Analysis of PET studies

Transcript Analysis of PET studies

Analysis of PET studies

Calculation of parametric images Turku PET Centre 2003-09-22 Vesa Oikonen

Dynamic PET image

• GE Advance: 35 image planes • 128x128 pixels / plane • N time frames: e.g. 0-30 s, 30-60 s, 60-120 s, 120-180 s, 180-300 s, ...

• Pixel value = radioactivity concentration (kBq/mL) during time frame

Parametric image

• Time frame information combined to one parametric image • Pixel value = Physiological measure – Examples: Perfusion (mL blood)/(min x mL tissue) Glucose uptake rate (µmol glucose) / (min x mL tissue) Binding potential (B’ max /K d )

Alternative analysis paths

SPM Parametric image Dynamic image Regional curves Regional results

Advantages of parametric image:

• Effects are easy to see • ROI definition is better • Parametric image can be used in SPM

Disadvantages of parametric image:

• Calculation in ”black box” • Distribution of regional pixel values is often skewed • Results can be biased

How to calculate parametic images:

http://pet.utu.fi/staff/vesoik/ •Program downloads •Documentation •Frequently Asked Questions

SUV and FUR

• Standardized Uptake Value = SUV • ROI divided by patient weight • no blood sampling required • simple value for assessing cumulated radioactivity • Fractional Uptake Rate = FUR • ROI corrected for plasma AUC (area under curve) • blood samples necessary

SUV image: demonstration

1. Check time frames 2. Sum selected frames, or extract one (last) frame 3. Use calculator to determine injected dose / body weight or BSA 4. Divide sum image by this result F:\demo>dir *.img

Volume in drive F is PET Volume Serial Number is EC0C-22C8 Directory of F:\demo 2003-09-11 23:03 19,812,352 ua1015dy1.img

1 File(s) 19,812,352 bytes 0 Dir(s) 4,168,876,032 bytes free F:\demo>ctiframe ua1015dy1.img

Frame Start End Dur (sec) Start End Dur (min) 1 0 30 30 0.00 0.50 0.50

2 30 60 30 0.50 1.00 0.50

3 60 90 30 1.00 1.50 0.50

4 90 120 30 1.50 2.00 0.50

5 120 180 60 2.00 3.00 1.00

6 180 240 60 3.00 4.00 1.00

7 240 300 60 4.00 5.00 1.00

8 300 600 300 5.00 10.00 5.00

9 600 900 300 10.00 15.00 5.00

10 900 1200 300 15.00 20.00 5.00

11 1200 1500 300 20.00 25.00 5.00

12 1500 1800 300 25.00 30.00 5.00

13 1800 2100 300 30.00 35.00 5.00

14 2100 2400 300 35.00 40.00 5.00

15 2400 2700 300 40.00 45.00 5.00

16 2700 3000 300 45.00 50.00 5.00

17 3000 3300 300 50.00 55.00 5.00

F:\demo>ctisum ua1015dy1.img 13 17 ua1015sum.img

....................................done.

F:\demo>ecatcalc ua1015sum.img : 14.2 ua1015suv.img

F:\demo>

FUR image: demonstration

1. Check time frames 2. Sum last frames or extract last frame 3. Calculate plasma AUC from 0 to mid PET time 4. Divide sum image by plasma AUC F:\demo>ctiframe ua1015dy1.img

