Contribution of an Automatic Algorithm for Quantifying the Volume of Aneurysmal Subarachnoid Hemorrhage to the Evaluation of the Risk of Occurrence of Delayed Cerebral Ischemia: A Cohort Study.

Acute hydrocephalus CT scan Delayed cerebral ischemia Outcome Radiological scores Subarachnoid hemorrhage

Journal

Neurocritical care
ISSN: 1556-0961
Titre abrégé: Neurocrit Care
Pays: United States
ID NLM: 101156086

Informations de publication

Date de publication:
08 Oct 2024
Historique:
received: 03 06 2024
accepted: 11 09 2024
medline: 9 10 2024
pubmed: 9 10 2024
entrez: 8 10 2024
Statut: aheadofprint

Résumé

This study focuses on aneurysmal subarachnoid hemorrhage (aSAH) with a high risk of delayed cerebral ischemia (DCI) and acute hydrocephalus (AH). The aim was to compare the performance of an automatic algorithm for quantifying the volume of intracranial blood with the reference radiological scales to predict DCI, AH, and neurological outcome. This was a single-center retrospective observational study of a cohort of patients with aSAH. We developed an automated blood detection algorithm based on the specific density of the blood clot. The blood clot was segmented on the first brain scan (total, supratentorial, cisternal, intraventricular). The predictive value of our model was compared, using the area under the receiver operating characteristic curve (ROC We analyzed the scans of 145 patients with aSAH. In our cohort, 51 patients (43%) had DCI and 70 patients (54%) had AH. At 3 months, 22% of patients had died and 19% had poor outcome (Glasgow Outcome Scale extended 2-4). Cisternal blood volume was significantly correlated with cisternal Hijdra scale (R With no manual intervention, our algorithm performed as well as the best radiological scores in predicting the occurrence of DCI, AH, and neurological outcome.

Sections du résumé

BACKGROUND BACKGROUND
This study focuses on aneurysmal subarachnoid hemorrhage (aSAH) with a high risk of delayed cerebral ischemia (DCI) and acute hydrocephalus (AH). The aim was to compare the performance of an automatic algorithm for quantifying the volume of intracranial blood with the reference radiological scales to predict DCI, AH, and neurological outcome.
METHODS METHODS
This was a single-center retrospective observational study of a cohort of patients with aSAH. We developed an automated blood detection algorithm based on the specific density of the blood clot. The blood clot was segmented on the first brain scan (total, supratentorial, cisternal, intraventricular). The predictive value of our model was compared, using the area under the receiver operating characteristic curve (ROC
RESULTS RESULTS
We analyzed the scans of 145 patients with aSAH. In our cohort, 51 patients (43%) had DCI and 70 patients (54%) had AH. At 3 months, 22% of patients had died and 19% had poor outcome (Glasgow Outcome Scale extended 2-4). Cisternal blood volume was significantly correlated with cisternal Hijdra scale (R
CONCLUSIONS CONCLUSIONS
With no manual intervention, our algorithm performed as well as the best radiological scores in predicting the occurrence of DCI, AH, and neurological outcome.

Identifiants

pubmed: 39379750
doi: 10.1007/s12028-024-02135-7
pii: 10.1007/s12028-024-02135-7
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

© 2024. Springer Science+Business Media, LLC, part of Springer Nature and Neurocritical Care Society.

