Mediation of Successful Reperfusion Effect through Infarct Growth and Cerebral Edema: A Pooled, Patient-Level Analysis of EXTEND-IA Trials and SELECT Prospective Cohort.

OBJECTIVE: Reperfusion therapy is highly beneficial for ischemic stroke. Reduction in both infarct growth and edema are plausible mediators of clinical benefit with reperfusion. We aimed to quantify these mediators and their interrelationship. METHODS: In a pooled, patient-level analysis of the EXTEND-IA trials and SELECT study, we used a mediation analysis framework to quantify infarct growth and cerebral edema (midline shift) mediation effect on successful reperfusion (modified Treatment in Cerebral Ischemia ≥ 2b) association with functional outcome (modified Rankin Scale distribution). Furthermore, we evaluated an additional pathway to the original hypothesis, where infarct growth mediated successful reperfusion effect on midline shift. RESULTS: A total 542 of 665 (81.5%) eligible patients achieved successful reperfusion. Baseline clinical and imaging characteristics were largely similar between those achieving successful versus unsuccessful reperfusion. Median infarct growth was 12.3ml (interquartile range [IQR] = 1.8-48.4), and median midline shift was 0mm (IQR = 0-2.2). Of 249 (37%) demonstrating a midline shift of ≥1mm, median shift was 2.75mm (IQR = 1.89-4.21). Successful reperfusion was associated with reductions in both predefined mediators, infarct growth (ß = -1.19, 95% confidence interval [CI] = -1.51 to -0.88, p < 0.001) and midline shift (adjusted odds ratio = 0.36, 95% CI = 0.23-0.57, p < 0.001). Successful reperfusion association with improved functional outcome (adjusted common odds ratio [acOR] = 2.68, 95% CI = 1.86-3.88, p < 0.001) became insignificant (acOR = 1.39, 95% CI = 0.95-2.04, p = 0.094) when infarct growth and midline shift were added to the regression model. Infarct growth and midline shift explained 45% and 34% of successful reperfusion effect, respectively. Analysis considering an alternative hypothesis demonstrated consistent results. INTERPRETATION: In this mediation analysis from a pooled, patient-level cohort, a significant proportion (~80%) of successful reperfusion effect on functional outcome was mediated through reduction in infarct growth and cerebral edema. Further studies are required to confirm our findings, detect additional mediators to explain successful reperfusion residual effect, and identify novel therapeutic targets to further enhance reperfusion benefits. ANN NEUROL 2023;93:793-804.

Endovascular Thrombectomy for Large Ischemic Stroke Across Ischemic Injury and Penumbra Profiles.

Importance: Whether endovascular thrombectomy (EVT) efficacy for patients with acute ischemic stroke and large cores varies depending on the extent of ischemic injury is uncertain. Objective: To describe the relationship between imaging estimates of irreversibly injured brain (core) and at-risk regions (mismatch) and clinical outcomes and EVT treatment effect. Design, Setting, and Participants: An exploratory analysis of the SELECT2 trial, which randomized 352 adults (18-85 years) with acute ischemic stroke due to occlusion of the internal carotid or middle cerebral artery (M1 segment) and large ischemic core to EVT vs medical management (MM), across 31 global centers between October 2019 and September 2022. Intervention: EVT vs MM. Main Outcomes and Measures: Primary outcome was functional outcome-90-day mRS score (0, no symptoms, to 6, death) assessed by adjusted generalized OR (aGenOR; values >1 represent more favorable outcomes). Benefit of EVT vs MM was assessed across levels of ischemic injury defined by noncontrast CT using ASPECTS score and by the volume of brain with severely reduced blood flow on CT perfusion or restricted diffusion on MRI. Results: Among 352 patients randomized, 336 were analyzed (median age, 67 years; 139 [41.4%] female); of these, 168 (50%) were randomized to EVT, and 2 additional crossover MM patients received EVT. In an ordinal analysis of mRS at 90 days, EVT improved functional outcomes compared with MM within ASPECTS categories of 3 (aGenOR, 1.71 [95% CI, 1.04-2.81]), 4 (aGenOR, 2.01 [95% CI, 1.19-3.40]), and 5 (aGenOR, 1.85 [95% CI, 1.22-2.79]). Across strata for CT perfusion/MRI ischemic core volumes, aGenOR for EVT vs MM was 1.63 (95% CI, 1.23-2.16) for volumes ≥70 mL, 1.41 (95% CI, 0.99-2.02) for ≥100 mL, and 1.47 (95% CI, 0.84-2.56) for ≥150 mL. In the EVT group, outcomes worsened as ASPECTS decreased (aGenOR, 0.91 [95% CI, 0.82-1.00] per 1-point decrease) and as CT perfusion/MRI ischemic core volume increased (aGenOR, 0.92 [95% CI, 0.89-0.95] per 10-mL increase). No heterogeneity of EVT treatment effect was observed with or without mismatch, although few patients without mismatch were enrolled. Conclusion and Relevance: In this exploratory analysis of a randomized clinical trial of patients with extensive ischemic stroke, EVT improved clinical outcomes across a wide spectrum of infarct volumes, although enrollment of patients with minimal penumbra volume was low. In EVT-treated patients, clinical outcomes worsened as presenting ischemic injury estimates increased. Trial Registration: ClinicalTrials.gov Identifier: NCT03876457.

