Artificial intelligence for digital breast tomosynthesis: Impact on diagnostic performance, reading times, and workload in the era of personalized screening

The ultimate goals of the application of artificial intelligence (AI) to digital breast tomosynthesis (DBT) are the reduction of reading times, the increase of diagnostic performance, and the reduction of interval cancer rates. In this review, after outlining the journey from computer-aided detection/diagnosis systems to AI applied to digital mammography (DM), we summarize the results of studies where AI was applied to DBT, noting that long-term advantages of DBT screening and its crucial ability to decrease the interval cancer rate are still under scrutiny. AI has shown the capability to overcome some shortcomings of DBT in the screening setting by improving diagnostic performance and by reducing recall rates (from -2 % to -27 %) and reading times (up to -53 %, with an average 20 % reduction), but the ability of AI to reduce interval cancer rates has not yet been clearly investigated. Prospective validation is needed to assess the cost-effectiveness and real-world impact of AI models assisting DBT interpretation, especially in large-scale studies with low breast cancer prevalence. Finally, we focus on the incoming era of personalized and risk-stratified screening that will first see the application of contrast-enhanced breast imaging to screen women with extremely dense breasts. As the diagnostic advantage of DBT over DM was concentrated in this category, we try to understand if the application of AI to DM in the remaining cohorts of women with heterogeneously dense or non-dense breast could close the gap in diagnostic performance between DM and DBT, thus neutralizing the usefulness of AI application to DBT

Sensors - Proceedings of the 2nd National Conference on Sensors, 2014

In recent years, there has been a growing interest for possible application of wireless smart sensor networks. One area in which these platforms can offer considerable advantages over classical solutions is the monitoring of civil structures. This work analyze possible benefits and critical issues associated with the use of wireless sensor networks for vibrational monitoring of civil infrastructures. On the basis of the analysis of an experimental setup for the health monitoring of an heritage structure, the main advantages and limitations of a wireless sensor network for vibrational monitoring are outlined. A possible approach for the design of a sensor node supporting on-board vibrational data processing is discussed. Possible advantages of the proposed architecture are analyzed and a preliminary characterization of a custom prototype is presented

Developing and Testing High-Performance SHM Sensors Mounting Low-Noise MEMS Accelerometers

Recently, there has been increased interest in adopting novel sensing technologies for continuously monitoring structural systems. In this respect, micro-electrical mechanical system (MEMS) sensors are widely used in several applications, including structural health monitoring (SHM), in which accelerometric samples are acquired to perform modal analysis. Thanks to their significantly lower cost, ease of installation in the structure, and lower power consumption, they enable extensive, pervasive, and battery-less monitoring systems. This paper presents an innovative high-performance device for SHM applications, based on a low-noise triaxial MEMS accelerometer, providing a guideline and insightful results about the opportunities and capabilities of these devices. Sensor nodes have been designed, developed, and calibrated to meet structural vibration monitoring and modal identification requirements. These components include a protocol for reliable command dissemination through network and data collection, and improvements to software components for data pipelining, jitter control, and high-frequency sampling. Devices were tested in the lab using shaker excitation. Results demonstrate that MEMS-based accelerometers are a feasible solution to replace expensive piezo-based accelerometers. Deploying MEMS is promising to minimize sensor node energy consumption. Time and frequency domain analyses show that MEMS can correctly detect modal frequencies, which are useful parameters for damage detection. The acquired data from the test bed were used to examine the functioning of the network, data transmission, and data quality. The proposed architecture has been successfully deployed in a real case study to monitor the structural health of the Marcus Aurelius Exedra Hall within the Capitoline Museum of Rome. The performance robustness was demonstrated, and the results showed that the wired sensor network provides dense and accurate vibration data for structural continuous monitoring

Long-term structural monitoring of the damaged Basilica S. Maria di Collemaggio through a low-cost wireless sensor network

