Whole brain CT perfusion maps with paradoxical low mean transit time to predict infarct core

Transcription

1 Whole brain CT perfusion maps with paradoxical low mean transit time to predict infarct core Poster No.: B-292 Congress: ECR 2011 Type: Scientific Paper Topic: Neuro Authors: S. Chakraborty, M. E. Ahmad, R. Glikstein, M. Hogan, D. Dowlatshahi, G. Stotts; Ottawa, ON/CA Keywords: Neuroradiology brain, CT, CT-Quantitative, Ischemia / Infarction DOI: /ecr2011/B-292 Any information contained in this pdf file is automatically generated from digital material submitted to EPOS by third parties in the form of scientific presentations. References to any names, marks, products, or services of third parties or hypertext links to thirdparty sites or information are provided solely as a convenience to you and do not in any way constitute or imply ECR's endorsement, sponsorship or recommendation of the third party, information, product or service. ECR is not responsible for the content of these pages and does not make any representations regarding the content or accuracy of material in this file. As per copyright regulations, any unauthorised use of the material or parts thereof as well as commercial reproduction or multiple distribution by any traditional or electronically based reproduction/publication method ist strictly prohibited. You agree to defend, indemnify, and hold ECR harmless from and against any and all claims, damages, costs, and expenses, including attorneys' fees, arising from or related to your use of these pages. Please note: Links to movies, ppt slideshows and any other multimedia files are not available in the pdf version of presentations. Page 1 of 21

2 Purpose CT perfusion (CTP) is used to differentiate infarct core from potentially salvageable ischemic tissue in acute strokes[1 on page ]. CTP is based upon central volume technique (CBF= CBV/MTT)[2 on page ] and uses complex deconvolution method to generate various perfusion maps[3 on page ]. Traditionally the low CBV (Cerebral Blood Volume) is considered to be reflective of infarct core, while low CBF (Cerebral Blood Flow) and high MTT (Mean Transit Time) and TTP (Time to Peak) are suggestive of infarct core plus ischemic penumbra[4 on page ]. The paradoxical low MTT in the region of ischemia has not described in the current CTP literature to best of our knowledge. We reviewed whole brain CT perfusion studies performed for the evaluation of acute stroke in our institution and recorded the observation of low MTT in the region of ischemia, in comparison to final outcome. The study was performed with permission from institutional research ethics board. In whole brain CTP imaging using Toshiba Aquilion One 320 detector row scanner, the perfusion data is processed in the Vitrea fx 4D workstation and CBV, CBF, MTT and TTP perfusion color maps were generated using Tracer Delay Invariant Singular Value Decomposition (SVD+) post processing algorithm[5 on page, 6 on page ]. This is proprietary software and detail is not known, however this is similar to dsvd (delay corrected SVD) method described in the literature[7 on page ]. This is a method wherein the delay in contrast agent arrival is corrected by the amount of contrast agent delay between the AIF (Arterial Input) and brain tissue. The deconvolution of the AIF and the tissue time-density curve determines the (delay corrected) impulse residue function for the tissue volume in each pixel. The CBF map is determined as the maximum value of the impulse residue function. CBV was calculated as the ratio of the area under the curve of the tissue and a large vein and MTT is calculated using central volume principle (MTT=CBV/CBF)[2 on page ]. Therefore, very low cerebral perfusion in the region of infarct core can theoretically affect the indirect calculation of MTT, for example very low CBV can result in artifactual low MTT values in the infarct core (MTT=CBV/CBF). Methods and Materials We retrospectively reviewed the clinical and imaging data of 134 patients presenting with acute stroke in less than 6 hours from onset of symptoms over a period of 18 months. 22 patients with low MTT in the region of ischemia were further evaluated for comparison with final infarct volume. Page 2 of 21

3 Whole brain perfusion scans were acquired on Toshiba Aquilion One 320 detector row scanner using 40 ml of iodinated IV contrast. Total 19 dynamic whole brain volume acquisitions were obtained over 60 seconds. The images were post processed to generate standard CBV, CBF, MTT and TTP perfusion maps on Vitrea fx 4D brain perfusion analysis software. The color perfusion maps were evaluated for obvious perfusion deficit. Quantification of perfusion changes were performed by placing manual oval region of interest (ROI) in area of the abnormality. Control values were also recorded from contra lateral asymptomatic hemisphere. The obvious low MTT deficit on color map with difference of more than 2 seconds was recorded. The follow up CT or MRI scans were reviewed for acute infarcts in region of perfusion deficit, performed in hours. The sensitivity, specificity, positive and the negative predictive values were estimated for the sign of low MTT to see whether this would accurately predict the presence of infarct based upon the follow up imaging. Images for this section: Page 3 of 21

