Delay Correction for the Assessment of Blood-Brain Barrier Permeability Using First-Pass Dynamic Perfusion CT

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Fig 1.
A 75-year-old patient with a left MCA ischemic stroke. Prognostic PCT map shows a mixed pattern of infarct core (red) and penumbra (green).
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Fig 2.
Absolute permeability (milliliters per 100 g per minute) maps for the reference standard 90- to 240-second delayed acquisition and for the 0- to 90-second first-pass acquisition with delay correction, the 30- to 90-second first-pass acquisition with delay correction, and the 0- to 90-second first-pass acquisition without delay correction. BBBP values calculated from the delay-corrected 30- to 90-second first-pass acquisition overlapped with the ones calculated from the reference standard 90- to 240-second delayed acquisition in the ischemic parenchymal tissue and were slightly underestimated in the nonischemic parenchymal tissue. The delay-corrected first-pass did not show the overestimation of BBBP values in the penumbra that were seen with the first-pass acquisition without delay correction.

Table 1:

Study patient characteristics

Table 2:

Absolute permeability (mL/100 g/min) measurements^a

	90–240 Seconds	30–90 Seconds	0–90 Seconds	0–90 Seconds
	Reference Standard	Delay Correction	Delay Correction	No Delay Correction
Nonischemic	2.07 (1.83–2.34)	1.54 (1.39–1.71)	1.57 (1.24–2.00)	1.95 (1.74–2.18)
		P < .001	P = .002	P = .125
Infarct	2.48 (2.15–2.87)	2.09 (1.85–2.37)	1.66 (1.30–2.11)	2.49 (2.21–2.79)
		P = .074	P < .001	P = .874
Tissue at risk	2.43 (2.16–2.74)	2.45 (2.21–2.72)	1.93 (1.52–2.46)	3.49 (3.14–3.88)
		P = .921	P = .066	P < .001

a Mean absolute permeability values and corresponding 95% CIs shown for different regions-of-interest and acquisition-time datasets, as well as P values derived from the GEE models.

Table 3:

√MSE calculated for the fitting of the Patlak line^a

	90–240 Seconds	30–90 Seconds	0–90 Seconds	0–90 Seconds
	Reference Standard	Delay Correction	Delay Correction	No Delay Correction
Nonischemic	1.56 (1.36,1.79)	1.12 (0.97–1.30)	2.38 (1.74–3.26)	4.04 (3.04–5.36)
		P < .001	P = .002	P < .001
Infarct	1.79 (1.49, 2.15)	1.19 (1.02–1.39)	2.54 (1.85–3.49)	4.05 (3.03–5.38)
		P < .001	P = .026	P < .001
Tissue at risk	1.65 (1.45, 1.87)	1.14 (1.00–1.29)	2.86 (2.07–3.95)	4.25 (3.24–5.56)
		P< .001	P< .001	P< .001

a Mean √MSE and corresponding 95% CIs are shown for different region-of-interest and acquisition-time datasets, as well as P values derived from the GEE models. √MSE is a measure of variability of data points around a straight line: a value close to zero indicates a smaller spread of data points around the line, corresponding to a better fit.