Radiomics-Based Predictive Nomogram for Assessing the Risk of Intracranial Aneurysms.

Background: Aneurysm wall enhancement (AWE) has the potential to be used as an imaging biomarker for the risk stratification of intracranial aneurysms (IAs). Radiomics provides a refined approach to quantify and further characterize AWE's textural features. This study examines the performance of AWE quantification combined with clinical information in detecting symptomatic IAs. Methods: Ninety patients harboring 104 IAs (29 symptomatic and 75 asymptomatic) underwent high-resolution magnetic resonance imaging (HR-MRI). The assessment of AWE was performed using two different methods: 3D-AWE mapping and composite radiomics-based score (RadScore). The dataset was split into training and testing subsets. The testing set was used to build two different nomograms using each modality of AWE assessment combined with patients' demographic information and aneurysm morphological data. Finally, each nomogram was evaluated on an independent testing set. Results: A total of 22 radiomic features were significantly different between symptomatic and asymptomatic IAs. The 3D-AWE Mapping nomogram achieved an area under the curve (AUC) of 0.77 (63% accuracy, 78% sensitivity and 58% specificity). The RadScore nomogram exhibited a better performance, achieving an AUC of 0.83 (77% accuracy, 89% sensitivity and 73% specificity). Conclusions : Combining AWE quantification through radiomic analysis with patient demographic data in a clinical nomogram achieved high accuracy in detecting symptomatic IAs.

Decoding Molecular Mechanisms Underlying Outcomes After Ischemic Stroke Thrombectomy by RNA Sequencing of Retrieved Clots.

BACKGROUND: Transcriptomic profiling has emerged as a powerful tool for exploring the molecular landscape of ischemic stroke clots and providing insights into the pathophysiological mechanisms underlying stroke progression and recovery. In this study, we aimed to investigate the relationship between stroke clot transcriptomes and stroke thrombectomy outcome, as measured by early neurological improvement (ENI) 30 (i.e., a 30% reduction in NIHSS at 24 h post-thrombectomy). HYPOTHESIS: We hypothesized that there exist distinct clot gene expression patterns between good and poor neurological outcomes. METHODS: Transcriptomic analysis of 32 stroke clots retrieved by mechanical thrombectomy was conducted. Transcriptome data of these clots were analyzed to identify differentially expressed genes (DEGs), defined as those with a log(fold-change) ≥ 1.5 and q < 0.05 between samples with good and poor early neurological outcomes. Gene ontology and bioinformatics analyses were performed on genes with p < 0.01 to identify enriched biological processes and Ingenuity Pathway Analysis canonical pathways. Moreover, AUC analysis assessed the predictive power of DEGs for 90-day function outcome (mRS ≤ 2) and cellular composition of clot was predicted using CIBERSORT. We also assessed whether differential enrichment of immune cell types could indicate patient survival. RESULTS: A total of 41 DEGs were identified. Bioinformatics showed that enriched biological processes and pathways emphasized the chronic immune response and matrix metalloproteinase inhibition. Moreover, 25 of the DEGs were found to be significant predictors of 90-day mRS. These genes were indicative of monocytes enrichment and neutrophil depletion in patients with poorer outcomes. CONCLUSION: Our study revealed a distinct gene expression pattern and dysregulated biological pathways associated with ENI. This expression pattern was also predictive of long-term outcome, suggesting a biological link between those ENIs and 90-day mRS.

Single-Cell Transcriptional Signatures of Glomerular Disease in Transgenic Mice with APOL1 Variants.

BACKGROUND: APOL1 high-risk variants contribute to kidney disease among African-ancestry individuals. We sought to describe cell-specific APOL1 variants-induced pathways using two mouse models. METHODS: We characterized bacterial artificial chromosome (BAC)/APOL1 transgenic mice crossed with HIV-associated nephropathy (HIVAN) Tg26 mice and BAC/APOL1 transgenic mice given interferon-γ. RESULTS: Both mouse models showed more severe glomerular disease in APOL1-G1 compared to APOL1-G0 mice. Bulk RNA-seq of HIVAN model-glomeruli identified synergistic podocyte-damaging pathways activated by APOL1-G1 and by the HIV transgene. Single-nuclear RNA-seq revealed podocyte-specific patterns of differentially-expressed genes as a function of APOL1 alleles. Shared activated pathways, e.g. mTOR, and differentially-expressed genes, e.g. Ccn2, in podocytes in both models suggest novel markers of APOL1-associated kidney disease. HIVAN mouse-model podocyte single-nuclear RNA-seq data showed similarity to human focal segmental glomerulosclerosis glomerular RNA-seq data. Differential effects of the APOL1-G1 variant on the eukaryotic Initiation factor-2 pathway highlighted differences between the two models. CONCLUSIONS: These findings in two mouse models demonstrated both shared and distinct cell type-specific transcriptomic signatures induced by APOL1 variants. These findings suggest novel therapeutic opportunities for APOL1 glomerulopathies.

