E-156 Brainomix easpects software improves interobserver agreement and accuracy of neurologist and neuroradiologists in interpretation of aspects score and outperforms human readers in prediction of final infarct

Brinjikji, Waleed; Benson, John C.; Campeau, Norbert G.; Carr, Caitlin; Cogswell, Petrice M; Klaas, James P.; Liebo, Greta B.; Little, James W.; Luetmer, Patrick H.; Messina, Steven A.; Nagelschneider, Alex A.; Schwartz, Kimberly; Wood, Christopher P.; Nasr, Deena M.; Braksick, Sherri A.; Kallmes, David F.

doi:10.1136/neurintsurg-2020-snis.188

Cited by 3 publications

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“…highly time-sensitive evolving stroke cases to optimise triaging and treatment, showing a potential for translation to strokeprevention for AF patients (Figure 7, right panels) (117)(118)(119)(120). Ultimately, combining biophysical modelling accelerated by deep learning approaches in a similar manner may allow for mechanismbased treatment to be tailored to the patient prior to the occurrence of stroke, massively improving patient outcomes and reducing healthcare costs as proposed in Figure 7 (left panels).…”

Section: Application Of Artificial Intelligencementioning

confidence: 99%

Imaging and biophysical modelling of thrombogenic mechanisms in atrial fibrillation and stroke

Qureshi

Lip

Nordsletten

et al. 2023

Front. Cardiovasc. Med.

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Atrial fibrillation (AF) underlies almost one third of all ischaemic strokes, with the left atrial appendage (LAA) identified as the primary thromboembolic source. Current stroke risk stratification approaches, such as the CHA2DS2-VASc score, rely mostly on clinical comorbidities, rather than thrombogenic mechanisms such as blood stasis, hypercoagulability and endothelial dysfunction—known as Virchow’s triad. While detection of AF-related thrombi is possible using established cardiac imaging techniques, such as transoesophageal echocardiography, there is a growing need to reliably assess AF-patient thrombogenicity prior to thrombus formation. Over the past decade, cardiac imaging and image-based biophysical modelling have emerged as powerful tools for reproducing the mechanisms of thrombogenesis. Clinical imaging modalities such as cardiac computed tomography, magnetic resonance and echocardiographic techniques can measure blood flow velocities and identify LA fibrosis (an indicator of endothelial dysfunction), but imaging remains limited in its ability to assess blood coagulation dynamics. In-silico cardiac modelling tools—such as computational fluid dynamics for blood flow, reaction-diffusion-convection equations to mimic the coagulation cascade, and surrogate flow metrics associated with endothelial damage—have grown in prevalence and advanced mechanistic understanding of thrombogenesis. However, neither technique alone can fully elucidate thrombogenicity in AF. In future, combining cardiac imaging with in-silico modelling and integrating machine learning approaches for rapid results directly from imaging data will require development under a rigorous framework of verification and clinical validation, but may pave the way towards enhanced personalised stroke risk stratification in the growing population of AF patients. This Review will focus on the significant progress in these fields.

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Section: Application Of Artificial Intelligencementioning

confidence: 99%

Imaging and biophysical modelling of thrombogenic mechanisms in atrial fibrillation and stroke

Qureshi

Lip

Nordsletten

et al. 2023

Front. Cardiovasc. Med.

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“…This will provide objective and consistent quantification of imaging biomarkers to ensure robust matching to historical controls, as well as the evaluation of imaging endpoints, and will help to reduce the risk of bias when analyzing data. NCCT, CTA and CTP will be processed using e-ASPECTS, e-CTA, and e-CTP modules within e-Stroke respectively (53)(54)(55)(56)(57)(58). e-Stroke imaging software is intended to be used as a decision support tool and will be used to facilitate adjudication of patient inclusion criteria for prospective patients and historical controls, where the results are intended for this purpose.…”

Section: Post-processing Softwarementioning

confidence: 99%

Efficacy of Cerebrolysin Treatment as an Add-On Therapy to Mechanical Thrombectomy in Patients With Acute Ischemic Stroke Due to Large Vessel Occlusion: Study Protocol for a Prospective, Open Label, Single-Center Study With 12 Months of Follow-Up

Staszewski

Stępień²,

Piusińska‐Macoch³

et al. 2022

Front. Neurol.

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This study is designed to determine the efficacy of Cerebrolysin treatment as an add-on therapy to mechanical thrombectomy (MT) in reducing global disability in subjects with acute ischemic stroke (AIS). We have planned a single center, prospective, open-label, single-arm study with a 12-month follow-up of 50 patients with moderate to severe AIS, with a small established infarct core and with good collateral circulation who achieve significant reperfusion following MT and who receive additional Cerebrolysin within 8 h of stroke onset compared to 50 historical controls treated with MT alone, matched for age, clinical severity, occlusion location, baseline perfusion lesion volume, onset to reperfusion time, and use of iv thrombolytic therapy. The primary outcome measure will be the overall proportion of subjects receiving Cerebrolysin compared to the control group experiencing a favorable functional outcome (by modified Rankin Scale 0–2) at 90 days, following stroke onset. The secondary objectives are to determine the efficacy of Cerebrolysin as compared to the control group in reducing the risk of symptomatic secondary hemorrhagic transformation, improving neurological outcomes (NIHSS 0–2 at day 7, day 30, and 90), reducing mortality rates (over the 90-day and 12 months study period), and improving: activities of daily living (by Barthel Index), health-related quality of life (EQ-5D-5L) assessed at day 30, 90, and at 12 months. The other measures of efficacy in the Cerebrolysin group will include: assessment of final stroke volume and penumbral salvage (measured by CT/CTP at 30 days) and its change compared to baseline volume, changes over time in language function (by the 15-item Boston Naming Test), hemispatial neglect (by line bisection test), global cognitive function (by The Montreal Cognitive Assessment), and depression (by Hamilton Depression Rating Scale) between day 30 and day 90 assessments). The patients will receive 30 ml of Cerebrolysin within 8 h of AIS stroke onset and continue treatment once daily until day 21 (first cycle) and they will receive a second cycle of treatment (30 ml/d for 21 days given in the Outpatient Department or Neurorehabilitation Clinic) from day 69 to 90.