Novel 3D magnetic resonance fingerprinting radiomics in adult brain tumors: a feasibility study.

OBJECTIVES: To test the feasibility of using 3D MRF maps with radiomics analysis and machine learning in the characterization of adult brain intra-axial neoplasms. METHODS: 3D MRF acquisition was performed on 78 patients with newly diagnosed brain tumors including 33 glioblastomas (grade IV), 6 grade III gliomas, 12 grade II gliomas, and 27 patients with brain metastases. Regions of enhancing tumor, non-enhancing tumor, and peritumoral edema were segmented and radiomics analysis with gray-level co-occurrence matrices and gray-level run-length matrices was performed. Statistical analysis was performed to identify features capable of differentiating tumors based on type, grade, and isocitrate dehydrogenase (IDH1) status. Receiver operating curve analysis was performed and the area under the curve (AUC) was calculated for tumor classification and grading. For gliomas, Kaplan-Meier analysis for overall survival was performed using MRF T1 features from enhancing tumor region. RESULTS: Multiple MRF T1 and T2 features from enhancing tumor region were capable of differentiating glioblastomas from brain metastases. Although no differences were identified between grade 2 and grade 3 gliomas, differentiation between grade 2 and grade 4 gliomas as well as between grade 3 and grade 4 gliomas was achieved. MRF radiomics features were also able to differentiate IDH1 mutant from the wild-type gliomas. Radiomics T1 features for enhancing tumor region in gliomas correlated to overall survival (p < 0.05). CONCLUSION: Radiomics analysis of 3D MRF maps allows differentiating glioblastomas from metastases and is capable of differentiating glioblastomas from metastases and characterizing gliomas based on grade, IDH1 status, and survival. KEY POINTS: • 3D MRF data analysis using radiomics offers novel tissue characterization of brain tumors. • 3D MRF with radiomics offers glioma characterization based on grade, IDH1 status, and overall patient survival.

Implementing a Streamlined Radiology Workflow to Close the Loop on Incidental Imaging Findings in the Emergency Department.

