SPECT deadtime count loss correction using monitor source method

Purpose: Deadtime-count-loss (DTloss) correction using monitor source (MS) requires: 1) uniform fractional DTloss across FOV, 2) high statistics MS images both with & without the object. The aims are validating condition 1 and developing a practical protocol that satisfies conditions 2 with minimal additional study duration.Methods and Materials: SPECT images of non-uniform phantoms (4GBq 99mTc) along with MS (20MBq 99mTc) attached to each detector were acquired multiple times over 48 hours in photopeak and scatter energy window (EW) using Siemens-SymbiaS and GE-D670. Planar images of the MS alone were acquired. Photopeak counts for the MS ROIs were > 100kcts. Fractional DTloss uniformity across the FOV was evaluated by correlating count rates in different ROIs on projection images at different DTloss levels. The correction factor for each SPECT projection at every time point was calculated as the ratio of time-corrected MS count rates with & without the phantom.The DTloss-corrected projections for each SPECT acquisition were decay corrected to one time point. The correction accuracy was assessed against DTloss estimated by paralyzable model. The accuracy of projection-based DTloss correction for SPECT was evaluated. A method to model projection DTloss based on a subset of measured projection DTloss was investigated. The relation of DTloss between photopeak and scatter EW was explored.Results: The fractional DTloss was uniform across the FOV (r > 0.99), validating condition 1. The MS method was accurate to > 99% for planar and SPECT. Measured DTloss from 3-to-5 projections/detector may be used to estimate DTloss with accuracy > 98% for all SPECT projections by modeling DTloss with measured projection rate. The correction factor in photopeak and scatter EW are equivalent with > 99% agreement.Conclusion: MS method can accurately correct planar and SPECT DTloss. Sparse sampling of the projection DTloss allows acquiring MS counts with high statistics with minimal additional study duration making it clinically practical.--------------------------------------Cite this article as: Siman W, Kappadath SC. SPECT deadtime count loss correction using monitor source method. Int J Cancer Ther Oncol 2014; 2(2):020234. DOI: 10.14319/ijcto.0202.3

Voxel-based partial volume correction for accurate quantitative voxel values

Purpose: The accuracy of voxelized information in emission imaging is limited by spatial resolution (FWHM = 2.35σ) producing biases for objects smaller than 3 FWHM. If the signal distribution is non‐uniform within 3σ of the voxel of interest then equilibrium does not exist and partial volume effect (PVE) compromises voxel accuracy. We propose a mathematical model to improve the accuracy of quantitative images of arbitrary distribution by bounding true voxel signal and estimating PVE for each voxel.Methods: A monotonically increasing parametric dataset is created for each voxel of an emission image by radial integration from the voxel center to radius = 6σ. Each cumulative integration plot from r = 3σ to 6σ is fit to a function A*4π /3*r3 + B*ΔV derived assuming a local uniform signal distribution (A) where ΔV is the voxel volume. The constant BΔV represents the converged within 3σ integral of PVE. B > 0 implies spill‐out, B < 0 spill‐in, and B = 0 no PVE. We tested the proposed model on simulations of 1D&2D datasets containing known signal distributions and 18F‐PET/CT images of a 6cc lung lesion and bladder.Results: Signal accuracy was > 99% in simulated 1D & 2D datasets. For the tumor, the original maximum value was 10kBq/ml. We obtained A = 3.5kBq/ml and B = 14kBq/ml for a total of 17.7kBq/ml. This yields (A+B)/original = 1.8 indicating substantial spill‐out of ~80% and a large error for the original voxel value. For a voxel in the center of the bladder, the original value was 46kBq/ml with A = 44kBq/ml, B = 7kBq/ml. (A+B)/original = 1.11 indicating near‐equilibrium at center of bladder and low spill-out of ~11% as expected. Local signal images (A) resemble low‐pass filtered original image and (B) shows the magnitude and direction of PVE. Conclusion: A new mathematical model to estimate the accuracy of voxels in quantitative images of arbitrary distribution has been developed. Analysis of additional patients is underway.-------------------------------------Cite this article as: Mikell J, Kappadath SC. Voxel-based partial volume correction for accurate quantitative voxel values. Int J Cancer Ther Oncol 2014; 2(2):020229. DOI: 10.14319/ijcto.0202.2

