Vessel volume decrease during early brain injury period as predictor for evolving delayed cerebral ischemia after SAH – a case-control study

Vessel volume decrease during early brain injury period as predictor for evolving delayed cerebral ischemia after SAH – a case-control study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Vessel volume decrease during early brain injury period as predictor for evolving delayed cerebral ischemia after SAH – a case-control study Tobias Pantel, Beate Kranawetter, Jennifer Sauvigny, Franz L. Ricklefs, and 8 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5427555/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Introduction : Delayed cerebral ischemia (DCI) secondary to aneurysmal subarachnoid hemorrhage (SAH) is a feared complication with frequent negative impact on the neurological outcome. Although early diagnosis and treatment is crucial, identifying patients at increased risk is difficult despite clinical risk stratifies such as the VASOGRADE score. Since a reduction in vessel volumes occurs regularly in this cohort and may indicate evolving DCI, the aim of this study was to investigated the reduction in vessel volume in the early brain injury (EBI) phase as an additional predictive marker for the development of DCI. Methods : A bi-centric retrospective case-control study for the period 01/2018 to 12/2020 was conducted. Inclusion criteria were 1) angiographically confirmed aneurysmatic bleeding source and 2) cranial CT (CCT) scan with CT-angiography on admission (SAH onset) and between EBI (day 1–3). Patient-related, disease-specific and outcome parameters (modified Rankin scale (mRs)) were collected. VASOGRADE score was calculated and the volume of M1 segments of the middle cerebral arteries were measured. Subsequently, the occurrence of DCI was unblinded and the data were statistically analyzed. Results : 80 patients met the inclusion criteria, of those 32 developed a DCI. Vessel volume was reduced in the DCI cohort at SAH onset (0.072 ± 0.027 cm 3 vs. 0.108 ± 0.029 cm 3 , p < 0.001) and during EBI period (0.085 ± 0.028 cm 3 vs. 0.121 ± 0.029 cm 3 , p < 0.001). ROC-analysis unveiled a volume of 0.095 cm 3 AUC 0.836; p < 0.001) at SAH onset and 0.105 cm 3 (AUC 0.837; p < 0.001) for the EBI period as predictive for the development of DCI. The predictive statistical markers of the volume threshold were superior to those of the VASOGRADE score. Conclusions : Our data indicate that a reduction in vessel volume during the early brain injury (EBI) phase is a predictive marker for delayed cerebral ischemia (DCI). Furthermore, the statistical parameters associated with the volume threshold suggest that it serves as a more accurate predictor of DCI risk compared to the VASOGRADE score. SAH DCI EBI predictor DCI Figures Figure 1 Introduction Patients presenting with aneurysmal subarachnoid hemorrhage (aSAH) represent a critical and challenging population within neurocritical care 1,2 . Among the complications, delayed cerebral ischemia (DCI) is notably recognized for its substantial impact on the neurological course and overall outcomes in these patients 1-4 . Research data indicate that DCI occurs in approximately 20-40% of individuals with aSAH 4 . Despite considerable research efforts aimed at elucidating the underlying pathophysiological mechanisms and improving diagnostic and therapeutic strategies, no major advances have yet been achieved. Substantial research has defined key concepts of early brain injury (EBI) and DCI after SAH 5 . EBI refers to pathophysiological processes within the first three days post-SAH, but lacks a standard definition 5,6 . Mechanisms like blood-brain barrier disruption, neuroinflammation, and coagulation disturbances contribute to oxidative stress and microthrombosis, which are now seen as pivotal in cerebral perfusion deficits and long-term neurological outcomes 6,7 . The role of cerebral vasospasm, once central to neurological decline, is being reevaluated 8-10 . However, transcranial Doppler (TCD) remains crucial for monitoring cerebral blood flow, especially in sedated patients 11 . Abnormal TCD results often lead to follow-up imaging (CCT, CTA, CCTP), with early detection of perfusion deficits linked to better outcomes 12 . Recent experimental studies have further indicated that cerebral vasospasm and cortical perfusion deficits can occur independently 10 . Immunological processes and microvascular occlusions have been implicated as key factors in this phenomenon 7,13,14 . Multiple studies focusing on these specific aspects suggest that these pathophysiological processes begin in the early phase following hemorrhage, as previously described 5 . Progress has also been made in recent years in the clinical approaches to risk assessment with regard to DCI with the establishment of predictive scoring systems such as VASOGRADE 15 . However, these methods are limited by the potential for subjective interpretation, which impedes the ability to achieve fully objective predictions. Based on these findings, we considered it scientifically justified to focus in our study on the EBI phase as a critical pathophysiological window and to investigate whether vessel volume during this period could predict the occurrence of DCI. In addition, we compared the statistical prediction parameters with those of the VASOGRADE score and investigated whether a combination of these approaches would improve the prediction accuracy. Material and Methods Ethics and study design The study was reported to the responsible Ethics Committees (local ethical review board of Hamburg, Germany (2022-300166-WF, Göttingen (4/3/23)) and was performed in accordance with the ethical standards laid down in the Declaration of Helsinki and its latter amendments. Because the data were anonymized, and the study was retrospective, informed consent was waived. As study design we used a case-control study which constructed and executed using the appropriate guideline 16 . Data acquisition Databases of the Departments for Neurosurgery at the University Medical Center in Hamburg and Göttingen, Germany, were screened for patients treated due to aneurysmal SAH from 01/2018 to 12/2020. Inclusion criteria were 1) angiographically confirmed aneurysm as bleeding source, 2) cranial CT scans with angiography immediately after i) SAH onset (within the first 24 hours) and between ii) EBI (day 1-3) period with 3) corresponding TCD examinations. Patients in whom the exact time of SAH onset remained unclear (e.g., headache event already several days ago) were excluded from the study. The study matched cases and controls by selecting patients with angiographically confirmed aneurysms who underwent consistent cranial CT angiography at SAH onset and during the early brain injury period, with blinded data collection to minimize bias. The selection of patients was blinded, so that no information on clinical course during CTA analyzation were available, except for the radiological findings. The diagnosis of DCI was made using criteria described in the literature and the exact date of diagnosis was collected 4 . Corresponding TCD data were extracted from the internal TCD datasets. Clinical information, common patient (age, sex, e.g.) and disease specific parameters (World Federation of Neurosurgical Societies (WFNS)- and modified Fisher grade e.g.) were collected from patient health records. VASOGRADE score was calculated in accordance with the published guidelines 15,17 . All data were collected in anonymized files. Therapeutic procedure Diagnosis of SAH was made by CCT scan, and a digital subtraction angiography (DSA) was performed to further diagnose the source of bleeding. Subsequently, by interdisciplinary consensus, the aneurysm was treated endovascularly or microsurgically. In case of an incipient hydrocephalus, an external ventricular drain (EVD) or lumbar drainage (LD) was placed. Intensive medical therapy was performed in a specialized neurocritical unit in accordance with current guidelines and recommendations for the treatment of patients with aneurysmal SAH. All patients received nimodipine according to current guidelines 18 . Patients were routinely screened with TCD by trained staff in the intensive care unit (ICU) 18 . Flow velocities (FV) for MCA120cm/s were considered pathological 11 . In case of increasing FVs >160 cm/s, CTA and CCTP were acquired 18 . Vessel volume analysis CTA data sets with a slice thickness of 0.5 mm were used to analyze vessel volumes. CTAs were classified according to the day of performance (initial CCT scan: SAH onset (within the first 24 hours); day 1-3: EBI; day 4-10: early DCI). Analysis of the CTA datasets was performed using Brainlab software (Version “Origin Server 3.3”, Brainlab AG, Munich, Germany). The M1 segment of the middle cerebral artery (MCA) was marked according to the anatomic landmarks between the carotid T and the bifurcation in all three sectional planes (transverse, coronary, sagittal) (Figure 1A). The volume for each segment was recorded separately for each side and expressed in cubic centimeters (cm³). To test whether there is a possible correlation between volume and segment length, the diameter of each segment was assessed at two distinct points along its length. The segment length was then calculated based on these geometric parameters. The analysis was performed independently by three investigators (T.P., J.S.(Hamburg), B.K.