MRI scarcity in low- and middle-income countries.

Since the introduction of MRI as a sustainable diagnostic modality, global accessibility to its services has revealed a wide discrepancy between populations-leaving most of the population in LMICs without access to this important imaging modality. Several factors lead to the scarcity of MRI in LMICs; for example, inadequate infrastructure and the absence of a dedicated workforce are key factors in the scarcity observed. RAD-AID has contributed to the advancement of radiology globally by collaborating with our partners to make radiology more accessible for medically underserved communities. However, progress is slow and further investment is needed to ensure improved global access to MRI.

Artificial Intelligence in Low- and Middle-Income Countries: Innovating Global Health Radiology.

Scarce or absent radiology resources impede adoption of artificial intelligence (AI) for medical imaging by resource-poor health institutions. They face limitations in local equipment, personnel expertise, infrastructure, data-rights frameworks, and public policies. The trustworthiness of AI for medical decision making in global health and low-resource settings is hampered by insufficient data diversity, nontransparent AI algorithms, and resource-poor health institutions' limited participation in AI production and validation. RAD-AID's three-pronged integrated strategy for AI adoption in resource-poor health institutions is presented, which includes clinical radiology education, infrastructure implementation, and phased AI introduction. This strategy derives from RAD-AID's more-than-a-decade experience as a nonprofit organization developing radiology in resource-poor health institutions, both in the United States and in low- and middle-income countries. The three components synergistically provide the foundation to address health care disparities. Local radiology personnel expertise is augmented through comprehensive education. Software, hardware, and radiologic and networking infrastructure enables radiology workflows incorporating AI. These educational and infrastructure developments occur while RAD-AID delivers phased introduction, testing, and scaling of AI via global health collaborations.

Overcoming Challenges for Successful PACS Installation in Low-Resource Regions: Our Experience in Nigeria.

In this paper, we walk you through our challenges, successes, and experience while participating in a Global Health Outreach Project at the University College Hospital (UCH) Ibadan, Nigeria. The scope of the project was to install a Picture Archive and Communication System (PACS) to establish a centralized viewing network at UCH's Radiology Department, for each of their digital modalities. Installing a PACS requires robust servers, the ability to retrieve and archive studies, ensuring workstations can view studies, and the configuration of imaging modalities to send studies. We anticipated that we might experience hurdles for each of these requirements, due to limited resources and without the availability to make a site visit prior to the start of the project. While we ultimately experienced delays and troubleshooting was required at each turn of the install, with the help of dedicated volunteers both on and off-site and the UCH staff, our shared goal was accomplished.

Lower Respiratory Tract Infection of the Ferret by 2009 H1N1 Pandemic Influenza A Virus Triggers Biphasic, Systemic, and Local Recruitment of Neutrophils.

UNLABELLED: Infection of the lower respiratory tract by influenza A viruses results in increases in inflammation and immune cell infiltration in the lung. The dynamic relationships among the lung microenvironments, the lung, and systemic host responses during infection remain poorly understood. Here we used extensive systematic histological analysis coupled with live imaging to gain access to these relationships in ferrets infected with the 2009 H1N1 pandemic influenza A virus (H1N1pdm virus). Neutrophil levels rose in the lungs of H1N1pdm virus-infected ferrets 6 h postinfection and became concentrated at areas of the H1N1pdm virus-infected bronchiolar epithelium by 1 day postinfection (dpi). In addition, neutrophil levels were increased throughout the alveolar spaces during the first 3 dpi and returned to baseline by 6 dpi. Histochemical staining revealed that neutrophil infiltration in the lungs occurred in two waves, at 1 and 3 dpi, and gene expression within microenvironments suggested two types of neutrophils. Specifically, CCL3 levels, but not CXCL8/interleukin 8 (IL-8) levels, were higher within discrete lung microenvironments and coincided with increased infiltration of neutrophils into the lung. We used live imaging of ferrets to monitor host responses within the lung over time with [(18)F]fluorodeoxyglucose (FDG). Sites in the H1N1pdm virus-infected ferret lung with high FDG uptake had high levels of proliferative epithelium. In summary, neutrophils invaded the H1N1pdm virus-infected ferret lung globally and focally at sites of infection. Increased neutrophil levels in microenvironments did not correlate with increased FDG uptake; hence, FDG uptake may reflect prior infection and inflammation of lungs that have experienced damage, as evidenced by bronchial regeneration of tissues in the lungs at sites with high FDG levels. IMPORTANCE: Severe influenza disease is characterized by an acute infection of the lower airways that may progress rapidly to organ failure and death. Well-developed animal models that mimic human disease are essential to understanding the complex relationships of the microenvironment, organ, and system in controlling virus replication, inflammation, and disease progression. Employing the ferret model of H1N1pdm virus infection, we used live imaging and comprehensive histological analyses to address specific hypotheses regarding spatial and temporal relationships that occur during the progression of infection and inflammation. We show the general invasion of neutrophils at the organ level (lung) but also a distinct pattern of localized accumulation within the microenvironment at the site of infection. Moreover, we show that these responses were biphasic within the lung. Finally, live imaging revealed an early and sustained host metabolic response at sites of infection that may reflect damage and repair of tissues in the lungs.

