Scientific Paper

Keywords: Computed tomography, Perfusion imaging, Myocardium, Tracer kinetic models

Intermodel disagreement of myocardial blood flow estimation from dynamic T CT perfusion imaging

Purpose of the study:

To assess the intermodel agreement of different tracer kinetic models to determine myocardial blood flow (MBF) and their diagnostic accuracy in coronary artery disease (CAD) at dynamic CT myocardial perfusion imaging (CTMPI).

Introduction

Dynamic CT myocardial perfusion imaging (CTMPI) for the evaluation of coronary artery disease (CAD) has gained interest due to technical improvements in both the hard- and software components of CT instruments. 
In comparison to other imaging modalities, CTMPI offers several advantages, the most important of which being the ability to quantify myocardial blood flow (MBF).

By using CTMPI in tandem with CT angiography (CTA), the morphological and functional characteristics of CAD can be evaluated within a single imaging modality.

Quantitative analysis of perfusion data reduces subjectivity and increases the accuracy of dynamic CTMPI analysis. MBF can be quantified with CTMPI using a deconvolution method with a tracer kinetic model. 

The multitude of tracer kinetic models that exist describe slightly different physiological processes with varying grades of complexity. The tracer kinetic models specifically used for the quantification of MBF based on dynamic CTMPI data are directly translated from MRI perfusion studies. As expected, the wide range of models that are used in MR and CT studies result in different thresholds and MBF values.

Reliable diagnosis of CAD, global ischemia, or even subclinical perfusion disturbances requires accurate MBF values in order to determine optimal thresholds. 

Ex-vivo Porcine Heart Model - LifeTec group PhysioHeart Platform
"there is no study comparing the different tracer kinetic models..."

To the best of our knowledge, there is no study comparing the different tracer kinetic models of dynamic CT myocardial perfusion in a clinical setting.

Further information regarding the accuracy of CT-derived quantitative myocardial perfusion measures is needed to determine the optimal quantification method for clinical practice. In addition, we took advantage of an ex-vivo porcine heart model to control flow parameters and to compare calculated values to true MBF values. 

Therefore, the aim of our study was to assess the intermodel agreement of different tracer kinetic models in determining myocardial blood flow (MBF) and evaluate their ability to determine hemodynamically significant CAD at dynamic CTMPI. 

Abstract:

Purpose: To assess the intermodel agreement of different tracer kinetic models to determine myocardial blood flow (MBF) and their diagnostic accuracy in coronary artery disease (CAD) at dynamic CT myocardial perfusion imaging (CTMPI). 

Methods: Three porcine hearts perfused in Langendorff mode and 15 patients with suspected CAD and perfusion single photon emission CT (SPECT) were included. 

Dynamic CTMPI was performed in shuttle-mode (70 kVp, 350mAs/rot) on 3rd generation dual-source CT. In porcine hearts and patients, myocardial segments (AHA-16- segment model) were drawn. Tissue attenuation curves were constructed per segment and arterial input functions were derived from the aorta. True MBF was calculated with input flow and weight of the porcine hearts. In patients, ischemic segments were based on SPECT results. MBF quantification was performed using the VPCT- software, Upslope, Extended Toft (ET), Two-compartment (TC) and Fermi models.

Patients

The study included a total of 15 patients (median age, 69 years), 3 of whom were male. Of these patients, 8 were without ischemia and 7 patients had at least one ischemic segment according to SPECT. Fig. 2 shows an example of CTMPI studies of two patients, one with ischemia and one without ischemia. 

None of the patients showed any sign of myocardial infarction based on analysis of the rest and stress SPECT images. Median radiation dose of the CTMPI acquisition was 3.44 mSv (IQR: 2.55–4.83). Patient characteristics are presented in Table 3. A total of 240 myocardial segments in stress acquisitions were analyzed. Of those 240 segments, 34 were considered ischemic based on SPECT image analysis.

  • Fig. 2 On the left the midventricular slice of a patient without ischemia, where the AIF (red) and the TAC (yellow) are presented. On the right, the midventricular slice of a patient with confirmed ischemia according to the SPECT acquisition in the mid-septal and mid-inferior segments. From this patient, the AIF curve is represented (red) along with two TAC, one from the non-ischemic mid-lateral regions (yellow) and one from the ischemic region (green). The ischemic TAC is clearly lower
    Fig. 2 On the left the midventricular slice of a patient without ischemia, where the AIF (red) and the TAC (yellow) are presented. On the right, the midventricular slice of a patient with confirmed ischemia according to the SPECT acquisition in the mid-septal and mid-inferior segments. From this patient, the AIF curve is represented (red) along with two TAC, one from the non-ischemic mid-lateral regions (yellow) and one from the ischemic region (green). The ischemic TAC is clearly lower
    Fig. 2 On the left the midventricular slice of a patient without ischemia, where the AIF (red) and the TAC (yellow) are presented. On the right, the midventricular slice of a patient with confirmed ischemia according to the SPECT acquisition in the mid-septal and mid-inferior segments. From this patient, the AIF curve is represented (red) along with two TAC, one from the non-ischemic mid-lateral regions (yellow) and one from the ischemic region (green). The ischemic TAC is clearly lower
  • Table 5
    Table 5
    Table 5
  • Table 3
    Table 3
    Table 3
  • Fig. 3 The ROC curves are depicted for the VPCT software, the upslope, Fermi, Extended Toft (ET) and Two Compartment (TC) model.
    Fig. 3 The ROC curves are depicted for the VPCT software, the upslope, Fermi, Extended Toft (ET) and Two Compartment (TC) model.
    Fig. 3 The ROC curves are depicted for the VPCT software, the upslope, Fermi, Extended Toft (ET) and Two Compartment (TC) model.

Results:

(for the results please download the journal publication below)

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Authors:

Marly van Assen | Gert Jan Pelgrim | Carlo N. De Cecco | Marco A. Stijnen | Beatrice M. Zaki | Matthijs Oudkerk | Rozemarijn Vliegenthart | U. Joseph Schoepf  

  • Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, 25 Courtenay Drive, Charleston, SC, USA 
  • Center for Medical Imaging, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
  • LifeTec Group, Eindhoven, the Netherlands
  • Division of Cardiothoracic Imaging, Nuclear Medicine and Molecular Imaging, Department of Radiology and Imaging Sciences, Emory University Hospital, Atlanta, GA, USA 

Publisher:

Elsevier - European Journal of Radiology [link to paper]

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