TAK-3 Inhibits Lipopolysaccharide-Induced Neuroinflammation in Traumatic Brain Injury Rats Through the TLR-4/NF-κB Pathway.

Purpose: The activation of the inflammatory response is regarded as a pivotal factor in the pathogenesis of TBI. Central nervous system infection often leads to the exacerbation of neuroinflammation following TBI, primarily caused by Gram-negative bacteria. This study aims to elucidate the effects of the novel anti-inflammatory drug TAK-3 on LPS-induced neuroinflammation in TBI rats. Methods: In conjunction with the rat controlled cortical impact model, we administered local injections of Lipopolysaccharide to the impact site. Subsequently, interventions were implemented through intraperitoneal injections of TAK-3 and NF-κB activitor2 to modulate the TLR4/NF-κB axis The impact of LPS on neurological function was assessed using mNSS, open field test, and brain water content measurement. Inflammatory markers, including TNF-α, IL-1ß, IL-6 and IL-10 were assessed to evaluate the condition of neuritis by Elisa. The activation of the TLR-4/NF-κB signaling pathway was detected by immunofluorescence staining and Western blot to assess the anti-inflammatory effects of TAK-3. Results: The administration of LPS exacerbated neurological damage in rats with TBI, as evidenced by a reduction in motor activity and an increase in anxiety-like behavior. Furthermore, LPS induced disruption of the blood-brain barrier integrity and facilitated the development of brain edema. The activation of microglia and astrocytes by LPS at the cellular and molecular levels has been demonstrated to induce a significant upregulation of neuroinflammatory factors. The injection of TAK-3 attenuated the neuroinflammatory response induced by LPS. Conclusion: The present study highlights the exacerbating effects of LPS on neuroinflammation in TBI through activation of the TLR-4/NF-κB signaling pathway. TAK-3 can modulate the activity of this signaling axis, thereby attenuating neuroinflammation and ultimately reducing brain tissue damage.

The Effect of Dexamethasone on Neuroinflammation and Cerebral Edema in Rats With Traumatic Brain Injury Combined With Seawater Drowning.

OBJECTIVE: To investigate the effect and mechanism of dexamethasone (DX) on axonal injury after traumatic brain injury (TBI) combined with seawater drowning (SWD) in rats. METHODS: To gain an in-depth understanding of TBI + SWD in rats, we established the compound injury model of rats by the Marmarou method and intratracheal pumping of seawater to simulate the pathological conditions. Rats in the DX group received intraperitoneal injections of DX (1 mg/kg) immediately after injury, and rats in the sham group and TBI + SWD group received intraperitoneal injections of the same amount of normal saline. RESULTS: Hematoxylin-eosin (HE) showed that DX improved matrix looseness, cell swelling, and nuclear condensation 168 hours after injury. Immunohistochemistry (IHC) staining showed that the protein expression of AQP4 was decreased in the DX group compared with the TBI + SWD group from 12 hours to 168 hours after injury. DX decreased the modified neurological severity score (mNSS) significantly at 24 hours and 168 hours after injury (P < 0.05). At 72 h and 168 h after injury, DX significantly lowered the expressions of IL-8 and TNF-α (P < 0.05). CONCLUSION: DX may play a neuroprotective role by reducing cerebral edema and inflammatory response after TBI + SWD injury in rats.

Association between Lipid-Lowering Drugs and Traumatic Subdural Hemorrhage: A Mendelian Randomization Study.

BACKGROUND: There are current clinical observations that atorvastatin may promote subdural hematoma resorption. We aimed to assess the causal effects of lipid-lowering agents 3-hydroxy-3-methylglutaryl coenzyme A reductase (HMGCR) inhibitors, Proproteinconvertase subtilisin/kexin type 9 (PCSK9) inhibitors and Niemann-Pick C1-like protein 1 (NPC1L1) inhibitors on traumatic subdural hematomas. METHODS: We used genetic instruments to proxy lipid-lowering drug exposure, with genetic instruments being genetic variants within or near low-density lipoprotein (LDL cholesterol)-associated drug target genes. These were analyzed by using a two-sample Mendelian randomization (MR) study. RESULTS: A causal relationship was found between HMGCR inhibitors and traumatic subdural hematoma (Inverse variance weighted (ß = -0.7593341 (Odds Ratio (OR) = 0.4679779), p = 0.008366947 < 0.05)). However, no causal relationship was found between PCSK9 inhibitors and NPC1L1 inhibitors and traumatic subdural hematoma (PCSK9 inhibitors: Inverse variance weighted (ß = 0.23897796 (OR = 1.2699505), p = 0.1126327), NPC1L1 inhibitors: Inverse variance weighted (ß = -0.02118558 (OR = 0.9790373), p = 0.9701686)). Sensitivity analysis of the data revealed good stability of the results. CONCLUSIONS: This two-sample MR study suggests a potential causal relationship between HMGCR inhibition (atorvastatin) and traumatic subdural hemorrhage.

