Applications, limitations and advancements of ultra-low-field magnetic resonance imaging: A scoping review.

Background: Ultra-low-field magnetic resonance imaging (ULF-MRI) has emerged as an alternative with several portable clinical applications. This review aims to comprehensively explore its applications, potential limitations, technological advancements, and expert recommendations. Methods: A review of the literature was conducted across medical databases to identify relevant studies. Articles on clinical usage of ULF-MRI were included, and data regarding applications, limitations, and advancements were extracted. A total of 25 articles were included for qualitative analysis. Results: The review reveals ULF-MRI efficacy in intensive care settings and intraoperatively. Technological strides are evident through innovative reconstruction techniques and integration with machine learning approaches. Additional advantages include features such as portability, cost-effectiveness, reduced power requirements, and improved patient comfort. However, alongside these strengths, certain limitations of ULF-MRI were identified, including low signal-to-noise ratio, limited resolution and length of scanning sequences, as well as variety and absence of regulatory-approved contrast-enhanced imaging. Recommendations from experts emphasize optimizing imaging quality, including addressing signal-to-noise ratio (SNR) and resolution, decreasing the length of scan time, and expanding point-of-care magnetic resonance imaging availability. Conclusion: This review summarizes the potential of ULF-MRI. The technology's adaptability in intensive care unit settings and its diverse clinical and surgical applications, while accounting for SNR and resolution limitations, highlight its significance, especially in resource-limited settings. Technological advancements, alongside expert recommendations, pave the way for refining and expanding ULF-MRI's utility. However, adequate training is crucial for widespread utilization.

Intraoperative use of low-field magnetic resonance imaging for brain tumors: A systematic review.

Background: Low-field magnetic resonance imaging (LF-MRI) has become a valuable tool in the diagnosis of brain tumors due to its high spatial resolution and ability to acquire images in a short amount of time. However, the use of LF-MRI for intraoperative imaging during brain tumor surgeries has not been extensively studied. The aim of this systematic review is to investigate the impact of low-field intraoperative magnetic resonance imaging (LF-IMRI) on the duration of brain tumor surgery and the extent of tumor resection. Methods: A comprehensive literature search was conducted using PubMed, Scopus, and Google Scholar from February 2000 to December 2022. The studies were selected based on the inclusion criteria and reviewed independently by two reviewers. The gathered information was organized and analyzed using Excel. Results: Our review of 21 articles found that low-field intraoperative MRI (LF-IMRI) with a field below 0.3T was used in most of the studies, specifically 15 studies used 0.15T LF-IMRI. The T1-weighted sequence was the most frequently reported, and the average scanning time was 24.26 min. The majority of the studies reported a positive impact of LF-IMRI on the extent of tumor resection, with an increase ranging from 11% to 52.5%. Notably, there were no studies describing the use of ultra-low-field (ULF) intraoperative MRI. Conclusion: The results of this systematic review will aid neurosurgeons and neuroradiologists in making informed decisions about the use of LF-MRI in brain tumor surgeries. Further, research is needed to fully understand the impact of LF-MRI in brain tumor surgeries and to optimize its use in the clinical setting. There is an opportunity to study the utility of ULF-MRI in brain tumor surgeries.

Utilization of an ultra-low-field, portable magnetic resonance imaging for brain tumor assessment in lower middle-income countries.

Background: Access to neuroimaging is limited in low-middle-income countries (LMICs) due to financial and resource constraints. A new, ultra-low-field, low-cost, and portable magnetic resonance imaging (pMRI) device could potentially increase access to imaging in LMICs. Case Description: We have presented the first brain tumor case scanned using an Ultra-low-field pMRI at Aga Khan University Hospital in Karachi, Pakistan. Conclusion: The imaging results suggest that the pMRI device can aid in neuroradiological diagnosis in resource-constrained settings. Further, research is needed to assess its compatibility for imaging other neurological disorders and compare its results with conventional MRI results.

Intraoperative use of ultra-low-field, portable magnetic resonance imaging - first report.

