MSK-TIM: A Telerobotic Ultrasound System for Assessing the Musculoskeletal System

The aim of this paper is to investigate technological advancements made to a robotic tele-ultrasound system for musculoskeletal imaging, the MSK-TIM (Musculoskeletal Telerobotic Imaging Machine). The hardware was enhanced with a force feedback sensor and a new controller was introduced. Software improvements were developed which allowed the operator to access ultrasound functions such as focus, depth, gain, zoom, color, and power Doppler controls. The device was equipped with Wi-Fi network capability which allowed the master and slave stations to be positioned in different locations. A trial assessing the system to scan the wrist was conducted with twelve participants, for a total of twenty-four arms. Both the participants and radiologist reported their experience. The images obtained were determined to be of satisfactory quality for diagnosis. The system improvements resulted in a better user and patient experience for the radiologist and participants. Latency with the VPN configuration was similar to the WLAN in our experiments. This research explores several technologies in medical telerobotics and provides insight into how they should be used in future. This study provides evidence to support larger-scale trials of the MSK-TIM for musculoskeletal imaging.

RadioGraphics Update: The 10 Pillars of Lung Cancer Screening-Rationale and Logistics of a Lung Cancer Screening Program

Editor's Note.-RadioGraphics Update articles supplement or update information found in full-length articles previously published in RadioGraphics. These updates, written by at least one author of the previous article, provide a brief synopsis that emphasizes important new information such as technological advances, revised imaging protocols, new clinical guidelines involving imaging, or updated classification schemes.

Deep learning-based age estimation from chest CT scans

PURPOSE

Medical imaging can be used to estimate a patient's biological age, which may provide complementary information to clinicians compared to chronological age. In this study, we aimed to develop a method to estimate a patient's age based on their chest CT scan. Additionally, we investigated whether chest CT estimated age is a more accurate predictor of lung cancer risk compared to chronological age.

METHODS

To develop our age prediction model, we utilized composite CT images and Inception-ResNet-v2. The model was trained, validated, and tested on 13,824 chest CT scans from the National Lung Screening Trial, with 91% for training, 5% for validation, and 4% for testing. Additionally, we independently tested the model on 1849 CT scans collected locally. To assess chest CT estimated age as a risk factor for lung cancer, we computed the relative lung cancer risk between two groups. Group 1 consisted of individuals assigned a CT age older than their chronological age, while Group 2 comprised those assigned a CT age younger than their chronological age.

RESULTS

Our analysis revealed a mean absolute error of 1.84 years and a Pearson's correlation coefficient of 0.97 for our local data when comparing chronological age with the estimated CT age. The model showed the most activation in the area associated with the lungs during age estimation. The relative risk for lung cancer was 1.82 (95% confidence interval, 1.65-2.02) for individuals assigned a CT age older than their chronological age compared to those assigned a CT age younger than their chronological age.

CONCLUSION

Findings suggest that chest CT age captures some aspects of biological aging and may be a more accurate predictor of lung cancer risk than chronological age. Future studies with larger and more diverse patients are required for the generalization of the interpretations.

Artificial Intelligence and Machine Learning in Lung Cancer Screening

Recent advances in artificial intelligence and machine learning (AI/ML) hold substantial promise to address some of the current challenges in lung cancer screening and improve health equity. This article reviews the status and future directions of AI/ML tools in the lung cancer screening workflow, focusing on determining screening eligibility, radiation dose reduction and image denoising for low-dose chest computed tomography (CT), lung nodule detection, lung nodule classification, and determining optimal screening intervals. AI/ML tools can assess for chronic diseases on CT, which creates opportunities to improve population health through opportunistic screening.

Applications of deep learning to reduce the need for iodinated contrast media for CT imaging: a systematic review

PURPOSE

The usage of iodinated contrast media (ICM) can improve the sensitivity and specificity of computed tomography (CT) for many clinical indications. However, the adverse effects of ICM administration can include renal injury, life-threatening allergic-like reactions, and environmental contamination. Deep learning (DL) models can generate full-dose ICM CT images from non-contrast or low-dose ICM administration or generate non-contrast CT from full-dose ICM CT. Eliminating the need for both contrast-enhanced and non-enhanced imaging or reducing the amount of required contrast while maintaining diagnostic capability may reduce overall patient risk, improve efficiency and minimize costs. We reviewed the current capabilities of DL to reduce the need for contrast administration in CT.

METHODS

We conducted a systematic review of articles utilizing DL to reduce the amount of ICM required in CT, searching MEDLINE, Embase, Compendex, Inspec, and Scopus to identify papers published from 2016 to 2022. We classified the articles based on the DL model and ICM reduction.

RESULTS

Eighteen papers met the inclusion criteria for analysis. Of these, ten generated synthetic full-dose (100%) ICM from real non-contrast CT, while four augmented low-dose to full-dose ICM CT. Three used DL to create synthetic non-contrast CT from real 100% ICM CT, while one paper used DL to translate the 100% ICM to non-contrast CT and vice versa. DL models commonly used generative adversarial networks trained and tested by paired contrast-enhanced and non-contrast or low ICM CTs. Image quality metrics such as peak signal-to-noise ratio and structural similarity index were frequently used for comparing synthetic versus real CT image quality.

CONCLUSION

DL-generated contrast-enhanced or non-contrast CT may assist in diagnosis and radiation therapy planning; however, further work to optimize protocols to reduce or eliminate ICM for specific pathology is still needed along with a dedicated assessment of the clinical utility of these synthetic images.

Neonatal Catheter and Tube Placement and Radiographic Assessment Statistics in Relation to Important Anatomic Landmarks

OBJECTIVE

 Neonatal catheters and tubes are commonly used for monitoring and support for intensive care and must be correctly positioned to avoid complications. Position assessment is routinely done by radiography. The objective of this study is to characterize neonatal catheter and tube placement in terms of the proportion of those devices that are malpositioned.

STUDY DESIGN

 Using an institutional dataset of 723 chest/abdominal radiographs of neonatal intensive care unit (ICU) patients (all within 60 days of birth), we assessed the proportion of catheters that are malpositioned. Many radiographs contained multiple catheter types. Umbilical venous catheters (UVCs; 448 radiographs), umbilical arterial catheters (UACs; 259 radiographs), endotracheal tubes (ETTs; 451 radiographs), and nasogastric tubes (NGTs; 603 radiographs) were included in our analysis.

RESULTS

 UVCs were malpositioned in 90% of radiographs, while UACs were malpositioned in 36%, ETTs in 30%, and NGTs in just 5%. The most common locations in which UVCs were malpositioned were in the right atrium (31%) and umbilical vein (21%), and for UACs the most common malpositioned tip location was the aortic arch (8%). For the remaining tubes, 5% of ETTs were found to be in the right main bronchus and 4% of NGTs were found in the esophagus.

CONCLUSION

 A substantial proportion of catheters and tubes are malpositioned, suggesting that optimizing methods of catheter placement and assessment ought to be areas of focus for future work.

