Strain concentration drives the anatomical distribution of injury in acute and chronic traumatic brain injury.

Brain tissue injury caused by mild traumatic brain injury (mTBI) disproportionately concentrates in the midbrain, cerebellum, mesial temporal lobe, and the interface between cortex and white matter at sulcal depths 1-12. The bio-mechanical principles that explain why physical impacts to different parts of the skull translate to common foci of injury concentrated in specific brain structures are unknown. A general and longstanding idea, which has not to date been directly tested in humans, is that different brain regions are differentially susceptible to strain loading11,13-15. We use Magnetic Resonance Elastography (MRE) in healthy participants to develop whole-brain bio-mechanical vulnerability maps that independently define which regions of the brain exhibit disproportionate strain concentration. We then validate those vulnerability maps in a prospective cohort of mTBI patients, using diffusion MRI data collected at three cross-sectional timepoints after injury: acute, sub-acute, chronic. We show that regions that exhibit high strain, measured with MRE, are also the sites of greatest injury, as measured with diffusion MR in mTBI patients. This was the case in acute, subacute, and chronic subgroups of the mTBI cohort. Follow-on analyses decomposed the biomechanical cause of increased strain by showing it is caused jointly by disproportionately higher levels of energy arriving to 'high-strain' structures, as well as the inability of 'high strain' structures to effectively disperse that energy. These findings establish a causal mechanism that explains the anatomy of injury in mTBI based on in vivo rheological properties of the human brain.

Characteristics associated with response to subcutaneously administered anti-CGRP monoclonal antibody medications in a real-world community cohort of persons living with migraine: A retrospective clinical and genetic study.

OBJECTIVE: To evaluate response to anti-calcitonin gene-related peptide (CGRP) migraine preventives in a real-world community cohort of persons living with migraine and to identify clinical and genetic characteristics associated with efficacious response. BACKGROUND: Erenumab-aooeb, fremanezumab-vrfm, and galcanezumab-gnlm target CGRP or its receptor; however, many patients are non-responsive. METHODS: In this retrospective clinical and genetic study, we identified 1077 adult patients who satisfied the International Classification of Headache Disorders, 3rd edition, criteria for migraine without aura, migraine with aura, or chronic migraine and who were prescribed an anti-CGRP migraine preventive between May 2018 and May 2021. Screening of 558 patients identified 289 with data at baseline and first follow-up visits; data were available for 161 patients at a second follow-up visit. The primary outcome was migraine days per month (MDM). In 198 genotyped patients, we evaluated associations between responders (i.e., patients with ≥50% reduction in MDM at follow-up) and genes involved in CGRP signaling or pharmacological response, and genetic and polygenic risk scores. RESULTS: The median time to first follow-up was 4.4 (0.9-22) months after preventive start. At the second follow-up, 5.7 (0.9-13) months later, 145 patients had continued on the same preventive. Preventives had strong, persistent effects in reducing MDM in responders (follow-up 1: η2 = 0.26, follow-up 2: η2 = 0.22). At the first but not second follow-up: galcanezumab had a larger effect than erenumab, while no difference was seen at either follow-up between galcanezumab and fremanezumab or fremanezumab and erenumab. The decrease in MDM at follow-up was generally proportional to baseline MDM, larger in females, and increased with months on medication. At the first follow-up only, patients with prior hospitalization for migraine or who had not responded to more preventive regimens had a smaller decrease in MDM. Reasons for stopping or switching a preventive varied between medications and were often related to cost and insurance coverage. At both follow-ups, patient tolerance (1: 92.2% [262/284]; 2: 95.2% [141/145]) and continued use (1: 77.5% [224/289]; 2: 80.6% [116/145]) were high and similar across preventives. Response consistency (always non-responders: 31.7% [46/145]; always responders: 56.5% [82/145], and one-time only responders: 11.7% [17/145]) was also similar across preventives. Non-responder status had nominally significant associations with rs12615320-G in RAMP1 (odds ratio [95% confidence interval]: 4.7 [1.5, 14.7]), and rs4680-A in COMT (0.6[0.4, 0.9]). Non-responders had a lower mean genetic risk score than responders (1.0 vs. 1.1; t(df) = -1.75(174.84), p = 0.041), and the fraction of responders increased with genetic and polygenic risk score percentile. CONCLUSIONS: In this real-world setting, anti-CGRP preventives reduced MDM persistently and had similar and large effect sizes on MDM reduction; however, clinical and genetic factors influenced response.