Références

de Rooij NK, Linn FHH, van der Plas JA, Algra A, Rinkel GJE. Incidence of subarachnoid haemorrhage: a systematic review with emphasis on region, age, gender and time trends. J Neurol Neurosurg Psychiatry. 2007;78(12):1365–72.
pubmed: 17470467 pmcid: 2095631 doi: 10.1136/jnnp.2007.117655
Etminan N, Chang HS, Hackenberg K, de Rooij NK, Vergouwen MDI, Rinkel GJE, et al. Worldwide incidence of aneurysmal subarachnoid hemorrhage according to region, time period, blood pressure, and smoking prevalence in the population: a systematic review and meta-analysis. JAMA Neurol. 2019;76(5):588.
pubmed: 30659573 pmcid: 6515606 doi: 10.1001/jamaneurol.2019.0006
De Winkel J, Cras TY, Dammers R, Van Doormaal PJ, Van Der Jagt M, Dippel DWJ, et al. Early predictors of functional outcome in poor-grade aneurysmal subarachnoid hemorrhage: a systematic review and meta-analysis. BMC Neurol. 2022;22(1):239.
pubmed: 35773634 pmcid: 9245240 doi: 10.1186/s12883-022-02734-x
Dreier JP, Woitzik J, Fabricius M, Bhatia R, Major S, Drenckhahn C, et al. Delayed ischaemic neurological deficits after subarachnoid haemorrhage are associated with clusters of spreading depolarizations. Brain. 2006;129(12):3224–37.
pubmed: 17067993 doi: 10.1093/brain/awl297
Pluta RM, Hansen-Schwartz J, Dreier J, Vajkoczy P, Macdonald RL, Nishizawa S, et al. Cerebral vasospasm following subarachnoid hemorrhage: time for a new world of thought. Neurol Res. 2009;31(2):151–8.
pubmed: 19298755 pmcid: 2706525 doi: 10.1179/174313209X393564
Crobeddu E, Mittal MK, Dupont S, Wijdicks EFM, Lanzino G, Rabinstein AA. Predicting the lack of development of delayed cerebral ischemia after aneurysmal subarachnoid hemorrhage. Stroke. 2012;43(3):697–701.
pubmed: 22198987 doi: 10.1161/STROKEAHA.111.638403
Kramer AH, Hehir M, Nathan B, Gress D, Dumont AS, Kassell NF, et al. A comparison of 3 radiographic scales for the prediction of delayed ischemia and prognosis following subarachnoid hemorrhage. J Neurosurg. 2008;109(2):199–207.
pubmed: 18671630 doi: 10.3171/JNS/2008/109/8/0199
Jiménez-Roldán L, Alén JF, Gómez PA, Lobato RD, Ramos A, Munarriz PM, et al. Volumetric analysis of subarachnoid hemorrhage: assessment of the reliability of two computerized methods and their comparison with other radiographic scales. J Neurosurg. 2013;118(1):84–93.
pubmed: 22998059 doi: 10.3171/2012.8.JNS12100
Norden AGW, Dijk GW, Huizen MD, Algra A, Rinkel GJE. Interobserver agreement and predictive value for outcome of two rating scales for the amount of extravasated blood after aneurysmal subarachnoid haemorrhage. J Neurol. 2006;253(9):1217–20.
pubmed: 16998645 doi: 10.1007/s00415-006-0205-0
Hijdra A, van Gijn J, Nagelkerke NJ, Vermeulen M, van Crevel H. Prediction of delayed cerebral ischemia, rebleeding, and outcome after aneurysmal subarachnoid hemorrhage. Stroke. 1988;19(10):1250–6.
pubmed: 3176085 doi: 10.1161/01.STR.19.10.1250
Hijdra A, Brouwers PJ, Vermeulen M, van Gijn J. Grading the amount of blood on computed tomograms after subarachnoid hemorrhage. Stroke. 1990;21(8):1156–61.
pubmed: 2389295 doi: 10.1161/01.STR.21.8.1156
Dupont SA, Wijdicks EFM, Manno EM, Lanzino G, Rabinstein AA. Prediction of angiographic vasospasm after aneurysmal subarachnoid hemorrhage: value of the Hijdra sum scoring system. Neurocrit Care. 2009;11(2):172–6.
pubmed: 19642027 doi: 10.1007/s12028-009-9247-3
Bretz JS, Von Dincklage F, Woitzik J, Winkler MKL, Major S, Dreier JP, et al. The Hijdra scale has significant prognostic value for the functional outcome of Fisher grade 3 patients with subarachnoid hemorrhage. Clin Neuroradiol. 2017;27(3):361–9.
pubmed: 27113903 doi: 10.1007/s00062-016-0509-0
van der Steen WE, Leemans EL, van den Berg R, Roos YBWEM, Marquering HA, Verbaan D, et al. Radiological scales predicting delayed cerebral ischemia in subarachnoid hemorrhage: systematic review and meta-analysis. Neuroradiology. 2019;61(3):247–56.
pubmed: 30693409 doi: 10.1007/s00234-019-02161-9
Hallevi H, Dar NS, Barreto AD, Morales MM, Martin-Schild S, Abraham AT, et al. The IVH score: a novel tool for estimating intraventricular hemorrhage volume: Clinical and research implications*. Crit Care Med. 2009;37(3):969.
