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Selection of Arterial Input Function for Postprocessing of Cerebral CT Perfusion in Chronic Unilateral High-grade Stenosis or Occlusion of the Carotid or Middle Cerebral Artery

Rationale and Objectives

We evaluated the effect of the arterial input function (AIF) on computed tomography perfusion (CTP) in patients with unilateral high-grade stenosis or occlusion in the carotid artery or middle cerebral artery without acute stroke.

Materials and Methods

CTP datasets were retrospectively postprocessed using the same venous output function and different AIF selections: the second segment of the anterior cerebral artery (A2 AIF), the second segment of the middle cerebral artery (MCA) on the lesion side (affected M2 AIF), and M2 on the contralateral side (nonaffected M2 AIF). We measured CTP values in the region of interest (ROI) in the bilateral MCA territory and evaluated the lesion-to-contralateral ratios.

Results

The mean and standard deviations of cerebral blood flow (CBF) on the normal side were similar to previously reported data only when using “non-affected M2 AIF.” Selecting an “affected M2 AIF” overestimated the CBF and shortened the mean transit time (MTT) in normal and lesion areas. Selecting an “A2 AIF” may cause overestimation of CBF in the normal side in patients with nonaffected-side A1 hypoplasia or occlusion. The sensitivity of the CBF ratio or MTT ratio to detect these unilateral cerebrovascular diseases was 100% using “nonaffected M2 AIF for bilateral MCA ROIs” and 70% (CBF ratio) and 90% (MTT ratio) using “respective AIF.”

Conclusion

The use of “nonaffected AIF for the bilateral MCA ROIs” was found to be the best of these AIF-ROI combinations in patients with chronic unilateral carotid or M1 severe stenosis or occlusion.

Computed tomography perfusion (CTP) has been used successfully as a functional imaging technique for patients with cerebrovascular disease. It allows rapid qualitative and quantitative evaluation of cerebral perfusion by generating maps of parameters such as cerebral blood flow (CBF), cerebral blood volume (CBV), mean transit time (MTT), and time to peak (TTP). In CTP, the first passage of a bolus of contrast agent through brain tissue is monitored. Often, quantification of CBF and MTT requires measurement of the arterial input function (AIF) . One may obtain different quantitative results when different arteries are chosen for the AIF. The AIF is optimally selected in one unaffected vessel that is perpendicular to the acquisition plane, which may be one of the anterior cerebral arteries (ACAs) or the contralateral middle cerebral artery (MCA) . Wintermark et al found that AIF selection had no significant influence on MTT and CBF values in ischemic territories in patients with a hemispheric stroke of less than 48 hours’ duration and that the ACA is an appropriate AIF for CTP processing in patients with acute stroke. Kamath et al found that the CBF value obtained with each vascular territory’s own AIF (respective AIF) on CTP correlated best with positron emission tomography (PET) CBF in patients with chronic cervical carotid artery occlusion.

The aim of this study was to evaluate the effect of different AIFs in the postprocessing of perfusion in patients with chronic high-grade unilateral arterial stenosis or occlusion without acute infarction. In addition, we examined whether the ACA and respective AIF would be appropriate for the postprocessing of perfusion data in these patients.

Materials and methods

Patients

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Table 1

Patient Demographics

No. Age Sex Disease Characteristics Site of Proper AIF 1 40 F Right ICA occlusion Left M2 2 84 M Left CCA occlusion Right A2 3 55 F Right proximal M1 occlusion Left M2 4 74 M Right ICA occlusion Left M2 5 77 M Left ICA occlusion Right A2 6 46 M Left M1 occlusion Right M2 7 66 M Right ICA occlusion Left M2 8 94 M Right ICA occlusion Left M2 9 63 M Right ICA 95% stenosis Left M2 10 80 M Right ICA occlusion Left M2 11 69 F Left ICA occlusion Right M2 12 88 M Left ICA 95% stenosis Right M2 13 80 M Right ICA 90% stenosis Left M2 14 54 M Right ICA occlusion Left M2 15 88 M Left ICA 94% stenosis Right M2 16 61 M Left ICA occlusion, right M1 <50% stenosis Right A2 17 68 F Left ICA 95% stenosis Right M2 18 84 M Left CCA occlusion, right ICA <50% stenosis Right A2 19 46 F Left ICA occlusion Right M2 20 78 M Right ICA 95% stenosis Left M2

CCA, common carotid artery; ICA, internal carotid artery; M1, first segment of the middle cerebral artery.

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CTP Scanning Protocol

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Data Postprocessing

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Image Analysis

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Figure 1, Region of interest drawing on the high ventricular plane (the same case as Figure 3 ).

Figure 2, Region of interest drawing on the supraventricular plane (the same case as Figure 4 ).

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Statistical Analysis

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Results

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Table 2

Measured Perfusion Data Obtained Using Different AIFs and P Values

Parameter 1. A2 AIF 2. Nonaffected M2 AIF 3. Affected M2 AIF Mean ± SD (Min.-Max.) Mean ± SD (Min.-Max.) Mean ± SD (Min.-Max.) Lesion side CBV 4.10 ± 0.46 (3.26–5.15) 4.05 ± 0.59 (3.28–5.46)4.08 ± 0.62 (3.14–5.81) CBF 30.25 ± 5.78 (17.59–44.20) ∗ 29.85 ± 6.30 (18.78–44.55) ∗ 37.22 ± 9.18 (21.03–67.86) MTT 8.45 ± 2.15 (5.67–17.09) ∗ 8.72 ± 2.44 (5.41–17.18) ∗ 6.97 ± 2.18 (3.73–14.29) TTP 17.68 ± 2.44 (13.62–23.79) 17.36 ± 2.76 (12.72–23.65)17.31 ± 2.88 (10.72–24.36) Contralateral side (normal side) CBV 3.61 ± 0.40 (2.55–4.55)3.57 ± 0.43 (2.80–4.75) 3.63 ± 0.51 (2.63–4.77) CBF 46.35 ± 15.45 (23.39–104.40) ∗ 42.00 ± 6.45 (31.81–58.02) ∗ 68.54 ± 26.91 (35.76–152.26) MTT 4.94 ± 1.15 (4.65–6.82) ∗ 5.25 ± 0.72 (3.93–6.84) ∗ 3.52 ± 1.01 (1.03–5.41) TTP 14.75 ± 2.18 (10.64–18.51)14.50 ± 2.02 (10.86–18.48) 14.46 ± 2.04 (10.53–18.57)

Unit of CBF: mL/100 g/min; CBV: mL/100 g; MTT: second; TTP: second.

