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Importance: Federally qualified health centers (FQHCs) have increasingly participated in the Medicare Shared Savings Program (MSSP) accountable care organizations (ACOs), one of the most widespread value-based programs. Although FQHCs may strengthen ACOs' ability to provide affordable care to diverse Medicare beneficiaries, evidence on ACOs' performance by FQHC participation is limited., Objectives: To compare beneficiary characteristics, utilization, expenditure, and quality between ACOs with and without FQHC participation and assess changes in ACO performance after including first FQHCs., Design, Setting, and Participants: Using MSSP public use files, this cross-sectional study compared performance of ACOs that always had FQHC participation with ACOs that never had FQHC participation from January 1, 2016, to December 31, 2022, supplemented with staggered difference-in-differences analyses of ACOs' first-time inclusion of FQHCs on performance measures. Data analysis was performed from December 1, 2023, to February 29, 2024., Exposure: Participation of FQHCs in the MSSP., Main Outcomes and Measures: Measures of ACO-assigned beneficiaries, utilization, expenditure, and quality per ACO-year., Results: Among 752 ACOs in the descriptive analysis, 140 ACOs always had at least 1 FQHC participant, whereas 612 ACOs never had FQHC participants. Compared with ACOs that never had FQHC participation, those that always had FQHC participation provided care to more socioeconomically disadvantaged beneficiaries (mean [SD] with dual eligibility, 2035.8 [2110.6] vs 1040.9 [1084.2] person-years; with disability, 3341.1 [3474.9] vs 1705.1 [1664.9] person-years; in racial and ethnic minoritized groups, 3690.6 [4118.4] vs 2515.1 [2762.9] person-years), with fewer primary care visits (mean [SD], 9956.6 [1926.3] vs 10 858.8 [2383.4] per 1000 person-years), more emergency department visits (mean [SD], 771.6 [190.9] vs 657.2 [160.0] per 1000 person-years), and lower levels of several quality measures. In the difference-in-differences analysis, 43 ACOs included FQHCs for the first time. Including first FQHCs was associated with increases of 872.9 dual-eligible (95% CI, 345.9-1399.8), 1137.6 disability (95% CI, 390.1-1885.1), and 1350.8 racial and ethnic minority (95% CI, 447.4-2254.1) person-years, with increases in rates of influenza immunization (5.9 percentage points [pp]; 95% CI, 1.4-10.4 pp), tobacco screening and cessation intervention (11.8 pp; 95% CI, 3.7-20.0 pp), and depression screening and follow-up (8.9 pp; 95% CI, 0.5-17.4 pp). No associations were observed between FQHC inclusion and utilization or expenditure., Conclusions and Relevance: In this repeated cross-sectional study, MSSP ACOs with FQHC participation served more socioeconomically disadvantaged Medicare beneficiaries than those without FQHC participation. The inclusion of first FQHCs was associated with increased rates of several preventive services without increasing costs. Participation of safety net practices appeared to improve access to ACOs among beneficiaries from underserved communities.

North Carolina Medicaid's Healthy Opportunities Pilots program is the country's first comprehensive program to evaluate the impact of paying community-based organizations to provide eligible Medicaid enrollees with an array of evidence-based services to address four domains of health-related social needs, one of which is housing. Using a mixed-methods approach, we mapped the distribution of severe housing problems and then examined the design and implementation of Healthy Opportunities Pilots housing services in the three program regions. Four cross-cutting implementation and policy themes emerged: accounting for variation in housing resources and needs to address housing insecurity, defining and pricing housing services in Medicaid, engaging diverse stakeholders across sectors to facilitate successful implementation, and developing sustainable financial models for delivery. The lessons learned and actionable insights can help inform the efforts of stakeholders elsewhere, particularly other state Medicaid programs, to design and implement cross-sectoral programs that address housing-related social needs by leveraging multiple policy-based resources. These lessons can also be useful for federal policy makers developing guidance on addressing housing-related needs in Medicaid.

Importance: Despite momentum for pediatric value-based payment models, little is known about tailoring design elements to account for the unique needs and utilization patterns of children and young adults., Objective: To simulate attribution to a hypothetical pediatric accountable care organization (ACO) and describe baseline demographic characteristics, expenditures, and utilization patterns over the subsequent year., Design, Setting, and Participants: This retrospective cohort study used Medicaid claims data for children and young adults aged 1 to 20 years enrolled in North Carolina Medicaid at any time during 2017. Children and young adults receiving at least 50% of their primary care at a large academic medical center (AMC) in 2017 were attributed to the ACO. Data were analyzed from April 2020 to March 2021., Main Outcomes and Measures: Primary outcomes were total cost of care and care utilization during the 2018 performance year., Results: Among 930 266 children and young adults (377 233 children [40.6%] aged 6-12 years; 470 612 [50.6%] female) enrolled in Medicare in North Carolina in 2017, 27 290 children and young adults were attributed to the ACO. A total of 12 306 Black non-Hispanic children and young adults (45.1%), 6308 Hispanic or Latinx children and young adults (23.1%), and 6531 White non-Hispanic children and young adults (23.9%) were included. Most attributed individuals (23 133 individuals [84.7%]) had at least 1 claim in the performance year. The median (IQR) total cost of care in 2018 was $347 ($107-$1123); 272 individuals (1.0%) accounted for nearly half of total costs. Compared with children and young adults in the lowest-cost quartile, those in the highest-cost quartile were more likely to have complex medical conditions (399 individuals [6.9%] vs 3442 individuals [59.5%]) and to live farther from the AMC (median [IQR distance, 6.0 [4.6-20.3] miles vs 13.9 [4.6-30.9] miles). Total cost of care was accrued in home (43%), outpatient specialty (19%), inpatient (14%) and primary (8%) care. More than half of attributed children and young adults received care outside of the ACO; the median (IQR) cost for leaked care was $349 ($130-$1326). The costliest leaked encounters included inpatient, ancillary, and home health care, while the most frequently leaked encounters included behavioral health, emergency, and primary care., Conclusions and Relevance: This cohort study found that while most children attributed to the hypothetical Medicaid pediatric ACO lived locally with few health care encounters, a small group of children with medical complexity traveled long distances for care and used frequent and costly home-based and outpatient specialty care. Leaked care was substantial for all attributed children, with the cost of leaked care being higher than the total cost of care. These pediatric-specific clinical and utilization profiles have implications for future pediatric ACO design choices related to attribution, accounting for children with high costs, and strategies to address leaked care.

Competing Interests: Funding Support and Author Disclosures Dr Casale has served as clinical and scientific advisor to GEN inCode. Dr Saunders has served as a consultant with Yale–New Haven Health System for the development of measures and development of quality measurement strategies for the Center for Medicare and Medicaid Innovation alternative payment models, which is funded under the Centers for Medicare and Medicaid Services contract no. 75FCMC18D0042/task order no. 75FCMC19F0003, “Quality Measure Development and Analytic Support,” base period. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose.

