of contrast-enhanced mammogram (CEM) in the characterization of circumscribed lesions detected in digital breast tomosynthesis (DBT) and correlated with histopathology. METHODS: A retrospective study was done on 205 circumscribed breast masses detected with DBT and for whom CEM was done before core biopsy/excision biopsy. Morphology of lesion enhancement was noted at a 2-min CEM image and depending on the enhancement pattern, they were classified as benign, malignant, and indeterminate. Indeterminate lesions were further characterized by contrast kinetics at 8 min and divided into benign and malignant lesions. The results were correlated with histopathology reports. RESULTS: Among the 205 lesions, 158 were benign and 47 were malignant by histopathology. All 47 malignant cases were diagnosed as malignant (sensitivity-100%) and 150 out of 158 benign lesions were diagnosed as benign by CEM (specificity-95%). Eight benign lesions were reported as malignant (false positive) by CEM. Positive predictive value was 85.4% (47/55); negative predictive value (NPV) was 100% (150/150); accuracy was 96% (197/205). CONCLUSIONS: The high sensitivity of CEM in our study suggests that CEM helps in the early diagnosis of benign-looking circumscribed breast malignancies. The high NPV of CEM helps to avoid unnecessary biopsies and interventions in benign lesions. ADVANCES IN KNOWLEDGE: This study describes the contrast enhancement pattern of benign and malignant circumscribed breast lesions and thereby helps in the diagnosis of malignancy at an early stage. CEM is a promising adjunct tool since it offers functional imaging as a supplement to anatomical imaging by DBT.

Digital breast tomosynthesis for breast cancer diagnosis in women with dense breasts and additional breast cancer risk factors: A systematic review.

INTRODUCTION: Digital breast tomosynthesis (DBT) may improve sensitivity in population screening. However, evidence is currently limited on the performance of DBT in patients at a higher risk of breast cancer. This systematic review compares the clinical effectiveness and cost-effectiveness of DBT, digital mammography (DM), and ultrasound, for breast cancer detection in women with dense breasts and additional risk factors. METHODS: Medline, Embase, and Evidence-Based Medicine Reviews via OvidSP were searched to identify literature from 2010 to August 21, 2023. Selection of studies, data extraction, and quality assessment (using QUADAS-2 and CHEERS) were completed in duplicate. Findings were summarised descriptively and narratively. RESULTS: Twenty-six studies met pre-specified inclusion criteria. In women with breast symptoms or recalled for investigation of screen-detected findings (19 studies), DBT may be more accurate than DM. For example, in symptomatic women, the sensitivity of DBT + DM ranged from 82.8 % to 92.5 % versus 56.8 %-81.3 % for mammography (DM/synthesised images). However, most studies had a high risk of bias due to participant selection. Evidence regarding DBT in women with a personal or family history of breast cancer, for DBT versus ultrasound alone, and cost-effectiveness of DBT was limited. CONCLUSIONS: In women with dense breasts and additional risk factors for breast cancer, evidence is limited about the accuracy of DBT compared to other imaging modalities, particularly in those with personal or family history of breast cancer. Future research in this population should consider head-to-head comparisons of imaging modalities to determine the relative effectiveness of these imaging tests. SYSTEMATIC REVIEW REGISTRATION: PROSPERO registration number CRD42021236470.

Dynamic reconstruction for digital tomosynthesis: a phantom proof of concept for breast care.

Objective. Digital tomosynthesis (DTS) is a type of limited-angle Computed Tomography (CT) used in orthopedic and oncology care to provide a pseudo-3D reconstructed volume of a body part from multiple x-ray projections. Patient motion during acquisitions results in artifacts which affect screening and diagnostic performances. Hence, accurate reconstruction of moving body parts from a tomosynthesis projection series is addressed in this paper, with a particular focus on the breast. The aim of this paper is to assess the feasibility of a novel dynamic reconstruction technique for DTS and evaluate its accuracy compared to an available ground truth.Approach. The proposed method is a combination of a 4D dynamic tomography strategy leveraging the formalism of Projection-based Digital Volume Correlation (P-DVC) with a multiscale approach to estimate and correct patient motion. Iterations of two operations are performed: (i) a motion-corrected reconstruction based on the Simultaneous Iterative Reconstruction Technique (SIRT) algorithm and (ii) a motion estimation from projection residuals, to obtain motion-free volumes. Performance is evaluated on a synthetic Digital Breast Tomosynthesis (DBT) case. Three slabs of a CIRS breast phantom are imaged on a Senographe PristinaTM, under plate-wise rigid body motions with amplitudes ranging up to 10 mm so that an independent measurement of the motion can be accessed.Results. Results show a motion estimation average precision down to 0.183 mm (1.83 voxels), when compared to the independent measurement. Moreover, an 84.2% improvement on the mean residual error and a 59.9% improvement on the root mean square error (RMSE) with the original static reconstruction are obtained.Significance. Visual and quantitative assessments of the dynamically reconstructed volumes show that the proposed method fully restores conspicuity for important clinical features contained in the phantom.