Observed intercamera variability in clinically relevantperformance characteristics for Siemens Symbia gammacameras

This is the peer reviewed version of the following article: Kappadath SC, Erwin WD, Wendt RE 3rd. Observed inter-camera variability of clinically relevant performance characteristics for Siemens Symbia gamma cameras. J Appl Clin Med Phys. 2006;7(4):74-80. Published 2006 Nov 28., which has been published in final form at doi:10.1120/jacmp.v7i4.2376. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions. This article may not be enhanced, enriched or otherwise transformed into a derivative work, without express permission from Wiley or by statutory rights under applicable legislation. Copyright notices must not be removed, obscured or modified. The article must be linked to Wiley’s version of record on Wiley Online Library and any embedding, framing or otherwise making available the article or pages thereof by third parties from platforms, services and websites other than Wiley Online Library must be prohibited.https://openworks.mdanderson.org/mdacc_imgphys_pubs/1009/thumbnail.jp

90Y PET/CT quantitative accuracy and image quality

Purpose: To optimize 90Y-PET/CT image reconstruction for quantitative accuracy and optimal image quality.Methods: PET/CT scans of a NEMA IEC phantom (3GBq 90YCl2, sphere uptake ratio of ~7) were acquired on 4 GE (BGO:DSTE, DST & LYSO:DRX, D690) and 1 Siemens (LSO:mCT) scanners in 3D list mode with 30 min/bed; replayed to 20, 15, 10 min/bed. Iterative reconstruction parameters explored were SUB × IT (3 – 80) and post-reconstruction filters: transaxial: 5 – 25 mm cutoff & z-axis (GE only): std vs. heavy. The effects of PSF modeling and TOF correction were evaluated for D690 and mCT. VOIs were drawn inside spheres and in adjacent background regions. The accuracy of sphere activity concentration (AC in kBq/mL) and contrast to noise ratio (CNR) was calculated as function of SUB × IT. Reconstructed PET images were also evaluated qualitatively for sphere detectability and artifacts.Results: AC converged to 70 – 90% accuracy for 37 mm sphere and further degraded for smaller spheres. Spheres at max CNR might not reach AC convergence yet. Smaller spheres have slower convergence but reach CNR max together with other spheres. Scan duration did not strongly affect sphere convergence but shorter scans increased noise and reduced detectability; 13 mm spheres were not visible going from 30 to 15 min/bed. Heavy z-axis (GE) and transaxial filter with 10 – 15 mm cutoff helped suppress noise and increase sphere detectability at the expense of accuracy. Images with PSF+TOF corrections had higher sphere detectability and converged faster. Hot cluster artifacts 5 – 7 times the background were seen in some cases with SUB × IT near convergence and lower filtration.Conclusion: Accurate 90Y AC was not achieved even at convergence and noise is a major concern. 90YPET/CT reconstruction parameters are different than those for 18F and benefit substantially from PSF+TOF corrections. Optimum image quality and accurate AC may not be simultaneously achievable.----------------------------------------Cite this article as: Siman W, Mawlawi O, Kappadath SC. 90Y PET/CT quantitative accuracy and image quality. Int J Cancer Ther Oncol 2014; 2(2):020235. DOI: 10.14319/ijcto.0202.3

A novel method to evaluate gamma camera rotational uniformity and sensitivity variation

Kappadath, S.C., Erwin, W.D. and Wendt, R.E., III (2009), A novel method to evaluate gamma camera rotational uniformity and sensitivity variation. Med. Phys., 36: 1947-1955. https://doi.org/10.1118/1.3125642https://openworks.mdanderson.org/mdacc_imgphys_pubs/1007/thumbnail.jp

Dose volume histogram‐based optimization of image reconstruction parameters for quantitative 90Y‐PET imaging

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/147185/1/mp13269.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/147185/2/mp13269_am.pd

Characterization of tumor dose heterogeneity for 90Y microsphere therapies using voxel- based dosimetry