KEY POINTS

· Neonatal catheters are frequently malpositioned.. · Most umbilical venous catheters need readjustment.. · X-ray and ultrasound are important for assessment.. · Catheter tips should be assessed in all X-rays..

Lung cancer screening

Randomised controlled trials, including the National Lung Screening Trial (NLST) and the NELSON trial, have shown reduced mortality with lung cancer screening with low-dose CT compared with chest radiography or no screening. Although research has provided clarity on key issues of lung cancer screening, uncertainty remains about aspects that might be critical to optimise clinical effectiveness and cost-effectiveness. This Review brings together current evidence on lung cancer screening, including an overview of clinical trials, considerations regarding the identification of individuals who benefit from lung cancer screening, management of screen-detected findings, smoking cessation interventions, cost-effectiveness, the role of artificial intelligence and biomarkers, and current challenges, solutions, and opportunities surrounding the implementation of lung cancer screening programmes from an international perspective. Further research into risk models for patient selection, personalised screening intervals, novel biomarkers, integrated cardiovascular disease and chronic obstructive pulmonary disease assessments, smoking cessation interventions, and artificial intelligence for lung nodule detection and risk stratification are key opportunities to increase the efficiency of lung cancer screening and ensure equity of access.

Clinical Impact and Generalizability of a Computer-Assisted Diagnostic Tool to Risk-Stratify Lung Nodules With CT

OBJECTIVE

To evaluate whether an imaging classifier for radiology practice can improve lung nodule classification and follow-up.

METHODS

A machine learning classifier was developed and trained using imaging data from the National Lung Screening Trial (NSLT) to produce a malignancy risk score (malignancy Similarity Index [mSI]) for individual lung nodules. In addition to NLST cohorts, external cohorts were developed from a tertiary referral lung cancer screening program data set and an external nonscreening data set of all nodules detected on CT. Performance of the mSI combined with Lung-RADS was compared with Lung-RADS alone and the Mayo and Brock risk calculators.

RESULTS

We analyzed 963 subjects and 1,331 nodules across these cohorts. The mSI was comparable in accuracy (area under the curve = 0.89) to existing clinical risk models (area under the curve = 0.86-0.88) and independently predictive in the NLST cohort of 704 nodules. When compared with Lung-RADS, the mSI significantly increased sensitivity across all cohorts (25%-117%), with significant increases in specificity in the screening cohorts (17%-33%). When used in conjunction with Lung-RADS, use of mSI would result in earlier diagnoses and reduced follow-up across cohorts, including the potential for early diagnosis in 42% of malignant NLST nodules from prior-year CT scans.

CONCLUSION

A computer-assisted diagnosis software improved risk classification from chest CTs of screening and incidentally detected lung nodules compared with Lung-RADS. mSI added predictive value independent of existing radiological and clinical variables. These results suggest the generalizability and potential clinical impact of a tool that is straightforward to implement in practice.

A pictorial review of the radiographic skeletal findings in Morquio syndrome (mucopolysaccharidosis type IV)

Morquio syndrome, also known as Morquio-Brailsford syndrome or mucopolysaccharidosis type IV (MPS IV), is a subgroup of mucopolysaccharidosis. It is an autosomal recessive lysosomal storage disorder. Two subtypes of Morquio syndrome have been identified. In MPS IVA, a deficiency in N-acetylgalactosamine-6-sulfate sulfatase interrupts the normal metabolic pathway of degrading glycosaminoglycans. Accumulated undigested glycosaminoglycans in the tissue and bones result in complications leading to severe skeletal deformity. In MPS IVB, a deficiency in beta-galactosidase results in a milder phenotype than in MPS IVA. Morquio syndrome presents a variety of clinical manifestations in a spectrum of mild to severe. It classically has been considered a skeletal dysplasia with significant skeletal involvement. However, the extraskeletal features can also provide valuable information to guide further work-up to assess the possibility of the disorder. Although the disease involves almost all parts of the body, it most commonly affects the axial skeleton, specifically the vertebrae. The characteristic radiologic findings in MPS IV, such as paddle-shaped ribs, odontoid hypoplasia, vertebral deformity, metaphyseal and epiphyseal bone dysplasia, and steep acetabula, are encompassed in the term "dysostosis multiplex," which is a common feature among other types of MPS and storage disorders. Myelopathy due to spinal cord compression and respiratory airway obstruction are the most critical complications related to mortality and morbidity. The variety of clinical features, as well as overlapping of radiological findings with other disorders, make diagnosis challenging, and delays in diagnosis and treatment may lead to critical complications. Timely imaging and radiologic expertise are important components for diagnosis. Gene therapies may provide robust treatment, particularly if genetic variations can be screened in utero.

Economic Evaluation of Telerobotic Ultrasound Technology to Remotely Provide Ultrasound Services in Rural and Remote Communities

INTRODUCTION

Telerobotic ultrasound technology allows radiologists and sonographers to remotely provide ultrasound services in underserved areas. This study aimed to compare costs associated with using telerobotic ultrasound to provide ultrasound services in rural and remote communities to costs associated with alternate models.

METHODS

A cost-minimization approach was used to compare four ultrasound service delivery models: telerobotic ultrasound (Model 1), telerobotic ultrasound and an itinerant sonographer (Model 2), itinerant sonographer without telerobotic ultrasound (Model 3), and travel to another community for all exams (Model 4). In Models 1-3, travel was assumed when exams could not be successfully performed telerobotically or by an itinerant sonographer. A publicly funded healthcare payer perspective was used for the reference case and a societal perspective was used for a secondary non-reference case. Costs were based on the literature and experience using telerobotic ultrasound in Saskatchewan, Canada. Costs were expressed in 2020 Canadian dollars.

RESULTS

Average cost per ultrasound exam was $342, $323, $368, and $478 for Models 1, 2, 3, and 4, respectively, from a publicly funded healthcare payer perspective, and $461, $355, $447, and $849, respectively, from a societal perspective. In one-way sensitivity analyses, Model 2 was the lowest cost from a payer perspective for communities with population >2075 people, distance >350 km from the nearest ultrasound facility, or >47% of the population eligible for publicly funded medical transportation.

CONCLUSION

Health systems may wish to consider solutions such as telerobotic ultrasound and itinerant sonographers to reduce healthcare costs and improve access to ultrasound in rural and remote communities.

Social jobs and the returns to drinking

We uniquely show that the returns to drinking in social jobs exceed those in non-social jobs. The higher returns remain when controlling for worker personality, when including individual fixed effects and in a series of robustness exercises. This showing fits the hypothesis that drinking assists the formation of social capital, capital that has greater value in social jobs. We are also the first to show that drinking may proxy both general and specific social capital formation. Drinking during a previous employer and during a current employer have returns and each have higher returns in a current social job.