Radiological abnormalities in progressive multifocal leukoencephalopathy: Identifying typical and atypical imaging patterns for early diagnosis and differential considerations.

Progressive multifocal leukoencephalopathy (PML) is a rare viral central nervous system (CNS) demyelinating disease primarily associated with a compromised immune system. PML is seen mainly in individuals with human immunodeficiency virus, lymphoproliferative disease, and multiple sclerosis. Patients on immunomodulators, chemotherapy, and solid organ or bone marrow transplants are predisposed to PML. Recognition of various PML-associated typical and atypical imaging abnormalities is critical for early diagnosis and differentiating it from other conditions, especially in high-risk populations. Early PML recognition should expedite efforts at immune-system restoration, allowing for a favorable outcome. This review aims to provide a practical overview of radiological abnormalities in PML patients and address differential considerations.

Multimodality imaging of neurodegenerative disorders with a focus on multiparametric magnetic resonance and molecular imaging.

Neurodegenerative diseases afflict a large number of persons worldwide, with the prevalence and incidence of dementia rapidly increasing. Despite their prevalence, clinical diagnosis of dementia syndromes remains imperfect with limited specificity. Conventional structural-based imaging techniques also lack the accuracy necessary for confident diagnosis. Multiparametric magnetic resonance imaging and molecular imaging provide the promise of improving specificity and sensitivity in the diagnosis of neurodegenerative disease as well as therapeutic monitoring of monoclonal antibody therapy. This educational review will briefly focus on the epidemiology, clinical presentation, and pathologic findings of common and uncommon neurodegenerative diseases. Imaging features of each disease spanning from conventional magnetic resonance sequences to advanced multiparametric methods such as resting-state functional magnetic resonance imaging and arterial spin labeling imaging will be described in detail. Additionally, the review will explore the findings of each diagnosis on molecular imaging including single-photon emission computed tomography and positron emission tomography with a variety of clinically used and experimental radiotracers. The literature and clinical cases provided demonstrate the power of advanced magnetic resonance imaging and molecular techniques in the diagnosis of neurodegenerative diseases and areas of future and ongoing research. With the advent of combined positron emission tomography/magnetic resonance imaging scanners, hybrid protocols utilizing both techniques are an attractive option for improving the evaluation of neurodegenerative diseases.

Clinical performance of a multiparametric MRI-based post concussive syndrome index.

Introduction: Diffusion Tensor Imaging (DTI) has revealed measurable changes in the brains of patients with persistent post-concussive syndrome (PCS). Because of inconsistent results in univariate DTI metrics among patients with mild traumatic brain injury (mTBI), there is currently no single objective and reliable MRI index for clinical decision-making in patients with PCS. Purpose: This study aimed to evaluate the performance of a newly developed PCS Index (PCSI) derived from machine learning of multiparametric magnetic resonance imaging (MRI) data to classify and differentiate subjects with mTBI and PCS history from those without a history of mTBI. Materials and methods: Data were retrospectively extracted from 139 patients aged between 18 and 60 years with PCS who underwent MRI examinations at 2 weeks to 1-year post-mTBI, as well as from 336 subjects without a history of head trauma. The performance of the PCS Index was assessed by comparing 69 patients with a clinical diagnosis of PCS with 264 control subjects. The PCSI values for patients with PCS were compared based on the mechanism of injury, time interval from injury to MRI examination, sex, history of prior concussion, loss of consciousness, and reported symptoms. Results: Injured patients had a mean PCSI value of 0.57, compared to the control group, which had a mean PCSI value of 0.12 (p = 8.42e-23) with accuracy of 88%, sensitivity of 64%, and specificity of 95%, respectively. No statistically significant differences were found in the PCSI values when comparing the mechanism of injury, sex, or loss of consciousness. Conclusion: The PCSI for individuals aged between 18 and 60 years was able to accurately identify patients with post-concussive injuries from 2 weeks to 1-year post-mTBI and differentiate them from the controls. The results of this study suggest that multiparametric MRI-based PCSI has great potential as an objective clinical tool to support the diagnosis, treatment, and follow-up care of patients with post-concussive syndrome. Further research is required to investigate the replicability of this method using other types of clinical MRI scanners.

