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Base of Skull

The base of the skull, also known as the cranial base, is a complex anatomical region that encompasses the lowermost part of the skull.
It is a critical area for various medical and surgical procedures, including those related to the treatment of base of skull disorders, cranial base tumors, and other neurological conditions.
PubCompare.ai, the leading AI-driven research platform, can help optimize your base of skull research protocols by easily locating the best protocols from literature, pre-prints, and patents through powerful AI-driven comparisons.
Streamline your research process and discover the most effective solutions for your base of skull studies with PubCompare.ai.

Most cited protocols related to «Base of Skull»

Total body imaging was acquired using the GE Healthcare Lunar iDXA and analyzed using enCORE software version 13.6. Daily quality control scans were acquired during the study period. No hardware or software changes were made during the course of the trial. Subjects were scanned using standard imaging and positioning protocols. For measuring android fat, a region-of-interest is automatically defined whose caudal limit is placed at the top of the iliac crest and its height is set to 20% of the distance from the top of the iliac crest to the base of the skull to define its cephalad limit (Figure 1). Abdominal SF and VF were estimated within the android region. Fat mass data from DXA was transformed into CT adipose tissue volume using a constant correction factor (0.94 g/cm3). This constant is generally consistent with the density of adipose tissue (29 (link)) and represents a value that was optimized in our training algorithm and not altered in the validation procedure.
Publication 2012
Abdomen Base of Skull Cone-Beam Computed Tomography Human Body Iliac Crest Tissue, Adipose

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Publication 2009
Base of Skull Brain Cerebrospinal Fluid Head White Matter

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Publication 2011
Base of Skull Bevacizumab Chemoradiotherapy Cisplatin Fluorouracil Maxillary Sinus Nasal Cavity Nasopharynx Neck Necrosis Nodes, Lymph Pharmaceutical Adjuvants Pharyngeal Space, Lateral Pterygopalatine Fossa Radiotherapy Radiotherapy, Intensity-Modulated Scan, CT PET Sphenoid Sinus Therapeutics Veins

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Publication 2015
Anisotropy Base of Skull Brain Brain Stem Cerebellum Cortex, Cerebral Infant Multimodal Imaging Muscle Rigidity Tissues
Two trained observers (MVH and KJF), independently and blinded to each other’s results, performed WML segmentation using the MCMxxxVI method and FLAIR-derived thresholds (comparisons summarised in Table 2). The FLAIR thresholds derived from the three most caudal slice pairs were discarded from further analyses as they were clearly different (Fig. 3). We calculated the minimum (threshold 1) and maximum (threshold 2) per patient and also a single threshold equal to the average of all 168 thresholds (9 slice pairs, 14 subjects). The single threshold was evaluated because some studies use only one threshold for segmenting WMLs in all patients [2 (link)]. The resulting three WML masks were visually assessed, blind to threshold value and to each other, for accuracy by an experienced neuroradiologist (JMW) who determined the number of false positive and partial and total false negative WMLs per brain region.

Threshold (Th) values calculated from each pair of slices for each subject. Threshold 1 is from the brain slice nearest the skull base and threshold 12 from the slice nearest the vertex

Comparisons performed to evaluate the segmentation methods

Segmentation methodIntra-observer reliabilityInter-observer reliabilityVisual assessment
MCMxxxVI manually removing false positive WMLs
MCMxxxVI without removing false positive WMLs
Thresholding in FLAIR manually removing false positive WMLs
Thresholding in FLAIR without removing false positive WMLs
We expressed the WML volumes derived from each method in voxels and calculated the mean, maximum and minimum differences using Bland-Altman analyses [28 ]. The effect of slice location and WML load on FLAIR-derived thresholds was explored using a linear mixed model and expressed as means with 95% confidence intervals (CI). Separate simple linear regression analyses were used to test for the effect of observer variation of RG boundary values on WML volume. The results of the intra- and inter-observer reliability tests are expressed in voxels, not cubic millimetres because of the inter-slice gap (5 mm), i.e. we did not at this stage apply stereology to interpolate between slices. Finally, we evaluated the effect of motion artefact and magnetic field heterogeneities [29 (link)] on WML volume measurement [13 (link), 30 (link)].
Publication 2010
Base of Skull Brain Cuboid Bone Genetic Heterogeneity Magnetic Fields Patients Visually Impaired Persons

Most recents protocols related to «Base of Skull»

