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Clivus

The clivus is a bony structure located at the base of the skull, formed by the fusion of the sphenoid and occipital bones.
It serves as a critical component of the cranial base, providing attachment points for important muscles and ligaments.
Detailed understanding of the clivus anatomy and its variations is essential for neurosurgical procedures, particularly those involving the skull base.
This MeSH term provides a concise overview of the clivus, its anatomical features, and its clincal relevance to researchers and clinicans studying this important cranial structure.

Most cited protocols related to «Clivus»

1
Cerebral Vascular Anatomy and Infarction
Topographical determination of acute unilateral cerebellar infarction in the PICA territory was performed using visual correlation between Amarenco’s templates and the locations of high signal intensities from DWI that were more than 2 cm in diameter.8 (link) Two of the authors (JMH and CSC) came to a topographical consensus. We defined acute unilateral pontine infarction as DWI lesions involving the pons unilaterally. To evaluate the frequency of affected sites in the cerebellum and pons, we made contour maps using MRIcro software (C Rorden, www.mricro.com).
The diameter of each vessel was calculated as the average of the measurements made at three consecutive points, 3 mm apart, starting from the vertebrobasilar junction (both VAs and the BA). The “dominant” VA was defined as (1) having the larger diameter within a strict criterion for diameter (ie, a side to side diameter difference ⩾0.3 mm)7 (link) or as (2) the VA connected to the BA in a more straight fashion if both VAs were visually similar to a criterion of angle on CT angiography.
The direction of BA curvature was designated as “right (R)” or “left (L) side” according to a course of BA navigation at the vertebrobasilar junction. The degree of BA curvature was evaluated using a previously suggested CT based method,9 (link) based on the lateral-most position of the BA throughout its course (0, midline; 1 (R or L), medial to lateral margin of the clivus or dorsum sellae; 2 (R or L), lateral to the lateral margin of the clivus or dorsum sellae; and 3, in the cerebellopontine angle cistern). Moderate to severe BA curvature was defined as ⩾2 of the above criteria. The height of the bifurcation of the BA was scored as:1, within the suprasellar cistern; 2, at the level of the third ventricle floor; and 3, indenting and elevating the floor of the third ventricle.
Hong J.M., Chung C.S., Bang O.Y., Yong S.W., Joo I.S, & Huh K. (2009). Vertebral artery dominance contributes to basilar artery curvature and peri-vertebrobasilar junctional infarcts. Journal of Neurology, Neurosurgery, and Psychiatry, 80(10), 1087-1092.
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Publication 2009
Blood Vessel Cerebellopontine Angle Cerebellum Clivus Computed Tomography Angiography Infarction Microtubule-Associated Proteins Pica Pons Ventricles, Third
2
Neuroimaging Analysis of Parkinson's Disease
Neuroimaging data were prospectively acquired with a Siemens 3T Verio scanner using an 8-channel head coil. For gray and white matter analyses we acquired 2 T1-weighted scans (176 contiguous sagittal slices, 1mm3 voxels, 256×256 matrix, TR/TE= 2500/3.77ms, 7/8 Partial Fourier, acquisition time 9:22). The first of the two T1 scans was analyzed for this analysis. For skull segmentation, T2-weighted images were acquired (176 contiguous sagittal slices, 1mm3 voxels, 256×256 matrix, TR/ TE= 3200/ 409ms, GRAPPA, acquisition time 4:43). Images were visually examined for excessive motion, and images showing more than a moderate degree of motion were excluded from the analyses.
For all participants in the first analysis (PD vs control), TICV was measured by exporting the inner surface of the skull from FSL version 4.1 Brain Extraction Tool (BET; Smith 2002 (link)). These initial intracranial masks were then manually edited by expert raters to fill the enclosure within the inner surface of the skull. The inferior portion of the mask terminated on a line between the bottom of the occipital bone and the clivus. Reliability was high (intra-rater and inter-rater reliability DSC > 0.99). The final variable of interest was TICV in mm3. For participants added for the large vs small TICV analysis, TICV was measured using an automated method from Freesurfer (Fischl et al 2002 (link)), which combines all voxels labeled as white matter, gray matter, and CSF to create a volume that represents TICV.
