Reconstruction Cost Research Articles

Model-based reconstruction for looping-star MRI.

The aim of this study was to develop a reconstruction method that more fully models the signals and reconstructs gradient echo (GRE) images without sacrificing the signal to noise ratio and spatial resolution, compared to conventional gridding and model-based image reconstruction method. By modeling the trajectories for every spoke and simplifying the scenario to only echo-in and echo-out mixture, the approach explicitly models the overlapping echoes. After modeling the overlapping echoes with two system matrices, we use the conjugate gradient algorithm (CG-SENSE) with the nonuniform FFT (NUFFT) to optimize the image reconstruction cost function. The proposed method is demonstrated in phantoms and in-vivo volunteer experiments for three-dimensional, high-resolution T2*-weighted imaging and functional MRI tasks. Compared to the gridding method, the high resolution protocol exhibits improved spatial resolution and reduced signal loss as a result of less intra-voxel dephasing. The fMRI task shows that the proposed model-based method produced images with reduced artifacts and blurring as well as more stable and prominent time courses. The proposed model-based reconstruction results shows improved spatial resolution and reduced artifacts. The fMRI task shows improved time series and activation map due to the reduced overlapping echoes and under-sampling artifacts.

Financial Toxicity in Breast Reconstruction: The Role of the Surgeon-Patient Cost-of-Care Discussion.

The financial burden of breast cancer treatment and reconstruction is a significant concern for patients. Patient desire for preoperative cost-of-care counseling while navigating the reconstructive process remains unknown. A cross-sectional survey of women from the Love Research Army was conducted. An electronic survey was distributed to women over 18 years of age and at least 1 year after postmastectomy breast reconstruction. Descriptive statistics and multivariable modeling were used to determine desire for and occurrence of cost-of-care discussions, and factors associated with preference for such discussions. Secondary outcomes included the association of financial toxicity with desire for cost discussions. Among 839 women who responded, 620 women (74.1%) did not speak to their plastic surgeon and 480 (57.4%) did not speak to a staff member regarding costs of breast reconstruction. Of the 550 women who reported it would have been helpful to discuss costs, 315 (57.3%) were not engaged in a financial conversation initiated by a health care provider. A greater proportion of women who reported financial toxicity, compared to those who did not, would have preferred to discuss costs with their plastic surgeon (65.2% vs. 43.5%, p < 0.001) or a staff member (75.5% vs. 59.3%, p < 0.001). Among women with financial toxicity, those who had some form of insurance (private, Medicaid, Medicare, "other") were significantly more likely to prefer a cost-of-care discussion ( p < 0.001, p = 0.02, p = 0.05, p = 0.01). Financial discussions about the potential costs of breast reconstruction seldom occurred in this national cohort. Given the reported preference and unmet need for financial discussions by a majority of women, better cost transparency and communication is needed.

Learned Full Waveform Inversion Incorporating Task Information for Ultrasound Computed Tomography.

Ultrasound computed tomography (USCT) is an emerging imaging modality that holds great promise for breast imaging. Full-waveform inversion (FWI)-based image reconstruction methods incorporate accurate wave physics to produce high spatial resolution quantitative images of speed of sound or other acoustic properties of the breast tissues from USCT measurement data. However, the high computational cost of FWI reconstruction represents a significant burden for its widespread application in a clinical setting. The research reported here investigates the use of a convolutional neural network (CNN) to learn a mapping from USCT waveform data to speed of sound estimates. The CNN was trained using a supervised approach with a task-informed loss function aiming at preserving features of the image that are relevant to the detection of lesions. A large set of anatomically and physiologically realistic numerical breast phantoms (NBPs) and corresponding simulated USCT measurements was employed during training. Once trained, the CNN can perform real-time FWI image reconstruction from USCT waveform data. The performance of the proposed method was assessed and compared against FWI using a hold-out sample of 41 NBPs and corresponding USCT data. Accuracy was measured using relative mean square error (RMSE), structural self-similarity index measure (SSIM), and lesion detection performance (DICE score). This numerical experiment demonstrates that a supervised learning model can achieve accuracy comparable to FWI in terms of RMSE and SSIM, and better performance in terms of task performance, while significantly reducing computational time.

Meshed Dermal Sling for Prepectoral Breast Reconstruction.

