Non-Invasive Vagus Nerve Stimulation Improves Brain Lesion Volume and Neurobehavioral Outcomes in a Rat Model of Traumatic Brain Injury.

Abstract Traumatic brain injury (TBI) continues to be a major cause of death and disability worldwide. This study assessed the effectiveness of non-invasive vagus nerve stimulation (nVNS) in reducing brain lesion volume and improving neurobehavioral performance in a rat model of TBI. Animals were randomized into three experimental groups: (1) TBI with sham stimulation treatment (Control), (2) TBI treated with five lower doses (2-min) nVNS, and (3) TBI treated with five higher doses (2 × 2-min) nVNS. We used the gammaCore nVNS device to deliver stimulations. Magnetic resonance imaging studies were performed 1 and 7 days post-injury to confirm lesion volume. We observed smaller brain lesion volume in the lower dose nVNS group compared with the control group on days 1 and 7. The lesion volume for the higher dose nVNS group was significantly smaller than either the lower dose nVNS or the control groups on days 1 and 7 post-injury. The apparent diffusion coefficient differences between the ipsilateral and contralateral hemispheres on day 1 were significantly smaller for the higher dose (2 × 2 min) nVNS group than for the control group. Voxel-based morphometry analysis revealed an increase in the ipsilateral cortical volume in the control group caused by tissue deformation and swelling. On day 1, these abnormal volume changes were 13% and 55% smaller in the lower dose and higher dose nVNS groups, respectively, compared with the control group. By day 7, nVNS dampened cortical volume loss by 35% and 89% in the lower dose and higher dose nVNS groups, respectively, compared with the control group. Rotarod, beam walking, and anxiety performances were significantly improved in the higher-dose nVNS group on day 1 compared with the control group. The anxiety indices were also improved on day 7 post-injury compared with the control and the lower-dose nVNS groups. In conclusion, the higher dose nVNS (five 2 × 2-min stimulations) reduced brain lesion volume to a level that further refined the role of nVNS therapy for the acute treatment of TBI. Should nVNS prove effective in additional pre-clinical TBI models and later in clinical settings, it would have an enormous impact on the clinical practice of TBI in both civilian and military settings, as it can easily be adopted into routine clinical practice.

Predefined and data driven CT densitometric features predict critical illness and hospital length of stay in COVID-19 patients.

The aim of this study was to compare whole lung CT density histograms to predict critical illness outcome and hospital length of stay in a cohort of 80 COVID-19 patients. CT chest images on segmented lungs were retrospectively analyzed. Functional Principal Component Analysis (FPCA) was used to find the main modes of variations on CT density histograms. CT density features, the CT severity score, the COVID-GRAM score and the patient clinical data were assessed for predicting the patient outcome using logistic regression models and survival analysis. ROC analysis predictors of critically ill status: 87.5th percentile CT density (Q875)-AUC 0.88 95% CI (0.79 0.94), F1-CT-AUC 0.87 (0.77 0.93) Standard Deviation (SD-CT)-AUC 0.86 (0.73, 0.93). Multivariate models combining CT-density predictors and Neutrophil-Lymphocyte Ratio showed the highest accuracy. SD-CT, Q875 and F1 score were significant predictors of hospital length of stay (LOS) while controlling for hospital death using competing risks models. Moreover, two multivariate Fine-Gray regression models combining the clinical variables: age, NLR, Contrast CT factor with either Q875 or F1 CT-density predictors revealed significant effects for the prediction of LOS incidence in presence of a competing risk (death) and acceptable predictive performances (Bootstrapped C-index 0.74 [0.70 0.78]).

Assessing invasiveness of subsolid lung adenocarcinomas with combined attenuation and geometric feature models.