A VBM analysis was performed on T1 structural images to investigate voxel-wise grey matter changes between PD patients and control participants. Structural data was analyzed with FSL-VBM (Douaud et al. 2007 (link)), an optimized VBM protocol (Good et al. 2001 (link)) carried out with FSL tools (Smith et al. 2004 (link)). First, structural images were brain-extracted and grey matter-segmented before being registered to the MNI 152 standard space using non-linear registration (Andersson et al. 2007 ). The resulting images were averaged and flipped along the x-axis to create a left-right symmetric, study-specific grey matter template. Second, all native grey matter images were non-linearly registered to this study-specific template and "modulated" to correct for local expansion (or contraction) due to the non-linear component of the spatial transformation. The modulated grey matter images were then smoothed with an isotropic Gaussian kernel with a sigma of 3 mm.
Crowley S., Huang H., Tanner J., Zho Q., Schwab N.A., Hizel L., Ramon D., Brumback B., Ding M, & Price C. (2018). Considering Total Intracranial Volume and Other Nuisance Variables in Brain Voxel Based Morphometry in Idiopathic PD. Brain imaging and behavior, 12(1), 1-12.
Publication 2016
Brain Clivus Cranium Epistropheus Gray Matter Head Occipital Bone Patients Radionuclide Imaging VBM protocol White Matter
3
Cervical Ossification Index for OPLL Evaluation
Age, sex, presence of diabetes, and body mass index (BMI) were collected as basic clinical data (S1 Table). CT images of the whole spine, including the cervical, thoracic, and lumbosacral spine from the occipital bone to the sacrum, were obtained in each patient. The incidence of OPLL in the cervical spine from the clivus to C7 and in other spinal regions from T1 to S1 was evaluated on mid-sagittal CT images. Image analysis was independently performed by five senior spine surgeons (T.H., K.T., K.M., A.I., and T.Y.). To quantify hyperostosis of the posterior longitudinal ligament, the distribution of OPLL at each vertebral body and intervertebral disc level was recorded, and the number of levels at which OPLL was present was defined as the ossification index (OP-index), as described previously [9 (link)]. The number of ossified lesions in the cervical spine was defined as the cervical OP-index. Patients were categorized into three groups according to the cervical OP-index: Grade 1, cervical OP-index ≤ 5; Grade 2, cervical OP-index 6–9; and Grade 3, cervical OP-index ≥ 10 (cervical OP-index classification). In addition to the OP-index, the sum of the intervertebral segments showing ossification of the anterior longitudinal ligament (OALL; cervical OA-index) was noted (S1 Table). The cervical OP-index classification and two indexes are shown in Fig 1.
Prior to image review, all testers read images from the same 20 patients to check inter-observer agreement. The average Kappa coefficient of inter-observer agreement was 0.76 (95% confidence interval [CI] = 0.71–0.81). Kappa values 0.00–0.20 were considered to indicate slight agreement; 0.21–0.40, fair agreement; 0.41–0.60, moderate agreement; 0.61–0.80, substantial agreement; and 0.811.00, almost perfect agreement [17 (link)]. Therefore, this finding indicates substantial agreement and consistency with the results of the previous study [9 (link)]. We also evaluated the degree of OPLL occupying the cervical spinal canal, with classification of the canal narrowing ratio (CNR) [18 (link)] at the most compressed segment defined as follows: Grade 1, 0% < CNR ≤ 25%; Grade 2, 25% < CNR ≤ 50%; Grade 3, 50% < CNR ≤ 75%; and Grade 4, CNR > 75%. First, we compared male and female populations in terms of the physical and radiologic data. We next evaluated the usefulness of the cervical OP-index classification for predicting the presence of OPLL in the thoracolumbar spine. Finally, we used a multiple regression model to investigate the factors associated with the OP-index in all patients.
Hirai T., Yoshii T., Iwanami A., Takeuchi K., Mori K., Yamada T., Wada K., Koda M., Matsuyama Y., Takeshita K., Abematsu M., Haro H., Watanabe M., Watanabe K., Ozawa H., Kanno H., Imagama S., Fujibayashi S., Yamazaki M., Matsumoto M., Nakamura M., Okawa A, & Kawaguchi Y. (2016). Prevalence and Distribution of Ossified Lesions in the Whole Spine of Patients with Cervical Ossification of the Posterior Longitudinal Ligament A Multicenter Study (JOSL CT study). PLoS ONE, 11(8), e0160117.
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Publication 2016
Cervical Vertebrae Cervix Uteri Clivus Diabetes Mellitus Hyperostosis Index, Body Mass Intervertebral Disc Longitudinal Ligaments, Anterior Males Neck Occipital Bone Ossification of the Posterior Longitudinal Ligament of Spine Osteogenesis Patients Physical Examination Population Group Posterior Longitudinal Ligaments Pulp Canals Sacrum Surgeons Vertebral Body Vertebral Column Woman