The best breast reconstruction solution after mastectomy remains a topic of wide debate. Recently, the focus in the field of implant-based reconstruction has been on the increasing indications for prepectoral reconstruction. This offers undoubted advantages over subpectoral reconstruction, ranging from better aesthetic results and patient comfort to a less invasive procedure that spares the pectoralis major muscle, reducing pain and postoperative recovery time. The dermal sling is a reconstructive variant introduced by Bostwick in the 1990s and is commonly used to complete the subpectoral pocket in one- or two-stage reconstruction, creating a dual-plane reconstruction. This method may be indicated after mastectomy for both therapeutic and prophylactic purposes. It can also be used for unilateral and bilateral reconstructions. We propose a new meshed dermal sling technique that allows complete prepectoral reconstruction without the use of acellular dermal matrix, thus reducing the cost of reconstruction. It also allows the indication for complete prepectoral reconstruction to be extended to patients with medium breast volume and grade 1 or 2 ptosis, without the need to use acellular dermal matrix or the pectoralis major muscle to complete the breast pocket.

DIR3D: Cascaded Dual-Domain Inter-Scale Mutual Reinforcement 3D Network for highly accelerated 3D MR image reconstruction

Deep Learning has been successfully applied to reconstruct Magnetic Resonance (MR) images from undersampled k-space data to achieve the acceleration of MRI. However, most existing works focused on 2D MRI scans and perform reconstruction in a slice-by-slice manner due to the tremendous computation and memory cost of 3D MRI reconstruction, resulting in a blank in the research of 3D MRI acceleration. Providing more accurate and diagnostic information, 3D MRI requires excessively long scan time. To accelerate 3D MRI, in this work, we design a lightweight and powerful cascaded 3D network DIR3D utilizing a previously proposed computation-friendly data processing strategy. Specifically, we propose an efficient block called Dual-Domain Inter-Scale Mutual Reinforcement Block (DIRB) to fuse multi-scale features locally and globally with neglectable computation and memory costs, which enhances the representative ability of the network. To allow more flexibility, we further redesign the commonly used Data Consistency (DC) layer by introducing a learnable adaptor which enables the network to perform point-wise adaptive merge of the reconstructed and sampled k-space data while ensuring data consistency. We conduct comprehensive experiments on the Stanford MRIData and evaluate our DIR3D from multiple perspectives. When achieving the same acceleration factors, our proposed DIR3D consistently outperforms other state-of-the-art 2D methods at multiple subsampling masks, especially for highly undersampled data, which provides strong evidence for the superiority of our DIR3D for 3D MRI acceleration. Additionally, at the inference stage, our DIR3D can achieve a much higher reconstruction efficiency.

EE741 Costs of Breast Surgery Reconstruction and Mastectomy in France between 2019 and 2021

EE741 Costs of Breast Surgery Reconstruction and Mastectomy in France between 2019 and 2021

Identifying variation in the cost of abdominally based breast reconstruction in the UK

To understand variation in the cost of autologous breast reconstruction in the UK, including identifying key areas of cost variability, differences between and within units and the impact of enhanced recovery protocols (ERAS). A micro-costing study was designed based on the responses to a national survey of clinical preferences completed by the majority of plastic surgeons and anaesthetists involved in the UK. Detailed costs were estimated from macro elements such as ward and theatre running costs, down to that of surgical meshes, anaesthetic drugs and flap monitoring devices. The largest variation in cost arose from postoperative location and length of stay, preoperative imaging and flap monitoring strategies. Plastic surgeon costs varied from £1282 to £3141, whereas anaesthetic costs were between £32 and £151 (not including salary). Estimated cost variation within units was up to £893 per case. Units with ERAS had significantly lower total costs than those without (p < 0.05). This study reveals significant cost variation in breast reconstruction in the UK based on clinician preferences. Many areas of practice driving this variation lack strong evidence of any clinical advantage. The total cost of a deep inferior epigastric perforator in the majority, if not all units, likely surpasses the national tariff for reimbursement, particularly when considering additional resource demand for immediate and bilateral breast reconstruction, as well as future symmetrisation procedures. Whilst units should look to streamline costs through ERAS, there should also be a realistic tariff that promotes excellent care.