Dual Layer vs Single Layer Woven EndoBridge Device in the Treatment of Intracranial Aneurysms: A Propensity Score-Matched Analysis.

BACKGROUND: The Woven EndoBridge (WEB) devices have been used for treating wide neck bifurcation aneurysms (WNBAs) with several generational enhancements to improve clinical outcomes. The original device dual-layer (WEB DL) was replaced by a single-layer (WEB SL) device in 2013. This study aimed to compare the effectiveness and safety of these devices in managing intracranial aneurysms. METHODS: A multicenter cohort study was conducted, and data from 1,289 patients with intracranial aneurysms treated with either the WEB SL or WEB DL devices were retrospectively analyzed. Propensity score matching was utilized to balance the baseline characteristics between the two groups. Outcomes assessed included immediate occlusion rate, complete occlusion at last follow-up, retreatment rate, device compaction, and aneurysmal rupture. RESULTS: Before propensity score matching, patients treated with the WEB SL had a significantly higher rate of complete occlusion at the last follow-up and a lower rate of retreatment. After matching, there was no significant difference in immediate occlusion rate, retreatment rate, or device compaction between the WEB SL and DL groups. However, the SL group maintained a higher rate of complete occlusion at the final follow-up. Regression analysis showed that SL was associated with higher rates of complete occlusion (OR: 0.19; CI: 0.04 to 0.8, p = 0.029) and lower rates of retreatment (OR: 0.12; CI: 0 to 4.12, p = 0.23). CONCLUSION: The WEB SL and DL devices demonstrated similar performances in immediate occlusion rates and retreatment requirements for intracranial aneurysms. The SL device showed a higher rate of complete occlusion at the final follow-up.

The impact of postoperative aspirin in patients undergoing Woven EndoBridge: a multicenter, institutional, propensity score-matched analysis.

BACKGROUND: The Woven EndoBridge (WEB) device is frequently used for the treatment of intracranial aneurysms. Postoperative management, including the use of aspirin, varies among clinicians and institutions, but its impact on the outcomes of the WEB has not been thoroughly investigated. METHODS: This was a retrospective, multicenter study involving 30 academic institutions in North America, South America, and Europe. Data from 1492 patients treated with the WEB device were included. Patients were categorized into two groups based on their postoperative use of aspirin (aspirin group: n=1124, non-aspirin group: n=368). Data points included patient demographics, aneurysm characteristics, procedural details, complications, and angiographic and functional outcomes. Propensity score matching (PSM) was applied to balance variables between the two groups. RESULTS: Prior to PSM, the aspirin group exhibited significantly higher rates of modified Rankin scale (mRS) mRS 0-1 and mRS 0-2 (89.8% vs 73.4% and 94.1% vs 79.8%, p<0.001), lower rates of mortality (1.6% vs 8.6%, p<0.001), and higher major compaction rates (13.4% vs 7%, p<0.001). Post-PSM, the aspirin group showed significantly higher rates of retreatment (p=0.026) and major compaction (p=0.037) while maintaining its higher rates of good functional outcomes and lower mortality rates. In the multivariable regression, aspirin was associated with higher rates of mRS 0-1 (OR 2.166; 95% CI 1.16 to 4, p=0.016) and mRS 0-2 (OR 2.817; 95% CI 1.36 to 5.88, p=0.005) and lower rates of mortality (OR 0.228; 95% CI 0.06 to 0.83, p=0.025). However, it was associated with higher rates of retreatment (OR 2.471; 95% CI 1.11 to 5.51, p=0.027). CONCLUSIONS: Aspirin use post-WEB treatment may lead to better functional outcomes and lower mortality but with higher retreatment rates. These insights are crucial for postoperative management after WEB procedures, but further studies are necessary for validation.

