Comparison of coherence measures for assessment of impaired cerebral autoregulation D. De Smet*, J. Vanderhaegen**, G. Naulaers** and S. Van Huffel* KATHOLIEKE UNIVERSITEIT LEUVEN, BELGIUM *DEPARTMENT OF ELECTRICAL ENGINEERING (ESAT-SCD) **NEONATAL INTENSIVE CARE UNIT, UNIVERSITY HOSPITALS LEUVEN

Introduction Problem : defective cerebrovascular autoregulation Δ CBF brain injuries Premature infants : propensity for development because : Δ MABP frequent Δ MABP Δ CBF in some infants 1st mean to detect defective autoregulation : Δ MABP Δ CBF Acronyms : CBF : Cerebral Blood Flow MABP : Mean Arterial blood Pressure 1.Introduction 2.Datasets 3.Preprocessing 4.Sampling frequency 5.Welsh coherence 6.Critical score value 7.In the practice 8.Conclusion

Introduction But, if Δ SaO 2 = 0, then Δ HbD Δ CBF(hypothesis) 2nd mean to detect defective autoregulation : Δ MABP Δ HbD with Δ SaO 2 = 0 Acronyms : HbD : cerebral intravascular oxygenation (=HbO 2 -HbR) SaO 2 : arterial oxygen saturation Aim : allow correction with medication such that Δ CBF=0 Method: The coherence coefficient is a measure of the linear dependence between two signals in the frequency domain. 1.Introduction 2.Datasets 3.Preprocessing 4.Sampling frequency 5.Welsh coherence 6.Critical score value 7.In the practice 8.Conclusion

Datasets More than 50 premature infants with need for intensive care from the hospitals of Zürich, Utrecht, and Leuven. MABP, SaO 2, and the NIRS-measured HbD/rSO2/TOI measured simultaneously in the first days of life. Acronyms : MABP : mean arterial blood ressure HbD : cerebral intravascular oxygenatinon rSO2 : regional oxygen saturation TOI cerebral tissue oxygenation NIRS : near infrared spectroscopy SaO 2 : arterial oxygen saturation 1.Introduction 2.Datasets 3.Preprocessing 4.Sampling frequency 5.Welsh coherence 6.Critical score value 7.In the practice 8.Conclusion

Preprocessing Each artifact point was deleted (Soul et al. 2007) Step 1: keep signals within normal ranges

Preprocessing Step 2: remove artifacts in MABP

Preprocessing Step 3: remove artifacts in SaO2

Preprocessing Step 4: remove artifacts in HbD

Preprocessing Preprocessing makes the coherence growing (S. Van Huffel, iSOTT 08) Preprocessing has bad consequence on the frequency content of the signals

Sampling frequency Condition : sampling frequency (f s ) > signal fluctuation frequency Cyclical fluctuations in the case of continuously measured signals : CBV/HbTot : 2 to 4.7 cycles/min 1 and 3 to 6 cycles/min 2 (by NIRS) MABP : One cycle every 1 to 2.5 min 1 f s > 0.1Hz Acronyms : CBV : cerebral blood volume HbTot : total haemoglobin MABP : mean arterial blood pressure _____________________________________________________ [1] von Siebenthal et al., Brain & Development, [2] Urlesberger et al., Neuropediatrics, Introduction 2.Datasets 3.Preprocessing 4.Sampling frequency 5.Welsh coherence 6.Critical score value 7.In the practice 8.Conclusion

Step 1 : divide signal in epochs (C-windows). Divide each C- window in N segments (called H-windows as it is a highpass filtering) Welsh coherence Step 2 : (1) detrend, (2) apply Hanning windowing, and (3) compute the PSD/CSD for each H-window Acronyms : P xy (f) : crosspower spectral density (CSD) of x(t) and y(t) at a given frequency f P xx (f), P yy (f) : power spectral densities (PSD) of x(t), respectively y(t)

Step 3 : average the N modified H-windows Step 4 : keep frequency band of interest (f Cut : cutoff freq.) Welsh coherence Step 5 : compute average amplitude of spectrum in the frequency band of interest

REMARK 1 The FFT (fast Fourier transform) supposes the signals are periodical REMARK 2 A complete period of the signal should be contained in a each H-window REMARK 3 The higher the value of N, the lower the variance of the estimates of the spectra (SNR grows) Problem : if N is too large, then the amplitude of the spectra diminishes 1 N close to 8 2,3 _____________________________________________________ [1] De Smet., Unpublished, [2] Kay, Prentice Hall, 1988 (book). [3] Taylor, Circulation, Welsh coherence 1.Introduction 2.Datasets 3.Preprocessing 4.Sampling frequency 5.Welsh coherence 6.Critical score value 7.In the practice 8.Conclusion

