Abstract 025: CTA carotid web structural characteristics as predictors for contrast stagnation on DSAs
Introduction Carotid webs (CaWs) have been shown to present with a long time of contrast stagnation during digital subtraction angiography (DSA) runs, and this has been proposed as a potential underlying physiopathological feature facilitating thrombosis and stroke. We aim to evaluate the relationsh...
Saved in:
| Main Authors: | , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2023-11-01
|
| Series: | Stroke: Vascular and Interventional Neurology |
| Online Access: | https://www.ahajournals.org/doi/10.1161/SVIN.03.suppl_2.025 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850268257571831808 |
|---|---|
| author | Mateus Damiani Monteiro Mohamed A Tarek Jason W Allen David Landzberg Raul Nogueira Jaydevsih Dolia Charlie C Park Bernardo Liberato MIchael R Frankel Diogo C Haussen |
| author_facet | Mateus Damiani Monteiro Mohamed A Tarek Jason W Allen David Landzberg Raul Nogueira Jaydevsih Dolia Charlie C Park Bernardo Liberato MIchael R Frankel Diogo C Haussen |
| author_sort | Mateus Damiani Monteiro |
| collection | DOAJ |
| description | Introduction Carotid webs (CaWs) have been shown to present with a long time of contrast stagnation during digital subtraction angiography (DSA) runs, and this has been proposed as a potential underlying physiopathological feature facilitating thrombosis and stroke. We aim to evaluate the relationship of quantified contrast stagnation with vascular imaging structural characteristics and clinical features of CaW. Methods We retrospectively assessed 48 patients with CaWs who underwent computerized tomography angiography (CTA) and DSA. CaWs’ structural characteristics were evaluated: 1) Length/Base/Thickness: base is the distance between the shoulders of the lesion, while the length is the distance between the midpoint of the base to the web apex. The thickness of the web is the length divided by the base; 2) Angles: we assessed three different web angles: caudal, middle, and cranial angles. All angles are referred to the axis of the vessel. The axis of the carotid is defined as the line spanning a specific length of 15 mm from the exact center of the distal common carotid artery to the center of the internal carotid artery;. The caudal angle is the angle between the line tangent to the caudal wall of the web and the vessel axis. The middle angle is the angle between the length of the web and the vessel axis. The cranial angle is the angle between the line tangent to the cranial wall of the web and the vessel axis. 3) Pocket Area/perimeter: these these measures were calculated by free‐hand delineation of delineating the web rostral surface of the web up to a straight line drawn at 90 degrees from the vessel axis of the carotid artery tangent to the web apex of the web through the vessel posterior wall. The perimeter is the perimeter of the hand‐delimited pocket area; 4) Orientation: it is the CaW ridge in relationship to the horizontal plane based on axial CTA cuts. A region of interest was placed in the DSA post‐web region, the mean Hounsfield units within the ROI was calculated for each frame of the run and a time density curve plotted. CaW structural measurementmeasurements were correlated with the hemodynamic parameters, such as stagnation time and area under the curve (AUC), and the hemodynamic parametersthese were correlated with clinical characteristics. Results Mean age of patients was 52.6 (±10 years), 32 (66.7%) were women, 40 (83.3%) were black, 29 (60.4%) had hypertension, 47 (97.9%) had stroke, from these, 89.4% had a large vessel occlusion. Base size had a weak correlation with AUC (p=0.02) and AUC from peak to 80% clearance (p<0.01). No other correlations were found between CaW structural features (length, thickness, caudal, middle and cranial angles, pocket area and perimeter, and orientation) and hemodynamic parameters (stagnation time, stagnation time from peak to the point of 80% contrast clearance, AUC, and AUC from peak to the point of 80% of contrast clearance). Moreover, there are no correlations between those hemodynamic parameters with admission NIH, systolic or diastolic blood pressure, heart rate, clot burden, ASPECTS, automated CT cerebral perfusion defect volume [Tmax>6 seconds], 90 day NIHSS, and 90 day mRS. Conclusion Base size was correlated with the AUC and AUC from the peak to the 80% clearance. No other hemodynamic parameters were correlated with the clinical characteristics. The relationship between DSA contrast stagnation and clinical outcomes remains unclear. |
| format | Article |
| id | doaj-art-862d32b04e984acfba32fa381245f1f4 |
| institution | OA Journals |
| issn | 2694-5746 |
| language | English |
| publishDate | 2023-11-01 |
| publisher | Wiley |
| record_format | Article |
| series | Stroke: Vascular and Interventional Neurology |