Intracranial Abnormalities with Diffusion Restriction.

Multiple pathologic conditions can cause changes in the random movement of water, which can be detected with diffusion-weighted imaging (DWI). DWI plays a powerful clinical role in detecting restricted diffusion associated with acute brain infarction. Other disorders can also result in restricted diffusion. This article focuses on showing examples of common and uncommon disorders that have restricted diffusion secondary to cytotoxic and/or intramyelinic edema. These disorders include ischemia, infection, noninfectious demyelinating diseases, genetic mutations affecting metabolism, acquired metabolic disorders, toxic or drug exposures, neoplasms and tumorlike lesions, radiation treatment, trauma, and denervation.

Post-concussive mTBI in Student Athletes: MRI Features and Machine Learning.

Purpose: To determine and characterize the radiomics features from structural MRI (MPRAGE) and Diffusion Tensor Imaging (DTI) associated with the presence of mild traumatic brain injuries on student athletes with post-concussive syndrome (PCS). Material and Methods: 122 student athletes (65 M, 57 F), median (IQR) age 18.8 (15-20) years, with a mixed level of play and sports activities, with a known history of concussion and clinical PCS, and 27 (15 M, 12 F), median (IQR) age 20 (19, 21) years, concussion free athlete subjects were MRI imaged in a clinical MR machine. MPRAGE and DTI-FA and DTI-ADC images were used to extract radiomic features from white and gray matter regions within the entire brain (2 ROI) and the eight main lobes of the brain (16 ROI) for a total of 18 analyzed regions. Radiomic features were divided into five different data sets used to train and cross-validate five different filter-based Support Vector Machines. The top selected features of the top model were described. Furthermore, the test predictions of the top four models were ensembled into a single average prediction. The average prediction was evaluated for the association to the number of concussions and time from injury. Results: Ninety-one PCS subjects passed inclusion criteria (91 Cases, 27 controls). The average prediction of the top four models had a sensitivity of 0.80, 95% CI: [0.71, 0.88] and specificity of 0.74 95%CI [0.54, 0.89] for distinguishing subjects from controls. The white matter features were strongly associated with mTBI, while the whole-brain analysis of gray matter showed the worst association. The predictive index was significantly associated with the number of concussions (p < 0.0001) and associated with the time from injury (p < 0.01). Conclusion: MRI Radiomic features are associated with a history of mTBI and they were successfully used to build a predictive machine learning model for mTBI for subjects with PCS associated with a history of one or more concussions.

Quality improvement and practice-based research in sleep medicine using structured clinical documentation in the electronic medical record.

