Associations of thrombus perviousness derived from entire thrombus segmentation with functional outcome in patients with acute ischemic stroke

DOT sign indicates persistent hypoperfusion and poor outcome in patients with incomplete reperfusion following thrombectomy

BACKGROUND

Distal occlusions associated with incomplete reperfusion (expanded Thrombolysis in Cerebral Infarction,

METHODS

Retrospective registry analysis of patients undergoing endovascular therapy between July 2020 and December 2022, with available immediate post-interventional FPDCT and 24 hours follow-up perfusion imaging. Persistent hypoperfusion was defined as a perfusion deficit at 24 hours directly corresponding to the area of incomplete reperfusion on final angiography run. The DOT sign was defined as a punctiform or tubular hyperdense signal increase on FPDCT indicative of a residual occlusion. Association between the DOT sign (present/absent) with the occurrence of persistent hypoperfusion and poor outcome (modified Rankin scale (mRS) score 3-6) was evaluated using logistic regression analysis.

RESULTS

Of 292 patients included (median age 73 years; 47% female), 209 had incomplete reperfusion. Among patients with incomplete reperfusion, 61% had a present DOT sign and 46% had persistent hypoperfusion. In the overall cohort, but also within each eTICI stratum, a present DOT sign was associated with persistent hypoperfusion on 24±12 hours follow-up perfusion imaging (adjusted odds ratio (aOR) 4.8, 95% confidence interval (CI) 2.0 to 12.3 for patients with eTICI 2 a-2c). A present DOT sign was also associated with poor outcome (aOR 2.6, 95% CI 1.1 to 6.2).

CONCLUSION

Patients with Collapse

Key Words

• CT Angiography
• Intervention
• MR perfusion
• Stroke
• Thrombectomy

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MESH Headings Collapse

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Affiliation(s)

Adnan Mujanovic Department of Diagnostic and Interventional Neuroradiology, University Hospital Bern Inselspital, Bern, Switzerland Graduate School for Health Sciences, University of Bern, Bern, Switzerland
Daniel Windecker Department of Diagnostic and Interventional Neuroradiology, University Hospital Bern Inselspital, Bern, Switzerland
Bettina Serrallach Department of Diagnostic and Interventional Neuroradiology, University Hospital Bern Inselspital, Bern, Switzerland
Christoph C Kurmann Department of Diagnostic and Interventional Neuroradiology, University Hospital Bern Inselspital, Bern, Switzerland Graduate School for Health Sciences, University of Bern, Bern, Switzerland Department of Diagnostic, Interventional and Pediatric Radiology, University Hospital Bern Inselspital, Bern, Switzerland
Roman Rohner Department of Diagnostic and Interventional Neuroradiology, University Hospital Bern Inselspital, Bern, Switzerland Graduate School for Health Sciences, University of Bern, Bern, Switzerland
Elias Auer Department of Neurology, Inselspital University Hospital Bern, Bern, Switzerland
Petra Cimflova Department of Diagnostic and Interventional Neuroradiology, University Hospital Bern Inselspital, Bern, Switzerland Department of Neuroradiology, University Hospital Freiburg, Freiburg, Germany Department of Medical Imaging, St. Anne's University Hospital Brno, Brno, Czech Republic
Thomas R Meinel Department of Neurology, Inselspital University Hospital Bern, Bern, Switzerland
Franziska Dorn Department of Neuroradiology, University Hospital Bonn, Bonn, Germany
René Chapot Department of Neuroradiology and Endovascular Therapy, Alfried Krupp Krankenhaus Ruttenscheid, Essen, Germany
David Seiffge Department of Neurology, Inselspital University Hospital Bern, Bern, Switzerland
Eike Immo I Piechowiak Department of Diagnostic and Interventional Neuroradiology, University Hospital Bern Inselspital, Bern, Switzerland
Tomas Dobrocky Department of Diagnostic and Interventional Neuroradiology, University Hospital Bern Inselspital, Bern, Switzerland
Jan Gralla Department of Diagnostic and Interventional Neuroradiology, University Hospital Bern Inselspital, Bern, Switzerland
Urs Fischer Department of Neurology, Inselspital University Hospital Bern, Bern, Switzerland
Sara Pilgram-Pastor Department of Diagnostic and Interventional Neuroradiology, University Hospital Bern Inselspital, Bern, Switzerland
Johannes Kaesmacher Department of Diagnostic and Interventional Neuroradiology, University Hospital Bern Inselspital, Bern, Switzerland Diagnostic and Interventional Neuroradiology, CIC-IT 1415, CHRU de Tours, Tours, France Le Studium Loire Valley Institute for Advanced Studies, Orléans, France