(Göttingen)), blinded for the clinical data, to reduce the influence of individual measurement errors on the overall result. Statistics After completion of the CTA analysis, patients were unblinded and assigned to the DCI and non-DCI cohorts. Data are displayed as mean ± standard deviation (sd) for continuous variables or absolute and relative numbers for categorical variables. Differences in continuous variables were analyzed with the Mann-Whitney U-test, and differences in proportions were analyzed with the Fisher’s exact test. A two-sided p-value less than 0.05 was considered as statistically significant. A ROC curve analysis for CCT scan after SAH onset and the EBI period (day 1-3) was performed. The predictive statistical markers (sensitivity, specificity, negative predictive value and positive predictive value) were calculated. All analyses were performed using GraphPad Prism (Version 9.3.1, San Diego, CA, USA). Results In total, we were able to identify 80 patients who met the inclusion criteria for our study during the indicated time period. Thirty-two of them developed a DCI during intensive care treatment. Patient age (57.1 ± 13.1 vs. 51.6 ± 14.8 yrs.) in the DCI and non-DCI cohorts were without statistical differences. Both cohorts were predominantly female (n=24, 75% vs. n=35, 73.9%). A high WFNS score was represented in the DCI cohort compared with the non-DCI cohort (p<0.05) (Table 1). The mean volume of the M1 segment on the initial CCT scan after SAH onset was 0.072 ± 0.027 cm 3 in patients developing DCI in the course of the disease. In comparison, a volume of 0.108 ± 0.029 cm 3 was found in patients not developing DCI (p<0.001). Similarly, there was a difference for the time period of EBI (day 1-3), where vessel volume was 0.085 ± 0.028 cm 3 in the DCI compared to 0.121 ± 0.029 cm 3 in the non-DCI cohort (p<0.001) (Figure 1c). Furthermore, statistically significant differences in M1 volume were also confirmed in several subgroup analyses (Table 2). The correlation between the volume and the length of the M1 segments yielded a non-significant correlation coefficient of 0.35 (p=0.07). It is worth noting, that in the DCI cohort, the DCI diagnosis was made at day 6 post-SAH onset except for two cases (6.3%, n=2). No diagnosis of DCI was made during the EBI phase (day 0-3) (Figure 1d). The calculated VASOGRADE score classified 20 (62.5%) patients in the DCI cohort as category RED, with the remainder in the categories GREEN and YELLOW. In the non-DCI cohort, the majority of patients (n=48, 66,7%) were classified in the categories GREEN and YELLOW. Respectively, for VASOGRADE-RED a sensitivity of 65.3% and a specificity of 64.4% was found in our cohort (Table 3). The ROC curve analyses for the M1-volume immediately after SAH onset resulted in 0.095 cm 3 (AUC 0.83, 95%confidence interval [CI], 0.73 to 0.91; p<0.001) as a cut-off value for prediction of a developing DCI (Figure 1F). For the time point EBI (day1-3) the value 0.105 cm 3 (AUC 0.83, 95%confidence interval [CI], 0.76 to 0.91; p<0.001) was determined (figure 1e). The sensitivity of the volume threshold 0.095cm 3 at SAH onset was 65.3% and the specificity 76.8%. Furthermore, the volume threshold 0.105cm 3 for the EBI period had a sensitivity of 71.1% and a specificity of 82.9% (Table 3). The combination of volume thresholds and VASOGRADE-RED also showed good statistical values for the prediction of DCI, which were superior to those of the VASOGRADE score alone (Table 3). Discussion We investigated the association between the vessel volumes of the MCA-M1 segments as well as the significance of the VASOGRADE score in the EBI period in patients with aneurysmal SAH with regard to DCI prediction. The main findings of our study are: 1) M1 segment volumes of patients developing DCI are significantly reduced immediately after aneurysm rupture with persistence in the phase of EBI compared to patients without this complication. The length of the M1 segment is insignificant in this context. 2) Furthermore, we were able to define a M1 cut-off volume for the prediction of DCI. These changes are detectable immediately after hospital admission. 3) The predictive statistical markers for the vessel volume are comparably good to those of the VASOGRADE score. The combination of both methods then showed a clear optimization of the predictive power. Our results demonstrate a highly significant lower vessel volume in SAH patients with later developing DCI, regardless of the length of the M1 segment. The difference existed equally for the day of SAH onset (day 0) as well as for the EBI period (day 1-3) and thus could be detectable immediately after SAH onset. Through the further analyses we show, first, that the evaluation is reproducible because the data from both participating centers are comparable. On the other hand, we show that the volume reduction in the MCA-M1 segment is present even if the ruptured aneurysm is located elsewhere. Thus, we measure not only a local but a global phenomenon (Table 3). The clinical diagnosis of DCI in our cohort was made in the preponderance from day 6 onward, with only two patients being diagnosed as early as day 4. Consistent with data from other studies, patients with DCI in our cohort also had a significantly worse neurologic outcome compared with patients without DCI, once again highlighting the need for clinical predictors to identify patients at risk 3 . Precise risk assessment based on clinical parameters is generally the most desirable option. The VASOGRADE score was developed for this reason and uses the WFNS and modified Fisher score and therefore two parameters that are collected on initial contact with the patient 15,17 . Published in 2015, de Oliveira Manoel et al. report on a sufficient risk stratification along three categories that classify patients with ascending DCI risk 15,17 . The authors hope that this will provide a good estimate of which patients require prolonged ICU monitoring, for example. A detailed look at the statistical prediction parameters reveals that they do not permit an individual risk prediction. We classified our cohort analogous to the procedure described in the literature and determined the predictive markers 17 . The statistical markers reported in the literature were confirmed for our cohort 17 . Unfortunately, no individual risk prediction can be made by calculating this score. To investigate the clinical significance of the volume data, we performed a ROC curve analysis (start of SAH (day 0) and EBI period (day 1-3)). In the end, we were able to determine a cut-off value for both time points that showed good sensitive and specific parameters for the occurrence of DCI. The statistical prediction parameters were then calculated for both threshold values, which were better than the VASOGRADE score. The negative predictive value, at 87% in each case, was very good and significantly higher than that of the VASOGRADE-RED category. On the other hand, this shows the good quality of the volume parameter in the risk assessment and also allows a more individual risk stratification than was previously the case. We then combined both methods and recalculated the statistical prediction values in order to check whether a further increase in accuracy could be achieved. However, a further optimization of the predictive markers was only possible with regard to sensitivity; the other parameters did not benefit. We therefore believe that the volume threshold in the M1 segment allows very good risk stratification in the SAH cohort and has better statistical parameters than the frequently used and cited VASOGRADE score 17 . Finally, however, the question arises how to interpret the vessel volume changes in the EBI phase. In our opinion, one possible explanation for the pathophysiology described above is that the initial volume reduction as an expression of multiple processes that begin immediately after the onset of hemorrhage 6 . We would like to mention here that we were able to exclude a possible bias that the segment length could have on the segment volume, which underlines the significance of our data. Furthermore, previous studies showed that in the early phase after SAH, impairment of the cortical perfusion is also already detectable in CCT perfusion scans, which is associated with a poor neurological course 12,19,20 . We see this as further confirmation of our results focusing on the EBI phase. The limitation of the statement of our study results from the retrospective character of the case-control study design, which should be taken into account when interpreting and classifying the data. A bias in the results could occur due to the inclusion criteria, because we only included patients in the analysis who had CTAs for all defined time points. Some of the treated SAH patients are excluded from the analysis for this reason. On the other hand, we would like to cite the strength of our study. First, this is a bicentric study, which provides a relevant number of patients from two independent cohorts. Furthermore, we describe data collected from a homogeneous cohort with comparable patient-individual as well as disease-specific characteristics. In particular, we included patients with low- and high-grade SAH to eliminate this confounder as much as possible. Two other important aspects of our study are mentioned in the following. We use CTA as the basis of our study, a diagnostic tool that is part of the initial imaging protocol in these patients. Thus, additional examinations that deviate from the emergency protocol do not occur. Also, CTA is a method that is available in virtually every emergency department and does not require special CCT equipment, as is the case with CCT perfusion imaging. Furthermore, Neulen et al. were able to show that volumetric analysis of the cerebral arteries is a validated method that provides reproducible data 21,22 . Conclusion In summary, the approach presented here for measuring M1 volume is reproducible, objective and easy to interpret. We have successfully established thresholds below which DCI is unlikely to occur. Furthermore, the statistical performance of this method exceeded that of the VASOGRADE score. Our results allow a clear distinction between patients at high risk of DCI and those who are expected to have a milder disease course. Against the background of limited resources in the ICU, this method could help to distinguish patients who require longer monitoring in the ICU from those who benefit from a shorter observation period. A prospective clinical trial that takes these findings into account is warranted. Declarations 1. Manuscript Compliance Confirmation: This manuscript complies with all instructions to authors as outlined in the Neurocritical Care Author Guidelines. 