Implementation and evaluation of a pilot antenatal ultrasound imaging programme using tele-ultrasound in Ethiopia

INTRODUCTION

Ultrasound imaging is an important aspect of antenatal care, though access to antenatal ultrasound imaging is limited in many developing countries. The objective of this study was to evaluate a pilot programme which aimed to improve access to antenatal ultrasound for rural Ethiopians through enhanced training of healthcare providers (including midwives, nurses and clinical officers) with support remotely provided by obstetricians using a tele-ultrasound platform.

METHODS

Thirteen healthcare providers in the North Shoa Zone in Ethiopia completed training to enable them to perform antenatal ultrasound with the remote supervision of an obstetrician via a tele-ultrasound platform. Pregnant women attending an antenatal appointment at two facilities were offered an antenatal ultrasound exam performed by one of the healthcare providers. Image interpretations between obstetricians and healthcare providers were compared. Participants and healthcare providers were invited to complete a questionnaire regarding their experience with tele-ultrasound, and participants, healthcare providers and obstetricians were interviewed regarding their experience with the tele-ultrasound pilot programme.

RESULTS

2795 pregnant women had an antenatal ultrasound exam. Of 100 exams randomly selected to assess concordance between healthcare providers' and obstetricians' image interpretations, concordance ranged from 79% to 100% for each parameter assessed. 99.4% of participants surveyed indicated that they would recommend antenatal ultrasound using tele-ultrasound to friends and family. Themes relating to participants' experiences of having a tele-ultrasound exam were reduced travel and cost, equivalence in quality of virtual care to in-person care and empowerment through diagnostic information.

CONCLUSION

Healthcare provider-performed antenatal ultrasound - supported by obstetricians via tele-ultrasound - showed high levels of concordance, was well-received by participants and provided rural Ethiopian women with enhanced access to antenatal imaging.

Fungal Planet description sheets: 1383-1435

Novel species of fungi described in this study include those from various countries as follows: Australia, Agaricus albofoetidus, Agaricus aureoelephanti and Agaricus parviumbrus on soil, Fusarium ramsdenii from stem cankers of Araucaria cunninghamii, Keissleriella sporoboli from stem of Sporobolus natalensis, Leptosphaerulina queenslandica and Pestalotiopsis chiaroscuro from leaves of Sporobolus natalensis, Serendipita petricolae as endophyte from roots of Eriochilus petricola, Stagonospora tauntonensis from stem of Sporobolus natalensis, Teratosphaeria carnegiei from leaves of Eucalyptus grandis × E. camaldulensis and Wongia ficherai from roots of Eragrostis curvula. Canada, Lulworthia fundyensis from intertidal wood and Newbrunswickomyces abietophilus (incl. Newbrunswickomyces gen. nov.) on buds of Abies balsamea. Czech Republic, Geosmithia funiculosa from a bark beetle gallery on Ulmus minor and Neoherpotrichiella juglandicola (incl. Neoherpotrichiella gen. nov.) from wood of Juglans regia. France, Aspergillus rouenensis and Neoacrodontium gallica (incl. Neoacrodontium gen. nov.) from bore dust of Xestobium rufovillosum feeding on Quercus wood, Endoradiciella communis (incl. Endoradiciella gen. nov.) endophytic in roots of Microthlaspi perfoliatum and Entoloma simulans on soil. India, Amanita konajensis on soil and Keithomyces indicus from soil. Israel, Microascus rothbergiorum from Stylophora pistillata. Italy, Calonarius ligusticus on soil. Netherlands, Appendopyricularia juncicola (incl. Appendopyricularia gen. nov.), Eriospora juncicola and Tetraploa juncicola on dead culms of Juncus effusus, Gonatophragmium physciae on Physcia caesia and Paracosmospora physciae (incl. Paracosmospora gen. nov.) on Physcia tenella, Myrmecridium phragmitigenum on dead culm of Phragmites australis, Neochalara lolae on stems of Pteridium aquilinum, Niesslia nieuwwulvenica on dead culm of undetermined Poaceae, Nothodevriesia narthecii (incl. Nothodevriesia gen. nov.) on dead leaves of Narthecium ossifragum and Parastenospora pini (incl. Parastenospora gen. nov.) on dead twigs of Pinus sylvestris. Norway, Verticillium bjoernoeyanum from sand grains attached to a piece of driftwood on a sandy beach. Portugal, Collybiopsis cimrmanii on the base of living Quercus ilex and amongst dead leaves of Laurus and herbs. South Africa, Paraproliferophorum hyphaenes (incl. Paraproliferophorum gen. nov.) on living leaves of Hyphaene sp. and Saccothecium widdringtoniae on twigs of Widdringtonia wallichii. Spain, Cortinarius dryosalor on soil, Cyphellophora endoradicis endophytic in roots of Microthlaspi perfoliatum, Geoglossum lauri-silvae on soil, Leptographium gemmatum from fluvial sediments, Physalacria auricularioides from a dead twig of Castanea sativa, Terfezia bertae and Tuber davidlopezii in soil. Sweden, Alpova larskersii, Inocybe alpestris and Inocybe boreogodeyi on soil. Thailand, Russula banwatchanensis, Russula purpureoviridis and Russula lilacina on soil. Ukraine, Nectriella adonidis on overwintered stems of Adonis vernalis. USA, Microcyclus jacquiniae from living leaves of Jacquinia keyensis and Penicillium neoherquei from a minute mushroom sporocarp. Morphological and culture characteristics are supported by DNA barcodes. Citation: Crous PW, Boers J, Holdom D, et al. 2022. Fungal Planet description sheets: 1383-1435. Persoonia 48: 261-371. https://doi.org/10.3767/persoonia.2022.48.08.

The future of artificial intelligence in medicine: Medical-legal considerations for health leaders

Artificial Intelligence (AI) is becoming increasingly common in healthcare and has potential to improve the efficiency and quality of healthcare services. As the utility of AI expands, medical-legal questions arise regarding the possible legal implications of incorporating AI into clinical practice. Particularly, the unique black box nature of AI brings distinct challenges. There is limited guidance addressing liability when AI is used in clinical practice, and traditional legal principles present limitations when applied to novel uses of AI. Comprehensive solutions to address the challenges of AI have not been well established in North America. As AI continues to evolve in healthcare, appropriate guidance from professional regulatory bodies may help the medical field realize AI’s utility and encourage its safe use. As the options for AI in medicine evolve, physicians and health leaders would be prudent to consider the evolving medical-legal context regarding use of AI in clinical practices and facilities.

A Telerobotic Ultrasound Clinic Model of Ultrasound Service Delivery to Improve Access to Imaging in Rural and Remote Communities

OBJECTIVE

Patients living in many rural and remote areas do not have readily available access to ultrasound services because of a lack of sonographers and radiologists in these communities. The objective of this study was to determine the feasibility of using telerobotic ultrasound to establish a service delivery model to remotely provide access to diagnostic ultrasound in rural and remote communities.

