Skip to main content
Log in

Optimal strategy for measuring intraventricular temperature using acceleration motion compensation diffusion-weighted imaging

  • Published:
Radiological Physics and Technology Aims and scope Submit manuscript

Abstract

DWI thermometry is affected by CSF pulsation. To achieve more accurate determination of intraventricular temperature, we compared conventional DWI (c-DWI), acceleration motion compensation DWI (aMC-DWI), and motion compensation DWI (MC-DWI) when using two different b values (commonly used b value [1000 s/mm2] and theoretically optimized b value according to the diffusion coefficient of the CSF [400 s/mm2]). Eight healthy volunteers were scanned using a 3.0-T magnetic resonance (MR) system. The temperature map was created using the diffusion coefficient from DWI with b = 1000 and 400 s/mm2, respectively. The intraventricular temperatures in the lateral ventricles (LV) with less CSF pulsation, and the third ventricle (TV), which has more CSF pulsation, were compared between three techniques using the Friedman test. We measured the body temperature in the axilla to compare it with the intraventricular temperature. With b = 1000 s/mm2, the intraventricular temperatures in TV for c-DWI were significantly higher (43.12 ± 2.86 °C) than those for the aMC-DWI (37.68 ± 1.66 °C; P < 0.05), whereas those in LV were not significantly different (P = 0.093). With b = 400 s/mm2, the intraventricular temperatures in TV for c-DWI (75.07 ± 5.48 °C) were significantly higher than those for the aMC-DWI (38.63 ± 0.92 °C; P < 0.05), whereas those in LV were not significantly different (P = 0.093). aMC-DWI provided an intraventricular temperature that was close to or slightly higher than the body temperature in either condition. However, c-DWI- and MC-DWI-measured temperatures were higher than the body temperature, particularly in the TV. Thus, aMC-DWI can accurately determine the intraventricular temperature.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  1. Karaszewski B, Wardlaw JM, Marshall I, Cvoro V, Wartolowska K, Haga K, et al. Measurement of brain temperature with magnetic resonance spectroscopy in acute ischemic stroke. Ann Neurol. 2006;60:438–46.

    Article  Google Scholar 

  2. Hasan KM, Lincoln JA, Nelson FM, Wolinsky JS, Narayana PA. Lateral ventricular cerebrospinal fluid diffusivity as a potential neuroimaging marker of brain temperature in multiple sclerosis: a hypothesis and implications. Magn Reson Imaging. 2015;33:262–9.

    Article  Google Scholar 

  3. Rango M, Arighi A, Bonifati C, Bresolin N. Increased brain temperature in Parkinson’s disease. NeuroReport. 2012;23(3):129–33.

    Article  Google Scholar 

  4. Rumana CS, Gopinath SP, Uzura M, Valadka AB, Robertson CS. Brain temperature exceeds systemic temperature in head-injured patients. Crit Care Med. 1998;26:562–7.

    Article  CAS  Google Scholar 

  5. Cady EB, D’Souza PC, Penrice J, Lorek A. The estimation of local brain temperature by in vivo 1H magnetic resonance spectroscopy. Magn Reson Med. 1995;33:862–7.

    Article  CAS  Google Scholar 

  6. Cline HE, Hynynen K, Schneider E, Hardy CJ, Maier SE, Watkins RD, et al. Simultaneous magnetic resonance phase and magnitude temperature maps in muscle. Magn Reson Med. 1996;35:309–15.

    Article  CAS  Google Scholar 

  7. Parker DL. Applications of NMR imaging in hyperthermia: an evaluation of the potential for localized tissue heating and noninvasive temperature monitoring. IEEE Trans Biomed Eng. 1984;31:161–7.

    Article  CAS  Google Scholar 

  8. Delannoy J, Chen C-N, Turner R, Levin RL, Le Bihan D. Noninvasive temperature imaging using diffusion MRI. Magn Reson Med. 1991;19:333–9.

    Article  CAS  Google Scholar 

  9. Chenevert TL, Pipe JG. Effect of bulk tissue motion on quantitative perfusion and diffusion magnetic resonance imaging. Magn Reson Med. 1991;19:261–5.

    Article  CAS  Google Scholar 

  10. Mürtz P, Flacke S, Träber F, van den Brink JS, Gieseke J, Schild HH. Abdomen: diffusion-weighted MR imaging with pulse-triggered single-shot sequences. Radiology. 2002;224:258–64.