Background: Quality measurement has become a priority for national healthcare reform, and valid measures are necessary to discriminate hospital performance and support value-based healthcare delivery. The Commission on Cancer (CoC) is the largest cancer-specific accreditor of hospital quality in the United States and has implemented Quality of Care Measures to evaluate cancer care delivery. However, none has been formally tested as a valid metric for assessing hospital performance based on actual patient outcomes., Methods: Eligibility and compliance with the Quality of Care Measures are reported within the National Cancer Database, which also captures data for robust patient-level risk adjustment. Hospital-level compliance was calculated for the core measures, and the association with patient survival was tested using Cox regression., Results: Seven hundred sixty-eight thousand nine hundred sixty-nine unique cancer cases were included from 1323 facilities. Increasing hospital-level compliance was associated with improved survival for only two measures, including a 35% reduced risk of mortality for the gastric cancer measure G15RLN (HR 0.65, 95% CI 0.58-0.72) and a 19% reduced risk of mortality for the colon cancer measure 12RLN (HR 0.81, 95% CI 0.77-0.85). For the lung cancer measure LNoSurg, increasing compliance was paradoxically associated with an increased risk of mortality (HR 1.14, 95% CI 1.08-1.20). For the remaining measures, hospital-level compliance demonstrated no consistent association with patient survival., Conclusion: Hospital-level compliance with the CoC's Quality of Care Measures is not uniformly aligned with patient survival. In their current form, these measures do not reliably discriminate hospital performance and are limited as a tool for value-based healthcare delivery., (© 2021 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.)

Stroke is one of the leading causes of morbidity and mortality in the United States. While age-adjusted stroke mortality was falling, it has leveled off in recent years due in part to advances in medical technology, health care options, and population health interventions. In addition to adverse trends in stroke-related morbidity and mortality across the broader population, there are sociodemographic inequities in stroke risk. These challenges can be addressed by focusing on predicting and preventing modifiable upstream risk factors associated with stroke, but there is a need to develop a practical framework that health care organizations can use to accomplish this task across diverse settings. Accordingly, this article describes the efforts and vision of the multi-stakeholder Predict & Prevent Learning Collaborative of the Value in Healthcare Initiative, a collaboration of the American Heart Association and the Robert J. Margolis, MD, Center for Health Policy at Duke University. This article presents a framework of a potential upstream stroke prevention program with evidence-based implementation strategies for predicting, preventing, and managing stroke risk factors. It is meant to complement existing primary stroke prevention guidelines by identifying frontier strategies that can address gaps in knowledge or implementation. After considering a variety of upstream medical or behavioral risk factors, the group identified 2 risk factors with substantial direct links to stroke for focusing the framework: hypertension and atrial fibrillation. This article also highlights barriers to implementing program components into clinical practice and presents implementation strategies to overcome those barriers. A particular focus was identifying those strategies that could be implemented across many settings, especially lower-resource practices and community-based enterprises representing broad social, economic, and geographic diversity. The practical framework is designed to provide clinicians and health systems with effective upstream stroke prevention strategies that encourage scalability while allowing customization for their local context.

Utilization management strategies, including prior authorization, are commonly used to facilitate safe and guideline-adherent provision of new, individualized, and potentially costly cardiovascular therapies. However, as currently deployed, these approaches encumber multiple stakeholders. Patients are discouraged by barriers to appropriate access; clinicians are frustrated by the time, money, and resources required for prior authorizations, the frequent rejections, and the perception of being excluded from the decision-making process; and payers are weary of the intensive effort to design and administer increasingly complex prior authorization systems to balance value and appropriate use of these treatments. These issues highlight an opportunity to collectively reimagine utilization management as a transparent and collaborative system. This would benefit the entire healthcare ecosystem, especially in light of the shift to value-based payment. This article describes the efforts and vision of the multistakeholder Prior Authorization Learning Collaborative of the Value in Healthcare Initiative, a partnership between the American Heart Association and the Robert J. Margolis, MD, Center for Health Policy at Duke University. We outline how healthcare organizations can take greater utilization management responsibility under value-based contracting, especially under different state policies and local contexts. Even with reduced payer-mandated prior authorization in these arrangements, payers and healthcare organizations will have a continued shared need for utilization management. We present options for streamlining these programs, such as gold carding and electronic and automated prior authorization processes. Throughout the article, we weave in examples from cardiovascular care when possible. Although reimagining prior authorization requires collective action by all stakeholders, it may significantly reduce administrative burden for clinicians and payers while improving outcomes for patients.

The pipeline of new cardiovascular drugs is relatively limited compared with many other clinical areas. Challenges causing lagging drug innovation include the duration and expense of cardiovascular clinical trials needed for regulatory evaluation and approvals, which generally must demonstrate noninferiority to existing standards of care and measure longer-term outcomes. By comparison, there has been substantial progress in cardiovascular device innovation. There has also been progress in cardiovascular trial participation equity in recent years, especially among women, due in part to important efforts by Food and Drug Administration, National Institutes of Health, American Heart Association, and others. Yet women and especially racial and ethnic minority populations remain underrepresented in cardiovascular trials, indicating much work ahead to continue recent success. Given these challenges and opportunities, the multistakeholder Partnering with Regulators Learning Collaborative of the Value in Healthcare Initiative, a collaboration of the American Heart Association and the Robert J. Margolis, MD, Center for Health Policy at Duke University, identified how to improve the evidence generation process for cardiovascular drugs and devices. Drawing on a series of meetings, literature reviews, and analyses of regulatory options, the Collaborative makes recommendations across four identified areas for improvement. First, we offer strategies to enhance patient engagement in trial design, convenient participation, and meaningful end points and outcomes to improve patient recruitment and retention (major expenses in clinical trials). Second, new digital technologies expand the potential for real-world evidence to streamline data collection and reduce cost and time of trials. However, technical challenges must be overcome to routinely leverage real-world data, including standardizing data, managing data quality, understanding data comparability, and ensuring real-world evidence does not worsen inequities. Third, as trials are driven by evidence needs of regulators and payers, we recommend ways to improve their collaboration in trial design to streamline and standardize efficient and innovative trials, reducing costs and delays. Finally, we discuss creative ways to expand the minuscule proportion of sites involved in cardiovascular evidence generation and medical product development. These actions, paired with continued policy research into better ways to pay for and equitably develop therapies, will help reduce the cost and complexity of drug and device research, development, and trials.

Heart failure (HF) is a leading cause of hospitalizations and readmissions in the United States. Particularly among the elderly, its prevalence and costs continue to rise, making it a significant population health issue. Despite tremendous progress in improving HF care and examples of innovation in care redesign, the quality of HF care varies greatly across the country. One major challenge underpinning these issues is the current payment system, which is largely based on fee-for-service reimbursement, leads to uncoordinated, fragmented, and low-quality HF care. While the payment landscape is changing, with an increasing proportion of all healthcare dollars flowing through value-based payment models, no longitudinal models currently focus on chronic HF care. Episode-based payment models for HF hospitalization have yielded limited success and have little ability to prevent early chronic disease from progressing to later stages. The available literature suggests that primary care-based longitudinal payment models have indirectly improved HF care quality and cardiovascular care costs, but these models are not focused on addressing patients' longitudinal chronic disease needs. This article describes the efforts and vision of the multi-stakeholder Value-Based Models Learning Collaborative of The Value in Healthcare Initiative, a collaboration of the American Heart Association and the Robert J. Margolis, MD, Center for Health Policy at Duke University. The Learning Collaborative developed a framework for a HF value-based payment model with a longitudinal focus on disease management (to reduce adverse clinical outcomes and disease progression among patients with stage C HF) and prevention (an optional track to prevent high-risk stage B pre-HF from progressing to stage C). The model is designed to be compatible with prevalent payment models and reforms being implemented today. Barriers to success and strategies for implementation to aid payers, regulators, clinicians, and others in developing a pilot are discussed.

