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.

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.

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.

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.

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.

COVID-19 Pandemic Impact on Decreased Imaging Utilization: A Single Institutional Experience.

RATIONALE AND OBJECTIVES: Predictive models and anecdotal articles suggest radiology practices were losing 50%-70% of their normal imaging volume during the COVID-19 pandemic. Using actual institutional data, we investigated the change in imaging utilization and revenue during this public health crisis. MATERIALS AND METHODS: Imaging performed within the 8-week span between March 8 and April 30, 2020 was categorized into the COVID-19 healthcare crisis timeframe. The first week of this date range and the 10 weeks prior were used to derive the normal practice expected volume. A rolling 7-day total value was used for volume tracking and comparison. Total imaging utilization was derived and organized by patient setting (outpatient, inpatient, emergency) and imaging modality (X-ray, CT, Mammography, MRI, Nuclear Medicine/PET, US). The three highest volume hospitals were analyzed. Revenue information was collected from the hospital billing system. RESULTS: System-wide imaging volume decreased by 55% between April 7 and 13, 2020. Outpatient exams decreased by 68% relative to normal practice. Emergency exams decreased by 48% and inpatient exams declined by 31%. Mammograms and nuclear medicine scans were the most affected modalities, decreasing by 93% and 61%, respectively. The main campus hospital experienced less relative imaging volume loss compared to the other smaller and outpatient-driven hospitals. At its lowest point, the technical component revenue from main campus imaging services demonstrated a 49% negative variance from normal practice. CONCLUSION: The trends and magnitude of the actual imaging utilization data presented will help inform evidence-based decisions for more accurate volume predictions, policy changes, and institutional preparedness for current and future pandemics.

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.

Decreased functional connectivity in the fronto-parietal network in children with mood disorders compared to children with dyslexia during rest: An fMRI study.

Background: The DSM-5 separates the diagnostic criteria for mood and behavioral disorders. Both types of disorders share neurocognitive deficits of executive function and reading difficulties in childhood. Children with dyslexia also have executive function deficits, revealing a role of executive function circuitry in reading. The aim of the current study is to determine whether there is a significant relationship of functional connectivity within the fronto-parietal and cingulo-opercular cognitive control networks to reading measures for children with mood disorders, behavioral disorders, dyslexia, and healthy controls (HC). Method: Behavioral reading measures of phonological awareness, decoding, and orthography were collected. Resting state fMRI data were collected, preprocessed, and then analyzed for functional connectivity. Differences in the reading measures were tested for significance among the groups. Global efficiency (GE) measures were also tested for correlation with reading measures in 40 children with various disorders and 17 HCs. Results: Significant differences were found between the four groups on all reading measures. Relative to HCs and children with mood disorders or behavior disorders, children with dyslexia as a primary diagnosis scored significantly lower on all three reading measures. Children with mood disorders scored significantly lower than controls on a test of phonological awareness. Phonological awareness deficits correlated with reduced resting state functional connectivity MRI (rsfcMRI) in the cingulo-opercular network for children with dyslexia. A significant difference was also found in fronto-parietal global efficiency in children with mood disorders relative to the other three groups. We also found a significant difference in cingulo-opercular global efficiency in children with mood disorders relative to the Dyslexia and Control groups. However, none of these differences correlate significantly with reading measures. Conclusions/significance: Reading difficulties involve abnormalities in different cognitive control networks in children with dyslexia compared to children with mood disorders. Findings of the current study suggest increased functional connectivity of one cognitive control network may compensate for reduced functional connectivity in the other network in children with mood disorders. These findings provide guidance to clinical professionals for design of interventions tailored for children suffering from reading difficulties originating from different pathologies.

Reading related white matter structures in adolescents are influenced more by dysregulation of emotion than behavior.

Mood disorders and behavioral are broad psychiatric diagnostic categories that have different symptoms and neurobiological mechanisms, but share some neurocognitive similarities, one of which is an elevated risk for reading deficit. Our aim was to determine the influence of mood versus behavioral dysregulation on reading ability and neural correlates supporting these skills in youth, using diffusion tensor imaging in 11- to 17-year-old children and youths with mood disorders or behavioral disorders and age-matched healthy controls. The three groups differed only in phonological processing and passage comprehension. Youth with mood disorders scored higher on the phonological test but had lower comprehension scores than children with behavioral disorders and controls; control participants scored the highest. Correlations between fractional anisotropy and phonological processing in the left Arcuate Fasciculus showed a significant difference between groups and were strongest in behavioral disorders, intermediate in mood disorders, and lowest in controls. Correlations between these measures in the left Inferior Longitudinal Fasciculus were significantly greater than in controls for mood but not for behavioral disorders. Youth with mood disorders share a deficit in the executive-limbic pathway (Arcuate Fasciculus) with behavioral-disordered youth, suggesting reduced capacity for engaging frontal regions for phonological processing or passage comprehension tasks and increased reliance on the ventral tract (e.g., the Inferior Longitudinal Fasciculus). The low passage comprehension scores in mood disorder may result from engaging the left hemisphere. Neural pathways for reading differ mainly in executive-limbic circuitry. This new insight may aid clinicians in providing appropriate intervention for each disorder.