METHODS

Telerobotic ultrasound clinics were developed in three remote communities more than 500 km away from our academic medical center. Sonographers remotely performed all ultrasound examinations using telerobotic ultrasound systems, and examinations were subsequently interpreted by radiologists at an academic medical center. Diagnostic performance was assessed by each interpreting radiologist using a standardized reporting form. Patient experience was assessed through quantitative and qualitative analysis of survey responses. Operational challenges and solutions were identified.

RESULTS

Eighty-seven telerobotic ultrasound examinations were remotely performed and included in this study, with the most frequent examination types being abdominal (n = 35), first-trimester obstetrical (n = 26), and second-trimester complete obstetrical (n = 12). Across all examination types, 70% of telerobotic ultrasound examinations were sufficient for diagnosis, minimizing travel or reducing wait times for these patients. Ninety-five percent of patients would be willing to have another telerobotic ultrasound examination in the future. Operational challenges were related to technical infrastructure, human resources, and coordination between clinic sites.

CONCLUSION

Telerobotic ultrasound can provide access to diagnostic ultrasound services to underserved rural and remote communities without regular ultrasound services, thereby reducing disparities in access to care and improving health equity.

Pediatric chest radiograph interpretation: how far has artificial intelligence come? A systematic literature review

Most artificial intelligence (AI) studies have focused primarily on adult imaging, with less attention to the unique aspects of pediatric imaging. The objectives of this study were to (1) identify all publicly available pediatric datasets and determine their potential utility and limitations for pediatric AI studies and (2) systematically review the literature to assess the current state of AI in pediatric chest radiograph interpretation. We searched PubMed, Web of Science and Embase to retrieve all studies from 1990 to 2021 that assessed AI for pediatric chest radiograph interpretation and abstracted the datasets used to train and test AI algorithms, approaches and performance metrics. Of 29 publicly available chest radiograph datasets, 2 datasets included solely pediatric chest radiographs, and 7 datasets included pediatric and adult patients. We identified 55 articles that implemented an AI model to interpret pediatric chest radiographs or pediatric and adult chest radiographs. Classification of chest radiographs as pneumonia was the most common application of AI, evaluated in 65% of the studies. Although many studies report high diagnostic accuracy, most algorithms were not validated on external datasets. Most AI studies for pediatric chest radiograph interpretation have focused on a limited number of diseases, and progress is hindered by a lack of large-scale pediatric chest radiograph datasets.

A toolkit for haptic force feedback in a telerobotic ultrasound system

OBJECTIVE

To develop a collision engine (haptic force feedback simulator) compatible with a 5-degrees-of-freedom (DOF) haptic wand. This has broad applications such as telerobotic ultrasound systems. Integrating force feedback into systems is critical to optimize remote scanning. A collision engine compatible with a 5-DOF haptic wand was developed based on the Gilbert-Johnson-Keerthi algorithm. The collision engine calculated force during collision between the wand and a virtual object based on code developed using MATLAB. A proportional force was subsequently returned to a user via the haptic wand, thereby simulating the collision force for the user. Three experiments were conducted to assess the accuracy of the collision engine on curved and flat surfaces.

RESULTS

The average errors in calculation of distances between the wand and virtual object were 2.1 cm, 3.4 cm, and 4.2 cm for the model of the human hand, cylinder, and cuboid, respectively. The collision engine accurately simulated forces on a flat surface, though was less accurate on curved surfaces. Future work will incorporate haptic force feedback into a telerobotic ultrasound system. The haptic force simulator presented here may also be used in the development of ultrasound simulators for training and education.

Sociodemographic and Geographic Factors Associated With Non-Obstetrical Ultrasound Imaging Utilization: A Population-Based Study

OBJECTIVE

Ultrasound is one of the most commonly used imaging modalities, though some populations face barriers in accessing ultrasound services, potentially resulting in disparities in utilization. The objective of this study was to assess the association between sociodemographic and geographic factors and non-obstetrical ultrasound utilization in the province of Saskatchewan, Canada.

METHODS

All non-obstetrical ultrasound exams performed from 2014 to 2018 in Saskatchewan, Canada were retrospectively identified from province-wide databases. Univariate and multivariate Poisson regression analyses were performed to assess the association between ultrasound utilization and sex, age, First Nations status, Charlson Comorbidity Index, urban vs. rural residence, geographic remoteness, and neighborhood income.

RESULTS

A total of 1,324,846 individuals (5,857,044 person-years) were included in the analysis. Female sex (adjusted incidence rate ratio [aIRR], 2.20; 95% confidence interval [CI], 2.19-2.22), age (aIRR, 4.97; 95% CI, 4.90-5.05 for ≥57 years vs. <11 years), comorbidities (aIRR, 4.36 for Charlson Comorbidity Index >10 vs. 0; 95% CI, 3.78-5.03), and higher neighborhood income (aIRR, 1.04; 95% CI, 1.02-1.05 for highest vs. lowest quintile) were associated with higher rates of ultrasound utilization. Individuals who were status First Nations (aIRR, 0.91; 95% CI, 0.90-0.92) or resided in geographically remote areas (aIRR, 0.87 for most vs. least remote; 95% CI, 0.83-0.91) had lower rates of ultrasound utilization. Individuals who lived in a rural area also had lower rates of ultrasound utilization (aIRR, 0.93; 95% CI, 0.92-0.94).

CONCLUSION

Substantial disparities exist in non-obstetrical ultrasound utilization among individuals in low-income neighborhoods, status First Nations individuals, and individuals in rural and remote communities.

Review of Artificial Intelligence Training Tools and Courses for Radiologists

Artificial intelligence (AI) systems play an increasingly important role in all parts of the imaging chain, from image creation to image interpretation to report generation. In order to responsibly manage radiology AI systems and make informed purchase decisions about them, radiologists must understand the underlying principles of AI. Our task force was formed by the Radiology Research Alliance (RRA) of the Association of University Radiologists to identify and summarize a curated list of current educational materials available for radiologists.

Combined lumbar spine MRI and CT appropriateness checklist: a quality improvement project in Saskatchewan, Canada

Background

As rates of advanced imaging for lower back pain (LBP) continue to increase, there is a need to ensure the appropriateness of imaging.

Objective

The goal of this project was to reduce the number of inappropriate magnetic resonance imaging (MRI) and computed tomography (CT) requests for LBP patients and facilitate appropriate imaging by developing a combined imaging appropriateness checklist for lumbar spine MRI and CT.

Methods

In prior work, we developed and adopted individual evidence-based lumbar spine MRI and CT checklists into the radiology requisition process. In the current project, a combined checklist was developed and trialed in one of the former Saskatchewan health regions (Five Hills) beginning in May 2018. Using statistical process control, control charts compared the monthly number of imaging requests pre-checklist implementation and post-checklist implementation from May 2017 to February 2020. The monthly number of lumbar spine MRI and CT requisitions in the nearby former Saskatchewan Regina Qu’Appelle Health Region, in which the combined checklist was not trialed, was also plotted and compared as a balancing measure.

