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A phantom design for assessment of detectability in PET
S. R. Cherry, J. A. Sorenson, and M. E. Phelps, Physics in Nuclear Medicine (Elsevier Health Sciences, Amsterdam, The Netherlands, 2012).
R. R. Raylman, P. V. Kison, and R. L. Wahl, “Capabilities of two- and three-dimensional FDG-PET for detecting small lesions and lymph nodes in the upper torso: A dynamic phantom study,” Eur. J. Nucl. Med. Mol. Imaging 26(1), 39–45 (1999).
P. Christian, “Use of a precision fillable clinical simulator phantom for PET/CT scanner validation in multi-center clinical trials: The SNM clinical trials network (CTN) program,” J. Nucl. Med. 53(supplement 1), 437 (2012).
J. J. Sunderland and P. E. Christian, “Quantitative PET/CT scanner performance characterization based upon the society of nuclear medicine and molecular imaging clinical trials network oncology clinical simulator phantom,” J. Nucl. Med. 56(1), 145–152 (2015).
C. Lartizien, P. E. Kinahan, and C. Comtat, “A lesion detection observer study comparing 2-dimensional versus fully 3-dimensional whole-body PET imaging protocols,” J. Nucl. Med. 45(4), 714–723 (2004).
D. J. Kadrmas, M. E. Casey, N. F. Black, J. J. Hamill, V. Y. Panin, and M. Conti, “Experimental comparison of lesion detectability for four fully-3D PET reconstruction schemes,” IEEE Trans. Med. Imaging 28(4), 523–534 (2009).
D. J. Kadrmas and P. E. Christian, “Comparative evaluation of lesion detectability for 6 PET imaging platforms using a highly reproducible whole-body phantom with 22Na lesions and localization ROC analysis,” J. Nucl. Med. 43(11), 1545–1554 (2002).
D. C. Hunt, H. Easton, and C. B. Caldwell, “Design and construction of a quality control phantom for SPECT and PET imaging,” Med. Phys. 36(12), 5404–5411 (2009).
F. P. DiFilippo, J. P. Price, D. N. Kelsch, and R. F. Muzic, “Porous phantoms for PET and SPECT performance evaluation and quality assurance,” Med. Phys. 31(5), 1183–1194 (2004).
S. D. Wollenweber, “A multi-contrast, multi-resolution phantom for radionuclide imaging using a single activity concentration fill,” IEEE Trans. Nucl. Sci. 61(5), 2503–2509 (2014).
M. F. Bieniosek, B. J. Lee, and C. S. Levin, “Technical note: Characterization of custom 3D printed multimodality imaging phantoms,” Med. Phys. 42(10), 5913–5918 (2015).
H. C. Gifford, M. A. King, D. J. De Vries, and E. J. Soares, “Channelized hotelling and human observer correlation for lesion detection in hepatic SPECT imaging,” J. Nucl. Med. 41(3), 514–521 (2000).
H. C. Gifford, M. A. King, P. H. Pretorius, and R. G. Wells, “A comparison of human and model observers in multislice LROC studies,” IEEE Trans. Med. Imaging 24(2), 160–169 (2005).
S. D. Wollenweber, B. M. W. Tsui, D. S. Lalush, E. C. Frey, K. J. LaCroix, and G. T. Gullberg, “Comparison of hotelling observer models and human observers indefect detection from myocardial SPECT imaging,” IEEE Trans. Nucl. Sci. 46(6), 2098–2103 (1999).
S. D. Wollenweber, B. M. W. Tsui, D. S. Lalush, E. C. Frey, and G. T. Gullberg, “Evaluation of myocardial defect detection between parallel-hole and fan-beam SPECT using the hotelling trace,” IEEE Trans. Nucl. Sci. 45(4), 2205–2210 (1998).
K. L. Gilland, B. M. W. Tsui, Y. Qi, and G. T. Gullberg, “Comparison of channelized hotelling and human observers in determining optimum OS-EM reconstruction parameters for myocardial SPECT,” IEEE Trans. Nucl. Sci. 53(3), 1200–1204 (2006).
D. De Laat, F. Vallentin, and F. M. D. O. Filho, “Upper bounds for packings of spheres of several radii,” Forum Math. Sigma 2(e23), 1–42 (2014).
A. M. Alessio, C. W. Stearns, S. Tong, S. G. Ross, S. Kohlmyer, A. Ganin, and P. E. Kinahan, “Application and evaluation of a measured spatially variant system model for PET image reconstruction,” IEEE Trans. Med. Imaging 29(3), 938–949 (2010).
C. F. Gauss, “Besprechung des Buchs von LA Seeber: Intersuchungen über die Eigenschaften der positiven ternären quadratischen Formen usw,” Göttingsche Gelehrt. Anzeigen 2, 188–196 (1831).
Unpublished data—Average from 81 whole-body FDG PET/CT studies from a single imaging center.
C. K. Abbey, H. H. Barrett, and M. P. Eckstein, “Practical issues and methodology in assessment of image quality using model observers,” Med. Imaging: Phys. Med. Imaging 3032, 182–194 (1997).
H.-W. Tseng, J. Fan, M. A. Kupinski, P. Sainath, and J. Hsieh, “Assessing image quality and dose reduction of a new x-ray computed tomography iterative reconstruction algorithm using model observers,” Med. Phys. 41(7), 071910 (12pp.) (2014).