PET scans were acquired using either Signa PET/MRI 3 Tesla system, GE Healthcare, Waukesha, WI, USA (N = 46) or PET/CT, Discovery-690, GE Healthcare (N = 39).
Fasting condition was requested on the day of 68Ga-PSMA PET/MRI and PET/CT scan.
PET scans were acquired from the skull base to mid-thigh (5–6 FOVs, 4 min/FOV), and started approximately 60 min (mean ± SD, 63 ± 6 min) after injection of 111–273 MBq (Mean ± SD, 168 ± 33 MBq) of 68Ga-PSMA. PET images, acquired with either PET/MRI or PET/CT scanner, were reconstructed using fully 3D ordered subset expectation-maximization (OSEM) algorithm, time-of-flight (TOF) and point-spread-function (PSF).
68Ga PSMA PET image read-out was performed by two Nuclear Medicine physicians on an Advantage Workstation (AW, General Electric Healthcare, Waukesha, WI, USA) and the presence of 68GA-PSMA intraprostatic increased uptake was considered positive for malignancy.
Publication 2023
Base of Skull CAT SCANNERS X RAY Electricity gallium GA-68 gozetotide Malignant Neoplasms Physicians Positron-Emission Tomography Radionuclide Imaging Scan, CT PET Thigh X-Ray Computed Tomography
The mice with or without cardiac-targeted ChRmine expression were implanted with custom-made headplates, reference electrodes and cyanoacrylate-adhesive-based ‘clear-skull caps’ as previously described66 (link). After recovery, mice were water-restricted and habituated to head fixation, but they were allowed to drink water to satiate thirst before recording sessions. Craniotomies were made with a dental drill at least several hours before recording sessions and were sealed with Kwik-Cast (World Precision Instruments). Exposed craniotomies before, during and after recordings were kept moist with frequent application of saline until sealed with Kwik-Cast.
Before recordings, the mice were placed into the pacemaker vests and reliable pacing was confirmed by ECG under brief anaesthesia with isoflurane. Then the mice were head-fixed and allowed to recover. Next, one or two (for simultaneous bilateral recordings) four-shank Neuropixels 2.0 probes mounted on a multi-probe manipulator system (New Scale Technologies) and controlled by SpikeGLX software (Janelia Research Campus) were inserted through the craniotomies at variable angles (0–20°) depending on the recording geometry. Typically the probes were aimed to touch the skull around the insula, which could be inferred from probe bending or changes in local field potential, and then were retracted around 100 µm and allowed to sit in place for at least 15 min before recordings. Recordings were performed along each of the four shanks sequentially while mice received 5 s of optical stimulation (900 bpm (15 Hz)) with inter-trial intervals of at least 15–25 s. Probes were cleaned with trypsin between recording sessions. Spike sorting was performed by Kilosort 2.5 and auxiliary software as previously described66 (link).
After recordings, the brains were perfused, cleared, imaged and registered to the Allen Brain Atlas as previously described66 (link). Using the traces of lipophilic dye CM-DiI or DiD (which coated the probes before each insertion) and electrophysiological features, the atlas coordinates of the recorded single units were determined.
The spikes from single units were aligned to pacing onset, and the visualized peri-stimulus time histograms were calculated by subtracting 5 s baseline firing rate, 10 ms binning and 500 ms half-Gaussian filtering. The population-averaged firing rate of each region was calculated by combining z-scores (before filtering) over time for all single units in the region of interest. Specifically, we used hierarchical bootstrap to combine data from multiple levels as previously described66 (link). For each condition, 100 bootstrap datasets were generated, and their mean and s.d. represented the mean and s.e.m. of the initial dataset. For statistical tests comparing ChRmine and control groups, the one-sided P value for the null hypothesis (the ChRmine firing rate subtracted by the control firing rate is zero) was calculated as the fraction of these subtracted values from the pairs of the resampled means (averaged over the time window of interest) that were smaller than zero.
Publication 2023
Base of Skull Brain CD3EAP protein, human CM-DiI Craniotomy Cranium Cyanoacrylates Dental Anesthesia Dental Health Services Drill Head Heart Insula of Reil Isoflurane Mice, Laboratory Pacemaker, Artificial Cardiac Photic Stimulation Saline Solution Thirst Touch Trypsin
The delineated CSF space was separated manually from the final CSF mask in ITK-SNAP into seven compartments (Appendix 1—figure 3B ‘Filtration and labeling’), for further statistical comparison: lateral ventricles; third ventricle; fourth ventricle; basilar artery; basal perivascular space at the skull base surrounding the Circle of Willis; parietal perivascular spaces and cisterns (ventrally from the position of posterior cerebral artery, via space neighboring the transverse sinuses and dorsally to the junction of the superior sagittal sinus and transverse sinuses); remaining perivascular space within the olfactory area, surrounding anterior cerebral and frontopolaris arteries, middle cerebral arteries branches, and posterior cisterns including pontine and cisterna magna. For supplementary comparison, the segmented lateral, third and fourth ventricular spaces were considered jointly as the ventricular space, and the basilar, basal and the remaining anterior/posterior CSF spaces were considered jointly as the whole perivascular space. Number of voxels was counted, and the volume of each segment was calculated by multiplying the voxels count by the voxel dimension from the original 3D-CISS image, for subsequent statistical comparison.