Predictive value of cyst/tumor volume ratio of pituitary adenoma for tumor cell proliferation.

BACKGROUND: MRI has been widely used to predict the preoperative proliferative potential of pituitary adenoma (PA). However, the relationship between the cyst/tumor volume ratio (C/T ratio) and the proliferative potential of PA has not been reported. Herein, we determined the predictive value of the C/T ratio of PA for tumor cell proliferation. METHODS: The clinical data of 72 patients with PA and cystic change on MRI were retrospectively analyzed. PA volume, cyst volume, and C/T ratio were calculated. The corresponding intraoperative specimens were collected. Immunohistochemistry and hematoxylin-eosin staining were performed to evaluate the Ki67 index and nuclear atypia. Patients were categorized according to the Ki67 index (< 3% and ≥ 3%) and nuclear atypia (absence and presence). Univariate and multivariate analyses were used to identify the significant predictors of the Ki67 index and nuclear atypia. The receiver operating characteristic curve assessed the prediction ability of the significant predictors. RESULTS: Larger tumor volumes, smaller cyst volumes, and lower C/T ratios were found in patients with higher Ki67 indexes and those with nuclear atypia (P < 0.05). C/T ratio was an independent predictor of the Ki67 index (odds ratio = 0.010, 95% confidence interval = 0.000-0.462) and nuclear atypia (odds ratio = 0.010, 95% confidence interval = 0.000-0.250). The predictive value of the C/T ratio did not differ significantly from that of tumor volume (P > 0.05) but was better than that of cyst volume (P < 0.05). The area under the curve of the C/T ratio for predicting the Ki67 index and nuclear atypia was larger than that for predicting cyst volume and tumor volume. CONCLUSIONS: C/T ratios can be used to predict PA tumor proliferation preoperatively. Our findings may facilitate the selection of surgery timing and the efficacy evaluation of surgery.

MRI 3D SPACE T2WI for Pituitary Adenoma Cavernous Sinus Invasion Diagnosis.

OBJECTIVE: This study aims to assess the utility of magnetic resonance imaging (MRI) 3D SPACE T2-weighted imaging (T2WI) sequences in evaluating cavernous sinus invasion by pituitary adenomas. METHODS: Data were collected from patients who underwent continuous pituitary MRIexaminations at the Medical Imaging Center of our hospital from October 2019 to February 2021. Eligible cases were evaluated for sagittal and axial T1WI sequences, coronal 3D SPACE T2WI sequences, and sagittal and coronal enhanced T1-weighted imaging (T1WI) sequences using the INFINITT PACS workstation. The Wilcoxon signed-rank test for paired samples and the Mann-Whitney U test for 2 independent samples were used to statistically analyze differences in image quality scores among various groups. In addition, the sensitivity, specificity, positive predictive value, and negative predictive value of each observation index were compared with intraoperative results. RESULTS: 3D SPACE T2WI showed superior cavernous sinus imaging quality compared with contrast enhanced T1WI and T2WI plain scans (P < 0.05). The sensitivity, specificity, positive predictive value, and negative predictive value were 100%, 90.0%, 55.60%, and 100.0%, respectively. The accuracy for pituitary adenoma invasiveness diagnosis based on cavernous sinus medial wall integrity was 94.40%. CONCLUSIONS: The imaging quality of the medial wall of the cavernous sinus on the 3D SPACE T2WI plain scan sequence surpassed that of contrast enhanced T1WI TSE-enhanced scans and T2WI TSE plain scans. The continuous observation of the medial wall of the cavernous sinus using this sequence holds great diagnostic value for assessing cavernous sinus invasion by pituitary adenomas. This strategy is more reliable than traditional MRI observation indicators.

Multi-center application of a convolutional neural network for preoperative detection of cavernous sinus invasion in pituitary adenomas.

