Classification of Intracranial Aneurysm Patients

1983 ◽  
pp. 1103-1112 ◽  
Author(s):  
John L. Fox
Keyword(s):  
Intracranial Aneurysm

scholarly journals The classification of intracranial aneurysm neck: a single center research experience

2018 ◽  
Vol 4 (1) ◽  
Author(s):  
Cai-Qiang Huang ◽  
De-Zhi Kang ◽  
Liang-Hong Yu ◽  
Shu-Fa Zheng ◽  
Pei-Sen Yao ◽  
...  
Keyword(s):  
Intracranial Aneurysm ◽  
Research Experience ◽  
Single Center ◽  
Aneurysm Neck ◽  
Center Research

scholarly journals CT Angiography-Based Radiomics for Classification of Intracranial Aneurysm Rupture

2021 ◽  
Vol 12 ◽  
Author(s):  
Osamah Alwalid ◽  
Xi Long ◽  
Mingfei Xie ◽  
Jiehua Yang ◽  
Chunyuan Cen ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Intracranial Aneurysm ◽  
Regression Model ◽  
Ct Angiography ◽  
Logistic Regression Model ◽  
Aneurysm Rupture ◽  
Classification Model ◽  
High Morbidity ◽  
Unruptured Aneurysms

Background: Intracranial aneurysm rupture is a devastating medical event with a high morbidity and mortality rate. Thus, timely detection and management are critical. The present study aimed to identify the aneurysm radiomics features associated with rupture and to build and evaluate a radiomics classification model of aneurysm rupture.Methods: Radiomics analysis was applied to CT angiography (CTA) images of 393 patients [152 (38.7%) with ruptured aneurysms]. Patients were divided at a ratio of 7:3 into retrospective training (n = 274) and prospective test (n = 119) cohorts. A total of 1,229 radiomics features were automatically calculated from each aneurysm. The feature number was systematically reduced, and the most important classifying features were selected. A logistic regression model was constructed using the selected features and evaluated on training and test cohorts. Radiomics score (Rad-score) was calculated for each patient and compared between ruptured and unruptured aneurysms.Results: Nine radiomics features were selected from the CTA images and used to build the logistic regression model. The radiomics model has shown good performance in the classification of the aneurysm rupture on training and test cohorts [area under the receiver operating characteristic curve: 0.92 [95% confidence interval CI: 0.89–0.95] and 0.86 [95% CI: 0.80–0.93], respectively, p < 0.001]. Rad-score showed statistically significant differences between ruptured and unruptured aneurysms (median, 2.50 vs. −1.60 and 2.35 vs. −1.01 on training and test cohorts, respectively, p < 0.001).Conclusion: The results indicated the potential of aneurysm radiomics features for automatic classification of aneurysm rupture on CTA images.

Reversible Panhypopituitarism Caused by a Suprasellar Aneurysm

Neurosurgery ◽  
1982 ◽  
Vol 10 (5) ◽  
pp. 604-611 ◽  
Author(s):  
Joseph G. Verbalis ◽  
Paul B. Nelson ◽  
Alan G. Robinson
Keyword(s):  
Intracranial Aneurysm ◽  
Pituitary Function ◽  
Giant Intracranial Aneurysm ◽  
Pituitary Dysfunction ◽  
Mass Lesions

Abstract A case of panhypopituitarism and hyperprolactinemia caused by a giant intracranial aneurysm is presented. The case is unique because both the pattern of the pituitary dysfunction and the complete normalization of all pituitary function after decompression of the aneurysm demonstrate the importance of pure compressive effects of mass lesions on pituitary function. The literature regarding return of pituitary function after resection of sellar and suprasellar masses is reviewed, and a schema for classification of pituitary dysfunction caused by mass lesions is proposed.

scholarly journals Assessing the Utility and Accuracy of ICD10-CM Nontraumatic Subarachnoid Hemorrhage Codes for Intracranial Aneurysm Research