Frame Start End Dur (sec) Start End Dur (min) 1 0 30 30 0.00 0.50 0.50

2 30 60 30 0.50 1.00 0.50

3 60 90 30 1.00 1.50 0.50

4 90 120 30 1.50 2.00 0.50

5 120 180 60 2.00 3.00 1.00

6 180 240 60 3.00 4.00 1.00

7 240 300 60 4.00 5.00 1.00

8 300 600 300 5.00 10.00 5.00

9 600 900 300 10.00 15.00 5.00

10 900 1200 300 15.00 20.00 5.00

11 1200 1500 300 20.00 25.00 5.00

12 1500 1800 300 25.00 30.00 5.00

13 1800 2100 300 30.00 35.00 5.00

14 2100 2400 300 35.00 40.00 5.00

15 2400 2700 300 40.00 45.00 5.00

16 2700 3000 300 45.00 50.00 5.00

17 3000 3300 300 50.00 55.00 5.00

F:\demo>ctisplit ua1015dy1.img 17 1-35 ua1015last.img

F:\demo>interpol -a -i -x52.5 ua1015vp.kbq

F:\demo>ecatcalc ua1015last.img : 714.4 ua1015fur.img

Net uptake rate K

• Measure of irreversible uptake • Unit (ml plasma)/(min x ml tissue) Calculated using two methods: 1. Graphical analysis (Gjedde-Patlak plot) 2. Compartmental model fit

Glucose uptake image: demonstration

1. Calculate K 2. Calculate correction factor i image 100

   

Plasma Tissue glu

cos

density

mM ml

  F:\demo>imgki ua1015vp.kbq ua1015dy1.img 10 ua1015ki.img

reading dynamic image ua1015dy1.img

computing MTGA pixel-by-pixel ...................................done.

Ki image ua1015ki.img saved.

F:\demo>ecatcalc ua1015ki.img x 924.6 ua1015gur.img

F:\demo>ecat2tif ua1015gur.img ua1015gur_20.tif 20 1 reading ua1015gur.img

writing file ua1015gur_20.tif

maximum pixel value in matrix is 50.2228, unit unknown F:\demo> 3. Multiply K i this factor image by 4. View image to check success Unit: (µmol glucose)/ (min x 100g tissue)

K

image from compartmental model fit: demonstration 1(2)

1. Calculate K 2. View image to check success i image 3. Calculate regional K i average and SD values 4. Calculate structural averages over image planes 5. List the regional results on screen F:\demo>imglhki ua1015vp.kbq ua1015dy1.img ua1015ki.img

reading dynamic image ua1015dy1.img

computing NNLS pixel-by-pixel ...................................done.

parametric image ua1015ki.img saved.

F:\demo>ecat2tif ua1015ki.img ua1015ki_20.tif 20 1 reading ua1015ki.img

writing file ua1015ki_20.tif

maximum pixel value in matrix is 0.0531314, unit unknown F:\demo> Unit: (ml plasma)/ (min x ml tissue)

K

image from compartmental model fit: demonstration 2(2)

F:\demo>img2dft ua1015ki.img ua1015*.roi -Vsd calculated sfro dx Pl006 calculated sfro sin Pl006 … calculated cer sin Pl025 290 regional TACs written in ua1015ki.dft

Variance data written in ua1015ki.sd

… 290 TAC(s) are deleted; backup is in ua1015ki.dft% F:\demo>dftlist ua1015ki.dft

1: sfro dx All 1.791e+04 2.861e-02 2: sfro sin All 1.795e+04 2.795e-02 3: rwmdx All 4.552e+03 2.249e-02 4: rwmsin All 4.599e+03 2.017e-02 5: par dx All 5.463e+03 2.717e-02 6: par sin All 5.510e+03 2.771e-02 7: mfro sin All 1.688e+04 3.156e-02 8: mfro dx All 1.702e+04 3.130e-02 9: ifro dx All 1.142e+04 2.969e-02 10: ifro sin All 1.184e+04 2.967e-02 11: occ dx All 1.032e+04 2.633e-02 12: occ sin All 1.079e+04 2.747e-02 13: stem sin All 1.167e+04 2.816e-02 14: stem dx All 1.188e+04 2.901e-02 15: mtem sin All 1.261e+04 2.702e-02 16: mtem dx All 1.170e+04 2.898e-02 17: cing dx All 8.732e+03 2.996e-02 18: cing sin All 9.292e+03 2.797e-02 19: item dx All 9.875e+03 2.723e-02 20: item sin All 1.002e+04 2.598e-02 21: th dx All 5.534e+03 3.018e-02 22: th sin All 5.509e+03 3.060e-02 23: str sin All 9.757e+03 3.113e-02 24: str dx All 9.385e+03 3.038e-02