Objectives: To describe the landscape of Medicaid and the Children's Health Insurance Program beneficiary incentive programs for child health and garner key stakeholder insights on incentive program rationale, child and family engagement, and program evaluation., Methods: We identified beneficiary health incentive programs from 2005 to 2018 through a search of peer-reviewed and publicly available documents and through semistructured interviews with 80 key stakeholders (Medicaid and managed-care leadership, program evaluators, patient advocates, etc). This study highlights insights from 23 of these stakeholders with expertise on programs targeting child health (<18 years old) to understand program rationale, beneficiary engagement, and program evaluation., Results: We identified 82 child health-targeted beneficiary incentive programs in Medicaid and the Children's Health Insurance Program. Programs most commonly incentivized well-child checks ( n = 77), preventive screenings ( n = 30), and chronic disease management ( n = 30). All programs included financial incentives (eg, gift cards, premium incentives); some also offered incentive material prizes ( n = 12; eg, car seats). Loss-framed incentives were uncommon ( n = 1; eg, lost benefits) and strongly discouraged by stakeholders. Stakeholders suggested family engagement strategies including multigenerational incentives or incentives addressing social determinants of health. Regarding evaluation, stakeholders suggested incentivizing evidence-based preventive services (eg, vaccinations) rather than well-child check attendance, and considering proximal measures of child well-being (eg, school functioning)., Conclusions: As the landscape of beneficiary incentive programs for child health evolves, policy makers have unique opportunities to leverage intergenerational and social approaches for family engagement and to more effectively increase and evaluate programs' impact., Competing Interests: POTENTIAL CONFLICT OF INTEREST: Ms Vulimiri is employed by the North Carolina Department of Health and Human Services. Dr Saunders receives funding from a grant from the Robert Wood Johnson Foundation, which has supported work on an issue brief about Medicaid incentives for health behaviors. Dr Ubel has consulted for Humana, Inc. Dr McClellan is an independent board member for Johnson and Johnson, Cigna, and Alignment Healthcare; cochairs the Accountable Care Learning Collaborative and the Guiding Committee for the Health Care Payment Learning and Action Network; and receives fees for serving as an advisor for Cota, the Mitre Corporation, and the National Institute for Health Care Management; the other authors have indicated they have no potential conflicts of interest to disclose., (Copyright © 2019 by the American Academy of Pediatrics.)

Care for people living with serious illness is suboptimal for many reasons, including underpayment for key services (such as care coordination and social supports) in fee-for-service reimbursement. Accountable care organizations (ACOs) have potential to improve serious illness care because of their widespread dissemination, strong financial incentives for care coordination in downside-risk models, and flexibility in shared savings spending. Through a national survey we found that 94 percent of ACOs at least partially identify their seriously ill beneficiaries, yet only 8-21 percent have widely implemented serious illness initiatives such as advance care planning or home-based palliative care. We selected six diverse ACOs with successful programs for case studies and interviewed fifty-three leaders and front-line personnel. Cross-cutting themes include the need for up-front investment beyond shared savings to build serious illness infrastructure and workforce; supporting the business case for organizational buy-in; how ACO contract specifications affect savings for serious illness populations; and using data and health information technology to manage populations. We discuss the implications of the recent Medicare ACO regulatory overhaul and other policies related to serious illness quality measures, risk adjustment, attribution methods, supporting rural ACOs, and enhancing timely data access.

Radiologists play a critical role in helping the health care system achieve greater value. Unfortunately, today radiology is often judged by simple "checkbox" metrics, which neither directly reflect the value radiologists provide nor the outcomes they help drive. To change this system, first, we must attempt to better define the elusive term value and, then, quantify the value of imaging through more relevant and meaningful metrics that can be more directly correlated with outcomes. This framework can further improve radiology's value by enhancing radiologists' integration into the care team and their engagement with patients. With these improvements, we can maximize the value of imaging in the overall care of patients., (Copyright © 2018 American College of Radiology. Published by Elsevier Inc. All rights reserved.)

The ability of accountable care organizations (ACOs) to continue reducing costs and improving quality depends on understanding what affects their survival. We examined such factors for survival in the Medicare Shared Savings Program (MSSP) of 624 ACOs between performance years 2013 and 2017 (1,849 ACO-years). Overall, ACO exits from the MSSP decreased after ACOs' third year. Shared-savings bonus payment achievement, more care coordination, higher financial performance benchmarks, market-level Medicare cost growth, lower-risk patients, and contracts with upside-only risk were associated with longer survival. Quality scores, postacute care spending, organizational traits, and most market-context characteristics had no significant association with survival, which indicates that diverse organizations and markets can be successful. Put in context with the recently finalized MSSP rule from December 2018, our findings suggest that while new flexibilities for low-revenue ACOs likely reduce uncertainty for some, MSSP ACOs may need more than the new period of one to three years to prepare for downside risk. Policy makers should offer more support to ACOs (especially those with higher-risk patients) for building organizational competencies and should consider how benchmarking policy can fairly assess ACOs from regions with differing levels of cost growth.

Medicaid programs are increasingly adopting incentive programs to improve health behaviors among beneficiaries. There is limited evidence on what incentives are being offered to Medicaid beneficiaries, how programs are engaging beneficiaries, and how programs are evaluated. In 2017-18 we synthesized available information on these programs and interviewed eighty policy stakeholders to identify the rationale behind key program design decisions and stakeholders' recommendations for beneficiary engagement and program evaluation. Key underlying program rationales included improving the use of preventive services and promoting personal responsibility. Beneficiary engagement strategies emphasized meeting members where they are and offering prizes or services customized for certain groups. Stakeholders recommended collaborating with external evaluators to design and conduct robust evaluations of incentive programs. Finally, stakeholders recommended aligning beneficiary incentives with provider incentives and other payment reforms through the use of common meaningful measures to streamline program evaluation.

Objective: Surgical site infection (SSI) is the most common nosocomial infection, in vascular surgery patients, who experience a high rate of readmission. Facilitating transition from hospital to outpatient care with digital image-based wound monitoring has the potential to detect and to enable treatment of SSI at an early stage. In this study, we evaluated whether smartphone digital images can supplant in-person evaluation of postoperative vascular surgery wounds., Methods: We developed a wound assessment checklist using previously validated criteria. We recruited adults who underwent a vascular surgical procedure between 2014 and 2015, involving an incision of at least 3 cm, from a high-volume academic vascular surgery service. Vascular surgery care providers evaluated wounds in person using the assessment checklist; a different group of providers evaluated wounds by a smartphone digital image. Inter-rater agreement coefficients for wound characteristics and treatment plan were calculated within and between the in-person group and the digital image group; the sensitivity and specificity of digital images relative to in-person evaluation were determined., Results: We assessed a total of 80 wounds. Regardless of modality, inter-rater agreement was poor when wounds were evaluated for the presence of ecchymosis and redness; moderate for cellulitis; and high for the presence of a drain, necrosis, or dehiscence. As expected, the presence of drainage was more readily observed in person. Inter-rater agreement was high for both in-person and image-based assessment with respect to course of treatment, with near-perfect agreement for treatments ranging from antibiotics to surgical débridement to hospital readmission. No difference in agreement emerged when raters evaluated poor-quality compared with high-quality images. For most parameters, specificity was higher than sensitivity for image-based compared with "gold standard" in-person assessment., Conclusions: Using smartphone digital images is a valid method for evaluating postoperative vascular surgery wounds and is comparable to in-person evaluation with regard to most wound characteristics. The inter-rater reliability for determining treatment recommendations was universally high. Remote wound monitoring and assessment may play an integral role in future transitional care models to decrease readmission for SSI in vascular or other surgical patients. These findings will inform smartphone implementation in the clinical care setting as wound images transition from informal clinical communication to becoming part of the care standard., (Copyright © 2016 Society for Vascular Surgery. Published by Elsevier Inc. All rights reserved.)

