Live predator stress in adolescence results in distinct adult behavioral consequences and dorsal diencephalic brain activation patterns

Exposure to traumatic events during childhood increases the risk of adult psychopathology, including anxiety, depression, alcohol use disorders and their co-morbidity. Early life trauma also results in increased symptom complexity, treatment resistance and poor treatment outcomes. The purpose of this study was to establish a novel rodent model of adolescent stress, based on an ethologically relevant life-threatening event, live predator exposure. Rats were exposed to a live predator for 10 min. at three different time points (postnatal day (PND)31, 46 and 61). Adult depression-, anxiety-like behaviors and ethanol consumption were characterized well past the last acute stress event (two weeks). Behavioral profiles across assessments were developed to characterize individual response to adolescent stress. CNS activation patterns in separate groups of subjects were characterized after the early (PND31) and last predator exposure (PND61). Subjects exposed to live-predator adolescent stress generally exhibited less exploratory behavior, less propensity to venture into open spaces, a decreased preference for sweet solutions and decreased ethanol consumption in a two-bottle preference test. Additional studies demonstrated blunted cortisol response and CNS activation patterns suggestive of habenula, rostromedial tegmental (RMTg), dorsal raphe and central amygdala involvement in mediating the adult consequences of adolescent stress. Thus, adolescent stress in the form of live-predator exposure results in significant adult behavioral and neurobiological disturbances. Childhood trauma, its impact on neurodevelopment and the subsequent development of mood disorders is a pervasive theme in mental illness. Improving animal models and our neurobiological understanding of the symptom domains impacted by trauma could significantly improve treatment strategies.

Normal T1 relaxometry and extracellular volume of the pancreas in subjects with no pancreas disease: correlation with age and gender

OBJECTIVE

Determine normal T₁ and extracellular volume (ECV) of the pancreas in subjects with no pancreas disease and correlate with age and gender.

SUBJECTS AND METHODS

We imaged 120 healthy subjects (age range 20-78 years) who are on annual screening with MRI/MRCP for the possibility of pancreatic cancer. Subjects had a predisposition to develop pancreatic cancer, but no history of pancreas disease or acute symptoms. Equal number (n = 60) of subjects were scanned on either 1.5 T or 3 T scanner using dual flip angle spoiled gradient echo technique incorporating fat suppression and correction for B₁ field inhomogeneity. Optimization of imaging parameters was performed using a T₁ phantom. ECV was calculated using pre- and post-contrast T₁ of the pancreas and plasma. Regression analysis and Mann-Whitney tests were used for statistical analysis.

RESULTS

Median T₁ on 1.5 T was 654 ms (IQR 608-700); median T₁ on 3 T was 717 ms (IQR 582-850); median ECV on 1.5 T was 0.28 (IQR 0.21-0.33), and median ECV on 3 T was 0.25 (IQR 0.19-0.28). Age had a mild positive correlation with T₁ (r = 0.24, p = 0.009), but not with ECV (r = 0.06, p = 0.54). T₁ and ECV were similar in both genders (p > 0.05).

CONCLUSION

This study measured the median T₁ and ECV of the pancreas in subjects with no pancreas disease. Pancreas shows longer T₁ relaxation times in older population, whereas extracellular fraction remains unchanged. Median T₁ values were different between two magnet strengths; however, no difference was seen between genders and ECV fractions.

Accurate Patient-Specific Machine Learning Models of Glioblastoma Invasion Using Transfer Learning

BACKGROUND AND PURPOSE

MR imaging-based modeling of tumor cell density can substantially improve targeted treatment of glioblastoma. Unfortunately, interpatient variability limits the predictive ability of many modeling approaches. We present a transfer learning method that generates individualized patient models, grounded in the wealth of population data, while also detecting and adjusting for interpatient variabilities based on each patient's own histologic data.

MATERIALS AND METHODS

We recruited patients with primary glioblastoma undergoing image-guided biopsies and preoperative imaging, including contrast-enhanced MR imaging, dynamic susceptibility contrast MR imaging, and diffusion tensor imaging. We calculated relative cerebral blood volume from DSC-MR imaging and mean diffusivity and fractional anisotropy from DTI. Following image coregistration, we assessed tumor cell density for each biopsy and identified corresponding localized MR imaging measurements. We then explored a range of univariate and multivariate predictive models of tumor cell density based on MR imaging measurements in a generalized one-model-fits-all approach. We then implemented both univariate and multivariate individualized transfer learning predictive models, which harness the available population-level data but allow individual variability in their predictions. Finally, we compared Pearson correlation coefficients and mean absolute error between the individualized transfer learning and generalized one-model-fits-all models.