OBJECTIVE: Cavernous sinus invasion (CSI) plays a pivotal role in determining management in pituitary adenomas. The study aimed to develop a Convolutional Neural Network (CNN) model to diagnose CSI in multiple centers. METHODS: A total of 729 cases were retrospectively obtained in five medical centers with (n = 543) or without CSI (n = 186) from January 2011 to December 2021. The CNN model was trained using T1-enhanced MRI from two pituitary centers of excellence (n = 647). The other three municipal centers (n = 82) as the external testing set were imported to evaluate the model performance. The area-under-the-receiver-operating-characteristic-curve values (AUC-ROC) analyses were employed to evaluate predicted performance. Gradient-weighted class activation mapping (Grad-CAM) was used to determine models' regions of interest. RESULTS: The CNN model achieved high diagnostic accuracy (0.89) in identifying CSI in the external testing set, with an AUC-ROC value of 0.92 (95% CI, 0.88-0.97), better than CSI clinical predictor of diameter (AUC-ROC: 0.75), length (AUC-ROC: 0.80), and the three kinds of dichotomizations of the Knosp grading system (AUC-ROC: 0.70-0.82). In cases with Knosp grade 3A (n = 24, CSI rate, 0.35), the accuracy the model accounted for 0.78, with sensitivity and specificity values of 0.72 and 0.78, respectively. According to the Grad-CAM results, the views of the model were confirmed around the sellar region with CSI. CONCLUSIONS: The deep learning model is capable of accurately identifying CSI and satisfactorily able to localize CSI in multicenters.

SIRT1-Mediated HMGB1 Deacetylation Suppresses Neutrophil Extracellular Traps Related to Blood-Brain Barrier Impairment After Cerebral Venous Thrombosis.

Cerebral venous thrombosis (CVT) is a neurovascular disease with recently increasing incidence. Aseptic inflammatory responses play an important role in the pathology of CVT. Recent studies report that neutrophil extracellular traps (NETs) are major triggers of thrombosis and inflammation in stroke, but their effect on brain injury in CVT requires further validation. In this study, two CVT animal models were used to simulate superior sagittal sinus thrombosis and cortical vein thrombosis. The effects of brain tissue infiltration of NETs and the molecular mechanisms associated with NET formation were deeply explored in combination with proteomics, histology, and serology. The results showed that the cortical vein thrombosis model could be combined with more severe blood-brain barrier (BBB) disruption and showed more severe cerebral hemorrhage. Decreased Sirtuin 1 (SIRT1) expression promotes high mobility group box 1 (HMGB1) acetylation, causing increased cytosolic translocation and extracellular release, and HMGB1 can promote NET formation and recruitment. In addition, corticocerebral accumulation of NETs contributes to BBB damage. This establishes a vicious cycle between BBB damage and NET accumulation. SIRT1 mediated-HMGB1 deacetylation may play a critical role in attenuating BBB damage following CVT. This study employed a combined validation using models of venous sinus thrombosis and cortical vein thrombosis to investigate the deacetylation role of SIRT1, aiming to offer new insights into the pathological mechanisms of brain injury following CVT.

Biomarkers for predicting the severity of spinal cord injury by proteomic analysis.

Purpose: Currently, there is a shortage of the protein biomarkers for classifying spinal cord injury (SCI) severity. We attempted to explore the candidate biomarkers for predicting SCI severity. Methods: SCI rat models with mild, moderate, and severe injury were constructed with an electro-mechanic impactor. The behavior assessment and pathological examinations were conducted before and after SCI. Then, quantitative liquid chromatography-mass spectrometry (LC-MS/MS) was performed in spinal cord tissues with different extents of injury. The differentially expressed proteins (DEPs) in SCI relative to controls were identified, followed by Mfuzz clustering, function enrichment analysis, and protein-protein interaction (PPI) network construction. The differential changes of candidate proteins were validated by using a parallel reaction monitoring (PRM) assay. Results: After SCI modeling, the motor function and mechanical pain sensitivity of SCI rats were impaired, dependent on the severity of the injury. A total of 154 DEPs overlapped in the mild, moderate, and severe SCI groups, among which 82 proteins were classified in clusters 1, 2, 3, 5, and 6 with similar expression patterns at different extents of injury. DEPs were closely related to inflammatory response and significantly enriched in the IL-17 signaling pathway. PPI network showed that Fgg (Fibrinogen gamma chain), Fga (Fibrinogen alpha chain), Serpinc1 (Antithrombin-III), and Fgb (Fibrinogen beta chain) in cluster 1 were significant nodes with the largest degrees. The upregulation of the significant nodes in SCI samples was validated by PRM. Conclusion: Fgg, Fga, and Fgb may be the putative biomarkers for assessing the extent of SCI.