Comprehensive energy efficiency optimization algorithm for steel load considering network reconstruction and demand response

Industrial loads are usually energy intensive and inefficient. The optimization of energy efficiency management in steel plants is still in the early stage of development. Considering the topology of power grid, it is an urgent problem to improve the operation economy and load side energy efficiency of steel plants. In this paper, a two-level collaborative optimization method is proposed, which takes into account the dynamic reconstruction cost, transmission loss cost, energy cost and demand response benefit. The upper level objective is the optimization of topology in the grid structure to optimize the power loss and dynamic reconstruction costs of the grid. The lower level is the energy cost considering demand response, real time price and dynamic demand response price. Firstly, the mathematical models of stable load, impact load and the steel production line load are built. The key parameters are identified by the Back Propagation neural network algorithm according to the actual production data. Secondly, considering the constraints of grid structure and load operation capacity, the impact of dynamic grid loss and real-time dynamic electricity price on the energy efficiency of the whole grid are analyzed in depth. The optimal operation model considering the dynamic reconfiguration and grid tramission loss of distribution network is built. Taking a steel plant park in Northeast China as an example, it is proved that the optimization model can improve energy efficiency on the load side by optimizing energy consumption and demand response participation time on load side. The energy cost is reduced by 17.77% on the load side, the network loss is reduced by 1.8%, and the operating cost of the power grid is reduced by 26.2%, which has a positive effect on improving energy utilization efficiency, reducing distribution network loss, and improving overall economic efficiency.

A database and empirical model for earthquake post-loss amplification

The impact of destructive earthquakes might exceed the local capacity to cope with disasters and lead to an increase in the reconstruction costs. This phenomenon is commonly termed as post-loss amplification, and its main causes include the increase in the cost of construction materials and labor due to the sudden demand, the need to reconstruct following higher standards, or other unexpected costs. We reviewed 70 past earthquakes to identify events where post-loss amplification was observed, and collected a set of seismogenic, socio-economic, geographical, and impact variables for those events. Using this database, we developed two models to predict post-loss amplification, using a composite indicator that reflects the level of destruction in the region, or a parameter that characterizes the frequency of the event. This study indicates increased costs (&gt;10%) for events where the economic losses exceed 1% of the regional gross domestic product, or for events with an estimated return period of at least 10 years. These models can be applied directly in the amplification of economic losses in earthquake scenarios or in probabilistic seismic risk assessment.

The Effect of Staged Versus Usual Care Physiotherapy on Knee Function Following Anterior Cruciate Ligament Reconstruction.

The long duration and high cost of anterior cruciate ligament reconstruction (ACLR) rehabilitation can pose barriers to completing rehabilitation, the latter stages of which progress to demanding sport-specific exercises critical for a safe return to sport. A staged approach shifting in-person physiotherapy sessions to later months of recovery may ensure patients undergo the sport-specific portion of ACLR rehabilitation. Design/Objective: To compare postoperative outcomes of knee function in patients participating in a staged ACLR physiotherapy program to patients participating in usual care physiotherapy through a randomized controlled trial. One hundred sixty-two patients were randomized to participate in staged (n = 80) or usual care physiotherapy (n = 82) following ACLR and assessed preoperatively and postoperatively at 2weeks, 6weeks, 3months, and 6months. The staged group completed the ACLR rehabilitation protocol at home for the first 3months, followed by usual care in-person sessions. The usual care group completed in-person sessions for their entire rehabilitation. Outcome measures included the Lower Extremity Functional Scale, International Knee Documentation Committee Questionnaire, pain, range of motion, strength, and hop testing. There were no statistically significant between-group differences in measures of knee function at 6 months postoperative. Patients in the usual care group reported significantly higher International Knee Documentation Committee scores at 3 months postoperative (mean difference = 5.8; 95% confidence interval, 1.3 to 10.4; P = .01). A staged approach to ACLR rehabilitation does not appear to impede knee function at 6 months postoperative but may result in worse patient reported outcomes at early follow-ups.

Move up or move over: mapping opportunities for climate adaptation in Pakistan’s Indus plains

The 2022 Indus floods in Pakistan underscore the urgency of adapting to more frequent and severe natural disasters in a warming world. Post-disaster reconstruction offers a chance to built-in adaptation measures, but identifying feasible and cost-effective adaptation options is challenging, especially in data-scarce regions. Here we employ a high-resolution rapid assessment of flood stages combined with demographic data to identify adaptation opportunities and costs for the Indus floodplains. Under a plausible set of assumptions, we find that rebuilding houses in a flood-proof, elevated manner (‘moving up’) or (temporary) relocation (‘moving over’) could have protected 13%, respectively 16% of people affected during the 2022 floods, while the remaining 70% of people were exposed to shallow water levels that could have been addressed with low-cost adaptation. Implementing these measures during ongoing reconstruction could be an effective adaptation to future floods but will come with substantial costs. Rebuilding in a flood-proofed manner (‘moving up’) alone would already increase costs by 26%–63% ($1.5bn–$3.6bn) compared to estimated reconstruction costs without adaptation ($5.8bn). Additional costs would be incurred by relocation and adaptation of other infrastructure. The absence of local flood stage and socio-economic data creates uncertainty and points to future research avenues. Yet, our prototype approach demonstrates the value of rapid assessments for guiding post-disaster adaptation of livelihoods to future floods.