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“…Olyan területeken sikeresek elsősorban, ahol a rutinfeladatok elvégzését tudják automatizálni, pontosítani, illetve felgyorsítani [23]. Az akut stroke ellátása a mesterséges intelligencia egyik ilyen, gyorsan fejlődő alkalmazási területe, ahol az automatizált értékelés a diagnózis pontosságának és a betegellátás minőségének javítását tudja eredményezni [24,25]. A stroke-ellátás alapja a CT-(esetleg MR-) vizsgálatok megfelelő elemzése és standardizált értékelése rövid idő alatt, így ennek automatizálása és az eredmények megosztása jelentős javulást eredményez a strokeellátás működésében [23,26].…”

Section: Az Akut Stroke Képalkotásának Automatizált Szoftveres Támogatása -E-stroke Suiteunclassified

Stroke-ellátást támogató teleradiológiai hálózat a Nyugat- és Dél-Dunántúlon

Bogner

Chadaide

Lenzsér

et al. 2021

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Összefoglaló. Bevezetés: A stroke kezelésének lehetőségei az utóbbi években jelentősen megváltoztak: a thrombolysis után bevezetésre került a mechanikus thrombectomia, és a terápiás időablak is jelentősen kitágult az utóbbi évek nagy multicentrikus tanulmányai alapján. Ezek a lehetőségek új igényeket fogalmaztak meg a képalkotó diagnosztikával szemben: az ischaemia okozta morfológiai elváltozások mellett az artériás és a kollaterális rendszer állapotát, valamint bizonyos esetekben az agy szöveti perfúzióját is szükséges meghatározni. Ezeket a komplex kiértékelési feladatokat ma már mesterségesintelligencia-algoritmusok támogathatják, melyek a kiértékelést pár perc alatt elvégezve segítenek a terápiás döntés kialakításában. Célkitűzés: A Dél- és a Nyugat-dunántúli régióban hat intézmény részvételével egy dedikált stroke teleradiológiai hálózat kialakítása. Módszer: A stroke-CT-kiértékelő szoftver és a képkommunikáció integrációja, a vizsgálati protokollok technikai paramétereinek egységesítése, a kiértékelési eredmények teleradiológiai megjelenítése valósult meg a hálózat kialakítása során. Eredmények: A hálózat egységesítette nemcsak a stroke-CT-protokollok beállításait, de beutalási és értékelési szempontjait is. A stroke-CT-kiértékelések és a mechanikus thrombectomiák száma is emelkedett az elmúlt egy évben. Következtetés: A dedikált teleradiológiai stroke-hálózat segítségével optimalizálni kívánjuk a régió stroke-ellátását: egyrészt lehetőleg ne maradjanak ellátatlanul a thrombectomiából valószínűleg profitáló betegek, másrészt ne terheljük az ellátórendszert olyan esetekkel, melyekről a teljes dokumentáció ismeretében derül ki, hogy nem javasolt a beavatkozás. Orv Hetil. 2021; 162(17): 668–675. Summary. Introduction: The possibilities of cerebral stroke management have changed substantially during the last few years. Following a few multicentric studies, mechanical thrombectomy became an established method besides thrombolysis. In addition, the therapeutic window for both methods is much wider now than before. These changes described above demanded more information of CT morphological changes due to ischemia, but the condition and functionality of the arterial and collateral system, and occasionally tissue perfusion performance should also be characterized. Recently, evaluation of different computer tomographic (CT) measurements can be done using artificial intelligence based methods, which perform data analysis in a few minutes. Objective: To establish a dedicated stroke teleradiology network with artificial intelligence based image analysis in Western and Southern Transdanubia in Hungary that involves six partner institutes. Method: Integration of automated image analysis with teleradiology software was established, and the technical parameters of examination protocols were unified. Results of stroke CT image analysis became accessible through the teleradiology network. Results: The daily use of integrated central image analysis and image communication had a positive impact on referrals and therapeutic evaluation of stroke cases. The number of image processing and mechanical thrombectomy increased during the last year. Conclusion: With the help of the dedicated teleradiology stroke network, we want to optimize the stroke care in the region: on the one hand, patients who are likely to benefit from thrombectomy should not be left unattended, on the other, the health care system should not be burdened with cases, when intervention is not recommended having the complete clinical data accessed. Orv Hetil. 2021; 162(17): 668–675.

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E-156 Brainomix easpects software improves interobserver agreement and accuracy of neurologist and neuroradiologists in interpretation of aspects score and outperforms human readers in prediction of final infarct

Cited by 3 publications

References 0 publications

Imaging and biophysical modelling of thrombogenic mechanisms in atrial fibrillation and stroke

Imaging and biophysical modelling of thrombogenic mechanisms in atrial fibrillation and stroke

Efficacy of Cerebrolysin Treatment as an Add-On Therapy to Mechanical Thrombectomy in Patients With Acute Ischemic Stroke Due to Large Vessel Occlusion: Study Protocol for a Prospective, Open Label, Single-Center Study With 12 Months of Follow-Up

Stroke-ellátást támogató teleradiológiai hálózat a Nyugat- és Dél-Dunántúlon

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