BACKGROUND: We developed and implemented a structured clinical documentation support (SCDS) toolkit within the electronic medical record, to optimize patient care, facilitate documentation, and capture data at office visits in a sleep medicine/neurology clinic for patient care and research collaboration internally and with other centers. METHODS: To build our SCDS toolkit, physicians met frequently to develop content, define the cohort, select outcome measures, and delineate factors known to modify disease progression. We assigned tasks to the care team and mapped data elements to the progress note. Programmer analysts built and tested the SCDS toolkit, which included several score tests. Auto scored and interpreted tests included the Generalized Anxiety Disorder 7-item, Center for Epidemiological Studies Depression Scale, Epworth Sleepiness Scale, Pittsburgh Sleep Quality Index, Insomnia Severity Index, and the International Restless Legs Syndrome Study Group Rating Scale. The SCDS toolkits also provided clinical decision support (untreated anxiety or depression) and prompted enrollment of patients in a DNA biobank. RESULTS: The structured clinical documentation toolkit captures hundreds of fields of discrete data at each office visit. This data can be displayed in tables or graphical form. Best practice advisories within the toolkit alert physicians when a quality improvement opportunity exists. As of May 1, 2019, we have used the toolkit to evaluate 18,105 sleep patients at initial visit. We are also collecting longitudinal data on patients who return for annual visits using the standardized toolkits. We provide a description of our development process and screenshots of our toolkits. CONCLUSIONS: The electronic medical record can be structured to standardize Sleep Medicine office visits, capture data, and support multicenter quality improvement and practice-based research initiatives for sleep patients at the point of care.

Optimizing the electronic medical record to improve patient care and conduct quality improvement initiatives in a concussion specialty clinic.

Objective: To use the electronic medical record (EMR) to optimize patient care, facilitate documentation, and support quality improvement and practice-based research in a concussion (mild traumatic brain injury; mTBI) clinic.Methods: We built a customized structured clinical documentation support (SCDS) toolkit for patients in a concussion specialty clinic. The toolkit collected hundreds of fields of discrete, standardized data. Autoscored and interpreted score tests include the Generalized Anxiety Disorder 7-item scale, Center for Epidemiology Studies Depression scale, Insomnia Severity Index, and Glasgow Coma Scale. Additionally, quantitative score measures are related to immediate memory, concentration, and delayed recall. All of this data collection occurred in a standard appointment length.Results: To date, we evaluated 619 patients at an initial office visit after an mTBI. We provided a description of our toolkit development process, and a summary of the data electronically captured using the toolkit.Conclusions: The electronic medical record can be used to effectively structure and standardize care in a concussion clinic. The toolkit supports the delivery of care consistent with Best Practices, provides opportunities for point of care decision support, and writes comprehensive progress notes that can be communicated to other providers.

Neurology steering board effects change for a major electronic health record vendor.

Neurologists are among the least satisfied physicians with their current electronic health record (EHR), with many known pain points and great opportunities for improved tools and workflows. Improved EHR functionality can have major implications for patient care, physician efficiency, and prevention of burnout. We describe the advocacy of the American Academy of Neurology for improved EHR usability and the resultant formation and subsequent accomplishments of a Neurology Subspecialty Steering Board at 1 major EHR vendor (Epic).

Building of EMR Tools to Support Quality and Research in a Memory Disorders Clinic.

The electronic medical record (EMR) presents an opportunity to standardize patient data collection based on quality guidelines and conduct practice-based research. We describe the development of a customized EMR "toolkit" that standardizes patient data collection with hundreds of discrete fields that supports Best Practices for treating patients with memory disorders. The toolkit also supports practice-based research. We describe the design and successful implementation of a customized EMR toolkit to support Best Practices in the care of patients with memory disorders. We discuss applications, including quality improvement projects and current research initiatives, using the toolkit. This toolkit is being shared with other departments of Neurology as part of the Neurology Practice-Based Research Network. Data collection is ongoing, including longitudinal follow-up. This toolkit will generate data that will allow for descriptive and hypothesis driven research as well-quality improvement among patients seen in a memory clinic.

Design and Implementation of Structured Clinical Documentation Support Tools for Treating Stroke Patients.