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Dynamic Perviousness Has Predictive Value for Clot Fibrin Content in Acute Ischemic Stroke

Dynamic perviousness is a novel imaging biomarker, with clot density measurements at multiple timepoints to allow longer contrast to thrombus interaction. We investigated the correlations between dynamic perviousness and clot composition in the setting of acute ischemic stroke. Thirty-nine patients with large vessel occlusion (LVO) undergoing mechanical thrombectomy (MT) were analyzed. Patients received a three-phase CT imaging pre-thrombectomy and histopathological analysis of retrieved clots. Clot densities for every phase and change in densities between phases were calculated, leading to four patterns of dynamic perviousness: no contrast uptake, early contrast uptake with and without washout and late uptake. Clots were categorized into three groups based on dominant histologic composition: red blood cell (RBC)-rich, fibrin/platelet-rich and mixed. Clot composition was correlated with dynamic perviousness using the Kruskal-Wallis test and Pearson's correlation analysis. The dynamic perviousness categories showed a significant difference between fibrin-rich clots when compared to RBC-rich plus mixed groups. The uptake without washout category had significantly fewer fibrin clots compared to the uptake with washout (p = 0.036), and nearly significantly fewer fibrin clots when compared to the no uptake category (p = 0.057). Contrast uptake with different patterns of contrast washout showed significant differences of the likelihood for fibrin-rich clots.

Dynamic Perviousness: A Novel Imaging Marker for Predicting Mechanical Thrombectomy Outcomes in Acute Ischemic Stroke

BACKGROUND

The predictive value of thrombus standard perviousness (SP) in acute ischemic stroke (AIS) for the technical success rates of mechanical thrombectomy (MT) or functional outcomes is not yet conclusive. We investigated the relationship between dynamic perviousness (DP) and revascularization results using time-dependent enhancement curve types determined with computed tomography (CT).

METHODS

A retrospective analysis of 137 AIS patients was performed. DP was calculated as the thrombus attenuation increase (TAI) using three time points and categorized into four groups: (1) no enhancement (CNE); (2) late enhancement (CLE); (3) early enhancement with washout (CW); (4) early enhancement without washout (CNW). Associations with the technical success rate and functional outcomes were assessed.

RESULTS

Late enhancement (CLE) had approximately two times higher odds for successful MT as compared to clots with other enhancement dynamics. The odds ratios (logistic regression model with CNW as the reference) for the TICI III scores were 4.04 (p = 0.067), 1.82 (p = 0.3), and 1.69 (p = 0.4) for CLE, CW, and CNE, respectively. The NIHSS scores at discharge and mRS scores at three months showed regression coefficients (linear regression model with CNW as reference) of -3.05 (p = 0.10), -1.17 (p = 0.51), and -1.24 (p = 0.47); and -1.30 (p = 0.097), -0.85 (p = 0.25), and -0.15 (p = 0.83) for CLE, CW, and CNE, respectively.

CONCLUSIONS

Thrombi with late enhancement patterns showed a higher revascularization rate and better outcomes as compared to clots with early uptake or no washout.

Dynamic Perviousness Predicts Revascularization Success in Acute Ischemic Stroke

BACKGROUND

The predictive value of thrombus perviousness in acute ischemic stroke (AIS), as measured by computed tomography (CT), has been intensively studied with conflicting results. In this study, we investigate the predictive potential of the novel concept of dynamic perviousness using three-dimensional (3D) volumetric evaluation of occlusive thrombi.