Distribution volume DV

Measure of reversible uptake Calculated using two methods: 1. Graphical analysis: Logan plot 2. Compartmental model fit

DV and DVR images using plasma input: demonstration

1. Calculate DV image 2. Calculate regional average DV values 3. Calculate structural averages over image planes 4. Divide DV image by reference region DV 5. View image to check success F:\demo>imgdv uf0061ap.pure.kbq uf0061dy1.img 15 uf0061dv.img

reading dynamic image uf0061dy1.img

computing logan plot pixel-by-pixel ...................................done.

DV image uf0061dv.img saved.

F:\demo>img2dft uf0061dv.img uf0061*.roi

… 48 regional TACs written in uf0061dv.dft

F:\demo>dftavg -rm uf0061dv.dft

… 48 TAC(s) are deleted; backup is in uf0061dv.dft% F:\demo>dftlist uf0061dv.dft

1: frad All 4.062e+03 6.174e+00 … 23: pons All 1.027e+03 1.040e+00 24: cerd All 1.389e+04 3.995e+00 F:\demo>ecatcalc uf0061dv.img : 1.040 uf0061dvr.img

F:\demo>ecat2tif uf0061dvr.img uf0061dvr_20.tif 20 1 reading uf0061dvr.img

writing file uf0061dvr_20.tif

maximum pixel value in matrix is 9.64954, unit unknown DVR is unitless

DVR images using reference region input: demonstration

1. Open Notepad (Start>Programs> Accessories>Notepad) 2. Write the commands 3. Save file as ”dvr.bat” in the data directory 4. Run the batch file with study number as argument, e.g. ”dvr uf0061” 5. View image to check success Contents of batch file dvr.bat : echo off echo Calculate regional TACs img2dft %1dy1.img %1*.roi

echo Calculate average reference tissue TAC dftavg -rm %1dy1.dft pons echo Extract reference tissue TAC to a separate datafile del %1pons.dft

dftadd %1pons.dft %1dy1.dft pons echo Calculate parametric Logan plot imgdv %1pons.dft %1dy1.img 15 %1dvr.img

echo Make TIFF format image just for checking ecat2tif %1dvr.img %1dvr_20.tif 20 1 echo Calculate regional DVR values img2dft %1dvr.img %1*.roi

echo Calculate regional averages over image planes dftavg %1dvr.dft

echo List DVR values on screen dftlist %1dvr.dft

DVR is unitless

DV image using plasma input and compartmental model fit: demonstration

Contents of batch file dv.bat : 1. Open Notepad (Start>Programs> Accessories>Notepad) 2. Write the commands 3. Save file as ”dv.bat” in the data directory 4. Run the batch file with study number as argument, e.g. ”dv uf0061” 5. View image to check success echo off echo Fit DV pixel-by-pixel imglhdv %1ap.pure.kbq %1dy1.img %1dv.img

echo Make TIFF format image just for checking ecat2tif %1dv.img %1dv_20.tif 20 1 echo Calculate regional DV values img2dft %1dv.img %1*.roi

echo Calculate regional averages over image planes dftavg %1dv.dft

echo List DV values on screen dftlist %1dv.dft

Unit of DV is (ml plasma)/(ml tissue)

Comparison of the analysis methods

Graphical analysis: + no information needed of model compartments – restricted to linear portion of data Compartmental model fit: + Not restricted to linear portion of data – requires good quality input curve and delay correction

Advantages of batch files

• Less writing = less errors • Calculation steps are easy to check and repeat • Changes are simple to perform using any text editor (Wordpad, textedit) • Unix and Linux have scripting languages with even more features

Simplified reference tissue model (SRTM)

Binding potential = receptor density × affinity Determined with three programs: 1. RPM (Matlab required) 2. imgsrtm Linearized model fit 3. imgbfbp , substitute for RPM (Matlab-independent)

BP image using imgsrtm: demonstration

1. Open Notepad (Start>Programs> Accessories>Notepad) 2. Write the commands 3. Save file as ”srtm.bat” in the data directory 4. Run the batch file with study number as argument, and direct output to log file, e.g.

