ADC based thermometry of the brain in children

Matthias W. Wagner 1, Steven E. Stern 2, Alexander Oshmyansky 1,2, Thierry A. G. M. Huisman 1, Andrea Poretti 1

1 Section of Pediatric Neuroradiology, Division of Pediatric Radiology, Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins

University School of Medicine, Baltimore, MD, USA ² School of Mathematical Sciences, Faculty of Science and Engineering, Queensland University of Technology, Brisbane,

QLD, Australia

EP-134

ASNR 53rd Annual Meeting, Chicago, April 25-30, 2015

Disclosure

We have nothing to disclose No relevant financial relations interfering

with the presentation

MRI ideal tool to measure brain temperature non-invasively

Techniques: 1. T1 and T2 relaxation times 2. ADC based3. Magnetization transfer4. Temperature-responsive water saturation shift

referencing 5. Proton resonance frequency

Brain temperature

Sakai, Sai, Tazoe et al: ↓ ventricular temperature with ↑ age ¹

↓ brain core temperature in mild traumatic brain injury ²

↓ brain core temperature in multiple sclerosis ³

↑ in ventricular temperature in moyamoya disease ⁴

Hasan et al: ↑ left ventricular temperature in multiple sclerosis ⁵

ADC based thermometry in adults

¹ Sakai K, Yamada K, Mori S, Sugimoto N, Nishimura T. NMR Biomed. 2011;24(9):1063-7.² Tazoe J, Yamada K, Sakai K, Akazawa K, Mineura K. Neuroradiology. 2014.³ Sai A, Shimono T, Sakai K, Takeda A, Shimada H, Tsukamoto T, et al. J Magn Reson Imaging. 2013.⁴ Yamada K, Sakai K, Akazawa K, Yuen S, Sugimoto N, Sasajima H, et al. Neuroreport. 2010;21(13):851-5.⁵ Hasan KM, Lincoln JA, Nelson FM, Wolinsky JS, Narayana PA. Magn Reson Imaging. 2014.

versus

1. Extraction¹ Semi-automated extraction

of ADC values of each voxel on Trace of Diffusion map

Region of Interest covering the lateral ventricles

Trace of diffusion map

ADC based thermometry: How to do?

¹ Sakai K, Yamada K, Sugimoto N. NMR Biomed. 2012;25(2):340-6.

2. Apply equations ¹,²,³ 3. “Mode method” ¹ Generation of a histogram

plotting the frequency of temperature over temperature

Mode point of 8th order polynomial curve fitted to histogram = representative to ADC based ventricular temperature

D = Diffusion constant (mm²/s)b = applied diffusion weighting value (s/mm²) S0 / S = voxel signal intensities of reference on DWI/DTI T = temperature (⁰C)

ADC based thermometry

¹ Sakai K, Yamada K, Sugimoto N. NMR Biomed. 2012;25(2):340-6. ² Kozak LR, Bango M, Szabo M, Rudas G, Vidnyanszky Z, Nagy Z. Acta Paediatr. 2010;99(2):237-43. ³ Mills R. The Journal of Physical Chemistry. 1973;77(5):685-8.

Purpose / Possible applications

To determine the feasibility of ADC based thermometry to assess intraventricular temperature in children

Monitoring of therapeutic hypothermia in:1. Neonatal hypoxic-ischemic injury 2. Cardiac arrest3. Global hypoxia after drowning 4. Traumatic brain injury

Inclusion criteria

A. Age at MRI < 18 years

B. Ventricles without non-physiological material (e.g. blood, pus, tumour tissue)

C. 8 age groups covering 0-18 years to account for age dependent change of ventricular size 0-1 year, 1-2 years, 2-4 years, 4-6 years, 6-8 years, 8-10 years, 10-14 years, 14-18 years

Methods: Validation

Calculated intraventricular temperature is correlated with estimated brain temperature based on temporal artery temperature measurement

Measurements before/after each MRI scan calculation of a mean temperature

Temporal artery temperature = body core temperature = brain temperature - 0.4 ⁰C

Estimated brain temperature = temporal artery temperature + 0.4 ⁰C

Methods

Statistical analysisDifference (ΔT) intraventricular temperature

(ADC based thermometry) brain temperature (temporal artery scan)

Spearman’s rank correlation coefficient calculated estimated brain temperature

Standard linear regression for the two temperature measurements

Results 1

Inclusion of 120 childrenCorrelation coefficient (r) of ADC based

temperatures + estimated brain temperatures = 0.1, r-squared (R²) = 0.01 1% of changes in estimated brain temperature attributable to changes in ADC based temperature

Standard linear regression: p = 0.28 no statistically significant relationship between the two temperature measurements

Wide range of ΔT calculated estimated intracranial temperature: - 5.80 ⁰C to +2.85 ⁰C

Results 2

Reasons for ↑ ΔT

1. Ventricular size: ↑ ventricular size with ↑ age

Children: ↓ number of ventricular voxels available to calculate intraventricular temperature

↑ proportion of voxels interfacing with adjacent gray/white matter ↑ partial volume effects in children with small ventricles ↑ impact on calculated temperature

↓ number of ventricular voxels ↓ exactness of calculated temperature

Reasons for ↑ ΔT

2. Choroid plexus: Impact of ependymal cells on diffusion measurement

Size of choroid plexus stable with ↑ age choroid plexus ↑ impact on temperature calculations in subjects with smaller ventricles

Our finding: ↓ ΔT in children with larger ventricles (>8000 voxels)

Absolute ΔT: 0 ⁰C - 2.6 ⁰C for ventricles >8000 voxels and 0 ⁰C - 5.8 ⁰C for <8000 voxels

Reasons for ↑ ΔT

Conclusion

ADC based thermometry = unreliable method to calculate the intracranial temperature in children

Most likely due to smaller lateral ventricles compared to adults