Utility of single-energy and dual-energy computed tomography in clot characterization: An in-vitro study

Black hole sign migration in short-term brain CT scans: A possible link with clot evolution and histology

The black hole sign (BHS) is a rare radiological sign seen in the hyperacute phase of bleeding. It manifests within a hemorrhage in early hours, with limited studies exploring clot formation and evolution over a short duration. Despite various hypothesized mechanisms, the precise lifetime and dynamics of black hole sign development remain unclear. We describe the rare finding of a black hole sign within a deep brain hemorrhage, initially observed in the lateral portion of the clot during the first CT scan. Remarkably, in a subsequent CT scan, just 1 hour later, the BHS migrated towards the inner edge. Notably, while the hemorrhage size remained largely unchanged within this short timeframe, hyperacute bleeding led to increased perihematomal edema and sulci flattening. Histopathological features of the "evolving clot" are initially characterized by heightened cellularity. This increased cell density renders the hematoma less resistant to compressive forces, such as heightened endocranial pressure, offering a plausible explanation for the crushing and displacement of the BHS. Our study sheds light on the unique radiological progression of BHS within a deep brain ICH, emphasizing its association with dynamic clot formation and the consequential impact on surrounding structures.

The Value of Dual-Energy Computed Tomography Angiography-Derived Parameters in the Evaluation of Clot Composition

OBJECTIVES

We aimed to assess the value of dual-energy computed tomography angiography (DE-CTA) derived parameters as a quantitative biomarker of thrombus composition in acute ischemic stroke (AIS).

METHODS

AIS patients who underwent DE-CTA before thrombectomy between August 2016 and September 2022 were included in this study. We assessed the relative proportion of red blood cells (RBCs) and the fibrin/platelet ratio (F/P) of the retrieved clots and categorized the clots as RBC-dominant (RBCs > F/P) or F/P-dominant (F/P > RBCs). The thrombus based parameters were measured on polyenergetic images (PEI), virtual monoenergetic (VM), virtual non-contrast (VNC), iodine concentration (IC), and effective atomic number (Zeff) images respectively, and the slope of the spectral Hounsfield unit curve (λHU) was calculated. These parameters were compared in the DE-CTA images of RBC- and F/P-dominant thrombi. The diagnostic performance of the parameters was analyzed using the ROC curve. Correlations between thrombus composition and DE-CTA-derived parameters were assessed.

RESULTS

The retrieved clots in 54 of 88 patients (61.36%) were RBC-dominant. The RBC-dominant thrombi showed significantly higher VNC values and lower IC, λHU, and Zeff values than the F/P-dominant thrombi (p < 0.05). The CT density measured on IC images showed the largest AUC value (AUC, 0.94; sensitivity, 77.78%; specificity, 100.00%). The Spearman rank-order correlation coefficient values showed that CT density measured on IC images of the thrombus showed the strongest association with the proportion of RBCs (r = -0.64, p < 0.001) and F/P (r = 0.65, p < 0.001).

CONCLUSIONS

DE-CTA-derived parameters, especially the CT density measured on IC images, could be associated with thrombus composition and allow for personalized thrombectomy strategies.

Deep learning prediction of stroke thrombus red blood cell content from multiparametric MRI

BACKGROUND AND PURPOSE

Thrombus red blood cell (RBC) content has been shown to be a significant factor influencing the efficacy of acute ischemic stroke treatment. In this study, our objective was to evaluate the ability of convolutional neural networks (CNNs) to predict ischemic stroke thrombus RBC content using multiparametric MR images.

MATERIALS AND METHODS

Retrieved stroke thrombi were scanned ex vivo using a three-dimensional multi-echo gradient echo sequence and histologically analyzed. 188 thrombus R2*, quantitative susceptibility mapping and late-echo GRE magnitude image slices were used to train and test a 3-layer CNN through cross-validation. Data augmentation techniques involving input equalization and random image transformation were employed to improve network performance. The network was assessed for its ability to quantitatively predict RBC content and to classify thrombi into RBC-rich and RBC-poor groups.