MicroCT and Histological Analysis of Clot Composition in Acute Ischemic Stroke : A Comparative Study of MT-Retrieved Clots and Clot Analogs.

PURPOSE: Assessing clot composition on prethrombectomy computed tomography (CT) imaging may help in stroke treatment planning. In this study we seek to use microCT imaging of fabricated blood clots to understand the relationship between CT radiographic signals and the biological makeup. METHODS: Clots (n = 10) retrieved by mechanical thrombectomy (MT) were collected, and 6 clot analogs of varying RBC composition were made. We performed paired microCT and histological image analysis of all 16 clots using a ScanCo microCT 100 (4.9 µm resolution) and standard H&E staining (imaged at 40×). From these data types, first order statistic (FOS) radiomics were computed from microCT, and percent composition of RBCs (%RBC) was computed from histology. Polynomial and linear regression (LR) were used to build statistical models based on retrieved thrombus microCT and %RBC that were evaluated for their ability to predict the %RBC of clot analogs from mean HU. Correlation analyses of microCT FOS with composition were completed for both retrieved clots and analogs. RESULTS: The LR model fits relating MT-retrieved clot %RBC with mean (R2 = 0.625, p = 0.006) and standard deviation (R2 = 0.564, p < 0.05) in HUs on microCT were significant. Similarly, LR models relating analog histological %RBC to analog protocol %RBC (R2 = 0.915, p = 0.003) and mean HUs on microCT (R2 = 0.872, p = 0.007) were also significant. When the LR model built using MT-retrieved clots was used to predict analog %RBC from mean HUs, significant correlation was observed between predictions and actual histological %RBC (R2 = 0.852, p = 0.009). For retrieved clots, significant correlations were observed for energy and total energy with %RBC and %FP (|R| > 0.7, q < 0.01). Analogs further demonstrated significant correlation between FOS energy, total energy, variance and %WBC (|R| > 0.9, q < 0.01). CONCLUSION: MicroCT can be used to build models that predict AIS clot composition from routine CT parameters and help us to better understand radiomic signatures associated with clot composition and first pass outcomes. In future work, such observations can be used to better infer clot composition and inform thrombectomy prognostics from pretreatment CTs.

FAK and p130Cas modulate stiffness-mediated early transcription and cellular metabolism.

Cellular metabolism is influenced by the stiffness of the extracellular matrix. Focal adhesion kinase (FAK) and its binding partner, p130Cas, transmit biomechanical signals about substrate stiffness to the cell to regulate a variety of cellular responses, but their roles in early transcriptional and metabolic responses remain largely unexplored. We cultured mouse embryonic fibroblasts with or without siRNA-mediated FAK or p130Cas knockdown and assessed the early transcriptional responses of these cells to placement on soft and stiff substrates by RNA sequencing and bioinformatics analyses. Exposure to the stiff ECM altered the expression of genes important for metabolic and biosynthetic processes, and these responses were influenced by knockdown of FAK and p130Cas. Our findings reveal that FAK-p130Cas signaling mechanotransduces ECM stiffness to early transcriptional changes that alter cellular metabolism and biosynthesis.

Preradiosurgical Embolization of Arteriovenous Malformations Reduces Target Volume - The Main Determinant for Complete Obliteration.

BACKGROUND: Embolization and stereotactic radiosurgery (SRS) have increasingly been used to treat complex arteriovenous malformations (AVMs). We studied outcomes of AVM patients treated through a multidisciplinary approach, examined the effect of embolization on SRS success, and analyzed predictors of treatment failure. METHODS: We retrospectively reviewed a prospectively maintained database of patients with AVMs treated with Gamma Knife (Leksell) SRS over an 11-year period. Patients with incomplete medical records and follow-up <2 years were excluded. Demographics, clinical presentation, previous rupture history, angiographic nidus size, Spetzler-Martin (S-M) grade, adjunctive endovascular embolization and microsurgical resection, radiologic evidence of obliteration and hemorrhage, and clinical outcomes (modified Rankin Scale [mRS] scores) were recorded. Radiosurgery-related details including nidus volume and number of sessions and radiosurgery-, embolization-, and resection-associated complications were also recorded. RESULTS: Eighty-three patients (mean age, 41.0 ± 21.3 years) were included. Mean reduction in AVM nidus target volume with endovascular embolization was 66.0 ± 19.7%. S-M grade reduction was achieved in 51.6% cases. Total obliteration after SRS was achieved in 56 AVMs (67.5%) after 2 years, and in 38 (86.4%) after 4 years. Two (2.4%) patients had rehemorrhage after SRS. Overall complication rate was 3.6%. Median angiographic follow-up was 55.5 months. Favorable outcomes (mRS = 0-2) were seen in 77.1%. SRS target volume was an independent predictor of treatment failure regardless of pre-SRS embolization. CONCLUSIONS: High AVM obliteration rates were achieved with judicious use of radiosurgery alone or with embolization. Embolization reduced target nidus volume by an average of 66%. SRS target volume was an independent predictor of treatment failure.