The aim of this study was to develop and test multiclass predictive models for assessing the invasiveness of individual lung adenocarcinomas presenting as subsolid nodules on computed tomography (CT). 227 lung adenocarcinomas were included: 31 atypical adenomatous hyperplasia and adenocarcinomas in situ (class H1), 64 minimally invasive adenocarcinomas (class H2) and 132 invasive adenocarcinomas (class H3). Nodules were segmented, and geometric and CT attenuation features including functional principal component analysis features (FPC1 and FPC2) were extracted. After a feature selection step, two predictive models were built with ordinal regression: Model 1 based on volume (log) (logarithm of the nodule volume) and FPC1, and Model 2 based on volume (log) and Q.875 (CT attenuation value at the 87.5% percentile). Using the 200-repeats Monte-Carlo cross-validation method, these models provided a multiclass classification of invasiveness with discriminative power AUCs of 0.83 to 0.87 and predicted the class probabilities with less than a 10% average error. The predictive modelling approach adopted in this paper provides a detailed insight on how the value of the main predictors contribute to the probability of nodule invasiveness and underlines the role of nodule CT attenuation features in the nodule invasiveness classification.

Transfemoral Approach to Induce Transient Middle Cerebral Artery Occlusion in Rats: The Use of Commercially Available Endovascular Wires.

BACKGROUND: Animal models of stroke play a crucial role in determining the pathophysiology of stroke progression and assessment of any new therapeutic approaches. Transient middle cerebral artery occlusion (tMCAo) in rodent models are the most common site-specific type of ischemia because of their relevance to the clinical setting. Compared with the intraluminal filament technique for inducing tMCAo, the transfemoral approach using endovascular wires is relatively a new technique METHODS: Here we present the use of commercially available wires used for neuro-endovascular surgical procedures to induce tMCAo in rats via a transfemoral approach. We used male Wistar rats in four groups to assess the effect of occlusion time (1 vs. 2 hours) and the wire type (PT2 TM 0.014″ vs. TransendTM EX, 0.014″, Boston Scientific, MA, USA). Infarct volume, edema, neurological deficits, and pro-inflammatory/anti-inflammatory blood biomarkers were used as outcome measures. RESULTS: We observed a significant effect of the wire type on the infarct volume (p value = 0.0096) where infarcts were slightly larger in the PT2 wiregroups. However, the occlusion time had no significant effect on infarct volume, even though the interaction between wire-type * occlusion-time was significant (p value = 0.024). Also, the amount of edema and blood pro-inflammatory/anti-inflammatory biomarkers were not statistically different among the wire-type and occlusion-time groups. CONCLUSIONS: The choice of appropriate endovascular wire should probably be the focus of the study design instead of the occlusion time when planning an experiment. The transfemoral approach using endovascular wires for inducing tMCAo in rats provides a more consistent outcome with fewer complications compared with suture filament models.

Exploration of Multiparameter Hematoma 3D Image Analysis for Predicting Outcome After Intracerebral Hemorrhage.

BACKGROUND: Rapid diagnosis and proper management of intracerebral hemorrhage (ICH) play a crucial role in the outcome. Prediction of the outcome with a high degree of accuracy based on admission data including imaging information can potentially influence clinical decision-making practice. METHODS: We conducted a retrospective multicenter study of consecutive ICH patients admitted between 2012-2017. Medical history, admission data, and initial head computed tomography (CT) scan were collected. CT scans were semiautomatically segmented for hematoma volume, hematoma density histograms, and sphericity index (SI). Discharge unfavorable outcomes were defined as death or severe disability (modified Rankin Scores 4-6). We compared (1) hematoma volume alone; (2) multiparameter imaging data including hematoma volume, location, density heterogeneity, SI, and midline shift; and (3) multiparameter imaging data with clinical information available on admission for ICH outcome prediction. Multivariate analysis and predictive modeling were used to determine the significance of hematoma characteristics on the outcome. RESULTS: We included 430 subjects in this analysis. Models using automated hematoma segmentation showed incremental predictive accuracies for in-hospital mortality using hematoma volume only: area under the curve (AUC): 0.85 [0.76-0.93], multiparameter imaging data (hematoma volume, location, CT density, SI, and midline shift): AUC: 0.91 [0.86-0.97], and multiparameter imaging data plus clinical information on admission (Glasgow Coma Scale (GCS) score and age): AUC: 0.94 [0.89-0.99]. Similarly, severe disability predictive accuracy varied from AUC: 0.84 [0.76-0.93] for volume-only model to AUC: 0.88 [0.80-0.95] for imaging data models and AUC: 0.92 [0.86-0.98] for imaging plus clinical predictors. CONCLUSIONS: Multiparameter models combining imaging and admission clinical data show high accuracy for predicting discharge unfavorable outcome after ICH.