Mycobacterium tuberculosis dysregulates MMP/TIMP balance to drive rapid cavitation and unrestrained bacterial proliferation.

Active tuberculosis (TB) often presents with advanced pulmonary disease, including irreversible lung damage and cavities. Cavitary pathology contributes to antibiotic failure, transmission, morbidity and mortality. Matrix metalloproteinases (MMPs), in particular MMP-1, are implicated in TB pathogenesis. We explored the mechanisms relating MMP/TIMP imbalance to cavity formation in a modified rabbit model of cavitary TB. Our model resulted in consistent progression of consolidation to human-like cavities (100% by day 28), with resultant bacillary burdens (>10(7) CFU/g) far greater than those found in matched granulomatous tissue (10(5) CFU/g). Using a novel, breath-hold computed tomography (CT) scanning and image analysis protocol, we showed that cavities developed rapidly from areas of densely consolidated tissue. Radiological change correlated with a decrease in functional lung tissue, as estimated by changes in lung density during controlled pulmonary expansion (R(2) = 0.6356, p < 0.0001). We demonstrated that the expression of interstitial collagenase (MMP-1) was specifically greater in cavitary compared to granulomatous lesions (p < 0.01), and that TIMP-3 significantly decreased at the cavity surface. Our findings demonstrated that an MMP-1/TIMP imbalance is associated with the progression of consolidated regions to cavities containing very high bacterial burdens. Our model provided mechanistic insight, correlating with human disease at the pathological, microbiological and molecular levels. It also provided a strategy to investigate therapeutics in the context of complex TB pathology. We used these findings to predict a MMP/TIMP balance in active TB and confirmed this in human plasma, revealing the potential of MMP/TIMP levels as key components of a diagnostic matrix aimed at distinguishing active from latent TB (PPV = 92.9%, 95% CI 66.1-99.8%, NPV = 85.6%; 95% CI 77.0-91.9%).

In vivo prediction of tuberculosis-associated cavity formation in rabbits.

The presence of cavitary lesions in patients with tuberculosis poses a significant clinical concern due to the risk of infectivity and the risk of antibiotic treatment failure. We describe 2 algorithms that use noninvasive positron emission tomography (PET) and computed tomography (CT) to predict the development of cavitary lesions in rabbits. Analysis of the PET region of interest predicted cavitary disease with 100% sensitivity and 76% specificity, and analysis of the CT region of interest predicted cavitary disease with 83.3% sensitivity and 76.9% specificity. Our results show that restricting our analysis to regions with high [(18)F]-fluorodeoxyglucose uptake provided the best combination of sensitivity and specificity.

Radiology preparedness in ebola virus disease: guidelines and challenges for disinfection of medical imaging equipment for the protection of staff and patients.