2. Authorship Requirements TP: Conceptualization, Investigation, Software, Formal analysis, Methodology, Writing - Original Draft, Review & Editing BK: Investigation, Formal analysis, Writing - Review & Editing JS: Formal analysis, Writing - Review & Editing FLR: Visualization, Writing - Review & Editing RD: Investigation, Formal analysis, Writing - Review & Editing CT: Formal analysis, Methodology, Validation, Writing - Review & Editing VM: Investigation, Writing - Review & Editing HSM: Validation, Writing - Review & Editing PC: Investigation, Writing - Review & Editing TS: Formal analysis, Writing - Review & Editing DM: Investigation, Writing - Review & Editing LD: Conceptualization, Supervision, Validation, Writing - Review & Editing Approval: The final manuscript has been reviewed and approved by all authors, each of whom agrees to take responsibility for all aspects of the work. 3. Originality of the manuscript Confirmation of originality: This manuscript has not been published elsewhere and is not under consideration by another journal. 4. Compliance with ethical guidelines Ethical Approval: Ethics Committees (local ethical review board of Hamburg, Germany (2022-300166-WF, Göttingen (4/3/23)) 5. Disclosure of conflicts of interest All authors have disclosed any potential conflicts of interest related to the submitted work, ensuring transparency and compliance with ethical research standards. 6. Reporting Checklist A reporting checklist has been added at the end of the manuscript. References Lawton MT, Vates GE. Subarachnoid Hemorrhage. N Engl J Med . Jul 20 2017;377(3):257-266. doi:10.1056/NEJMcp1605827 Roos YB, de Haan RJ, Beenen LF, Groen RJ, Albrecht KW, Vermeulen M. Complications and outcome in patients with aneurysmal subarachnoid haemorrhage: a prospective hospital based cohort study in the Netherlands. J Neurol Neurosurg Psychiatry . Mar 2000;68(3):337-41. doi:10.1136/jnnp.68.3.337 Stienen MN, Smoll NR, Weisshaupt R, et al. Delayed cerebral ischemia predicts neurocognitive impairment following aneurysmal subarachnoid hemorrhage. World Neurosurg . Nov 2014;82(5):e599-605. doi:10.1016/j.wneu.2014.05.011 Vergouwen MD, Vermeulen M, van Gijn J, et al. Definition of delayed cerebral ischemia after aneurysmal subarachnoid hemorrhage as an outcome event in clinical trials and observational studies: proposal of a multidisciplinary research group. Stroke . Oct 2010;41(10):2391-5. doi:10.1161/STROKEAHA.110.589275 Sehba FA, Hou J, Pluta RM, Zhang JH. The importance of early brain injury after subarachnoid hemorrhage. Prog Neurobiol . Apr 2012;97(1):14-37. doi:10.1016/j.pneurobio.2012.02.003 Alsbrook DL, Di Napoli M, Bhatia K, et al. Pathophysiology of Early Brain Injury and Its Association with Delayed Cerebral Ischemia in Aneurysmal Subarachnoid Hemorrhage: A Review of Current Literature. J Clin Med . Jan 28 2023;12(3)doi:10.3390/jcm12031015 Frontera JA, Provencio JJ, Sehba FA, et al. The Role of Platelet Activation and Inflammation in Early Brain Injury Following Subarachnoid Hemorrhage. Neurocrit Care . Feb 2017;26(1):48-57. doi:10.1007/s12028-016-0292-4 Frontera JA, Fernandez A, Schmidt JM, et al. Defining vasospasm after subarachnoid hemorrhage: what is the most clinically relevant definition? Stroke . Jun 2009;40(6):1963-8. doi:10.1161/STROKEAHA.108.544700 Dankbaar JW, Rijsdijk M, van der Schaaf IC, Velthuis BK, Wermer MJ, Rinkel GJ. Relationship between vasospasm, cerebral perfusion, and delayed cerebral ischemia after aneurysmal subarachnoid hemorrhage. Neuroradiology . Dec 2009;51(12):813-9. doi:10.1007/s00234-009-0575-y Neulen A, Meyer S, Kramer A, et al. Large Vessel Vasospasm Is Not Associated with Cerebral Cortical Hypoperfusion in a Murine Model of Subarachnoid Hemorrhage. Transl Stroke Res . Jul 12 2018;10(3):319-26. doi:10.1007/s12975-018-0647-6 Kumar G, Shahripour RB, Harrigan MR. Vasospasm on transcranial Doppler is predictive of delayed cerebral ischemia in aneurysmal subarachnoid hemorrhage: a systematic review and meta-analysis. J Neurosurg . May 2016;124(5):1257-64. doi:10.3171/2015.4.JNS15428 Starnoni D, Maduri R, Hajdu SD, et al. Early Perfusion Computed Tomography Scan for Prediction of Vasospasm and Delayed Cerebral Ischemia After Aneurysmal Subarachnoid Hemorrhage. World Neurosurg . Oct 2019;130:e743-e752. doi:10.1016/j.wneu.2019.06.213 Mohme M, Sauvigny T, Mader MM, et al. Immune Characterization in Aneurysmal Subarachnoid Hemorrhage Reveals Distinct Monocytic Activation and Chemokine Patterns. Transl Stroke Res . Dec 2020;11(6):1348-1361. doi:10.1007/s12975-019-00764-1 Neulen A, Pantel T, Kosterhon M, et al. Neutrophils mediate early cerebral cortical hypoperfusion in a murine model of subarachnoid haemorrhage. Sci Rep . Jun 11 2019;9(1):8460. doi:10.1038/s41598-019-44906-9 Oliveira Souza NV, Rouanet C, Solla DJF, et al. The Role of VASOGRADE as a Simple Grading Scale to Predict Delayed Cerebral Ischemia and Functional Outcome After Aneurysmal Subarachnoid Hemorrhage. Neurocrit Care . Feb 2023;38(1):96-104. doi:10.1007/s12028-022-01577-1 von Elm E, Altman DG, Egger M, et al. [The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting of observational studies]. Internist (Berl) . Jun 2008;49(6):688-93. Das Strengthening the Reporting of Observational Studies in Epidemiology (STROBE-) Statement. doi:10.1007/s00108-008-2138-4 de Oliveira Manoel AL, Jaja BN, Germans MR, et al. The VASOGRADE: A Simple Grading Scale for Prediction of Delayed Cerebral Ischemia After Subarachnoid Hemorrhage. Stroke . Jul 2015;46(7):1826-31. doi:10.1161/STROKEAHA.115.008728 Hoh BL, Ko NU, Amin-Hanjani S, et al. 2023 Guideline for the Management of Patients With Aneurysmal Subarachnoid Hemorrhage: A Guideline From the American Heart Association/American Stroke Association. Stroke . Jul 2023;54(7):e314-e370. doi:10.1161/STR.0000000000000436 Malinova V, Doring K, Psychogios MN, Rohde V, Mielke D. Impact of Implementing an Elaborated CT Perfusion Protocol for Aneurysmal SAH on Functional Outcome: CTP Protocol for SAH. AJNR Am J Neuroradiol . Nov 2021;42(11):1956-1961. doi:10.3174/ajnr.A7279 Etminan N, Beseoglu K, Heiroth HJ, Turowski B, Steiger HJ, Hanggi D. Early perfusion computerized tomography imaging as a radiographic surrogate for delayed cerebral ischemia and functional outcome after subarachnoid hemorrhage. Stroke . May 2013;44(5):1260-6. doi:10.1161/STROKEAHA.111.675975 Neulen A, Kunzelmann S, Kosterhon M, et al. Automated Grading of Cerebral Vasospasm to Standardize Computed Tomography Angiography Examinations After Subarachnoid Hemorrhage. Front Neurol . 2020;11:13. doi:10.3389/fneur.2020.00013 Neulen A, Pantel T, Kosterhon M, et al. A segmentation-based volumetric approach to localize and quantify cerebral vasospasm based on tomographic imaging data. PLoS One . 2017;12(2):e0172010. doi:10.1371/journal.pone.0172010 Tables Table 1: Population characteristics for the DCI and non-DCI cohort. Feature DCI (n= 32 ) non-DCI (n= 48 ) P value Age [years], mean (SD) 56.5 (12.7) 52.3 (12.8) NS Female , n (%) 24 (75) 35 (73.9) NS Aneurysmlocation, n (%) Anterior circulation 18 (47.2) 34 (70.8) NS Posterior circulation 14 (43.8) 14 (29.2) Hydrocephalus, n (%) 27 (84.4) 29 (60.4) p<0.05 WFNS, n (%) 1 7 (21.8) 23 (47.9) p<0.05 2 3 (9.3) 3 (6.3) 3 4 (12.4) 4 (8.3) 4 7 (21.8) 13 (27) 5 11 (34.7) 5 (10.5) Fisher grade, n (%) 1 1 (3.1) 1 (2) NS 2 3 (9.4) 7 (14.6) 3 11 (34.4) 14 (29.2) 4 17 (53.1) 20 (54.2) VASOGRADE score, n (%) Green 3 (9.2) 8 (16,7) NS Yellow 9 (28.3) 24 (50) Red 20 (62.5) 16 (33.3) Glasgow Outcome Scale (GOS), n (%) Favorable Outcome 11 (34.4) 28 (58.3) p=0.003 Unfavorable Outcome 13 (40.6) 18 (37.5) Dead 8 (25) 2 (4.2) Table 2: Listed are the M1 volumes of the various cohorts studied, each distinguished between DCI and non-DCI cohorts. *Division based on the respective aneurysmal localization. Volume day 0 DCI cohort (cm 3 ) non-DCI cohort (cm 3 ) p-value Subgroup 1 0.080 ± 0.025 0.106 ± 0.011 =0.0292 Subgroup 2 0.067 ± 0.028 0.113 ± 0.015 <0.001 Anterior circulation* 0.083 ± 0.026 0.109 ± 0.007 <0.001 Posterior circulation* 0.057 ± 0.06 0.112 ± 0.013 =0.009 Left M1-segment 0.066 ± 0.015 0.107 ± 0.008 <0.001 Right M1-segment 0.079 ± 0.030 0.109 ± 0.008 =0.002 Volume day 1-3 DCI cohort (cm 3 ) non-DCI cohort (cm 3 ) p-value Subgroup 1 0.093 ± 0.027 0.121 ± 0.010 =0.0094 Subgroup 2 0.080 ± 0.040 0.120 ± 0.030 <0.001 Anterior circulation* 0.088 ± 0.029 0.117 ± 0.006 <0.001 Posterior circulation* 0.077 ± 0.017 0.115 ± 0.006 =0.006 Left M1-segment 0.074 ± 0.046 0.120 ± 0.008 <0.001 Right M1-segment 0.095 ± 0.025 0.121 ± 0.007 =0.005 Volume day 4-10 DCI cohort (cm 3 ) non-DCI cohort (cm 3 ) p-value Subgroup 1 0.077 ± 0.015 0.093 ± 0.010 =0.125 Subgroup 2 0.091 ± 0.029 xxx xxx Anterior circulation* 0.085 ± 0.007 0.092 ± 0.009 =0.43 Posterior circulation* 0.084 ± 0.013 0.097 ± 0.020 =0.52 Left M1-segment 0.076 ± 0.014 0.090 ± 0.010 =0.19 Right M1-segment 0.094 ± 0.019 0.096 ± 0.011 =0.86 Table 3: Sensitivity, specificity, positive predictive value, and negative predictive value for delayed cerebral ischemia prediction using VASOGRADE-Red, M1 volume thresholds (<0.0905 cm³ and <0.105 cm³), and combined VASOGRADE-Red with M1 volume thresholds. Sensitivity Specificity Positive predictive value Negative predictive value VASOGRADE-Red 62.5% 66.7% 55.6% 72.7% M1 volume <0.0905 cm 3 65.3% 76.8% 47.2% 87.5% M1 volume <0.105 cm 3 81.3% 74.3% 63.6% 87.8% VASOGRADE-Red & M1 volume <0.0905 cm 3 83.3% 65.3% 62.5% 85% VASOGRADE-Red & M1 volume <0.105 cm 3 81.2% 65.5% 70.2% 77.7% Supplementary Files STROBEStatement.