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.

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.

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.

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.

Amygdala-prefrontal cortical functional connectivity during implicit emotion processing differentiates youth with bipolar spectrum from youth with externalizing disorders.

OBJECTIVE: Both bipolar spectrum disorders (BPSD) and attention deficit hyperactivity disorder (ADHD) present with emotion-regulation deficits, but require different clinical management. We examined how the neurobiological underpinnings of emotion regulation might differentiate youth with BPSD versus ADHD (and healthy controls, HCs), specifically assessing functional connectivity (FxC) of amygdala-prefrontal circuitry during an implicit emotion processing task. METHODS: We scanned a subset of the Longitudinal Assessment of Manic Symptoms (LAMS) sample, a clinically recruited cohort with elevated behavioral and emotional dysregulation, and age/sex-ratio matched HCs. Our sample consisted of 22 youth with BPSD, 30 youth with ADHD/no BPSD, and 26 HCs. We used generalized psychophysiological interaction (gPPI) to calculate group differences to emerging emotional faces vs. morphing shapes in FxC between bilateral amygdala and ventral prefrontal cortex/anterior cingulate cortex. RESULTS: FxC between amygdala and left ventrolateral prefrontal cortex (VLPFC) in response to emotions vs. shapes differed by group (p=.05): while BPSD showed positive FxC (emotions>shapes), HC and ADHD showed inverse FxC (emotions

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.

State of Integration Between PACS and Other IT Systems: A National Survey of Academic Radiology Departments.

PURPOSE: The aim of this study was to investigate the state of integration between PACS and other IT systems relevant to radiologists' routine work across US academic radiology departments (ARDs). The results were intended to assess readiness for the ongoing transition to value-based health care by providing insights into currently challenging areas of integration but also areas associated with high levels of anticipated workflow efficiency improvements. METHODS: A cross-sectional survey was conducted using an online survey approved by the Society of Chairs of Academic Radiology Departments and sent to its members. Collected responses were analyzed with descriptive statistics and Fisher's exact tests. RESULTS: The response rate was 26% (34 of 132 members), and the respondents covered a large spectrum of ARDs considering location, size aspects, year of PACS introduction, and filmless production. Most notable findings included widespread high-level integration of PACS with dictation systems (>90%), low penetration of integration between PACS and critical notification systems (15%), and an overall better integration of PACS and radiology information systems (82%) than of PACS and electronic medical records (47%). CONCLUSIONS: Integration supporting radiologists' personal productivity is well spread among US ARDs, but as we transition into a value-based health care delivery model, there is a need to focus further integration efforts on systems with the greatest potential to document value in a patient-centric setting. Examples of such focus areas include integration of PACS and electronic medical records, adoption of vendor-neutral archives, and the use of workflow management systems.

Can Emotional and Behavioral Dysregulation in Youth Be Decoded from Functional Neuroimaging?

INTRODUCTION: High comorbidity among pediatric disorders characterized by behavioral and emotional dysregulation poses problems for diagnosis and treatment, and suggests that these disorders may be better conceptualized as dimensions of abnormal behaviors. Furthermore, identifying neuroimaging biomarkers related to dimensional measures of behavior may provide targets to guide individualized treatment. We aimed to use functional neuroimaging and pattern regression techniques to determine whether patterns of brain activity could accurately decode individual-level severity on a dimensional scale measuring behavioural and emotional dysregulation at two different time points. METHODS: A sample of fifty-seven youth (mean age: 14.5 years; 32 males) was selected from a multi-site study of youth with parent-reported behavioral and emotional dysregulation. Participants performed a block-design reward paradigm during functional Magnetic Resonance Imaging (fMRI). Pattern regression analyses consisted of Relevance Vector Regression (RVR) and two cross-validation strategies implemented in the Pattern Recognition for Neuroimaging toolbox (PRoNTo). Medication was treated as a binary confounding variable. Decoded and actual clinical scores were compared using Pearson's correlation coefficient (r) and mean squared error (MSE) to evaluate the models. Permutation test was applied to estimate significance levels. RESULTS: Relevance Vector Regression identified patterns of neural activity associated with symptoms of behavioral and emotional dysregulation at the initial study screen and close to the fMRI scanning session. The correlation and the mean squared error between actual and decoded symptoms were significant at the initial study screen and close to the fMRI scanning session. However, after controlling for potential medication effects, results remained significant only for decoding symptoms at the initial study screen. Neural regions with the highest contribution to the pattern regression model included cerebellum, sensory-motor and fronto-limbic areas. CONCLUSIONS: The combination of pattern regression models and neuroimaging can help to determine the severity of behavioral and emotional dysregulation in youth at different time points.