To compensate for the brain capsule volume differences and provide a reliable measure of the brain’s CSF space volume between animals, a ratio of the CSF to the brain volume (intracranial volume) was calculated for each delineated CSF segment as: RatioCSFspace=CSFcompartmentvolumeBrainvolumeCSFwholesegmentedvolume
The ratios obtained for each of the CSF compartments, as well as the segmented brain volumes were compared between KO and WT animals using nonparametric Mann-Whitney U-test.
Publication 2023
Animals Arteries Base of Skull Basilar Artery Brain Brain Perivascular Spaces Capsule Circle of Willis CISH protein, human Filtration Heart Ventricle Magna, Cisterna Middle Cerebral Artery Pons Posterior Cerebral Artery Sense of Smell Sinus, Superior Sagittal Transverse Sinuses Ventricle, Lateral Ventricles, Fourth Ventricles, Third
All participants including the affected brothers BI (age 28) and BII (age 25) underwent MRI using the Human Connectome Protocol and PET for tau pathology using flortaucipir. Brother BII also underwent amyloid PET imaging using florbetapir at age 27.
For tau PET, 10.3 mCi 18F-AV-1451 was administrated through an intravenous catheter and images were obtained beginning 75 min after injection. Six frames, 5 min apart, were collected and averaged. A low-dose CT transmission scan was obtained for attenuation correction. For amyloid PET, ∼50 min after intravenous administration of 10.4 mCi of 18F-florbetapir, PET images were obtained of the brain from vertex to skull base. Low-dose CT scan was obtained over the same anatomic range for attenuation correction.
To quantify flortaucipir PET imaging, we first ran recon-all script from FreeSurfer 6.0 to get high-resolution segmentations from the T1 image. Desikan–Killiany atlas16 (link) was used to define 36 anatomical regions. PET images were then co-registered to T1 native space. The Muller-Gartner method was used to correct the partial volume effect of flortaucipir PET image using PETSurfer in FreeSurfer 6.0. Standard uptake value ratios (SUVRs) were then calculated using cerebellar grey matter from the T1 image as the reference region. Partial volume–corrected SUVR was also mapped to the cortical surface that is parcellated to 36 regions for each cerebral hemisphere.
In order to investigate the integrity of white matter associated with the F388S PSEN1 substitution, diffusion MRI was performed using the Human Connectome Protocol. T1-weighted MR image and diffusion MR image of each subject were preprocessed by Human Connectome Protocol pipeline17 (link) with version 3.27. Diffusion MRI data were acquired with two opposite phase encoding directions that are anterior to posterior (AP) and posterior to anterior (PA). Raw diffusion MRI data were corrected by topup and eddy functions in FSL to reduce the distortion caused by susceptibility-induced distortion and eddy current-induced distortion. After distortion correction, diffusion MRI data were resampled to T1 image space. The diffusion tensor model and associated eigenvalues (λ1, λ2, λ3) were estimated with the MRtrix3 software.18 (link) Fractional anisotropy, mean diffusivity (MD), radial diffusivity and axial diffusivity were then computed. These diffusivity measures were mapped back to T1 space using the linear transformation obtained from the registration between B0 image and T1 image processed by recon-all. White matter is also parcellated into 36 regions for each cerebral hemisphere using the method as cortical region parcellation. Mean values of these diffusivity measures in each white matter region are then calculated for statistical analysis.
Publication 2023
(18)AV-1451 Amyloid Proteins Anisotropy Base of Skull Body Regions Brain Brothers Catheters Cerebellar Gray Matter Cerebral Hemispheres Cortex, Cerebral Diffusion Diffusion Magnetic Resonance Imaging florbetapir flortaucipir Human Connectome Intravenous Infusion PSEN1 protein, human Reading Frames Susceptibility, Disease Transmission, Communicable Disease White Matter X-Ray Computed Tomography
Ten structures on the skull base were identified and marked including the anterior tip of OC (OCAT), basion (Bas), extracranial orifice of HC (eHC), FM, intracranial orifice of HC (iHC), JF, OC, opisthion (Op), the posterior most end of JF (pJF), and the posterior tip of OC (OCPT) (Fig. 1) [4 (link), 25 ].
Publication 2023
Base of Skull

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More about "Base of Skull"

The cranial base, also known as the base of the skull, is a complex anatomical region that forms the lowermost part of the skull.
This critical area is essential for various medical and surgical procedures, including the treatment of base of skull disorders, cranial base tumors, and other neurological conditions.
The cranial base is composed of several bones, such as the occipital, sphenoid, and temporal bones, which work together to protect the brain and facilitate important functions.
Researchers and clinicians can optimize their base of skull studies by leveraging the powerful AI-driven comparisons offered by PubCompare.ai, the leading research platform.
This innovative tool allows users to easily locate the best protocols from literature, pre-prints, and patents, streamlining the research process and helping to discover the most effective solutions for their base of skull investigations.
In addition to the base of skull, related terms and subtopics include the craniofacial region, skull base, clivus, foramen magnum, and cranial nerves.
Imaging modalities such as Biograph mCT, Biograph mCT 64, Discovery STE, LightSpeed VCT, Discovery ST, Gemini TF64, Biograph 64, Discovery 690, and Gemini TF can play a crucial role in the diagnosis and management of base of skull disorders and conditions.
By incorporating these key terms and technologies, researchers can enhance their understanding and exploration of this complex and vital anatomical region.