The work presents the inter-disciplinary multi-year project focused on the permanent seismic monitoring of a historical structure, the Basilica S. Maria di Collemaggio, by means of an advanced wireless sensor network. Considered among the architectural masterpieces of the Italian Romanesque, the structural behaviour of the monumental masonry church is strongly debated after the heavy damages and the partial collapse that occurred during the 2009 L\u2019Aquila earthquake. From the perspective of information technology, critical issues in the wireless data acquisition and communication are analysed. The sensor network design, deployment and performance are discussed with respect to the high-demanding service requirements \u2014 as well as the non-negligible management costs \u2014 specifically related to the long-term monitoring of a monumental masonry structure in a seismic area. From the perspective of experimental signal analysis, the acceleration data collected during a 3-year period of seismic monitoring are analysed in the frequency and time domains. The results allow the clear detection of complex interactions between the masonry structures and some of the temporary protective installations. Stochastic subspace identification procedures are applied, with critical analysis of their effectiveness in the assessment of reliable modal models from the building response to real seismic events. Finally, the robustness of the modal identification obtained from the structural responses to different near- and far-field micro-earthquakes is discussed, with the aid of numerical models of the damaged and protected church configuration

Structural health monitoring of the Basilica S. Maria di Collemaggio'

The work deals with the main findings obtained during the development of a permanent structural health monitoring system for a monumental church, the Basilica S. Maria di Collemaggio, strongly damaged by the 2009 L\u2019Aquila earthquake. Ongoing studies on the causes of the partial collapse occurred in the transept area have accompanied the monitoring system design and field testing. Benefits and critical issues related with the use of wireless sensor networks technology are analyzed in the specific case of monumental buildings monitoring. The specific features of the implemented system, designed to detect low-amplitude earthquake-induced vibrations, are discussed. Information obtained during one-year data acquisition is summarized together with critical observations on the operating system

Mammography biomarkers of cardiovascular and musculoskeletal health: A review

Breast density (BD) and breast arterial calcifications (BAC) can expand the role of mammography. In premenopause, BD is related to body fat composition: breast adipose tissue and total volume are potential indicators of fat storage in visceral depots, associated with higher risk of cardiovascular disease (CVD). Women with fatty breast have an increased likelihood of hypercholesterolemia. Women without cardiometabolic diseases with higher BD have a lower risk of diabetes mellitus, hypertension, chest pain, and peripheral vascular disease, while those with lower BD are at increased risk of cardiometabolic diseases. BAC, the expression of Monckeberg sclerosis, are associated with CVD risk. Their prevalence, 13 % overall, rises after menopause and is reduced in women aged over 65 receiving hormonal replacement therapy. Due to their distinct pathogenesis, BAC are associated with hypertension but not with other cardiovascular risk factors. Women with BAC have an increased risk of acute myocardial infarction, ischemic stroke, and CVD death; furthermore, moderate to severe BAC load is associated with coronary artery disease. The clinical use of BAC assessment is limited by their time-consuming manual/visual quantification, an issue possibly solved by artificial intelligence-based approaches addressing BAC complex topology as well as their large spectrum of extent and x-ray attenuations. A link between BD, BAC, and osteoporosis has been reported, but data are still inconclusive. Systematic, standardised reporting of BD and BAC should be encourage

Dynamic testing and health monitoring via wireless sensor networks in the post-earthquake assessment of structural conditions at L\u2019Aquila

The use of vibration measures during ambient dynamic testing or integrated within permanent structural health monitoring systems may play a fundamental role in urban areas rich of strategic and monumental buildings, especially in postearthquake scenarios, as the city of L\u2019Aquila, struck by the devastating seismic events of April 2006. In particular, a careful use of different output-only identification procedures may help in extracting the structural signature from low-cost and easy-to-deployed wireless networks of dynamic sensors. This valuable experimental information may significantly increase the general confidence in understanding the real dynamic behavior of the structures which suffered moderate or severe damage due to the seismic action. The paper presents a pair of case-studies related to a historical church (the \u201cBasilica di Collemaggio\u201d) and some modern buildings (the Engineering Faculty of L\u2019Aquila), currently object of wide-spectrum analyses, including dynamic testing and structural model updating aiming to design retrofitting interventions. On this respect, the initial deployment and the current development of a permanent monitoring system based on a wireless network of accelerometers is illustrated

3T multiparametric MRI of the prostate. Does intravoxel incoherent motion diffusion imaging have a role in the detection and stratification of prostate cancer in the peripheral zone?

