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Volume 18 Supplement 1

19th Annual SCMR Scientific Sessions

  • Workshop presentation
  • Open Access

Venous oxygen saturation estimation from multiple T2 maps with varying inter-echo spacing

  • 1, 2,
  • 3,
  • 4,
  • 3 and
  • 5, 6
Journal of Cardiovascular Magnetic Resonance201618 (Suppl 1) :W29

  • Published:


  • Congenital Heart Disease
  • Pulse Oximeter
  • Nuisance Parameter
  • Heart Disease Patient
  • Congenital Heart Disease Patient


Dependence of blood T2 on O2 saturation has led to non-invasive MRI-based techniques for determining venous O2 saturation (SvO2) [1-3]. However, applying a general calibration factor derived from in vitro experiments can lead to inaccurate and largely varying SvO2 estimates in the target population. We aim to show that based on the Luz-Meiboom relation 1/T2 = 1/T2o + Hct(1-Hct) τex[(1-%SO2/100)αω0]2(1-2*τex180 tanh(τ180/2*τex))[4], individual SvO2 can be determined from multiple T2 maps, each acquired at a specific inter-echo spacing (τ180).


Three T2 prepared SSFP quantitative T2 maps (τ180=10, 12 and 15 ms, TR >3000 ms, FA = 400, 2.8 × 2.8 × 10 mm3, 2NEX, free breathing) were acquired in seven volunteers (age: 32.6 ± 12.2 yrs) on a 3T MRI system (Tim Trio, Siemens Healthcare). T2 preparation involved an MLEV refocusing pulse train with 2, 4, 8 and 12 composite pulses. Venous and arterial blood T2 were measured in each map in an ROI in the ventricles. For each subject, the multiple τ180 measurements were processed jointly to estimate SvO2 along with other nuisance parameters (T2o and τex) via constrained nonlinear least squares fitting in Matlab (The Mathworks Inc, Natick, MA, USA). The values of hematocrit (Hct), arterial O2 saturation (SaO2), and α were fixed at 41%, 97%, and 0.4 ppm respectively.


Figure 1 shows T2 maps acquired in a volunteer. Table 1 shows mean ± SD of venous and arterial T2 and estimated parameters. Venous and arterial blood T2 agree with previously reported values at 3T [2,3]. Estimated SvO2 for all volunteers falls within the normal physiological range (60-80%).
Figure 1
Figure 1

T2 prepared SSFP quantitative T2 maps (four-chamber view) acquired in a volunteer at different τ 180 (10, 12 and 15 ms).

Table 1

τ180 (ms)

TET2p (ms)

Venous T2 (ms)

Arterial T2 (ms)

Estimated Parameters



125.7 ± 11.7

169.4 ± 12.8

SvO2: 72.6 ± 5.1% T2o: 168.6 ± 12.8 ms τex: 5.4 ± 3.5 ms



122.2 ± 9.8

176.4 ± 22.6




110.6 ± 13.2

161.2 ± 16.7


The T2 preparation times (TET2p) at which T2 maps were acquired for a specific τ180, the mean ± SD of venous and arterial T2 values measured in an ROI in the right and left ventricles in all volunteers, and mean ± SD of the parameters estimated from the maps.


The measured T2 of blood is dependent on Hct, O2 saturation, and τ180. We have shown that if these parameters are known, SvO2 can be non-invasively determined from arterial and venous blood T2 maps acquired at multiple τ180. This provides in-vivo, patient-specific calibration, and may reduce the uncertainty and error in SvO2 estimation from applying a general calibration factor to the entire patient population. Although in this preliminary study we have assumed a fixed Hct and SaO2 for all subjects, greater accuracy may be achieved by measuring individual Hct and SaO2 from a blood sample and a pulse oximeter respectively. Nevertheless, our results show that the proposed approach is feasible, giving reasonable SvO2 estimates. Future studies will involve validation of the single assumed parameter, α, in the T2-SO2 model, optimization of the set of τ180 times, and further evaluation of the accuracy and precision of T2 mapping in determining blood O2 saturation. This would lead to the development of rapid, accurate, non-invasive, in-vivo quantification of SvO2 from T2 maps, which would be highly beneficial for heart failure and congenital heart disease patients.

Authors’ Affiliations

Department of Biomedical Engineering, The Ohio State University, Columbus, OH, USA
Dorothy M. Davis Heart and Lung Research Institute, The Ohio State University Wexner Medical Center, Columbus, OH, USA
Department of Electrical and Computer Engineering, The Ohio State University, Columbus, OH, USA
Siemens Healthcare, Columbus, OH, USA
Division of Cardiovascular Medicine, Department of Internal Medicine, The Ohio State University Wexner Medical Center, Columbus, OH, USA
Department of Radiology, The Ohio State University Wexner Medical Center, Columbus, OH, USA


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  3. Qin Q, et al: MRM. 2011, 65 (2): 471-479.PubMed CentralView ArticlePubMedGoogle Scholar
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© Varghese et al. 2016

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver ( applies to the data made available in this article, unless otherwise stated.