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.

Cervical dural arteriovenous malformation and large epidural venous varices in a rare adult presentation of congenital vascular bone syndrome.

61-year-old male presented with shortness of breath and chest pain. Workup for acute myocardial infarction was negative; however, computed tomography angiography visualized what a vascular malformation within the cervical spinal canal. Given the patient's history of Servelle-Martorell syndrome, neurovascular imaging was performed. We present the unique vascular findings of a right thyrocervical trunk-based dural arteriovenous malformation (dAVM) and a large epidural venous varix. The cervical dAVM induced intervertebral foraminal widening and polyradiculopathy, representing a rare adult case of congenital vascular bone syndrome.

White matter structure in youth with behavioral and emotional dysregulation disorders: a probabilistic tractographic study.

IMPORTANCE: Psychiatric disorders in youth characterized by behavioral and emotional dysregulation are often comorbid and difficult to distinguish. An alternative approach to conceptualizing these disorders is to move toward a diagnostic system based on underlying pathophysiologic processes that may cut across conventionally defined diagnoses. Neuroimaging techniques have potentials for the identification of these processes. OBJECTIVE: To determine whether diffusion imaging, a neuroimaging technique examining white matter (WM) structure, can identify neural correlates of emotional dysregulation in a sample of youth with different psychiatric disorders characterized by behavioral and emotional dysregulation. DESIGN, SETTING, AND PARTICIPANTS: Using global probabilistic tractography, we examined relationships between WM structure in key tracts in emotional regulation circuitry (ie, cingulum, uncinate fasciculus, and forceps minor) and (1) broader diagnostic categories of behavioral and emotional dysregulation disorders (DDs) and (2) symptom dimensions cutting across conventional diagnoses in 120 youth with behavioral and/or emotional DDs, a referred sample of the Longitudinal Assessment of Manic Symptoms (LAM) study. Thirty age- and sex-matched typically developing youth (control participants) were included. Multivariate multiple regression models were used. The study was conducted from July 1, 2010, to February 28, 2014. MAIN OUTCOMES AND MEASURES: Fractional anisotropy as well as axial and radial diffusivity were estimated and imported into a well-established statistical package. We hypothesized that (1) youth with emotional DDs and those with both behavioral and emotional DDs would show significantly lower fractional anisotropy compared with youth with behavioral DDs in these WM tracts and (2) that there would be significant inverse relationships between dimensional measures of affective symptom severity and fractional anisotropy in these tracts across all participants. RESULTS: Multivariate multiple regression analyses revealed decreased fractional anisotropy and decreased axial diffusivity within the uncinate fasciculus in youth with emotional DDs vs those with behavioral DDs, those with both DDs, and the controls (F6,160 = 2.4; P = .032; all pairwise comparisons, P < .002). In the same model, greater severity of manic symptoms was positively associated with higher fractional anisotropy across all affected youth (F3,85 = 2.8; P = .044). CONCLUSIONS AND RELEVANCE: These findings suggest that abnormal uncinate fasciculus and cingulum WM structure may underlie emotional, but not behavioral, dysregulation in pediatric psychiatric disorders and that a different neural mechanism may exist for comorbid emotional and behavioral DDs.