Image Generation and Clinical task-based Image Assessment


In oncology and cardiology, lesion and defect detection is critical for the diagnosis and treatment of patients. More information about our efforts to improve the medical imaging of lesions in the lungs and the liver, and the detection of heart defects can be found in the links below.


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  • Myocardial Defect Detection

    It is expected that both noise and activity distribution can have impact on the detectability of a myocardial defect in a cardiac PET study. We performed phantom studies to investigate the detectability of a defect in the myocardium for different noise levels and activity distributions. We evaluated the performance of three reconstruction schemes: Filtered Back-Projection (FBP), Ordinary Poisson Ordered Subset Expectation Maximization (OP–OSEM), and Point Spread Function corrected OSEM (PSF–OSEM). We used the Channelized Hotelling Observer (CHO) for the task of myocardial defect detection. We found that the detectability of a myocardial defect is almost entirely dependent on the noise level and the contrast between the defect and its surroundings.

    Selected Figures:

    Figure 4: Reconstructed image slices and line profiles through the myocardial defect. doi:10.1371/journal.pone.0088200.g004

    Figure 4: Reconstructed image slices and line profiles through the myocardial defect.
    doi:10.1371/journal.pone.0088200.g004

    Figure 6: CHO SNR versus defect/myocardium (A) and myocardium/background (B) concentration ratios. The dashed lines were obtained using weighted least squares linear regression. doi:10.1371/journal.pone.0088200.g006

    Figure 6: CHO SNR versus defect/myocardium (A) and myocardium/background (B) concentration ratios. The dashed lines were obtained using weighted least squares linear regression.
    doi:10.1371/journal.pone.0088200.g006

    Eugene S. Mananga, Georges El Fakhri, Joshua Schaefferkoetter, Ali A. Bonab, Jinsong Ouyang, Myocardial Defect Detection Using PET-CT: Phantom Studies, PLoS ONE, 2014. [Link]

     

  • Objective Assessment of Image Quality
    for Estimation and Detection Tasks

    We are developing a rigorous evaluation methodology
    for objective assessment of image quality for lesion detection and
    activity quantitation tasks. We have applied our methods to assess the
    performance of different acquisition (2D vs 3D) and processing methods
    for variable patient sizes in the context of lesion detection in whole
    body FDG-PET. Our results show that for lesion detection and activity
    quantitation tasks, 3D imaging yielded better lesion detectability than
    2D (p<0.025, two-tailed paired t-test) in patients of normal size (Body
    Mass Index [BMI] ¾ 31). However 2D imaging yielded better lesion
    detectability than 3D in large patients (BMI > 31) as 3D performance
    deteriorated in large patients (p<0.05). 2D and 3D yielded similar
    results for different lesion sizes. We have extended our work to the
    assessment of performance of Time of Flight PET and determined the gains
    that can be achieved in lung and liver cancer for lesion detection tasks
    in a cohort of 100 patients in collaboration with Dr. Karp's lab at
    UPENN.

    image quality

    Related Papers:
    • El Fakhri G., Surti S., Trott C.M.,
      Scheuermann J., Karp J.S. Improvement in Lesion
      Detection with Whole-Body Oncologic TOF - PET. J. Nucl.
      Med. 2011; 52: 347-353.
      [PDF]

    • Surti S., Scheuermann J., El Fakhri
      G., Daube-Witherspoon M.E., Abi-Hatem N., Moussallem E.,
      Lim R., Benard F., Mankoff D., and Karp J.S. Impact of
      TOF PET on whole-body oncologic studies: a human
      observer lesion detection and localization study. J.
      Nucl. Med. 2011; 52: 712-719.
      [PDF]

    • El Fakhri G., Santos P., Badawi R.D.,
      Holdsworth C.H., Van den Abbeele A.D., Kijewski M.F.
      Impact of acquisition geometry, image processing, and
      patient habitus on tumor detection in whole - body
      FDG-PET. J. Nucl. Med. 2007; 48: 1951-1960.
      [PDF]

    • Moore S.C., Kijewski M.F., and El
      Fakhri G. Collimator optimization for detection and
      quantitation tasks: application to gallium-67 imaging.
      IEEE Trans. Med. Imag; 2005; 24: 1347-1356.