Background: Intraoperative use of portable magnetic resonance imaging (pMRI) has become a valuable tool in a surgeon's arsenal since its inception. It allows intraoperative localization of tumor extent and identification of residual disease, hence maximizing tumor resection. Its utility has been widespread in high-income countries for the past 20 years, but in lower-middle-income countries (LMIC), it is still not widely available due to several reasons, including cost constraints. The use of intraoperative pMRI may be a cost-effective and efficient substitute for conventional MRI machines. The authors present a case where a pMRI device was used intraoperatively in an LMIC setting. Case Description: The authors performed a microscopic transsphenoidal resection of a sellar lesion with intraoperative imaging using the pMRI system on a 45-year-old man with a nonfunctioning pituitary macroadenoma. Without the need for an MRI suite or other MRI-compatible equipment, the scan was conducted within the confinements of a standard operating room. Low-field MRI showed some residual disease and postsurgical changes, comparable to postoperative high-field MRI. Conclusion: To the best of our knowledge, our report provides the first documented successful intraoperative transsphenoidal resection of a pituitary adenoma using an ultra-low-field pMRI device. The device can potentially enhance neurosurgical capacity in resource-constrained settings and improve patient outcomes in developing country.

The Retail Outlet Health Kiosk Hypertension Trial (ROKHYT): Pilot Results.

BACKGROUND: Blood pressure (BP) control was only 43.7% in the National Health and Nutrition Survey (NHANES) survey in 2017-2018. Scalable, nonclinic-based strategies to control BP are needed. We therefore conducted a pilot trial of a text-messaging intervention in a national network of retail outlet health kiosks with BP devices. All study procedures were conducted remotely. METHODS: Eligible individuals (N = 140), based on average BP greater than or equal to 140/90 mm Hg at kiosks during the prior year, were randomized to intervention vs. usual care. Intervention consisted of tailored text messages providing educational information with embedded links to educational videos on topics related to BP control. BP measurements were obtained at kiosks at 3, 6, and 12 months following randomization; control was defined as BP < 140/90 mm Hg. Follow-up at 12 months was curtailed due to SARS-CoV-2. We therefore combined 12-month (N = 62) or carried forward 6-month (N = 61) data as the primary end point. RESULTS: Participants were 51.4% male, 70.7% white/Caucasian, had mean age of 52.1 years, and mean baseline BP 145.5/91.8 mm Hg. At the end point, 37.7% intervention vs. 27.4% usual care subjects achieved BP control (difference, 10.3%, 95% confidence interval -6.2%, 26.8%). In an intention-to-treat analysis with multiple imputation of missing data, 12-month BP control was 29.0% vs. 19.8% favoring intervention (difference, 9.2%. 95% confidence interval -7.3%, 25.7%); intervention vs. control differences in adjusted mean BP levels were systolic BP: -5.4 mm Hg (95% confidence interval: -13.5, 2.7) and diastolic BP: +0.6 mm Hg (95% confidence interval: -4.2, 5.4). CONCLUSIONS: These pilot results support the potential for a highly scalable text-messaging intervention to improve BP. CLINICAL TRIALS REGISTRATION: Trial Number NCT03515681.

Emerging ethical issues raised by highly portable MRI research in remote and resource-limited international settings.

