A Mobile Agent-Based Electronic Marketplace

The electronic marketplace is a new medium for exchanging information, goods, services, and payments. The marketplace houses infrastructure, facilitates transactions, and matches buyers with sellers. An agent-based marketplace allows corporate data to be maintained by local buyers and sellers and transferred to the marketplace only when orders are matched. This provides participating companies with autonomy and independence. This study proposes a framework of using the mobile agent to demonstrate autonomous behavior in the electronic marketplace

Quantitative MRI Musculoskeletal Techniques: An Update.

OBJECTIVE. For many years, MRI of the musculoskeletal system has relied mostly on conventional sequences with qualitative analysis. More recently, using quantitative MRI applications to complement qualitative imaging has gained increasing interest in the MRI community, providing more detailed physiologic or anatomic information. CONCLUSION. In this article, we review the current state of quantitative MRI, technical and software advances, and the most relevant clinical and research musculoskeletal applications of quantitative MRI

Fat suppression for ultrashort echo time imaging using a novel soft-hard composite radiofrequency pulse.

PurposeTo design a soft-hard composite pulse for fat suppression and water excitation in ultrashort echo time (UTE) imaging with minimal short T2 signal attenuation.MethodsThe composite pulse contains a narrow bandwidth soft pulse centered on the fat peak with a small negative flip angle (-α) and a short rectangular pulse with a small positive flip angle (α). The fat magnetization experiences both tipping-down and -back with an identical flip angle and thus returns to the equilibrium state, leaving only the excited water magnetization. Bloch simulations, as well as knee, tibia, and ankle UTE imaging studies, were performed to investigate the effectiveness of fat suppression and corresponding water signal attenuation. A conventional fat saturation (FatSat) module was used for comparison. Signal suppression ratio (SSR), defined as the ratio of signal difference between non-fat-suppression and fat-suppression images over the non-fat-suppression signal, was introduced to evaluate the efficiency of the composite pulse.ResultsNumerical simulations demonstrate that the soft-hard pulse has little saturation effect on short T2 water signals. Knee, tibia, and ankle UTE imaging results suggest that comparable fat suppression can be achieved with the soft-hard pulse and the FatSat module. However, much less water saturation is induced by the soft-hard pulse, especially for short T2 tissues, with SSRs reduced from 71.8 ± 6.9% to 5.8 ± 4.4% for meniscus, from 68.7 ± 5.5% to 7.7 ± 7.6% for bone, and from 62.9 ± 12.0% to 4.8 ± 3.2% for the Achilles tendon.ConclusionThe soft-hard composite pulse can suppress fat signals in UTE imaging with little signal attenuation on short T2 tissues

AcidoCEST-UTE MRI for the Assessment of Extracellular pH of Joint Tissues at 3 T.

ObjectivesThe goal of this study was to demonstrate feasibility of measuring extracellular pH in cartilage and meniscus using acidoCEST technique with a 3-dimensional ultrashort echo time readout (acidoCEST-UTE) magnetic resonance imaging (MRI).Materials and methodsMagnetization transfer ratio asymmetry, radiofrequency (RF) power mismatch, and relative saturation transfer were evaluated in liquid phantoms for iopromide, iopamidol, and iohexol over a pH range of 6.2 to 7.8, at various agent concentrations, temperatures, and buffer concentrations. Tissue phantoms containing cartilage and meniscus were evaluated with the same considerations for iopamidol and iohexol. Phantoms were imaged with the acidoCEST-UTE MRI sequence at 3 T. Correlation coefficients and coefficients of variations were calculated. Paired Wilcoxon rank-sum tests were used to evaluate for statistically significant differences.ResultsThe RF power mismatch and relative saturation transfer analyses of liquid phantoms showed iopamidol and iohexol to be the most promising agents for this study. Both these agents appeared to be concentration independent and feasible for use with or without buffer and at physiologic temperature over a pH range of 6.2 to 7.8. Ultimately, RF power mismatch fitting of iohexol showed the strongest correlation coefficients between cartilage, meniscus, and fluid. In addition, ratiometric values for iohexol are similar among liquid as well as different tissue types.ConclusionsMeasuring extracellular pH in cartilage and meniscus using acidoCEST-UTE MRI is feasible

Knee menisci segmentation and relaxometry of 3D ultrashort echo time cones MR imaging using attention U-Net with transfer learning.