| spelling | doaj-art-862d32b04e984acfba32fa381245f1f42025-08-20T01:53:31ZengWileyStroke: Vascular and Interventional Neurology2694-57462023-11-013S210.1161/SVIN.03.suppl_2.025Abstract 025: CTA carotid web structural characteristics as predictors for contrast stagnation on DSAsMateus Damiani Monteiro0Mohamed A Tarek1Jason W Allen2David Landzberg3Raul Nogueira4Jaydevsih Dolia5Charlie C Park6Bernardo Liberato7MIchael R Frankel8Diogo C Haussen9Emory University Georgia United StatesEmory University Georgia United StatesEmory University Georgia United StatesEmory University Georgia United StatesUPMC Stroke Institute Pennsylvania United StatesEmory University Georgia United StatesEmory University Georgia United StatesEmory University Georgia United StatesEmory University Georgia United StatesEmory University Georgia United StatesIntroduction Carotid webs (CaWs) have been shown to present with a long time of contrast stagnation during digital subtraction angiography (DSA) runs, and this has been proposed as a potential underlying physiopathological feature facilitating thrombosis and stroke. We aim to evaluate the relationship of quantified contrast stagnation with vascular imaging structural characteristics and clinical features of CaW. Methods We retrospectively assessed 48 patients with CaWs who underwent computerized tomography angiography (CTA) and DSA. CaWs’ structural characteristics were evaluated: 1) Length/Base/Thickness: base is the distance between the shoulders of the lesion, while the length is the distance between the midpoint of the base to the web apex. The thickness of the web is the length divided by the base; 2) Angles: we assessed three different web angles: caudal, middle, and cranial angles. All angles are referred to the axis of the vessel. The axis of the carotid is defined as the line spanning a specific length of 15 mm from the exact center of the distal common carotid artery to the center of the internal carotid artery;. The caudal angle is the angle between the line tangent to the caudal wall of the web and the vessel axis. The middle angle is the angle between the length of the web and the vessel axis. The cranial angle is the angle between the line tangent to the cranial wall of the web and the vessel axis. 3) Pocket Area/perimeter: these these measures were calculated by free‐hand delineation of delineating the web rostral surface of the web up to a straight line drawn at 90 degrees from the vessel axis of the carotid artery tangent to the web apex of the web through the vessel posterior wall. The perimeter is the perimeter of the hand‐delimited pocket area; 4) Orientation: it is the CaW ridge in relationship to the horizontal plane based on axial CTA cuts. A region of interest was placed in the DSA post‐web region, the mean Hounsfield units within the ROI was calculated for each frame of the run and a time density curve plotted. CaW structural measurementmeasurements were correlated with the hemodynamic parameters, such as stagnation time and area under the curve (AUC), and the hemodynamic parametersthese were correlated with clinical characteristics. Results Mean age of patients was 52.6 (±10 years), 32 (66.7%) were women, 40 (83.3%) were black, 29 (60.4%) had hypertension, 47 (97.9%) had stroke, from these, 89.4% had a large vessel occlusion. Base size had a weak correlation with AUC (p=0.02) and AUC from peak to 80% clearance (p<0.01). No other correlations were found between CaW structural features (length, thickness, caudal, middle and cranial angles, pocket area and perimeter, and orientation) and hemodynamic parameters (stagnation time, stagnation time from peak to the point of 80% contrast clearance, AUC, and AUC from peak to the point of 80% of contrast clearance). Moreover, there are no correlations between those hemodynamic parameters with admission NIH, systolic or diastolic blood pressure, heart rate, clot burden, ASPECTS, automated CT cerebral perfusion defect volume [Tmax>6 seconds], 90 day NIHSS, and 90 day mRS. Conclusion Base size was correlated with the AUC and AUC from the peak to the 80% clearance. No other hemodynamic parameters were correlated with the clinical characteristics. The relationship between DSA contrast stagnation and clinical outcomes remains unclear.https://www.ahajournals.org/doi/10.1161/SVIN.03.suppl_2.025 |
| spellingShingle | Mateus Damiani Monteiro Mohamed A Tarek Jason W Allen David Landzberg Raul Nogueira Jaydevsih Dolia Charlie C Park Bernardo Liberato MIchael R Frankel Diogo C Haussen Abstract 025: CTA carotid web structural characteristics as predictors for contrast stagnation on DSAs Stroke: Vascular and Interventional Neurology |
| title | Abstract 025: CTA carotid web structural characteristics as predictors for contrast stagnation on DSAs |
| title_full | Abstract 025: CTA carotid web structural characteristics as predictors for contrast stagnation on DSAs |
| title_fullStr | Abstract 025: CTA carotid web structural characteristics as predictors for contrast stagnation on DSAs |
| title_full_unstemmed | Abstract 025: CTA carotid web structural characteristics as predictors for contrast stagnation on DSAs |
| title_short | Abstract 025: CTA carotid web structural characteristics as predictors for contrast stagnation on DSAs |
| title_sort | abstract 025 cta carotid web structural characteristics as predictors for contrast stagnation on dsas |
| url | https://www.ahajournals.org/doi/10.1161/SVIN.03.suppl_2.025 |
| work_keys_str_mv | AT mateusdamianimonteiro abstract025ctacarotidwebstructuralcharacteristicsaspredictorsforcontraststagnationondsas AT mohamedatarek abstract025ctacarotidwebstructuralcharacteristicsaspredictorsforcontraststagnationondsas AT jasonwallen abstract025ctacarotidwebstructuralcharacteristicsaspredictorsforcontraststagnationondsas AT davidlandzberg abstract025ctacarotidwebstructuralcharacteristicsaspredictorsforcontraststagnationondsas AT raulnogueira abstract025ctacarotidwebstructuralcharacteristicsaspredictorsforcontraststagnationondsas AT jaydevsihdolia abstract025ctacarotidwebstructuralcharacteristicsaspredictorsforcontraststagnationondsas AT charliecpark abstract025ctacarotidwebstructuralcharacteristicsaspredictorsforcontraststagnationondsas AT bernardoliberato abstract025ctacarotidwebstructuralcharacteristicsaspredictorsforcontraststagnationondsas AT michaelrfrankel abstract025ctacarotidwebstructuralcharacteristicsaspredictorsforcontraststagnationondsas AT diogochaussen abstract025ctacarotidwebstructuralcharacteristicsaspredictorsforcontraststagnationondsas |