Smaller, more affordable, and more portable MRI brain scanners offer exciting opportunities to address unmet research needs and long-standing health inequities in remote and resource-limited international settings. Field-based neuroimaging research in low- and middle-income countries (LMICs) can improve local capacity to conduct both structural and functional neuroscience studies, expand knowledge of brain injury and neuropsychiatric and neurodevelopmental disorders, and ultimately improve the timeliness and quality of clinical diagnosis and treatment around the globe. Facilitating MRI research in remote settings can also diversify reference databases in neuroscience, improve understanding of brain development and degeneration across the lifespan in diverse populations, and help to create reliable measurements of infant and child development. These deeper understandings can lead to new strategies for collaborating with communities to mitigate and hopefully overcome challenges that negatively impact brain development and quality of life. Despite the potential importance of research using highly portable MRI in remote and resource-limited settings, there is little analysis of the attendant ethical, legal, and social issues (ELSI). To begin addressing this gap, this paper presents findings from the first phase of an envisioned multi-staged and iterative approach for creating ethical and legal guidance in a complex global landscape. Section 1 provides a brief introduction to the emerging technology for field-based MRI research. Section 2 presents our methodology for generating plausible use cases for MRI research in remote and resource-limited settings and identifying associated ELSI issues. Section 3 analyzes core ELSI issues in designing and conducting field-based MRI research in remote, resource-limited settings and offers recommendations. We argue that a guiding principle for field-based MRI research in these contexts should be including local communities and research participants throughout the research process in order to create sustained local value. Section 4 presents a recommended path for the next phase of work that could further adapt these use cases, address ethical and legal issues, and co-develop guidance in partnership with local communities.

Machine Learning for Child and Adolescent Health: A Systematic Review.

CONTEXT: In the last few decades, data acquisition and processing has seen tremendous amount of growth, thus sparking interest in machine learning (ML) within the health care system. OBJECTIVE: Our aim for this review is to provide an evidence map of the current available evidence on ML in pediatrics and adolescent medicine and provide insight for future research. DATA SOURCES: A literature search was conducted by using Medline, the Cochrane Library, the Cumulative Index to Nursing and Allied Health Literature Plus, Web of Science Library, and EBSCO Dentistry & Oral Science Source. STUDY SELECTION: Articles in which an ML model was assessed for the diagnosis, prediction, or management of any condition in children and adolescents (0-18 years) were included. DATA EXTRACTION: Data were extracted for year of publication, geographical location, age range, number of participants, disease or condition under investigation, study methodology, reference standard, type, category, and performance of ML algorithms. RESULTS: The review included 363 studies, with subspecialties such as psychiatry, neonatology, and neurology having the most literature. A majority of the studies were from high-income (82%; n = 296) and upper middle-income countries (15%; n = 56), whereas only 3% (n = 11) were from low middle-income countries. Neural networks and ensemble methods were most commonly tested in the 1990s, whereas deep learning and clustering emerged rapidly in the current decade. LIMITATIONS: Only studies conducted in the English language could be used in this review. CONCLUSIONS: The interest in ML has been growing across various subspecialties and countries, suggesting a potential role in health service delivery for children and adolescents in the years to come.

The SENIEUR protocol and the efficacy of hepatitis B vaccination in healthy elderly persons by age, gender, and vaccine route.

BACKGROUND: Reduced response to hepatitis B vaccines is associated with aging, confounding and comorbid conditions, as well as inadvertent subcutaneous (SC) inoculation. We hypothesized that the antibody and T cell-mediated immune responses (T-CMI) of elderly adults to a vaccine intended for intramuscular (IM) administration would be attenuated when deposited into SC fat, independent of confounding conditions. RESULTS: Fifty-two healthy, community dwelling elderly adults (65-82 years), seronegative for HBV, were enrolled in the SENIEUR protocol as a strictly healthy population. These seniors were randomized to receive a licensed alum-adjuvanted recombinant HBV vaccine either SC or IM, with the inoculum site verified by imaging. The response rates, defined as hepatitis B surface antibodies (HBsAb) ≥10 IU/L, were significantly lower in the elderly than in young adults, a group of 12, healthy, 21-34-year-old volunteers. Moreover, elderly participants who received the vaccine IM were significantly more likely to be responders than those immunized SC (54% versus 16%, p = 0.008). The low seroconversion rate in the IM group progressively declined with increasing age, and responders had significantly lower HBsAb titers and limited isotype responses. Moreover, T-CMI (proliferation and cytokine production) were significantly reduced in both percentage of responders and intensity of the response for both Th1 and Th2 subsets in the elderly. CONCLUSIONS: Our data demonstrate the blunted immunogenicity of SC inoculation as measured by peak titers and response rates. Further, the qualitative and quantitative deficits in B- and T-CMI responses to primary alum adjuvanted protein antigens persisted even in strictly healthy elderly populations with verified IM placement compared to younger populations. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov, NCT04162223. Registered 14 November 2019. Retrospectively registered.