A Brief Review of Edema-Adjusted Infarct Volume Measurement Techniques for Rodent Focal Cerebral Ischemia Models with Practical Recommendations.

BACKGROUND: Determining cerebral infarction volume is an important part of preclinical studies to determine the benefit of potential therapies on stroke outcome. A well-known problem in determining the actual infarction volume of rodent models is the presence of edema. Because of this, algorithms must be utilized to obtain the edema-adjusted (E A)-infarct volume. Different methods based on 2,3,5-triphenyltetrazolium hydrochloride (TTC) staining have been published describing algorithms to determine the E A-infarct volume. MATERIALS AND METHODS: Simulated models of infarction and corresponding swelling were employed to determine which absolute method of calculation (Lin et al., Reglodi et al., or Belayev et al.) is the most accurate in calculating the absolute E A-infarct volume. RESULTS: The Reglodi and Belayev methods were statistically more accurate in measuring E A-infarct volume than Lin's method, p = 0.0078. Though there was no significant difference between Reglodi's and Belayev's methods for the E A-infarction volume calculation, Reglodi's approach was closer to the ground-truth infarct volume while also being simpler and more straightforward to use. CONCLUSION: We recommend that Reglodi's method, that is E A-infarct volume = infarct volume × (contralateral hemisphere/ipsilateral hemisphere), to be used in calculating E A-infarct volume in TTC stained rodent brains. Further, factors such as inhomogeneous infarction distribution in a given brain slice can also contribute to the error in volume calculation. Therefore, the average of the infarct area obtained from anterior and posterior views of a given slice should be used to account for the variation. Considering different factors, we have provided a summary recommendation for calculating the infarction volume.

Lung Density Analysis Using Quantitative Chest CT for Early Prediction of Chronic Lung Allograft Dysfunction.

BACKGROUND: Chronic lung allograft dysfunction (CLAD) limits long-term survival after lung transplantation (LTx). Early detection or prediction of CLAD can lead to changes in patient management that, in turn, may improve prognosis. The purpose of this study was to investigate the utility of quantitative computed tomography (CT) lung density analysis in early prediction of CLAD. METHODS: This retrospective cohort was drawn from all consecutive adult, first LTxs performed between 2006 and 2011. Post-transplant monitoring included scheduled surveillance bronchoscopies with concurrent pulmonary-functions tests and low-dose chest CT. Quantitative density metrics (QDM) derived from CT scans obtained at the time of 10%-19% decline in forced expiratory volume in 1 second (FEV1) were evaluated: 114 bilateral LTx recipients (66 with CLAD and 48 stable) and 23 single LTx recipients (11 with CLAD, 12 stable) were included in the analysis. RESULTS: In both single and double LTx, at the time of 10%-19% drop in FEV1 from baseline, the QDM was higher in patients who developed CLAD within 3 years compared with those patients who remained stable for at least 3.5 years. The area under the receiver operating characteristic curve (AUC) was 0.89 for predicting CLAD in single LTx and 0.63 in bilateral LTx. A multipredictor AUC accounting for FEV1, QDM, presence of consolidation, and ground glass opacities increased the AUC to 0.74 in double LTx. CONCLUSIONS: QDM derived from a CT histogram at the time of early drop in FEV1 may allow prediction of CLAD in patients after single or double LTx.

Histogram-based models on non-thin section chest CT predict invasiveness of primary lung adenocarcinoma subsolid nodules.

109 pathologically proven subsolid nodules (SSN) were segmented by 2 readers on non-thin section chest CT with a lung nodule analysis software followed by extraction of CT attenuation histogram and geometric features. Functional data analysis of histograms provided data driven features (FPC1,2,3) used in further model building. Nodules were classified as pre-invasive (P1, atypical adenomatous hyperplasia and adenocarcinoma in situ), minimally invasive (P2) and invasive adenocarcinomas (P3). P1 and P2 were grouped together (T1) versus P3 (T2). Various combinations of features were compared in predictive models for binary nodule classification (T1/T2), using multiple logistic regression and non-linear classifiers. Area under ROC curve (AUC) was used as diagnostic performance criteria. Inter-reader variability was assessed using Cohen's Kappa and intra-class coefficient (ICC). Three models predicting invasiveness of SSN were selected based on AUC. First model included 87.5 percentile of CT lesion attenuation (Q.875), interquartile range (IQR), volume and maximum/minimum diameter ratio (AUC:0.89, 95%CI:[0.75 1]). Second model included FPC1, volume and diameter ratio (AUC:0.91, 95%CI:[0.77 1]). Third model included FPC1, FPC2 and volume (AUC:0.89, 95%CI:[0.73 1]). Inter-reader variability was excellent (Kappa:0.95, ICC:0.98). Parsimonious models using histogram and geometric features differentiated invasive from minimally invasive/pre-invasive SSN with good predictive performance in non-thin section CT.

