Top

Published in:

Open Access 18-03-2024 | Stroke | Diagnostic Neuroradiology

Impact of temporal resolution on perfusion metrics, therapy decision, and radiation dose reduction in brain CT perfusion in patients with suspected stroke

Authors: Alexander Rau, Marco Reisert, Thomas Stein, Katharina Mueller-Peltzer, Stephan Rau, Fabian Bamberg, Christian A. Taschner, Horst Urbach, Elias Kellner

Published in: Neuroradiology | Issue 5/2024

Abstract

Purpose

CT perfusion of the brain is a powerful tool in stroke imaging, though the radiation dose is rather high. Several strategies for dose reduction have been proposed, including increasing the intervals between the dynamic scans. We determined the impact of temporal resolution on perfusion metrics, therapy decision, and radiation dose reduction in brain CT perfusion from a large dataset of patients with suspected stroke.

Methods

We retrospectively included 3555 perfusion scans from our clinical routine dataset. All cases were processed using the perfusion software VEOcore with a standard sampling of 1.5 s, as well as simulated reduced temporal resolution of 3.0, 4.5, and 6.0 s by leaving out respective time points. The resulting perfusion maps and calculated volumes of infarct core and mismatch were compared quantitatively. Finally, hypothetical decisions for mechanical thrombectomy following the DEFUSE-3 criteria were compared.

Results

The agreement between calculated volumes for core (ICC = 0.99, 0.99, and 0.98) and hypoperfusion (ICC = 0.99, 0.99, and 0.97) was excellent for all temporal sampling schemes. Of the 1226 cases with vascular occlusion, 14 (1%) for 3.0 s sampling, 23 (2%) for 4.5 s sampling, and 63 (5%) for 6.0 s sampling would have been treated differently if the DEFUSE-3 criteria had been applied. Reduction of temporal resolution to 3.0 s, 4.5 s, and 6.0 s reduced the radiation dose by a factor of 2, 3, or 4.

Conclusion

Reducing the temporal sampling of brain perfusion CT has only a minor impact on image quality and treatment decision, but significantly reduces the radiation dose to that of standard non-contrast CT.

Available only for authorised users

Albers GW, Marks MP, Kemp S et al (2018) Thrombectomy for stroke at 6 to 16 hours with selection by perfusion imaging. N Engl J Med 378:708–718. https://doi.org/10.1056/NEJMoa1713973CrossRefPubMedPubMedCentral

Nogueira RG, Jadhav AP, Haussen DC et al (2018) Thrombectomy 6 to 24 hours after stroke with a mismatch between deficit and infarct. N Engl J Med 378:11–21. https://doi.org/10.1056/NEJMoa1706442CrossRefPubMed

Powers WJ, Rabinstein AA, Ackerson T et al (2019) Guidelines for the early management of patients with acute ischemic stroke: 2019 update to the 2018 guidelines for the early management of acute ischemic stroke: a guideline for healthcare professionals from the American Heart Association/American Stroke Association. Stroke 50:e344–e418. https://doi.org/10.1161/STR.0000000000000211CrossRefPubMed

Othman AE, Afat S, Brockmann MA et al (2016) Radiation dose reduction in perfusion CT imaging of the brain: a review of the literature. J Neuroradiol 43:1–5. https://doi.org/10.1016/j.neurad.2015.06.003CrossRefPubMed

Vagal A, Wintermark M, Nael K et al (2019) Automated CT perfusion imaging for acute ischemic stroke: pearls and pitfalls for real-world use. Neurology 93:888–898. https://doi.org/10.1212/WNL.0000000000008481CrossRefPubMed

Hoang JK, Wang C, Frush DP et al (2013) Estimation of radiation exposure for brain perfusion CT: standard protocol compared with deviations in protocol. AJR Am J Roentgenol 201:W730-734. https://doi.org/10.2214/AJR.12.10031CrossRefPubMed

Kloska SP, Fischer T, Sauerland C et al (2010) Increasing sampling interval in cerebral perfusion CT: limitation for the maximum slope model. Acad Radiol 17:61–66. https://doi.org/10.1016/j.acra.2009.07.009CrossRefPubMed

Wiesmann M, Berg S, Bohner G et al (2008) Dose reduction in dynamic perfusion CT of the brain: effects of the scan frequency on measurements of cerebral blood flow, cerebral blood volume, and mean transit time. Eur Radiol 18:2967–2974. https://doi.org/10.1007/s00330-008-1083-xCrossRefPubMed

Wintermark M, Smith WS, Ko NU et al (2004) Dynamic perfusion CT: optimizing the temporal resolution and contrast volume for calculation of perfusion CT parameters in stroke patients. AJNR Am J Neuroradiol 25:720–729PubMedPubMedCentral

10.

Kämena A, Streitparth F, Grieser C et al (2007) Dynamic perfusion CT: optimizing the temporal resolution for the calculation of perfusion CT parameters in stroke patients. Eur J Radiol 64:111–118. https://doi.org/10.1016/j.ejrad.2007.02.025CrossRefPubMed

11.