RESULTS

Tumor cell density significantly correlated with relative CBV (r = 0.33, P < .001), and T1-weighted postcontrast (r = 0.36, P < .001) on univariate analysis after correcting for multiple comparisons. With single-variable modeling (using relative CBV), transfer learning increased predictive performance (r = 0.53, mean absolute error = 15.19%) compared with one-model-fits-all (r = 0.27, mean absolute error = 17.79%). With multivariate modeling, transfer learning further improved performance (r = 0.88, mean absolute error = 5.66%) compared with one-model-fits-all (r = 0.39, mean absolute error = 16.55%).

CONCLUSIONS

Transfer learning significantly improves predictive modeling performance for quantifying tumor cell density in glioblastoma.

Retrospective Validation of a Computer-Assisted Quantification Model of Intracerebral Hemorrhage Volume on Accuracy, Precision, and Acquisition Time, Compared with Standard ABC/2 Manual Volume Calculation

BACKGROUND AND PURPOSE

Intracerebral hemorrhage accounts for 6.5%-19.6% of all acute strokes. Initial intracerebral hemorrhage volume and expansion are both independent predictors of clinical outcomes and mortality. Therefore, a rapid, unbiased, and precise measurement of intracerebral hemorrhage volume is a key component of clinical management. The most commonly used method, ABC/2, results in overestimation. We developed an interactive segmentation program, SegTool, using a novel graphic processing unit, level set algorithm. Until now, the speed, bias, and precision of SegTool had not been validated.

MATERIALS AND METHODS

In a single stroke academic center, 2 vascular neurologists and 2 neuroradiologists independently performed a test-retest experiment that involved repeat measurements of static, unchanging intracerebral hemorrhage volumes on CT from 76 intracerebral hemorrhage cases. Measurements were made with SegTool and ABC/2. True intracerebral hemorrhage volumes were estimated from a consensus of repeat manual tracings by 2 operators. These data allowed us to estimate measurement bias, precision, and speed.

RESULTS

The measurements with SegTool were not significantly different from the true intracerebral hemorrhage volumes, while ABC/2 overestimated volume by 45%. The interrater measurement variability with SegTool was 50% less than that with ABC/2. The average measurement times for ABC/2 and SegTool were 35.7 and 44.6 seconds, respectively.

CONCLUSIONS

SegTool appears to have attributes superior to ABC/2 in terms of accuracy and interrater reliability with a 9-second delay in measurement time (on average); hence, it could be useful in clinical trials and practice.

MRI-Based Texture Analysis to Differentiate Sinonasal Squamous Cell Carcinoma from Inverted Papilloma

BACKGROUND AND PURPOSE

Because sinonasal inverted papilloma can harbor squamous cell carcinoma, differentiating these tumors is relevant. The objectives of this study were to determine whether MR imaging-based texture analysis can accurately classify cases of noncoexistent squamous cell carcinoma and inverted papilloma and to compare this classification performance with neuroradiologists' review.

MATERIALS AND METHODS

Adult patients who had inverted papilloma or squamous cell carcinoma resected were eligible (coexistent inverted papilloma and squamous cell carcinoma were excluded). Inclusion required tumor size of >1.5 cm and preoperative MR imaging with axial T1, axial T2, and axial T1 postcontrast sequences. Five well-established texture analysis algorithms were applied to an ROI from the largest tumor cross-section. For a training dataset, machine-learning algorithms were used to identify the most accurate model, and performance was also evaluated in a validation dataset. On the basis of 3 separate blinded reviews of the ROI, isolated tumor, and entire images, 2 neuroradiologists predicted tumor type in consensus.