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5 Fig. 1: 83 year old female with sudden onset of left face/arm and leg weakness and slurred speech, history of atrial fibrillation. tpa was administered with no bleeding complications. There was significant improvement in the proximal motor function of the left arm. Axial non-contrast CT shows a faint area of loss of the gray-white matter differentiation in the right posterior frontal lobe. Fig. 2: CT angiogram demonstrates a cutoff in the ascending M2 segment (arrow) of the right middle cerebral artery in keeping with an acute thrombus. Page 5 of 21

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7 Fig. 3: Axial MTT map shows low central area in blue (arrow) with surrounding area of prolonged MTT. Page 7 of 21

8 Fig. 4: Axial TTP map shows area of prolonged TTP in red. Page 8 of 21

9 Fig. 5: Axial CBV map shows central area low CBV in blue. Fig. 6: Coronal MTT map shows low central area in blue (arrow) with surrounding area of prolonged MTT. Page 9 of 21

10 Fig. 7: Follow up axial CT image shows established subacute infarct that include the area of low MTT abnormality. Page 10 of 21

11 Results 134 patients were included in the study. 41 patients were excluded due to inadequate studies (n=14) and no follow up scans (n=27). 60 of remaining 93 patients had obvious abnormality on color perfusion maps. 43 patients had obvious abnormality on MTT perfusion maps. 22 of these 43 patients showed low MTT (color coded as blue on RGB scale) in the center of otherwise high MTT (red on RGB scale). Overall, MTT map has lower sensitivity (71%) for the detection of ischemia (confirmed by follow up imaging). The paradoxical low MTT sign has even lower sensitivity, seen only in 36% of cases. However, this has very high specificity and all 22 patients with low MTT developed infarct in the same region on follow up imaging. However, the final volumes of final infarct were approximately 20% bigger as compared to volume of low MTT abnormality. Images for this section: Page 11 of 21

12 Fig. 1: 65 year old right handed man presented to the emergency department with acute onset of left sided weakness in his face, arm and leg. He had history of triple CAGB 15 years ago and also atrial fibrillation. On admission NIH score was 18. He received intravenous tpa with some benefit. On follow up he has minimal movement on the left side and mostly moves his left side to withdraw from painful stimuli. He seems to have left sided neglect. Admission axial non-contrast CT shows changes of early infarction in right MCA territory. Page 12 of 21

13 Fig. 2: Axial CT angiogram demonstrates a cutoff in the distal M1 segment (arrow) of the right middle cerebral artery in keeping with an acute thrombus. Page 13 of 21

14 Fig. 3: Axial MTT map shows low central area in blue with surrounding area of prolonged MTT in red. Page 14 of 21

15 Fig. 4: Axial TTP map shows area of prolonged TTP in red. Page 15 of 21

16 Fig. 5: Axial CBV map shows low CBV central area in blue. Page 16 of 21

17 Fig. 6: Coronal MTT map shows low MTT central area in blue with surrounding area of prolonged MTT in red. Page 17 of 21

18 Fig. 7: Coronal TTP map shows area of prolonged TTP in red. Page 18 of 21

19 Fig. 8: Follow up axial CT image shows established subacute infarct that include the area of low MTT abnormality but also extended to more posterior part showing prolonged MTT. Page 19 of 21

20 Fig. 9: 3D volume rendered MTT map shows area of central low MTT in blue with surrounding prolonged MTT in red. Page 20 of 21

21 Conclusion The low MTT in the region of ischemia is an interesting perfusion artifact, which accurately predicts the established infarct. Therefore, it may be possible to predict the tissue at risk on a single perfusion map with low MTT showing infarct core and high MTT suggesting ischemic penumbra. References 1. Wintermark, M., et al., Perfusion-CT assessment of infarct core and penumbra: receiver operating characteristic curve analysis in 130 patients suspected of acute hemispheric stroke. Stroke, (4): p Meier, P. and K.L. Zierler, On the theory of the indicator-dilution method for measurement of blood flow and volume. J Appl Physiol, (12): p Konstas, A.A., et al., Theoretic basis and technical implementations of CT perfusion in acute ischemic stroke, part 1: Theoretic basis. AJNR Am J Neuroradiol, (4): p Mayer, T.E., et al., Dynamic CT perfusion imaging of acute stroke. AJNR Am J Neuroradiol, (8): p Wu, O., et al., Tracer arrival timing-insensitive technique for estimating flow in MR perfusion-weighted imaging using singular value decomposition with a block-circulant deconvolution matrix. Magn Reson Med, (1): p J. Wang, O.M., B. Frake, T. Naoko, O. Miwa;. Delay insensitive singular value decomposition algorithm for brain perfusion analysis using shifted artery curves and preconditioning techniques. in ECR Kudo, K., et al., Difference in tracer delay-induced effect among deconvolution algorithms in CT perfusion analysis: quantitative evaluation with digital phantoms. Radiology, (1): p Personal Information Page 21 of 21