Stent-assisted Woven EndoBridge device for the treatment of intracranial aneurysms: an international multicenter study.

OBJECTIVE: The Woven EndoBridge (WEB) device is an intrasaccular flow disruptor designed for wide-necked bifurcation aneurysms. These aneurysms may require the use of a concomitant stent. The objective of this study was to determine the clinical and radiological outcomes of patients undergoing stent-assisted WEB treatment. In addition, the authors also sought to determine the predictors of a concomitant stent in aneurysms treated with the WEB device. METHODS: The data for this study were taken from the WorldWideWEB Consortium, an international multicenter cohort including patients treated with the WEB device. Aneurysms were classified into two groups based on treatment: stent-assisted WEB and WEB device alone. The authors compared clinical and radiological outcomes of both groups. Univariable and multivariable binary logistic regression analyses were performed to determine factors that predispose to stent use. RESULTS: The study included 691 intracranial aneurysms (31 with stents and 660 without stents) treated with the WEB device. The adequate occlusion status did not differ between the two groups at the latest follow-up (83.3% vs 85.6%, p = 0.915). Patients who underwent stenting had more thromboembolic (32.3% vs 6.5%, p < 0.001) and procedural (16.1% vs 3.0%, p < 0.001) complications. Aneurysms treated with a concomitant stent had wider necks, greater heights, and lower dome-to-neck ratios. Increasing neck size was the only significant predictor for stent use. CONCLUSIONS: This study demonstrates that there is no difference in the degree of aneurysm occlusion between the two groups; however, complications were more frequent in the stent group. In addition, a wider aneurysm neck predisposes to stent assistance in WEB-treated aneurysms.

Survivin as a mediator of stiffness-induced cell cycle progression and proliferation of vascular smooth muscle cells.

Stiffened arteries are a pathology of atherosclerosis, hypertension, and coronary artery disease and a key risk factor for cardiovascular disease events. The increased stiffness of arteries triggers a phenotypic switch, hypermigration, and hyperproliferation of vascular smooth muscle cells (VSMCs), leading to neointimal hyperplasia and accelerated neointima formation. However, the mechanism underlying this trigger remains unknown. Our analyses of whole-transcriptome microarray data from mouse VSMCs cultured on stiff hydrogels simulating arterial pathology identified 623 genes that were significantly and differentially expressed (360 upregulated and 263 downregulated) relative to expression in VSMCs cultured on soft hydrogels. Functional enrichment and gene network analyses revealed that these stiffness-sensitive genes are linked to cell cycle progression and proliferation. Importantly, we found that survivin, an inhibitor of apoptosis protein, mediates stiffness-dependent cell cycle progression and proliferation as determined by gene network and pathway analyses, RT-qPCR, immunoblotting, and cell proliferation assays. Furthermore, we found that inhibition of cell cycle progression did not reduce survivin expression, suggesting that survivin functions as an upstream regulator of cell cycle progression and proliferation in response to ECM stiffness. Mechanistically, we found that the stiffness signal is mechanotransduced via the FAK-E2F1 signaling axis to regulate survivin expression, establishing a regulatory pathway for how the stiffness of the cellular microenvironment affects VSMC behaviors. Overall, our findings indicate that survivin is necessary for VSMC cycling and proliferation and plays a role in regulating stiffness-responsive phenotypes.

Evaluating a 3D deep learning pipeline for cerebral vessel and intracranial aneurysm segmentation from computed tomography angiography-digital subtraction angiography image pairs.