Results

In Five Hills, a shift (decrease) was observed in the monthly number of lumbar spine MRI requisitions 7 months following the implementation of the combined checklist. However, the monthly number of lumbar spine CT requisitions did not change significantly. In the Regina Qu’Appelle Health Region, there was a shift (increase) in the monthly number of lumbar spine MRI requisitions, while the monthly number of lumbar spine CT requests decreased after the implementation of the combined checklist.

Conclusions

The combined checklist with evidence-based indications for lumbar spine MRI and CT imaging in LBP patients appeared to reduce the complexity associated with two previous individual checklists and facilitate imaging appropriateness. Accountable benefits may include the reduction of radiation exposure as a result of unnecessary and repeated imaging and reduction in wait times for CT and/or MRI.

Access to ultrasound imaging: A qualitative study in two northern, remote, Indigenous communities in Canada

Ultrasound imaging is an essential component of healthcare services. This study sought to explore perceptions of access, and factors which shape access, to ultrasound imaging in two northern, remote, Indigenous communities in Canada. Using interpretive description as a methodological approach and a multi-dimensional conceptualisation of access to care as a theoretical framework, 15 semi-structured interviews were conducted in the northern Canadian communities of Stony Rapids and Black Lake, Saskatchewan. All participants had an obstetrical or non-obstetrical ultrasound exam performed in the past 10 years. Interviews were audio recorded and interview transcripts were analysed using constant comparative analysis. Geographic isolation from imaging facilities was a central barrier to participants accessing ultrasound imaging. Other barriers became apparent when participants had to travel for ultrasound, including fear of air travel, isolation from family, financial means, and unfamiliarity with larger cities. Barriers such as family and work responsibilities were exacerbated by the barrier of geography. Participants overcame these barriers as they were motivated by potential diagnostic benefits of ultrasound imaging. This study highlights disparities in access to ultrasound for northern, remote, Indigenous populations. Future efforts to improve access to imaging should consider barriers of distance to imaging facilities and strategies to bridge these barriers.

Development and assessment of a telesonography system for musculoskeletal imaging

Background

Telesonography systems have been developed to overcome barriers to accessing diagnostic ultrasound for patients in rural and remote communities. However, most previous telesonography systems have been designed for performing only abdominal and obstetrical exams. In this paper, we describe the development and assessment of a musculoskeletal (MSK) telesonography system.

Methods

We developed a 4-degrees-of-freedom (DOF) robot to manipulate an ultrasound probe. The robot was remotely controlled by a radiologist operating a joystick at the master site. The telesonography system was used to scan participants’ forearms, and all participants were conventionally scanned for comparison. Participants and radiologists were surveyed regarding their experience. Images from both scanning methods were independently assessed by an MSK radiologist.

Results

All ten ultrasound exams were successfully performed using our developed MSK telesonography system, with no significant delay in movement. The duration (mean ± standard deviation) of telerobotic and conventional exams was 4.6 ± 0.9 and 1.4 ± 0.5 min, respectively (p = 0.039). An MSK radiologist rated quality of real-time ultrasound images transmitted over an internet connection as “very good” for all telesonography exams, and participants rated communication with the radiologist as “very good” or “good” for all exams. Visualisation of anatomic structures was similar between telerobotic and conventional methods, with no statistically significant differences.

Conclusions

The MSK telesonography system developed in this study is feasible for performing soft tissue ultrasound exams. The advancement of this system may allow MSK ultrasound exams to be performed over long distances, increasing access to ultrasound for patients in rural and remote communities.

Telerobotic Sonography for Remote Diagnostic Imaging: Narrative Review of Current Developments and Clinical Applications

Access to sonographers and sonologists is limited in many communities around the world. Telerobotic sonography (robotic ultrasound) is a new technology to increase access to sonography, providing sonographers and sonologists the ability to manipulate an ultrasound probe from a distant location and remotely perform ultrasound examinations. This narrative review discusses the development of telerobotic ultrasound systems, clinical studies evaluating the feasibility and diagnostic accuracy of telerobotic sonography, and emerging use of telerobotic sonography in clinical settings. Telerobotic sonography provides an opportunity to provide real-time ultrasound examinations to underserviced rural and remote communities to increase equity in the delivery of diagnostic imaging.

Automatic Detection and Classification of Multiple Catheters in Neonatal Radiographs with Deep Learning

We develop and evaluate a deep learning algorithm to classify multiple catheters on neonatal chest and abdominal radiographs. A convolutional neural network (CNN) was trained using a dataset of 777 neonatal chest and abdominal radiographs, with a split of 81%-9%-10% for training-validation-testing, respectively. We employed ResNet-50 (a CNN), pre-trained on ImageNet. Ground truth labelling was limited to tagging each image to indicate the presence or absence of endotracheal tubes (ETTs), nasogastric tubes (NGTs), and umbilical arterial and venous catheters (UACs, UVCs). The dataset included 561 images containing two or more catheters, 167 images with only one, and 49 with none. Performance was measured with average precision (AP), calculated from the area under the precision-recall curve. On our test data, the algorithm achieved an overall AP (95% confidence interval) of 0.977 (0.679-0.999) for NGTs, 0.989 (0.751-1.000) for ETTs, 0.979 (0.873-0.997) for UACs, and 0.937 (0.785-0.984) for UVCs. Performance was similar for the set of 58 test images consisting of two or more catheters, with an AP of 0.975 (0.255-1.000) for NGTs, 0.997 (0.009-1.000) for ETTs, 0.981 (0.797-0.998) for UACs, and 0.937 (0.689-0.990) for UVCs. Our network thus achieves strong performance in the simultaneous detection of these four catheter types. Radiologists may use such an algorithm as a time-saving mechanism to automate reporting of catheters on radiographs.

Development and Cost Analysis of a Lung Nodule Management Strategy Combining Artificial Intelligence and Lung-RADS for Baseline Lung Cancer Screening

OBJECTIVES

To develop a lung nodule management strategy combining the Lung CT Screening Reporting and Data System (Lung-RADS) with an artificial intelligence (AI) malignancy risk score and determine its impact on follow-up investigations and associated costs in a baseline lung cancer screening population.

MATERIALS AND METHODS

Secondary analysis was undertaken of a data set consisting of AI malignancy risk scores and Lung-RADS classifications from six radiologists for 192 baseline low-dose CT studies. Low-dose CT studies were weighted to model a representative cohort of 3,197 baseline screening patients. An AI risk score threshold was defined to match average sensitivity of six radiologists applying Lung-RADS. Cases initially Lung-RADS category 1 or 2 with a high AI risk score were upgraded to category 3, and cases initially category 3 or higher with a low AI risk score were downgraded to category 2. Follow-up investigations resulting from Lung-RADS and the AI-informed management strategy were determined. Investigation costs were based on the 2019 US Medicare Physician Fee Schedule.

RESULTS

The AI-informed management strategy achieved sensitivity and specificity of 91% and 96%, respectively. Average sensitivity and specificity of six radiologists using Lung-RADS only was 91% and 66%, respectively. Using the AI-informed management strategy, 41 (0.2%) category 1 or 2 classifications were upgraded to category 3, and 5,750 (30%) category 3 or higher classifications were downgraded to category 2. Minimum net cost savings using the AI-informed management strategy was estimated to be $72 per patient screened.