Pre- and Postoperative Magnetic Resonance Imaging Comparative Studies of Pituitary Tissues Following Transsphenoidal Resection of Pituitary Macroadenomas.

BACKGROUND: Magnetic resonance imaging (MRI) has become the most important radiological procedure for diagnosing and following pituitary tumors. But previous MRI studies on pituitary adenomas are mainly focused on the posterior pituitary. Few research has been done on residual normal pituitary tissue before and after transsphenoidal surgery. This retrospective cohort study investigates the pre- and postoperative magnetic resonance imaging characteristics of normal pituitary tissues regarding transsphenoidal resection of pituitary macroadenomas. METHODS: Pre- and postoperative magnetic resonance imaging scanning of 112 consecutive pituitary macroadenoma patients who underwent tumor resection via transsphenoidal approach was performed, and their medical records were studied. RESULTS: On preoperative MRI, 66 cases of pituitary stalks were identifiable, 9 of them were roughly in the middle, and 57 cases showed left or right deviation, with the angle between pituitary stalks and the sagittal plane was 5.32°-64.05° (average 21.65°). Among the 57 patients with preoperative pituitary stalk deviation, 55 of the pituitary stalk deviations improved in 1 week after surgery, and 30 cases were almost in the middle in 4-6 months after operation, with the other cases get better in varying degrees. The diameter of pituitary stalk was 1.08-3.89 mm (mean 2.36 mm) in pre-operation, and 1.29-3.43 mm (mean 2.30 mm) in 4-6 months after operation. The length of pituitary stalk was 1.41-11.74 mm (mean 6.12 mm) preoperatively, 3.61-11.63 mm (mean 6.93 mm) early postoperatively, and 5.37-17.57 mm (mean 8.83 mm) in 4-6 months after operation. Pituitary stalk was thickened or compressed on preoperative MR images, and gradually recovered to normal during postoperative period. It tended to be in the middle position and its length increased gradually until 4-6 months after operation. On preoperative MRI, 69 out of 112 patients showed residual pituitary tissues (RPT)(+) on enhanced MRI. RPT were likely located above the adenomas in somatotroph adenoma patients. Morphological restitution of postoperative normal pituitary tissues was better in lateral displacement than in superior or superolateral patterns on preoperative magnetic resonance imaging. Postoperative normal pituitary tissues usually subsided directly in superior displacement pattern on preoperative MRI, while were likely to be confined in the lateral side in lateral and superolateral displacement patients. Postoperative morphologic remodeling grade of RPT was positively correlated with the maximum diameter of pituitary adenoma (p = 0.000), but not with age. CONCLUSIONS: The larger the tumor diameter, the worse the pituitary morphological recovery after tumor resection. Relative locations of normal pituitary and adenoma tissues may be related to adenoma type and may affect postoperative reconstruction of residual normal pituitary tissues. These findings enable surgeons to distinguish pituitary tissue from residual or recurring tumor tissue on postoperative magnetic resonance imaging.

Acute subdural haematoma exacerbates cerebral blood flow disorder and promotes the development of intraoperative brain bulge in patients with severe traumatic brain injury.

BACKGROUND: Decompressive craniectomy (DC) is a routine procedure used for the treatment of severe traumatic brain injury (TBI) with concomitant acute subdural haematoma (SDH). However, certain patients are prone to developing malignant brain bulge during DC, which prolongs the operative time and worsens patient outcomes. Previous studies have shown that malignant intraoperative brain bulge (IOBB) may be associated with excessive arterial hyperaemia caused by cerebrovascular system disorders. Through a clinical retrospective analysis and prospective observations, we found that the cerebral blood flow of patients who possessed risk factors manifested high resistance and low flow velocity, which severely affected brain tissue perfusion and resulted in the occurrence of malignant IOBB. In the current literature, rat models of severe brain injury-associated brain bulge have rarely been reported. METHODS: To gain an in-depth understanding of cerebrovascular changes and the cascade of responses related to brain bulge, we introduced acute SDH into the Marmarou model for the preparation of a rat model of high intracranial pressure (ICP) to simulate the pathological conditions experienced by patients with severe brain injury. RESULTS: With the introduction of a 400-µL haematoma, significant dynamic changes occurred in ICP, mean arterial pressure, and relative blood perfusion rate of the cerebral cortical vessels. ICP increased to 56.9 ± 2.3 mmHg, mean arterial pressure showed reactive decrease, and the blood flow of cerebral cortical arteries and veins on the non-SDH-affected side decreased to < 10%. These changes could not fully recover even after DC. This resulted in generalised damage to the neurovascular unit and a lag effect to the venous blood reflux, which triggered malignant IOBB formation during DC. CONCLUSION: An excessive increase in ICP causes cerebrovascular dysfunction and brings about a cascade of damage to brain tissue, which forms the basis for the development of diffuse brain swelling. The subsequent heterogeneous responses of the cerebral arteries and veins during craniotomy may be the main cause of primary IOBB. Clinicians should pay particular attention to the redistribution of CBF to various vessels when performing DC in patients with severe TBI.

