Nuklearmedizinsche Klinik und Poliklinik Klinikum rechts der Isar Technische Universität München Image reconstruction, MR-based attenuation correction,

Nuklearmedizinsche Klinik und PoliklinikKlinikum rechts der IsarTechnische Universität München

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Image reconstruction, MR-based attenuation correction, parametric imaging for PET

Jorge CabelloNuklearmedizinische Klinik im Klinikum rechts der Isar, Technische Universität München, Munich, Germany



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Gantt chart

Implement preliminary version of PRESTO

Adapt PRESTO to new geometry

Comparison of sinograms and LOR/histograms

GPU implementation of PRESTO

Implementation attenuation correction

Comparison clinical data

Implementation of parametric reconstruction

Integration in PRESTO

Comparison between direct and indirect methods

01/01/14 20/07/14 05/02/15 24/08/15 11/03/16 27/09/16 15/04/17 01/11/171/1/2014

12/1/2014

7/1/2015

12/1/2015

6/1/2016

12/1/2016

6/1/2016

11/1/2016

12/1/2016


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Gantt chart

• First sinogram 31st March.• First proof DL better as SL at sinogram level 11th April.• First images (back-projected sinograms) 4th July.

• Robust software understanding (GATE-translator-PRESTO).

• Final decision for dual layer design 8th July.

Tasks Start date Duration (days) End dateImplement preliminary version of PRESTO 01.01.2014 119 30.04.2014Adapt PRESTO to new geometry 01.12.2014 211 30.06.2015Comparison of sinograms and LOR/histograms 01.07.2015 152 30.11.2015GPU implementation of PRESTO 01.12.2015 182 31.05.2016Implementation attenuation correction 01.06.2016 182 30.11.2016Comparison clinical data 01.12.2016 61 31.01.2017Implementation of parametric reconstruction 01.06.2016 152 31.10.2016Integration in PRESTO 01.11.2016 29 30.11.2016Comparison between direct and indirect methods 01.12.2016 61 31.01.2017


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TRIMAGE 6/14 mm (DLDv2)



Crystal lengths

Radial spatial resolution

Tangential spatial resolution

6/14 mm 5.18 mm 6.14 mm

8/12 mm 4.87 mm 5.89 mm

10/10 mm 5.20 mm 6.03 mm

Radial profile

Tangential profile


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Gantt chart










01/01/14 20/07/14 05/02/15 24/08/15 11/03/16 27/09/16 15/04/17 01/11/171/1/2014

12/1/2014

7/1/2015

12/1/2015

6/1/2016

12/1/2016

6/1/2016

11/1/2016

12/1/2016


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Gantt chart










01/01/14 20/07/14 05/02/15 24/08/15 11/03/16 27/09/16 15/04/17 01/11/171/1/2014

12/1/2014

7/1/2015

12/1/2015

6/1/2016

12/1/2016

6/1/2016

11/1/2016

12/1/2016

First sinogram Differences between SL and DL

Software chainestablished

DL design established


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Inter-detectors gaps • Homogeneous cylinders.

• Water phantom 37 MBq x 80 s (no attenuation/normalization correction)

20 cm (64% FOV)

20 cm

4th November


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• Water phantom 37 MBq x 80 s (no normalization correction)

20 cm (64% FOV)

20 cm

10th December


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• Water phantom 37 MBq x 80 s

20 cm (64% FOV)

20 cm

10th December


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Inter-detectors gaps • Two uniform cylinders.


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Inter-detectors gaps • Two uniform cylinders.


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To do• Still some artefacts to fix in the

reconstruction.• Need to confirm quality of simulated

data.• Comparison LOR-histograms vs adaptive

size sinograms on impact in image quality (1/7/15-30-11-15).


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MR-based attenuation correction


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Internal air mask UTE1 (Ba0,i)

Internal air mask UTE2 (Ba1,i)

External air mask(Ba,o)

Internal air mask(Ba,i)

Air mask (Ba)

Post processingµ-mapR2b,x + soft

tissue + filter

Low dose CT

UTE1 (TE 70 µs)

UTE2 (TE 2.36 ms)

Set to 0 voxels with values Inf, NaN and

<0Normalize R2 map

Separate bone and soft tissue by hard threshold (0.004)

Calculate µ and σ from bone tissue

Threshold bone using µ+σ as

thresholdRemove small blobs

Binarized µ-map (µ-mapR2b,bin)

Clipped µ-map (µ- mapR2b,clp)

Equalized µ-map (µ- mapR2b,equ)

R2 map

Raw µ-map (µ-mapR2b,raw)

µ-mapR2,x

Completely automatic.

Computation time ~5 s.

Implemented in Matlab.


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Results (Schizofrenia)


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Gantt chart










01/01/14 20/07/14 05/02/15 24/08/15 11/03/16 27/09/16 15/04/17 01/11/171/1/2014

12/1/2014

7/1/2015

12/1/2015

6/1/2016

12/1/2016

6/1/2016

11/1/2016

12/1/2016

First sinogram Differences between SL and DL

Software chainestablished

DL design established

MR-based attenuationcorrection


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To do• Compare this approach with the original

proposed in the TDR ANN.• Can the MR produce artefact-free UTE

images?


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Next 6 months?• Reconstruction

• Robust attenuation and normalization correction.

• Determine the impact of the inter-detector gaps.

• Comparison LOR-histogram and sinogram reconstruction.

• MR-based attenuation correction• Comparison between UTE-based (Munich)

and ANN-based (Jülich) attenuation correction.

• Possibly to include an alternative method in the comparison.

Documents

Nuklearmedizinsche Klinik und Poliklinik Klinikum rechts der Isar Technische Universität München Image reconstruction, MR-based attenuation correction,