Inducing Different Brain Injury Levels Using Shock Wave Lithotripsy.

OBJECTIVES: To assess the feasibility of inducing different severities of shock wave (SW)-induced traumatic brain injury (TBI) using lithotripsy. METHODS: Wistar rats (n = 36) were divided into 2 groups: group 1 (n = 20) received 5 SW pulses, and group 2 (n = 16) received 15 SWs pulses. The SW pulses were delivered to the right side of the frontal cortex. Neurologic and behavioral assessments (Garcia test, beam walking, rotarod, and elevated plus maze) were performed at the baseline and at 3, 6, 24, 72, and 168 hours after injury. At day 7 after injury (168 hours), we performed cerebral angiography to assess the presence of cerebral vasospasm and vascular damage due to SW-induced TBI. At the conclusion of the study, the animals were euthanized to assess damage to brain tissue using an overall histologic severity score. RESULTS: The Garcia score was significantly higher, and the anxiety index (based on the elevated plus maze) was significantly lower in group 1 compared to group 2 (P < .05). The anxiety index for group 1 returned to the baseline level in a fast nonlinear fashion, whereas the anxiety index for group 2 followed a distinct slow linear reduction. Cerebral angiograms revealed a more severe vasospasm for the animals in group 2 compared to group 1 (P = .027). We observed a statistically significant difference in the overall histologic severity scores between the groups. The median (interquartile range) overall histologic severity scores for groups 1 and 2 were 3.0 (2.75) and 6.5 (6.0), respectively (P = .023). CONCLUSIONS: We have successfully established different SW-induced TBI severities in our SW-induced TBI model by delivering different numbers of SW pulses to brain tissue.

Quantitative chest CT for subtyping chronic lung allograft dysfunction and its association with survival.

Chronic lung allograft dysfunction (CLAD) is a major cause of mortality in lung transplant recipients. CLAD can be sub-divided into at least 2 subtypes with distinct mortality risk characteristics: restrictive allograft syndrome (RAS), which demonstrates increased overall computed tomography (CT) lung density in contrast with bronchiolitis obliterans syndrome (BOS), which demonstrates reduced overall CT lung density. This study aimed to evaluate a reader-independent quantitative density metric (QDM) derived from CT histograms to associate with CLAD survival. A retrospective study evaluated CT scans corresponding to CLAD onset using pulmonary function tests in 74 patients (23 RAS, 51 BOS). Two different QDM values (QDM1 and QDM2) were calculated using CT lung density histograms. Calculation of QDM1 includes the extreme edges of the histogram. Calculation of QDM2 includes the central region of the histogram. Kaplan-Meier analysis and Cox regression analysis were used for CLAD prognosis. Higher QDM values were significantly associated with decreased survival. The hazard ratio for death was 3.2 times higher at the 75th percentile compared to the 25th percentile using QDM1 in a univariate model. QDM may associate with CLAD patient prognosis.

Changes in [18F]Fluorodeoxyglucose Activities in a Shockwave-Induced Traumatic Brain Injury Model Using Lithotripsy.