Pituitary stalk changes on magnetic resonance imaging following pituitary adenoma resection using a transsphenoidal approach.

Objective: We aimed to investigate the magnetic resonance imaging (MRI) findings and clinical significance of position and changes in morphology of the pituitary stalk following pituitary adenoma (PA) resection using a transsphenoidal approach. Methods: We collected clinical and MRI data of 108 patients with PA after transsphenoidal surgery. Diameter, length, and coronal deviation of the pituitary stalk were measured pre-, post-, and mid-term post-operatively, to observe pituitary stalk morphology. Results: Of 108 patients, 53 pituitary stalks were recognisable pre-operatively. The angle between the pituitary stalk and the median line was 7.22°-50.20° (average, 25.85°) in 22 patients with left-sided pituitary stalks and 5.32°-64.05° (average, 21.63°) in 20 patients with right-sided pituitary stalks. Of 42 patients with preoperative pituitary stalk deviation, 41 had an early postoperative recovery and 1 had increased deviation. In the mid-term postoperative period, 21 of 42 patients had pituitary stalks located centrally. In 53 patients, the pituitary stalk length was 1.41-11.74 mm (mean, 6.12 mm) pre-operatively, 3.61-11.63 mm (mean, 6.93 mm) in the early postoperative period, and 5.37-17.57 mm (mean, 8.83 mm) in the mid-term postoperative period. In the early postoperative period, 58 (53.70%) patients had posterior pituitary bright spots (PPBS) and 28 (25.92%) had diabetes insipidus (DI). Conclusion: Pre-operatively, the pituitary stalk was compressed and thinned. Post-operatively, it could be stretched to a "normal state", and its position showed a gradual centring trend. Post-operatively, the length of the pituitary stalk gradually increased. The PPBS in the early postoperative period negatively correlated with postoperative DI.

Predictive role of shock index in the early formation of cerebral infarction in patients with TBI and cerebral herniation.

Background and purpose: Traumatic brain injury (TBI) with brain herniation predisposes to posttraumatic cerebral infarction (PTCI), which in turn seriously affects the prognosis of patients. At present, there is a lack of effective indicators that can accurately predict the occurrence of PTCI. We aimed to find possible risk factors for the development of PTCI by comparing the preoperative and postoperative clinical data of TBI patients with brain herniation. Methods: The clinical data of 120 patients with craniocerebral trauma and brain herniation were retrospectively analyzed. Among them, 54 patients had cerebral infarction within 3-7 days after injury. The two groups of patients were compared through univariate and multivariate logistic regression analysis, and a classification tree model and a nomogram model were constructed. Finally, receiver operating characteristic curve analysis and decision curve analysis were conducted to analyze the clinical utility of the prediction model. Results: Logistic regression analysis showed that factors like the Glasgow Coma Scale (GCS) score (P = 0.002), subarachnoid hemorrhage (SAH) (P = 0.005), aspiration pneumonia (P < 0.001), decompressive craniectomy (P < 0.05), intracranial pressure (ICP) monitoring (P = 0.006), the shock index (SI) (P < 0.001), the mean arterial pressure (MAP) (P = 0.005), and blood glucose (GLU) (P < 0.011) appeared to show a significant statistical correlation with the occurrence of infarction (P < 0.05), while age, sex, body temperature (T), D-dimer levels, and coagulation tests were not significantly correlated with PTCI after cerebral herniation. Combined with the above factors, Classification and Regression Tree was established, and the recognition accuracy rate reached 76.67%. Conclusions: GCS score at admission, no decompressive craniectomy, no ICP monitoring, combined SAH, combined aspiration pneumonia, SI, MAP, and high GLU were risk factors for infarction, of which SI was the primary predictor of PTCI in TBI with an area under the curve of 0.775 (95% CI = 0.689-0.861). Further large-scale studies are needed to confirm these results.

