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Background: Cephalohematomas (CH) are benign neonatal fluid collections that arise between the periosteum and skull due to birth trauma, and usually resolve spontaneously without intervention. CH may rarely become infected. Case Description: The authors report a case of sterile CH requiring surgical evacuation in a persistently febrile neonate treated with intravenous (IV) antibiotics for Escherichia coli urosepsis. Diagnostic tap of the CH yielded no pathogens, but given the persistence of fevers, surgical evacuation was performed. The patient demonstrated clinical improvement postoperatively. Conclusion: A systematic review of literature was conducted through a MEDLINE search using the keyword “cephalohematoma.” Articles were screened for cases of infected CH and their subsequent management. Clinicopathological characteristics and outcomes of the present case were reviewed and compared to those in the literature. Infected CH were reported in 25 articles describing 58 patients. Common pathogens included E. coli and Staphylococcal species. Treatment included a course of IV antibiotics (10 days–6 weeks) and often included percutaneous aspiration (n = 47) for diagnostic and therapeutic purposes. Surgical evacuation was performed in 23 cases. To the authors’ knowledge, the present case is the first documented report in which evacuation of a culture-negative CH resulted in resolution of the patient’s clinical symptoms of sepsis that persisted despite appropriate antibiotic treatment. This suggests that patients with CH should be evaluated through diagnostic tap of the collection if there are signs of local or persistent systemic infection. Surgical evacuation may be indicated if percutaneous aspiration does not result in clinical improvement.

BACKGROUND Hypertrophic cranial pachymeningitis is a rare inflammatory disorder characterized by thickening of the dura mater and multiple cranial neuropathies. Although an infectious etiology may be present, often no specific cause is discovered. OBSERVATIONS The authors described a 71-year-old man with progressive right eye vision loss, ptosis, and complete ophthalmoplegia with imaging findings suggestive of hypertrophic cranial pachymeningitis. Extensive studies, including cerebrospinal fluid studies, showed negative results. Blood serum, cell-free evaluation, and paraffin-embedded dural tissue testing had positive results for Pseudomonas aeruginosa, which allowed treatment tailored to the organism and a salutary clinical outcome. LESSONS The constellation of neurological and radiological findings may make a diagnosis difficult in an inflammatory setting. The most precise methodology for establishing a diagnosis involves sampling the dura and testing it for infectious pathology. However, if results are inconclusive, further cell-free serum sampling with next-generation sequencing is a viable option for identifying pathogens with infectious concerns. This case highlighted the importance of multimodality studies for identifying a targetable pathogen.

Background Parkinson’s Disease (PD) is a clinically diagnosed neurodegenerative disorder that affects both motor and non-motor neural circuits. Speech deterioration (hypokinetic dysarthria) is a common symptom, which often presents early in the disease course. Machine learning can help movement disorders specialists improve their diagnostic accuracy using non-invasive and inexpensive voice recordings. Method We used “Parkinson Dataset with Replicated Acoustic Features Data Set” from the UCI-Machine Learning repository. The dataset included 44 speech-test based acoustic features from patients with PD and controls. We analyzed the data using various machine learning algorithms including Light and Extreme Gradient Boosting, Random Forest, Support Vector Machines, K-nearest neighborhood, Least Absolute Shrinkage and Selection Operator Regression, as well as logistic regression. We also implemented a variable importance analysis to identify important variables classifying patients with PD. Results The cohort included a total of 80 subjects: 40 patients with PD (55% men) and 40 controls (67.5% men). Disease duration was 5 years or less for all subjects, with a mean Unified Parkinson’s Disease Rating Scale (UPDRS) score of 19.6 (SD 8.1), and none were taking PD medication. The mean age for PD subjects and controls was 69.6 (SD 7.8) and 66.4 (SD 8.4), respectively. Our best-performing model used Light Gradient Boosting to provide an AUC of 0.951 with 95% confidence interval 0.946–0.955 in 4-fold cross validation using only seven acoustic features. Conclusions Machine learning can accurately detect Parkinson’s disease using an inexpensive and non-invasive voice recording. Light Gradient Boosting outperformed other machine learning algorithms. Such approaches could be used to inexpensively screen large patient populations for Parkinson’s disease.