PURPOSE: To evaluate the potential added value of the intravoxel incoherent motion model to conventional multiparametric magnetic resonance protocol in order to differentiate between healthy and neoplastic prostate tissue in the peripheral zone. MATERIAL AND METHODS: Mono-exponential and bi-exponential fits were used to calculate ADC and IVIM parameters in 53 patients with peripheral zone biopsy proved tumor. Inferential statistics analysis was performed on T2, ADC and IVIM parameters (D, D*, f) comparing healthy and neoplastic tissues. Linear discriminant analysis was performed for the conventional parameters (T2 and ADC), the IVIM parameters (molecular diffusion coefficient (D), perfusion-related diffusion coefficient (D*), and perfusion fraction (f) and the combined T2-weighted imaging/DWI and IVIM parameters (T2, ADC, D, D* and f). A correlation with Gleason scores was achieved. RESULTS: The values of T2, ADC and D were significantly lower in cancerous tissues (2749.82 ± 1324.67 ms, 0.76 ± 0.27 × 10(-3)mm(2)/s and 0.99 ± 0.38 × 10(-3)mm(2)/s respectively) compared to those found in the healthy tissues (3750.70 ± 1735.37 ms, 1.39 ± 0.48 × 10(-3)mm(2)/s and 1.77 ± 0.36 × 10(-3)mm(2)/s respectively); D* parameter was significantly increased in neoplastic compared to healthy tissue (15.56 ± 12.91 × 10(-3)mm(2)/s and 10.25 ± 10.52 × 10(-3)mm(2)/s respectively). The specificity, sensitivity and accuracy of the T2-weighted imaging/DWI and IVIM parameters were 100, 96 and 98%, respectively, compare to 88, 92 and 90% and 96, 92 and 94 for T2-weighted imaging/ADC and IVIM alone. CONCLUSIONS: IVIM parameters increase the specificity and sensitivity in the evaluation of peripheral zone prostate cancer. A statistical difference between low grade tumors and high grade tumors has been demostrated in that ADC, D and D* dataset; in particular, D has been found to have the highest significativity

Use of an antagonist of HMGB1 in mice affected by malignant mesothelioma: a preliminary ultrasound and optical imaging study

Background: Malignant mesothelioma (MM) is an aggressive tumor, with a poor prognosis, usually unresectable due to late diagnosis, mainly treated with chemotherapy. BoxA, a truncated form of "high mobility group box 1" (HMGB1), acting as an HMGB1 antagonist, might exert a defensive action against MM. We investigated the potential of BoxA for MM treatment using experimental 40-MHz ultrasound and optical imaging (OI) in a murine model. Methods: Murine MM cells infected with a lentiviral vector expressing the luciferase gene were injected into the peritoneum of 14 BALB/c mice (7 × 104 AB1-B/c-LUC cells). These mice were randomized to treatment with BoxA (n = 7) or phosphate-buffered saline (controls, n = 7). The experiment was repeated with 40 mice divided into two groups (n = 20 + 20) and treated as above to confirm the result and achieve greater statistical power. Tumor presence was investigated by experimental ultrasound and OI; suspected peritoneal masses underwent histopathology and immunohistochemistry examination. Results: In the first experiment, none of the 7 controls survived beyond day 27, whereas 4/7 BoxA-treated mice (57.1%) survived up to day 70. In the second experiment, 6/20 controls (30.0%) and 16/20 BoxA-treated mice (80.0%) were still alive at day 34 (p = 0.004). In both experiments, histology confirmed the malignant nature of masses detected using experimental ultrasound and OI. Conclusion: In our preclinical experience on a murine model, BoxA seems to exert a protective role toward MM. Both experimental ultrasound and OI proved to be reliable techniques for detecting MM peritoneal masses