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5427555","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":378316556,"identity":"b9407382-f254-4427-97de-ed40fa19a6b8","order_by":0,"name":"Tobias Pantel","email":"","orcid":"","institution":"University Medical Center Hamburg-Eppendorf: Universitatsklinikum Hamburg-Eppendorf","correspondingAuthor":false,"prefix":"","firstName":"Tobias","middleName":"","lastName":"Pantel","suffix":""},{"id":378316557,"identity":"dd0b3f8d-33a9-4372-a19d-ec7d461864ff","order_by":1,"name":"Beate Kranawetter","email":"","orcid":"","institution":"University Medical Center Göttingen: Universitatsmedizin Gottingen","correspondingAuthor":false,"prefix":"","firstName":"Beate","middleName":"","lastName":"Kranawetter","suffix":""},{"id":378316558,"identity":"e032262b-faa1-423d-97ff-b06dbe039010","order_by":2,"name":"Jennifer Sauvigny","email":"","orcid":"","institution":"University Hospital Hamburg-Eppendorf: Universitatsklinikum Hamburg-Eppendorf","correspondingAuthor":false,"prefix":"","firstName":"Jennifer","middleName":"","lastName":"Sauvigny","suffix":""},{"id":378316559,"identity":"905b27ed-a6d5-40b9-bb86-616c0448a443","order_by":3,"name":"Franz L. Ricklefs","email":"","orcid":"","institution":"University Medical Center Hamburg-Eppendorf: Universitatsklinikum Hamburg-Eppendorf","correspondingAuthor":false,"prefix":"","firstName":"Franz","middleName":"L.","lastName":"Ricklefs","suffix":""},{"id":378316560,"identity":"3e45065b-d4e6-41b8-b68a-488df3b94231","order_by":4,"name":"Richard Drexler","email":"","orcid":"","institution":"University Medical Center Hamburg-Eppendorf: Universitatsklinikum Hamburg-Eppendorf","correspondingAuthor":false,"prefix":"","firstName":"Richard","middleName":"","lastName":"Drexler","suffix":""},{"id":378316561,"identity":"7ba53fb0-5c47-473b-8a3d-4298a5159a67","order_by":5,"name":"Christian Thaler","email":"","orcid":"","institution":"University Medical Center Hamburg-Eppendorf: Universitatsklinikum Hamburg-Eppendorf","correspondingAuthor":false,"prefix":"","firstName":"Christian","middleName":"","lastName":"Thaler","suffix":""},{"id":378316562,"identity":"d3f603a1-ce2f-437c-9f91-997762ce80d0","order_by":6,"name":"Vesna Malinova","email":"","orcid":"","institution":"University Medical Center Göttingen: Universitatsmedizin Gottingen","correspondingAuthor":false,"prefix":"","firstName":"Vesna","middleName":"","lastName":"Malinova","suffix":""},{"id":378316563,"identity":"b543e615-1685-4633-8b85-1d8ad92c64d7","order_by":7,"name":"Hanno S. Meyer","email":"","orcid":"","institution":"University Medical Center Hamburg-Eppendorf: Universitatsklinikum Hamburg-Eppendorf","correspondingAuthor":false,"prefix":"","firstName":"Hanno","middleName":"S.","lastName":"Meyer","suffix":""},{"id":378316564,"identity":"a4379560-e45f-4d8b-a147-40c1400355c5","order_by":8,"name":"Patrick Czorlich","email":"","orcid":"","institution":"University Medical Center Hamburg-Eppendorf: Universitatsklinikum Hamburg-Eppendorf","correspondingAuthor":false,"prefix":"","firstName":"Patrick","middleName":"","lastName":"Czorlich","suffix":""},{"id":378316565,"identity":"0142f8a4-d561-4e5d-a417-6e24b169f3ea","order_by":9,"name":"Thomas Sauvigny","email":"","orcid":"","institution":"University Medical Center Hamburg-Eppendorf: Universitatsklinikum Hamburg-Eppendorf","correspondingAuthor":false,"prefix":"","firstName":"Thomas","middleName":"","lastName":"Sauvigny","suffix":""},{"id":378316566,"identity":"96b106ed-d30a-4638-9be4-01bc269ccbdd","order_by":10,"name":"Dorothee Mielke","email":"","orcid":"","institution":"University Hospital Augsburg: Universitatsklinikum Augsburg","correspondingAuthor":false,"prefix":"","firstName":"Dorothee","middleName":"","lastName":"Mielke","suffix":""},{"id":378316567,"identity":"5671a56e-44f8-4427-bd94-e94354555943","order_by":11,"name":"Lasse Dührsen","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAx0lEQVRIiWNgGAWjYBACPgYGAwbGBhCT+QCIhrDxATaEFrYEkrXwGBCrhXmbxMcd9+z5pXu+Sc6oYJDtJ6yFrUxy5pnixJlzzm6T3HCGwXgmIWvYGHjMpHnbEhIMbuRuk3zYxpC44QAxWv62Jdjb38h5JvnwH0PifqK0MLYlMG6QyGGT3NgAtIWgX5jZii172xISZ9xIM7accUzCeAYhW/jZmzfe+Al0GP+M5Ic3e2psZPsbCFnDjMqVIKR+FIyCUTAKRgExAAC9fjxdmIRXkAAAAABJRU5ErkJggg==","orcid":"","institution":"University Medical Center Hamburg-Eppendorf: Universitatsklinikum Hamburg-Eppendorf","correspondingAuthor":true,"prefix":"","firstName":"Lasse","middleName":"","lastName":"Dührsen","suffix":""}],"badges":[],"createdAt":"2024-11-10 20:27:26","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5427555/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5427555/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":71741786,"identity":"5b02cd76-af15-45b4-867e-4a861540e14a","added_by":"auto","created_at":"2024-12-18 08:17:57","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":104928,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eA: \u003c/strong\u003eFor analysis, the M1 segment was selected according to its anatomical landmarks and recorded in all three spatial planes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFigure 1B:\u003c/strong\u003e M1 volume in the DCI cohort was decreased at all three time points, and M1 segments were more slender compared with M1 segments in the non-DCI cohort.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFigure 1C: \u003c/strong\u003eThe determined vessel volumes were statistically significantly different between the two patient cohorts at all three time points. According to the volume specification of the software, these are expressed in cubic centimeters.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFigure 1D: \u003c/strong\u003ePlot of the respective mean values of flow velocities (FVs) in the M1 segment on the different days, split between DCI and non-DCI cohorts. A clear increase of the FVs can only be observed from day 6 on. In the non-DCI cohort, the FVs remain without increase.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFigure 1E \u0026amp; F: \u003c/strong\u003eROC curve analysis for the time points SAH onset (F) and EBI (day 1-3) (G) with a good aera under the curve (AUG) for both analyses.\u003c/p\u003e","description":"","filename":"CTADCIv2.png","url":"https://assets-eu.researchsquare.com/files/rs-5427555/v1/d7823c9bb5381ceb504d9ab3.png"},{"id":77165171,"identity":"da0fe9a4-b913-48a4-a01a-cd0dbaef442d","added_by":"auto","created_at":"2025-02-25 19:30:45","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":940900,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5427555/v1/46be1c4f-a2a4-44ac-83fd-d884cc6e2a69.pdf"},{"id":71743249,"identity":"a896aba0-f84d-484d-a57c-27b487c49ad5","added_by":"auto","created_at":"2024-12-18 08:25:57","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":21543,"visible":true,"origin":"","legend":"","description":"","filename":"STROBEStatement.docx","url":"https://assets-eu.researchsquare.com/files/rs-5427555/v1/5bd01d3ce4c180cd9f15c0c9.docx"}],"financialInterests":"","formattedTitle":"Vessel volume decrease during early brain injury period as predictor for evolving delayed cerebral ischemia after SAH – a case-control study","fulltext":[{"header":"Introduction","content":"\u003cp\u003ePatients presenting with aneurysmal subarachnoid hemorrhage (aSAH) represent a critical and challenging population within neurocritical care \u003csup\u003e1,2\u003c/sup\u003e. Among the complications, delayed cerebral ischemia (DCI) is notably recognized for its substantial impact on the neurological course and overall outcomes in these patients \u003csup\u003e1-4\u003c/sup\u003e. Research data indicate that DCI occurs in approximately 20-40% of individuals with aSAH \u003csup\u003e4\u003c/sup\u003e. Despite considerable research efforts aimed at elucidating the underlying pathophysiological mechanisms and improving diagnostic and therapeutic strategies, no major advances have yet been achieved.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSubstantial research has defined key concepts of early brain injury (EBI) and DCI after SAH \u003csup\u003e5\u003c/sup\u003e. EBI refers to pathophysiological processes within the first three days post-SAH, but lacks a standard definition \u003csup\u003e5,6\u003c/sup\u003e. Mechanisms like blood-brain barrier disruption, neuroinflammation, and coagulation disturbances contribute to oxidative stress and microthrombosis, which are now seen as pivotal in cerebral perfusion deficits and long-term neurological outcomes \u003csup\u003e6,7\u003c/sup\u003e. The role of cerebral vasospasm, once central to neurological decline, is being reevaluated \u003csup\u003e8-10\u003c/sup\u003e. However, transcranial Doppler (TCD) remains crucial for monitoring cerebral blood flow, especially in sedated patients \u003csup\u003e11\u003c/sup\u003e. Abnormal TCD results often lead to follow-up imaging (CCT, CTA, CCTP), with early detection of perfusion deficits linked to better outcomes \u003csup\u003e12\u003c/sup\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eRecent experimental studies have further indicated that cerebral vasospasm and cortical perfusion deficits can occur independently \u003csup\u003e10\u003c/sup\u003e. Immunological processes and microvascular occlusions have been implicated as key factors in this phenomenon \u003csup\u003e7,13,14\u003c/sup\u003e. Multiple studies focusing on these specific aspects suggest that these pathophysiological processes begin in the early phase following hemorrhage, as previously described \u003csup\u003e5\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eProgress has also been made in recent years in the clinical approaches to risk assessment with regard to DCI with the establishment of predictive scoring systems such as VASOGRADE \u003csup\u003e15\u003c/sup\u003e. However, these methods are limited by the potential for subjective interpretation, which impedes the ability to achieve fully objective predictions.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eBased on these findings, we considered it scientifically justified to focus in our study on the EBI phase as a critical pathophysiological window and to investigate whether vessel volume during this period could predict the occurrence of DCI. In addition, we compared the statistical prediction parameters with those of the VASOGRADE score and investigated whether a combination of these approaches would improve the prediction accuracy.