Abels B, Klotz E, Tomandl BF et al (2011) CT perfusion in acute ischemic stroke: a comparison of 2-second and 1-second temporal resolution. AJNR Am J Neuroradiol 32:1632–1639. https://doi.org/10.3174/ajnr.A2576CrossRefPubMedPubMedCentral

12.

Ioannidis GS, Christensen S, Nikiforaki K et al (2021) Cerebral CT perfusion in acute stroke: the effect of lowering the tube load and sampling rate on the reproducibility of parametric maps. Diagnostics (Basel) 11:1121. https://doi.org/10.3390/diagnostics11061121CrossRefPubMed

13.

Ma G, Cao Y-Z, Shen G-C et al (2023) CT perfusion with increased temporal sampling interval to predict target mismatch status in patients with acute ischemic stroke. Neuroradiology 65:105–111. https://doi.org/10.1007/s00234-022-03026-4CrossRefPubMed

14.

Olivot J-M, Mlynash M, Thijs VN et al (2009) Optimal Tmax threshold for predicting penumbral tissue in acute stroke. Stroke 40:469–475. https://doi.org/10.1161/STROKEAHA.108.526954CrossRefPubMed

15.

Lin L, Bivard A, Krishnamurthy V et al (2016) Whole-brain CT perfusion to quantify acute ischemic penumbra and core. Radiology 279:876–887. https://doi.org/10.1148/radiol.2015150319CrossRefPubMed

16.

Kellner E, Urbach H (2021) Machine outputs must be checked. Clin Neuroradiol 31:507–508. https://doi.org/10.1007/s00062-021-01012-6CrossRefPubMedPubMedCentral

17.

Psychogios M-N, Sporns PB, Ospel J et al (2021) Automated perfusion calculations vs. visual scoring of collaterals and CBV-ASPECTS : has the machine surpassed the eye? Clin Neuroradiol 31:499–506. https://doi.org/10.1007/s00062-020-00974-3CrossRefPubMed

18.

Mangla R, Ekhom S, Jahromi BS et al (2014) CT perfusion in acute stroke: know the mimics, potential pitfalls, artifacts, and technical errors. Emerg Radiol 21:49–65. https://doi.org/10.1007/s10140-013-1125-9CrossRefPubMed

19.

Straka M, Albers GW, Bammer R (2010) Real-time diffusion-perfusion mismatch analysis in acute stroke. J Magn Reson Imaging 32:1024–1037. https://doi.org/10.1002/jmri.22338CrossRefPubMedPubMedCentral

20.

Ringelstein A, Lechel U, Fahrendorf DM et al (2014) Radiation exposure in perfusion CT of the brain. J Comput Assist Tomogr 38:25. https://doi.org/10.1097/RCT.0b013e3182a3f9a0CrossRefPubMed

21.

Zensen S, Guberina N, Opitz M et al (2021) Radiation exposure of computed tomography imaging for the assessment of acute stroke. Neuroradiology 63:511–518. https://doi.org/10.1007/s00234-020-02548-zCrossRefPubMed

22.

Cros M, Geleijns J, Joemai RMS, Salvadó M (2016) Perfusion CT of the brain and liver and of lung tumors: use of Monte Carlo simulation for patient dose estimation for examinations with a cone-beam 320-MDCT scanner. Am J Roentgenol 206:129–135. https://doi.org/10.2214/AJR.15.14913CrossRef

23.

Becks MJ, Manniesing R, Vister J et al (2019) Brain CT perfusion improves intracranial vessel occlusion detection on CT angiography. J Neuroradiol 46:124–129. https://doi.org/10.1016/j.neurad.2018.03.003CrossRefPubMed

24.

van der Hoeven EJRJ, Dankbaar JW, Algra A et al (2015) Additional diagnostic value of computed tomography perfusion for detection of acute ischemic stroke in the posterior circulation. Stroke 46:1113–1115. https://doi.org/10.1161/STROKEAHA.115.008718CrossRefPubMed

25.

Kudo K, Sasaki M, Yamada K et al (2010) Differences in CT perfusion maps generated by different commercial software: quantitative analysis by using identical source data of acute stroke patients. Radiology 254:200–209. https://doi.org/10.1148/radiol.254082000CrossRefPubMed

26.

Koopman MS, Berkhemer OA, Geuskens RREG et al (2019) Comparison of three commonly used CT perfusion software packages in patients with acute ischemic stroke. J Neurointerv Surg 11:1249–1256. https://doi.org/10.1136/neurintsurg-2019-014822CrossRefPubMed

27.

Zhou X, Nan Y, Ju J et al (2022) Comparison of two software packages for perfusion imaging: ischemic core and penumbra estimation and patient triage in acute ischemic stroke. Cells 11:2547. https://doi.org/10.3390/cells11162547CrossRefPubMedPubMedCentral

28.