pubmed: 19237905 pmcid: 2692316 doi: 10.1097/CCM.0b013e318198683a
van der Steen WE, Zijlstra IA, Verbaan D, Boers AMM, Gathier CS, van den Berg R, et al. Association of quantified location-specific blood volumes with delayed cerebral ischemia after aneurysmal subarachnoid hemorrhage. Am J Neuroradiol. 2018;39(6):1059–64.
pubmed: 29650786 pmcid: 7410623 doi: 10.3174/ajnr.A5626
Steiner T, Juvela S, Unterberg A, Jung C, Forsting M, Rinkel G. European stroke organization guidelines for the management of intracranial aneurysms and subarachnoid haemorrhage. Cerebrovasc Dis. 2013;35(2):93–112.
pubmed: 23406828 doi: 10.1159/000346087
Carrera E, Schmidt JM, Oddo M, Ostapkovich N, Claassen J, Rincon F, et al. Transcranial doppler ultrasound in the acute phase of aneurysmal subarachnoid hemorrhage. Cerebrovasc Dis. 2009;27(6):579–84.
pubmed: 19390184 doi: 10.1159/000214222
Fisher CM, Kistler JP, Davis JM. Relation of cerebral vasospasm to subarachnoid hemorrhage visualized by computerized tomographic scanning. Neurosurgery. 1980;6(1):1–9.
pubmed: 7354892 doi: 10.1227/00006123-198001000-00001
Frontera JA, Claassen J, Schmidt JM, Wartenberg KE, Temes R, Connolly ES, et al. Prediction of symptomatic vasospasmafter subarachnoid hemorrhage: the modified fisher scale. Neurosurgery. 2006;59(1):21–7.
pubmed: 16823296
Claassen J, Bernardini GL, Kreiter K, Bates J, Du YE, Copeland D, et al. Effect of cisternal and ventricular blood on risk of delayed cerebral ischemia after subarachnoid hemorrhage: the fisher scale revisited. Stroke. 2001;32(9):2012–20.
pubmed: 11546890 doi: 10.1161/hs0901.095677
Dengler NF, Diesing D, Sarrafzadeh A, Wolf S, Vajkoczy P. The barrow neurological institute scale revisited: predictive capabilities for cerebral infarction and clinical outcome in patients with aneurysmal subarachnoid hemorrhage. Neurosurgery. 2017;81(2):341–9.
pubmed: 28201763 doi: 10.1093/neuros/nyw141
Morgan TC, Jesse D, Danielle S, Lees KR, Chanel A, Mishra NK, et al. The modified graeb score. Stroke. 2013;44(3):635–41.
pubmed: 23370203 pmcid: 6800016 doi: 10.1161/STROKEAHA.112.670653
LeRoux PD, Haglund MM, Newell DW, Grady MS, Winn HR. Intraventricular hemorrhage in blunt head trauma: an analysis of 43 cases. Neurosurgery. 1992;31(4):678–85.
pubmed: 1407453
Boers AM, Zijlstra IA, Gathier CS, van den Berg R, Slump CH, Marquering HA, et al. Automatic quantification of subarachnoid hemorrhage on noncontrast CT. Am J Neuroradiol. 2014;35(12):2279–86.
pubmed: 25104292 pmcid: 7965299 doi: 10.3174/ajnr.A4042
Teasdale G, Jennett B. Assessment of coma and impaired consciousness: a practical scale. The Lancet. 1974;304(7872):81–4.
doi: 10.1016/S0140-6736(74)91639-0
Report of World Federation of Neurological Surgeons Committee on a Universal Subarachnoid Hemorrhage Grading Scale. J Neurosurg [Internet]. 1988;68(6). Available from: https://thejns.org/view/journals/j-neurosurg/68/6/article-jns.1988.68.6.0985.xml.xml
Vergouwen MDI, Vermeulen M, van Gijn J, Rinkel GJE, Wijdicks EF, Muizelaar JP, 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. 2010;41(10):2391–5.
pubmed: 20798370 doi: 10.1161/STROKEAHA.110.589275
Jennett B, Snoek J, Bond MR, Brooks N. Disability after severe head injury: observations on the use of the Glasgow outcome scale. J Neurol Neurosurg Psychiatry. 1981;44(4):285–93.
pubmed: 6453957 pmcid: 490949 doi: 10.1136/jnnp.44.4.285
Wilson JTL, Pettigrew LEL, Teasdale GM. Structured interviews for the Glasgow outcome scale and the extended glasgow outcome scale: guidelines for their use. J Neurotrauma. 1998;15(8):573–85.
pubmed: 9726257 doi: 10.1089/neu.1998.15.573
DeLong ER, DeLong DM, Clarke-Pearson DL. Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. Biometrics. 1988;44(3):837–45.
pubmed: 3203132 doi: 10.2307/2531595
Friedman JA, Piepgras DG, Iii LGT, Nichols DA, Wijdicks EFM. Volumetric quantification of Fisher Grade 3 aneurysmal subarachnoid hemorrhage: a novel method to predict symptomatic vasospasm on admission computerized tomography scans. J Neurosurg. 2002;97:7.
doi: 10.3171/jns.2002.97.2.0401
Ko SB, Choi HA, Carpenter AM, Helbok R, Schmidt JM, Badjatia N, et al. Quantitative analysis of hemorrhage volume for predicting delayed cerebral ischemia after subarachnoid hemorrhage. Stroke. 2011;42(3):669–74.