Inverse correlation between daily outdoor temperature and blood pressure in six US cities.

This study aims to evaluate the relationship between mean outdoor temperature and mean daily blood pressure (BP) and heart rate (HR) among six, large, geographically and climatically diverse US cities. We collected BP and HR data from Higi stations, located in a wide range of neighborhood grocery stores and retail pharmacies, from six US cities (Houston, Los Angeles, Miami, Boise, Chicago, and New York City). Outdoor daily temperature data were collected from the National Centers for Environmental Information's database. Pearson's correlation was used to assess the linear relationship between mean daily outdoor temperature and mean daily BP and HR for each city from May 2016 through April 2017. A total of 2 140 626 BP and HR readings were recorded in the six study cities. Mean outdoor temperature was inversely correlated with both mean daily average systolic (r=-0.69, P<0.0001) and diastolic (r=-0.71; P<0.0001) BPs, but not HR (r<0.0001, P=0.48). We also found that temperature change had a larger impact on BP in equatorial climates such as Miami compared with colder and more temperature variable cities like Chicago and Boise. Previous studies have found that BP varies seasonally, but few have looked at the impact of daily temperature on both BP and HR changes. Our study is one of the largest and most climatically diverse populations ever looking at this relationship. Our results suggest that temperature, and perhaps geography, should play a role in tailoring individualized evaluation and treatment for hypertensive diseases.

Implications of surface-rendered facial CT images in patient privacy.

OBJECTIVE: Three-dimensional and multiplanar reconstruction of CT images has become routine in diagnostic imaging. The technology also facilitates surface reconstruction, in which facial features and, as a result, patient identity may be recognized, leading to risk of violations of patient privacy rights. The purpose of this study was to assess whether volunteer viewers can recognize faces on 3D reconstructed images as specific patients. SUBJECTS AND METHODS: A total of 328 participants were included: 29 patients underwent clinically indicated CT of the maxillofacial sinuses or cerebral vasculature and were also photographed (group A); 150 patients volunteered to have their faces photographed (group B); and 149 observers reviewed the images. Surface-reconstructed 3D images of group A were generated from CT data, and digital photographs of both groups A and B were acquired for a total of 179 facial photographs. Image reviewers were recruited with a web-based questionnaire that required observers to match surface-reconstructed images generated from CT data with randomized digital photographs from among the 179 photographs. Data analyses were performed to determine the ability of observers to successfully match surface-reconstructed images with facial photographs. RESULTS: The overall accuracy among the image observers was approximately 61%. No significant differences were found with regard to sex, age, or ethnicity and accuracy of image observers. CONCLUSION: Image reviewers were relatively poor at even side-by-side matching of patient photographs with 3D surface-reconstructed images. This finding suggests that successful identification of patients using surface-rendered faces may be a relatively difficult task for observers.

The relative effect of vendor variability in CT perfusion results: a method comparison study.

OBJECTIVE: There are known interoperator, intraoperator, and intervendor software differences that can influence the reproducibility of quantitative CT perfusion values. The purpose of this study was to determine the relative impact of operator and software differences in CT perfusion variability. MATERIALS AND METHODS: CT perfusion imaging data were selected for 11 patients evaluated for suspected ischemic stroke. Three radiologists each independently postprocessed the source data twice, using four different vendor software applications. Results for cerebral blood volume (CBV), cerebral blood flow (CBF), and mean transit time (MTT) were recorded for the lentiform nuclei in both hemispheres. Repeated variables multivariate analysis of variance was used to assess differences in the means of CBV, CBF, and MTT. Bland-Altman analysis was used to assess agreement between pairs of vendors, readers, and read times. RESULTS: Choice of vendor software, but not interoperator or intraoperator disagreement, was associated with significant variability (p < 0.001) in CBV, CBF, and MTT. The mean difference in CT perfusion values was greater for pairs of vendors than for pairs of operators. CONCLUSION: Different vendor software applications do not generate quantitative perfusion results equivalently. Intervendor difference is, by far, the largest cause of variability in perfusion results relative to interoperator and intraoperator difference. Caution should be exercised when interpreting quantitative CT perfusion results because these values may vary considerably depending on the postprocessing software.