Actionable incidental findings (AIFs) are common imaging findings unrelated to the clinical indication for the imaging test for which follow-up is recommended. Increasing utilization of imaging in the emergency department (ED) in recent years has resulted in more patients with AIFs. When these findings are not properly communicated and followed up upon, there is harm to the patient's health outcome as well as possible increased financial costs for the patient, the health system, and potential litigation. Tracking these findings can be difficult, especially so in a large health system. In this report, we detail our experience implementing a closed-loop AIF program within the ED of 11 satellite hospitals of a large academic health system. Our new workflow streamlined radiologist reporting of AIFs through system macros and by using a standardized form integrated into the dictation software. Upon completion of the form, an automatic email is sent to a dedicated nurse navigator who documented the findings and closed the loop by coordinating follow-up imaging or clinic visits with patients, primary care providers, and specialists. Through the new workflow, a total of 1207 incidental finding reports have been submitted from July 2021 to May 2022. The vast majority of AIFs were identified on CT, and the most common categories included lung nodules, pancreas lesions, liver lesions, and other potentially cancerous lesions. At least 10 new cancers have been detected. We hope this report can help guide other health systems in the design of a closed-loop incidental findings program.

Collaborative Development of a PACS-Integrated Quality Control Dashboard: a Single Institutional Experience.

Regular communication between technologists and radiologists is necessary for maintaining optimal diagnostic image quality throughout a radiology practice. In a large hospital system with multiple sites, this task becomes increasingly difficult without simultaneously causing significant disruptions in the clinical workflow and decreased throughput. Thus, establishing a system for quality control reporting that enables effective communication in a seamless and convenient manner is imperative. In this report, we describe the development of a new integrated system, in collaboration with our PACS vendor, with tools that allow for instant reporting of quality errors and dashboards providing real-time up-to-date quality data across our hospital system, directly accessible from PACS. To date, 8,167 quality reports have been logged in our new system with roughly 355 submissions per month. Early user engagement and consensus feedback among radiologists and technologists have been positive suggesting an overall improvement from prior systems. We hope this report can help inform other radiology enterprises seeking to improve quality control reporting within their clinical practice.

Assessing Telehealth Through the Lens of the Provider: Considerations for the Post-COVID-19 Era.

Introduction: Following the coronavirus disease (COVID-19) pandemic restrictions, many health care systems turned to telehealth as an alternative to in-person care. Current literature describes sustained patient satisfaction levels with virtual care throughout the pandemic era. However, provider opinions on the transforming landscape are largely unknown. Objectives: The aim of this study is to better understand provider intentions and limitations to telehealth adoption, along with preferences by various specialties and in various settings. Methods: A mixed-methods study design was used. An attitudinal survey was sent to 2,633 health care providers at a large, quaternary, integrated health system. The survey collected deidentified quantitative and qualitative data on factors influencing provider use, satisfaction, and concerns with telehealth during and after the initial pandemic-era restrictions. Results: Five hundred eighteen providers participated in the survey. Utilization of telehealth was largely motivated by (1) improving patient access (mean 29.3%; range 28-31.6%) and (2) patient interest (mean 23%; range 17.1-28.8%). Barriers included (1) technology limitations (mean 16.1%; range 12.4-23.8%) and (2) reimbursement uncertainties (mean 15.2%; range 4.8-18.8%). Preference for virtual care was reported to be highest in ambulatory settings, including direct-to-patient care and outpatient care. Discussion: Provider preference for telehealth, regardless of specialty or health care setting, revolves around a consumer-centric care delivery model, with increased access to care being a central theme. While provider values are patient oriented, this study found that concerns included connectivity, quality, and patient privacy. Amid changing care standards and regulations, provider preference is supportive of virtual care platforms, both now and postpandemic.

Magnetic resonance fingerprinting: an overview.

Magnetic resonance fingerprinting (MRF) is an evolving quantitative MRI framework consisting of unique data acquisition, processing, visualization, and interpretation steps. MRF is capable of simultaneously producing multiple high-resolution property maps including T1, T2, M0, ADC, and T2* measurements. While a relatively new technology, MRF has undergone rapid development for a variety of clinical applications from brain tumor characterization and epilepsy imaging to characterization of prostate cancer, cardiac imaging, among others. This paper will provide a brief overview of current state of MRF technology including highlights of technical and clinical advances. We will conclude with a brief discussion of the challenges that need to be overcome to establish MRF as a quantitative imaging biomarker.

Radiomic analysis of magnetic resonance fingerprinting in adult brain tumors.