RESULTS

The CNN predicted thrombus RBC content with an accuracy of 62% (95% CI 48-76%) when trained on the original dataset and improved to 72% (95% CI 60-84%) on the augmented dataset. The network classified thrombi as RBC-rich or poor with an accuracy of 71% (95% CI 58-84%) and an area under the curve of 0.72 (95% CI 0.57-0.87) when trained on the original dataset and improved to 80% (95% CI 69-91%) and 0.84 (95% CI 0.73-0.95), respectively, on the augmented dataset.

CONCLUSIONS

The CNN was able to accurately predict thrombus RBC content using multiparametric MR images, and could provide a means to guide treatment strategy in acute ischemic stroke.

Magnetic resonance imaging quantitative T2* mapping to predict the red blood cell content of in vivo thrombi retrieved from patients with large vessel occlusions in acute ischemic stroke

BACKGROUND AND PURPOSE

Magnetic resonance imaging quantitative T2* mapping has shown reliable identification of thrombus red blood cell content in vitro. The thrombus composition has been in vivo, associated with outcomes after endovascular therapy for acute ischemic stroke. We aim to analyze the red blood cell content of thrombi retrieved from patients with large vessel occlusions in relation to the thrombus-T2* relaxation time in magnetic resonance imaging.

MATERIAL AND METHODS

Consecutive acute ischemic stroke patients treated by endovascular therapy were scanned with an magnetic resonance imaging quantitative T2* mapping sequence. Quantitative histologic evaluations of red blood cell content were performed. A linear regression assessed the association between vascular risk factors, comorbidities, antithrombotic drugs intake, baseline National Institutes of Health Stroke Scale (NIHSS), intravenous thrombolysis before endovascular therapy, time between onset and groin puncture, patient's outcome at 3 months, magnetic resonance imaging quantitative T2* mapping results, and the red blood cell content of thrombi. The correlation between the mean thrombus-T2* relaxation time and red blood cell content was assessed by calculating the Pearson correlation coefficient.

RESULTS

Among 31 thrombi, 16 were "Fibrin rich" and 15 "red blood cell dominant." The median red blood cell content was 39 (range, 0-90; interquartile range, 37). The median (interquartile range) thrombus-T2* relaxation time was shorter in "red blood cell dominant" thrombi (21, interquartile range 6) than in "Fibrin rich" thrombi (24, interquartile range 7), without significant difference (p = 0.15), as shown in the Box plot. An inverse correlation between thrombus-T2* relaxation time and red blood cell content was found, with a correlation coefficient of -0.41 (95% CI, -0.67 to -0.08, p = 0.02).

CONCLUSION

Our study shows that a shorter thrombus-T2* relaxation time is related to a higher red blood cell content within in vivo thrombi.

A review on the association of thrombus composition with mechanical and radiological imaging characteristics in acute ischemic stroke

Thrombus composition and mechanical properties significantly impact the ease and outcomes of thrombectomy procedures in patients with acute ischemic stroke. A wide variation exists in the composition of thrombi between patients. If a relationship can be determined between the composition of a thrombus and its mechanical behaviour, as well as between the composition of a thrombus and its radiological imaging characteristics, then there is the potential to personalise thrombectomy treatment based on each individual thrombus. This review aims to give an overview of the current literature addressing this issue. Here, we present a scoping review detailing associations between thrombus composition, mechanical behaviour and radiological imaging characteristics. We conducted two searches 1) on the association between thrombus composition and the mechanical behaviour of the tissue and 2) on the association between radiological imaging characteristics and thrombus composition in the acute stroke setting. The review suggests that higher fibrin and lower red blood cell (RBC) content contribute to stiffer thrombi independent of the loading mode. Further, platelet-contracted thrombi are stiffer than non-contracted compositional counterparts. Fibrin content contributes to the elastic portion of viscoelastic behaviour while RBC content contributes to the viscous portion. It is possible to identify fibrin-rich or RBC-rich thrombi with computed tomography and magnetic resonance imaging vessel signs. Standardisation is required to quantify the association between thrombus density on non-contrast computed tomography and the RBC content. The characterisation of the thrombus fibrin network has not been addressed so far in radiological imaging but may be essential for the prediction of device-tissue interactions and distal thrombus embolization. The association between platelet-driven clot contraction and radiological imaging characteristics has not been explicitly investigated. However, evidence suggests that perviousness may be a marker of clot contraction.