BACKGROUND: Conditions requiring cervical decompression and stabilization are commonly treated using anterior cervical discectomy and fusion using an anterior cage-plate construct. Anterior zero profile integrated cages are an alternative to a cage-plate construct, but literature suggests they may result in less motion reduction. Interfacet cages may improve integrated cage stability. This study evaluated the motion reduction of integrated cages with and without supplemental interfacet fixation. Motion reduction of integrated cages were also compared to published cage-plate results. METHODS: Seven cadaveric (C2-T1) spines were tested in flexion-extension, lateral bending, and rotation. Specimens were tested: 1) intact, 2) C6-C7 integrated cage, 3) C6-C7 integrated cage + interfacet cages, 4) additional integrated cages at C3-C4 and C4-C5, 5) C3-C4, C4-C5 and C6-C7 integrated cages + interfacet cages. Motion, lordosis, disc and neuroforaminal height were assessed. FINDINGS: Integrated cage at C6-C7 decreased flexion-extension by 37% (P=0.06) and C3-C5 by 54% (P

Background : Parkinson’s Disease (PD) is a clinically diagnosed neurodegenerative disorder that affects both motor and non-motor neural circuits. Speech deterioration (hypokinetic dysarthria) is a common symptom, which often presents early in the disease course. Machine learning can help movement disorders specialists improve their diagnostic accuracy using non-invasive and inexpensive voice recordings. Method : We used “Parkinson Dataset with Replicated Acoustic Features Data Set” from the UCI-Machine Learning repository. The dataset included 45 features including sex and 44 speech test based acoustic features from 40 patients with Parkinson’s disease and 40 controls. We analyzed the data using various machine learning algorithms including tree-based ensemble approaches such as random forest and extreme gradient boosting. We also implemented a variable importance analysis to identify important variables classifying patients with PD. Results : The cohort included total of 80 subjects; 40 patients with PD (55% men) and 40 controls (67.5% men). PD patients showed at least two of the three symptoms; resting tremor, bradykinesia, or rigidity. All patients were over 50 years old and the mean age for PD subjects and controls were 69.6 (SD 7.8) and 66.4 (SD 8.4), respectively. Our final model provided an AUC of 0.940 with 95% confidence interval 0.935-0.945in 4-folds cross validation using only six acoustic features including Delta3 (Run2), Delta0 (Run 3), MFCC4 (Run 2), Delta10 (Run 2/Run 3), MFCC10 (Run 2) and Jitter_Rap (Run 1/Run 2). Conclusions : Machine learning can accurately detect Parkinson’s disease using an inexpensive and non-invasive voice recording. Such technologies can be deployed into smartphones for screening of large patient populations for Parkinson’s disease.

We seek a methodological approach to assess circadian processes in subjects who have recently experienced traumatic brain injury, using regularly gathered intracranial temperature data. The health effects of circadian regulation are profound, yet assessments of circadian processes are often infeasible in the neurotrauma intensive care unit (ICU). We assess circadian periodicity through the energy density spectrum, applying model-based and model-free methods: an extended Kalman filter (using the Kronauer model) in conjunction with a fast Fourier transform (FFT), and the Lomb–Scargle periodogram, respectively. We compute the change in relative energy in a narrow band of the spectrum, corresponding to a period of 23-25 h, over the first 48 and last 48 h of each subject's stay in the ICU. The change in relative energy in the spectrum increases in subjects with Good outcomes, and decreases in subjects with Poor outcomes, with statistical significance. For those subjects with Good outcome, we show evidence of regulation in circadian phase using an adaptive notch filter.

Normal blood flow in the brain as a response to pressure fluctuations is commonly referred to as cerebral autoregulation. Linear, nonparametric models of cerebral autoregulation were estimated for 77 human subjects afflicted with brain injury, with mean arterial pressure used as input, and invasively measured regional cerebral blood flow used as output. The data were continuously monitored from the beginning of subject hospital stay. Mean transfer function gain as a function of frequency was calculated for each subject over a limited time window spanning 48 h, starting postsurgery. The mean transfer function gain of the cerebral autoregulation model provided a highly accurate, statistically significant, assessment of patient outcome. Subjects were accurately grouped by outcome, with a high significance (p