PURPOSE: This is a radiomics study investigating the ability of texture analysis of MRF maps to improve differentiation between intra-axial adult brain tumors and to predict survival in the glioblastoma cohort. METHODS: Magnetic resonance fingerprinting (MRF) acquisition was performed on 31 patients across 3 groups: 17 glioblastomas, 6 low-grade gliomas, and 8 metastases. Using regions of interest for the solid tumor and peritumoral white matter on T1 and T2 maps, second-order texture features were calculated from gray-level co-occurrence matrices and gray-level run length matrices. Selected features were compared across the three tumor groups using Wilcoxon rank-sum test. Receiver operating characteristic curve analysis was performed for each feature. Kaplan-Meier method was used for survival analysis with log rank tests. RESULTS: Low-grade gliomas and glioblastomas had significantly higher run percentage, run entropy, and information measure of correlation 1 on T1 than metastases (p < 0.017). The best separation of all three tumor types was seen utilizing inverse difference normalized and homogeneity values for peritumoral white matter in both T1 and T2 maps (p < 0.017). In solid tumor T2 maps, lower values in entropy and higher values of maximum probability and high-gray run emphasis were associated with longer survival in glioblastoma patients (p < 0.05). Several texture features were associated with longer survival in glioblastoma patients on peritumoral white matter T1 maps (p < 0.05). CONCLUSION: Texture analysis of MRF-derived maps can improve our ability to differentiate common adult brain tumors by characterizing tumor heterogeneity, and may have a role in predicting outcomes in patients with glioblastoma.

Quantifying the decrease in emergency department imaging utilization during the COVID-19 pandemic at a multicenter healthcare system in Ohio.

PURPOSE: To illustrate the change in emergency department (ED) imaging utilization at a multicenter health system in the state of Ohio during the COVID-19 pandemic. METHODS: A retrospective observational study was conducted assessing ED imaging volumes between March 1, 2020, and May 11, 2020, during the COVID-19 crisis. A rolling 7-day total value was used for volume tracking and comparison. Total imaging utilization in the ED was compared with new COVID-19 cases in our region. Utilization was first categorized by modality and then by plain films and computed tomography (CT) scans grouped by body part. CT imaging of the chest was specifically investigated by assessing both CT chest only exams and CT chest, abdomen, and pelvis (C/A/P) exams. Ultimately, matching pair-wise statistical analysis of exam volumes was performed to assess significance of volume change. RESULTS: Our multicenter health system experienced a 46% drop in imaging utilization (p < 0.0001) during the pandemic. Matching pair-wise analysis showed a statistically significant volume decrease by each modality and body part. The exceptions were non-contrast chest CT, which increased (p = 0.0053), and non-trauma C/A/P CT, which did not show a statistically significant volume change (p = 0.0633). CONCLUSION: ED imaging utilization trends revealed through actual health system data will help inform evidence-based decisions for more accurate volume predictions and therefore institutional preparedness for current and future pandemics.

Magnetic resonance fingerprinting.

Magnetic resonance is an exceptionally powerful and versatile measurement technique. The basic structure of a magnetic resonance experiment has remained largely unchanged for almost 50 years, being mainly restricted to the qualitative probing of only a limited set of the properties that can in principle be accessed by this technique. Here we introduce an approach to data acquisition, post-processing and visualization--which we term 'magnetic resonance fingerprinting' (MRF)--that permits the simultaneous non-invasive quantification of multiple important properties of a material or tissue. MRF thus provides an alternative way to quantitatively detect and analyse complex changes that can represent physical alterations of a substance or early indicators of disease. MRF can also be used to identify the presence of a specific target material or tissue, which will increase the sensitivity, specificity and speed of a magnetic resonance study, and potentially lead to new diagnostic testing methodologies. When paired with an appropriate pattern-recognition algorithm, MRF inherently suppresses measurement errors and can thus improve measurement accuracy.

Magnetic Resonance Fingerprinting to Characterize Childhood and Young Adult Brain Tumors.