CONCLUSION

Using an AI risk score combined with Lung-RADS at baseline lung cancer screening may result in fewer follow-up investigations and substantial cost savings.

Artificial intelligence-based imaging analytics and lung cancer diagnostics: Considerations for health system leaders

Lung cancer is a leading cause of cancer death in Canada, and accurate, early diagnosis are critical to improving clinical outcomes. Artificial Intelligence (AI)-based imaging analytics are a promising healthcare innovation that aim to improve the accuracy and efficiency of lung cancer diagnosis. Maximizing their clinical potential while mitigating their risks and limitations will require focused leadership informed by interdisciplinary expertise and system-wide insight. We convened a knowledge exchange workshop with diverse Saskatchewan health system leaders and stakeholders to explore issues surrounding the use of AI in diagnostic imaging for lung cancer, including implementation opportunities, challenges, and priorities. This technology is anticipated to improve patient outcomes, reduce unnecessary healthcare spending, and increase knowledge. However, health system leaders must also address the needs for robust data, financial investment, effective communication and collaboration between healthcare sectors, privacy and data protections, and continued interdisciplinary research to achieve this technology's potential benefits.

Telerobotic ultrasound to provide obstetrical ultrasound services remotely during the COVID-19 pandemic

Introduction

Obstetrical ultrasound imaging is critical in identifying at-risk pregnancies and informing clinical management. The coronavirus disease 2019 (COVID-19) pandemic has exacerbated challenges in accessing obstetrical ultrasound for patients in underserved rural and remote communities where this service is not available. This prospective descriptive study describes our experience of providing obstetrical ultrasound services remotely using a telerobotic ultrasound system in a northern Canadian community isolated due to a COVID-19 outbreak.

Methods

A telerobotic ultrasound system was used to perform obstetrical ultrasound exams remotely in La Loche, Canada, a remote community without regular access to obstetrical ultrasound. Using a telerobotic ultrasound system, a sonographer 605 km away remotely controlled an ultrasound probe and ultrasound settings. Twenty-one exams were performed in a five-week period during a COVID-19 outbreak in the community, including limited first-, second- and third-trimester exams (n = 11) and complete second-trimester exams (n = 10). Participants were invited to complete a survey at the end of the telerobotic ultrasound exam describing their experiences with telerobotic ultrasound. Radiologists subsequently interpreted all exams and determined the adequacy of the images for diagnosis.

Results

Of 11 limited obstetrical exams, radiologists indicated images were adequate in nine (81%) cases, adequate with some reservations in one (9%) case and inadequate in one (9%) case. Of 10 second-trimester complete obstetrical exams, radiologists indicated images were adequate in two (20%) cases, adequate with some reservations in three (30%) cases and inadequate in five (50%) cases. Second-trimester complete obstetrical exams were limited due to a combination of body habitus, foetal lie and telerobotic technology.

Discussion

A telerobotic ultrasound system may be used to answer focused clinical questions such as foetal viability, dating and foetal presentation in a timely manner while minimising patient travel to larger centres and potential exposure to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), during the COVID-19 pandemic.

Artificial Intelligence Solutions for Analysis of X-ray Images

Artificial intelligence (AI) presents a key opportunity for radiologists to improve quality of care and enhance the value of radiology in patient care and population health. The potential opportunity of AI to aid in triage and interpretation of conventional radiographs (X-ray images) is particularly significant, as radiographs are the most common imaging examinations performed in most radiology departments. Substantial progress has been made in the past few years in the development of AI algorithms for analysis of chest and musculoskeletal (MSK) radiographs, with deep learning now the dominant approach for image analysis. Large public and proprietary image data sets have been compiled and have aided the development of AI algorithms for analysis of radiographs, many of which demonstrate accuracy equivalent to radiologists for specific, focused tasks. This article describes (1) the basis for the development of AI solutions for radiograph analysis, (2) current AI solutions to aid in the triage and interpretation of chest radiographs and MSK radiographs, (3) opportunities for AI to aid in noninterpretive tasks related to radiographs, and (4) considerations for radiology practices selecting AI solutions for radiograph analysis and integrating them into existing IT systems. Although comprehensive AI solutions across modalities have yet to be developed, institutions can begin to select and integrate focused solutions which increase efficiency, increase quality and patient safety, and add value for their patients.

Computer-aided Assessment of Catheters and Tubes on Radiographs: How Good Is Artificial Intelligence for Assessment?

Catheters are the second most common abnormal finding on radiographs. The position of catheters must be assessed on all radiographs because serious complications can arise if catheters are malpositioned. However, due to the large number of radiographs obtained each day, there can be substantial delays between the time a radiograph is obtained and when it is interpreted by a radiologist. Computer-aided approaches hold the potential to assist in prioritizing radiographs with potentially malpositioned catheters for interpretation and automatically insert text indicating the placement of catheters in radiology reports, thereby improving radiologists' efficiency. After 50 years of research in computer-aided diagnosis, there is still a paucity of study in this area. With the development of deep learning approaches, the problem of catheter assessment is far more solvable. This review provides an overview of current algorithms and identifies key challenges in building a reliable computer-aided diagnosis system for assessment of catheters on radiographs. This review may serve to further the development of machine learning approaches for this important use case. Supplemental material is available for this article. © RSNA, 2020.

Development of a risk assessment model to differentiate malignant and benign musculoskeletal soft-tissue masses on magnetic resonance imaging

INTRODUCTION

This study aimed to develop a risk stratification model to differentiate benign and malignant MRI-imaged musculoskeletal soft-tissue tumours, informing decisions surrounding biopsy and follow-up imaging.

METHODS

Imaging of patients who underwent MRI and subsequent biopsy to evaluate a soft-tissue mass was retrospectively reviewed. Features analysed included patient age; tumour size; shape; margins; enhancement pattern; signal intensity pattern; deep fascia, neurovascular bundle, bone and joint involvement; and the presence of necrosis, haemorrhage, oedema and intralesional fat. Univariate comparisons, by final histopathological status, employed t-tests and chi-square tests, followed by simple and multiple logistic regressions. Variables included in the final multiple regression model were used to define a three-level risk stratification strategy.

RESULTS

One-hundred and ten patients were included in the analysis. Univariate relationships were identified between malignancy and age, tumour size, deep fascia involvement, neurovascular involvement, necrosis, haemorrhage, oedema and heterogeneous enhancement (all P < 0.01). Final multiple regression modelling included size, enhancement and oedema. Thirty of 40 (75%) tumours >5 cm with surrounding oedema ('high risk') were malignant, 13 of 47 (28%) tumours with one or more of tumour size >5 cm, surrounding oedema or heterogeneous enhancement ('moderate risk') were malignant, and none of the 16 tumours ≤5 cm with the absence of surrounding oedema and heterogeneous enhancement ('low risk') were malignant.