Studying Stroke Thrombus Composition After Thrombectomy: What Can We Learn?

The composition of ischemic stroke thrombi has gained an increasing amount of interest in recent years. The implementation of endovascular procedures in standard stroke care has granted researchers the unique opportunity to examine patient thrombus material. Increasing evidence indicates that stroke thrombi are complex and heterogenous, consisting of various biochemical (eg, fibrin, von Willebrand Factor, and neutrophil extracellular traps) and cellular (eg, red blood cells, platelets, leukocytes, and bacteria) components. This complex composition may explain therapeutic limitations and also offer novel insights in several aspects of stroke management. Better understanding of thrombus characteristics could, therefore, potentially lead to improvements in the management of patients with stroke. In this review, we provide a comprehensive overview of the lessons learned by examining stroke thrombus composition after endovascular thrombectomy and its potential relevance for thrombectomy success rates, thrombolysis, clinical outcomes, stroke etiology, and radiological imaging.

Study of correlations between CT properties of retrieved cerebral thrombi with treatment outcome of stroke patients

Background

All the patients with suspected stroke are directed to whole-brain CT scan. The purpose of this scan is to look for early features of ischemia and to rule out alternative diagnoses than stroke. In case of ischemic stroke, CT diagnostics (including CT angiography) is used mainly to locate the occlusion and its size, while the Hounsfield Units (HU) values of the thrombus causing the stroke are usually overlooked on CT scan or considered not important. The aim of this study was to demonstrate that the HU value is relevant and can help in better treatment planning.

Patients and methods

There were 25 patients included in the study, diagnosed with ischemic stroke in the middle cerebral artery (MCA) territory. In all patients, systemic thrombolysis was not successful and the mechanical recanalization was needed. The retrieved thrombi were also analyzed histologically for the determination of red blood cells (RBC) proportion. CT of the proximal MCA (M1) segment was analyzed for average HU value and its variability both in the occluded section and the symmetrical normal site. These CT parameters were then statistically studied for the possible correlations with different clinical, histological and procedure parameters using the Linear Regression and the Pearson correlation coefficient.

Results

Relevant positive correlations were found between average HU value of thrombus and outcome modified Rankin Scale (mRS), initial mRS, number of passes with thrombectomy device as well as RBC proportion.

Conclusions

Results of the present study suggest that measured HU values in CT images of the cerebral thrombi may help in the assessment of thrombus compaction and therefore better treatment planning.

In-Vitro Visualization of Thrombus Growth in Artificial Lungs Using Real-Time X-Ray Imaging: A Feasibility Study

PURPOSE

Extracorporeal membrane oxygenation has gained increasing attention in the treatment of patients with acute and chronic cardiopulmonary and respiratory failure. However, clotting within the oxygenators or other components of the extracorporeal circuit remains a major complication that necessitates at least a device exchange and bears risks of adverse events for the patients. In order to better predict thrombus growth within oxygenators, we present an approach for in-vitro visualization of thrombus growth using real-time X-ray imaging.

