scholarly journals Detection of clustered anomalies in single-voxel morphometry as a rapid automated method for identifying intracranial aneurysms

2021 ◽  
Vol 89 ◽  
pp. 101888
Author(s):  
Mark C. Allenby ◽  
Ee Shern Liang ◽  
James Harvey ◽  
Maria A. Woodruff ◽  
Marita Prior ◽  
...  
Keyword(s):  
Intracranial Aneurysms ◽  
Automated Method ◽  
Single Voxel

scholarly journals Detection of clustered anomalies in single-voxel morphometry as a rapid automated method for identifying intracranial aneurysms

2020 ◽  
Author(s):  
Mark C Allenby ◽  
Ee Shern Liang ◽  
James Harvey ◽  
Maria A Woodruff ◽  
Marita Prior ◽  
...  
Keyword(s):  
Intracranial Aneurysms ◽  
Image Resolution ◽  
Detection Sensitivity ◽  
List Type ◽  
Rupture Risk ◽  
Vascular Abnormalities ◽  
Automated Method ◽  
Single Voxel ◽  
Unruptured Intracranial Aneurysms ◽  
Risk Patients

AbstractUnruptured intracranial aneurysms (UIAs) are prevalent neurovascular anomalies which, in rare circumstances, rupture to create a catastrophic subarachnoid haemorrhage. Although surgical management can reduce rupture risk, the majority of IAs exist undiscovered until rupture. Current computer-aided UIA diagnoses sensitively detect and measure UIAs within cranial angiograms, but remain limited to low specificities whose output requires considerable neuroradiologist interpretation not amenable to broad screening efforts. To address these limitations, we propose an analysis which interprets single-voxel morphometry of segmented neurovasculature to identify UIAs. Once neurovascular anatomy of a specified resolution is segmented, interrelationships between voxel-specific morphometries are estimated and spatially-clustered outliers are identified as UIA candidates. Our automated solution detects UIAs within magnetic resonance angiograms (MRA) at unmatched 86% specificity and 81% sensitivity using 3 minutes on a conventional laptop. Our approach does not rely on interpatient comparisons or training datasets which could be difficult to amass and process for rare incidentally discovered UIAs within large MRA files, and in doing so, is versatile to user-defined segmentation quality, to detection sensitivity, and across a range of imaging resolutions and modalities. We propose this method as a unique tool to aid UIA screening, characterisation of abnormal vasculature in at-risk patients, morphometry-based rupture risk prediction, and identification of other vascular abnormalities. Graphical AbstractHighlightsRapid and automated detection of unruptured intracranial aneurysms (UIAs) in MRAsHighly specific, sensitive UIA detection to reduce radiologist input for screeningDetection is versatile to image resolution, modality and has tuneable mm sensitivity

scholarly journals Semiautomated 3D mapping of aneurysmal wall enhancement with 7T-MRI

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Ashrita Raghuram ◽  
Alberto Varon ◽  
Jorge A. Roa ◽  
Daizo Ishii ◽  
Yongjun Lu ◽  
...  
Keyword(s):  
Intracranial Aneurysms ◽  
3D Imaging ◽  
High Resolution Imaging ◽  
Biological Processes ◽  
Automated Method ◽  
Aneurysm Wall ◽  
Unruptured Intracranial Aneurysms ◽  
Potential Biomarker ◽  
Resolution Imaging ◽  
Objective Tool

AbstractAneurysm wall enhancement (AWE) after the administration of contrast gadolinium is a potential biomarker of unstable intracranial aneurysms. While most studies determine AWE subjectively, this study comprehensively quantified AWE in 3D imaging using a semi-automated method. Thirty patients with 33 unruptured intracranial aneurysms prospectively underwent high-resolution imaging with 7T-MRI. The signal intensity (SI) of the aneurysm wall was mapped and normalized to the pituitary stalk (PS) and corpus callosum (CC). The CC proved to be a more reliable normalizing structure in detecting contrast enhancement (p < 0.0001). 3D-heatmaps and histogram analysis of AWE were used to generate the following metrics: specific aneurysm wall enhancement (SAWE), general aneurysm wall enhancement (GAWE) and focal aneurysm wall enhancement (FAWE). GAWE was more accurate in detecting known morphological determinants of aneurysm instability such as size ≥ 7 mm (p = 0.049), size ratio (p = 0.01) and aspect ratio (p = 0.002). SAWE and FAWE were aneurysm specific metrics used to characterize enhancement patterns within the aneurysm wall and the distribution of enhancement along the aneurysm. Blebs were easily identified on 3D-heatmaps and were more enhancing than aneurysm sacs (p = 0.0017). 3D-AWE mapping may be a powerful objective tool in characterizing different biological processes of the aneurysm wall.

scholarly journals Three-dimensional morphological analysis of intracranial aneurysms: A fully automated method for aneurysm sac isolation and quantification

2011 ◽  
Vol 38 (5) ◽  
pp. 2439-2449 ◽  
Author(s):  
Ignacio Larrabide ◽  
Maria Cruz Villa-Uriol ◽  
Rubén Cárdenes ◽  
Jose Maria Pozo ◽  
Juan Macho ◽  
...  
Keyword(s):  
Intracranial Aneurysms ◽  
Morphological Analysis ◽  
Three Dimensional ◽  
Automated Method

Computer Indexing of Electron Diffraction Patterns Including the Effects of Lattice Symmetry

1977 ◽  
Vol 35 ◽  
pp. 22-23
Author(s):  
J. S. Lally ◽  
R. J. Lee
Keyword(s):  
Electron Diffraction ◽  
Zone Axis ◽  
Crystal Thickness ◽  
Double Diffraction ◽  
Automated Method ◽  
Lattice Symmetry ◽  
Intensity Calculations ◽  
Unknown Structure ◽  
Diffraction Patterns ◽  
Orientation Parameters

In the 50 year period since the discovery of electron diffraction from crystals there has been much theoretical effort devoted to the calculation of diffracted intensities as a function of crystal thickness, orientation, and structure. However, in many applications of electron diffraction what is required is a simple identification of an unknown structure when some of the shape and orientation parameters required for intensity calculations are not known. In these circumstances an automated method is needed to solve diffraction patterns obtained near crystal zone axis directions that includes the effects of systematic absences of reflections due to lattice symmetry effects and additional reflections due to double diffraction processes.Two programs have been developed to enable relatively inexperienced microscopists to identify unknown crystals from diffraction patterns. Before indexing any given electron diffraction pattern, a set of possible crystal structures must be selected for comparison against the unknown.

Sign in / Sign up

Export Citation Format

Share Document