OBJECTIVE To evaluate a feline-specific multiplex, bead-based assay system for detection of recombinant and native proteins in serum samples and in EDTA-treated and heparinized plasma samples. SAMPLE Serum samples and EDTA-treated and heparinized plasma samples from 30 sick cats and 9 healthy client-owned cats and heparinized whole blood samples from 5 healthy purpose-bred cats. PROCEDURES Ability of the assay system to detect 19 recombinant and native immunologically active proteins in plasma and serum samples from healthy and purpose-bred cats was evaluated via spike-and-recovery tests, assessments of inter- and intra-assay variation, linearity results, and leukocyte stimulation. Effects of various concentrations of heparin and serum matrix solution on percentages of analytes recovered were also evaluated. Analyte concentrations in samples from healthy and sick cats were measured and compared between groups. RESULTS Percentages of analytes recovered were unsatisfactory for most assays. Serum and heparinized plasma samples yielded better recovery results than did EDTA-treated plasma samples. Use of serum matrix solution did not improve results. Use of heparin concentrations greater than the recommended range affected the results. Linearity of results was difficult to assess because of the poor recovery. For the analytes that were recovered sufficiently for assessment, linearity appeared to be reasonable despite the limited detection. CONCLUSIONS AND CLINICAL RELEVANCE Poor percentages of analytes recovered and adverse effects of sample protein matrix limited the usefulness of the multiplex, bead-based assay system for measurement of immunologically active proteins in solutions with high protein content; however, recovery results were fairly linear, potentially allowing evaluation of feline plasma or serum samples with high analyte concentrations.

Objective: Surgical site infection (SSI) is one of the most common postoperative complications after vascular reconstruction, producing significant morbidity and hospital readmission. In contrast to SSI that develops while patients are still hospitalized, little is known about the cohort of patients who develop SSI after discharge. In this study, we explore the factors that lead to postdischarge SSI, investigate the differences between risk factors for in-hospital vs postdischarge SSI, and develop a scoring system to identify patients who might benefit from postdischarge monitoring of their wounds., Methods: Patients who underwent major vascular surgery from 2005 to 2012 for aneurysm and lower extremity occlusive disease were identified from the American College of Surgeons National Surgical Quality Improvement Program Participant Use Files. Patients were categorized as having no SSI, in-hospital SSI, or SSI after hospital discharge. Predictors of postdischarge SSI were determined by multivariable logistic regression and internally validated by bootstrap resampling. Risk scores were assigned to all significant variables in the model. Summative risk scores were collapsed into quartile-based ordinal categories and defined as low, low/moderate, moderate/high, and high risk. Multivariable logistic regression was used to determine predictors of in-hospital SSI., Results: Of the 49,817 patients who underwent major vascular surgery, 4449 (8.9%) were diagnosed with SSI (2.1% in-hospital SSI; 6.9% postdischarge SSI). By multivariable analysis, factors significantly associated with increased odds of postdischarge SSI include female gender, obesity, diabetes, smoking, hypertension, coronary artery disease, critical limb ischemia, chronic obstructive pulmonary disease, dyspnea, neurologic disease, prolonged operative time >4 hours, American Society of Anesthesiology class 4 or 5, lower extremity revascularization or aortoiliac procedure, and groin anastomosis. The model exhibited moderate discrimination (bias-corrected C statistic, 0.691) and excellent internal calibration. The postdischarge SSI rate was 2.1% for low-risk patients, 5.1% for low/moderate-risk patients, 7.8% for moderate/high-risk patients, and 14% for high-risk patients. In a comparative analysis, comorbidities were the primary driver of postdischarge SSI, whereas in-hospital factors (operative time, emergency case status) and complications predicted in-hospital SSI., Conclusions: The majority of SSIs after major vascular surgery develop following hospital discharge. We have created a scoring system that can select a cohort of patients at high risk for SSI after discharge. These patients can be targeted for transitional care efforts focused on early detection and treatment with the goal of reducing morbidity and preventing readmission secondary to SSI., (Copyright © 2015 Society for Vascular Surgery. Published by Elsevier Inc. All rights reserved.)

Background: Information technology is transforming health care communication. Using smartphones to remotely monitor incisional wounds via digital photos as well as collect postoperative symptom information has the potential to improve patient outcomes and transitional care. We surveyed a vulnerable patient population to evaluate smartphone capability and willingness to adopt this technology., Methods: We surveyed 53 patients over a 9-mo period on the vascular surgery service at a tertiary care institution. Descriptive statistics were calculated to describe survey item response., Results: A total of 94% of recruited patients (50 of 53) participated. The cohort was 50% female, and the mean age was age 70 y (range: 41-87). The majority of patients owned cell phones (80%) and 23% of these cell phones were smartphones. Ninety percent of patients had a friend or family member that could help take and send photos with a smartphone. Ninety-two percent of patients reported they would be willing to take a digital photo of their wound via a smartphone (68% daily, 22% every other day, 2% less than every other day, and 8% not at all). All patients reported they would be willing to answer questions related to their health via a smartphone. Patients identified several potential difficulties with regard to adopting a smartphone wound-monitoring protocol including logistics related to taking photos, health-related questions, and coordination with caretakers., Conclusions: Our survey demonstrates that an older patient cohort with significant comorbidity is able and willing to adopt a smartphone-based postoperative monitoring program. Patient training and caregiver participation will be essential to the success of this intervention., (Copyright © 2015 Elsevier Inc. All rights reserved.)

Background: The association between early outpatient follow-up and 30-day readmission has not been evaluated in any surgical population. Our study characterizes the relationship between outpatient follow-up and early readmissions among surgical patients., Methods: We queried the medical record at a large, tertiary care institution (July 2008-December 2012) to determine rates of 30-day outpatient follow-up and readmission for general or vascular operative procedures., Results: The majority of discharges for general (84% of 7,552) and vascular (75% of 2,362) surgery had a follow-up visit before readmission or within 30 days of discharge. General surgery patients who were not readmitted had high rates of follow-up (88%) and received follow-up at approximately 2 weeks postdischarge (median, 11 days after discharge). In contrast, readmitted general surgery patients received first follow-up at 1 week (median, 8 days); 49% had follow-up. Vascular surgery patients showed a similar trend. More than one half of patients readmitted after follow-up were readmitted within 24 hours of their most recent outpatient visit., Conclusion: Current routine follow-up does not occur early enough to detect adverse events and prevent readmission. Early outpatient care may prevent readmission in some patients, but often serves as a conduit for readmission among patients already experiencing complications., (Copyright © 2014 Elsevier Inc. All rights reserved.)