    • El Fakhri G., Kijewski M.F., Albert M.S., Johnson K.A., and Moore S.C. Quantitative SPECT leads to improved performance in discrimination tasks related to prodromal Alzheimer’s disease. J. Nucl. Med. 2004; 45: 2026-2031.
      [PDF]

    • El Fakhri G., Kijewski M.F., Johnson
      K.A., Syrkin G, Killiany R.J., Becker JA, Zimmerman
      R.E., Albert M.S. MRI-Guided SPECT perfusion measures
      and volumetric MRI in prodromal Alzheimer’s disease.
      Arch Neurol 2003; 60: 1066-1072. [PDF]

    • El Fakhri G., Moore S.C., and Kijewski
      M.F. Optimization of Ga-67 imaging for detection and
      estimation tasks: dependence of imaging performance on
      spectral acquisition parameters. Med Phys 2002; 29:
      1859-1866. [PDF]

    • Jadvar H, Moore SC, Kijewski MF, Bonab
      A, Zimmerman RE, Fischman AJ. Evaluation of SPECT
      imaging systems based on activity estimation in small
      brain structures. J. Nucl. Med. 2000;41:180P.


     

  • Monte Carlo Simulation of Particle Propagation

    Monte Carlo simulation is a numerical tool that uses random numbers in
    order to approximately solve integral problems. Monte Carlo simulation
    can be used to model particle propagation in complex geometries and is
    therefore capable of simulating PET and SPECT acquisitions. We have
    developed and fully validated a detailed Monte Carlo simulation of
    block-based scintillation detectors used in PET. This code is currently
    being used by other researchers to generate realistic PET simulations
    that are useful to assess the accuracy of various corrections and
    reconstruction strategies.

     

    Representative Figures:


    monte carlo

    Figure 1. Energy
    spectra of a cylindrical water filled phantom obtained with GATE (solid
    lines) and our simulator (symbols). Finite energy resolution was not
    modeled so as not to confound potential discrepancies between spectra.
    These were decomposed in their zeroth, first, second and third scatter
    orders, corresponding to 0, 1, 2 and 3 interactions in the object before
    detection. Arrow 1 on the zeroth order shows a Compton edge at 341 keV
    due to primary photons that scattered once at 180º in the detector.
    Arrow 2 on the first order shows a Compton edge at 170 keV due to
    photons that backscattered once in the object and then deposited all
    their energy in the detector. This figure essentially shows our
    simulator is as accurate as GATE for estimating energy spectra but is
    ~10 times faster even without using variance reduction techniques.

     

     


    monte carlo

     

    Figure 2. Central slice of the NEMA NU-2 2001
    image quality phantom imaged on a real GE Discovery ST scanner and
    simulated with SimSET and our simulator. Modeling crystals and blocks in
    our simulator allows to model more accurately the spatial resolution of
    the system and therefore partial volume effect that affect small spheres
    contrasts.

     

    Related Papers:

    • Guérin B. and El Fakhri G. Realistic
      PET Monte Carlo simulation with pixellated block
      detectors, light sharing, random coincidences and
      dead-time modeling. IEEE Trans Nucl Sci. 2008; 55:
      942-952. [PDF]

    • Ouyang J., El
      Fakhri G., Moore S.C. Improved activity estimation with
      MC-JOSEM versus TEW-JOSEM in 111In SPECT. Med. Phys. 2008; 35:
      2029-2040. [PDF]

    • Ouyang J., El
      Fakhri G., Moore S.C. Fast Monte Carlo Simulation Based
      Joint Iterative Reconstruction for Simultaneous
      99mTc/123I Brain SPECT Imaging. Med. Phys. 2007; 34:
      3263-3272. [PDF]

    • Moore SC and El Fakhri G. Realistic
      Monte Carlo simulation of Ga-67 SPECT imaging. IEEE
      Trans. Nucl. Sci. 2001.