Detection of cervical spine fracture on computed radiography images a monitor resolution study.

RATIONALE AND OBJECTIVES: The purpose of this study was to evaluate the diagnostic accuracy of radiologists using monochrome medical-grade 5 megapixel (MP), 3 MP, 2 MP, and 1 MP displays for the detection of cervical fractures on cervical radiographs, while controlling factors such as luminance and ambient conditions. MATERIALS AND METHODS: Institutional review board approval was obtained. Two hundred lateral cervical computed radiography images, 97 with fractures, were randomly displayed on 5-MP, 3-MP, 2-MP, or 1-MP liquid crystal displays (LCDs) for a total of 450 interpretations per display. These radiographs were presented in eight sessions, each with 25 radiographs, to nine readers. The reference standard for all cases was computed tomography. Ambient lighting, monitor luminance, and gamma were controlled throughout the study. Measures included receiver operator characteristic areas under the curve (AUC), sensitivity, specificity, and accuracy, mean elapsed time by display, and mean confidence level by display. One way analysis of variance was performed. Results were considered to be significant at an alpha level of 0.05. RESULTS: AUCs were 0.76 (95% CI, 0.72-0.80) for the 1 MP, 0.80 (95% CI, 0.76-0.84) for the 2 MP, 0.77 (95% CI, 0.73-0.81) for the 3 MP, and 0.76 (95% CI, 0.72-0.80) for the 5 MP medical grade LCDs. There was no significant difference in the AUCs (P values between .0651 and .8693), confidence (P = .158), or interpretation times (P = .751). CONCLUSION: When controlling factors such as luminance and ambient light, a difference in accuracy in the detection of cervical fractures by resolution could not be detected when using medical-grade displays. Interpretation time and confidence were also not affected by resolution.

Ontology-assisted analysis of Web queries to determine the knowledge radiologists seek.

Radiologists frequently search the Web to find information they need to improve their practice, and knowing the types of information they seek could be useful for evaluating Web resources. Our goal was to develop an automated method to categorize unstructured user queries using a controlled terminology and to infer the type of information users seek. We obtained the query logs from two commonly used Web resources for radiology. We created a computer algorithm to associate RadLex-controlled vocabulary terms with the user queries. Using the RadLex hierarchy, we determined the high-level category associated with each RadLex term to infer the type of information users were seeking. To test the hypothesis that the term category assignments to user queries are non-random, we compared the distributions of the term categories in RadLex with those in user queries using the chi square test. Of the 29,669 unique search terms found in user queries, 15,445 (52%) could be mapped to one or more RadLex terms by our algorithm. Each query contained an average of one to two RadLex terms, and the dominant categories of RadLex terms in user queries were diseases and anatomy. While the same types of RadLex terms were predominant in both RadLex itself and user queries, the distribution of types of terms in user queries and RadLex were significantly different (p < 0.0001). We conclude that RadLex can enable processing and categorization of user queries of Web resources and enable understanding the types of information users seek from radiology knowledge resources on the Web.

Utilization of a radiology-centric search engine.