”srtm ub0419 > ub0419.log” 5. View images to check success BP Contents of batch file srtm.bat : echo off echo Calculate regional TACs img2dft %1dy1.img %1*.roi

echo Calculate average reference tissue TAC dftavg -rm %1dy1.dft cer echo Extract reference tissue TAC to a separate datafile del %1cer.dft

dftadd %1cer.dft %1dy1.dft cer echo Calculate parametric BP, R1 and k2 images imgsrtm %1dy1.img %1cer.dft %1bp.img -R1=%1r1.img -k2=%1k2.img

echo Make TIFF format images just for checking ecat2tif %1bp.img %1bp_20.tif 20 1 ecat2tif %1r1.img %1r1_20.tif 20 1 ecat2tif %1k2.img %1k2_20.tif 20 1 echo Calculate regional BP values img2dft %1bp.img %1*.roi

echo Calculate regional averages over image planes dftavg -rm %1bp.dft

echo List BP values on screen dftlist %1bp.dft

R 1 k 2 BP and R 1 are unitless. Unit of k 2 is min -1

Blood flow (perfusion)

Determined by two methods: 1. Autoradiographic (ARG) method 2. Compartmental model fit

Flow image using ARG: demonstration

1. Calibrate blood TAC and correct for decay and time delay and dispersion 2. Open Notepad (Start>Programs> Accessories>Notepad) 3. Write the commands 4. Save file as ”arg.bat” in the data directory 5. Run the batch file with study number as argument, e.g.

”arg uo0300” 6. View image to check success Flow Contents of batch file arg.bat : echo off echo Calculate look-up table arlkup %1fit.kbq 1.0 150 0 120 5000 %1.lkup

echo Calculate integral image (change if framing is different) ctisum -i %1dy1.img 1 12 %1int.img

echo Get flow for each pixel from the table ctilkup %1int.img %1.lkup %1flow.img

echo Make TIFF image just for checking ecat2tif %1flow.img %1flow.tif 14 1 echo Calculate regional averages img2dft %1flow.img %1*.roi

echo List regional flow values on screen dftlist %1flow.dft

With this method, unit of flow is (ml blood) / (min × 100 ml tissue)

Flow image using compartmental model fit: demonstration

1. Calibrate blood TAC and correct for decay and time delay and dispersion 2. Open Notepad (Start>Programs> Accessories>Notepad) 3. Write the commands 4. Save file as ”flow.bat” in the data directory 5. Run the batch file with study number as argument, e.g.

”flow uo0300” 6. View images to check success Flow Contents of batch file flow.bat : echo off echo Calculate parametric flow and partition volume image imgflow %1fit.kbq %1dy1.img 240 %1f.img -Va=NONE -DV=%1p.img

echo Make TIFF images just for checking ecat2tif %1f.img %1f.tif 14 1 ecat2tif %1p.img %1p.tif 14 1 echo Calculate regional averages img2dft %1f.img %1*.roi

img2dft %1p.img %1*.roi

echo List regional flow values on screen dftlist %1f.dft

echo List regional p values on screen dftlist %1p.dft

p With this method, unit of flow is (ml blood) / (min × ml tissue).

Unit of p is (ml blood) / (ml tissue)

Supported image file formats

• Currently all programs use ECAT 6.3 (*.img; ECAT 931, GE Advance) • Now some programs, and in the near future all programs can also use ECAT 7.x (*.v; ECAT HR+) • Analyze -format will be supported, possibly also Interfile -format