Purpose: Dosimetry for 90Y microsphere therapies (YMT) with Standard (SM) and Partition (PM) models provide only uniform dose estimates to tumor and liver. Our objective is to calculate tumor dose heterogeneity, known to effect response, using voxel-based dosimetry and investigate the limitations of SM and PM.Methods: Voxel-based dosimetry was performed on 17 YMT patients using Monte Carlo DOSXYZnrc. 90Y activity and tissue/density distributions were based on quantitative 90Y bremsstrahlung SPECT/CT. Tumors (n=31), liver, and treatment lobe/segments were segmented on diagnostic CT or MR. Dose volume histograms (DVH) were created for tumors and normal liver. Bland-Altman analysis compared voxel-based mean absorbed doses to tumor and liver with SM and PM. Tumor and normal liver absorbed dose heterogeneity were investigated through metrics: integral uniformity (IU), D10/D90, COV. Correlations of heterogeneity with voxel-based mean doses and volumes were evaluated.Results: Heterogeneity metrics (mean ± 1σ) for tumor dose were COV = 0.48 ± 0.28, D10/D90 = 4.7 ± 3.9, and IU = 0.8 ± 0.18. Heterogeneity metrics correlated with tumor volume (r > 0.58) but not tumor mean doses (r < 0.20). Voxel-based tumor mean doses correlated with PM (r = 0.84) but not SM (r = 0.08). Both yielded poor limits of agreement with of 83 ± 174 and -28 ± 181 Gy, respectively. Normal liver heterogeneity metrics (mean ± 1σ) were COV = 0.83 ± 0.29, D10/D90 = 12 ± 15, and IU = 0.97 ± 0.03. Only D10/D90 (r = 0.49) correlated with mean normal liver absorbed dose. Voxel-based normal liver/lobe mean doses correlated with PM (r = 0.96), but had poor limits of agreement (26 ± 29 Gy).Conclusion: Tumor doses have high levels of heterogeneity that increase with volume but are independent of dose. Voxel-based DVH and dose heterogeneity metrics will promote accurate characterization of tumor response following YMT.--------------------------------------Cite this article as: Mikell J, Mourtada F, Mahvash A, Kappadath SC. Characterization of tumor dose heterogeneity for 90Y microsphere therapies using voxel- based dosimetry. Int J Cancer Ther Oncol 2014; 2(2):020228. DOI: 10.14319/ijcto.0202.2

Astrophysical and Cosmological Implications of Large Volume String Compactifications

We study the spectrum, couplings and cosmological and astrophysical implications of the moduli fields for the class of Calabi-Yau IIB string compactifications for which moduli stabilisation leads to an exponentially large volume V ~ 10^{15} l_s^6 and an intermediate string scale m_s ~ 10^{11}GeV, with TeV-scale observable supersymmetry breaking. All K\"ahler moduli except for the overall volume are heavier than the susy breaking scale, with m ~ ln(M_P/m_{3/2}) m_{3/2} ~ (\ln(M_P/m_{3/2}))^2 m_{susy} ~ 500 TeV and, contrary to standard expectations, have matter couplings suppressed only by the string scale rather than the Planck scale. These decay to matter early in the history of the universe, with a reheat temperature T ~ 10^7 GeV, and are free from the cosmological moduli problem (CMP). The heavy moduli have a branching ratio to gravitino pairs of 10^{-30} and do not suffer from the gravitino overproduction problem. The overall volume modulus is a distinctive feature of these models and is an M_{planck}-coupled scalar of mass m ~ 1 MeV and subject to the CMP. A period of thermal inflation can help relax this problem. This field has a lifetime ~ 10^{24}s and can contribute to dark matter. It may be detected through its decays to 2\gamma or e^+e^-. If accessible the e^+e^- decay mode dominates, with Br(\chi \to 2 \gamma) suppressed by a factor (ln(M_P/m_{3/2}))^2. We consider the potential for detection of this field through different astrophysical sources and find that the observed gamma-ray background constrains \Omega_{\chi} <~ 10^{-4}. The decays of this field may generate the 511 keV emission line from the galactic centre observed by INTEGRAL/SPI.Comment: 31 pages, 2 figures; v2. refs adde