     

  • Clinical Projects

    Clinical Projects


    Below is a listing of our published clinical studies. Please follow the links to learn more about each project.
    clinical

    Related Papers:

    • El Fakhri G., Kardan A., Sitek A., Dorbala S.,
      Abi-Hatem N., Lahoud Y., Fischman A.J., Coughlan M.,
      Yasuda T., Di Carli M.F. Reproducibility and Accuracy of
      Quantitative Myocardial Blood Flow Assessment Using
      82Rb-PET: Comparison with 13N-Ammonia. J.
      Nucl. Med.
      2009; 50:1062-1071.
      [PDF]

    • Anagnostopoulos C., Almonacid A., El Fakhri G.,
      Currilova Z., Sitek A., Roughton M., Dorbala S., Popma
      J., Di Carli M. Quantitative Relationship Between
      Coronary Vasodilator Reserve Assessed by Rubidium-82 PET
      Imaging and Coronary Artery Stenosis Severity. Eur. J.
      Nucl. Med. Mol. Imag. 2008; 35: 1593-1601.
      [PDF]

    • Habert M.O., Lacomblez L., Makusd P., El Fakhri G.,
      Pradat P.F., Meininger V. Brain perfusion imaging in
      amyotrophic lateral sclerosis : Extent of cortical
      changes according to the severity and topography of
      motor impairment. Amyotrophic Lateral Sclerosis, 2007;
      8: 9-15.

    • Kas A., Payoux P., Habert M.O., Malek M., Cointepas Y.,
      El Fakhri G., Itti E., Remy P. Validation of
      standardized normalization template for statistical
      parametric mapping analysis of 123I-FPCIT images. J.
      Nucl. Med; 2007; 48: 1459-1467. [PDF]

    • El Fakhri G., Santos P., Badawi R.D., Holdsworth C.H.,
      Van den Abbeele A.D., Kijewski M.F. Impact of
      acquisition geometry, image processing, and patient
      habitus on tumor detection in whole - body FDG-PET. J.
      Nucl. Med. 2007; 48: 1951-1960. [PDF]

    • Mamede M., El Fakhri G., Abreu-e-Lima P., Gandler W.,
      Nose V., Gerbaudo V. Pre-operative estimation of
      esophageal tumor metabolic length in FDG PET images with
      surgical pathology confirmation. Ann Nucl Med. 2007; 21:
      553-562. [PDF]

    • Di Carli M.F., Dorbala S., Meserve J., El Fakhri G.,
      Sitek A., Moore S.C. Clinical myocardial perfusion
      PET-CT. J. Nucl. Med; 2007; 48: 783-793.
      [PDF]

    • El Fakhri G., Habert M.O., Maksud P., Kas A., Malek Z.,
      Kijewski M.F., and Lacomblez L. Quantitative
      simultaneous 99mTc-ECD/123I-FP-CIT SPECT in Parkinson
      disease and multiple system atrophy. Eur. J. Nucl. Med.
      Mol. Imag. 2006; 33: 87-92. [PDF]

    • El Fakhri G., Kijewski M.F., Albert M.S., Johnson K.A.,
      and Moore S.C. Quantitative SPECT leads to improved
      performance in discrimination tasks related to prodromal
      Alzheimer’s disease. J. Nucl. Med. 2004; 45: 2026-2031.
      [PDF]

    • El Fakhri G., Kijewski M.F., Johnson K.A., Syrkin G,
      Killiany R.J., Becker JA, Zimmerman R.E., Albert M.S.
      MRI-Guided SPECT perfusion measures and volumetric MRI
      in prodromal Alzheimer’s disease. Arch Neurol 2003; 60:
      1066-1072. [PDF]