A Convolutional Neural Network Model for Detecting Sellar Floor Destruction of Pituitary Adenoma on Magnetic Resonance Imaging Scans.

Objective: Convolutional neural network (CNN) is designed for image classification and recognition with a multi-layer neural network. This study aimed to accurately assess sellar floor invasion (SFI) of pituitary adenoma (PA) using CNN. Methods: A total of 1413 coronal and sagittal magnetic resonance images were collected from 695 patients with PAs. The enrolled images were divided into the invasive group (n = 530) and the non-invasive group (n = 883) according to the surgical observation of SFI. Before model training, 100 images were randomly selected for the external testing set. The remaining 1313 cases were randomly divided into the training and validation sets at a ratio of 80:20 for model training. Finally, the testing set was imported to evaluate the model performance. Results: A CNN model with a 10-layer structure (6-layer convolution and 4-layer fully connected neural network) was constructed. After 1000 epoch of training, the model achieved high accuracy in identifying SFI (97.0 and 94.6% in the training and testing sets, respectively). The testing set presented excellent performance, with a model prediction accuracy of 96%, a sensitivity of 0.964, a specificity of 0.958, and an area under the receptor operator curve (AUC-ROC) value of 0.98. Four images in the testing set were misdiagnosed. Three images were misread with SFI (one with conchal type sphenoid sinus), and one image with a relatively intact sellar floor was not identified with SFI. Conclusion: This study highlights the potential of the CNN model for the efficient assessment of PA invasion.

Cerebral venous hemodynamic responses in a mouse model of traumatic brain injury.

Traumatic brain injury (TBI) is a serious public health problem that endangers human health and is divided into primary and secondary injuries. Previous work has confirmed that changes in cerebral blood flow (CBF) are related to the progression of secondary injury, although clinical studies have shown that CBF monitoring cannot fully and accurately evaluate disease progression. These studies have almost ignored the monitoring of venous blood flow; however, as an outflow channel of the cerebral circulation, it warrants discussion. To explore the regulation of venous blood flow after TBI, the present study established TBI mouse models of different severities, observed changes in cerebral venous blood flow by laser speckle flow imaging, and recorded intracranial pressure (ICP) after brain injury to evaluate the correlation between venous blood flow and ICP. Behavioral and histopathological assessments were performed after the intervention. The results showed that there was a significant negative correlation between ICP and venous blood flow (r = -0.795, P < 0.01), and both recovered to varying degrees in the later stages of observation. The blood flow changes in regional microvessels were similar to those in venous, and the expression of angiogenesis proteins around the impact area was significantly increased. In conclusion, this study based on the TBI mouse model, recorded the changes in venous blood flow and ICP and revealed that venous blood flow can be used as an indicator of the progression of secondary brain injury.

Microscopic Transsphenoidal Resection of Giant Pituitary Adenomas: Analysis of the Factors Limiting the Degree of Resection in 73 Cases.

Purpose: To analyze the risk factors affecting the gross-total resection of giant pituitary adenomas using a transsphenoidal approach under a microscope to provide a reference basis for formulating an appropriate surgical strategy. Methods: The clinical data of patients who underwent microscopic transsphenoidal resection of giant pituitary adenomas in a single center from January 2011 to December 2020 were retrospectively analyzed. Based on magnetic resonance imaging and surgical records, the predictive factors affecting the gross-total resection of giant pituitary adenomas under microscopy were determined through univariate and multivariate analyses. Results: A total of 73 patients with giant pituitary adenomas underwent transsphenoidal microsurgery. Gross-total resection was performed in 19 cases (26%), subtotal resection in 31 cases (42%), partial resection in 21 cases (29%), and the degree of resection was <50% in only two cases (3%). After binary logistic analysis, it was found that it was more difficult to completely remove giant pituitary adenomas with a Knosp grade 3-4 [odds ratio (OR) = 0.214, 95% confidence interval (CI): 0.05-0.917; P = 0.038], greater proportion of tumor suprasellar volume (odds ratio = 0.937, 95% confidence interval: 0.898-0.978; P = 0.003), and intraoperative evidence of invasion of the cavernous sinus (odds ratio = 0.187, 95% CI: 0.039-0.898; P = 0.036). Conclusion: It is difficult to remove a giant pituitary adenoma invading the cavernous sinus completely with a higher degree of invasion of the suprasellar region using microscopic transsphenoidal surgery. The combined application of multiple surgical methods can help to improve the degree of resection during a single operation.