BACKGROUND AND PURPOSE: Standardized electronic medical record tools provide an opportunity to efficiently provide care that conforms to Best Practices and supports quality improvement and practice-based research initiatives. METHODS: We describe the development of a customized structured clinical documentation "toolkit" that standardizes patient data collection to conform to Best Practices for treating patients with stroke. The toolkit collects patients' demographic information, relevant score test measures, and captures information on disability, treatment, and outcomes. RESULTS: We describe here our creation and implementation of the toolkits and provide example screenshots. As of August 1, 2018, we have evaluated 2332 patients at an initial visit for a possible stroke. We provide basic descriptive data gathered from the use of the toolkits, demonstrating their utility in collecting patient data in a manner that supports both quality clinical care and research initiatives. CONCLUSIONS: We have developed an EMR toolkit to support Best Practices in the care of patients with stroke. We discuss quality improvement projects and current research initiatives using the toolkit. This toolkit is being shared with other Departments of Neurology as part of the Neurology Practice-Based Research Network.

Factors Affecting Cognition and Depression in Adult Patients with Epilepsy.

BACKGROUND AND PURPOSE: Epilepsy patients are more likely to experience depressive symptoms and cognitive impairment compared to individuals in the general population. As the reasons for this are not definitively known, we sought to determine what factors correlate most strongly with cognition and a screening test for depression in epilepsy patients. METHODS: Our study population included 379 adult patients diagnosed with epilepsy or seizure in our neurology clinic. We collected detailed demographic and clinical data during patient visits using structured clinical documentation support tools that we have built within our commercial electronic medical records system (Epic), including a depression score (Neurological Disorders Depression Inventory for Epilepsy, NDDIE) and cognition score test measures (specifically in this study, Mini-Mental State Examination [MMSE]). Medication, age, gender, body mass index, duration of epilepsy, seizure frequency, current number of anti-epileptic medications, years of education were assessed in relation to baseline score as well as change in score from initial visit to first annual follow-up. RESULTS: Of the analyzed factors, two statistically significant associations were found after correction for multiple testing. Male gender and lower anti-seizure medication count were associated with better mood, as assessed by NDDIE score, at initial visit. Specifically, male gender was associated with a 1.3 decrease in NDDIE and for each additional anti-seizure medication, there was an associated 1.2 increase in NDDIE. CONCLUSIONS: However, these factors were not associated with change in NDDIE score from initial to first annual follow-up visit. These findings, although interesting, are preliminary. Additionally, these findings were based on a homogenous (mainly Caucasian) clinic-based population and detailed information on previous medication use was lacking. Further work is needed to replicate these findings and to understand any mechanisms that may explain these associations.

Domain-Specific Diaschisis: Lesions to Parietal Action Areas Modulate Neural Responses to Tools in the Ventral Stream.

Neural responses to small manipulable objects ("tools") in high-level visual areas in ventral temporal cortex (VTC) provide an opportunity to test how anatomically remote regions modulate ventral stream processing in a domain-specific manner. Prior patient studies indicate that grasp-relevant information can be computed about objects by dorsal stream structures independently of processing in VTC. Prior functional neuroimaging studies indicate privileged functional connectivity between regions of VTC exhibiting tool preferences and regions of parietal cortex supporting object-directed action. Here we test whether lesions to parietal cortex modulate tool preferences within ventral and lateral temporal cortex. We found that lesions to the left anterior intraparietal sulcus, a region that supports hand-shaping during object grasping and manipulation, modulate tool preferences in left VTC and in the left posterior middle temporal gyrus. Control analyses demonstrated that neural responses to "place" stimuli in left VTC were unaffected by lesions to parietal cortex, indicating domain-specific consequences for ventral stream neural responses in the setting of parietal lesions. These findings provide causal evidence that neural specificity for "tools" in ventral and lateral temporal lobe areas may arise, in part, from online inputs to VTC from parietal areas that receive inputs via the dorsal visual pathway.

Successful utilization of the EMR in a multiple sclerosis clinic to support quality improvement and research initiatives at the point of care.