RESULTS

The inverted papilloma (n = 24) and squamous cell carcinoma (n = 22) cohorts were matched for age and sex, while squamous cell carcinoma tumor volume was larger (P = .001). The best classification model achieved similar accuracies for training (17 squamous cell carcinomas, 16 inverted papillomas) and validation (7 squamous cell carcinomas, 6 inverted papillomas) datasets of 90.9% and 84.6%, respectively (P = .537). For the combined training and validation cohorts, the machine-learning accuracy (89.1%) was better than that of the neuroradiologists' ROI review (56.5%, P = .0004) but not significantly different from the neuroradiologists' review of the tumors (73.9%, P = .060) or entire images (87.0%, P = .748).

CONCLUSIONS

MR imaging-based texture analysis has the potential to differentiate squamous cell carcinoma from inverted papilloma and may, in the future, provide incremental information to the neuroradiologist.

Blood pressure-lowering effect of the sodium glucose co-transporter-2 inhibitor ertugliflozin, assessed via ambulatory blood pressure monitoring in patients with type 2 diabetes and hypertension

This study compared the blood pressure-lowering effect of ertugliflozin (1, 5, 25 mg), hydrochlorothiazide (HCTZ; 12.5 mg) and placebo in 194 patients with type 2 diabetes mellitus and hypertension for 4 weeks using ambulatory blood pressure monitoring. Endpoints (change from baseline to week 4) were: 24-h mean systolic blood pressure (SBP; primary); daytime, night-time, seated predose SBP, 24-h, daytime, night-time, seated predose diastolic blood pressure, 24-h urinary glucose excretion and fasting plasma glucose (FPG; secondary). Safety and tolerability were monitored. Significant decreases in placebo-corrected 24-h mean SBP (-3.0 to -4.0 mmHg) were recorded for all doses of ertugliflozin (for HCTZ, this was -3.2 mmHg). Daytime, but not night-time SBP was consistently reduced. Ertugliflozin produced dose-dependent significant decreases in FPG and increases in urinary glucose excretion. No notable changes in plasma renin activity or urinary aldosterone were seen. The most common adverse events were urinary tract infection, genital fungal infection, upper respiratory tract infection and musculoskeletal pain.

Sodium channel slow inactivation as a therapeutic target for myotonia congenita

OBJECTIVE

Patients with myotonia congenita have muscle hyperexcitability due to loss-of-function mutations in the chloride channel in skeletal muscle, which causes spontaneous firing of muscle action potentials (myotonia), producing muscle stiffness. In patients, muscle stiffness lessens with exercise, a change known as the warmup phenomenon. Our goal was to identify the mechanism underlying warmup and to use this information to guide development of novel therapy.

METHODS

To determine the mechanism underlying warmup, we used a recently discovered drug to eliminate muscle contraction, thus allowing prolonged intracellular recording from individual muscle fibers during induction of warmup in a mouse model of myotonia congenita.

RESULTS

Changes in action potentials suggested slow inactivation of sodium channels as an important contributor to warmup. These data suggested that enhancing slow inactivation of sodium channels might offer effective therapy for myotonia. Lacosamide and ranolazine enhance slow inactivation of sodium channels and are approved by the US Food and Drug Administration for other uses in patients. We compared the efficacy of both drugs to mexiletine, a sodium channel blocker currently used to treat myotonia. In vitro studies suggested that both lacosamide and ranolazine were superior to mexiletine. However, in vivo studies in a mouse model of myotonia congenita suggested that side effects could limit the efficacy of lacosamide. Ranolazine produced fewer side effects and was as effective as mexiletine at a dose that produced none of mexiletine's hypoexcitability side effects.

INTERPRETATION

We conclude that ranolazine has excellent therapeutic potential for treatment of patients with myotonia congenita.

MRI texture analysis predicts p53 status in head and neck squamous cell carcinoma

BACKGROUND AND PURPOSE

Head and neck cancer is common, and understanding the prognosis is an important part of patient management. In addition to the Tumor, Node, Metastasis staging system, tumor biomarkers are becoming more useful in understanding prognosis and directing treatment. We assessed whether MR imaging texture analysis would correctly classify oropharyngeal squamous cell carcinoma according to p53 status.

MATERIALS AND METHODS

A cohort of 16 patients with oropharyngeal squamous cell carcinoma was prospectively evaluated by using standard clinical, histopathologic, and imaging techniques. Tumors were stained for p53 and scored by an anatomic pathologist. Regions of interest on MR imaging were selected by a neuroradiologist and then analyzed by using our 2D fast time-frequency transform tool. The quantified textures were assessed by using the subset-size forward-selection algorithm in the Waikato Environment for Knowledge Analysis. Features found to be significant were used to create a statistical model to predict p53 status. The model was tested by using a Bayesian network classifier with 10-fold stratified cross-validation.