METHODS

An in-vitro test setup was developed using low-dose anticoagulated ovine blood and allowing for thrombus growth within 4 h. The setup was installed in a custom-made X-ray setup that uses phase-contrast for imaging, thus providing enhanced soft-tissue contrast, which improves the differentiation between blood and potential thrombus growth. During experimentation, blood samples were drawn for the analysis of blood count, activated partial thromboplastin time and activated clotting time. Additionally, pressure and flow data was monitored and a full 360° X-ray scan was performed every 15 min.

RESULTS

Thrombus formation indicated by a pressure drop and changing blood parameters was monitored in all three test devices. Red and white thrombi (higher/lower attenuation, respectively) were successfully segmented in one set of X-ray images.

CONCLUSION

We showed the feasibility of a new in-vitro method for real-time thrombus growth visualization by means of phase contrast X-ray imaging. In addition, with more blood parameters that are clinically relevant, this approach might contribute to improved oxygenator exchange protocols in the clinical routine.

Intimal Sarcoma of the Great Vessels

Intimal sarcomas of the pulmonary artery and aorta are rare entities with a poor prognosis. In many instances, pulmonary artery sarcomas are misinterpreted as acute or chronic pulmonary thromboembolism, whereas aortic intimal sarcomas are often misdiagnosed as protuberant atherosclerotic disease or intimal thrombus. Discernment of intimal sarcomas from these and other common benign entities is essential for the timely initiation of aggressive therapy. The most useful imaging modalities for assessment of a suspected intimal sarcoma include CT angiography, fluorine 18-fluorodeoxyglucose PET, and MRI. The authors discuss the clinical features, current treatment options, characteristic imaging findings, and underlying pathologic features of intimal sarcomas. The authors emphasize imaging discernment of intimal sarcomas and how their differential diagnosis is informed by knowledge of radiologic-pathologic correlation. The most reliable distinguishing imaging features are also emphasized to improve accurate and timely diagnosis. Online supplemental material is available for this article. ^©RSNA, 2021.

Imaging-based prediction of histological clot composition from admission CT imaging

BACKGROUND

Thrombus composition has been shown to be a major determinant of recanalization success and occurrence of complications in mechanical thrombectomy. The most important parameters of thrombus behavior during interventional procedures are relative fractions of fibrin and red blood cells (RBCs). We hypothesized that quantitative information from admission non-contrast CT (NCCT) and CT angiography (CTA) can be used for machine learning based prediction of thrombus composition.

METHODS

The analysis included 112 patients with occlusion of the carotid-T or middle cerebral artery who underwent thrombectomy. Thrombi samples were histologically analyzed and fractions of fibrin and RBCs were determined. Thrombi were semi-automatically delineated in CTA scans and NCCT scans were registered to the same space. Two regions of interest (ROIs) were defined for each thrombus: small-diameter ROIs capture vessel walls and thrombi, large-diameter ROIs reflect peri-vascular tissue responses. 4844 quantitative image markers were extracted and evaluated for their ability to predict thrombus composition using random forest algorithms in a nested fivefold cross validation.

RESULTS

Test set receiver operating characteristic area under the curve was 0.83 (95% CI 0.80 to 0.87) for differentiating RBC-rich thrombi and 0.84 (95% CI 0.80 to 0.87) for differentiating fibrin-rich thrombi. At maximum Youden-Index, RBC-rich thrombi were identified at 77% sensitivity and 74% specificity; for fibrin-rich thrombi the classifier reached 81% sensitivity at 73% specificity.

CONCLUSIONS

Machine learning based analysis of admission imaging allows for prediction of clot composition. Perspectively, such an approach could allow selection of clot-specific devices and retrieval procedures for personalized thrombectomy strategies.

Dual-energy computed tomography in acute ischemic stroke: state-of-the-art

Abstract

Dual-energy computed tomography (DECT) allows distinguishing between tissues with similar X-ray attenuation but different atomic numbers. Recent studies demonstrated that this technique has several areas of application in patients with ischemic stroke and a potential impact on patient management. After endovascular stroke therapy (EST), hyperdense areas can represent either hemorrhage or contrast staining due to blood-brain barrier disruption, which can be differentiated reliably by DECT. Further applications are improved visualization of early infarctions, compared to single-energy computed tomography, and prediction of transformation into infarction or hemorrhage in contrast-enhancing areas. In addition, DECT allows detection and evaluation of the material composition of intra-arterial clots after EST. This review summarizes the clinical state-of-the-art of DECT in patients with stroke, and features some prospects for future developments.