Application of Convolutional Neural Network in the Diagnosis of Cavernous Sinus Invasion in Pituitary Adenoma.

Objectives: Convolutional neural network (CNN) is a deep-learning method for image classification and recognition based on a multi-layer NN. In this study, CNN was used to accurately assess cavernous sinus invasion (CSI) in pituitary adenoma (PA). Methods: A total of 371 patients with PA were enrolled in the retrospective study. The cohort was divided into the invasive (n = 102) and non-invasive groups (n = 269) based on surgically confirmed CSI. Images were selected on the T1-enhanced imaging on MR scans. The cohort underwent a fivefold division of randomized datasets for cross-validation. Then, a tenfold augmented dataset (horizontal flip and rotation) of the training set was enrolled in the pre-trained Resnet50 model for transfer learning. The testing set was imported into the trained model for evaluation. Gradient-weighted class activation mapping (Grad-CAM) was used to obtain the occlusion map. The diagnostic values were compared with different dichotomizations of the Knosp grading system (grades 0-1/2-4, 0-2/3a-4, and 0-3a/3b-4). Results: Based on Knosp grades, 20 cases of grade 0, 107 cases of grade 1, 82 cases of grade 2, 104 cases of grade 3a, 22 cases of grade 3b, and 36 cases of grade 4 were recorded. The CSI rates were 0%, 3.7%, 18.3%, 37.5%, 54.5%, and 88.9%. The predicted accuracies of the three dichotomies were 60%, 74%, and 81%. The area under the receiver operating characteristic (AUC-ROC) of Knosp grade for CSI prediction was 0.84; the cutoff was 2.5 with a Youden value of 0.62. The accuracies of the CNN model ranged from 0.80 to 0.96, with AUC-ROC values ranging from 0.89 to 0.98. The Grad-CAM saliency maps confirmed that the region of interest of the model was around the sellar region. Conclusions: We constructed a CNN model with a high proficiency at CSI diagnosis. A more accurate CSI identification was achieved with the constructed CNN than the Knosp grading system.

Cerebral Blood Flow Disorder in Acute Subdural Hematoma and Acute Intraoperative Brain Bulge.

Context: Acute subdural hematoma (ASDH) has a high incidence and high mortality. During surgery for ASDH, brain tissue sometimes rapidly swells and protrudes into the bone window during or after removal of the hematoma. This phenomenon, known as acute intraoperative brain bulge, progresses rapidly and can cause ischemic necrosis of brain tissue or even mortality. The mechanism of this phenomenon remains unclear. Objective: To investigate the changes in cerebral surface blood flow during ASDH and acute intraoperative brain bulge in rats. Methods: Adult male Sprague-Dawley rats were selected to establish an ASDH model, and acute intraoperative brain bulge was induced by late-onset intracranial hematoma. The changes in cerebral surface blood flow during ASDH and acute intraoperative brain bulge were observed with a laser speckle imaging system, and intracranial pressure (ICP) was monitored. Results: ICP in rats increased significantly after ASDH (P < 0.05). The blood perfusion rate (BPR) values of the superior sagittal sinus, collateral vein and artery decreased significantly in rats with subdural hematomas (P < 0.05). There was no significant difference between the preoperative and 90-min postoperative BPR values of rats. ICP was significantly increased in rats with acute intraoperative brain bulge (P < 0.05) and decreased significantly after the removal of delayed hematomas (P < 0.05). The BPR of the superior sagittal sinus, collateral vein and artery decreased significantly during brain bulge (P < 0.05). After the removal of delayed hematomas, BPR increased significantly, but it remained significantly different from the values measured before brain bulge (P < 0.05). Conclusion: ASDH may cause not only high intracranial pressure but also cerebral blood circulation disorders. Brain bulge resulting from late-onset intracranial hematoma may aggravate these circulation disorders. If the cause of brain bulge in a given patient is late-onset intracranial hematoma, clinicians should promptly perform surgery to remove the hematoma and relieve circulation disorders, thus preventing more serious complications.

A novel rat model for cerebral venous sinus thrombosis: verification of similarity to human disease via clinical analysis and experimental validation.