PurposeTo develop a deep learning-based method for knee menisci segmentation in 3D ultrashort echo time (UTE) cones MR imaging, and to automatically determine MR relaxation times, namely the T1, T1ρ , and T2∗ parameters, which can be used to assess knee osteoarthritis (OA).MethodsWhole knee joint imaging was performed using 3D UTE cones sequences to collect data from 61 human subjects. Regions of interest (ROIs) were outlined by 2 experienced radiologists based on subtracted T1ρ -weighted MR images. Transfer learning was applied to develop 2D attention U-Net convolutional neural networks for the menisci segmentation based on each radiologist's ROIs separately. Dice scores were calculated to assess segmentation performance. Next, the T1, T1ρ , T2∗ relaxations, and ROI areas were determined for the manual and automatic segmentations, then compared.ResultsThe models developed using ROIs provided by 2 radiologists achieved high Dice scores of 0.860 and 0.833, while the radiologists' manual segmentations achieved a Dice score of 0.820. Linear correlation coefficients for the T1, T1ρ , and T2∗ relaxations calculated using the automatic and manual segmentations ranged between 0.90 and 0.97, and there were no associated differences between the estimated average meniscal relaxation parameters. The deep learning models achieved segmentation performance equivalent to the inter-observer variability of 2 radiologists.ConclusionThe proposed deep learning-based approach can be used to efficiently generate automatic segmentations and determine meniscal relaxations times. The method has the potential to help radiologists with the assessment of meniscal diseases, such as OA

Advanced magnetic resonance imaging of cartilage components in haemophilic joints reveals that cartilage hemosiderin correlates with joint deterioration.

IntroductionEvidence suggests that toxic iron is involved in haemophilic joint destruction.AimTo determine whether joint iron deposition is linked to clinical and imaging outcomes in order to optimize management of haemophilic joint disease.MethodsAdults with haemophilia A or haemophilia B (n = 23, ≥ age 21) of all severities were recruited prospectively to undergo assessment with Hemophilia Joint Health Scores (HJHS), pain scores (visual analogue scale [VAS]) and magnetic resonance imaging (MRI) at 3T using conventional MRI protocols and 4-echo 3D-UTE-Cones sequences for one affected arthropathic joint. MRI was scored blinded by two musculoskeletal radiologists using the International Prophylaxis Study Group (IPSG) MRI scale. Additionally, UTE-T2* values of cartilage were quantified. Correlations between parameters were performed using Spearman rank correlation. Two patients subsequently underwent knee arthroplasty, which permitted linking of histological findings (including Perl's reaction) with MRI results.ResultsMRI scores did not correlate with pain scores or HJHS. Sixteen joints had sufficient cartilage for UTE-T2* analysis. T2* values for cartilage correlated inversely with HJHS (rs  = -0.81, P < 0.001) and MRI scores (rs  = -0.52, P = 0.037). This was unexpected since UTE-T2* values decrease with better joint status in patients with osteoarthritis, suggesting that iron was present and responsible for the effects. Histological analysis of cartilage confirmed iron deposition within chondrocytes, associated with low UTE-T2* values.ConclusionsIron accumulation can occur in cartilage (not only in synovium) and shows a clear association with joint health. Cartilage iron is a novel biomarker which, if quantifiable with innovative joint-specific MRI T2* sequences, may guide treatment optimization

Train Small, Model Big: Scalable Physics Simulators via Reduced Order Modeling and Domain Decomposition

Numerous cutting-edge scientific technologies originate at the laboratory scale, but transitioning them to practical industry applications is a formidable challenge. Traditional pilot projects at intermediate scales are costly and time-consuming. An alternative, the E-pilot, relies on high-fidelity numerical simulations, but even these simulations can be computationally prohibitive at larger scales. To overcome these limitations, we propose a scalable, physics-constrained reduced order model (ROM) method. ROM identifies critical physics modes from small-scale unit components, projecting governing equations onto these modes to create a reduced model that retains essential physics details. We also employ Discontinuous Galerkin Domain Decomposition (DG-DD) to apply ROM to unit components and interfaces, enabling the construction of large-scale global systems without data at such large scales. This method is demonstrated on the Poisson and Stokes flow equations, showing that it can solve equations about $15 - 40$ times faster with only $\sim$ $1\%$ relative error. Furthermore, ROM takes one order of magnitude less memory than the full order model, enabling larger scale predictions at a given memory limitation.Comment: 40 pages, 12 figures. Submitted to Computer Methods in Applied Mechanics and Engineerin

The Public Health Impact of Paxlovid COVID-19 Treatment in the United States

The antiviral drug Paxlovid has been shown to rapidly reduce viral load. Coupled with vaccination, timely administration of safe and effective antivirals could provide a path towards managing COVID-19 without restrictive non-pharmaceutical measures. Here, we estimate the population-level impacts of expanding treatment with Paxlovid in the US using a multi-scale mathematical model of SARS-CoV-2 transmission that incorporates the within-host viral load dynamics of the Omicron variant. We find that, under a low transmission scenario (Re∼1.2) treating 20% of symptomatic cases would be life and cost saving, leading to an estimated 0.26 (95% CrI: 0.03, 0.59) million hospitalizations averted, 30.61 (95% CrI: 1.69, 71.15) thousand deaths averted, and US$52.16 (95% CrI: 2.62, 122.63) billion reduction in health- and treatment-related costs. Rapid and broad use of the antiviral Paxlovid could substantially reduce COVID-19 morbidity and mortality, while averting socioeconomic hardship