CONCLUSIONS

A model including tumour size, enhancement and oedema has potential to stratify soft-tissue tumours into high-, intermediate- and low-risk categories; this may inform decisions surrounding biopsy and follow-up imaging.

A Crossover Comparison of Standard and Telerobotic Approaches to Prenatal Sonography

OBJECTIVES

To determine the feasibility of a telerobotic approach to remotely perform prenatal sonographic examinations.

METHODS

Thirty participants were prospectively recruited. Participants underwent a limited examination (assessing biometry, placental location, and amniotic fluid; n = 20) or a detailed examination (biometry, placental location, amniotic fluid, and fetal anatomic survey; n = 10) performed with a conventional ultrasound system. This examination was followed by an equivalent examination performed with a telerobotic ultrasound system, which enabled sonographers to remotely control all ultrasound settings and fine movements of the ultrasound transducer from a distance. Telerobotic images were read independently from conventional images.

RESULTS

The mean gestational age ± SD of the 30 participants was 22.9 ± 5.3 weeks. Paired-sample t tests showed no statistically significant difference between conventional and telerobotic measurements of fetal head circumference, biparietal diameter, or single deepest vertical pocket of amniotic fluid; however, a small but statistically significant difference was observed in measurements of abdominal circumference and femur length (P < .05). Intraclass correlations showed excellent agreement (>0.90) between telerobotic and conventional measurements of all 4 biometric parameters. Of 21 fetal structures included in the anatomic survey, 80% of the structures attempted across all patients were sufficiently visualized by the telerobotic system (range, 57%-100% per patient). Ninety-seven percent of patients strongly or somewhat agreed that they would be willing to have another telerobotic examination in the future.

CONCLUSIONS

A telerobotic approach is feasible for remotely performing prenatal sonographic examinations. Telerobotic sonography (robotic telesonography) may allow for the development of satellite ultrasound clinics in rural, remote, or low-volume communities, thereby increasing access to prenatal imaging in underserved communities.

Adult-onset leukoencephalopathy with axonal spheroids and pigmented glia (ALSP): Integrating the literature on hereditary diffuse leukoencephalopathy with spheroids (HDLS) and pigmentary orthochromatic leukodystrophy (POLD)

Adult-onset leukoencephalopathy with axonal spheroids and pigmented glia (ALSP) is a progressive degenerative white matter disorder. ALSP was previously recognized as two distinct entities, hereditary diffuse leukoencephalopathy with spheroids (HDLS) and pigmentary orthochromatic leukodystrophy (POLD). However, recent identification of mutations in the tyrosine kinase domain of the colony stimulating factor 1 receptor (CSF1R) gene, which regulates mononuclear cell lineages including microglia, have provided genetic and mechanistic evidence that POLD and HDLS should be regarded as a single clinicopathologic entity. We describe two illustrative cases of ALSP which presented with neuropsychiatric symptoms, progressive cognitive decline, and motor and gait disturbances. Antemortem diagnoses of autopsy-confirmed ALSP vary significantly, and include primary progressive multiple sclerosis, frontotemporal dementia, Alzheimer disease, atypical cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL), corticobasal syndrome, and atypical Parkinson disease, suggesting that ALSP may be significantly underdiagnosed. This article presents a systematic review of ALSP in the context of two illustrative cases to help integrate the literature on HDLS and POLD. Consistent use of the term ALSP is suggested for clarity in the literature going forward.

Invasive lobular carcinoma of the male breast - a systematic review with an illustrative case study

Male breast cancer is rare, comprising only 1% of all mammary cancers; invasive ductal carcinoma is by far the commonest subtype in both men and women. Though lobular breast cancer is the second most common subtype seen in women, such cancers are extremely uncommon in men, and this is likely related to the lack of lobular development in the male breast. Thus, due to the rarity of this subtype among breast cancers, compounded by the overall rarity of breast cancer in men, current understanding of the pathogenesis of this disease and its management is largely derived from case series and extrapolation of information from the larger cohort of female patients. This paper provides a systematic review on invasive lobular carcinoma of the male breast in the context of an illustrative case study. A comprehensive analysis of the National Cancer Institute's Surveillance, Epidemiology, and End Results Data 1973-2013 leading to an exploration of the pathogenesis, epidemiology, clinical presentation, diagnosis, tumor characteristics, and management of lobular breast carcinoma in men is also discussed. Lobular subtype of breast cancer remains an enigmatic elusive disease that needs additional research to unravel its overall pathogenesis and molecular profile to provide insight for improved therapeutic management options.

Initial Experience Using a Telerobotic Ultrasound System for Adult Abdominal Sonography

PURPOSE

The study sought to assess the feasibility of performing adult abdominal examinations using a telerobotic ultrasound system in which radiologists or sonographers can control fine movements of a transducer and all ultrasound settings from a remote location.

METHODS

Eighteen patients prospectively underwent a conventional sonography examination (using EPIQ 5 [Philips] or LOGIQ E9 [GE Healthcare]) followed by a telerobotic sonography examination (using the MELODY System [AdEchoTech] and SonixTablet [BK Ultrasound]) according to a standardized abdominal imaging protocol. For telerobotic examinations, patients were scanned remotely by a sonographer 2.75 km away. Conventional examinations were read independently from telerobotic examinations. Image quality and acceptability to patients and sonographers was assessed.

RESULTS

Ninety-two percent of organs visualized on conventional examinations were sufficiently visualized on telerobotic examinations. Five pathological findings were identified on both telerobotic and conventional examinations, 3 findings were identified using only conventional sonography, and 2 findings were identified using only telerobotic sonography. A paired sample t test showed no significant difference between the 2 modalities in measurements of the liver, spleen, and diameter of the proximal aorta; however, telerobotic assessments overestimated distal aorta and common bile duct diameters and underestimated kidney lengths (P values < .05). All patients responded that they would be willing to have another telerobotic examination.

CONCLUSIONS

A telerobotic ultrasound system is feasible for performing abdominal ultrasound examinations at a distant location with minimal training and setup requirements and a moderate learning curve. Telerobotic sonography (robotic telesonography) may open up the possibility of remote ultrasound clinics for communities that lack skilled sonographers and radiologists, thereby improving access to care.

Cost analysis of a home-based nurse care coordination program

Objectives

To determine whether a home-based care coordination program focused on medication self-management would affect the cost of care to the Medicare program and whether the addition of technology, a medication-dispensing machine, would further reduce cost.

Design

Randomized, controlled, three-arm longitudinal study.

Setting

Participant homes in a large Midwestern urban area.

Participants

Older adults identified as having difficulty managing their medications at discharge from Medicare Home Health Care (N = 414).

Intervention

A team consisting of advanced practice nurses (APNs) and registered nurses (RNs) coordinated care for two groups: home-based nurse care coordination (NCC) plus a pill organizer group and NCC plus a medication-dispensing machine group.

Measurements

To measure cost, participant claims data from 2005 to 2011 were retrieved from Medicare Part A and B Standard Analytical Files.