\u003c/p\u003e"},{"header":"Material and Methods","content":"\u003cp\u003e\u003cstrong\u003eEthics and study design\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was reported to the responsible Ethics Committees (local ethical review board of Hamburg, Germany (2022-300166-WF, Göttingen (4/3/23)) and was performed in accordance with the ethical standards laid down in the Declaration of Helsinki and its latter amendments. Because the data were anonymized, and the study was retrospective, informed consent was waived. As study design we used a case-control study which\u0026nbsp;constructed and executed using the appropriate guideline\u0026nbsp;\u003csup\u003e16\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData acquisition\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDatabases of the Departments for Neurosurgery at the University Medical Center in Hamburg and Göttingen, Germany, were screened for patients treated due to aneurysmal SAH from 01/2018 to 12/2020. Inclusion criteria were 1) angiographically confirmed aneurysm as bleeding source, 2) cranial CT scans with angiography immediately after i) SAH onset (within the first 24 hours) and between ii) EBI (day 1-3) period with 3) corresponding TCD examinations. Patients in whom the exact time of SAH onset remained unclear (e.g., headache event already several days ago) were excluded from the study. The study matched cases and controls by selecting patients with angiographically confirmed aneurysms who underwent consistent cranial CT angiography at SAH onset and during the early brain injury period, with blinded data collection to minimize bias. The selection of patients was blinded, so that no information on clinical course during CTA analyzation were available, except for the radiological findings. The diagnosis of DCI was made using criteria described in the literature and the exact date of diagnosis was collected \u003csup\u003e4\u003c/sup\u003e. Corresponding TCD data were extracted from the internal TCD datasets. Clinical information, common patient (age, sex, e.g.) and disease specific parameters (World Federation of Neurosurgical Societies (WFNS)- and modified Fisher grade e.g.) were collected from patient health records. VASOGRADE score was calculated in accordance with the published guidelines \u003csup\u003e15,17\u003c/sup\u003e. All data were collected in anonymized files.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTherapeutic procedure\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDiagnosis of SAH was made by CCT scan, and a digital subtraction angiography (DSA) was performed to further diagnose the source of bleeding. Subsequently, by interdisciplinary consensus, the aneurysm was treated endovascularly or microsurgically. In case of an incipient hydrocephalus, an external ventricular drain (EVD) or lumbar drainage (LD) was placed. Intensive medical therapy was performed in a specialized neurocritical unit in accordance with current guidelines and recommendations for the treatment of patients with aneurysmal SAH. All patients received nimodipine according to current guidelines \u003csup\u003e18\u003c/sup\u003e. Patients were routinely screened with TCD by trained staff in the intensive care unit (ICU) \u003csup\u003e18\u003c/sup\u003e. Flow velocities (FV) for MCA\u0026lt;120cm/s were considered normal,\u0026nbsp;\u0026gt;120cm/s were considered pathological\u0026nbsp;\u003csup\u003e11\u003c/sup\u003e. In case of increasing FVs \u0026gt;160 cm/s, CTA and CCTP were acquired\u0026nbsp;\u003csup\u003e18\u003c/sup\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eVessel volume analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCTA data sets with a slice thickness of 0.5 mm were used to analyze vessel volumes. CTAs were classified according to the day of performance (initial CCT scan: SAH onset (within the first 24 hours); day 1-3: EBI; day 4-10: early DCI). Analysis of the CTA datasets was performed using Brainlab software (Version “Origin Server 3.3”, Brainlab AG, Munich, Germany). The M1 segment of the middle cerebral artery (MCA) was marked according to the anatomic landmarks between the carotid T and the bifurcation in all three sectional planes (transverse, coronary, sagittal) (Figure 1A). The volume for each segment was recorded separately for each side and expressed in cubic centimeters (cm³). To test whether there is a possible correlation between volume and segment length, the diameter of each segment was assessed at two distinct points along its length. The segment length was then calculated based on these geometric parameters. The analysis was performed independently by three investigators (T.P., J.S.(Hamburg), B.K.(Göttingen)), blinded for the clinical data, to reduce the influence of individual measurement errors on the overall result.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAfter completion of the CTA analysis, patients were unblinded and assigned to the DCI and non-DCI cohorts. Data are displayed as mean ± standard deviation (sd) for continuous variables or absolute and relative numbers for categorical variables. Differences in continuous variables were analyzed with the Mann-Whitney U-test, and differences in proportions were analyzed with the Fisher’s exact test. A two-sided p-value less than 0.05 was considered as statistically significant. A ROC curve analysis for CCT scan after SAH onset and the EBI period (day 1-3) was performed. The predictive statistical markers (sensitivity, specificity, negative predictive value and positive predictive value) were calculated. All analyses were performed using GraphPad Prism (Version 9.3.1, San Diego, CA, USA).\u0026nbsp;\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eIn total, we were able to identify 80 patients who met the inclusion criteria for our study during the indicated time period. Thirty-two of them developed a DCI during intensive care treatment. Patient age\u0026nbsp;(57.1 \u0026plusmn; 13.1 vs. 51.6 \u0026plusmn; 14.8 yrs.) in the DCI and non-DCI cohorts were without statistical differences. Both cohorts were predominantly female (n=24, 75% vs. n=35, 73.9%). A high WFNS score was represented in the DCI cohort compared with the non-DCI cohort (p\u0026lt;0.05) (Table 1).\u003c/p\u003e\n\u003cp\u003eThe mean volume of the M1 segment on the initial CCT scan after SAH onset was 0.072 \u0026plusmn; 0.027 cm\u003csup\u003e3\u003c/sup\u003e in patients developing DCI in the course of the disease. In comparison, a volume of 0.108 \u0026plusmn; 0.029 cm\u003csup\u003e3\u003c/sup\u003e was found in patients not developing DCI (p\u0026lt;0.001). Similarly, there was a difference for the time period of EBI (day 1-3), where vessel volume was 0.085 \u0026plusmn; 0.028 cm\u003csup\u003e3\u0026nbsp;\u003c/sup\u003ein the DCI compared to 0.121 \u0026plusmn; 0.029 cm\u003csup\u003e3\u003c/sup\u003e in the non-DCI cohort (p\u0026lt;0.001)\u0026nbsp;(Figure 1c). Furthermore, statistically significant differences in M1 volume were also confirmed in several subgroup analyses (Table 2). The correlation between the volume and the length of the M1 segments yielded a non-significant correlation coefficient of 0.35 (p=0.07). It is worth noting, that in the DCI cohort,\u0026nbsp;the DCI diagnosis was made at day 6 post-SAH onset except for two cases (6.3%, n=2). No diagnosis of DCI was made during the EBI phase (day 0-3)\u0026nbsp;(Figure 1d).\u003c/p\u003e\n\u003cp\u003eThe calculated VASOGRADE score classified 20 (62.5%) patients in the DCI cohort as category RED, with the remainder in the categories GREEN and YELLOW. In the non-DCI cohort, the majority of patients (n=48, 66,7%) were classified in the categories GREEN and YELLOW. Respectively, for VASOGRADE-RED a sensitivity of 65.3% and a specificity of 64.4% was found in our cohort (Table 3).\u003c/p\u003e\n\u003cp\u003eThe ROC curve analyses for the M1-volume immediately after SAH onset resulted in 0.095 cm\u003csup\u003e3\u003c/sup\u003e (AUC 0.83, 95%confidence interval [CI], 0.73 to 0.91; p\u0026lt;0.001) as a cut-off value for prediction of a developing DCI (Figure 1F). For the time point EBI (day1-3) the value 0.105 cm\u003csup\u003e3\u003c/sup\u003e (AUC 0.83, 95%confidence interval [CI], 0.76 to 0.91; p\u0026lt;0.001) was determined (figure 1e). The sensitivity of the volume threshold 0.095cm\u003csup\u003e3\u003c/sup\u003e at SAH onset was 65.3% and the specificity 76.8%. Furthermore, the volume threshold 0.105cm\u003csup\u003e3\u003c/sup\u003e for the EBI period had a sensitivity of 71.1% and a specificity of 82.9% (Table 3). The combination of volume thresholds and VASOGRADE-RED also showed good statistical values for the prediction of DCI, which were superior to those of the VASOGRADE score alone (Table 3).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eWe investigated the association between the vessel volumes of the MCA-M1 segments as well as the significance of the VASOGRADE score in the EBI period in patients with aneurysmal SAH with regard to DCI prediction. The main findings of our study are: 1) M1 segment volumes of patients developing DCI are significantly reduced immediately after aneurysm rupture with persistence in the phase of EBI compared to patients without this complication. The length of the M1 segment is insignificant in this context. 2) Furthermore, we were able to define a M1 cut-off volume for the prediction of DCI. These changes are detectable immediately after hospital admission. 3) The predictive statistical markers for the vessel volume are comparably good to those of the VASOGRADE score. The combination of both methods then showed a clear optimization of the predictive power.\u003c/p\u003e\n\u003cp\u003eOur results demonstrate a highly significant lower vessel volume in SAH patients with later developing DCI, regardless of the length of the M1 segment. The difference existed equally for the day of SAH onset (day 0) as well as for the EBI period (day 1-3) and thus could be detectable immediately after SAH onset.\u0026nbsp;Through the further analyses we show, first, that the evaluation is reproducible because the data from both participating centers are comparable. On the other hand, we show that the volume reduction in the MCA-M1 segment is present even if the ruptured aneurysm is located elsewhere. Thus, we measure not only a local but a global phenomenon (Table 3). The clinical diagnosis of DCI in our cohort was made in the preponderance from day 6 onward, with only two patients being diagnosed as early as day 4. Consistent with data from other studies, patients with DCI in our cohort also had a significantly worse neurologic outcome compared with patients without DCI, once again highlighting the need for clinical predictors to identify patients at risk \u003csup\u003e3\u003c/sup\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePrecise risk assessment based on clinical parameters is generally the most desirable option. The VASOGRADE score was developed for this reason and uses the WFNS and modified Fisher score and therefore two parameters that are collected on initial contact with the patient \u003csup\u003e15,17\u003c/sup\u003e.