OBJECT: Magnetic resonance fingerprinting (MRF) allows rapid, simultaneous mapping of T1 and T2 relaxation times and may be an important diagnostic tool to measure tissue characteristics in pediatric brain tumors. We examined children and young adults with primary brain tumors to determine whether MRF can discriminate tumor from normal-appearing white matter and distinguish tumor grade. METHODS: MRF was performed in 23 patients (14 children and 9 young adults) with brain tumors (19 low-grade glioma, 4 high-grade tumors). T1 and T2 values were recorded in regions of solid tumor (ST), peritumoral white matter (PWM), and contralateral white matter (CWM). Nonparametric tests were used for comparison between groups and regions. RESULTS: Median scan time for MRF and a sequence for tumor localization was 11 min. MRF-derived T1 and T2 values distinguished ST from CWM (T1: 1,444 ± 254 ms vs. 938 ± 96 ms, p = 0.0002; T2: 61 ± 22 ms vs. 38 ± 9 ms, p = 0.0003) and separated high-grade tumors from low-grade tumors (T1: 1,863 ± 70 ms vs. 1,355 ± 187 ms, p = 0.007; T2: 90 ± 13 ms vs. 56 ± 19 ms, p = 0.013). PWM was distinct from CWM (T1: 1,261 ± 359 ms vs. 933 ± 104 ms, p = 0.0008; T2: 65 ± 51 ms vs. 38 ± 8 ms, p = 0.008), as well as from tumor (T1: 1,261 ± 371 ms vs. 1,462 ± 248 ms, p = 0.047). CONCLUSIONS: MRF is a fast sequence that can rapidly distinguish important tissue components in pediatric brain tumor patients. MRF-derived T1 and T2 distinguished tumor from normal-appearing white matter, differentiated tumor grade, and found abnormalities in peritumoral regions. MRF may be useful for rapid quantitative measurement of tissue characteristics and distinguish tumor grade in children and young adults with brain tumors.

Implementation and Benefits of a Vendor-Neutral Archive and Enterprise-Imaging Management System in an Integrated Delivery Network.

The use of digital imaging has substantially grown in recent decades, in traditional services, new specialties, and departments. The need to share these data among departments and caregivers necessitated central archiving systems that are able to communicate with various viewing applications and electronic medical records. This promoted the development of modern vendor neutral archive (VNA) systems. The need to aggregate and share imaging data from various departments promoted the development of enterprise-imaging (EI) solutions that replace departmental silos of data with central healthcare enterprise databases. To describe the implementation process of a VNA-EI solution in a large health system and its outcomes. We review the background of VNA and EI solutions development and describe the characteristics and advantages of such systems. We then describe our experience in implementation of these solutions in a large integrated healthcare delivery network in northeast Ohio. We then present the process, challenges, costs, advantages, and outcomes of such implementation. The VNA and EI solution was launched in December 2015 and is still ongoing. It currently includes 54 radiology and 26 cardiology sites affiliated with the University Hospitals health system. This process was associated with more than 10% cost savings, 30% reduction in storage costs, superior support for disaster recovery, and 80% decrease in unscheduled outages. All these were achieved despite a 120% increase in archive retrieval needs and a 40% growth in image production. Implementation of a VNA and EI solution was successful and resulted in numerous measurable and qualitative improvements in a large and growing health system.

Radiologists' Variation of Time to Read Across Different Procedure Types.

The workload of US radiologists has increased over the past two decades as measured through total annual relative value units (RVUs). This increase in RVUs generated suggests that radiologists' productivity has increased. However, true productivity (output unit per input unit; RVU per time) is at large unknown since actual time required to interpret and report a case is rarely recorded. In this study, we analyzed how the time to read a case varies between radiologists over a set of different procedure types by retrospectively extracting reading times from PACS usage logs. Specifically, we tested two hypotheses that; i) relative variation in time to read per procedure type increases as the median time to read a procedure type increases, and ii) relative rankings in terms of median reading speed for individual radiologists are consistent across different procedure types. The results that, i) a correlation of -0.25 between the coefficient of variation and median time to read and ii) that only 12 out of 46 radiologists had consistent rankings in terms of time to read across different procedure types, show both hypotheses to be without support. The results show that workload distribution will not follow any general rule for a radiologist across all procedures or a general rule for a specific procedure across many readers. Rather the findings suggest that improved overall practice efficiency can be achieved only by taking into account radiologists' individual productivity per procedure type when distributing unread cases.