Using machine learning and surface reconstruction to accurately differentiate different trajectories of mood and energy dysregulation in youth.

Difficulty regulating positive mood and energy is a feature that cuts across different pediatric psychiatric disorders. Yet, little is known regarding the neural mechanisms underlying different developmental trajectories of positive mood and energy regulation in youth. Recent studies indicate that machine learning techniques can help elucidate the role of neuroimaging measures in classifying individual subjects by specific symptom trajectory. Cortical thickness measures were extracted in sixty-eight anatomical regions covering the entire brain in 115 participants from the Longitudinal Assessment of Manic Symptoms (LAMS) study and 31 healthy comparison youth (12.5 y/o;-Male/Female = 15/16;-IQ = 104;-Right/Left handedness = 24/5). Using a combination of trajectories analyses, surface reconstruction, and machine learning techniques, the present study aims to identify the extent to which measures of cortical thickness can accurately distinguish youth with higher (n = 18) from those with lower (n = 34) trajectories of manic-like behaviors in a large sample of LAMS youth (n = 115; 13.6 y/o; M/F = 68/47, IQ = 100.1, R/L = 108/7). Machine learning analyses revealed that widespread cortical thickening in portions of the left dorsolateral prefrontal cortex, right inferior and middle temporal gyrus, bilateral precuneus, and bilateral paracentral gyri and cortical thinning in portions of the right dorsolateral prefrontal cortex, left ventrolateral prefrontal cortex, and right parahippocampal gyrus accurately differentiate (Area Under Curve = 0.89;p = 0.03) youth with different (higher vs lower) trajectories of positive mood and energy dysregulation over a period up to 5years, as measured by the Parent General Behavior Inventory-10 Item Mania Scale. Our findings suggest that specific patterns of cortical thickness may reflect transdiagnostic neural mechanisms associated with different temporal trajectories of positive mood and energy dysregulation in youth. This approach has potential to identify patterns of neural markers of future clinical course.

Longitudinal relationships among activity in attention redirection neural circuitry and symptom severity in youth.

BACKGROUND: Changes in neural circuitry function may be associated with longitudinal changes in psychiatric symptom severity. Identification of these relationships may aid in elucidating the neural basis of psychiatric symptom evolution over time. We aimed to distinguish these relationships using data from the Longitudinal Assessment of Manic Symptoms (LAMS) cohort. METHODS: Forty-one youth completed two study visits (mean=21.3 months). Elastic-net regression (Multiple response Gaussian family) identified emotional regulation neural circuitry that changed in association with changes in depression, mania, anxiety, affect lability, and positive mood and energy dysregulation, accounting for clinical and demographic variables. RESULTS: Non-zero coefficients between change in the above symptom measures and change in activity over the inter-scan interval were identified in right amygdala and left ventrolateral prefrontal cortex. Differing patterns of neural activity change were associated with changes in each of the above symptoms over time. Specifically, from Scan1 to Scan2, worsening affective lability and depression severity were associated with increased right amygdala and left ventrolateral prefrontal cortical activity. Worsening anxiety and positive mood and energy dysregulation were associated with decreased right amygdala and increased left ventrolateral prefrontal cortical activity. Worsening mania was associated with increased right amygdala and decreased left ventrolateral prefrontal cortical activity. These changes in neural activity between scans accounted for 13.6% of the variance; that is 25% of the total explained variance (39.6%) in these measures. CONCLUSIONS: Distinct neural mechanisms underlie changes in different mood and anxiety symptoms overtime.

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.

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.

Synchronized navigation of current and prior studies using image registration improves radiologist's efficiency.

PURPOSE: The purpose of this study was to investigate how the use of multi-modal rigid image registration integrated within a standard picture archiving and communication system affects the efficiency of a radiologist while performing routine interpretations of cases including prior examinations. METHODS: Six radiologists were recruited to read a set of cases (either 16 neuroradiology or 14 musculoskeletal cases) during two crossover reading sessions. Each radiologist read each case twice, one time with synchronized navigation, which enables spatial synchronization across examinations from different study dates, and one time without. Efficiency was evaluated based upon time to read a case and amount of scrolling while browsing a case using Wilcoxon signed rank test. RESULTS: Significant improvements in efficiency were found considering either all radiologists simultaneously, the two sections separately and the majority of individual radiologists for time to read and for amount of scrolling. The relative improvement for each individual radiologist ranged from 4 to 32% for time to read and from 14 to 38% for amount of scrolling. CONCLUSION: Image registration providing synchronized navigation across examinations from different study dates provides a tool that enables radiologists to work more efficiently while reading cases with one or more prior examinations.