4
Optimizing PET Image Analysis Time
PET images were analyzed using coregistered MR images and a standardized template as previously described (2 (link)). Regional VT and rate constants from standard 1- and 2-tissue-compartment models (9 (link)) were calculated using PMOD, version 2.95 (PMOD Technologies Ltd.) (10 ), with the arterial input function corrected for radiometabolites. Because of the uptake of radioactivity in the skull with 18F-FMPEP-d2, 4 regions were drawn on the coregistered MR images of each subject and applied to the PET images: combined left and right parietal bones, 9.3 ± 0.8 cm3; occiput, 24.0 ± 1.5 cm3; and clivus, 5.2 ± 1.6 cm3.
To determine the minimal scanning time necessary to obtain stable values of VT, we analyzed the PET data from each subject after removing variable durations of the terminal portion of the scan. We analyzed brain data of all subjects from 0–300 to 0–30 min, with 10-min decrements.
Terry G.E., Hirvonen J., Liow J.S., Zoghbi S.S., Gladding R., Tauscher J.T., Schaus J.M., Phebus L., Felder C.C., Morse C.L., Donohue S.R., Pike V.W., Halldin C, & Innis R.B. (2009). Imaging and Quantitation of Cannabinoid CB1 Receptors in Human and Monkey Brains Using 18F-Labeled Inverse Agonist Radioligands. Journal of nuclear medicine : official publication, Society of Nuclear Medicine, 51(1), 112-120.
Publication 2009
18F-FMPEP-d2 Arteries Brain Clivus Cranium Parietal Bone Radioactivity Radionuclide Imaging Tissues
5
Glioblastoma Metabolite Imaging Protocol
EPSI data were available from a database of patients with glioblastoma previously enrolled in a phase II clinical trial (23 (link)) who received post-surgical scans. All scans were conducted in a 3T MRI scanner with a 32-channel head coil (Siemens Medical) and were obtained following surgical resection but prior to the start of radiation therapy and chemotherapy. Anatomic volumes obtained used a T1-weighted (T1w) magnetization-prepared rapid gradient echo pulse sequence (TR = 1900 ms, TE = 3.52 ms, 256 × 256 matrix, flip angle (FA) = 9°). A whole-brain 3D EPSI sequence (TR = 1551 ms, TE = 17.6 ms, FA = 71°, final matrix size of 64 × 64 × 32) was obtained during the same scanning session, as previously reported (3 (link)). Both sequences were obtained at a +15 degree tilt in the sagittal plane from the anterior commissure-posterior commissure line in order to capture the entire cerebrum while minimizing acquisition in the clivus, sinuses, and retro-orbital fat. An oblique saturation band was placed in the sagittal plane from the optic chiasm to the cerebellum to suppress signal from those regions. Image reconstruction and formation of metabolite images were carried out using the Metabolite Imaging and Data Analysis System (MIDAS) package (5 (link),6 (link)). Briefly, this processing includes spatial reconstruction, frequency alignment, B0 field correction, co-registration of the T1w and EPSI volumes, registration of the T1w volume to an anatomic atlas, lipid suppression, spectral fitting, and normalization with internal water signal to produce relative concentrations of metabolites. Additionally, pre-filtering of data using algorithms built into MIDAS was applied to all data to replicate the workflow currently used in clinical studies. First, a mask based on an anatomic atlas was applied to exclude voxels outside of the brain, which drastically reduces the number of voxels to be analyzed. Voxels with a water linewidth > 18 Hz, as calculated from T2 decay, were removed prior to spectral fitting to save computation time. After fitting, voxels with a metabolite linewidth > 18 Hz were also removed; this step served as an initial filter to remove spectra known to be of poor quality prior to visual review. A representative volume contained 10,298 voxels after filtering, however, since the data is also interpolated and smoothed in each dimension during reconstruction it is estimated that approximately 1,280 independent spectra remain within the brain volume. Spectra were then randomly sampled from a grid with a skip factor of 2, including both regions of tumor and healthy tissue, and exported for analysis. A total of 8,894 spectra collected from 9 patients with glioblastoma were collected.
Gurbani S.S., Schreibmann E., Maudsley A.A., Cordova J.S., Soher B.J., Poptani H., Verma G., Barker P.B., Shim H, & Cooper L.A. (2018). A Convolutional Neural Network to Filter Artifacts in Spectroscopic Magnetic Resonance Imaging. Magnetic resonance in medicine, 80(5), 1765-1775.
Publication 2018
Brain Cerebellum Cerebrum Clivus ECHO protocol factor A Glioblastoma Head Lipids Neoplasms Operative Surgical Procedures Optic Chiasms Patients Pharmacotherapy Radiotherapy Reconstructive Surgical Procedures Sinuses, Nasal Tissues