    Article  Google Scholar 

  11. Nasu K, Kuroki Y, Fujii H, Minami M. Hepatic pseudo-anisotropy: a specific artifact in hepatic diffusion-weighted images obtained with respiratory triggering. Magn Reson Mater Phys Biol Med. 2007;20:205–11.

    Article  Google Scholar 

  12. Kozak LR, Bango M, Szabo M, Rudas G, Vidnyanszky Z, Nagy Z. Using diffusion MRI for measuring the temperature of cerebrospinal fluid within the lateral ventricles. Acta Paediatr Int J Paediatr. 2010;99:237–43.

    CAS  Google Scholar 

  13. Yamada K, Sakai K, Akazawa K, Yuen S, Sugimoto N, Sasajima H, et al. Moyamoya patients exhibit higher brain temperatures than normal controls. NeuroReport. 2010;21:851–5.

    Article  Google Scholar 

  14. Sai A, Shimono T, Sakai K, Takeda A, Shimada H, Tsukamoto T, et al. Diffusion-weighted imaging thermometry in multiple sclerosis. J Magn Reson Imaging. 2014;40:649–54.

    Article  Google Scholar 

  15. Kuriyama N, Yamada K, Sakai K, Tokuda T, Akazawa K, Tomii Y, et al. Ventricular temperatures in idiopathic normal pressure hydrocephalus (iNPH) measured with DWI-based MR thermometry. Magn Reson Med Sci. 2015;14:305–12.

    Article  CAS  Google Scholar 

  16. Sumida K, Sato N, Ota M, Sakai K, Nippashi Y, Sone D, et al. Intraventricular cerebrospinal fluid temperature analysis using MR diffusion-weighted imaging thermometry in Parkinson’s disease patients, multiple system atrophy patients, and healthy subjects. Brain Behav. 2015;5:1–9.

    Article  Google Scholar 

  17. Maki JH, Macfall JR, Johnson GA. The use of gradient flow compensation to separate diffusion and microcirculatory flow in MRI. Magn Reson Med. 1991;17:95–107.

    Article  CAS  Google Scholar 

  18. Ozaki M, Inoue Y, Miyati T, Hata H, Mizukami S, Komi S, et al. Motion artifact reduction of diffusion-weighted MRI of the liver: use of velocity-compensated diffusion gradients combined with tetrahedral gradients. J Magn Reson Imaging. 2013;37:172–8.

    Article  Google Scholar 

  19. Welsh CL, DiBella EVR, Hsu EW. Higher-order motion-compensation for in vivo cardiac diffusion tensor imaging in rats. IEEE Trans Med Imaging. 2015;34:1843–53.

    Article  Google Scholar 

  20. Saritas EU, Lee JH, Nishimura DG. SNR dependence of optimal parameters for apparent diffusion coefficient measurements. IEEE Trans Med Imaging. 2011;30:424–37.

    Article  Google Scholar 

  21. Pattany PM, Phillips JJ, Chiu LC, Lipcamon JD, Duerk JL, McNally JM, et al. Motion artifact suppression technique (MAST) for MR imaging. J Comput Assist Tomogr. 1987;11:369–77.

    Article  CAS  Google Scholar 

  22. Tofts PS, Jackson JS, Tozer DJ, Cercignani M, Keir G, MacManus DG, et al. Imaging cadavers: cold FLAIR and noninvasive brain thermometry using CSF diffusion. Magn Reson Med. 2008;59:190–5.

    Article  Google Scholar 

  23. Miyati T, Mase M, Kasai H, Hara M, Yamada K, Shibamoto Y, et al. Noninvasive MRI assessment of intracranial compliance in idiopathic normal pressure hydrocephalus. J Magn Reson Imaging. 2007;26:274–8.

    Article  Google Scholar 

  24. Bloomfield IG, Johnston IH, Bilston LE. Effects of proteins, blood cells and glucose on the viscosity of cerebrospinal fluid. Pediatr Neurosurg. 1998;28:246–51.

    Article  CAS  Google Scholar 

  25. Covaciu L, Rubertsson S, Ortiz-Nieto F, Ahlström H, Weis J. Human brain MR spectroscopy thermometry using metabolite aqueous-solution calibrations. J Magn Reson Imaging. 2010;31:807–14.

    Article  Google Scholar 

  26. Matsumae M, Hirayama A, Atsumi H, Yatsushiro S, Kuroda K. Velocity and pressure gradients of cerebrospinal fluid assessed with magnetic resonance imaging. J Neurosurg. 2014;120:218–27.

