Time dependency of automated collateral scores in computed tomography angiography and computed tomography perfusion images in patients with intracranial arterial occlusion

被引:2
|
作者
Su, Jiahang [1 ]
Wolff, Lennard [1 ]
van Doormaal, Pieter Jan [1 ]
Dippel, Diederik W. J. [2 ]
van Zwam, Wim [3 ]
Niessen, Wiro J. [1 ,4 ]
van der Lugt, Aad [1 ]
van Walsum, Theo [1 ]
机构
[1] Erasmus MC, Dept Radiol & Nucl Med, Rotterdam, Netherlands
[2] Erasmus MC, Dept Neurol, Rotterdam, Netherlands
[3] Maastricht UMC, Dept Radiol, Maastricht, Netherlands
[4] Delft Univ Technol, Fac Appl Sci, Delft, Netherlands
关键词
Ischemic Stroke; Collateral score; CTA; CTP; CT ANGIOGRAPHY; ACUTE STROKE; ISCHEMIC-STROKE; CIRCULATION; MULTIPHASE; PARAMETERS; OUTCOMES; PHASE;
D O I
10.1007/s00234-022-03050-4
中图分类号
R74 [神经病学与精神病学];
学科分类号
摘要
Purpose The assessment of collateral status may depend on the timing of image acquisition. The purpose of this study is to investigate whether there are optimal time points in CT Perfusion (CTP) for collateral status assessment, and compare collaterals scores at these time points with collateral scores from multiphase CT angiography (mCTA). Methods Patients with an acute intracranial occlusion who underwent baseline non-contrast CT, mCTA and CT perfusion were selected. Collateral status was assessed using an automatically computed Collateral Ratio (CR) score in mCTA, and predefined time points in CTP acquisition. CRs extracted from CTP were correlated with CRs from mCTA. In addition, all CRs were related to baseline National Institutes of Health Stroke Scale (NIHSS) and Alberta Stoke Program Early CT Score (ASPECTS) with linear regression analysis to find the optimal CR. Results In total 58 subjects (median age 74 years; interquartile range 61-83 years; 33 male) were included. When comparing the CRs from the CTP vs. mCTA acquisition, the strongest correlations were found between CR from baseline mCTA and the CR at the maximal intensity projection of time-resolved CTP (r = 0.81) and the CR at the peak of arterial enhancement point (r = 0.78). Baseline mCTA-derived CR had the highest correlation with ASPECTS (beta = 0.36 (95%CI 0.11, 0.61)) and NIHSS (beta = - 0.48 (95%CI - 0.72, - 0.16)). Conclusion Collateral status assessment strongly depends on the timing of acquisition. Collateral scores obtained from mCTA imaging is close to the optimal collateral score obtained from CTP imaging.
引用
收藏
页码:313 / 322
页数:10
相关论文
共 50 条
  • [1] Time dependency of automated collateral scores in computed tomography angiography and computed tomography perfusion images in patients with intracranial arterial occlusion
    Jiahang Su
    Lennard Wolff
    Pieter Jan van Doormaal
    Diederik W.J. Dippel
    Wim van Zwam
    Wiro J Niessen
    Aad van der Lugt
    Theo van Walsum
    Neuroradiology, 2023, 65 : 313 - 322
  • [2] Collateral Status in Ischemic Stroke: A Comparison of Computed Tomography Angiography, Computed Tomography Perfusion, and Digital Subtraction Angiography
    Kauw, Frans
    Dankbaar, Jan W.
    Martin, Blake W.
    Ding, Victoria Y.
    Boothroyd, Derek B.
    van Ommen, Fasco
    de Jong, Hugo W. A. M.
    Kappelle, L. Jaap
    Velthuis, Birgitta K.
    Heit, Jeremy J.
    Wintermark, Max
    JOURNAL OF COMPUTER ASSISTED TOMOGRAPHY, 2020, 44 (06) : 984 - 992
  • [3] Computed Tomography Angiography and Myocardial Computed Tomography Perfusion in Patients With Coronary Stents
    Rief, Matthias
    Zimmermann, Elke
    Stenzel, Fabian
    Martus, Peter
    Stangl, Karl
    Greupner, Johannes
    Knebel, Fabian
    Kranz, Anisha
    Schlattmann, Peter
    Laule, Michael
    Dewey, Marc
    JOURNAL OF THE AMERICAN COLLEGE OF CARDIOLOGY, 2013, 62 (16) : 1476 - 1485
  • [4] Computed Tomography, Computed Tomography Angiography, and Perfusion Computed Tomography Evaluation of Acute Ischemic Stroke
    Leiva-Salinas, Carlos
    Jiang, Bin
    Wintermark, Max
    NEUROIMAGING CLINICS OF NORTH AMERICA, 2018, 28 (04) : 565 - 572
  • [5] Diagnostic performance of an algorithm for automated collateral scoring on computed tomography angiography
    Lennard Wolff
    Simone M. Uniken Venema
    Sven P. R. Luijten
    Jeannette Hofmeijer
    Jasper M. Martens
    Marie Louise E. Bernsen
    Adriaan C. G. M. van Es
    Pieter Jan van Doormaal
    Diederik W. J. Dippel
    Wim van Zwam
    Theo van Walsum
    Aad van der Lugt
    European Radiology, 2022, 32 : 5711 - 5718
  • [6] Diagnostic performance of an algorithm for automated collateral scoring on computed tomography angiography
    Wolff, Lennard
    Venema, Simone M. Uniken
    Luijten, Sven P. R.
    Hofmeijer, Jeannette
    Martens, Jasper M.
    Bernsen, Marie Louise E.
    van Es, Adriaan C. G. M.
    van Doormaal, Pieter Jan
    Dippel, Diederik W. J.
    van Zwam, Wim
    van Walsum, Theo
    van der Lugt, Aad
    EUROPEAN RADIOLOGY, 2022, 32 (08) : 5711 - 5718
  • [7] Computed tomography perfusion and computed tomography angiography in vasospasm after subarachnoid hemorrhage
    Stecco, Alessandro
    Fabbiano, Francesco
    Amatuzzo, Paola
    Quagliozzi, Martina
    Soligo, Eleonora
    Divenuto, Ignazio
    Panzarasa, Gabriele
    Carriero, Alessandro
    JOURNAL OF NEUROSURGICAL SCIENCES, 2018, 62 (04) : 397 - 405
  • [8] Evaluation of the relationship between computed tomography angiography collateral scores and clinical outcome
    Yabalak, Ahmet
    Ogun, Muhammed Nur
    Onalan, Aysenur
    Murat Yilmaz, Murat
    Tokmak, Hilmiye
    Ersoy, Sadettin
    Bilgili, Fatma
    Bakkal, Tahsin
    ARQUIVOS DE NEURO-PSIQUIATRIA, 2024, 82 (03) : 1 - 7
  • [9] Myocardial computed tomography perfusion after Computed tomography angiography in patients with coronary stents: comparison with conventional coronary angiography
    Qin Jie
    Hao Baoshun
    Liao Hongying
    JOURNAL OF THE AMERICAN COLLEGE OF CARDIOLOGY, 2014, 64 (16) : C231 - C231
  • [10] Computed Tomography Perfusion is aUseful Adjunct to Computed Tomography Angiography in the Diagnosis of Brain Death
    Sawicki, M.
    Solek-Pastuszka, J.
    Chamier-Cieminska, K.
    Walecka, A.
    Walecki, J.
    Bohatyrewicz, R.
    CLINICAL NEURORADIOLOGY, 2019, 29 (01) : 101 - 108