\u0026nbsp;Published in 2015, de Oliveira Manoel et al. report on a sufficient risk stratification along three categories that classify patients with ascending DCI risk\u0026nbsp;\u003csup\u003e15,17\u003c/sup\u003e. The authors hope that this will provide a good estimate of which patients require prolonged ICU monitoring, for example. A detailed look at the statistical prediction parameters reveals that they do not permit an individual risk prediction.\u0026nbsp;We classified our cohort analogous to the procedure described in the literature and determined the predictive markers\u0026nbsp;\u003csup\u003e17\u003c/sup\u003e. The statistical markers reported in the literature were confirmed for our cohort\u0026nbsp;\u003csup\u003e17\u003c/sup\u003e. Unfortunately, no individual risk prediction can be made by calculating this score. To investigate the clinical significance of the volume data, we performed a ROC curve analysis (start of SAH (day 0) and EBI period (day 1-3)). In the end, we were able to determine a cut-off value for both time points that showed good sensitive and specific parameters for the occurrence of DCI. The statistical prediction parameters were then calculated for both threshold values, which were better than the VASOGRADE score. The negative predictive value, at 87% in each case, was very good and significantly higher than that of the VASOGRADE-RED category. On the other hand, this shows the good quality of the volume parameter in the risk assessment and also allows a more individual risk stratification than was previously the case. We then combined both methods and recalculated the statistical prediction values in order to check whether a further increase in accuracy could be achieved. However, a further optimization of the predictive markers was only possible with regard to sensitivity; the other parameters did not benefit. We therefore believe that the volume threshold in the M1 segment allows very good risk stratification in the SAH cohort and has better statistical parameters than the frequently used and cited VASOGRADE score\u0026nbsp;\u003csup\u003e17\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eFinally, however, the question arises how to interpret the vessel volume changes in the EBI phase. In our opinion, one possible explanation for the pathophysiology described above is that the initial volume reduction as an expression of multiple processes that begin immediately after the onset of hemorrhage \u003csup\u003e6\u003c/sup\u003e. We would like to mention here that we were able to exclude a possible bias that the segment length could have on the segment volume, which underlines the significance of our data. Furthermore, previous studies showed that in the early phase after SAH, impairment of the cortical perfusion is also already detectable in CCT perfusion scans, which is associated with a poor neurological course \u003csup\u003e12,19,20\u003c/sup\u003e. We see this as further confirmation of our results focusing on the EBI phase.\u003c/p\u003e\n\u003cp\u003eThe limitation of the statement of our study results from the retrospective character of the case-control study design, which should be taken into account when interpreting and classifying the data. A bias in the results could occur due to the inclusion criteria, because we only included patients in the analysis who had CTAs for all defined time points. Some of the treated SAH patients are excluded from the analysis for this reason. On the other hand, we would like to cite the strength of our study.\u0026nbsp;First, this is a bicentric study, which provides a relevant number of patients from two independent cohorts.\u0026nbsp;Furthermore, we describe data collected from a homogeneous cohort with comparable patient-individual as well as disease-specific characteristics.\u0026nbsp;In particular, we included patients with low- and high-grade SAH to eliminate this confounder as much as possible. Two other important aspects of our study are mentioned in the following. We use CTA as the basis of our study, a diagnostic tool that is part of the initial imaging protocol in these patients. Thus, additional examinations that deviate from the emergency protocol do not occur. Also, CTA is a method that is available in virtually every emergency department and does not require special CCT equipment, as is the case with CCT perfusion imaging. Furthermore, Neulen et al. were able to show that volumetric analysis of the cerebral arteries is a validated method that provides reproducible data \u003csup\u003e21,22\u003c/sup\u003e.\u0026nbsp;\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn summary, the approach presented here for measuring M1 volume is reproducible, objective and easy to interpret. We have successfully established thresholds below which DCI is unlikely to occur. Furthermore, the statistical performance of this method exceeded that of the VASOGRADE score. Our results allow a clear distinction between patients at high risk of DCI and those who are expected to have a milder disease course. Against the background of limited resources in the ICU, this method could help to distinguish patients who require longer monitoring in the ICU from those who benefit from a shorter observation period. A prospective clinical trial that takes these findings into account is warranted.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e1. Manuscript Compliance\u003c/p\u003e\n\u003cp\u003eConfirmation: This manuscript complies with all instructions to authors as outlined in the Neurocritical Care Author Guidelines.\u003c/p\u003e\n\u003cp\u003e2. Authorship Requirements\u003c/p\u003e\n\u003cp\u003eTP:\u0026nbsp;Conceptualization, Investigation, Software, Formal analysis, Methodology, Writing - Original Draft, Review \u0026amp; Editing\u003c/p\u003e\n\u003cp\u003eBK: Investigation, Formal analysis, Writing - Review \u0026amp; Editing\u003c/p\u003e\n\u003cp\u003eJS: Formal analysis, Writing - Review \u0026amp; Editing\u003c/p\u003e\n\u003cp\u003eFLR: Visualization, Writing - Review \u0026amp; Editing\u003c/p\u003e\n\u003cp\u003eRD: Investigation, Formal analysis, Writing - Review \u0026amp; Editing\u003c/p\u003e\n\u003cp\u003eCT: Formal analysis, Methodology, Validation, Writing - Review \u0026amp; Editing\u003c/p\u003e\n\u003cp\u003eVM: Investigation, Writing - Review \u0026amp; Editing\u003c/p\u003e\n\u003cp\u003eHSM: Validation, Writing - Review \u0026amp; Editing\u003c/p\u003e\n\u003cp\u003ePC: Investigation, Writing - Review \u0026amp; Editing\u003c/p\u003e\n\u003cp\u003eTS: Formal analysis, Writing - Review \u0026amp; Editing\u003c/p\u003e\n\u003cp\u003eDM: Investigation, Writing - Review \u0026amp; Editing\u003c/p\u003e\n\u003cp\u003eLD: Conceptualization, Supervision, Validation, Writing - Review \u0026amp; Editing\u003c/p\u003e\n\u003cp\u003eApproval: The final manuscript has been reviewed and approved by all authors, each of whom agrees to take responsibility for all aspects of the work.\u003c/p\u003e\n\u003cp\u003e3. Originality of the manuscript\u003c/p\u003e\n\u003cp\u003eConfirmation of originality: This manuscript has not been published elsewhere and is not under consideration by another journal.\u003c/p\u003e\n\u003cp\u003e4. Compliance with ethical guidelines\u003c/p\u003e\n\u003cp\u003eEthical Approval:\u0026nbsp;Ethics Committees (local ethical review board of Hamburg, Germany (2022-300166-WF, Göttingen (4/3/23))\u003c/p\u003e\n\u003cp\u003e5. Disclosure of conflicts of interest\u003c/p\u003e\n\u003cp\u003eAll authors have disclosed any potential conflicts of interest related to the submitted work, ensuring transparency and compliance with ethical research standards.\u003c/p\u003e\n\u003cp\u003e6. Reporting Checklist\u003c/p\u003e\n\u003cp\u003eA reporting checklist has been added at the end of the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eLawton MT, Vates GE. Subarachnoid Hemorrhage. \u003cem\u003eN Engl J Med\u003c/em\u003e. Jul 20 2017;377(3):257-266. doi:10.1056/NEJMcp1605827\u003c/li\u003e\n\u003cli\u003eRoos YB, de Haan RJ, Beenen LF, Groen RJ, Albrecht KW, Vermeulen M. Complications and outcome in patients with aneurysmal subarachnoid haemorrhage: a prospective hospital based cohort study in the Netherlands. \u003cem\u003eJ Neurol Neurosurg Psychiatry\u003c/em\u003e. Mar 2000;68(3):337-41. doi:10.1136/jnnp.68.3.337\u003c/li\u003e\n\u003cli\u003eStienen MN, Smoll NR, Weisshaupt R, et al. Delayed cerebral ischemia predicts neurocognitive impairment following aneurysmal subarachnoid hemorrhage. \u003cem\u003eWorld Neurosurg\u003c/em\u003e. Nov 2014;82(5):e599-605. doi:10.1016/j.wneu.2014.05.011\u003c/li\u003e\n\u003cli\u003eVergouwen MD, Vermeulen M, van Gijn J, et al. Definition of delayed cerebral ischemia after aneurysmal subarachnoid hemorrhage as an outcome event in clinical trials and observational studies: proposal of a multidisciplinary research group. \u003cem\u003eStroke\u003c/em\u003e. Oct 2010;41(10):2391-5. doi:10.1161/STROKEAHA.110.589275\u003c/li\u003e\n\u003cli\u003eSehba FA, Hou J, Pluta RM, Zhang JH. The importance of early brain injury after subarachnoid hemorrhage. \u003cem\u003eProg Neurobiol\u003c/em\u003e. Apr 2012;97(1):14-37. doi:10.1016/j.pneurobio.2012.02.003\u003c/li\u003e\n\u003cli\u003eAlsbrook DL, Di Napoli M, Bhatia K, et al. Pathophysiology of Early Brain Injury and Its Association with Delayed Cerebral Ischemia in Aneurysmal Subarachnoid Hemorrhage: A Review of Current Literature. \u003cem\u003eJ Clin Med\u003c/em\u003e. Jan 28 2023;12(3)doi:10.3390/jcm12031015\u003c/li\u003e\n\u003cli\u003eFrontera JA, Provencio JJ, Sehba FA, et al. The Role of Platelet Activation and Inflammation in Early Brain Injury Following Subarachnoid Hemorrhage. \u003cem\u003eNeurocrit Care\u003c/em\u003e. Feb 2017;26(1):48-57. doi:10.1007/s12028-016-0292-4\u003c/li\u003e\n\u003cli\u003eFrontera JA, Fernandez A, Schmidt JM, et al. Defining vasospasm after subarachnoid hemorrhage: what is the most clinically relevant definition? \u003cem\u003eStroke\u003c/em\u003e. Jun 2009;40(6):1963-8. doi:10.1161/STROKEAHA.108.544700\u003c/li\u003e\n\u003cli\u003eDankbaar