Internet-based search engines have become a significant component of medical practice. Physicians increasingly rely on information available from search engines as a means to improve patient care, provide better education, and enhance research. Specialized search engines have emerged to more efficiently meet the needs of physicians. Details about the ways in which radiologists utilize search engines have not been documented. The authors categorized every 25th search query in a radiology-centric vertical search engine by radiologic subspecialty, imaging modality, geographic location of access, time of day, use of abbreviations, misspellings, and search language. Musculoskeletal and neurologic imagings were the most frequently searched subspecialties. The least frequently searched were breast imaging, pediatric imaging, and nuclear medicine. Magnetic resonance imaging and computed tomography were the most frequently searched modalities. A majority of searches were initiated in North America, but all continents were represented. Searches occurred 24 h/day in converted local times, with a majority occurring during the normal business day. Misspellings and abbreviations were common. Almost all searches were performed in English. Search engine utilization trends are likely to mirror trends in diagnostic imaging in the region from which searches originate. Internet searching appears to function as a real-time clinical decision-making tool, a research tool, and an educational resource. A more thorough understanding of search utilization patterns can be obtained by analyzing phrases as actually entered as well as the geographic location and time of origination. This knowledge may contribute to the development of more efficient and personalized search engines.

Effect of ambient sound masking on the accuracy of computerized speech recognition.

PURPOSE: To evaluate the direct effect that sound masking has on computerized speech recognition (SR) accuracy in the digital reading room while eliminating the Lombard effect. MATERIALS AND METHODS: This study complies with HIPAA requirements, and the institutional review board determined that approval was not required; informed consent was obtained. Ten radiologists digitally recorded 20 selected reports. Recorded reports were transcribed by using a commercial SR system at sound-masking levels 1-4, representing lowest to highest A-weighted sound pressure measurements in decibels. Dictated reports were compared with original reports to determine numbers of errors. A repeated-measures analysis of variance was used for overall comparison of mean percentage of transcription inaccuracies across sound-masking levels, and paired t tests were used to compare each sound-masking level to the baseline. RESULTS: Mean percentage of transcription inaccuracies at baseline was 11.6% (range, 6.3%-26.1%). Mean percentages of transcription inaccuracies at sound-masking levels 1-4 were 11.3%, 12.3%, 13.0%, and 13.6%, respectively. Mean percentages of transcription inaccuracies differed across all sound-masking levels (P < .001) but not between baseline and sound-masking level 1 (P = .313). Mean percentages of transcription inaccuracies at sound-masking levels 2-4 were each significantly higher than at baseline (P < .01 for each). CONCLUSION: Low-level sound masking provided slightly but not significantly improved SR accuracy, whereas higher levels decreased transcription accuracy. Appropriate levels of sound masking in reading room environments may decrease the negative effect of ambient noise without a deleterious effect on SR accuracy.

Vision and quality in the digital imaging environment: how much does the visual acuity of radiologists vary at an intermediate distance?

OBJECTIVE: The purpose of this study was to examine the intermediate-distance visual acuity of a cross section of radiologists and to identify variation in visual acuity during a typical workday. SUBJECTS AND METHODS: Forty-eight radiologists completed a brief survey before undergoing visual acuity testing, with corrective lenses if routinely used, at three times of the day. Testing was performed with modified versions of a U.S. Federal Aviation Administration visual acuity test instrument. RESULTS: The mean acuity of radiologists across all measurements was 20/15 (logarithm of the minimum angle of resolution [logMAR], -0.109 +/- 0.105 [SD]). Visual acuity ranged from 20/30 to 20/10 (logMAR, 0.176 to -0.301). Mean visual acuity in the morning session was approximately 20/16 (logMAR, -0.0856). This value was statistically significantly lower than the mean visual acuity in both the early afternoon (logMAR, -0.124; p = 0.003) and the late afternoon (logMAR, -0.118; p = 0.015), both of which were approximately 20/15. This change was within the expected test-retest variability of Snellen acuity measurements. CONCLUSION: Although a statistically significant difference was detected between the visual acuity of radiologists in the morning and acuity in other parts of the day, this difference was relatively modest and within previously published ranges of variability for similar visual acuity tests. It is unlikely that such variation in visual acuity among radiologists influences diagnostic performance. Not every radiologist had 20/20 vision, a few needed visual correction, and more than a few had not undergone a thorough eye examination for as many as 15 years before the study.