pubmed: 21257823 doi: 10.1161/STROKEAHA.110.600775
Rosen DS, Macdonald RL, Huo D, Goldenberg FD, Novakovic RL, Frank JI, et al. Intraventricular hemorrhage from ruptured aneurysm: clinical characteristics, complications, and outcomes in a large, prospective, multicenter study population. J Neurosurg. 2007;107(2):261–5.
pubmed: 17695378 doi: 10.3171/JNS-07/08/0261
Reilly C, Amidei C, Tolentino J, Jahromi BS, Loch Macdonald R. Clot volume and clearance rate as independent predictors of vasospasm after aneurysmal subarachnoid hemorrhage. J Neurosurg. 2004;101(2):255–61.
pubmed: 15309916 doi: 10.3171/jns.2004.101.2.0255
Broderick JP, Brott TG, Duldner JE, Tomsick T, Huster G. Volume of intracerebral haemorrhage. A powerful and easy-to-use predictor of 30-day mortality. Stroke. 1993;24(7):987–93.
pubmed: 8322400 doi: 10.1161/01.STR.24.7.987
Lagares A, Jiménez-Roldán L, Gomez PA, Munarriz PM, Castaño-León AM, Cepeda S, et al. Prognostic value of the amount of bleeding after aneurysmal subarachnoid hemorrhage: a quantitative volumetric study. Neurosurgery. 2015;77(6):898–907.
pubmed: 26308629 doi: 10.1227/NEU.0000000000000927
Wilson DA, Nakaji P, Abla AA, Uschold TD, Fusco DJ, Oppenlander ME, et al. A simple and quantitative method to predict symptomatic vasospasm after subarachnoid hemorrhage based on computed tomography: beyond the fisher scale. Neurosurgery. 2012;71(4):869–76.
pubmed: 22801639 doi: 10.1227/NEU.0b013e318267360f
Zijlstra IA, Gathier CS, Boers AM, Marquering HA, Slooter AJ, Velthuis BK, et al. Association of automatically quantified total blood volume after aneurysmal subarachnoid hemorrhage with delayed cerebral ischemia. Am J Neuroradiol. 2016;37(9):1588–93.
pubmed: 27102313 pmcid: 7984697 doi: 10.3174/ajnr.A4771
Kramer AH, Mikolaenko I, Deis N, Dumont AS, Kassell NF, Bleck TP, et al. Intraventricular hemorrhage volume predicts poor outcomes but not delayed ischemic neurological deficits among patients with ruptured cerebral aneurysms. Neurosurgery. 2010;67(4):1044–53.
pubmed: 20881568 doi: 10.1227/NEU.0b013e3181ed1379
Czorlich P, Ricklefs F, Reitz M, Vettorazzi E, Abboud T, Regelsberger J, et al. Impact of intraventricular hemorrhage measured by Graeb and LeRoux score on case fatality risk and chronic hydrocephalus in aneurysmal subarachnoid hemorrhage. Acta Neurochir (Wien). 2015;157(3):409–15.
pubmed: 25599911 doi: 10.1007/s00701-014-2334-z
Kang P, Raya A, Zipfel GJ, Dhar R. Factors associated with acute and chronic hydrocephalus in nonaneurysmal subarachnoid hemorrhage. Neurocrit Care. 2016;24(1):104–9.
pubmed: 26136147 doi: 10.1007/s12028-015-0152-7
Sheehan JP, Polin RS, Sheehan JM, Baskaya MK, Kassell NF. Factors Associated with Hydrocephalus after Aneurysmal Subarachnoid Hemorrhage. Neurosurgery. 1999;45(5):1120–8.
pubmed: 10549928 doi: 10.1097/00006123-199911000-00021
Yu H, Zhan R, Wen L, Shen J, Fan Z. The relationship between risk factors and prognostic factors in patients with shunt-dependent hydrocephalus after aneurysmal subarachnoid hemorrhage. J Craniofac Surg. 2014;25(3):902–6.
pubmed: 24657980 doi: 10.1097/SCS.0000000000000561
Champey J, Mourey C, Francony G, Pavese P, Gay E, Gergele L, et al. Strategies to reduce external ventricular drain–related infections: a multicenter retrospective study. J Neurosurg JNS. 2018;130(6):2034–6.
doi: 10.3171/2018.1.JNS172486
Czorlich P, Sauvigny T, Ricklefs F, Kluge S, Vettorazzi E, Regelsberger J, et al. The simplified acute physiology score II to predict hospital mortality in aneurysmal subarachnoid hemorrhage. Acta Neurochir (Wien). 2015;157(12):2051–9.
pubmed: 26467798 doi: 10.1007/s00701-015-2605-3
Jaja BNR, Cusimano MD, Etminan N, Hanggi D, Hasan D, Ilodigwe D, et al. Clinical prediction models for aneurysmal subarachnoid hemorrhage: a systematic review. Neurocrit Care. 2013;18(1):143–53.
pubmed: 23138544 doi: 10.1007/s12028-012-9792-z
Couret D, Boussen S, Cardoso D, Alonzo A, Madec S, Reyre A, et al. Comparison of scales for the evaluation of aneurysmal subarachnoid haemorrhage: a retrospective cohort study. Eur Radiol. 2024. https://doi.org/10.1007/s00330-024-10814-4 .
doi: 10.1007/s00330-024-10814-4 pubmed: 38836940