Objective: Reducing readmissions represents a unique opportunity to improve care and reduce health care costs and is the focus of major payers. A large number of surgical patients are readmitted to hospitals other than where the primary surgery was performed, resulting in clinical decisions that do not incorporate the primary surgeon and potentially alter outcomes. This study characterizes readmission to primary vs different hospitals after abdominal aortic aneurysm (AAA) repair and examines the implications with regard to mortality and cost., Methods: Patients who underwent open or endovascular aneurysm repair for AAA were identified from the Centers for Medicare and Medicaid Services Chronic Conditions Warehouse, a random 5% national sample of Medicare beneficiaries from 2005 to 2009. Outcomes for patients who underwent AAA repair and were readmitted within 30 days of initial discharge were compared based on readmission location (primary vs different hospital)., Results: A total of 885 patients underwent AAA repair and were readmitted within 30 days. Of these, 626 (70.7%) returned to the primary facility, and 259 (29.3%) returned to a different facility. Greater distance from patient residence to the primary hospital was the strongest predictor of readmission to a different facility. Patients living 50 to 100 miles from the primary hospital were more likely to be readmitted to a different hospital compared with patients living <10 miles away (odds ratio, 8.50; P < .001). Patients with diagnoses directly related to the surgery (eg, wound infection) were more likely to be readmitted to the primary hospital, whereas medical diagnoses (eg, pneumonia and congestive heart failure) were more likely to be treated at a different hospital. There was no statistically significant difference in mortality between patients readmitted to a different or the primary hospital. Median total 30-day payments were significantly lower at different vs primary hospitals (primary, $11,978 vs different, $11,168; P = .04)., Conclusions: Readmission to a different facility after AAA repair is common and occurs more frequently than for the overall Medicare population. Patients travelling a greater distance for AAA repair are more likely to return to different vs the primary hospital when further care is required. For AAA repair, quality healthcare may be achieved at marginally lower cost and with greater patient convenience for selected readmissions at hospitals other than where the initial procedure was performed., (Copyright © 2014 Society for Vascular Surgery. Published by Mosby, Inc. All rights reserved.)

Introduction: Despite significant advances in vascular biology, bioengineering, and pharmacology, restenosis remains a limitation to the overall efficacy of vascular reconstructions, both percutaneous and open. Although the pathophysiology of intimal hyperplasia is complex, a number of drugs and molecular tools have been identified that can prevent restenosis. Moreover, the focal nature of this process lends itself to treatment with local drug administration. This article provides a broad overview of current and future techniques for local drug delivery that have been developed to prevent restenosis after vascular interventions., Methods: A systematic electronic literature search using PubMed was performed for all accessible published articles through September 2012. In an effort to remain current, additional searches were performed for abstracts presented at relevant societal meetings, filed patents, clinical trials, and funded National Institutes of Health awards., Results: The efficacy of local drug delivery has been demonstrated in the coronary circulation with the current clinical use of drug-eluting stents. Until recently, however, drug-eluting stents were not found to be efficacious in the peripheral circulation. Further pursuit of intraluminal devices has led to the development of balloon-based technologies, with a recent surge in trials involving drug-eluting balloons. Early data appear encouraging, particularly for treatment of superficial femoral artery lesions, and several devices have recently received the Conformité Européene mark in Europe. Investigators have also explored the periadventitial application of biomaterials containing antirestenotic drugs, an approach that could be particularly useful for surgical bypass or endarterectomy. In the past, systemic drug delivery has been unsuccessful; however, there has been recent exploration of intravenous delivery of drugs designed specifically to target injured or reconstructed arteries. Our review revealed a multitude of additional interesting strategies, including >65 new patents issued during the past 2 years for approaches to local drug delivery focused on preventing restenosis., Conclusions: Restenosis after intraluminal or open vascular reconstruction remains an important clinical problem. Success in the coronary circulation has not translated into solutions for the peripheral arteries. However, our literature review reveals a number of promising approaches, including drug-eluting balloons, periadventitial drug delivery, and targeted systemic therapies. These and other innovations suggest that the future is bright and that a solution for preventing restenosis in peripheral vessels will soon be at hand., (Copyright © 2013 Society for Vascular Surgery. Published by Mosby, Inc. All rights reserved.)

Dual-energy contrast-enhanced breast tomosynthesis is a promising technique to obtain three-dimensional functional information from the breast with high resolution and speed. To optimize this new method, this study searched for the beam quality that maximized image quality in terms of mass detection performance. A digital tomosynthesis system was modeled using a fast ray-tracing algorithm, which created simulated projection images by tracking photons through a voxelized anatomical breast phantom containing iodinated lesions. The single-energy images were combined into dual-energy images through a weighted log subtraction process. The weighting factor was optimized to minimize anatomical noise, while the dose distribution was chosen to minimize quantum noise. The dual-energy images were analyzed for the signal difference to noise ratio (SdNR) of iodinated masses. The fast ray-tracing explored 523 776 dual-energy combinations to identify which yields optimum mass SdNR. The ray-tracing results were verified using a Monte Carlo model for a breast tomosynthesis system with a selenium-based flat-panel detector. The projection images from our voxelized breast phantom were obtained at a constant total glandular dose. The projections were combined using weighted log subtraction and reconstructed using commercial reconstruction software. The lesion SdNR was measured in the central reconstructed slice. The SdNR performance varied markedly across the kVp and filtration space. Ray-tracing results indicated that the mass SdNR was maximized with a high-energy tungsten beam at 49 kVp with 92.5 µm of copper filtration and a low-energy tungsten beam at 49 kVp with 95 µm of tin filtration. This result was consistent with Monte Carlo findings. This mammographic technique led to a mass SdNR of 0.92 ± 0.03 in the projections and 3.68 ± 0.19 in the reconstructed slices. These values were markedly higher than those for non-optimized techniques. Our findings indicate that dual-energy breast tomosynthesis can be performed optimally at 49 kVp with alternative copper and tin filters, with reconstruction following weighted subtraction. The optimum technique provides best visibility of iodine against structured breast background in dual-energy contrast-enhanced breast tomosynthesis.

Rationale and Objectives: Optimization studies for x-ray-based breast imaging systems using computer simulation can greatly benefit from a phantom capable of modeling varying anatomical variability across different patients. This study aimed to develop a three-dimensional phantom model with realistic and randomizable anatomical features., Materials and Methods: A voxelized breast model was developed consisting of an outer layer of skin and subcutaneous fat, a mixture of glandular and adipose, stochastically generated ductal trees, masses, and microcalcifications. Randomized realization of the breast morphology provided a range of patient models. Compression models were included to represent the breast under various compression levels along different orientations. A Monte Carlo (MC) simulation code was adapted to simulate x-ray based imaging systems for the breast phantom. Simulated projections of the phantom at different angles were generated and reconstructed with iterative methods, simulating mammography, breast tomosynthesis, and computed tomography (CT) systems. Phantom dose maps were further generated for dosimetric evaluation., Results: Region of interest comparisons of simulated and real mammograms showed strong similarities in terms of appearance and features. Noise-power spectra of simulated mammographic images demonstrated that the phantom provided target properties for anatomical backgrounds. Reconstructed tomosynthesis and CT images and dose maps provided corresponding data from a single breast enabling optimization studies. Dosimetry result provided insight into the dose distribution difference between modalities and compression levels., Conclusion: The anthropomorphic breast phantom, combined with the MC simulation platform, generated a realistic model for a breast imaging system. The developed platform is expected to provide a versatile and powerful framework for optimizing volumetric breast imaging systems., (Copyright © 2011 AUR. Published by Elsevier Inc. All rights reserved.)

DYT1 dystonia is an autosomal-dominantly inherited movement disorder, which is usually caused by a GAG deletion in the TOR1A gene. Due to the reduced penetrance of approximately 30-40%, the determination of the mutation in a subject is of limited use with regard to actual manifestation of symptoms. In the present study, we used Affymetrix oligonucleotide microarrays to analyze global gene expression in blood samples of 15 manifesting and 15 non-manifesting mutation carriers in order to identify a susceptibility profile beyond the GAG deletion which is associated with the manifestation of symptoms in DYT1 dystonia. We identified a genetic signature which distinguished between asymptomatic mutation carriers and symptomatic DYT1 patients with 86.7% sensitivity and 100% specificity. This genetic signature could correctly predict the disease state in an independent test set with a sensitivity of 87.5% and a specificity of 85.7%. Conclusively, this genetic signature might provide a possibility to distinguish DYT1 patients from asymptomatic mutation carriers., (Copyright 2009 Elsevier Inc. All rights reserved.)