An automatic computer-aided detection system for meniscal tears on magnetic resonance images.

Knee-related injuries including meniscal tears are common in both young athletes and the aging population, and require accurate diagnosis and surgical intervention when appropriate. With proper techniques and radiologists' experienced skills, confidence in detection of meniscal tears can be quite high. This paper develops a novel computer-aided detection (CAD) diagnostic system for automatic detection of meniscal tears in the knee. Evaluation of this CAD system using an archived database of images from 40 individuals with suspected knee injuries indicates that the sensitivity and specificity of the proposed CAD system are 83.87% and 75.19%, respectively, compared to the mean sensitivity and specificity of 77.41% and 81.39%, respectively, obtained by experienced radiologists in routine diagnosis without using the CAD. The experimental results suggest that the developed CAD system has great potential and promise in automatic detection of both simple and complex meniscal tears of the knee.

Informatics in radiology: IHE teaching file and clinical trial export integration profile: functional examples.

The digital revolution in radiology introduced the need for electronic export of medical images. However, the current export process is complicated and time consuming. In response to this continued difficulty, the Integrating the Healthcare Enterprise (IHE) initiative published the Teaching File and Clinical Trial Export (TCE) integration profile. The IHE TCE profile describes a method for using existing standards to simplify the export of key medical images for education, research, and publication. This article reviews the authors' experience in implementing the TCE profile in the following three processes: (a) the retrieval of images for a typical teaching file application within a TCE-compliant picture archiving and communication system (PACS); (b) the export of images, independent of TCE compliance of the PACS, to a typical teaching file application; and (c) the TCE-compliant transfer of images for publication. These examples demonstrate methods with which the TCE profile can be implemented to ease the burden of collecting key medical images from the PACS.

Informatics in radiology: GridCAD: grid-based computer-aided detection system.

Grid computing-the use of a distributed network of electronic resources to cooperatively perform subsets of computationally intensive tasks-may help improve the speed and accuracy of radiologic image interpretation by enabling collaborative computer-based and human readings. GridCAD, a software application developed by using the National Cancer Institute Cancer Biomedical Informatics Grid architecture, implements the fundamental elements of grid computing and demonstrates the potential benefits of grid technology for medical imaging. It allows users to query local and remote image databases, view images, and simultaneously run multiple computer-assisted detection (CAD) algorithms on the images selected. The prototype CAD systems that are incorporated in the software application are designed for the detection of lung nodules on thoracic computed tomographic images. GridCAD displays the original full-resolution images with an overlay of nodule candidates detected by the CAD algorithms, by human observers, or by a combination of both types of readers. With an underlying framework that is computer platform independent and scalable to the task, the software application can support local and long-distance collaboration in both research and clinical practice through the efficient, secure, and reliable sharing of resources for image data mining, analysis, and archiving.

GridIMAGE: a novel use of grid computing to support interactive human and computer-assisted detection decision support.

This paper describes a Grid-aware image reviewing system (GridIMAGE) that allows practitioners to (a) select images from multiple geographically distributed digital imaging and communication in medicine (DICOM) servers, (b) send those images to a specified group of human readers and computer-assisted detection (CAD) algorithms, and (c) obtain and compare interpretations from human readers and CAD algorithms. The currently implemented system was developed using the National Cancer Institute caGrid infrastructure and is designed to support the identification of lung nodules on thoracic computed tomography. However, the infrastructure is general and can support any type of distributed review. caGrid data and analytical services are used to link DICOM image databases and CAD systems and to interact with human readers. Moreover, the service-oriented and distributed structure of the GridIMAGE framework enables a flexible system, which can be deployed in an institution (linking multiple DICOM servers and CAD algorithms) and in a Grid environment (linking the resources of collaborating research groups). GridIMAGE provides a framework that allows practitioners to obtain interpretations from one or more human readers or CAD algorithms. It also provides a mechanism to allow cooperative imaging groups to systematically perform image interpretation tasks associated with research protocols.