We present a longitudinal study of cerebral metabolism using [18F]fluorodeoxyglucose (FDG) positron emission tomography (PET) in a rat model of shockwave-induced traumatic brain injury (SW-TBI). Anesthetized rats received 5 or 10 SW pulses to the right anterior lateral or dorsal frontal regions using SW lithotripsy. Animals were scanned for FDG uptake at baseline, 3 h post-injury, and 3 days post-injury, using a small animal PET/computed tomography (CT) scanner. FDG uptake at all time-points was quantified as the ratio of brain activity relative to peripheral activity in the left ventricle (LV) in the heart (Abrain/ALV) for the entire brain, each hemisphere, and four cortices (motor, cingulate, somatosensory, and retrosplenial). The mixed-designed models analysis of variance (ANOVA) for the hemispheric and global FDG uptake ratio showed a significant effect of the time-of-scan (p = 0.038) and measured region (p = 6.12e-09). We also observed a significant effect of the time-of-scan (p = 0.046) and measured region (p = 2.28e-09) for the FDG uptake ratio in four cortical regions. None of the measurements (global or local) showed a significant effect for the number of SW pulses (5 or 10) or SW location (lateral or dorsal frontal regions). Our data suggest that SW-TBI causes hypermetabolism on the impact side of the rat brain at 3 h post-injury compared with the baseline measurements. However, the increase in FDG uptake by day 3 post-injury was not significant. Further studies on post-TBI metabolic changes are needed to understand better the pathophysiology of the injury.

The role of biomechanical anatomical modeling via computed tomography for identification of restrictive allograft syndrome.

Chronic lung allograft dysfunction (CLAD) reduces long-term graft survival. It is important to distinguish CLAD subtypes: bronchiolitis obliterans syndrome (BOS) and restrictive allograft syndrome (RAS) as RAS has a worse prognosis and accurate subtyping could facilitate targeted treatments. However, the current diagnosis of CLAD subtypes is based on pulmonary function test (PFT) results that reflect global estimates of lung function; anatomical modeling based on computed tomography (CT) has the potential to provide detailed analysis of global and regional lung function. The purpose of this study is to evaluate the utility of CT-based anatomical modeling for the identification of RAS. This retrospective study included 51 patients (CLAD: 17 BOS and 17 RAS, control: 17 No-CLAD). CT data were assessed using a biomechanical model-based platform (MORFEUS) to characterize changes in lung deformation between baseline and disease onset. Lung deformation demonstrated high sensitivity and specificity (>80%) in differentiating RAS from BOS (P<.0001) and No-CLAD (P<.0001). There were matching radiological reading and inward deformation abnormalities in 79% of lung sections in patients with RAS. Anatomical modeling is complementary to conventional assessment in the diagnosis of RAS and potentially provides quantitative data that can help in the characterization and detailed assessment of heterogeneous lung parenchymal disease.

A Modified Method for Creating Elastase-Induced Aneurysms by Ligation of Common Carotid Arteries in Rabbits and Its Effect on Surrounding Arteries.

BACKGROUND AND PURPOSE: Rabbit models of intracranial aneurysms are frequently used in pre-clinical settings. This study aimed to demonstrate an alternative, extravascular method for creating elastase-induced aneurysms, and how ligation of the right common carotid arteries (RCCA) can impact flow redistribution into left CCA (LCCA). METHODS: Elastase-induced aneurysms in 18 New Zealand rabbits (4.14 ± 0.314 kg) were created by applying 3-5 U of concentrated elastase solution to the exterior of the right and left CCA roots (RCCA and LCCA). After the induction of the aneurysm, the aneurysm was either kept intact to the rest of the corresponding CCA, severed from the rest of the CCA to allow for a free standing aneurysm, or was anchored to nearby tissue to influence the angle and orientation of the aneurysm with respect to the parent vessel. Ultrasound studies were performed before and after creation of aneurysms to collect blood flow measurements inside the aneurysm pouch and surrounding arteries. Prior to sacrificing the animals, computed tomography angiography studies were performed. Harvested aneurysmal tissues were used for histological analysis. RESULTS: Elastase-induced aneurysms were successfully created by the extravascular approach. Histological studies showed that the biological response was similar to human cerebral aneurysms and previously published elastase-induced rabbit aneurysm models. Ultrasound measurements indicated that after the RCCA was ligated, blood flow significantly increased in the LCCA at one-month follow-up. CONCLUSION: An alternate method for creating elastase-induced aneurysms has been demonstrated. The novel aspects of our method allow for ligation of one or both common carotid arteries to create a single or bilateral aneurysm with an ability to control the orientation of the induced aneurysm.

Comparison of CT perfusion summary maps to early diffusion-weighted images in suspected acute middle cerebral artery stroke.

