Prediction of hyperperfusion phenomenon after carotid artery stenting and carotid angioplasty using quantitative DSA
Keita Yamauchi1, Yukiko Enomoto1, Katharina Otani2
1Department of Neurosurgery, Gifu University Graduate School of Medicine, Gifu, Japan.
Insights
Hyperperfusion phenomenon (HPP) after carotid procedures is rare but serious. Quantitative digital subtraction angiography (DSA) can predict HPP by measuring cerebral circulation time (CCT) changes before and after intervention.
Area of Science:
- Neurology
- Vascular Surgery
- Radiology
Background:
- Hyperperfusion syndrome (HPS) post-carotid interventions, though infrequent, carries significant morbidity and mortality risks.
- Accurate prediction of HPS is crucial for patient safety following carotid artery stenting and angioplasty.
Purpose of the Study:
- To assess the utility of quantitative digital subtraction angiography (DSA) in predicting hyperperfusion phenomenon (HPP) after carotid artery stenting and angioplasty.
- To establish predictive value of cerebral circulation time (CCT) measurements derived from DSA for HPP.
Main Methods:
- Thirty-three patients undergoing carotid interventions were analyzed.
- Cerebral circulation time (CCT) was calculated using quantitative DSA by measuring contrast transit times.
- Hyperperfusion phenomenon (HPP) was diagnosed post-procedure using 123I-IMP SPECT, serving as the reference standard.
Main Results:
- HPP was identified in 4 out of 33 patients via 123I-IMP SPECT.
- Patients with HPP exhibited significantly prolonged preprocedural CCT (13.0±6.1s vs 7.2±1.3s) and larger periprocedural CCT changes (5.9±5.7s vs 0.5±1.3s) compared to those without HPP.
- Optimal cut-off values for predicting HPP were identified as 8.0s for preprocedural CCT and 3.2s for periprocedural CCT change.
Conclusions:
- Prolonged preprocedural CCT and increased periprocedural CCT changes are associated with HPP occurrence.
- Quantitative DSA assessment of CCT offers a valuable tool for predicting HPP post-carotid interventions.
Background:
Hyperperfusion syndrome after carotid interventions has a low incidence but it can lead to morbidity and mortality.
Objective:
To evaluate the usefulness of quantitative DSA for predicting hyperperfusion phenomenon (HPP) after carotid artery stenting and angioplasty.
Methods:
Thirty-three consecutive patients with carotid stenosis treated with carotid artery stenting or angioplasty between February 2014 and August 2016 were included. Color-coded digital subtraction angiograms showing the time to maximum contrast intensity of each image pixel were obtained from conventional DSA before and after procedures. The cerebral circulation time (CCT) was defined as the difference in the relative time to maximum intensity between arterial and venous regions of interest set on the angiograms. HPP was diagnosed straight after the procedure with qualitative 123I-IMP single-photon emission CT (SPECT). Cut-off points for detecting HPP for preprocedural CCT and periprocedural change of CCT were assessed by receiver operating characteristic analysis using 123I-IMP SPECT as reference standard.
Results:
123I-IMP SPECT showed HPP in 4 of 33 patients. In these 4 patients, preprocedural prolongation of CCT (13.0±6.1 vs 7.2±1.3 s; p<0.001) was seen compared with patients without HPP as well as larger periprocedural changes of CCT (5.9±5.7 vs 0.5±1.3 s; p<0.001). The optimal cut-off points of preprocedural CCT and change of CCT for predicting HPP were 8.0 s (100% sensitivity, 69% specificity) and 3.2 s (75% sensitivity, 100% specificity), respectively.
Conclusions:
Preprocedural prolongation and greater periprocedural change of CCT are associated with the occurrence of HPP. Periprocedural evaluation of CCT may be useful for predicting HPP.
More Related Videos
10:41Analysis of Cerebral Vasospasm in a Murine Model of Subarachnoid Hemorrhage with High Frequency Transcranial Duplex Ultrasound
Published on: June 3, 2021
09:32Time-Resolved, Dynamic Computed Tomography Angiography for Characterization of Aortic Endoleaks and Treatment Guidance via 2D-3D Fusion-Imaging
Published on: December 9, 2021