Performance analysis of multiple erasure coding methods

The blockchain is a decentralized digital ledger that provides tamper-proof and privacy fea-tures, making it a secure solution for various applications, including IoT homes and smart ag-riculture. However, these devices typically have limited storage resources, which poses chal-lenges in supporting the blockchain consensus process and storing the blockchain ledger. To address this issue, erasure coding can be employed, which reduces storage overhead and pro-vides data protection. Therefore, it is necessary to analyze the performance of multiple erasure coding methods. In this paper, a performance analysis was presented on (15,12) RS code and (16,12) pyramid code to evaluate their performance from three dimensions: fault tolerance, read reconstruction cost, and storage overhead. MATLAB simulations were conducted to in-vestigate the repair capabilities of the two encoding methods in response to different numbers of node failures and evaluate their performance. Finally, the performance of both codes was discussed based on the previous analysis.

Branch Structure of the National Economy and Directions of its Optimization in the Post-War Period

Introduction. The war in Ukraine caused significant damage to the economy, but also provided many new opportunities, made adjustments to the paradigm of post-war economic development, in particular, in view of the need to rebuild industries and ensure the reliability of their operation in the future, the variability of logistics supply routes. The complexity of post-war reconstruction is aggravated by the fact that Ukraine must modernize the defense industry and, at the same time, reduce the country's budget deficit, which requires an increase in budget revenues. The radical changes necessary for this will require optimization of the sectoral structure of the country's economy.&#x0D; Aim and tasks. The purpose of the study is to create a methodological approach to the sectoral optimization of the national economy in the post-war period and, for this, to develop a structural-mathematical model, determine priority areas of development of branches, and mechanisms of structural optimization of branch development.&#x0D; Results. A methodological approach to sectoral optimization of the national economy in the post-war period was developed, in which a structural-mathematical model was implemented. To optimize the industry structure, the use of a "trigger" mechanism is proposed: when the stimulation of the development of individual projects in high-tech industries leads to the rapid development of adjacent sectors of the economy, The need for comprehensive use of intensive and extensive mechanisms of post-war economic restructuring is indicated due to the specifics of the development of industries, the significant industry differentiation of damages and losses, and the need for expenses for the transformation and restructuring of industries. A diversification approach with the selection of short-, medium-, and long-term industry strategies was proposed.&#x0D; Conclusions. The developed mathematical model allows for the combination of sectoral optimization strategies of the economy and optimization coordination of sectoral strategies at the national level. An assessment of the costs of reconstruction and industry transformation was carried out, and the application of internal financing mechanisms, in particular, an increase in the level of added value, was substantiated. The mathematical model illustrates the possibility of maximizing the added value. Considering this, directions for industry optimization and prerequisites for restoration, reconstruction, and optimization of the industry structure in the post-war period are proposed. The given areas of industry-wide impact of the trigger mechanism indicate the prospects of its introduction.

친환경 건축물의 가치 및 향후 과제

As environmental pollution and climate change intensify, many buildings are increasingly adopting equipment and materials that affect their energy efficiency. However, there are insufficient tools, guidance materials, and studies for determining the value of green buildings. When comparing the cost of green buildings and eco-friendly certification systems, we must consider whether the certification system is viewed from a regulatory or a benefit perspective. This study is a foundational study for the appraisal of eco-friendly buildings. It focused on building energy efficiency certification among eco-friendly certification systems and the construction cost factors that affect the cost method from a regulatory standpoint. Accordingly, we conducted a theoretical review focusing on research data pertaining to the domestic and international construction costs of eco-friendly buildings, as well as appraisal standards and guidelines. Additionally, examples of construction costs were applied and compared to reflect the value of eco-friendly buildings from the perspective of cost method. It is necessary to differentiate between use value and capital premium when calculating reconstruction costs and facility prices. In addition, an expert council must discuss cases in which the certification validity period has expired.