OBJECTIVES: To assess the accuracy and reliability of one vendor's (Vital Images, Toshiba Medical, Minnetonka, MN) automated CT perfusion (CTP) summary maps in identification and volume estimation of infarcted tissue in patients with acute middle cerebral artery (MCA) distribution infarcts. SUBJECTS AND METHODS: From 1085 CTP examinations over 5.5 years, 43 diffusion-weighted imaging (DWI)-positive patients were included who underwent both CTP and DWI <12 h after symptom onset, with another 43 age-matched patients as controls (DWI-negative). Automated delay-corrected postprocessing software (DC-SVD) generated both infarct "core only" and "core+penumbra" CTP summary maps. Three reviewers independently tabulated Alberta Stroke Program Early CT scores (ASPECTS) of both CTP summary maps and coregistered DWI. RESULTS: Of 86 included patients, 36 had DWI infarct volumes ≤70 ml, 7 had volumes >70 ml, and 43 were negative; the automated CTP "core only" map correctly classified each as >70 ml or ≤70 ml, while the "core+penumbra" map misclassified 4 as >70 ml. There were strong correlations between DWI volume with both summary map-based volumes: "core only" (r=0.93), and "core+penumbra" (r=0.77) (both p<0.0001). Agreement between ASPECTS scores of infarct core on DWI with summary maps was 0.65-0.74 for "core only" map, and 0.61-0.65 for "core+penumbra" (both p<0.0001). Using DWI-based ASPECTS scores as the standard, the accuracy of the CTP-based maps were 79.1-86.0% for the "core only" map, and 83.7-88.4% for "core+penumbra." CONCLUSION: Automated CTP summary maps appear to be relatively accurate in both the detection of acute MCA distribution infarcts, and the discrimination of volumes using a 70 ml threshold.

Image quality improvement in submillisievert computed tomographic colonography using a fast 3-dimensional noise reduction method.

OBJECTIVE: The objective of this study was to evaluate the image quality in submillisievert computed tomographic colonography (CTC) images using a structure preserving diffusion denoising method. METHODS: Image quality was compared before and after denoising in 31 patients. One hundred twenty-kilovolt, 30-mAs prone CTC scans were used as reference and compared with submillisievert 140-kV, 10-mAs supine scans. Two readers assessed 2-dimensional and endoluminal image quality. The image noise and the signal-to-noise ratio were measured. RESULTS: After denoising, image quality scores improved in both supine series and prone series (P < 0.0001), with the submillisievert denoised images being equal to or better than the native prone reference images. In both the supine images and the prone images, the noise was reduced by a factor of 2 and the signal-to-noise ratio was significantly higher (P < 0.001). The signal-to-noise ratio in the denoised submillisievert images was higher than those in the native prone images (P < 0.001). CONCLUSIONS: The structure preserving diffusion denoising method preserves the image quality in submillisievert CTC images compared with the native 30-mAs reference images.

Image quality improvement using an image-based noise reduction algorithm: initial experience in a phantom model for urinary stones.

OBJECTIVE: To determine signal-to-noise (SNR), contrast-to-noise ratio, and segmentation error measurements in various low-dose computed tomographic (CT) acquisitions of an anthropomorphic phantom containing urinary stones before and after implementation of a structure-preserving diffusion (SPD) denoising algorithm, and to compare the measurements with those of standard-dose CT acquisitions. METHODS: After institutional review board approval, written informed consent was waived and 36 calcium oxalate stones were evaluated after CT acquisitions in an anthropomorphic phantom at variable tube currents (33-137 mA s). The SPD denoising algorithm was applied to all images. Signal-to-noise ratio, contrast-to-noise ratio, and expected segmentation error were determined using manually drawn regions of interest to quantify the effect of the noise reduction on the image quality. RESULTS: The value of segmentation error measurements using the SPD denoising algorithm obtained at tube currents as low as 33 mA s (up to 75% dose reduction level) were similar to standard imaging at 137 mA s. The denoised images at reduced doses up to 75% dose reduction have higher SNR than the standard-dose images without denoising (P < 0.005). Stepwise regression showed significant (P < 0.001) effect of dose length product on SNR, and segmentation error measurements. CONCLUSIONS: Based on objective noise-related image quality metrics, the SPD denoising algorithm may be useful as a robust and fast tool, and it has the potential to improve image quality in low-dose CT ureter protocols.