The overlap of early Ebola virus disease (EVD) symptoms (eg, fever, headache, abdominal pain, diarrhea, emesis, and fatigue) with symptoms of other more common travel-related diseases (eg, malaria, typhoid fever, pneumonia, and meningococcemia) may result in delayed diagnosis of EVD before isolation of infected patients. Radiology departments should consider policies for and approaches to decontamination of expensive and potentially easily damaged radiology equipment. In addition, the protection of radiology personnel must be considered during the work-up phase of undiagnosed EVD patients presenting to emergency departments. The purpose of this article is to consider the effect of EVD on radiology departments and imaging equipment, with particular consideration of guidelines currently available from the Centers for Disease Control and Prevention that may be applicable to radiology.

Segmentation and Image Analysis of Abnormal Lungs at CT: Current Approaches, Challenges, and Future Trends.

The computer-based process of identifying the boundaries of lung from surrounding thoracic tissue on computed tomographic (CT) images, which is called segmentation, is a vital first step in radiologic pulmonary image analysis. Many algorithms and software platforms provide image segmentation routines for quantification of lung abnormalities; however, nearly all of the current image segmentation approaches apply well only if the lungs exhibit minimal or no pathologic conditions. When moderate to high amounts of disease or abnormalities with a challenging shape or appearance exist in the lungs, computer-aided detection systems may be highly likely to fail to depict those abnormal regions because of inaccurate segmentation methods. In particular, abnormalities such as pleural effusions, consolidations, and masses often cause inaccurate lung segmentation, which greatly limits the use of image processing methods in clinical and research contexts. In this review, a critical summary of the current methods for lung segmentation on CT images is provided, with special emphasis on the accuracy and performance of the methods in cases with abnormalities and cases with exemplary pathologic findings. The currently available segmentation methods can be divided into five major classes: (a) thresholding-based, (b) region-based, (c) shape-based, (d) neighboring anatomy-guided, and (e) machine learning-based methods. The feasibility of each class and its shortcomings are explained and illustrated with the most common lung abnormalities observed on CT images. In an overview, practical applications and evolving technologies combining the presented approaches for the practicing radiologist are detailed.

Recombinant human factor VIIa for alveolar hemorrhage following allogeneic stem cell transplantation.

The mortality rate of alveolar hemorrhage (AH) after allogeneic hematopoietic stem cell transplantation is greater than 60% with supportive care and high-dose steroid therapy. We performed a retrospective cohort analysis to assess the benefits and risks of recombinant human factor VIIa (rFVIIa) as a therapeutic adjunct for AH. Between 2005 and 2012, 57 episodes of AH occurred in 37 patients. Fourteen episodes (in 14 patients) were treated with steroids alone, and 43 episodes (in 23 patients) were treated with steroids and rFVIIa. The median steroid dose was 1.9 mg/kg/d (interquartile range [IQR], 0.8 to 3.5 mg/kg/d; methylprednisolone equivalents) and did not differ statistically between the 2 groups. The median rFVIIa dose was 41 µg/kg (IQR, 39 to 62 µg/kg), and a median of 3 doses (IQR, 2 to 17) was administered per episode. Concurrent infection was diagnosed in 65% of the episodes. Patients had moderately severe hypoxia (median PaO2/FiO2, 193 [IQR, 141 to 262]); 72% required mechanical ventilation, and 42% survived to extubation. The addition of rFVIIa did not alter time to resolution of AH (P = .50), duration of mechanical ventilation (P = .89), duration of oxygen supplementation (P = .55), or hospital mortality (P = .27). Four possible thrombotic events (9% of 43 episodes) occurred with rFVIIa. rFVIIa in combination with corticosteroids did not confer clear clinical advantages compared with corticosteroids alone. In patients with AH following hematopoietic stem cell transplantation, clinical factors (ie, worsening infection, multiple organ failure, or recrudescence of primary disease) may be more important than the benefit of enhanced hemostasis from rFVIIa.

Building Radiology Equity: Themes from the 2023 RAD-AID Conference on International Radiology and Global Health.

Low- and middle-income countries are significantly impacted by the global scarcity of medical imaging services. Medical imaging is an essential component for diagnosis and guided treatment, which is needed to meet the current challenges of increasing chronic diseases and preparedness for acute-care response. We present some key themes essential for improving global health equity, which were discussed at the 2023 RAD-AID Conference on International Radiology and Global Health. They include (1) capacity building, (2) artificial intelligence, (3) community-based patient navigation, (4) organizational design for multidisciplinary global health strategy, (5) implementation science, and (6) innovation. Although not exhaustive, these themes should be considered influential as we guide and expand global health radiology programs in low- and middle-income countries in the coming years.