Most recents protocols related to «Clivus»

1
Quantitative Susceptibility Mapping for Intracranial Arteries
QSM images were reconstructed from the magnitude and phase images acquired by multi-echo GRE sequence using STI Suite (https://people.eecs.berkeley.edu/~chunlei.liu/software.html) implemented in Matlab R2016a (The Mathworks)51 (link). The phase images from the multi-echoes were unwrapped using the Laplacian-based method, then the normalized phase was calculated based on a method by Li et al.52 (link). The magnitude images were masked to include the intracranial arteries while excluding other noisy regions (clivus and condyles of the occipital bone). The 9 masks were generated by adjusting the fractional intensity threshold using the FSL BET software53 , and an appropriate mask containing the best ROI including target vessels was selected through visual inspection. Using the normalized phase and the magnitude mask images, the tissue phase images were created after background removal using the magnitude mask and variable-kernel sophisticated harmonic artifact reduction for phase data method. Finally, QSM was calculated using the streak artifact reduction for QSM method8 (link),9 (link),54 (link),55 (link). Overall processing of QSM reconstruction took about 5 min for each patient on a personal computer equipped with a 1.8 GHz processer (Intel Core i7; Intel) and 16 GB memory. QSM was normalized relative to the CSF in the posterior horns of the lateral ventricles, avoiding the surrounding brain tissue and choroid plexus.
Park S.I., Kim D., Jung S.C., Nam Y., Alabdulwahhab A., Lee J, & Choi K.M. (2023). Feasibility and intra-and interobserver reproducibility of quantitative susceptibility mapping with radiomic features for intracranial dissecting intramural hematomas and atherosclerotic calcifications. Scientific Reports, 13, 3651.
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Publication 2023
Arteries Blood Vessel Brain Clivus Condyle ECHO protocol EEC Syndrome 1 Memory Occipital Bone Patients Plexus, Chorioid Posterior Horn of Spinal Cord Reconstructive Surgical Procedures Tissues Ventricle, Lateral
2
Clival Extent Classification for Surgical Risk
We classified tumor extension in 4 distinct subgroups: clival extension (CE) 1–4 depending on the preoperative CT and MR imaging. The classification was evaluated by 2 individual reviewers (Fig. 1):

CE1: Intraosseous lesion

CE2: Destruction of the osseous clival cortical bone

CE3: Brainstem reached without compression or infiltration

CE4: Compression/infiltration of the brainstem

Clival extent classification (CE) with various extent categories: CE1: Intraosseous lesion, CE2: Destruction of the osseous clival cortical bone, CE3: Brainstem reached without compression or infiltration, CE4: Compression/infiltration of the brainstem.