Purpose: To assess, in a voxelized anthropomorphic breast phantom, how the conspicuity of breast masses and microcalcifications may be affected by applying reduced breast compression in tomosynthesis., Materials and Methods: A breast tomosynthesis system was modeled by using a Monte Carlo program and a voxelized anthropomorphic breast phantom. The Monte Carlo program created simulated tomosynthesis projection images, which were reconstructed by using filtered back-projection software. Reconstructed images were analyzed for mass and microcalcification conspicuity, or the ratio of the lesion contrast to the anatomic and quantum noise surrounding the lesion. This analysis was performed at two compression levels (standard and 12.5% reduction) and for two breast compression thicknesses (4 and 6 cm). The change in conspicuity was analyzed for significance by using a bootstrap method and a paired Student t test., Results: While keeping the glandular radiation dose constant with respective standard and reduced compression levels, the mean mass conspicuities were 1.39 +/- 0.15 (standard error of the mean) and 1.46 +/- 0.22 for a 4-cm breast compression phantom and 1.26 +/- 0.15 and 1.22 +/- 0.20 for a 6-cm breast phantom, and the mean microcalcification conspicuities were 16.2 +/- 2.87 and 18.6 +/- 2.63 for a 4-cm breast phantom and 11.4 +/- 1.11 and 10.6 +/- 1.18 for a 6-cm breast compression phantom., Conclusion: For constant glandular dose, mass and microcalcification conspicuity remained approximately constant with decreased compression. Constant conspicuity implies that reduced compression would have a minimal effect on radiologists' performance, which suggests that there is justification for a measured reduction of breast compression for breast tomosynthesis, increasing the comfort of women undergoing the examination.

Rationale and Objectives: Correlation imaging (CI) is a form of multiprojection imaging in which multiple images of a patient are acquired from slightly different angles. Information from these images is combined to make the final diagnosis. A critical factor affecting the performance of CI is its data acquisition scheme, because nonoptimized acquisition may distort pathologic indicators. The authors describe a computer-aided detection (CADe) methodology to optimize the acquisition scheme of CI for superior diagnostic accuracy., Materials and Methods: Images from 106 subjects were used. For each subject, 25 angular projections of a single breast were acquired. Projection images were supplemented with a simulated 3-mm three-dimensional lesion. Each projection was then processed using a traditional CADe algorithm at high sensitivity, followed by the reduction of false-positives by combining the geometric correlation information available from the multiple images. The performance of the CI system was determined in terms of free-response receiver-operating characteristic curves and the areas under receiver-operating characteristic curves. For optimization, the components of acquisition, such as the number of projections and their angular span, were systematically changed to investigate which of the many possible combinations maximized the obtainable CADe sensitivity and specificity., Results: The performance of the CI system was improved by increasing the angular span. Increasing the number of angular projections beyond a certain number did not improve performance. Maximum performance was obtained between 7 and 10 projections spanning a maximum angular arc of 45 degrees ., Conclusion: The findings suggest the existence of an optimum acquisition scheme for CI of the breast. CADe results confirmed earlier predictions on the basis of observer models. An optimized CI system may be an important diagnostic tool for improved breast cancer detection.

We studied the influence of signal variability on human and model observers for detection tasks with realistic simulated masses superimposed on real patient mammographic backgrounds and synthesized mammographic backgrounds (clustered lumpy backgrounds, CLB). Results under the signal-known-exactly (SKE) paradigm were compared with signal-known-statistically (SKS) tasks for which the observers did not have prior knowledge of the shape or size of the signal. Human observers' performance did not vary significantly when benign masses were superimposed on real images or on CLB. Uncertainty and variability in signal shape did not degrade human performance significantly compared with the SKE task, while variability in signal size did. Implementation of appropriate internal noise components allowed the fit of model observers to human performance.

A long circulating liposomal, nanoscale blood pool agent encapsulating traditional iodinated contrast agent (65 mg I/mL) was used for micro-computed tomography (CT) imaging of rats implanted with R3230AC mammary carcinoma. Three-dimensional vascular architecture of tumors was imaged at 100-micron isotropic resolution. The image data showed good qualitative correlation with pathologic findings. The approach holds promise for studying tumor angiogenesis and for evaluating anti-angiogenesis therapies.

This study analyzed how the inherent quality of diagnostic information in digital mammography could be affected by breast compression. A digital mammography system was modeled using a Monte Carlo algorithm based on the Penelope program, which has been successfully used to model several medical imaging systems. First, the Monte Carlo program was validated against previous measurements and simulations. Once validated, the Monte Carlo software modeled a digital mammography system by tracking photons through a voxelized software breast phantom, containing anatomical structures and breast masses, and following photons until they were absorbed by a selenium-based flat-panel detector. Simulations were performed for two compression conditions (standard compression and 12.5% reduced compression) and three photon flux conditions (constant flux, constant detector signal, and constant glandular dose). The results showed that reduced compression led to higher scatter fractions, as expected. For the constant photon flux condition, decreased compression also reduced glandular dose. For constant glandular dose, the SdNR for a 4 cm breast was 0.60 +/- 0.11 and 0.62 +/- 0.11 under standard and reduced compressions, respectively. For the 6 cm case with constant glandular dose, the SdNR was 0.50 +/- 0.11 and 0.49 +/- 0.10 under standard and reduced compressions, respectively. The results suggest that if a particular imaging system can handle an approximately 10% increase in total tube output and 10% decrease in detector signal, breast compression can be reduced by about 12% in terms of breast thickness with little impact on image quality or dose.

Multiprojection imaging is a technique in which a plurality of digital radiographic images of the same patient are acquired within a short interval of time from slightly different angles. Information from each image is combined to determine the final diagnosis. Projection data are either reconstructed into slices as in the case of tomosynthesis or analyzed directly as in the case of multiprojection correlation imaging technique, thereby avoiding reconstruction artifacts. In this study, the authors investigated the optimum geometry of acquisitions of a multiprojection breast correlation imaging system in terms of the number of projections and their total angular span that yield maximum performance in a task that models clinical decision. Twenty-five angular projections of each breast from 82 human subjects in our breast tomosynthesis database were each supplemented with a simulated 3 mm mass. An approach based on Laguerre-Gauss channelized Hotelling observer was developed to assess the detectability of the mass in terms of receiver operating characteristic (ROC) curves. Two methodologies were developed to integrate results from individual projections into one combined ROC curve as the overall figure of merit. To optimize the acquisition geometry, different components of acquisitions were changed to investigate which one of the many possible configurations maximized the area under the combined ROC curve. Optimization was investigated under two acquisition dose conditions corresponding to a fixed total dose delivered to the patient and a variable dose condition, based on the number of projections used. In either case, the detectability was dependent on the number of projections used, the total angular span of those projections, and the acquisition dose level. In the first case, the detectability approximately followed a bell curve as a function of the number of projections with the maximum between 8 and 16 projections spanning angular arcs of about 23 degrees-45 degrees, respectively. In the second case, the detectability increased with the number of projections approaching an asymptote at 11-17 projections for an angular span of about 45 degrees. These results indicate the inherent information content of the multi-projection image data reflecting the relative role of quantum and anatomical noise in multiprojection breast imaging. The optimization scheme presented here may be applied to any multiprojection imaging modalities and may be extended by including reconstruction in the case of digital breast tomosynthesis and breast computed tomography.