Liu J, Wang J, Wu J et al (2023) Comparison of two computed tomography perfusion post-processing software to assess infarct volume in patients with acute ischemic stroke. Front Neurosci 17:1151823. https://doi.org/10.3389/fnins.2023.1151823CrossRefPubMedPubMedCentral

29.

Muehlen I, Sprügel M, Hoelter P et al (2022) Comparison of two automated computed tomography perfusion applications to predict the final infarct volume after thrombolysis in cerebral infarction 3 recanalization. Stroke 53:1657–1664. https://doi.org/10.1161/STROKEAHA.121.035626CrossRefPubMed

30.

Austein F, Riedel C, Kerby T et al (2016) Comparison of perfusion CT software to predict the final infarct volume after thrombectomy. Stroke 47:2311–2317. https://doi.org/10.1161/STROKEAHA.116.013147CrossRefPubMed

31.

Xiong Y, Huang CC, Fisher M et al (2019) Comparison of automated CT perfusion softwares in evaluation of acute ischemic stroke. J Stroke Cerebrovasc Dis 28:104392. https://doi.org/10.1016/j.jstrokecerebrovasdis.2019.104392CrossRefPubMed

32.

Horiguchi J, Kiura Y, Tanaka J et al (2011) Feasibility of extended-coverage perfusion and dynamic computer tomography (CT) angiography using toggling-table technique on 64-slice CT. J Neuroradiol 38:156–160. https://doi.org/10.1016/j.neurad.2010.10.004CrossRefPubMed

33.

Krishnan P, Murphy A, Aviv RI (2017) CT-based techniques for brain perfusion. Top Magn Reson Imaging 26:113–119. https://doi.org/10.1097/RMR.0000000000000129CrossRefPubMed

34.

Kasasbeh AS, Christensen S, Straka M et al (2016) Optimal computed tomographic perfusion scan duration for assessment of acute stroke lesion volumes. Stroke 47:2966–2971. https://doi.org/10.1161/STROKEAHA.116.014177CrossRefPubMedPubMedCentral

35.

Hartman JB, Moran S, Zhu C et al (2022) Use of CTA test dose to trigger a low cardiac output protocol improves acute stroke CTP data analyzed with RAPID software. Am J Neuroradiol 43:388–393. https://doi.org/10.3174/ajnr.A7428CrossRefPubMedPubMedCentral

36.

de Vries L, Emmer BJ, Majoie CBLM et al (2023) PerfU-Net: baseline infarct estimation from CT perfusion source data for acute ischemic stroke. Med Image Anal 85:102749. https://doi.org/10.1016/j.media.2023.102749CrossRefPubMed

37.

Lei Y, Niu C, Zhang J, et al (2023) CT image denoising and deblurring with deep learning: current status and perspectives. IEEE Transactions on Radiation and Plasma Medical Sciences 1–1. https://doi.org/10.1109/TRPMS.2023.3341903

38.

Moghari MD, Sanaat A, Young N et al (2023) Reduction of scan duration and radiation dose in cerebral CT perfusion imaging of acute stroke using a recurrent neural network. Phys Med Biol 68:165005. https://doi.org/10.1088/1361-6560/acdf3aCrossRef

Title: Impact of temporal resolution on perfusion metrics, therapy decision, and radiation dose reduction in brain CT perfusion in patients with suspected stroke
Authors: Alexander Rau
Marco Reisert
Thomas Stein
Katharina Mueller-Peltzer
Stephan Rau
Fabian Bamberg
Christian A. Taschner
Horst Urbach
Elias Kellner
Publication date: 18-03-2024
Publisher: Springer Berlin Heidelberg
Keywords: Stroke
Computed Tomography
Computed Tomography
Published in: Neuroradiology / Issue 5/2024
Print ISSN: 0028-3940
Electronic ISSN: 1432-1920
DOI: https://doi.org/10.1007/s00234-024-03335-w

2024 ASCO Annual Meeting

Springer Medicine

Impact of temporal resolution on perfusion metrics, therapy decision, and radiation dose reduction in brain CT perfusion in patients with suspected stroke

Abstract

Purpose

Methods

Results

Conclusion

2024 ASCO Annual Meeting

Springer Medicine

Abstract

Purpose

Methods

Results

Conclusion

Please log in to get access to this content

Other articles of this Issue 5/2024

Altered whole-brain functional network in patients with frontal low-grade gliomas: a resting-state functional MRI study

Combined vertebroplasty and pedicle screw insertion for vertebral consolidation: feasibility and technical considerations

Imaging of supratentorial intraventricular masses in children:a pictorial review— part 1

Balloon neck-plasty to create a wide-necked aneurysm in the elastase-induced rabbit model

A comparative study of diffusion kurtosis imaging and diffusion tensor imaging in detecting corticospinal tract impairment in diffuse glioma patients

Brain imaging prior to thrombectomy in the late window of large vessel occlusion ischemic stroke: a systematic review and meta-analysis