RESULTS

Feature selection identified 7 significant texture variables that were used in a predictive model. The resulting model predicted p53 status with 81.3% accuracy (P < .05). Cross-validation showed a moderate level of agreement (κ = 0.625).

CONCLUSIONS

This study shows that MR imaging texture analysis correctly predicts p53 status in oropharyngeal squamous cell carcinoma with ∼80% accuracy. As our knowledge of and dependence on tumor biomarkers expand, MR imaging texture analysis warrants further study in oropharyngeal squamous cell carcinoma and other head and neck tumors.

The clinical response to minocycline in multiple sclerosis is accompanied by beneficial immune changes: a pilot study

Minocycline has immunomodulatory and neuroprotective activities in vitro and in an animal model of multiple sclerosis (MS). We have previously reported that minocycline decreased gadolinium-enhancing activity over six months in a small trial of patients with active relapsing-remitting MS (RRMS). Here we report the impact of oral minocycline on clinical and magnetic resonance imaging (MRI) outcomes and serum immune molecules in this cohort over 24 months of open-label minocycline treatment. Despite a moderately high pretreatment annualized relapse rate (1.3/year pre-enrolment; 1.2/year during a three-month baseline period) prior to treatment, no relapses occurred between months 6 and 24. Also, despite very active MRI activity pretreatment (19/40 scans had gadolinium-enhancing activity during a three-month run-in), the only patient with gadolinium-enhancing lesions on MRI at 12 and 24 months was on half-dose minocycline. Levels of the p40 subunit of interleukin (IL)-12, which at high levels might antagonize the proinflammatory IL-12 receptor, were elevated over 18 months of treatment, as were levels of soluble vascular cell adhesion molecule-1. The activity of matrix metalloproteinase-9 was decreased by treatment. Thus, clinical and MRI outcomes are supported by systemic immunological changes and call for further investigation of minocycline in MS.

Resolution-dependent estimates of multiple sclerosis lesion loads

BACKGROUND

Changes in brain lesion loads assessed with magnetic resonance imaging obtained at 1.5 Telsa (T) are used as a measure of disease evolution in natural history studies and treatment trials of multiple sclerosis.

METHODS

A comparison was made between the total lesion volume and individual lesions observed on 1.5 T images and on high-resolution 4 T images. Lesions were quantified using a computer-assisted segmentation tool.

RESULTS

There was a 46% increase in the total number of lesions detected with 4 T versus 1.5 T imaging (p < 0.005). The 4 T also showed a 60% increase in total lesion volume when compared with the 1.5 T (p < 0.005). In several instances, the 1.5 T scans showed individual lesions that coalesced into larger areas of abnormality in the 4 T scans. The relationship between individual lesion volumes was linear (slope 1.231) showing that the lesion volume observed at 4 T increased with the size of the lesion detected at 1.5 T. The 4 T voxels were less than one quarter the size of those used at 1.5 T and there were no consistent differences between their signal-to-noise ratios.

CONCLUSIONS

The increase in signal strength that accompanied the increase in field strength compensated for the loss in signal amplitude produced by the use of smaller voxels. This enabled the acquisition of images with improved resolution, resulting in increased lesion detection at 4 T and larger lesion volumes.

Fitting of the beat pattern observed in NMR free-induction decay signals of concentrated carbohydrate-water solutions

A series of mathematical functions has been used to fit the proton free-induction decays (FIDs) of concentrated carbohydrate-water samples. For the solid protons, these functions included a sinc function, as well as the Fourier transforms of single and multiple Pake functions multiplied by a Gaussian broadening. The NMR signal from the mobile protons is described by an exponential function. It is found that in most cases the sinc function gives a satisfactory result and provides valuable information about the second moment M(2) and the ratio of solid to mobile protons (f(s) / f(m)). A good indication for using the sinc function is the presence of a beat in the FID. For high temperatures this approach breaks down, and a biexponential fit is more appropriate. If a clear dipolar splitting is observable in the NMR spectra, the Pake function (or a multiple Pake fit) should be used. In this case information about M(2) and f(s) / f(m) can also be obtained.