Deploying Artificial Intelligence for Thoracic Imaging Around the World.

PURPOSE: Artificial intelligence (AI) thoracic imaging applications are increasingly being deployed in low- and middle-income countries (LMICs). Radiologists have a critical gatekeeping role to ensure the effective and ethical implementation of AI solutions. RAD-AID International uses a three-pronged implementation strategy to overcome challenges pervasive in LMICs. METHODS: During a similar period, an AI software for chest radiography (CXR) interpretation was deployed at two tertiary hospitals located in Guyana and Nigeria. The three-pronged implementation strategy of clinical education, infrastructure implementation, and phased AI introduction was used. A PACS with a cloud component was installed at each institution. Radiology residents and attending physicians at these institutions completed an introduction-to-AI course to prime them for the use of AI solutions. A phased introduction of the AI software was performed to allow local validation as well as trust building and workflow integration. Local validation processes were used at each site by comparing AI outputs with standardized prospectively generated reports by local radiologists and study team members, allowing for slight differences in the goals of AI software use between sites. RESULTS: The PACS was successfully installed at both institutions. Thirty participants completed the introduction-to-AI course with an average pre-knowledge test score of 75% and an average posttest score of 95%. The focus of the validation process at various sites was reflective of the intended use of the AI software. In Guyana, it revealed an 87% concordance rate between radiologists and the AI model for triaging normal versus abnormal findings on CXR. In Nigeria, an 85% concordance rate between radiologists and the AI model for reporting tuberculosis on CXR was noted. The AI software was successfully deployed and is being used as intended at both institutions. CONCLUSIONS: There are unique barriers to the adoption of AI in LMICs requiring an implementation strategy in collaboration with local institutions and industry partners to ensure success.

Enhancing image analytic tools by fusing quantitative physiological values with image features.

Computer-aided diagnosis systems (CADs) can quantify the severity of diseases by analyzing a set of images and employing prior statistical models. In general, CADs have proven to be effective at providing quantitative measurements of the extent of a particular disease, thus helping physicians to better monitor the progression of cancer, infectious diseases, and other health conditions. Electronic Health Records frequently include a large amount of clinical data and medical history that can provide critical information about the underlying condition of a patient. We hypothesize that the fusion of image and clinical-physiological features can be used to enhance the accuracy of automatic image classification models. In particular, this paper shows how image analytic tools can move beyond classical image interpretation models to broader systems where image and physiological measurements are fused and used to create more generic detection models. To test our hypothesis, a CAD system capable of quantifying the severity of patients with pulmonary fibrosis has been developed. Results show that CAD systems augmented with multimodal physiological values are more robust and accurate at determining the severity of the disease.

Molecular imaging of influenza and other emerging respiratory viral infections.

Research on the pathogenesis and therapy of influenza and other emerging respiratory viral infections would be aided by methods that directly visualize pathophysiologic processes in patients and laboratory animals. At present, imaging of diseases, such as swine-origin H1N1 influenza, is largely restricted to chest radiograph and computed tomography (CT), which can detect pulmonary structural changes in severely ill patients but are more limited in characterizing the early stages of illness, differentiating inflammation from infection or tracking immune responses. In contrast, imaging modalities, such as positron emission tomography, single photon emission CT, magnetic resonance imaging, and bioluminescence imaging, which have become useful tools for investigating the pathogenesis of a range of disease processes, could be used to advance in vivo studies of respiratory viral infections in patients and animals. Molecular techniques might also be used to identify novel biomarkers of disease progression and to evaluate new therapies.

Evaluation of monkeypox disease progression by molecular imaging.