BACKGROUND: Cerebral venous sinus thrombosis (CVST) is a rare neurovascular disorder with highly variable manifestations and clinical courses. Animal models properly matched to the clinical form of CVST are necessary for elucidating the pathophysiology of the disease. In this study, we aimed to establish a rat model that accurately recapitulates the clinical features of CVST in human patients. METHODS: This study consisted of a clinical analysis and animal experiments. Clinical data for two centres obtained between January 2016 and May 2021 were collected and analysed retrospectively. In addition, a Sprague-Dawley rat model of CVST was established by inserting a water-swellable rubber device into the superior sagittal sinus, following which imaging, histological, haematological, and behavioural tests were used to investigate pathophysiological changes. Principal component analysis and hierarchical clustering heatmaps were used to evaluate the similarity between the animal models and human patients. RESULTS: The imaging results revealed the possibility of vasogenic oedema in animal models. Haematological analysis indicated an inflammatory and hypercoagulable state. These findings were mostly matched with the retrospective clinical data. Pathological and serological tests further revealed brain parenchymal damage related to CVST in animal models. CONCLUSIONS: We successfully established a stable and reproducible rat model of CVST. The high similarity between clinical patients and animal models was verified via cluster analysis. This model may be useful for the study of CVST pathophysiology and potential therapies.

Machine-Learning Prediction of Postoperative Pituitary Hormonal Outcomes in Nonfunctioning Pituitary Adenomas: A Multicenter Study.

Objective: No accurate predictive models were identified for hormonal prognosis in non-functioning pituitary adenoma (NFPA). This study aimed to develop machine learning (ML) models to facilitate the prognostic assessment of pituitary hormonal outcomes after surgery. Methods: A total of 215 male patients with NFPA, who underwent surgery in four medical centers from 2015 to 2021, were retrospectively reviewed. The data were pooled after heterogeneity assessment, and they were randomly divided into training and testing sets (172:43). Six ML models and logistic regression models were developed using six anterior pituitary hormones. Results: Only thyroid-stimulating hormone (p < 0.001), follicle-stimulating hormone (p < 0.001), and prolactin (PRL; p < 0.001) decreased significantly following surgery, whereas growth hormone (GH) (p < 0.001) increased significantly. The postoperative GH (p = 0.07) levels were slightly higher in patients with gross total resection, but the PRL (p = 0.03) level was significantly lower than that in patients with subtotal resection. The optimal model achieved area-under-the-receiver-operating-characteristic-curve values of 0.82, 0.74, and 0.85 in predicting hormonal hypofunction, new deficiency, and hormonal recovery following surgery, respectively. According to feature importance analyses, the preoperative levels of the same type and other hormones were all important in predicting postoperative individual hormonal hypofunction. Conclusion: Fluctuation in anterior pituitary hormones varies with increases and decreases because of transsphenoidal surgery. The ML models could accurately predict postoperative pituitary outcomes based on preoperative anterior pituitary hormones in NFPA.

Analysis of changes in the volume of edema around brain contusions and the influencing factors: A single-center, retrospective, observational study.

ABSTRACT: Traumatic brain injury (TBI), a common neurosurgical condition, has well-known treatment guidelines. However, the mechanisms underlying the varying severity of brain edema secondary to TBI are largely unknown, leading to controversial treatments.This study seeks to measure edema volumes around brain contusions in different regions, analyze factors related to differences in edema volume and provide a theoretical basis for brain edema treatment.Data from 113 brain contusion patients treated at the Department of Neurosurgery of Fuzhou General Hospital from January 2017 to November 2019 were analyzed retrospectively. Based on computed tomography (CT) data, the patients were divided into the venous group (brain contusion in regions with large cortical veins, n = 47) and the nonvenous group (brain contusions in other regions, n = 66). Here, 3D Slicer software was used to calculate the brain contusion volume on the first CT obtained after injury and the brain contusion volume and its surrounding edema on the 5th day after injury. The brain contusion volume to surrounding edema volume ratio was calculated, and the number of patients who showed brain contusion progression requiring surgery was determined. Hematocrit (Hct), fibrinogen (Fg), and d-dimer levels within 6 hours and on the 5th day after admission were also compared.Patients in the venous group had a significantly increased percentage of area with edema around the brain contusion compared with patients in the nonvenous group (P < .05), and the 2 groups showed no significant difference in the number of patients with brain contusion progression or surgical treatment (P > .05) or Hct, Fg, or d-dimer (D-D) levels. For all patients, Hct, Fg, and D-D levels within 6 hours after admission were significantly different from those on the 5th day (P < .05 for all).Cortical venous obstruction may be the most important factor influencing edema around brain contusions. The Fg level decreased slightly, and the D-D level increased to its peak rapidly after mild-moderate TBI. This change was followed by a gradual increase in the former and a gradual decrease in the latter.