The dissolution of organic solvents from Amerlock 400 epoxy paint

The dissolution of organic solvents from containment coatings into the sump water is expected to be a key rate-controlling process, influencing the pH, the steady-state water radiolysis product concentration, and the formation of organic iodides in containment following a postulated reactor accident. The dissolution process is therefore an important component in modelling iodine behaviour in post-accident containment. The rate of release of ethyl benzene and m- and o-xylene from Amerlock 400 epoxy paint in contact with water has been measured. The release rate was found to be comparable to the release rate of methyl isobutyl ketone from various polyurethane, vinyl, and epoxy paints. The pseudo-first-order rate constant for dissolution of the solvents from these containment coatings is dependent only upon paint thickness and temperature, whereas the total amount of solvent released depends upon paint thickness. The solvent-release process is governed by the rate of uptake of water by the coupons, a Fickian diffusion-controlled process.Key words: dissolution, kinetics, organic solvents, paint.

A new local multiscale Fourier analysis for medical imaging

The Stockwell transform (ST), recently developed for geophysics, combines features of the Fourier, Gabor and wavelet transforms; it reveals frequency variation over time or space. This valuable information is obtained by Fourier analysis of a small segment of a signal at a time. Localization of the Fourier spectrum is achieved by filtering the signal with frequency-dependent Gaussian scaling windows. This multi-scale time-frequency analysis provides information about which frequencies occur and more importantly when they occur. Furthermore, the Stockwell domain can be directly inferred from the Fourier domain and vice versa. These features make the ST a potentially effective tool to visualize, analyze, and process medical imaging data. The ST has proven useful in noise reduction and tissue texture analysis. Herein, we focus on the theory and effectiveness of the ST for medical imaging. Its effectiveness and comparison with other linear time-frequency transforms, such as the Gabor and wavelet transforms, are discussed and demonstrated using functional magnetic resonance imaging data.

Organisation of the external region of the starch granule as determined by infrared spectroscopy

Attenuated total reflectance-Fourier transform infrared (ATR-FTIR) was used to study the external regions of starch granules. Native starches (wheat, potato, maize, waxy maize and amylomaize) were analysed and compared to gelatinised and acid-hydrolysed starches. The IR spectra of potato and amylomaize starches were closer to that of highly ordered acid-hydrolysed starch than the other starches. FTIR was not able to differentiate between A- and B-type crystallinity so the difference observed between starches was not related to this factor. The variation between starch varieties was interpreted in terms of the level of ordered structure present on the edge of starch granules with potato and amylomaize being more ordered on their outer regions. This could explain the high resistance of both these starches to enzyme hydrolysis.

Improved contrast in multispectral phase images derived from magnetic resonance exams of multiple sclerosis patients

We describe a method to extract data from multispectral MR exams of patients with Multiple Sclerosis (MS). The technique produces images of "spectral phase" (SP) relative to a reference tissue. SP images allow retrospective suppression of signal in the reference tissue, while maintaining high spatial resolution. Image quality in SP images was determined from MR exams of 5 MS patients selected at random from a clinical trial underway at our institute. Exams consisting of proton density weighted (PDw), T2 weighted (T2w), T1 weighted (T1w), and gadolinium-DTPA enhanced T1w (GAD) images were acquired from each patient. The MR exams were corrected for intensity nonuniformity, then filtered with an algorithm based upon anisotropic diffusion, to reduce noise. Principal component (PC) images and SP images relative to cerebrospinal fluid (SP(CSF)), normal appearing white matter (SP(NAWM)), gray matter (SP(GM)), and temporalis muscle (SP(MUS)) were then calculated. Contrast between tissues and MS lesions in the MR and derived images was then determined by measuring the signal-difference-to-noise ratio (dSNR) between tissues. Our new SP images provided better tissue contrast than the original MR, filtered MR, and PC images. Contrast improved between CSF and NAWM (from 19.5 to 56), CSF and GM (from 15 to 36), GM and NAWM (from 8 to 14), MS lesions and CSF (from 16 to 35), and between MS lesions and NAWM (from 24 to 47). (Maximum contrast in the original MR images compared to maximum contrast in the SP images.) The additional contrast in SP images may aid the quantification and analysis of lesion activity in MR exams of MS patients.