Infection of nonhuman primates (NHPs) with monkeypox virus (MPXV) is currently being developed as an animal model of variola infection in humans. We used positron emission tomography and computed tomography (PET/CT) to identify inflammatory patterns as predictors for the outcome of MPXV disease in NHPs. Two NHPs were sublethally inoculated by the intravenous (IV) or intrabronchial (IB) routes and imaged sequentially using fluorine-18 fluorodeoxyglucose ((18)FDG) uptake as a nonspecific marker of inflammation/immune activation. Inflammation was observed in the lungs of IB-infected NHPs, and bilobular involvement was associated with morbidity. Lymphadenopathy and immune activation in the axillary lymph nodes were evident in IV- and IB-infected NHPs. Interestingly, the surviving NHPs had significant (18)FDG uptake in the axillary lymph nodes at the time of MPXV challenge with no clinical signs of illness, suggesting an association between preexisting immune activation and survival. Molecular imaging identified patterns of inflammation/immune activation that may allow risk assessment of monkeypox disease.

Estimating Catchment Populations of Global Health Radiology Outreach Using Geographic Information Systems Analysis.

PURPOSE: The purpose of this study was to design, develop, and test geographic information systems (GIS) analytic methods for quantifying and characterizing catchment populations across all sites served by a radiology global health organization. METHODS: The analysis included populations served by 78 low-resource medical facilities in 32 countries partnered with radiology nonprofit organization, RAD-AID International. Three constraints were used to approximate patient catchment areas: (1) 1-hour driving time, (2) 1-hour walking time, and (3) 10-mile circular radius. GIS calculated populations within each constraint using publicly available geospatial input databases, including a global digital elevation model, population and land cover data, and road locations from OpenStreetMap. Demographic and health data from the World Health Organization were incorporated to provide further characteristics of covered populations. RESULTS: The total populations served by all RAD-AID sites as measured by driving time, walking time, and 10-mile radius were 189,241,193 (47.8% female), 26,190,117 (48.7% female), and 110,884,095 (48.1% female), respectively. For individual locations, median population within 1-hour driving time was 1,795,977 (range: 8,742-30,630,800), with an average life expectancy of 68.4 ± 5.8 years. Median child mortality before age 5 was 3.8% (range: 0.9%-8.3%), and median prevalence of human immunodeficiency virus infection was 3.1% (range: 0.7%-10.9%). CONCLUSION: In this study, GIS provided a robust multisite analysis for estimating the potential global population reached by an international radiology outreach organization with targeted individual site measurements. Given heightened needs to accurately characterize global outreach populations, this GIS-based approach may be useful for analysis, outreach planning, and resource allocation among global health organizations.

Strategic Radiology Outreach Planning for Underserved Populations Using Geographic Information Systems.

PURPOSE: Geographic information systems (GIS) are widely used in public health research but rarely used in radiology research. GIS can be an impactful tool in radiology global health to locate medically underserved populations and poor transportation infrastructure, characterize medical needs, and design outreach programs. Using the example of aircraft-based outreach in Alaska, we demonstrate the utility of GIS in radiological program planning for global health. METHODS: Multicriteria GIS evaluations were performed to create a health severity index, using life expectancy and percentage uninsured data, and an accessibility severity index, using distance from roads and health centers or hospitals. These indices were combined with population density to create a final health access severity index (HASI). A map presenting suitable hybrid airship operating areas was produced using land cover data. Alaskan health care facilities were georeferenced to create a coordinate data set. Infrastructure was obtained from OpenStreetMap. Health data were accessed from the 2017 American Community Survey and CDC US Small-area Life Expectancy Estimates Project. RESULTS: GIS analyzed 738,050 Alaskans. The health severity index identified decreased health outcomes (high or very high severity) in 285,446 (39%) Alaskans, and the accessibility severity index determined decreased access to care in 218,201 (30%). Combined, the HASI established 165,108 (22%) Alaskans as underserved with high or very high overall severity. Thirty-nine percent of Alaska land area is suitable for hybrid airship operations, including 27% of HASI high and very high severity areas. CONCLUSIONS: GIS identified underserved populations for mobile radiology outreach in Alaska and may be useful for global health outreach planning and resource allocation.

Imaging findings in a fatal case of pandemic swine-origin influenza A (H1N1).