Salience-based VNF placement method for evolving multiple network slices

Network Function Virtualization (NFV) technology enables the deployment of a distinct network slice composed of various virtualized network functions (VNFs) required for offering a communication service. As the user population or network traffic volume fluctuates, the capacity of the network slices must be dynamically adjusted. It is necessary to decide whether to place VNFs in appropriate locations such that the quality of services (QoS) is guaranteed while optimally utilizing the allocated resources. The above challenge can be addressed by solving an optimization problem, such as integer linear programming. However, as solving the optimization problem requires a considerable amount of time, it is not applicable in agile network control mechanisms. In this paper, we propose a network function placement algorithm based on salience, which is one of the characteristic metrics of links in a graph. Our proposal is aimed to provide the adequate placement in short time to achieve the following objectives of keeping the slice reconstruction cost low and avoiding the cases of QoS degradation. The simulation results show that our scheme performs equally well for different sized slices (i.e., the user population). We found that the network reconfiguration costs are low and almost the same for various sized slices when they are reconstructed by the proposed method in a substrate network of 200 nodes. Furthermore, we confirmed that the proposed method keeps the slice reconstruction cost low and avoids blocking of slice reconstruction even in the situations when a resource competition occurs among multiple slices.

Optimized strategies of green and grey infrastructures for integrated control objectives of runoff, waterlogging and WWDP in old storm drainages

Frequent waterlogging occurs in old high-density urban areas where the sewage is inappropriately connected to storm drainages, resulting in serious wet weather discharge pollution (WWDP). To address urban waterlogging and runoff, the optimization of green infrastructures (GIs) and grey infrastructures (GRs) has been proposed to improve rainwater management efficiency. However, most strategies neglect WWDP and fail to achieve integrated control of runoff, waterlogging, and discharge pollution. In the present study, a new optimization method was introduced to identify optimal solutions for renovating outdated storm drainage systems, considering the management of discharge pollution in wet weather. A case study in Shanghai, China was conducted to demonstrate the application of the method. The cost-benefit index (CBI) of optimized GIs (0.06) was lower than that of optimized GRs (2.78) under 22.2 mm rainfall (no runoff and WWDP), but the costs of the former were only half those of the latter. In a 5-year return period storm (no waterlogging), optimized GIs had a significantly higher CBI (2.85 times) compared to optimized GRs, costing only 44 % of the latter. When WWDP reached the control objective (COD≤70 mg/L), the optimized GIs needed to be further optimized with GRs. The CBI of optimized GI-GRs was higher than GRs by 2.50, and the cost was 58% of the latter. In areas with frequent low-intensity rainfall, optimized GIs and GRs should be selected based on local cost or benefit requirements for drainage reconstruction. In high-intensity storm-prone areas, the optimized GI-GR combination should be selected for drainage reconstruction. The proposed method can compensate for the shortcomings of existing optimization methods in controlling WWDP for the reconstruction of old storm drainages.

Reparations as a tool for holding the Russia responsible for war crimes committed on the territory of Ukraine

Introduction. The actions of the Russian Federation on the territory of Ukraine grossly violate the principles and norms of international law. Taking into account the fact that during the year it was not possible to settle the military conflict diplomatically, that is, based on the observance of the principles and norms of international law and the UN Charter, there is a need to assess the possibilities of Ukraine receiving reparations and to study this instrument of international justice from the point of view of holding the Russian Federation accountable for the military crimes committed on the territory of Ukraine. The purpose of the paper is to study the essence and features of reparations to Ukraine, as a tool to hold the Russian Federation accountable for the purpose of compensation for losses and damages for war crimes committed on the territory of Ukraine. Results. It was established that the compensation determined according to the principle of restitution cannot be limited only to the legally defined maximum amount of compensation or to any calculation that does not follow from a strict assessment of damages as a result of the military aggression of the Russian Federation. In the case of loss of life or infliction of bodily harm, torture, sexual violence, the operation of such a principle is problematic due to the fact that these crimes do not have a specific monetary definition. The direct losses of Ukraine, as well as the amount of additional costs for economic recovery and reconstruction, are analyzed, taking into account the perspective of Ukraine's integration into the European Union. The need to develop and implement a legitimate international mechanism that would provide compensation for the damages caused by Russia and be effective despite its categorical refusal to cooperate was argued. Conclusions. It is suggested that new agreements on reparations be regulated by international agreements. For Ukraine, this model of legal behavior is appropriate, because, thanks to the imposed sanctions, a significant number of assets of the Russian Federation are frozen, being under the control of foreign governments and, in the future, can be used to restore Ukraine as compensation for losses caused by military actions.The results of the study can be used in the process of forming a legal mechanism for compensation for losses, provided that war crimes on the territory of Ukraine are recognized as genocide of the Ukrainian people.