Auteurs

Pierre Simeone (P)

Department of Anesthesiology and Critical Care Medicine, University Hospital Timone, Aix Marseille University, Marseille, France. pierre.simeone@ap-hm.fr.
Institute of Neuroscience of La Timone, CNRS, INT, Aix Marseille University, Marseille, France. pierre.simeone@ap-hm.fr.

Thomas Corrias (T)

Department of Anesthesiology and Critical Care Medicine, University Hospital Timone, Aix Marseille University, Marseille, France.

Nicolas Bruder (N)

Department of Anesthesiology and Critical Care Medicine, University Hospital Timone, Aix Marseille University, Marseille, France.

Salah Boussen (S)

Department of Anesthesiology and Critical Care Medicine, University Hospital Timone, Aix Marseille University, Marseille, France.

Dan Cardoso (D)

Department of Anesthesiology and Critical Care Medicine, University Hospital Timone, Aix Marseille University, Marseille, France.

Audrey Alonzo (A)

Department of Anesthesiology and Critical Care Medicine, University Hospital Timone, Aix Marseille University, Marseille, France.

Anthony Reyre (A)

Department of Radiology, University Hospital Timone, Aix Marseille University, Marseille, France.

Hervé Brunel (H)

Department of Radiology, University Hospital Timone, Aix Marseille University, Marseille, France.

Nadine Girard (N)

Department of Radiology, University Hospital Timone, Aix Marseille University, Marseille, France.

Thomas Graillon (T)

Department of Neurosurgery, University Hospital Timone, Aix Marseille University, Marseille, France.

Henry Dufour (H)

Department of Neurosurgery, University Hospital Timone, Aix Marseille University, Marseille, France.

David Couret (D)

Neurocritical Care Unit, University Hospital Saint Pierre, Réunion University, Saint Denis de La Réunion, France.
Reunion Island University, Institut National de La Santé Et de La Recherche Médicale, Diabète Athérothrombose Réunion Océan Indien, Saint Denis de La Réunion, France.

Lionel Velly (L)

Department of Anesthesiology and Critical Care Medicine, University Hospital Timone, Aix Marseille University, Marseille, France.
Institute of Neuroscience of La Timone, CNRS, INT, Aix Marseille University, Marseille, France.

Classifications MeSH