JW, Rijsdijk M, van der Schaaf IC, Velthuis BK, Wermer MJ, Rinkel GJ. Relationship between vasospasm, cerebral perfusion, and delayed cerebral ischemia after aneurysmal subarachnoid hemorrhage. \u003cem\u003eNeuroradiology\u003c/em\u003e. Dec 2009;51(12):813-9. doi:10.1007/s00234-009-0575-y\u003c/li\u003e\n\u003cli\u003eNeulen A, Meyer S, Kramer A, et al. Large Vessel Vasospasm Is Not Associated with Cerebral Cortical Hypoperfusion in a Murine Model of Subarachnoid Hemorrhage. \u003cem\u003eTransl Stroke Res\u003c/em\u003e. Jul 12 2018;10(3):319-26. doi:10.1007/s12975-018-0647-6\u003c/li\u003e\n\u003cli\u003eKumar G, Shahripour RB, Harrigan MR. Vasospasm on transcranial Doppler is predictive of delayed cerebral ischemia in aneurysmal subarachnoid hemorrhage: a systematic review and meta-analysis. \u003cem\u003eJ Neurosurg\u003c/em\u003e. May 2016;124(5):1257-64. doi:10.3171/2015.4.JNS15428\u003c/li\u003e\n\u003cli\u003eStarnoni D, Maduri R, Hajdu SD, et al. Early Perfusion Computed Tomography Scan for Prediction of Vasospasm and Delayed Cerebral Ischemia After Aneurysmal Subarachnoid Hemorrhage. \u003cem\u003eWorld Neurosurg\u003c/em\u003e. Oct 2019;130:e743-e752. doi:10.1016/j.wneu.2019.06.213\u003c/li\u003e\n\u003cli\u003eMohme M, Sauvigny T, Mader MM, et al. Immune Characterization in Aneurysmal Subarachnoid Hemorrhage Reveals Distinct Monocytic Activation and Chemokine Patterns. \u003cem\u003eTransl Stroke Res\u003c/em\u003e. Dec 2020;11(6):1348-1361. doi:10.1007/s12975-019-00764-1\u003c/li\u003e\n\u003cli\u003eNeulen A, Pantel T, Kosterhon M, et al. Neutrophils mediate early cerebral cortical hypoperfusion in a murine model of subarachnoid haemorrhage. \u003cem\u003eSci Rep\u003c/em\u003e. Jun 11 2019;9(1):8460. doi:10.1038/s41598-019-44906-9\u003c/li\u003e\n\u003cli\u003eOliveira Souza NV, Rouanet C, Solla DJF, et al. The Role of VASOGRADE as a Simple Grading Scale to Predict Delayed Cerebral Ischemia and Functional Outcome After Aneurysmal Subarachnoid Hemorrhage. \u003cem\u003eNeurocrit Care\u003c/em\u003e. Feb 2023;38(1):96-104. doi:10.1007/s12028-022-01577-1\u003c/li\u003e\n\u003cli\u003evon Elm E, Altman DG, Egger M, et al. [The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting of observational studies]. \u003cem\u003eInternist (Berl)\u003c/em\u003e. Jun 2008;49(6):688-93. Das Strengthening the Reporting of Observational Studies in Epidemiology (STROBE-) Statement. doi:10.1007/s00108-008-2138-4\u003c/li\u003e\n\u003cli\u003ede Oliveira Manoel AL, Jaja BN, Germans MR, et al. The VASOGRADE: A Simple Grading Scale for Prediction of Delayed Cerebral Ischemia After Subarachnoid Hemorrhage. \u003cem\u003eStroke\u003c/em\u003e. Jul 2015;46(7):1826-31. doi:10.1161/STROKEAHA.115.008728\u003c/li\u003e\n\u003cli\u003eHoh BL, Ko NU, Amin-Hanjani S, et al. 2023 Guideline for the Management of Patients With Aneurysmal Subarachnoid Hemorrhage: A Guideline From the American Heart Association/American Stroke Association. \u003cem\u003eStroke\u003c/em\u003e. Jul 2023;54(7):e314-e370. doi:10.1161/STR.0000000000000436\u003c/li\u003e\n\u003cli\u003eMalinova V, Doring K, Psychogios MN, Rohde V, Mielke D. Impact of Implementing an Elaborated CT Perfusion Protocol for Aneurysmal SAH on Functional Outcome: CTP Protocol for SAH. \u003cem\u003eAJNR Am J Neuroradiol\u003c/em\u003e. Nov 2021;42(11):1956-1961. doi:10.3174/ajnr.A7279\u003c/li\u003e\n\u003cli\u003eEtminan N, Beseoglu K, Heiroth HJ, Turowski B, Steiger HJ, Hanggi D. Early perfusion computerized tomography imaging as a radiographic surrogate for delayed cerebral ischemia and functional outcome after subarachnoid hemorrhage. \u003cem\u003eStroke\u003c/em\u003e. May 2013;44(5):1260-6. doi:10.1161/STROKEAHA.111.675975\u003c/li\u003e\n\u003cli\u003eNeulen A, Kunzelmann S, Kosterhon M, et al. Automated Grading of Cerebral Vasospasm to Standardize Computed Tomography Angiography Examinations After Subarachnoid Hemorrhage. \u003cem\u003eFront Neurol\u003c/em\u003e. 2020;11:13. doi:10.3389/fneur.2020.00013\u003c/li\u003e\n\u003cli\u003eNeulen A, Pantel T, Kosterhon M, et al. A segmentation-based volumetric approach to localize and quantify cerebral vasospasm based on tomographic imaging data. \u003cem\u003ePLoS One\u003c/em\u003e. 2017;12(2):e0172010. doi:10.1371/journal.pone.0172010\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1:\u003c/strong\u003e Population characteristics for the DCI and non-DCI cohort.\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"600\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFeature\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDCI\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n=\u003c/strong\u003e\u003cstrong\u003e32\u003c/strong\u003e\u003cstrong\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e\u003cstrong\u003enon-DCI\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n=\u003c/strong\u003e\u003cstrong\u003e48\u003c/strong\u003e\u003cstrong\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge [years], mean (SD)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e56.5 (12.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e52.3 (12.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFemale\u003c/strong\u003e\u003cstrong\u003e, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e24 (75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e35 (73.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAneurysmlocation, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003eAnterior circulation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e18 (47.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e34 (70.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003ePosterior circulation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e14 (43.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e14 (29.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHydrocephalus, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e27 (84.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e29 (60.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003ep\u0026lt;0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWFNS, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e7 (21.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e23 (47.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"5\" valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003ep\u0026lt;0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e3 (9.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e3 (6.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e4 (12.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e4 (8.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e7 (21.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e13 (27)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e11 (34.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e5 (10.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFisher grade, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e1 (3.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e1 (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e3 (9.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e7 (14.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e11 (34.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e14 (29.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e17 (53.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e20 (54.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVASOGRADE score, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003eGreen\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e3 (9.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e8 (16,7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003eYellow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e9 (28.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e24 (50)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003eRed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e20 (62.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e16 (33.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGlasgow Outcome Scale (GOS), n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003eFavorable Outcome\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e11 (34.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e28 (58.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003ep=0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003eUnfavorable Outcome\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e13 (40.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e18 (37.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003eDead\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e8 (25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e2 (4.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2:\u003c/strong\u003e Listed are the M1 volumes of the various cohorts studied, each distinguished between DCI and non-DCI cohorts. *Division based on the respective aneurysmal localization.