The purpose of this study was to examine the effects of different resolution and noise levels on task performance in digital mammography. This study created an image set with images at three different resolution levels, corresponding to three digital display devices, and three different noise levels, with noise magnitudes similar to full clinical dose, half clinical dose, and quarter clinical dose. The images were read by five experienced breast imaging radiologists. The data were then analyzed to compute two accuracy statistics (overall classification accuracy and lesion detection accuracy) and performance at four diagnostic tasks (detection of microcalcifications, benign masses, malignant masses, and discrimination of benign and malignant masses). Human observer results showed decreasing display resolution had little effect on overall classification accuracy and individual diagnostic task performance, but increasing noise caused overall classification accuracy to decrease by a statistically significant 21% as the breast dose went to one quarter of its normal clinical value. The noise effects were most prominent for the tasks of microcalcification detection and mass discrimination. When the noise changed from full clinical dose to quarter clinical dose, the microcalcification detection performance fell from 89% to 67% and the mass discrimination performance decreased from 93% to 79%, while malignant mass detection performance remained relatively constant with values of 88% and 84%, respectively. As a secondary aim, the image set was also analyzed by two observer models to examine whether their performance was similar to humans. Observer models differed from human observers and each other in their sensitivity to resolution degradation and noise. The primary conclusions of this study suggest that quantum noise appears to be the dominant image quality factor in digital mammography, affecting radiologist performance much more profoundly than display resolution.

Purpose: To experimentally determine the relationship between radiation dose and observer accuracy in the detection and discrimination of simulated lesions for digital mammography., Materials and Methods: This HIPAA-compliant study received institutional review board approval; the informed consent requirement was waived. Three hundred normal craniocaudal images were selected from an existing database of digital mammograms. Simulated mammographic lesions that mimicked benign and malignant masses and clusters of microcalcifications (3.3-7.4 cm in diameter) were then superimposed on images. Images were rendered without and with added radiographic noise to simulate effects of reducing the radiation dose to one half and one quarter of the clinical dose. Images were read by five experienced breast imaging radiologists. Results were analyzed to determine effects of reduced dose on overall interpretation accuracy, detection of microcalcifications and masses, discrimination between benign and malignant masses, and interpretation time., Results: Overall accuracy decreased from 0.83 with full dose to 0.78 and 0.62 with half and quarter doses, respectively. The decrease associated with transition from full dose to quarter dose was significant (P < .01), primarily because of an effect on detection of microcalcifications (P < .01) and discrimination of masses (P < .05). The level of dose reduction did not significantly affect detection of malignant masses (P > .5). However, reduced dose resulted in an increased mean interpretation time per image by 28% (P < .0001)., Conclusion: These findings suggest that dose reduction in digital mammography has a measurable but modest effect on diagnostic accuracy. The small magnitude of the effect in response to the drastic reduction of dose suggests potential for modest dose reductions in digital mammography.

The purpose of this study was to evaluate the effect of dose reduction in digital mammography on the detection of two lesion types-malignant masses and clusters of microcalcifications. Two free-response observer studies were performed-one for each lesion type. Ninety screening images were retrospectively selected; each image was originally acquired under automatic exposure conditions, corresponding to an average glandular dose of 1.3 mGy for a standard breast (50 mm compressed breast thickness with 50% glandularity). For each study, one to three simulated lesions were added to each of 40 images (abnormals) while 50 were kept without lesions (normals). Two levels of simulated system noise were added to the images yielding two new image sets, corresponding to simulated dose levels of 50% and 30% of the original images (100%). The manufacturer's standard display processing was subsequently applied to all images. Four radiologists experienced in mammography evaluated the images by searching for lesions and marking and assigning confidence levels to suspicious regions. The search data were analyzed using jackknife free-response (JA-FROC) methodology. For the detection of masses, the mean figure-of-merit (FOM) averaged over all readers was 0.74, 0.71, and 0.68 corresponding to dose levels of 100%, 50%, and 30%, respectively. These values were not statistically different from each other (F= 1.67, p=0.19) but showed a decreasing trend. In contrast, in the microcalcification study the mean FOM was 0.93, 0.67, and 0.38 for the same dose levels and these values were all significantly different from each other (F = 109.84, p < 0.0001). The results indicate that lowering the present dose level by a factor of two compromised the detection of microcalcifications but had a weaker effect on mass detection.

Mammography is currently the most established technique for the early detection of breast cancer. However, mammography would benefit from further improvements as it does produce some errors, such as not finding all early-stage cancers. The objectives of this study were first, to measure the timing of correct and incorrect reading decisions in mammography and second, to exploit those dependencies to improve accuracy in mammographic interpretation. To address these objectives, an experiment was conducted where experienced breast imaging radiologists reviewed 400 mammographic regions equally divided among images that contained simulated benign masses, malignant masses, malignant microcalcifications and no lesions. The experiment recorded the radiologists' decision as well as the length of time the mammogram was interpreted in. The experiment results showed that incorrect detection as well as incorrect classification decisions were associated with longer interpretation times (p<0.0001). The timing results were used to create a model that would flag cases for review that had a higher probability of error. The flagged cases had a median accuracy drop of 13% for detection decisions and 16% for classification decisions compared with unflagged cases. This suggests that interpretation time can be incorporated into mammographic decision-making in order to identify cases with higher probabilities of perceptual error that require further review.

Rationale and Objectives: To compare two display technologies, cathode ray tube (CRT) and liquid crystal display (LCD), in terms of diagnostic accuracy for several common clinical tasks in digital mammography., Materials and Methods: Simulated masses and microcalcifications were inserted into normal digital mammograms to produce an image set of 400 images. Images were viewed on one CRT and one LCD medical-quality display device by five experienced breast-imaging radiologists who rated the images using a categorical rating paradigm. The observer data were analyzed to determine overall classification accuracy, overall lesion detection accuracy, and accuracy for four specific diagnostic tasks: detection of benign masses, malignant masses, and microcalcifications, and discrimination of benign and malignant masses., Results: Radiologists had similar overall classification accuracy (LCD: 0.83 +/- 0.01, CRT: 0.82 +/- 0.01) and lesion detection accuracy (LCD: 0.87 +/- 0.01, CRT: 0.85 +/- 0.01) on both displays. The difference in accuracy between LCD and CRT for the detection of benign masses, malignant masses, and microcalcifications, and discrimination of benign and malignant masses was -0.019 +/- 0.009, 0.020 +/- 0.008, 0.012 +/- 0.013, and 0.0094 +/- 0.011, respectively. Overall, the two displays did not exhibit any statistically significant difference (P > .05)., Conclusion: This study explored the suitability of two different soft-copy displays for the viewing of mammographic images. It found that LCD and CRT displays offer similar clinical utility for mammographic tasks.