METHODS

The full thrombus volume in 65 patients with a hyperdense artery sign on non-contrast CT (NCCT), who underwent mechanical thrombectomy (MT), was segmented. Perviousness maps were computed voxel-wise for the entire thrombus volume as thrombus attenuation increase (TAI) between NCCT and CT angiography (CTA) as well as between CTA and late venous phase CT (CTV). Perviousness was analyzed for its association with NIHSS at admission, Thrombolysis In Cerebral Infarction (TICI) score, and number of MT passes.

RESULTS

The mean late-uptake TAI of thrombi with NIHSS scores greater than 21 at admission was approximately 100% higher than for lower scored NIHSS (p between 0.05 and 0.005). Concerning revascularization results, thrombi requiring less than four MT passes had ca. 80% higher group mean late-uptake TAI than clots requiring four or more passes (p = 0.03), and thrombi with TICI score III had ca. 95% higher group mean late-uptake TAI than thrombi with TICI II (p = 0.03). Standard perviousness showed no significant correlation with MT results.

CONCLUSION

Standard thrombus perviousness of 3D clot volume is not associated with revascularization results in AIS. In contrast, dynamic perviousness assessed with a voxel-wise characterization of 3D thrombi volume may be a better predictor of MT outcomes than standard perviousness.

Value of Automatically Derived Full Thrombus Characteristics: An Explorative Study of Their Associations with Outcomes in Ischemic Stroke Patients

(1) Background: For acute ischemic strokes caused by large vessel occlusion, manually assessed thrombus volume and perviousness have been associated with treatment outcomes. However, the manual assessment of these characteristics is time-consuming and subject to inter-observer bias. Alternatively, a recently introduced fully automated deep learning-based algorithm can be used to consistently estimate full thrombus characteristics. Here, we exploratively assess the value of these novel biomarkers in terms of their association with stroke outcomes. (2) Methods: We studied two applications of automated full thrombus characterization as follows: one in a randomized trial, MR CLEAN-NO IV (n = 314), and another in a Dutch nationwide registry, MR CLEAN Registry (n = 1839). We used an automatic pipeline to determine the thrombus volume, perviousness, density, and heterogeneity. We assessed their relationship with the functional outcome defined as the modified Rankin Scale (mRS) at 90 days and two technical success measures as follows: successful final reperfusion, which is defined as an eTICI score of 2b-3, and successful first-pass reperfusion (FPS). (3) Results: Higher perviousness was significantly related to a better mRS in both MR CLEAN-NO IV and the MR CLEAN Registry. A lower thrombus volume and lower heterogeneity were only significantly related to better mRS scores in the MR CLEAN Registry. Only lower thrombus heterogeneity was significantly related to technical success; it was significantly related to a higher chance of FPS in the MR CLEAN-NO IV trial (OR = 0.55, 95% CI: 0.31-0.98) and successful reperfusion in the MR CLEAN Registry (OR = 0.88, 95% CI: 0.78-0.99). (4) Conclusions: Thrombus characteristics derived from automatic entire thrombus segmentations are significantly related to stroke outcomes.

Connecting the DOTs: a novel imaging sign on flat-panel detector CT indicating distal vessel occlusions after thrombectomy

BACKGROUND

Immediate non-contrast post-interventional flat-panel detector CT (FPDCT) has been suggested as an imaging tool to assess complications after endovascular therapy (EVT). We systematically investigated a new imaging finding of focal hyperdensities correlating with remaining distal vessel occlusion after EVT.

METHODS

A single-center retrospective analysis was conducted for all acute ischemic stroke patients admitted between July 2020 and December 2022 who underwent EVT and immediate post-interventional FPDCT. A blinded core lab performed reperfusion grading on post-interventional digital subtraction angiography (DSA) images and evaluated focal hyperdensities on FPDCT (here called the distal occlusion tracker (DOT) sign). DOT sign was defined as a tubular or punctiform, vessel confined, hyperdense signal within the initial occlusion target territory. We assessed sensitivity and specificity of the DOT sign when compared with DSA findings.