OBJECTIVE: Computed tomography angiography (CTA) is the most widely used imaging modality for intracranial aneurysm (IA) management, yet it remains inferior to digital subtraction angiography (DSA) for IA detection, particularly of small IAs in the cavernous carotid region. The authors evaluated a deep learning pipeline for segmentation of vessels and IAs from CTA using coregistered, segmented DSA images as ground truth. METHODS: Using 50 paired CTA-DSA images, the authors trained (n = 27), validated (n = 3), and tested (n = 20) a deep learning model (3D DeepMedic) for cerebrovasculature segmentation from CTA. A landmark-based coregistration algorithm was used for registration and upsampling of CTA images to paired DSA images. Segmented vessels from the DSA were used as the ground truth. Accuracy of the model for vessel segmentation was evaluated using conventional metrics (dice similarity coefficient [DSC]) and vessel segmentation-specific metrics, like connectivity-area-length (CAL). On the test cases (20 IAs), 3 expert raters attempted to detect and segment IAs. For each rater, the authors recorded the rate of IA detection, and for detected IAs, raters segmented and calculated important IA morphology parameters to quantify the differences in IA segmentation by raters to segmentations by DeepMedic. The agreement between raters, DeepMedic, and ground truth was assessed using Krippendorf's alpha. RESULTS: In testing, the DeepMedic model yielded a CAL of 0.971 ± 0.007 and a DSC of 0.868 ± 0.008. The model prediction delineated all IAs and resulted in average error rates of < 10% for all IA morphometrics. Conversely, average IA detection accuracy by the raters was 0.653 (undetected IAs were present to a significantly greater degree on the ICA, likely due to those in the cavernous region, and were significantly smaller). Error rates for IA morphometrics in rater-segmented cases were significantly higher than in DeepMedic-segmented cases, particularly for neck (p = 0.003) and surface area (p = 0.04). For IA morphology, agreement between the raters was acceptable for most metrics, except for the undulation index (α = 0.36) and the nonsphericity index (α = 0.69). Agreement between DeepMedic and ground truth was consistently higher compared with that between expert raters and ground truth. CONCLUSIONS: This CTA segmentation network (DeepMedic trained on DSA-segmented vessels) provides a high-fidelity solution for CTA vessel segmentation, particularly for vessels and IAs in the carotid cavernous region.

The first endovascular rat glioma model for pre-clinical evaluation of intra-arterial therapeutics.

BACKGROUND: Several translational animal models have been described assessing intra-arterial (IA) treatments for malignant gliomas. We describe the first endovascular animal model that allows testing of IA drug delivery as a first-line treatment, which is difficult to do in actual patients. We report a unique protocol for vascular access and IA delivery in the rat model that, unlike prior reports, does not require direct puncture and opening of proximal cerebrovasculature which carries risk of ischemia in the animal brain post-delivery. METHODS: Wistar rats underwent left femoral artery catherization with a Balt Magic 1.2F catheter or Marathon Flow directed 1.5F Microcatheter with an Asahi Chikai 0.008 micro-guidewire which was navigated to the left internal carotid artery under x-ray. 25% mannitol was administered to test blood brain barrier breakdown (BBBB). Additional rats were implanted with C6 glioma cells in the left frontal lobe. C6 Glioma-Implanted Rats (C6GRs) were monitored for overall survival and tumor growth. Tumor volumes from MRI images were calculated utilizing 3D slicer. Additional rats underwent femoral artery catheterization with Bevacizumab, carboplatin, or irinotecan injected into the left internal carotid artery to test feasibility and safety. RESULTS: A successful endovascular access and BBBB protocol was established. BBBB was confirmed with positive Evans blue staining. 10 rats were successfully implanted with C6 gliomas with confirmed growths on MRI. Overall survival was 19.75 ± 2.21 days. 5 rats were utilized for the development of our femoral catheterization protocol and BBBB testing. With regards to IA chemotherapy dosage testing, control rats tolerated targeted 10 mg/kg of bevascizumab, 2.4 mg/kg of carboplatin, and 15 mg/kg of irinotecan IA ICA injections without any complications. CONCLUSIONS: We present the first endovascular IA rat glioma model that allows selective catheterization of the intracranial vasculature and assessment of IA therapies for gliomas without need for access and sacrifice of proximal cerebrovasculature.

Long-Term Follow-Up of Cerebral Aneurysms Completely Occluded at 6 Months After Intervention with the Woven EndoBridge (WEB) Device: a Retrospective Multicenter Observational Study.