2020 ◽  
Author(s):  
Christopher Roark ◽  
Melissa P. Wilson ◽  
Sheila Kubes ◽  
David Mayer ◽  
Laura K. Wiley
Keyword(s):  
Subarachnoid Hemorrhage ◽  
Intracranial Aneurysm ◽  
International Classification ◽  
Intracranial Artery ◽  
Patient History ◽  
Unruptured Intracranial Aneurysm ◽  
International Classification Of Disease ◽  
History Of

ABSTRACTBackgroundThe 10th revision of International Classification of Disease, Clinical Modification (ICD10-CM) increased the number of codes to identify nontraumatic subarachnoid hemorrhage from one to twenty-two. ICD10-CM codes are able to specify the location of aneurysms causing subarachnoid hemorrhage (aSAH), however it is not clear how frequently or accurately these codes are being used in practice.ObjectiveTo systematically evaluate the usage and accuracy of location-specific ICD10-CM codes for aSAH.MethodsWe extracted all uses of ICD10-CM codes for nontraumatic subarachnoid hemorrhage (I60.x) during the first three years following the implementation of ICD10-CM from the billing module of the EHR for UCHealth. For those codes that specified aSAH location (I60.0-I60.6), EHR documentation was reviewed to determine whether there was an active aSAH, any patient history of aSAH, or unruptured intracranial aneurysm/s and the locations of those outcomes.ResultsBetween October 1, 2015 – September 30, 2018, there were 3,119 instances of nontraumatic subarachnoid hemorrhage ICD10-CM codes (I60.00-I60.9), of which 297 (9.5%) code instances identified aSAH location (I60.0-I60.6). These codes accurately identified current aSAH (64%), any patient history of aSAH (84%), and any patient history of intracranial aneurysm (87%). The accuracy of identified outcome location was 53% in current aSAH, 72% for any history of aSAH, and 76% for any history of an intracranial artery.ConclusionsResearchers should use ICD10-CM codes with caution when attempting to detect active aSAH and/or aneurysm location.

Note on the spectral classification of carbon stars in the photographic infrared region

1966 ◽  
Vol 24 ◽  
pp. 21-23
Author(s):  
Y. Fujita
Keyword(s):  
Infrared Region ◽  
Spectral Classification ◽  
Carbon Stars

We have investigated the spectrograms (dispersion: 8Å/mm) in the photographic infrared region fromλ7500 toλ9000 of some carbon stars obtained by the coudé spectrograph of the 74-inch reflector attached to the Okayama Astrophysical Observatory. The names of the stars investigated are listed in Table 1.

Diagnostic Value of Electron Microscopy in Soft Tissue Tumors

1970 ◽  
Vol 28 ◽  
pp. 220-221
Author(s):  
Gerald Fine ◽  
Azorides R. Morales
Keyword(s):  
Cardiac Myxoma ◽  
Osteogenic Sarcoma ◽  
Diagnostic Value ◽  
Soft Tissue Tumors ◽  
Amelanotic Melanoma ◽  
Growth Patterns ◽  
Light Microscopic Level ◽  
Mesenchymal Tumors ◽  
Good Agreement

For years the separation of carcinoma and sarcoma and the subclassification of sarcomas has been based on the appearance of the tumor cells and their microscopic growth pattern and information derived from certain histochemical and special stains. Although this method of study has produced good agreement among pathologists in the separation of carcinoma from sarcoma, it has given less uniform results in the subclassification of sarcomas. There remain examples of neoplasms of different histogenesis, the classification of which is questionable because of similar cytologic and growth patterns at the light microscopic level; i.e. amelanotic melanoma versus carcinoma and occasionally sarcoma, sarcomas with an epithelial pattern of growth simulating carcinoma, histologically similar mesenchymal tumors of different histogenesis (histiocytoma versus rhabdomyosarcoma, lytic osteogenic sarcoma versus rhabdomyosarcoma), and myxomatous mesenchymal tumors of diverse histogenesis (myxoid rhabdo and liposarcomas, cardiac myxoma, myxoid neurofibroma, etc.)

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