REMARK 4 All parameters satisfy TH acts as a highpass filer The ratio TH/TC should be in the range of or smaller REMARK 5 The ratio THOver/TH should be equal to 0.5 if a Hanning window was applied to the H-windows prior to the periodogram average 2. _____________________________________________________ [1] De Smet., Unpublished, [2] Carter, IEEE Trans. on Audio and Electroacoustics, Welsh coherence 1.Introduction 2.Datasets 3.Preprocessing 4.Sampling frequency 5.Welsh coherence 6.Critical score value 7.In the practice 8.Conclusion

Consequence : TC= TH(N+1)/2 TH and TH/TC are the sole parameters we really can choose But … REMARK 6 TH have to satisfy : TH < TC TH > 10s 1,2 Acronyms : TC : duration of C-window (calculation window) TH : duration of H-window (highpass filtering window) N : number of averages in the Welsh method _____________________________________________________ [1] von Siebenthal et al., Brain & Development, [2] Urlesberger et al., Neuropediatrics, 1998 Welsh coherence 1.Introduction 2.Datasets 3.Preprocessing 4.Sampling frequency 5.Welsh coherence 6.Critical score value 7.In the practice 8.Conclusion

Critical Score Value The critical score value (CSV) is the value above which the amplitude of coherence witnesses a significant linear concordance between the input signals. Possible value for CSV are : CSV=0.5 1 or 2 Acronyms :  : significance level (e.g. 0.05) : to be chosen d : 2.83*TC/TH (for Hanning window) : TH to be chosen F : F hypothesis test The significance level  greatly influences the CSV, in the case that the remainder parameters are unchanged!! _____________________________________________________ [1] De Boer et al., Med. Biol. Eng. Comput., [2] Taylor et al., Circulation, Introduction 2.Datasets 3.Preprocessing 4.Sampling frequency 5.Welsh coherence 6.Critical score value 7.In the practice 8.Conclusion

Critical Score Value Problem : this formula doesn’t take into account THOver (and thus N) that also has an influence on the amplitude of the coherence spectrum 1 Solution : keep working with CSV=0.5 (two signals based on 50% shared variance), and calibrate 2 mean COH (on all infants) on mean correlation coefficient (COR) + look at the range of COH and COR. _____________________________________________________ [1, 2] De Smet., Unpublished 1.Introduction 2.Datasets 3.Preprocessing 4.Sampling frequency 5.Welsh coherence 6.Critical score value 7.In the practice 8.Conclusion

Morren 1 Soul 2 Wong 3 Optimization fsfs 6Hz (0.2Hz) 2Hz (O.4Hz) 1Hz>0.1Hz (von Siebenthal, Urlesberger) TC30min10min20minTH(N+1)/2 TCOver10min0min E.g. : TC/2 N21735close to 8 or calibr. TH12min5min10min> 2.5min (von Siebenthal) THOver11min55s2.5min7.5minTH/2 if Hanning (Carter) f Cut 0.01Hz0.04Hz0.02Hz<0.05Hz (von Siebenthal, Urlesberger, Nyq.) CSV (Taylor) with calibr. or Taylor’s CSV In the practice [1] Morren et al., Proc. of the Intern. Conf. of IEEE, [2] Soul et al., Pediatric Research, [3] Wong et al., Pediatrics, to be published. 1.Introduction 2.Datasets 3.Preprocessing 4.Sampling frequency 5.Welsh coherence 6.Critical score value 7.In the practice 8.Conclusion

Conclusion nice preprocessing but bad consequence on the frequency content of the signals the problem of the varying amplitude of COH is solved by another manner Taylor did it. We showed Taylor’s method does not account for the overlap between H- windows we proposed optimized parameters to apply the coherence method 1.Introduction 2.Datasets 3.Preprocessing 4.Sampling frequency 5.Welsh coherence 6.Critical score value 7.In the practice 8.Conclusion

Thanks to PhD grant Fin. Contributors Research Council KULeuven Flemish Government Belgian Federal Science Policy Office EU ESA Workgroup Prof. Dr. Ir. S. Van Huffel Prof Dr. G. Naulaers Lic. J. Vanderhaegen