Key points

• Dual-energy computed tomography (DECT) allows differentiation between tissues with similar X-ray attenuation but differentatomic numbers.

• DECT has several areas of application in patients with ischemic stroke and a potential impact on patient management.

• Prospects for future developments in DECT may improve treatment decision-making.

Characterization of thrombus composition with multimodality CT-based imaging: an in-vitro study

BACKGROUND

CT is the most commonly used imaging modality for acute ischemic stroke evaluation. There is growing interest to use pre-operative imaging to characterize clot composition in stroke. We performed an in-vitro study examining the ability of various CT techniques in differentiation between different clot types.

METHODS

Five clot types with varying fibrin and red blood cells (RBCs) densities (5% RBC and 95% fibrin; 25% RBC and 75% fibrin; 50% RBC and 50% fibrin; 75% RBC and 25% fibrin; 95% RBC and 5% fibrin) were prepared and scanned using various CT scanning protocols (single-energy, dual-energy, photon-counting detector CT, mixed images, and virtual monoenergetic images). Martius Scarlett Blue trichrome staining was performed to confirm the composition of each clot. Mean CT values of each type of clot under different scanning protocol were calculated and compared.

RESULTS

Mean CT values of the CT numbers in the five clot specimens for 5%, 25%, and 50% RBC clot were similar across modalities, and increased significantly for 75% and 95% RBC clots (P<0.0001). Mean CT values are highest in the Mono +50 keV images in each type of clot, and they were also significantly higher than all other imaging protocols (P<0.001). Dual-energy CT with Mono +50 keV images showed the greatest difference between attenuation in each type of clot.

CONCLUSION

Mono +50 keV dual-energy CT scan may be helpful for differentiating between RBC-rich and fibrin-rich thrombi seen in large-vessel occlusion patients.

A Review of the Applications of Dual-Energy CT in Acute Neuroimaging

Dual-energy computed tomography (CT) is a promising tool with increasing availability and multiple emerging and established clinical applications in neuroradiology. With its ability to allow characterization of materials based on their differential attenuation when imaged at two different energy levels, dual-energy CT can help identify the composition of brain, neck, and spinal components. Virtual monoenergetic imaging allows a range of simulated single energy-level reconstructions to be created with postprocessing. Low-energy reconstructions can aid identification of edema, ischemia, and subtle lesions due to increased soft tissue contrast as well as increasing contrast-to-noise ratios on angiographic imaging. Higher energy reconstructions can reduce image artifact from dental amalgam, aneurysm clips and coils, spinal hardware, dense contrast, and dense bones. Differentiating iodine from hemorrhage may help guide management of patients after thrombectomy and aid diagnosis of enhancing tumors within parenchymal hemorrhages. Iodine quantification may predict hematoma expansion in aneurysmal bleeds and outcomes in traumatic brain injury. Calcium and bone subtraction can be used to distinguish hemorrhage from brain parenchymal mineralization as well as improving visualization of extra-axial lesions and vessels adjacent to dense plaque or skull. This article reviews the basics of dual-energy CT and highlights many of its clinical applications in the evaluation of acute neurological presentations.