The Woven EndoBridge (WEB) device has been widely used to treat intracranial wide neck bifurcation aneurysms. Initial studies have demonstrated that approximately 90% of patients have same or improved long-term aneurysm occlusion after the initial 6-month follow up. The aim of this study is to assess the long-term follow-up in aneurysms that have achieved complete occlusion at 6 months. We also compared the predictive value of different imaging modalities used. This is an analysis of a prospectively maintained database across 13 academic institutions. We included patients with previously untreated cerebral aneurysms embolized using the WEB device who achieved complete occlusion at first follow-up and had available long-term follow-up. A total of 95 patients with a mean age of 61.6 ± 11.9 years were studied. The mean neck diameter and height were 3.9 ± 1.3 mm and 6.0 ± 1.8 mm, respectively. The mean time to first and last follow-up was 5.4 ± 1.8 and 14.1 ± 12.9 months, respectively. Out of all the aneurysms that were completely occluded at 6 months, 84 (90.3%) showed complete occlusion at the final follow-up, and 11(11.5%) patients did not achieve complete occlusion. The positive predictive value (PPV) of complete occlusion at first follow was 88.4%. Importantly, this did not differ between digital subtraction angiography (DSA), magnetic resonance angiography (MRA), or computed tomography angiography (CTA). This study underlines the importance of repeat imaging in patients treated with the WEB device even if complete occlusion is achieved short term. Follow-up can be performed using DSA, MRA or CTA with no difference in positive predictive value.

APOL1 kidney risk variants in glomerular diseases modeled in transgenic mice.

APOL1 high-risk variants partially explain the high kidney disease prevalence among African ancestry individuals. Many mechanisms have been reported in cell culture models, but few have been demonstrated in mouse models. Here we characterize two models: (1) HIV-associated nephropathy (HIVAN) Tg26 mice crossed with bacterial artificial chromosome (BAC)/APOL1 transgenic mice and (2) interferon-γ administered to BAC/APOL1 mice. Both models showed exacerbated glomerular disease in APOL1-G1 compared to APOL1-G0 mice. HIVAN model glomerular bulk RNA-seq identified synergistic podocyte-damaging pathways activated by the APOL1-G1 allele and by HIV transgenes. Single-nuclear RNA-seq revealed podocyte-specific patterns of differentially-expressed genes as a function of APOL1 alleles. Eukaryotic Initiation factor-2 pathway was the most activated pathway in the interferon-γ model and the most deactivated pathway in the HIVAN model. HIVAN mouse model podocyte single-nuclear RNA-seq data showed similarity to human focal segmental glomerulosclerosis (FSGS) glomerular bulk RNA-seq data. Furthermore, single-nuclear RNA-seq data from interferon-γ mouse model podocytes (in vivo) showed similarity to human FSGS single-cell RNA-seq data from urine podocytes (ex vivo) and from human podocyte cell lines (in vitro) using bulk RNA-seq. These data highlight differences in the transcriptional effects of the APOL1-G1 risk variant in a model specific manner. Shared differentially expressed genes in podocytes in both mouse models suggest possible novel glomerular damage markers in APOL1 variant-induced diseases. Transcription factor Zbtb16 was downregulated in podocytes and endothelial cells in both models, possibly contributing to glucocorticoid-resistance. In summary, these findings in two mouse models suggest both shared and distinct therapeutic opportunities for APOL1 glomerulopathies.

Tectonic infarct analysis: A computational tool for automated whole-brain infarct analysis from TTC-stained tissue.