BACKGROUND: Many physicians enter data into the electronic medical record (EMR) as unstructured free text and not as discrete data, making it challenging to use for quality improvement or research initiatives. OBJECTIVES: The objective of this research paper was to develop and implement a structured clinical documentation support (SCDS) toolkit within the EMR to facilitate quality initiatives and practice-based research in a multiple sclerosis (MS) practice. METHODS: We built customized EMR toolkits to capture standardized data at office visits. Content was determined through physician consensus on necessary elements to support best practices in treating patients with demyelinating disorders. We also developed CDS tools and best practice advisories within the toolkits to alert physicians when a quality improvement opportunity exists, including enrollment into our DNA biobanking study at the point of care. RESULTS: We have used the toolkit to evaluate 541 MS patients in our clinic and begun collecting longitudinal data on patients who return for annual visits. We provide a description and example screenshots of our toolkits, and a brief description of our cohort to date. CONCLUSIONS: The EMR can be effectively structured to standardize MS clinic office visits, capture data, and support quality improvement and practice-based research initiatives at the point of care.

Design and implementation of pragmatic clinical trials using the electronic medical record and an adaptive design.

OBJECTIVES: To demonstrate the feasibility of pragmatic clinical trials comparing the effectiveness of treatments using the electronic medical record (EMR) and an adaptive assignment design. METHODS: We have designed and are implementing pragmatic trials at the point-of-care using custom-designed structured clinical documentation support and clinical decision support tools within our physician's typical EMR workflow. We are applying a subgroup based adaptive design (SUBA) that enriches treatment assignments based on baseline characteristics and prior outcomes. SUBA uses information from a randomization phase (phase 1, equal randomization, 120 patients), to adaptively assign treatments to the remaining participants (at least 300 additional patients total) based on a Bayesian hierarchical model. Enrollment in phase 1 is underway in our neurology clinical practices for 2 separate trials using this method, for migraine and mild cognitive impairment (MCI). RESULTS: We are successfully collecting structured data, in the context of the providers' clinical workflow, necessary to conduct our trials. We are currently enrolling patients in 2 point-of-care trials of non-inferior treatments. As of March 1, 2018, we have enrolled 36% of eligible patients into our migraine study and 63% of eligible patients into our MCI study. Enrollment is ongoing and validation of outcomes has begun. DISCUSSION: This proof of concept article demonstrates the feasibility of conducting pragmatic trials using the EMR and an adaptive design. CONCLUSION: The demonstration of successful pragmatic clinical trials based on a customized EMR and adaptive design is an important next step in achieving personalized medicine and provides a framework for future studies of comparative effectiveness.

Structured Clinical Documentation to Improve Quality and Support Practice-Based Research in Headache.

OBJECTIVE: To use the electronic medical record (EMR) to optimize patient care, facilitate documentation, and support quality improvement and practice-based research, in a headache specialty clinic. BACKGROUND: Many physicians enter data into the EMR as unstructured free text and not as discrete data. This makes it challenging to use data for quality improvement or research initiatives. METHODS: We describe the process of building a customized structured clinical documentation support toolkit, specific for patients seen in a headache specialty clinic. The content was developed through frequent physician meetings to reach consensus on elements that define clinical Best Practices. Tasks were assigned to the care team and data mapped to the progress note. RESULTS: The toolkit collects hundreds of fields of discrete, standardized data. Auto scored and interpreted score tests include the Generalized Anxiety Disorder 7-item, Center for Epidemiology Studies Depression Scale, Migraine Disability Assessment questionnaire, Insomnia Sleep Index, and Migraine-Specific Quality of Life. We have developed Best Practice Advisories (BPA) and other clinical documentation support tools that alert physicians, when appropriate. As of April 1, 2018, we have used the toolkits at 4346 initial patient visits. We provide screenshots of our toolkits, details of data fields collected, and diagnoses of patients at the initial visit. CONCLUSIONS: The EMR can be used to effectively structure and standardize headache clinic visits for quality improvement and practice-based research. We are sharing our proprietary toolkit with other clinics as part of the Neurology Practice-Based Research Network. These tools are also facilitating clinical research enrollment and a pragmatic trial of comparative effectiveness at the point-of-care among migraine patients.