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eVolume day 0\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDCI cohort (cm\u003csup\u003e3\u003c/sup\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003enon-DCI cohort (cm\u003csup\u003e3\u003c/sup\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cem\u003eSubgroup 1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e0.080 \u0026plusmn; 0.025\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e0.106 \u0026plusmn; 0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e=0.0292\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cem\u003eSubgroup 2\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e0.067 \u0026plusmn; 0.028\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e0.113 \u0026plusmn; 0.015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cem\u003eAnterior circulation*\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e0.083 \u0026plusmn; 0.026\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e0.109 \u0026plusmn; 0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cem\u003ePosterior circulation*\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e0.057 \u0026plusmn; 0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e0.112 \u0026plusmn; 0.013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e=0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cem\u003eLeft M1-segment\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e0.066 \u0026plusmn; 0.015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e0.107 \u0026plusmn; 0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cem\u003eRight M1-segment\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e0.079 \u0026plusmn; 0.030\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e0.109 \u0026plusmn; 0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e=0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eVolume day 1-3\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDCI cohort (cm\u003csup\u003e3\u003c/sup\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003enon-DCI cohort (cm\u003csup\u003e3\u003c/sup\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cem\u003eSubgroup 1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e0.093 \u0026plusmn; 0.027\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e0.121 \u0026plusmn; 0.010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e=0.0094\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cem\u003eSubgroup 2\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e0.080 \u0026plusmn; 0.040\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e0.120 \u0026plusmn; 0.030\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cem\u003eAnterior circulation*\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e0.088 \u0026plusmn; 0.029\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e0.117 \u0026plusmn; 0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cem\u003ePosterior circulation*\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e0.077 \u0026plusmn; 0.017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e0.115 \u0026plusmn; 0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e=0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cem\u003eLeft M1-segment\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e0.074 \u0026plusmn; 0.046\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e0.120 \u0026plusmn; 0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cem\u003eRight M1-segment\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e0.095 \u0026plusmn; 0.025\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e0.121 \u0026plusmn; 0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e=0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eVolume day 4-10\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDCI cohort (cm\u003csup\u003e3\u003c/sup\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003enon-DCI cohort (cm\u003csup\u003e3\u003c/sup\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cem\u003eSubgroup 1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e0.077 \u0026plusmn; 0.015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e0.093 \u0026plusmn; 0.010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e=0.125\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cem\u003eSubgroup 2\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e0.091 \u0026plusmn; 0.029\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003exxx\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003exxx\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cem\u003eAnterior circulation*\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e0.085 \u0026plusmn; 0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e0.092 \u0026plusmn; 0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e=0.43\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cem\u003ePosterior circulation*\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e0.084 \u0026plusmn; 0.013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e0.097 \u0026plusmn; 0.020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e=0.52\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cem\u003eLeft M1-segment\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e0.076 \u0026plusmn; 0.014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e0.090 \u0026plusmn; 0.010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e=0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cem\u003eRight M1-segment\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e0.094 \u0026plusmn; 0.019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e0.096 \u0026plusmn; 0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e=0.86\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3:\u0026nbsp;\u003c/strong\u003eSensitivity, specificity, positive predictive value, and negative predictive value for delayed cerebral ischemia prediction using VASOGRADE-Red, M1 volume thresholds (\u0026lt;0.0905 cm\u0026sup3; and \u0026lt;0.105 cm\u0026sup3;), and combined VASOGRADE-Red with M1 volume thresholds.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"625\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSensitivity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSpecificity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePositive predictive value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNegative predictive value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVASOGRADE-Red\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e62.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e66.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e55.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e72.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eM1 volume \u0026lt;0.0905 cm\u003csup\u003e3\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e65.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e76.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e47.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e87.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eM1 volume \u0026lt;0.105 cm\u003csup\u003e3\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e81.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e74.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e63.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e87.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVASOGRADE-Red \u0026amp; M1 volume \u0026lt;0.0905 cm\u003csup\u003e3\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e83.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e65.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e62.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e85%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVASOGRADE-Red \u0026amp; M1 volume \u0026lt;0.105 cm\u003csup\u003e3\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e81.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e65.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e70.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e77.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"SAH, DCI, EBI, predictor DCI","lastPublishedDoi":"10.21203/rs.3.rs-5427555/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5427555/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eIntroduction\u003c/strong\u003e: Delayed cerebral ischemia (DCI) secondary to aneurysmal subarachnoid hemorrhage (SAH) is a feared complication with frequent negative impact on the neurological outcome. Although early diagnosis and treatment is crucial, identifying patients at increased risk is difficult despite clinical risk stratifies such as the VASOGRADE score. Since a reduction in vessel volumes occurs regularly in this cohort and may indicate evolving DCI, the aim of this study was to investigated the reduction in vessel volume in the early brain injury (EBI) phase as an additional predictive marker for the development of DCI.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e: A bi-centric retrospective case-control study for the period 01/2018 to 12/2020 was conducted. Inclusion criteria were 1) angiographically confirmed aneurysmatic bleeding source and 2) cranial CT (CCT) scan with CT-angiography on admission (SAH onset) and between EBI (day 1–3). Patient-related, disease-specific and outcome parameters (modified Rankin scale (mRs)) were collected. VASOGRADE score was calculated and the volume of M1 segments of the middle cerebral arteries were measured. Subsequently, the occurrence of DCI was unblinded and the data were statistically analyzed.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e: 80 patients met the inclusion criteria, of those 32 developed a DCI. Vessel volume was reduced in the DCI cohort at SAH onset (0.072 ± 0.027 cm\u003csup\u003e3\u003c/sup\u003e vs. 0.108 ± 0.029 cm\u003csup\u003e3\u003c/sup\u003e, p \u0026lt; 0.001) and during EBI period (0.085 ± 0.028 cm\u003csup\u003e3\u003c/sup\u003e vs. 0.121 ± 0.029 cm\u003csup\u003e3\u003c/sup\u003e, p \u0026lt; 0.001). ROC-analysis unveiled a volume of 0.095 cm\u003csup\u003e3\u003c/sup\u003e AUC 0.836; p \u0026lt; 0.001) at SAH onset and 0.105 cm\u003csup\u003e3\u003c/sup\u003e (AUC 0.837; p \u0026lt; 0.001) for the EBI period as predictive for the development of DCI. The predictive statistical markers of the volume threshold were superior to those of the VASOGRADE score.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e: Our data indicate that a reduction in vessel volume during the early brain injury (EBI) phase is a predictive marker for delayed cerebral ischemia (DCI). Furthermore, the statistical parameters associated with the volume threshold suggest that it serves as a more accurate predictor of DCI risk compared to the VASOGRADE score.\u003c/p\u003e","manuscriptTitle":"Vessel volume decrease during early brain injury period as predictor for evolving delayed cerebral ischemia after SAH – a case-control study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-12-18 08:17:52","doi":"10.21203/rs.3.rs-5427555/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"30ca35bf-0613-4071-992a-a86734b5e5eb","owner":[],"postedDate":"December 18th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-02-25T19:22:38+00:00","versionOfRecord":[],"versionCreatedAt":"2024-12-18 08:17:52","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5427555","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5427555","identity":"rs-5427555","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}