COST-UTILITY OF VARIOUS BIOLOGIC VERSUS ENDOPROSTHETIC RECONSTRUCTION FOR PRIMARY BONE SARCOMA OF THE HUMERUS

Background: The development of bone sarcoma treatment has resulted in a higher survival rate of patients including the developed surgical treatment called limb salvage surgery. Reconstructive surgery plays a vital role among patients and their quality of life after treatment. However, cost-effectiveness is another crucial factor in choosing a treatment method.&#x0D; Methods: Eighteen patients with osteosarcoma were recruited in this study. All were treated using limb salvage surgery. The data were collected using the utility coefficient from the EQ-5D-5L Health Questionnaire. The patient’s medical cost was obtained from Phramongkutklao Hospital, and all data were calculated for cost-effectiveness using the cost-utility analysis.&#x0D; Results: Endoprosthesis reconstruction exhibited the highest utility value of 0.85 QALY and the lowest treatment complications. Nevertheless, the most increased cost was an average of 238,432.34 THB. In terms of cost, the recycled autograft showed the lowest treatment cost at an average of 60,774.61 THB. However, the complication of this method was quite severe, with a 50% recurrence rate. Allograft reconstruction was the most cost-effective method with a lower cost than endoprosthesis reconstruction (61,341.40 THB), despite having a lower utility of 0.49 QALY.&#x0D; Conclusion: This study reported that endoprosthesis reconstruction resulted in more optimistic patient well-being but still indicated high cost. Using one-way sensitivity analysis, the QALY gain was only 16.9% of Thai per capita. When the cost of endoprosthesis reconstruction was reduced by only 15%, it could replace allograft reconstruction. In addition, an increase of the QALY, gaining only 20% of the average Thai per capita, would be cost-effective when the expense of endoprosthesis reconstruction was reduced by 4%.

Learning from the progressive collapse of buildings

As building structures in different parts of the world become increasingly exposed to extreme events, there has been a notable research and professional effort to ensure the design of more robust buildings which are insensitive to local failures. At the same time, several works performed in the field of forensic structural engineering have contributed to advancing knowledge on causes and risk factors of structural failure. This includes the creation of several collapse databases, most of which focus mainly on the underlying hazards causing failure. While such databases have provided invaluable insights for preventing structural failures, they do not lend themselves well to the analysis of how failure propagates, which can be useful for improving the progressive collapse resistance of buildings. To this end, a novel database of building collapses is presented in this article which systematically collects information on the hazards, initial failures and their corresponding propagation mechanisms. In addition, key information related to the context and the consequences of collapse is also gathered. Based on the information compiled in the database, this article provides an in-depth analysis of the most commonly occurring initial failures and propagation mechanisms, with significant conclusions extracted from the study of past collapses. The application of different consequence models for estimating fatalities and reconstruction costs is also presented, leading to recommendations for improving such models and related data collection strategies.

Risk-based transportation infrastructure management: An integrated framework and case study in USVI against coastal flood and sea level rise

This paper develops a comprehensive analytical framework for evaluating transportation infrastructure investment strategies for asset management considering the impacts of extreme natural hazards and climate change. We integrate quantitative risk analysis (RA) and economic impact analysis (EIA) into a comprehensive assessment of the benefits and costs of infrastructure maintenance, rehabilitation and reconstruction (MR&R) strategies. Moving beyond this, the framework explicitly incorporates the bidirectional feedback/impact between asset management (in normal situations) and risk management (against extreme conditions). To illustrate the application, the framework is applied to a case study on the roadway transportation system of the United States Virgin Islands (USVI), considering flood risk and the impact of future sea level rise. The case study demonstrates quantitative measures of the agency and user cost, risk, and other economic and environmental impacts under different MR&R, coastal flood and sea level rise scenarios. The framework supports high-level decision-making that transportation agencies face such as project prioritization, resilience planning, and capital planning. It can be generalized to analyze different types of infrastructure and natural hazards.