Definition of the rheological glass transition temperature in association with the concept of iso-free-volume

Small deformation dynamic oscillation was used to develop an index of physical significance for the rationalisation of the mechanical properties of high co-solute/biopolymer systems during vitrification. The index is based on the combined framework of Williams-Landel-Ferry equation with the free volume theory and is called the 'rheological glass transition temperature, T(g)' thus differentiating it from the empirical calorimetric T(g) used in thermal analysis. The rheological T(g) is located at the conjunction of two distinct molecular processes, namely: free-volume effects in the glass transition region and the predictions of the reaction-rate theory in the glassy state. The method of reduced variables was used to shift the mechanical spectra of shear moduli to composite curves. The temperature dependence of shift factors for all materials was identical provided that they were normalised at suitably different reference temperatures, which reflect iso-free-volume states. The treatment makes free volume the overriding parameter governing the mechanical relaxation times during vitrification of high co-solute/biopolymer systems regardless of physicochemical characteristics. We believe that potential applications resulting from this fundamental work are numerous for the food and pharmaceutical industries.

FTIR microspectroscopy study of composition fluctuations in extruded amylopectin-gelatin blends

The spatial variation in the composition of nonexpanded biopolymer blends prepared by extrusion of mixtures of gelatin with either native or pregelatinized waxy maize starch was studied using a 30-microm aperture FTIR microspectroscopy technique. The ratio of the areas of the "saccharide" bands (953-1180 cm(-1)) and the amide I and II bands (1483-1750 cm(-1)) was used to monitor the relative distributions of the two components of the blend. Two calibration methods were used to obtain amylopectin concentration values from the ratios of the IR bands. The results suggested a high degree of heterogeneity in these blends, despite the thorough mixing expected by twin-screw extrusion processing. The concentration fluctuations were greater for the blends produced by extruding gelatin and native waxy maize starch mixtures. This was in agreement with the reduced degree of conversion of the starch granules when extruded in the presence of gelatin. The FTIR 2-dimensional maps obtained suggested that in the blends produced from either native or pregelatinized starch at all concentrations studied (25/75, 50/50, and 75/25 amylopectin/gelatin) the gelatin constituted the continuous phase. The effect of the spatial resolution on the FTIR microspectroscopy results was considered and the proposed interpretation was verified by the use of polarized light microscopy and FTIR microspectroscopy acquired at higher spatial resolution (10 microm).

A semi-automatic technique for measurement of arterial wall from black blood MRI

Black blood magnetic resonance imaging (MRI) has become a popular technique for imaging the artery wall in vivo. Its noninvasiveness and high resolution make it ideal for studying the progression of early atherosclerosis in normal volunteers or asymptomatic patients with mild disease. However, the operator variability inherent in the manual measurement of vessel wall area from MR images hinders the reliable detection of relatively small changes in the artery wall over time. In this paper we present a semi-automatic method for segmenting the inner and outer boundary of the artery wall, and evaluate its operator variability using analysis of variance (ANOVA). In our approach, a discrete dynamic contour is approximately initialized by an operator, deformed to the inner boundary, dilated, and then deformed to the outer boundary. A group of four operators performed repeated measurements on 12 images from normal human subjects using both our semiautomatic technique and a manual approach. Results from the ANOVA indicate that the inter-operator standard error of measurement (SEM) of total wall area decreased from 3.254 mm2 (manual) to 1.293 mm2 (semi-automatic), and the intra-operator SEM decreased from 3.005 mm2 to 0.958 mm2. Operator reliability coefficients increased from less than 69% to more than 91% (inter-operator) and 95% (intra-operator). The minimum detectable change in wall area improved from more than 8.32 mm2 (intra-operator, manual) to less than 3.59 mm2 (inter-operator, semi-automatic), suggesting that it is better to have multiple operators measure wall area with our semi-automatic technique than to have a single operator make repeated measurements manually. Similar improvements in wall thickness and lumen radius measurements were also recorded. Since the semi-automatic technique has effectively ruled out the effect of the operator on these measurements, it may be possible to use such techniques to expand prospective studies of atherogenesis to multiple centers so as to increase access to real patient data without sacrificing reliability.