SPECT deadtime count loss correction using monitor source method

Purpose: Deadtime-count-loss (DTloss) correction using monitor source (MS) requires: 1) uniform fractional DTloss across FOV, 2) high statistics MS images both with &amp; without the object. The aims are validating condition 1 and developing a practical protocol that satisfies conditions 2 with minimal additional study duration.Methods and Materials: SPECT images of non-uniform phantoms (4GBq 99mTc) along with MS (20MBq 99mTc) attached to each detector were acquired multiple times over 48 hours in photopeak and scatter energy window (EW) using Siemens-SymbiaS and GE-D670. Planar images of the MS alone were acquired. Photopeak counts for the MS ROIs were &gt; 100kcts. Fractional DTloss uniformity across the FOV was evaluated by correlating count rates in different ROIs on projection images at different DTloss levels. The correction factor for each SPECT projection at every time point was calculated as the ratio of time-corrected MS count rates with &amp; without the phantom.The DTloss-corrected projections for each SPECT acquisition were decay corrected to one time point. The correction accuracy was assessed against DTloss estimated by paralyzable model. The accuracy of projection-based DTloss correction for SPECT was evaluated. A method to model projection DTloss based on a subset of measured projection DTloss was investigated. The relation of DTloss between photopeak and scatter EW was explored.Results: The fractional DTloss was uniform across the FOV (r &gt; 0.99), validating condition 1. The MS method was accurate to &gt; 99% for planar and SPECT. Measured DTloss from 3-to-5 projections/detector may be used to estimate DTloss with accuracy &gt; 98% for all SPECT projections by modeling DTloss with measured projection rate. The correction factor in photopeak and scatter EW are equivalent with &gt; 99% agreement.Conclusion: MS method can accurately correct planar and SPECT DTloss. Sparse sampling of the projection DTloss allows acquiring MS counts with high statistics with minimal additional study duration making it clinically practical.--------------------------------------Cite this article as: Siman W, Kappadath SC. SPECT deadtime count loss correction using monitor source method. Int J Cancer Ther Oncol 2014; 2(2):020234. DOI: 10.14319/ijcto.0202.34</p

Voxel-based partial volume correction for accurate quantitative voxel values

Purpose: The accuracy of voxelized information in emission imaging is limited by spatial resolution (FWHM = 2.35σ) producing biases for objects smaller than 3 FWHM. If the signal distribution is non‐uniform within 3σ of the voxel of interest then equilibrium does not exist and partial volume effect (PVE) compromises voxel accuracy. We propose a mathematical model to improve the accuracy of quantitative images of arbitrary distribution by bounding true voxel signal and estimating PVE for each voxel.Methods: A monotonically increasing parametric dataset is created for each voxel of an emission image by radial integration from the voxel center to radius = 6σ. Each cumulative integration plot from r = 3σ to 6σ is fit to a function A*4π /3*r3 + B*ΔV derived assuming a local uniform signal distribution (A) where ΔV is the voxel volume. The constant BΔV represents the converged within 3σ integral of PVE. B &gt; 0 implies spill‐out, B &lt; 0 spill‐in, and B = 0 no PVE. We tested the proposed model on simulations of 1D&amp;2D datasets containing known signal distributions and 18F‐PET/CT images of a 6cc lung lesion and bladder.Results: Signal accuracy was &gt; 99% in simulated 1D &amp; 2D datasets. For the tumor, the original maximum value was 10kBq/ml. We obtained A = 3.5kBq/ml and B = 14kBq/ml for a total of 17.7kBq/ml. This yields (A+B)/original = 1.8 indicating substantial spill‐out of ~80% and a large error for the original voxel value. For a voxel in the center of the bladder, the original value was 46kBq/ml with A = 44kBq/ml, B = 7kBq/ml. (A+B)/original = 1.11 indicating near‐equilibrium at center of bladder and low spill-out of ~11% as expected. Local signal images (A) resemble low‐pass filtered original image and (B) shows the magnitude and direction of PVE. Conclusion: A new mathematical model to estimate the accuracy of voxels in quantitative images of arbitrary distribution has been developed. Analysis of additional patients is underway.-------------------------------------Cite this article as: Mikell J, Kappadath SC. Voxel-based partial volume correction for accurate quantitative voxel values. Int J Cancer Ther Oncol 2014; 2(2):020229. DOI: 10.14319/ijcto.0202.29</p