Historically, determination of the critical cerebral perfusion pressure (CPP) was done in animals by a progressive lowering of arterial pressure yielding a nominal critical CPP of 60 mmHg. Subsequently, it was shown that if the CPP was decreased by increasing intracranial pressure (ICP), critical CPP fell to 30 mmHg. This discrepancy was unexplained. We recently provided evidence that the decrease in critical CPP was due to microvascular shunting resulting in maintained cerebral blood flow (CBF) at a lower CPP. We demonstrated by a progressive increase in ICP in rats using two-photon laser scanning microscopy (2PLSM) that the transition from capillary to microvascular shunt flow is a pathological process. We surmise that the loss of CBF autoregulation revealed by decreasing arterial pressure occurs by dilation of normal cerebral blood vessels whereas that which occurs by increasing ICP is due to microvascular shunting. Our observations indicate that the loss of CBF autoregulation we observed in brain injured patients that changes on an hourly or daily basis reflects an important pathophysiological process impacting on outcome that remains to be determined.

Hyperemia in the infarcted brain has been ­suggested for years by “red veins” reported by neurosurgeons, shunt peaks in radioactive blood flow clearance curves, and quantitative cerebral blood flow using stable xenon CT. Histological characterization of infarcted brain revealed capillary rarefaction with prominent microvascular shunts (MVS). Despite abundant histological evidence, the presence of cerebrovascular shunts have been largely ignored, perhaps because of a lack of physiological evidence demonstrating the transition from capillary flow to MVS flow. Our studies have shown that high intracranial pressure induces a transition from capillary to microvascular shunt flow resulting in cerebral hypoperfusion, tissue hypoxia and brain edema, which could be delayed by increasing cerebral perfusion pressure. The transition from capillary to microvascular shunt flow provides for the first time a physiological basis for evaluating the optimal cerebral perfusion pressure with increased intracranial pressure. It also provides a physiological basis for evaluating the effectiveness of various drugs and therapies in reducing intracranial pressure and the development of brain edema and tissue hypoxia after brain injury and ischemia. In summary, the clear-cut demonstration of the transition from capillary to MVS flow provides an important method for evaluating various therapies for the treatment of brain edema and loss of autoregulation.

We present a novel method for the geometric alignment of autoradiographs of the brain. The method is based on finding the spatial mapping and the one-to-one correspondences (or homologies) between point features extracted from the images and rejecting non-homologies as outliers. In this way, we attempt to account for the local, natural and artifactual differences between the autoradiograph slices. We have used the resulting automated algorithm on a set of left prefrontal cortex autoradiograph slices, specifically demonstrated its ability to perform point outlier rejection, validated its robustness property using synthetically generated spatial mappings and provided an anecdotal visual comparison with the well-known iterated closest-point (ICP) algorithm. Visualization of a stack of aligned left prefrontal cortex autoradiograph slices is also provided.

The sensitivity of sestamibi scanning techniques used for preoperative localization in primary hyperparathyroidism is a function of the parameters of image acquisition and processing.Criterion standard vs optimized technique.Tertiary referral center.One hundred forty-eight consecutive patients with primary hyperthyroidism were analyzed. Under the initial protocol, 97 patients underwent a preexisting standard sestamibi--single-photon emission computed tomographic scan and surgical exploration. The scanning technique was modified and in the revised protocol, 51 patients underwent imaging and surgical exploration.Image acquisition and processing revisions as follows: patient positioning standardized, collimator resolution adjusted, radioactive tracer delay extended, visualization field broadened, data extraction refined, and image processing filter modified.concordance among the scan and operative localization, lateralization, and cure rate.Initial protocol: 97 patients underwent surgery for primary hyperthyroidism with the initial sestamibi design. Eighty-one patients (83%) had a positive result, that is, at least 1 gland was identified; 77 patients (79%) had correct lateralization; and 49 patients (52%) had precise localization. Revised protocol: 51 patients underwent imaging under the optimized protocol. Forty-nine patients (96) had a positive result; 47 patients (92%) had correct lateralization; and 36 patients (70%) had precise localization. These improvements were significant, with P.05 for localization and P.01 for lateralization. Cure rates were 96% in both groups, confirmed by laboratory and pathologic findings.Sestamibi optimization in primary hyperparathyroidism can improve scan sensitivity. This may permit a focused minimally invasive operation.