The aim of this simple classification was to assess and quantify the risk and occurrence of complications based on imaging without histopathological diagnosis before the operation.
Butenschoen V.M., Krauss P., Bernhardt D., Negwer C., Combs S., Meyer B, & Gempt J. (2023). The transnasal endoscopic approach for resection of clival tumors: a single-center experience. Scientific Reports, 13, 3012.
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Publication 2023
Bone and Bones Bones Brain Stem Clivus Cortex, Cerebral Neoplasms
3
Endoscopic Clival Tumor Resection
We performed a consecutive case study of all patients treated endoscopically for tumors of the clivus, reviewing all patients who received operations via a transnasal endoscopic approach in our neurosurgical department between January 2009 and January 2020. We excluded patients suffering from skull base osteomyelitis or degenerative pathologies such as basilar invagination due to their distinct clinical outcome.
Pre- and postoperative data (with description of the surgical technique, EOR, and pre- and postoperative imaging) were retrieved from our records. We reviewed the preoperative goal of the operation (GTR, subtotal resection [STR], tumor debulking, and biopsy); clinical information included occurrence and side of cranial nerve palsy and duration of symptoms. The clinical status before and after operations and in follow-up was assessed according to the Karnofsky Performance Status Scale (KPSS).
If available, preoperative diagnostic imaging included pre- and postoperative computed tomography (CT) and magnetic resonance imaging (MRI) of the craniovertebral junction.
Butenschoen V.M., Krauss P., Bernhardt D., Negwer C., Combs S., Meyer B, & Gempt J. (2023). The transnasal endoscopic approach for resection of clival tumors: a single-center experience. Scientific Reports, 13, 3012.
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Publication 2023
Base of Skull Biopsy Clivus Neoplasms Osteomyelitis Palsies, Cranial Nerve Patients Surgical Endoscopy X-Ray Computed Tomography
4
Pituitary Tumor Characteristics on MRI
MRI were performed either in an outpatient setting or inpatient prior to surgery. Tumor size was measured on the preoperative MRI and then classified as micro- (< 1 cm), macroadenoma (≥ 1 cm and < 4 cm) or giant tumor (≥ 4 cm). Invasiveness including suprasellar, cavernous sinus, sphenoid sinus and clival invasion were additionally evaluated. Preoperative intratumoral bleeding seen on MRI and cystic components on T2 weighted images were also noted.
Sumislawski P., Huckhagel T., Krajewski K.L., Aberle J., Saeger W., Flitsch J, & Rotermund R. (2023). Cystic versus non-cystic silent corticotrophic adenomas: clinical and histological analysis of 62 cases after microscopic transsphenoidal surgery—a retrospective, single-center study. Scientific Reports, 13, 2468.
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Publication 2023
Clivus Cyst Gigantism Inpatient Neoplasms Operative Surgical Procedures Outpatients Sinus, Cavernous Sphenoid Sinus Vision
5
Diagnostic Criteria for Skull-Base Invasion in Nasopharyngeal Carcinoma
Based on the relevant literature 15 (link), 16 (link), the inclusion criteria for SBI of NPC were as follows: (1) a pathological diagnosis of NPC; and (2) an imaging diagnosis of SBI based on a low signal intensity defect of the bone cortex on MRI, high signal intensity bone marrow replaced by low signal intensity tissue on MRI, skull-base muscle signal changes, and an unclear demarcation between skull-base muscle and the primary tumor. The images had to show the invasion of 1 or more of the following sites: the pterygopalatine fossa, infratemporal fossa, sinus sphenoidalis, sellar floor, clivus, pars petrosa of the temporal bone, foramen ovale, foramen rupture, cavernous sinus, or jugular regions. Patients were excluded from the study if they met any of the following exclusion criteria: (1) had claustrophobia, a pacemaker, or severe liver and kidney insufficiency, or were in a coma, or had other symptoms; (2) had images of a quality that could not be assessed; (3) had other primary malignant tumors; and/or (4) did not have SBI according to the above SBI criteria.
Wu W., Xia J., Li B., Liu W., Ge Z., Tan Z., Bu Q., Chen W, & Li Y. (2023). Feasibility evaluation of intravoxel incoherent motion diffusion-weighted imaging in the diagnosis of skull-base invasion in nasopharyngeal carcinoma. Journal of Cancer, 14(2), 290-298.
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Publication 2023
Base of Skull Bone Marrow Claustrophobia Clivus Comatose Compact Bone Diagnosis Foramen Ovale Infratemporal Fossa Liver Malignant Neoplasms Muscle Tissue Neoplasms Pacemaker, Artificial Cardiac Patients Poly(ADP-ribose) Polymerases Pterygopalatine Fossa Renal Insufficiency Sinus, Cavernous Sphenoid Sinus Temporal Bone Tissues

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More about "Clivus"

The clivus is a critical component of the cranial base, a bony structure located at the base of the skull formed by the fusion of the sphenoid and occipital bones.
It provides attachment points for important muscles and ligaments, making it essential for various neurosurgical procedures involving the skull base.
Understanding the detailed anatomy and variations of the clivus is crucial for clinicians and researchers studying this important cranial structure.
The clivus, also known as the dorsum sellae or basilar part of the occipital bone, plays a vital role in the complex anatomy of the skull base.
Researchers may utilize various imaging techniques, such as high-definition endoscopes, Brilliance 64-slice CT scanners, and Intera Achieva MRI systems, to accurately visualize and analyze the clivus.
Additionally, techniques like the Two-step luminescence assay and Xeleris 3 workstation can provide valuable insights into the clivus and its surrounding structures.
The clivus is also relevant to broader medical topics, such as the use of antibiotics like penicillin and streptomycin, which can be important in the context of skull base infections or procedures.
By understanding the clivus and its anatomical variations, clinicians can optimize their approaches to neurosurgical interventions, improving patient outcomes and advancing the field of skull base surgery.
Whether you're a researcher, clinician, or someone interested in the human anatomy, the clivus is a fascinating and crucial component of the cranial base that deserves further exploration and understanding.