1. ADC based thermometry of the brain in children
EP-134
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
ASNR 53rd Annual Meeting, Chicago, April 25-30, 2015

2. Disclosure We have nothing to disclose
No relevant financial relations interfering with the presentation

3. Brain temperature
MRI  ideal tool to measure brain temperature non-invasively
Techniques:
T1 and T2 relaxation times
ADC based
Magnetization transfer
Temperature-responsive water saturation shift referencing
Proton resonance frequency

4. ADC based thermometry in adults
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
versus
¹ Sakai K, Yamada K, Mori S, Sugimoto N, Nishimura T. NMR Biomed. 2011;24(9):
² Tazoe J, Yamada K, Sakai K, Akazawa K, Mineura K. Neuroradiology
³ Sai A, Shimono T, Sakai K, Takeda A, Shimada H, Tsukamoto T, et al. J Magn Reson Imaging
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

5. ADC based thermometry: How to do?
Extraction¹
Trace of diffusion map
Semi-automated extraction of ADC values of each voxel on Trace of Diffusion map
Region of Interest covering the lateral ventricles
¹ Sakai K, Yamada K, Sugimoto N. NMR Biomed. 2012;25(2):340-6.

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

7. Purpose / Possible applications
To determine the feasibility of ADC based thermometry to assess intraventricular temperature in children
Monitoring of therapeutic hypothermia in:
Neonatal hypoxic-ischemic injury
Cardiac arrest
Global hypoxia after drowning
Traumatic brain injury

8. Inclusion criteria Age at MRI < 18 years
Ventricles without non-physiological material (e.g. blood, pus, tumour tissue)
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, years, years, years

9. 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 ⁰C
Estimated brain temperature = temporal artery temperature ⁰C

10. Methods Statistical analysis
Difference (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

11. Results 1 Inclusion of 120 children
Correlation 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

12. Results 2
Wide range of ΔT calculated  estimated intracranial temperature: ⁰C to ⁰C

13. Reasons for ↑ ΔT 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

14. Reasons for ↑ ΔT 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)

15. Reasons for ↑ ΔT
Absolute ΔT: 0 ⁰C ⁰C for ventricles >8000 voxels and 0 ⁰C ⁰C for <8000 voxels

16. Conclusion
ADC based thermometry = unreliable method to calculate the intracranial temperature in children
Most likely due to smaller lateral ventricles compared to adults