OBJECTIVE: Although most cases of swine-origin influenza A (H1N1) virus (S-OIV) have been self-limited, fatal cases raise questions about virulence and radiology's role in early detection. We describe the radiographic and CT findings in a fatal S-OIV infection. CONCLUSION: Radiography showed peripheral lung opacities. CT revealed peripheral ground-glass opacities suggesting peribronchial injury. These imaging findings raised suspicion of S-OIV despite negative H1N1 influenza rapid antigen test results from two nasopharyngeal swabs; subsequently, those results were proven to be false-negatives by reverse transcriptase polymerase chain reaction. This case suggests a role for CT in the early recognition of severe S-OIV.

Ultrasound for Breast Cancer Detection Globally: A Systematic Review and Meta-Analysis.

PURPOSE: Mammography is not always available or feasible. The purpose of this systematic review and meta-analysis is to assess the diagnostic performance of ultrasound as a primary tool for early detection of breast cancer. MATERIALS AND METHODS: For this systematic review and meta-analysis, we comprehensively searched PubMed and SCOPUS to identify articles from January 2000 to December 2018 that included data on the performance of ultrasound for detection of breast cancer. Studies evaluating portable, handheld ultrasound as an independent detection modality for breast cancer were included. Quality assessment and bias analysis were performed with the Quality Assessment of Diagnostic Accuracy Studies-2 tool. Sensitivity analyses and meta-regression were used to explore heterogeneity. The study protocol has been registered with the international prospective register of systematic reviews (PROSPERO identifier: CRD42019127752). RESULTS: Of the 526 identified studies, 26 were eligible for inclusion. Ultrasound had an overall pooled sensitivity and specificity of 80.1% (95% CI, 72.2% to 86.3%) and 88.4% (95% CI, 79.8% to 93.6%), respectively. When only low- and middle-income country data were considered, ultrasound maintained a diagnostic sensitivity of 89.2% and specificity of 99.1%. Meta-analysis of the included studies revealed heterogeneity. The high sensitivity of ultrasound for the detection of breast cancer was not statistically significantly different in subgroup analyses on the basis of mean age, risk, symptoms, study design, bias level, and study setting. CONCLUSION: Given the increasing burden of breast cancer and infeasibility of mammography in certain settings, we believe these results support the potential use of ultrasound as an effective primary detection tool for breast cancer, which may be beneficial in low-resource settings where mammography is unavailable.

Lymphocyte-driven regional immunopathology in pneumonitis caused by impaired central immune tolerance.

Autoimmune polyendocrinopathy-candidiasis-ectodermal dystrophy (APECED), a monogenic disorder caused by AIRE mutations, presents with several autoimmune diseases. Among these, endocrine organ failure is widely recognized, but the prevalence, immunopathogenesis, and treatment of non-endocrine manifestations such as pneumonitis remain poorly characterized. We enrolled 50 patients with APECED in a prospective observational study and comprehensively examined their clinical and radiographic findings, performed pulmonary function tests, and analyzed immunological characteristics in blood, bronchoalveolar lavage fluid, and endobronchial and lung biopsies. Pneumonitis was found in >40% of our patients, presented early in life, was misdiagnosed despite chronic respiratory symptoms and accompanying radiographic and pulmonary function abnormalities, and caused hypoxemic respiratory failure and death. Autoantibodies against BPIFB1 and KCNRG and the homozygous c.967_979del13 AIRE mutation are associated with pneumonitis development. APECED pneumonitis features compartmentalized immunopathology, with accumulation of activated neutrophils in the airways and lymphocytic infiltration in intraepithelial, submucosal, peribronchiolar, and interstitial areas. Beyond APECED, we extend these observations to lung disease seen in other conditions with secondary AIRE deficiency (thymoma and RAG deficiency). Aire-deficient mice had similar compartmentalized cellular immune responses in the airways and lung tissue, which was ameliorated by deficiency of T and B lymphocytes. Accordingly, T and B lymphocyte-directed immunomodulation controlled symptoms and radiographic abnormalities and improved pulmonary function in patients with APECED pneumonitis. Collectively, our findings unveil lung autoimmunity as a common, early, and unrecognized manifestation of APECED and provide insights into the immunopathogenesis and treatment of pulmonary autoimmunity associated with impaired central immune tolerance.