    Article  Google Scholar 

  27. Takizawa K, Matsumae M, Hayashi N, Hirayama A, Sano F, Yatsushiro S, et al. The choroid plexus of the lateral ventricle as the origin of CSF pulsation is questionable. Neurol Med Chir (Tokyo). 2018;58:23–31.

    Article  Google Scholar 

  28. Sund-Levander M, Forsberg C, Wahren LK. Normal oral, rectal, tympanic and axillary body temperature in adult men and women: a systematic literature review. Scand J Caring Sci. 2002;16:122–8.

    Article  Google Scholar 

  29. Mellergård P. Intracerebral temperature in neurosurgical patients: Intracerebral temperature gradients and relationships to consciousness level. Surg Neurol. 1995;43:91–5.

    Article  Google Scholar 

  30. Childs C, Hiltunen Y, Vidyasagar R, Kauppinen RA. Determination of regional brain temperature using proton magnetic resonance spectroscopy to assess brain-body temperature differences in healthy human subjects. Magn Reson Med. 2007;57:59–66.

    Article  CAS  Google Scholar 

  31. Surer E, Rossi C, Becker AS, Finkenstaedt T, Wurnig MC, Valavanis A, et al. Cardiac-gated intravoxel incoherent motion diffusion-weighted magnetic resonance imaging for the investigation of intracranial cerebrospinal fluid dynamics in the lateral ventricle: a feasibility study. Neuroradiology. 2018;60:413–9.

    Article  Google Scholar 

  32. Becker AS, Boss A, Klarhoefer M, Finkenstaedt T, Wurnig MC, Rossi C. NeuroImage investigation of the pulsatility of cerebrospinal fl uid using cardiac-gated intravoxel incoherent motion imaging. Neuroimage. 2018;169:126–33.

    Article  Google Scholar 

  33. Yildiz S, Thyagaraj S, Jin N, Zhong X, Heidari Pahlavian S, Martin BA, et al. Quantifying the influence of respiration and cardiac pulsations on cerebrospinal fluid dynamics using real-time phase-contrast MRI. J Magn Reson Imaging. 2017;46:431–9.

    Article  Google Scholar 

  34. Sakai K, Yamada K, Sugimoto N. Calculation methods for ventricular diffusion-weighted imaging thermometry: phantom and volunteer studies. NMR Biomed. 2012;25:340–6.

    Article  Google Scholar 

  35. Ota M, Sato N, Sakai K, Okazaki M, Maikusa N, Hattori K, et al. Altered coupling of regional cerebral blood flow and brain temperature in schizophrenia compared with bipolar disorder and healthy subjects. J Cereb Blood Flow Metab. 2014;34:1868–72.

    Article  Google Scholar 

  36. Hasan KM, Moeller FG, Narayana PA. DTI-based segmentation and quantification of human brain lateral ventricular CSF volumetry and mean diffusivity: validation, age, gender effects and biophysical implications. Magn Reson Imaging. 2014;32:405–12.

    Article  Google Scholar 

  37. Tazoe J, Yamada K, Sakai K, Akazawa K, Mineura K. Brain core temperature of patients with mild traumatic brain injury as assessed by DWI-thermometry. Neuroradiology. 2014;56:809–15.

    Article  Google Scholar 

  38. Stadlbauer A, Salomonowitz E, van der Riet W, Buchfelder M, Ganslandt O. Insight into the patterns of cerebrospinal fluid flow in the human ventricular system using MR velocity mapping. Neuroimage. 2010;51:42–52.

    Article  Google Scholar 

Download references

Acknowledgements

This work was supported in part by the JSPS KAKENHI (Grant-in-Aid for Encouragement of Scientists, 19H00436).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Tosiaki Miyati.

Ethics declarations

Conflict of interest

One of the authors (T. Ogino) is an employee of Philips Japan. The other authors declare that they have no conflicts of interest.

Statement of human rights

All procedures performed in studies involving human participants were in accordance with the ethical standards of the Institutional Review Board (IRB) and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed consent

Informed consent was obtained from each participant included in this study.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Shibukawa, S., Niwa, T., Ohno, N. et al. Optimal strategy for measuring intraventricular temperature using acceleration motion compensation diffusion-weighted imaging. Radiol Phys Technol 13, 136–143 (2020). https://doi.org/10.1007/s12194-020-00560-9

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12194-020-00560-9

Keywords

Navigation