Results

Ordinary least squares regression with covariate adjustment was used to estimate monthly dollar savings. Total Medicare costs were $447 per month lower in the NCC plus pill organizer group (P = .11) than in a control group that received usual care. For participants in the study at least 3 months, total Medicare costs were $491 lower per month in the NCC plus pill organizer group (P = .06) than in the control group. The cost of the NCC plus pill organizer intervention was $151 per month, yielding a net savings of $296 per month or $3,552 per year. The cost of the NCC plus medication-dispensing machine intervention was $251 per month, and total Medicare costs were $409 higher per month than in the NCC plus pill organizer group.

Conclusion

Nurse care coordination plus a pill organizer is a cost-effective intervention for frail elderly Medicare beneficiaries. The addition of the medication machine did not enhance the cost effectiveness of the intervention.

Use of the Tecpro Pork Quality Meter for assessing meat quality on the slaughterline

Conductivity measurements made with the Tecpro Pork Quality Meter at either 45 min or about 20 h post mortem on 224 pig cacassees which exhibited a wide range of raw meat quality were moderately correlated with initial pH (pH(45); r = 0.54 and 0.62) but less well correlated with reflectance (r = 0.32 and 0.37), drip loss (r = 0.34 and 0.47 and other objective measures of meat quality in the M. Longissimus dorsi. Measurements did not allow differentiation between normal and dark, firm, dry (DFD) meat but were of some value in identifying carcasses producing potentially pole, soft, exudative (PSE) meat. In the UK they would be more useful for monitoring meat quality in large groups or populations of pigs, than for categorising individual carcasses for grading on technological purposes.

Aging in place versus nursing home care: comparison of costs to Medicare and Medicaid

The objective of this study was to compare the community-based, long-term care program called Aging in Place (AIP) and nursing home care, in terms of cost to the Medicare and Medicaid programs. A retrospective cohort design was used in this study of 39 nursing home residents in the Midwest who were matched with 39 AIP participants. The AIP program consisted of a combination of Medicare home health, Medicaid home and community-based services (HCBS), and intensive nurse care coordination. Controlling for high inpatient Medicare cost in the 6 months prior and the 10 most frequently occurring chronic conditions, multiple regression was used to estimate the relationship of the AIP program on Medicare and Medicaid costs. Total Medicare and Medicaid costs were $1,591.61 lower per month in the AIP group (p < 0.01) when compared with the nursing home group over a 12-month period. The findings suggest that the provision of nurse-coordinated HCBS and Medicare home health services has potential to provide savings in the total cost of health care to the Medicaid program while not increasing the cost of the Medicare program.

The relationship of community-based nurse care coordination to costs in the Medicare and Medicaid programs

The purpose of this evaluation was to study the relationship of nurse care coordination (NCC) to the costs of Medicare and Medicaid in a community-based care program called Missouri Care Options (MCO). A retrospective cohort design was used comparing 57 MCO clients with NCC to 80 MCO clients without NCC. Total cost was measured using Medicare and Medicaid claims databases. Fixed effects analysis was used to estimate the relationship of the NCC intervention to costs. Controlling for high resource use on admission, monthly Medicare costs were lower ($686) in the 12 months of NCC intervention (p = .04) while Medicaid costs were higher ($203; p = .03) for the NCC group when compared to the costs of MCO group.

GATA4 is essential for jejunal function in mice

BACKGROUND & AIMS

Although the zinc-finger transcription factor GATA4 has been implicated in regulating jejunal gene expression, the contribution of GATA4 in controlling jejunal physiology has not been addressed.

METHODS

We generated mice in which the Gata4 gene was specifically deleted in the small intestinal epithelium. Measurements of plasma cholesterol and phospholipids, intestinal absorption of dietary fat and cholesterol, and gene expression were performed on these animals.

RESULTS

Mice lacking GATA4 in the intestine displayed a dramatic block in their ability to absorb cholesterol and dietary fat. Comparison of the global gene expression profiles of control jejunum, control ileum, and GATA4 null jejunum by gene array analysis revealed that GATA4 null jejunum lost expression of 53% of the jejunal-specific gene set and gained expression of 47% of the set of genes unique to the ileum. These alterations in gene expression included a decrease in messenger RNAs (mRNAs) encoding lipid and cholesterol transporters as well as an increase in mRNAs encoding proteins involved in bile acid absorption.

CONCLUSIONS

Our data demonstrate that GATA4 is essential for jejunal function including fat and cholesterol absorption and confirm that GATA4 plays a pivotal role in determining jejunal vs ileal identity.

Illness perception and health-related quality of life in multiple sclerosis

AIMS - A number of physical and psychological factors have been shown to affect health-related quality of life (HRQoL) in patients with multiple sclerosis (MS). Among these, the role of illness perceptions has not been established as an independent factor. This study, the first of its kind in an Australian population, aimed to use a large sample to determine the relative importance of individual factors to each domain of HRQoL, in particular the role of illness perception. MATERIALS AND METHODS - 580 patients with confirmed MS were assessed cross sectionally in a designated research clinic to determine the relative impact of physical factors (illness severity, duration, age, fatigue and pain) and psychological factors (mood, cognition and illness representations) on each domain of the SF-36. RESULTS - Categorical regression analysis showed that a combination of physical and psychological factors predicted 38-71% of variance in HRQoL. Illness perception was shown to have an independent effect on HRQoL in MS. The Extended Disability Status Scale was a significant determinant in all domains except for mental health. Depression was less prevalent than anxiety, but had a greater effect on function. CONCLUSION - Illness perception is an independent factor contributing to HRQoL in people with MS. Individual domains of HRQoL are associated with different patterns of physical and psychological factors. In the domains of role and social function, activities most highly valued by patients with MS, depression, anxiety, fatigue and illness perceptions are key determinants, all of which have the potential to be improved through specific interventions.

Differential effectiveness of depression disease management for rural and urban primary care patients

CONTEXT

Federally qualified health centers across the country are adopting depression disease management programs following federally mandated training; however, little is known about the relative effectiveness of depression disease management in rural versus urban patient populations.

PURPOSE

To explore whether a depression disease management program has a comparable impact on clinical outcomes over 2 years in patients treated in rural and urban primary care practices and whether the impact is mediated by receiving evidence-based care (antidepressant medication and specialty care counseling).

METHODS

A preplanned secondary analysis was conducted in a consecutively sampled cohort of 479 depressed primary care patients recruited from 12 practices in 10 states across the country participating in the Quality Enhancement for Strategic Teaming study.

FINDINGS

Depression disease management improved the mental health status of urban patients over 18 months but not rural patients. Effects were not mediated by antidepressant medication or specialty care counseling in urban or rural patients.

CONCLUSIONS

Depression disease management appears to improve clinical outcomes in urban but not rural patients. Because these programs compete for scarce resources, health care organizations interested in delivering depression disease management to rural populations need to advocate for programs whose clinical effectiveness has been demonstrated for rural residents.