Detection and Labeling of Vertebrae in MR Images Using Deep Learning with Clinical Annotations as Training Data.

The purpose of this study was to investigate the potential of using clinically provided spine label annotations stored in a single institution image archive as training data for deep learning-based vertebral detection and labeling pipelines. Lumbar and cervical magnetic resonance imaging cases with annotated spine labels were identified and exported from an image archive. Two separate pipelines were configured and trained for lumbar and cervical cases respectively, using the same setup with convolutional neural networks for detection and parts-based graphical models to label the vertebrae. The detection sensitivity, precision and accuracy rates ranged between 99.1-99.8, 99.6-100, and 98.8-99.8% respectively, the average localization error ranges were 1.18-1.24 and 2.38-2.60 mm for cervical and lumbar cases respectively, and with a labeling accuracy of 96.0-97.0%. Failed labeling results typically involved failed S1 detections or missed vertebrae that were not fully visible on the image. These results show that clinically annotated image data from one image archive is sufficient to train a deep learning-based pipeline for accurate detection and labeling of MR images depicting the spine. Further, these results support using deep learning to assist radiologists in their work by providing highly accurate labels that only require rapid confirmation.

Successful endovascular management of venous sinus thrombosis complicating trans-labyrinthine removal of vestibular schwanomma.

Cerebral venous sinus thrombosis (CVST) is a rare complication of surgical treatment of vestibular schwanomma. We present a rare case of extensive venous sinus thrombosis after trans-labyrinthine approach that was refractory to systemic anti-coagulation. Mechanical aspiration thrombectomy was utilized to re-canalize the venous sinuses and resulted in successful resolution of neurological symptoms. Indications of utilizing endovascular approaches are discussed that will enable skull base surgeons to address this uncommon yet potentially fatal complication.

Online Error Reporting for Managing Quality Control Within Radiology.

Information technology systems within health care, such as picture archiving and communication system (PACS) in radiology, can have a positive impact on production but can also risk compromising quality. The widespread use of PACS has removed the previous feedback loop between radiologists and technologists. Instead of direct communication of quality discrepancies found for an examination, the radiologist submitted a paper-based quality-control report. A web-based issue-reporting tool can help restore some of the feedback loop and also provide possibilities for more detailed analysis of submitted errors. The purpose of this study was to evaluate the hypothesis that data from use of an online error reporting software for quality control can focus our efforts within our department. For the 372,258 radiologic examinations conducted during the 6-month period study, 930 errors (390 exam protocol, 390 exam validation, and 150 exam technique) were submitted, corresponding to an error rate of 0.25 %. Within the category exam protocol, technologist documentation had the highest number of submitted errors in ultrasonography (77 errors [44 %]), while imaging protocol errors were the highest subtype error for computed tomography modality (35 errors [18 %]). Positioning and incorrect accession had the highest errors in the exam technique and exam validation error category, respectively, for nearly all of the modalities. An error rate less than 1 % could signify a system with a very high quality; however, a more likely explanation is that not all errors were detected or reported. Furthermore, staff reception of the error reporting system could also affect the reporting rate.

Analyzing PACS Usage Patterns by Means of Process Mining: Steps Toward a More Detailed Workflow Analysis in Radiology.

