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STIR – 1 Digital Phantom Project Kohsuke Kudo, Soren Christensen, Makoto Sasaki, and Leif Ostergaard.

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Presentation on theme: "STIR – 1 Digital Phantom Project Kohsuke Kudo, Soren Christensen, Makoto Sasaki, and Leif Ostergaard."— Presentation transcript:

1 STIR – 1 Digital Phantom Project Kohsuke Kudo, Soren Christensen, Makoto Sasaki, and Leif Ostergaard

2 Background A variety of post-processing programs and algorithms for CT perfusion and dynamic susceptibility contrast (DSC) MR perfusion are available from CT or MR manufacturers, third-party workstation vendors, and academic groups. However, the accuracy and reliability of these programs have not been subject to standardized quality control.

3 Purpose To design a digital phantom data set both for CT perfusion and DSC MR perfusion based on widely accepted tracer kinetic theory in which a range of true values of cerebral blood flow (CBF), cerebral blood volume (CBV), mean transit time (MTT), and tracer arrival delay are known. To evaluate the accuracy of post-processing programs using this digital phantom.

4 Methods – AIF/VOF Arterial input function (AIF) was generated using Gamma-variate function. Venous output function (VOF) was generated by deconvoluting AIF and Exponential R(t).

5 Methods – AIF/VOF Concentration time curves, C(t), were converted to signal time curves, S(t), for MR.

6 Methods – Tissue Curves Tissue curves were generated by deconvoluting AIF and R(t). Three kinds of R(t) were used, Exponential, Linear, and Box.

7 Methods – Tissue Curves Tissue curves were also converted to signal curves for MR.

8 Methods – Data Structure Slice #1 AIF/VOF Slice #2, 3 R(t) = Exp. CBV = 2, 4 % Slice #4, 5 R(t) = Linear CBV = 2, 4 % Slice #6, 7 R(t) = Box CBV = 2, 4 % The phantom data set had 7 slices and 50 phases (total 350 images). Curves for AIF/VOF were embedded in slice #1. Tissue curves were embedded in slice #2 to #7, with different R(t) and CBV.

9 Methods – AIF/VOF Image -3 -2 Delay (s) = 0 +1 +2 +3 AIFsVOF AIF without delay and VOF were used.

10 Methods – Tissue Images -3 -2 Delay (s) = 0 +1 +2 +3 MTT (s) =2412864.843.4 CBF (mL/100g/min)=5101520253035(CBV = 2%) 10203040506070(CBV = 4%)

11 Method – True Values R(t): Exponential, Linear, and Box Delay: -3, -2, -1, +0, +1, +2, and +3 sec CBV: 2 and 4% CBF: 5, 10, 15, 20, 25, 30, and 35 mL/100g/min 10, 20, 30, 40, 50, 60, and 70 mL/100g/min MTT:3.4, 4, 4.8, 6, 8, 12, and 24 sec

12 Methods – Evaluation CT Perfusion Commercial Software GE (CTP3, CTP4) Hitachi (IF) Philips (SVD) Siemens (LMS) Toshiba (bMTF, SVD+) Academic Software PMA (sSVD, bSVD) MR Perfusion Commercial Software GE (FM) Hitachi (FM) Philips (FM) Siemens (SVD) Academic Software EPITHET (SVD) Penguin (sSVD, oSVD) Rapid (sSVD, cSVD) PMA (sSVD, bSVD)

13 Methods - Evaluation Delay Sensitivity Visual Assessment Correlation coefficient with delay Accuracy Correlation coefficient with true value Significant Correlation = Delay Sensitive Higher Correlation = Accurate

14 Results PMA CBF sSVD Delay MTT/CBF

15 Results PMA CBF bSVD Delay MTT/CBF

16 Results – CTP Maps CBF CBV MTT GE CTP3 GE CTP4 Hitachi IF Philips SVD Siemens LLMS Toshiba bMTF Toshiba SVD+ PMA sSVD PMA bSVD

17 Results – MRP Maps CBF CBV MTT GE FM Hitachi FM Philips FM Siemens SVD PMA sSVD PMA bSVD Rapid sSVD Rapid cSVD Penguin sSVD Penguin oSVD Tmax PMA sSVD PMA bSVD Rapid sSVD Rapid cSVD Penguin sSVD Penguin oSVD EPITHET SVD

18 Results – Delay Dependency

19 Results - Accuracy

20 Results – CTP Significant correlation = Delay sensitive r < 0.9 Delay SensitivityAccuracy CBFCBVMTTCBFCBVMTT GE CTP3-0.1770.1040.321GE CTP30.9400.9740.907 GE CTP40.1880.4390.337GE CTP40.6990.6980.888 Hitachi0.0000.3160.404Hitachi0.8440.8980.885 Philips-0.4380.0110.376Philips0.7200.8670.828 Siemens Toshiba bMTF-0.4440.0270.455Toshiba bMTF0.3270.9850.851 Toshiba SVD+ PMA sSVD-0.3310.0000.341PMA sSVD0.8440.9580.880 PMA bSVD-0.0020.0000.016PMA bSVD0.9420.9580.965 Correlation Coefficient to DelayCorrelation Coefficient to True Value

21 Results – MRP r < 0.9 Significant correlation = Delay sensitive

22 Summary CT Perfusion Commercial Software GE(CTP3): accurate but delay sensitive GE(CTP4): sensitive to negative delay Hitachi(IF): CBV/MTT are delay sensitive Philips(SVD): delay sensitive Siemens(LMS): could not be analyzed Toshiba(bMTF): delay sensitive Toshiba(SVD+): could not be analyzed Academic Software PMA(sSVD): delay sensitive PMA(bSVD): delay insensitive and accurate

23 Summary MR Perfusion Commercial Software GE(FM): delay insensitive but not accurate Hitachi(FM) : delay insensitive but not accurate Philips(FM) : delay insensitive but not accurate Siemens(SVD) : delay sensitive Academic Software EPITHET(SVD): only Tmax Penguin(sSVD): delay sensitive Penguin(oSVD): delay insensitive Rapid(sSVD) : delay sensitive Rapid(cSVD) : delay insensitive and accurate PMA(sSVD) : delay sensitive PMA(bSVD) : delay insensitive and accurate

24 Newer Version of Phantom All the curves are embedded in “real” brain image, because some programs require anatomical configuration. AIF VOF Only “positive delays” are used, because negative delays are not realistic if we choose proper AIF. Five CBV values are embedded to see linearity of CBV. Noise was added stronger to resemble clinical data.

25 Preliminary Results for CT CBF CBV MTT GE CTP3 GE CTP4 Hitachi IF Philips SVD Siemens LLMS Toshiba bMTF Toshiba SVD+ PMA sSVD PMA bSVD

26 Conclusion The digital phantom can be used for the evaluation of accuracy and reliability of perfusion software packages, and also used for the certification and standardized quality control.

27 Thank you.


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