Background: Infarct volume measured from 2,3,5-triphenyltetrazolium chloride (TTC)-stained brain slices is critical to in vivo stroke models. In this study, we developed an interactive, tunable, software that automatically computes whole-brain infarct metrics from serial TTC-stained brain sections. Methods: Three rat ischemic stroke cohorts were used in this study (Total n = 91 rats; Cohort 1 n = 21, Cohort 2 n = 40, Cohort 3 n = 30). For each, brains were serially-sliced, stained with TTC and scanned on both anterior and posterior sides. Ground truth annotation and infarct morphometric analysis (e.g., brain-Vbrain, infarct-Vinfarct, and non-infarct-Vnon-infarct volumes) were completed by domain experts. We used Cohort 1 for brain and infarct segmentation model development (n = 3 training cases with 36 slices [18 anterior and posterior faces], n = 18 testing cases with 218 slices [109 anterior and posterior faces]), as well as infarct morphometrics automation. The infarct quantification pipeline and pre-trained model were packaged as a standalone software and applied to Cohort 2, an internal validation dataset. Finally, software and model trainability were tested as a use-case with Cohort 3, a dataset from a separate institute. Results: Both high segmentation and statistically significant quantification performance (correlation between manual and software) were observed across all datasets. Segmentation performance: Cohort 1 brain accuracy = 0.95/f1-score = 0.90, infarct accuracy = 0.96/f1-score = 0.89; Cohort 2 brain accuracy = 0.97/f1-score = 0.90, infarct accuracy = 0.97/f1-score = 0.80; Cohort 3 brain accuracy = 0.96/f1-score = 0.92, infarct accuracy = 0.95/f1-score = 0.82. Infarct quantification (cohort average): Vbrain (ρ = 0.87, p < 0.001), Vinfarct (0.92, p < 0.001), Vnon-infarct (0.80, p < 0.001), %infarct (0.87, p = 0.001), and infarct:non-infact ratio (ρ = 0.92, p < 0.001). Conclusion: Tectonic Infarct Analysis software offers a robust and adaptable approach for rapid TTC-based stroke assessment.

RNA Expression Signatures of Intracranial Aneurysm Growth Trajectory Identified in Circulating Whole Blood.

After detection, identifying which intracranial aneurysms (IAs) will rupture is imperative. We hypothesized that RNA expression in circulating blood reflects IA growth rate as a surrogate of instability and rupture risk. To this end, we performed RNA sequencing on 66 blood samples from IA patients, for which we also calculated the predicted aneurysm trajectory (PAT), a metric quantifying an IA's future growth rate. We dichotomized dataset using the median PAT score into IAs that were either more stable and more likely to grow quickly. The dataset was then randomly divided into training (n = 46) and testing cohorts (n = 20). In training, differentially expressed protein-coding genes were identified as those with expression (TPM > 0.5) in at least 50% of the samples, a q-value < 0.05 (based on modified F-statistics with Benjamini-Hochberg correction), and an absolute fold-change ≥ 1.5. Ingenuity Pathway Analysis was used to construct networks of gene associations and to perform ontology term enrichment analysis. The MATLAB Classification Learner was then employed to assess modeling capability of the differentially expressed genes, using a 5-fold cross validation in training. Finally, the model was applied to the withheld, independent testing cohort (n = 20) to assess its predictive ability. In all, we examined transcriptomes of 66 IA patients, of which 33 IAs were "growing" (PAT ≥ 4.6) and 33 were more "stable". After dividing dataset into training and testing, we identified 39 genes in training as differentially expressed (11 with decreased expression in "growing" and 28 with increased expression). Model genes largely reflected organismal injury and abnormalities and cell to cell signaling and interaction. Preliminary modeling using a subspace discriminant ensemble model achieved a training AUC of 0.85 and a testing AUC of 0.86. In conclusion, transcriptomic expression in circulating blood indeed can distinguish "growing" and "stable" IA cases. The predictive model constructed from these differentially expressed genes could be used to assess IA stability and rupture potential.

Multimodal CT imaging of ischemic stroke thrombi identifies scale-invariant radiomic features that reflect clot biology.

BACKGROUND: Biological interpretability of ischemic stroke clot imaging remains challenging. OBJECTIVE: To carry out paired CT/micro-CT imaging of ischemic stroke clots retrieved by thrombectomy with the aim of identifying interpretable image features that are correlated among pretreatment image modalities and post-treatment histopathology. METHODS: We performed multimodal CT imaging and histology for 10 stroke clots retrieved by mechanical thrombectomy. Clots were manually segmented from co-registered, pretreatment CT angiography (CTA) and non-contrast CT (NCCT). For the same cases, retrieved clots were iodine-stained, and imaged with a ScanCo micro-CT 100 (4.9 µm resolution). Afterwards, clots were subjected to histological processing (hematoxylin and eosin staining) and whole slide scanned (40X). Clot radiomic features (RFs) (n=93 per modality, 279 total) were extracted using PyRadiomics and histological composition was computed using Orbit Image Analysis. Correlation analysis was used to test associations between micro-CT and CTA (or NCCT) RFs as well as between RFs and histological composition. Statistical significance was considered at R≥0.65 and q<0.05. RESULTS: From paired RF correlation analysis, we identified 23 scale-invariant RFs with significant correlation between micro-CT and CTA (18), and micro-CT and NCCT (5). Correlation of unpaired RFs identified 377 positively and 36 negatively correlated RFs between micro-CT and CTA, and 168 positively and 41 negatively correlated RFs between micro-CT and NCCT. Scale-invariant RFs computed from CTA and NCCT demonstrated significant correlation with red blood cell and fibrin-platelet components, while micro-CT RFs were found to be correlated with white blood cell percent composition. CONCLUSION: Multimodal CT, radiomic, and histological analysis of stroke clots can help to bridge the gap between pretreatment imaging and clot pathobiology.