The performance of soft-copy displays plays a significant role in the overall image quality of a digital radiographic system. In this work, we discuss methods to characterize the resolution and noise of both cathode ray tube (CRT) and liquid crystal display (LCD) devices. We measured the image quality of five different commercial display devices, representing both CRT and LCD technologies, using a high-quality charge-coupled device (CCD) camera. The modulation transfer function (MTF) was calculated using the line technique, correcting for the MTF of the CCD camera and the display pixel size. The normalized noise power spectrum (NPS) was computed from two-dimensional Fourier analysis of uniform images. To separate the effects of pixel structure from interpixel luminance variations, we created structure-free images by eliminating the pixel structures of the display device. The NPS was then computed from these structure-free images to isolate interpixel luminance variations. We found that the MTF of LCDs remained close to the theoretical limit dictated by their inherent pixel size (0.85 +/- 0.08 at Nyquist frequency), in contrast to the MTF for the two CRT displays, which dropped to 0.15 +/- 0.08 at the Nyquist frequency. However, the NPS of LCDs showed significant peaks due to the subpixel structure, while the NPS of CRT displays exhibited a nearly flat power spectrum. After removing the pixel structure, the structured noise peaks for LCDs were eliminated and the overall noise magnitude was significantly reduced. The average total noise-to-signal ratio for CRT displays was 6.55% +/- 0.59%, of which 6.03% +/- 0.24% was due to interpixel luminance variations, while LCD displays had total noise to signal ratios of 46.1% +/- 5.1% of which 1.50% +/- 0.41% were due to interpixel luminance variations. Depending on the extent of the blurring and prewhitening processes of the human visual system, the magnitude of the display noise (including pixel structure) potentially perceived by the observer was reduced to 0.43% +/- 0.01% (accounting for blurring only) and 0.40 +/- 0.01% (accounting for blurring and prewhitening) for CRTs, and 1.02% +/- 0.22% (accounting for blurring only) and 0.36% +/- 0.08% (accounting for blurring and prewhitening) for LCDs.

The purpose of this study was to measure experimentally the physical performance of a prototype mammographic imager based on a direct detection, flat-panel array design employing an amorphous selenium converter with 70 microm pixels. The system was characterized for two different anode types, a molybdenum target with molybdenum filtration (Mo/Mo) and a tungsten target with rhodium filtration (W/Rh), at two different energies, 28 and 35 kVp, with approximately 2 mm added aluminum filtration. To measure the resolution, the presampled modulation transfer function (MTF) was measured using an edge method. The normalized noise power spectrum (NNPS) was measured by two-dimensional Fourier analysis of uniformly exposed mammograms. The detective quantum efficiencies (DQEs) were computed from the MTFs, the NNPSs, and theoretical ideal signal to noise ratios. The MTF was found to be close to its ideal limit and reached 0.2 at 11.8 mm(-1) and 0.1 at 14.1 mm(-1) for images acquired at an RQA-M2 technique (Mo/Mo anode, 28 kVp, 2 mm Al). Using a tungsten technique (MW2; W/Rh anode, 28 kVp, 2 mm Al), the MTF went to 0.2 at 11.2 mm(-1) and to 0.1 at 13.3 mm(-1). The DQE reached a maximum value of 54% at 1.35 mm(-1) for the RQA-M2 technique at 1.6 microC/kg and achieved a peak value of 64% at 1.75 mm(-1) for the tungsten technique (MW2) at 1.9 microC/kg. Nevertheless, the DQE showed strong exposure and frequency dependencies. The results indicated that the detector offered high MTFs and DQEs, but structured noise effects may require improved calibration before clinical implementation.

Our purpose in this study was to evaluate the fundamental image quality characteristics of a new slot-scan digital chest radiography system (ThoraScan, Delft Imaging Systems/Nucletron, Veenendaal, The Netherlands). The linearity of the system was measured over a wide exposure range at 90, 117, and 140 kVp with added Al filtration. System uniformity and reproducibility were established with an analysis of images from repeated exposures. The modulation transfer function (MTF) was evaluated using an established edge method. The noise power spectrum (NPS) and the detective quantum efficiency (DQE) of the system were evaluated at the three kilo-voltages over a range of exposures. Scatter fraction (SF) measurements were made using a posterior beam stop method and a geometrical chest phantom. The system demonstrated excellent linearity, but some structured nonuniformities. The 0.1 MTF values occurred between 3.3-3.5 mm(-1). The DQE(0.15) and DQE(2.5) were 0.21 and 0.07 at 90 kVp, 0.18 and 0.05 at 117 kVp, and 0.16 and 0.03 at 140 kVp, respectively. The system exhibited remarkably lower SFs compared to conventional full-field systems with anti-scatter grid, measuring 0.13 in the lungs and 0.43 in the mediastinum. The findings indicated that the slot-scan design provides marked scatter reduction leading to high effective DQE (DQEeff) of the system and reduced patient dose required to achieve high image quality.

One of the unanswered questions in digital radiography is the connection between physical image quality metrics and clinical detection performance. In this paper, we examine the impact of two physical metrics, resolution and noise, on the detectability of nodules in a pulmonary background for specific digital radiographic detectors. A detection experiment was performed on a simulated image set using anatomical backgrounds from a high-quality lung radiograph and three different simulated nodule sizes (2-3.5 mm). The resolution and noise of the resulting images were modified using existing routines to simulate a selenium-based and a cesium iodide-based flat-panel detector at comparable exposures. A location-known-exactly (LKE) observer performance experiment was performed in which four experienced chest radiologists and three physicists specializing in chest radiology scored the images. The data from the observer experiment were analyzed by receiver operating characteristic (ROC) methodology. The detectability, as measured by the parameter Az, was higher for the selenium detector than the cesium iodide detector for all nodule sizes by an average of 8.5%. For one nodule size (2.75 mm), the difference between detectors was statistically significant (p < 0.01). The findings indicate that for the particular task studied, the superior resolution performance of the selenium-based detector provided better detectability of subtle lung nodules even though the images had greater noise than images obtained with the cesium iodide detector.

A new computer simulation approach is presented that is capable of modeling several varieties of digital radiographic systems by their image quality characteristics. In this approach, the resolution and noise characteristics of ideal supersampled input images are modified according to input modulation transfer functions (MTFs) and noise power spectra (NPS). The modification process is separated into two routines-one for modification of the resolution and another for modification of the noise characteristics of the input image. The resolution modification routine blurs the input image by applying a frequency filter described by the input MTF. The resulting blurred image is then reduced to its final size to account for the sampling process of the digital system. The noise modification routine creates colored noise by filtering the frequency components of a white noise spectrum according to the input noise power. This noise is then applied to the image by a moving region of interest to account for variations in noise due to differences in attenuation. In order to evaluate the efficacy of the modification routines, additional routines were developed to assess the resolution and noise of digital images. The MTFs measured from the output images of the resolution modification routine were within 3% of the input MTF The NPS measured from the output images of the noise modification routine were within 2% of the input NPS. The findings indicate that the developed modification routines provide a good means of simulating the resolution and noise characteristics of digital radiographic systems for optimization or processing purposes.

Observations of seasonal variations of neutron flux from the high-energy neutron detector (HEND) on Mars Odyssey combined with direct measurements of the thickness of condensed carbon dioxide by the Mars Orbiter Laser Altimeter (MOLA) on Mars Global Surveyor show a latitudinal dependence of northern winter deposition of carbon dioxide. The observations are also consistent with a shallow substrate consisting of a layer with water ice overlain by a layer of drier soil. The lower ice-rich layer contains between 50 and 75 weight % water, indicating that the shallow subsurface at northern polar latitudes on Mars is even more water rich than that in the south.

After 55 days of mapping by the High Energy Neutron Detector onboard Mars Odyssey, we found deficits of high-energy neutrons in the southern highlands and northern lowlands of Mars. These deficits indicate that hydrogen is concentrated in the subsurface. Modeling suggests that water ice-rich layers that are tens of centimeters in thickness provide one possible fit to the data.