Clot Analog Attenuation in Non-contrast CT Predicts Histology: an Experimental Study Using Machine Learning

Exact histological clot composition remains unknown. The purpose of this study was to identify the best imaging variables to be extrapolated on clot composition and clarify variability in the imaging of thrombi by non-contrast CT. Using a CT-phantom and covering a wide range of histologies, we analyzed 80 clot analogs with respect to X-ray attenuation at 24 and 48 h after production. The mean, maximum, and minimum HU values for the axial and coronal reconstructions were recorded. Each thrombus underwent a corresponding histological analysis, together with a laboratory analysis of water and iron contents. Decision trees, a type of supervised machine learning, were used to select the primary variable altering attenuation and the best parameter for predicting histology. The decision trees selected red blood cells (RBCs) for correlation with all attenuation parameters (p < 0.001). Conversely, maximum attenuation on axial CT offered the greatest accuracy for discriminating up to four groups of clot histology (p < 0.001). Similar RBC-rich thrombi displayed variable imaging associated with different iron (p = 0.023) and white blood cell contents (p = 0.019). Water content varied among the different histologies but did not in itself account for the differences in attenuation. Independent factors determining clot attenuation were the RBCs (β = 0.33, CI = 0.219-0.441, p < 0.001) followed by the iron content (β = 0.005, CI = 0.0002-0.009, p = 0.042). Our findings suggest that it is possible to extract more and valuable information from NCCT that can be extrapolated to provide insights into clot histological and chemical composition.

Unenhanced Dual-Energy Computed Tomography: Visualization of Brain Edema

PURPOSE

The aim of this study was to determine whether dual-energy computed tomography (DECT) imaging is superior to conventional noncontrast computed tomography (CT) imaging for the detection of acute ischemic stroke.

MATERIALS AND METHODS

This was a retrospective, single-center study of 40 patients who presented to the emergency department (ED) of a major, acute care, teaching center with signs and symptoms of acute stroke. Only those patients who presented to the ED within 4 hours of symptom onset were included in this study. All 40 patients received a noncontrast DECT of the head at the time of presentation. Each patient also received standard noncontrast CT of the head 24 hours after their initial presentation to the ED. "Brain edema" images were then reconstructed using 3-material decomposition with parameters adjusted to suppress gray/white matter contrast while preserving edema and increasing its conspicuity. The initial unenhanced, mixed images, brain edema, and 24-hour follow-up true noncontrast (TNC) images were reviewed and assigned Alberta Stroke Program Early CT scores. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated.

RESULTS

Of the 40 patients, 28 (70%) were diagnosed with an acute infarction. Brain edema reconstructions were better able to predict end infarction volume, with Alberta Stroke Program Early CT scores similar to the 24-hour follow-up TNC CT (7.75 vs 7.7; P > 0.05), whereas the mixed images routinely underestimated the extent of infarction (8.975 vs 7.7; P < 0.001). Initial TNC images had a sensitivity, specificity, PPV, and NPV of 80% (95% confidence interval [CI], 51.9%-95.7%), 72.7% (95% CI, 39%-94%), 80% (95% CI, 51.9%-95.7%), and 72.73% (95% CI, 51.91%-95.67%), respectively. The DECT brain edema images provided a sensitivity, specificity, PPV, and NPV of 93.33% (95% CI, 68.05%-99.83%), 100% (95% CI, 71.51%-100%), 100% (95% CI, 76.84%-100%), and 91.67% (95% CI, 61.52%-99.79%), respectively. There was very good interrater reliability across all 3 imaging techniques.

CONCLUSION

Brain edema reconstructions are able to more accurately detect edema and end-infarct volume as compared with initial TNC images. This provides a better assessment of the degree and extent of infarction and may serve to better guide therapy in the future.

Clot Pathophysiology: Why Is It Clinically Important?

Cerebral ischemic stroke treatment may change significantly now that clots are actually physically removed from the patient using thrombectomy. This allows for an analysis of the content of the clots as well as the correlation of the imaging findings and the clot behavior and morphology. This article illustrates how the interaction of different clots varies in the clinical setting and how analysis of clot composition, as well as the search for new pharmacologic targets, can lead to a better understanding of the pathophysiology and therapy resistance, in turn providing possibilities for a better approach in the treatment.