AIF, arterial input function; CBF, cerebral blood flow; CBV, cerebral blood volume; MTT, mean transit time; TTP, time to peak.

Data compatible with “respective AIF” are in bold.

All differences were significant at P < .05 by repeated-measures analysis of variance.

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Figure 3, Arterial input function (AIF) selection and the maps of cerebral blood volume (CBV), cerebral blood flow (CBF), mean transit time (MTT), and time to peak (TTP) on a high ventricular plane in a patient with occlusion of the right internal carotid artery, as confirmed with a digital subtraction angiogram. The left A1 was patent. Row 1, AIF selection; row 2, CBV maps; row 3, CBF maps; row 4, MTT maps; row 5, TTP maps; column 1, AIF selected at A2; column 2, AIF selected at right M2 (ie, affected M2 AIF); column 3, AIF selected at left M2 (ie, nonaffected M2 AIF). The CBV and TTP maps show no change in different columns; therefore, CBV and TTP are not affected by AIF selection. The first and third columns of the CBF and MTT maps are similar because the selected AIF in A2 (first column) and M2 (third column) are supplied from the nonaffected side. The CBF and MTT maps of the second column obtained with affected M2 AIF are clearly different from those of the first and third columns.

Figure 4, Arterial input function (AIF) selection and the maps of cerebral blood volume (CBV), cerebral blood flow (CBF), mean transit time (MTT), and time to peak (TTP) on a supraventricular plane in a patient with high-grade stenosis of the right internal carotid artery, as confirmed with a digital subtraction angiogram. The left A1 and the right posterior communicating artery were not patent. Row 1, AIF selection; row 2, CBV maps; row 3, CBF maps; row 4, MTT maps; row 5, TTP maps; column 1, AIF selected at A2; column 2, AIF selected at right M2 (ie, affected M2 AIF); column 3, AIF selected at left M2 (ie, nonaffected M2 AIF). The CBV maps and TTP maps show no change in different columns; therefore, CBV and TTP are not affected by AIF selection. The first and second columns of the CBF and MTT maps are similar because the selected AIF in A2 (first column) and M2 (second column) are supplied from the affected side. The CBF and MTT maps of the third column obtained with nonaffected M2 AIF are clearly different from those in the first and second columns.

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Figure 5, Scatter plot of cerebral blood flow (CBF) and the nonaffected M2 arterial input function (AIF) against A2 AIF. The CBF of the normal-side middle cerebral artery (MCA) region of interest (ROI) obtained with A2 AIF had more scattering than those obtained with nonaffected M2 AIF. CBFs obtained with affected A2 AIF in three normal-side ROIs are outliers and overestimated (>70 mL/100 g/minute). Angiography showed hypoplasia and nonpatent A1 on the contralateral normal side in these cases.

Figure 6, Bland-Altman difference plot. From this plot, the difference (CBF A2 AIF - CBF non-affected M2 AIF ) is larger when the average of CBF A2 AIF and CBF non-affected M2 AIF is larger. If one of these AIFs is correct, then the AIF causing the larger average and larger difference is incorrect. There are three regions of interest (ROIs) with larger average and larger differences in this plot, all caused by large CBF obtained with A2 AIF (CBF >70 mL/100 g/minute).

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Figure 7, Scatter-plot of cerebral blood flow (CBF) and nonaffected M2 arterial input function (AIF) against affected M2 AIF. The CBFs of the normal-side middle cerebral artery (MCA) region of interest (ROI) obtained with affected M2 AIF had more scattering than those obtained with nonaffected M2 AIF. CBFs in 13 normal-side ROIs were outliers and overestimated (>70 mL/100 g/minute) using affected M2 AIF.

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Table 3

Lesion-to-contralateral Ratios Obtained Using Different AIFs and P Values

Parameter 1. Respective AIF 2. Nonaffected M2 AIF 3. Affected M2 AIF Mean ± SD (Min.-Max.) Mean ± SD (Min.-Max.) Mean ± SD (Min.-Max.) CBV ratio 1.15 ± 0.12 (0.89–1.41) 1.14 ± 0.12 (0.89–1.40) 1.13 ± 0.13 (0.84–1.41) CBF ratio 0.90 ± 0.21 (0.50–1.33) ∗ 0.71 ± 0.11 (0.51–0.93) ∗ † 0.59 ± 0.18 (0.28–0.89) MTT ratio 1.37 ± 0.48 (0.82–3.41) ∗ 1.66 ± 0.34 (1.09–2.55) ∗ 2.15 ± 0.89 (1.00–4.42) TTP ratio 1.19 ± 0.11 (0.98–1.53) 1.20 ± 0.10 (1.04–1.48) 1.20 ± 0.11 (1.02–1.54)

AIF, arterial input function; CBF, cerebral blood flow; CBV, cerebral blood volume; MTT, mean transit time; TTP, time to peak.

All difference is significant at P < .05 by repeated-measures analysis of variance.

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Discussion

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