Malformed vertebrae: a clinical and imaging review.

A variety of structural developmental anomalies affect the vertebral column. Malformed vertebrae can arise secondary to errors of vertebral formation, fusion and/or segmentation and developmental variation. Malformations can be simple with little or no clinical consequence, or complex with serious structural and neurologic implications. These anomalies can occasionally mimic acute trauma (bipartite atlas versus Jefferson fracture, butterfly vertebra versus burst fracture), or predispose the affected individual to myelopathy. Accurate imaging interpretation of vertebral malformations requires knowledge of ageappropriate normal, variant and abnormal vertebral morphology and the clinical implications of each entity. This knowledge will improve diagnostic confidence in acute situations and confounding clinical scenarios.This review article seeks to familiarize the reader with the embryology, normal and variant anatomy of the vertebral column and the imaging appearance and clinical impact of the spectrum of vertebral malformations arising as a consequence of disordered embryological development.Teaching points • Some vertebral malformations predispose the affected individual to trauma or myelopathy. • On imaging, malformed vertebrae can be indistinguishable from acute trauma. • Abnormalities in spinal cord development may be associated and must be searched for. • Accurate interpretation requires knowledge of normal, variant and abnormal vertebral morphology.

Mechanical birth-related trauma to the neonate: An imaging perspective.

Mechanical birth-related injuries to the neonate are declining in incidence with advances in prenatal diagnosis and care. These injuries, however, continue to represent an important source of morbidity and mortality in the affected patient population. In the United States, these injuries are estimated to occur among 2.6% of births. Although more usual in context of existing feto-maternal risk factors, their occurrence can be unpredictable. While often superficial and temporary, functional and cosmetic sequelae, disability or even death can result as a consequence of birth-related injuries. The Agency for Healthcare research and quality (AHRQ) in the USA has developed, through expert consensus, patient safety indicators which include seven types of birth-related injuries including subdural and intracerebral hemorrhage, epicranial subaponeurotic hemorrhage, skeletal injuries, injuries to spine and spinal cord, peripheral and cranial nerve injuries and other types of specified and non-specified birth trauma. Understandably, birth-related injuries are a source of great concern for the parents and clinician. Many of these injuries have imaging manifestations. This article seeks to familiarize the reader with the clinical spectrum, significance and multimodality imaging appearances of neonatal multi-organ birth-related trauma and its sequelae, where applicable. Teaching points • Mechanical trauma related to birth usually occurs with pre-existing feto-maternal risk factors.• Several organ systems can be affected; neurologic, musculoskeletal or visceral injuries can occur.• Injuries can be mild and transient or disabling, even life-threatening.• Imaging plays an important role in injury identification and triage of affected neonates.

The cingulate cortex of older adults with excellent memory capacity.

Memory deterioration is the earliest and most devastating cognitive deficit in normal aging and Alzheimer's disease (AD). Some older adults, known as "Supernormals", maintain excellent memory. This study examined relationships between cerebral amyloid deposition and functional connectivity (FC) within the cingulate cortex (CC) and between CC and other regions involved in memory maintenance between Supernormals, healthy controls (HC), and those at risk for AD (amnestic mild cognitive impairment [MCI]). Supernormals had significantly stronger FC between anterior CC and R-hippocampus, middle CC (MCC) and L-superior temporal gyrus, and posterior CC (PCC) and R-precuneus, while weaker FC between MCC and R-middle frontal gyrus and MCC and R-thalamus than other groups. All of these FC were significantly related to memory and global cognition in all participants. Supernormals had less amyloid deposition than other groups. Relationships between global cognition and FC were stronger among amyloid positive participants. Relationships between memory and FC remained regardless of amyloid level. This revealed how CC-related neural function participates in cognitive maintenance in the presence of amyloid deposition, potentially explaining excellent cognitive function among Supernormals.