In this paper, statistical analysis and techniques from process mining are employed to analyze interaction patterns originating from radiologists reading medical images in a picture archiving and communication system (PACS). Event logs from 1 week of data, corresponding to 567 cases of single-view chest radiographs read by 14 radiologists, were analyzed. Statistical analysis showed that the numbers of commands and command types used by the radiologists per case only have a slightly positive correlation with the time to read a case (0.31 and 0.55, respectively). Further, one way ANOVA showed that the factors time of day, radiologist and specialty were significant for the number of commands per case, whereas radiologist was also significant for the number of command types, but with no significance of any of the factors on time to read. Applying process mining to the event logs of all users showed that a seemingly "simple" examination (single-view chest radiographs) can be associated with a highly complex interaction process. However, repeating the process discovery on each individual radiologist revealed that the initially discovered complex interaction process consists of one group of radiologists with individually well-structured interaction processes and a second smaller group of users with progressively more complex usage patterns. Future research will focus on metrics to describe derived interaction processes in order to investigate if one set of interaction patterns can be considered as more efficient than another set when reading radiological images in a PACS.

Factors Affecting Radiologist's PACS Usage.

The purpose of this study was to determine if any of the factors radiologist, examination category, time of week, and week effect PACS usage, with PACS usage defined as the sequential order of computer commands issued by a radiologist in a PACS during interpretation and dictation. We initially hypothesized that only radiologist and examination category would have significant effects on PACS usage. Command logs covering 8 weeks of PACS usage were analyzed. For each command trace (describing performed activities of an attending radiologist interpreting a single examination), the PACS usage variables number of commands, number of command classes, bigram repetitiveness, and time to read were extracted. Generalized linear models were used to determine the significance of the factors on the PACS usage variables. The statistical results confirmed the initial hypothesis that radiologist and examination category affect PACS usage and that the factors week and time of week to a large extent have no significant effect. As such, this work provides direction for continued efforts to analyze system data to better understand PACS utilization, which in turn can provide input to enable optimal utilization and configuration of corresponding systems. These continued efforts were, in this work, exemplified by a more detailed analysis using PACS usage profiles, which revealed insights directly applicable to improve PACS utilization through modified system configuration.

Device localization and dynamic scan plane selection using a wireless magnetic resonance imaging detector array.

PURPOSE: A prototype wireless guidance device using single sideband amplitude modulation (SSB) is presented for a 1.5T magnetic resonance imaging system. METHODS: The device contained three fiducial markers each mounted to an independent receiver coil equipped with wireless SSB technology. Acquiring orthogonal projections of these markers determined the position and orientation of the device, which was used to define the scan plane for a subsequent image acquisition. Device localization and scan plane update required approximately 30 ms, so it could be interleaved with high temporal resolution imaging. Since the wireless device is used for localization and does not require full imaging capability, the design of the SSB wireless system was simplified by allowing an asynchronous clock between the transmitter and receiver. RESULTS: When coupled to a high readout bandwidth, the error caused by the lack of a shared frequency reference was quantified to be less than one pixel (0.78 mm) in the projection acquisitions. Image guidance with the prototype was demonstrated with a phantom where a needle was successfully guided to a target and contrast was delivered. CONCLUSION: The feasibility of active tracking with a wireless detector array is demonstrated. Wireless arrays could be incorporated into devices to assist in image-guided procedures.

Design and implementation of disaster recovery and business continuity solution for radiology PACS.

In the digital era of radiology, picture archiving and communication system (PACS) has a pivotal role in retrieving and storing the images. Integration of PACS with all the health care information systems e.g., health information system, radiology information system, and electronic medical record has greatly improved access to patient data at anytime and anywhere throughout the entire enterprise. In such an integrated setting, seamless operation depends critically on maintaining data integrity and continuous access for all. Any failure in hardware or software could interrupt the workflow or data and consequently, would risk serious impact to patient care. Thus, any large-scale PACS now have an indispensable requirement to include deployment of a disaster recovery plan to ensure secure sources of data. This paper presents our experience with designing and implementing a disaster recovery and business continuity plan. The selected architecture with two servers in each site (local and disaster recovery (DR) site) provides four different scenarios to continue running and maintain end user service. The implemented DR at University Hospitals Health System now permits continuous access to the PACS application and its contained images for radiologists, other clinicians, and patients alike.