RESULTS

The median age of the cohort (n=215) was 74 years (IQR 63-82) and 58.6% were male. The DOT sign was positive in half of the cohort (51%, 110/215). The DOT sign had high specificity (85%, 95% CI 72% to 93%), but only moderate sensitivity (63%, 95% CI 55% to 70%) for detection of residual vessel occlusions. In comparison to the core lab, operators overestimated complete reperfusion in a quarter of the entire cohort (25%, 53/215). In more than half of these cases (53%, 28/53) there was a positive DOT sign, which could have mitigated this overestimation.

CONCLUSION

The DOT sign appears to be a frequent finding on immediate post-interventional FPDCT. It correlates strongly with incomplete reperfusion and indicates residual distal vessel occlusions. In the future, it may be used to complement grading of reperfusion success and may help mitigating overestimation of reperfusion in the acute setting.

Thrombus imaging characteristics within acute ischemic stroke: similarities and interdependence

BACKGROUND

The effects of thrombus imaging characteristics on procedural and clinical outcomes after ischemic stroke are increasingly being studied. These thrombus characteristics - for eg, size, location, and density - are commonly analyzed as separate entities. However, it is known that some of these thrombus characteristics are strongly related. Multicollinearity can lead to unreliable prediction models. We aimed to determine the distribution, correlation and clustering of thrombus imaging characteristics based on a large dataset of anterior-circulation acute ischemic stroke patients.

METHODS

We measured thrombus imaging characteristics in the MR CLEAN Registry dataset, which included occlusion location, distance from the intracranial carotid artery to the thrombus (DT), thrombus length, density, perviousness, and clot burden score (CBS). We assessed intercorrelations with Spearman's coefficient (ρ) and grouped thrombi based on 1) occlusion location and 2) thrombus length, density and perviousness using unsupervised clustering.

RESULTS

We included 934 patients, of which 22% had an internal carotid artery (ICA) occlusion, 61% M1, 16% M2, and 1% another occlusion location. All thrombus characteristics were significantly correlated. Higher CBS was strongly correlated with longer DT (ρ=0.67, p<0.01), and moderately correlated with shorter thrombus length (ρ=-0.41, p<0.01). In more proximal occlusion locations, thrombi were significantly longer, denser, and less pervious. Unsupervised clustering analysis resulted in four thrombus groups; however, the cohesion within and distinction between the groups were weak.

CONCLUSIONS

Thrombus imaging characteristics are significantly intercorrelated - strong correlations should be considered in future predictive modeling studies. Clustering analysis showed there are no distinct thrombus archetypes - novel treatments should consider this thrombus variability.

Dual-energy CT in assessment of thrombus perviousness and its application in predicting outcomes after intravenous thrombolysis in acute ischemic stroke

PURPOSE

To evaluate the feasibility of using iodine overlay maps reconstructed from dual-energy CT (DECT) to assess thrombus perviousness and investigate its value in predicting outcomes after intravenous thrombolysis in patients with acute ischemic stroke.

METHOD

86 patients with proximal intracranial occlusions of the anterior circulation who underwent intravenous thrombolysis were included in this study. Thrombus iodine concentrations (IC_thrombus) and normalized iodine concentrations (NIC_thrombus) were compared to conventional perviousness parameters (thrombus attenuation increase, TAI; void fraction, ε and CTA-index). The associations between perviousness parameters and outcomes were analyzed by Spearman's correlation and regression analysis.

RESULTS

IC_thrombus and NIC_thrombus were significantly correlated with conventional perviousness parameters (P < 0.001). The median IC_thrombus was 6.81 (interquartile range [IQR], 4.76-8.73) mg/ml in the favorable functional outcome group, which was higher than 3.52 (IQR, 2.08-6.86) mg/ml in the unfavorable outcome group (P = 0.001). The median NIC_thrombus was 0.095 (IQR, 0.068-0.116) and 0.054 (IQR, 0.031-0.083) in the favorable and unfavorable outcome groups, respectively (P < 0.001). NIC_thrombus predicted favorable outcome with a higher area under the curve (AUC) of 0.755 than any conventional perviousness parameter (P < 0.05). In the multivariable regression model, IC_thrombus was independently associated with favorable outcome (odds ratio [OR] = 1.472, 95 % CI: 1.154-1.877, P = 0.002) and successful recanalization (OR = 1.356, 95 % CI: 1.093-1.681, P = 0.006). IC_thrombus was negatively correlated with the final infarct volume (FIV) (r = -0.262, P = 0.020). Results for NIC_thrombus were similar.