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.

Profiling of Circulating Gene Expression Reveals Molecular Signatures Associated with Intracranial Aneurysm Rupture Risk.

BACKGROUND: Following detection, rupture risk assessment for intracranial aneurysms (IAs) is critical. Towards molecular prognostics, we hypothesized that circulating blood RNA expression profiles are associated with IA risk. METHODS: We performed RNA sequencing on 68 blood samples from IA patients. Here, patients were categorized as either high or low risk by assessment of aneurysm size (≥ 5 mm = high risk) and Population, Hypertension, Age, Size, Earlier subarachnoid hemorrhage, Site (PHASES) score (≥ 1 = high risk). Modified F-statistics and Benjamini-Hochberg false discovery rate correction was performed on transcripts per million-normalized gene counts. Protein-coding genes expressed in ≥ 50% of samples with a q value < 0.05 and an absolute fold-change ≥ 2 were considered significantly differentially expressed. Bioinformatics in Ingenuity Pathway Analysis was performed to understand the biology of risk-associated expression profiles. Association was assessed between gene expression and risk via Pearson correlation analysis. Linear discriminant analysis models using significant genes were created and validated for classification of high-risk cases. RESULTS: We analyzed transcriptomes of 68 IA patients. In these cases, 31 IAs were large (≥ 5 mm), while 26 IAs had a high PHASES score. Based on size, 36 genes associated with high-risk IAs, and two were correlated with the size measurement. Alternatively, based on PHASES score, 76 genes associated with high-risk cases, and nine of them showed significant correlation to the score. Similar ontological terms were associated with both gene profiles, which reflected inflammatory signaling and vascular remodeling. Prediction models based on size and PHASES stratification were able to correctly predict IA risk status, with > 80% testing accuracy for both. CONCLUSIONS: Here, we identified genes associated with IA risk, as quantified by common clinical metrics. Preliminary classification models demonstrated feasibility of assessing IA risk using whole blood expression.

Gene expression profiles of ischemic stroke clots retrieved by mechanical thrombectomy are associated with disease etiology.

BACKGROUND: Determining stroke etiology is crucial for secondary prevention, but intensive workups fail to classify ~30% of strokes that are cryptogenic. OBJECTIVE: To examine the hypothesis that the transcriptomic profiles of clots retrieved during mechanical thrombectomy are unique to strokes of different subtypes. METHODS: We isolated RNA from the clots of 73 patients undergoing mechanical thrombectomy. Samples of sufficient quality were subjected to 100-cycle, paired-end RNAseq, and transcriptomes with less than 10 million unique reads were excluded from analysis. Significant differentially expressed genes (DEGs) between subtypes (defined by the Trial of Org 10 172 in Acute Stroke Treatment) were identified by expression analysis in edgeR. Gene ontology enrichment analysis was used to study the biologic differences between stroke etiologies. RESULTS: In all, 38 clot transcriptomes were analyzed; 6 from large artery atherosclerosis (LAA), 21 from cardioembolism (CE), 5 from strokes of other determined origin, and 6 from cryptogenic strokes. Among all comparisons, there were 816 unique DEGs, 174 of which were shared by at least two comparisons, and 20 of which were shared by all three. Gene ontology analysis showed that CE clots reflected high levels of inflammation, LAA clots had greater oxidoreduction and T-cell processes, and clots of other determined origin were enriched for aberrant platelet and hemoglobin-related processes. Principal component analysis indicated separation between these subtypes and showed cryptogenic samples clustered among several different groups. CONCLUSIONS: Expression profiles of stroke clots were identified between stroke etiologies and reflected different biologic responses. Cryptogenic thrombi may be related to multiple etiologies.