CONCLUSIONS

DECT is of great value in assessing thrombus perviousness. NIC_thrombus is a meaningful predictor of stroke prognosis and recanalization after intravenous thrombolysis in acute ischemic stroke.

Histologically interpretable clot radiomic features predict treatment outcomes of mechanical thrombectomy for ischemic stroke

PURPOSE

Radiomics features (RFs) extracted from CT images may provide valuable information on the biological structure of ischemic stroke blood clots and mechanical thrombectomy outcome. Here, we aimed to identify RFs predictive of thrombectomy outcomes and use clot histomics to explore the biology and structure related to these RFs.

METHODS

We extracted 293 RFs from co-registered non-contrast CT and CTA. RFs predictive of revascularization outcomes defined by first-pass effect (FPE, near to complete clot removal in one thrombectomy pass), were selected. We then trained and cross-validated a balanced logistic regression model fivefold, to assess the RFs in outcome prediction. On a subset of cases, we performed digital histopathology on the clots and computed 227 histomic features from their whole slide images as a means to interpret the biology behind significant RF.

RESULTS

We identified 6 significantly-associated RFs. RFs reflective of continuity in lower intensities, scattered higher intensities, and intensities with abrupt changes in texture were associated with successful revascularization outcome. For FPE prediction, the multi-variate model had high performance, with AUC = 0.832 ± 0.031 and accuracy = 0.760 ± 0.059 in training, and AUC = 0.787 ± 0.115 and accuracy = 0.787 ± 0.127 in cross-validation testing. Each of the 6 RFs was related to clot component organization in terms of red blood cell and fibrin/platelet distribution. Clots with more diversity of components, with varying sizes of red blood cells and fibrin/platelet regions in the section, were associated with RFs predictive of FPE.

CONCLUSION

Upon future validation in larger datasets, clot RFs on CT imaging are potential candidate markers for FPE prediction.

Spatial heterogeneity of occlusive thrombus in acute ischemic stroke: A systematic review

Following the advent of mechanical thrombectomy, occlusive clots in ischemic stroke have been amply characterized using conventional histopathology. Many studies have investigated the compositional variability of thrombi and the consequences of thrombus composition on treatment response. More recent evidence has emerged about the spatial heterogeneity of the clot or the preferential distribution of its components and compact nature. Here we review this emerging body of evidence, discuss its potential clinical implications, and propose the development of adequate characterization techniques.

Fully Automated Thrombus Segmentation on CT Images of Patients with Acute Ischemic Stroke

Thrombus imaging characteristics are associated with treatment success and functional outcomes in stroke patients. However, assessing these characteristics based on manual annotations is labor intensive and subject to observer bias. Therefore, we aimed to create an automated pipeline for consistent and fast full thrombus segmentation. We used multi-center, multi-scanner datasets of anterior circulation stroke patients with baseline NCCT and CTA for training (n = 228) and testing (n = 100). We first found the occlusion location using StrokeViewer LVO and created a bounding box around it. Subsequently, we trained dual modality U-Net based convolutional neural networks (CNNs) to segment the thrombus inside this bounding box. We experimented with: (1) U-Net with two input channels for NCCT and CTA, and U-Nets with two encoders where (2) concatenate, (3) add, and (4) weighted-sum operators were used for feature fusion. Furthermore, we proposed a dynamic bounding box algorithm to adjust the bounding box. The dynamic bounding box algorithm reduces the missed cases but does not improve Dice. The two-encoder U-Net with a weighted-sum feature fusion shows the best performance (surface Dice 0.78, Dice 0.62, and 4% missed cases). Final segmentation results have high spatial accuracies and can therefore be used to determine thrombus characteristics and potentially benefit radiologists in clinical practice.