A. Wunderlich, F. Noo, B. D. Gallas, and M. E. Heilbrun, “Exact confidence intervals for channelized hotelling observer performance in image quality studies,” IEEE Trans. Med. Imaging 34(2), 453–464 (2015).
G. El Fakhri, P. A. Santos, R. D. Badawi, C. H. Holdsworth, A. D. Van Den Abbeele, and M. F. Kijewski, “Impact of acquisition geometry, image processing, and patient size on lesion detection in whole-body 18F-FDG PET,” J. Nucl. Med. 48(12), 1951–1960 (2007).
D. J. Kadrmas, M. E. Casey, M. Conti, B. W. Jakoby, C. Lois, and D. W. Townsend, “Impact of time-of-flight on PET tumor detection,” J. Nucl. Med. 50(8), 1315–1323 (2009).
S. Surti, J. Scheuermann, G. El Fakhri, M. E. Daube-Witherspoon, R. Lim, N. Abi-Hatem, E. Moussallem, F. Benard, D. Mankoff, and J. S. Karp, “Impact of time-of-flight PET on whole-body oncologic studies: A human observer lesion detection and localization study,” J. Nucl. Med. 52(5), 712–719 (2011).
G. El Fakhri, S. Surti, C. M. Trott, J. Scheuermann, and J. S. Karp, “Improvement in lesion detection with whole-body oncologic time-of-flight PET,” J. Nucl. Med. 52(3), 347–353 (2011).
J. D. Schaefferkoetter, J. Yan, D. W. Townsend, and M. Conti, “Initial assessment of image quality for low-dose PET: Evaluation of lesion detectability,” Phys. Med. Biol. 60(14), 5543–5556 (2015).
K. A. Wangerin, M. Muzi, L. M. Peterson, H. M. Linden, A. Novakova, F. O. Sullivan, B. F. Kurland, D. A. Mankoff, and P. E. Kinahan, “Effect of 18F-FDG uptake time on lesion detectability in PET imaging of early-stage breast cancer,” Tomography 1(1), 53–59 (2015).
C. Lartizien, P. E. Kinahan, R. Swensson, C. Comtat, M. Lin, V. Villemagne, and R. Trebossen, “Evaluating image reconstruction methods for tumor detection in 3-dimensional whole-body PET oncology imaging,” J. Nucl. Med. 44(2), 276–290 (2003).
L. Yang, J. Zhou, A. Ferrero, R. D. Badawi, and J. Qi, “Regularization design in penalized maximum-likelihood image reconstruction for lesion detection in 3D PET,” Phys. Med. Biol. 59(2), 403–419 (2014).
K. Wangerin, S. Ahn, S. G. Ross, P. E. Kinahan, and R. M. Manjeshwar, “Improving lesion detectability in PET imaging with a penalized likelihood reconstruction algorithm,” Proc. SPIE 9416, 1–8 (2015).
D. J. Kadrmas, M. B. Oktay, M. E. Casey, and J. J. Hamill, “Effect of scan time on oncologic lesion detection in whole-body PET,” IEEE Trans. Nucl. Sci. 59(5), 1940–1947 (2012).
J. Schaefferkoetter, M. Casey, D. Townsend, and G. El Fakhri, “Clinical impact of time-of-flight and point response modeling in PET reconstructions: A lesion detection study,” Phys. Med. Biol. 58(5), 1465–1478 (2013).
H. Bal, L. Guerin, M. E. Casey, M. Conti, L. Eriksson, C. Michel, S. Fanti, C. Pettinato, S. Adler, and P. Choyke, “Improving PET spatial resolution and detectability for prostate cancer imaging,” Phys. Med. Biol. 59(15), 4411–4426 (2014).
J. S. Kim, P. E. Kinahan, C. Lartizien, C. Comtat, and T. K. Lewellen, “A comparison of planar versus volumetric numerical observers for detection task performance in whole-body PET imaging,” IEEE Trans. Nucl. Sci. 51(1), 34–40 (2004).
R. G. Wells, M. A. King, H. C. Gifford, and P. H. Pretorius, “Single-slice versus multi-slice display for human-observer lesion-detection studies,” IEEE Trans. Nucl. Sci. 47(3), 1037–1044 (2000).
J. Qi, “Analysis of lesion detectability in Bayesian emission reconstruction with nonstationary object variability,” IEEE Trans. Med. Imaging 23(3), 321–329 (2004).
H. C. Gifford, P. E. Kinahan, C. Lartizien, and M. A. King, “Evaluation of multiclass model observers in PET LROC studies,” IEEE Trans. Nucl. Sci. 54(1), 116–123 (2007).
J. Nuyts, C. Michel, L. Brepoels, L. De Ceuninck, C. Deroose, K. Goffin, F. M. Mottaghy, S. Stroobants, J. Van Riet, and R. Verscuren, “Performance of MAP reconstruction for hot lesion detection in whole-body PET/CT: An evaluation with human and numerical observers,” IEEE Trans. Med. Imaging 28(1), 67–73 (2009).
F. P. Difilippo, S. L. Gallo, R. S. Klatte, and S. Patel, “A fillable micro-hollow sphere lesion detection phantom using superposition,” Phys. Med. Biol. 55(18), 5363–5381 (2010).
J. D. Sain and H. H. Barrett, “Performance evaluation of a modular gamma camera using a detectability index,” J. Nucl. Med. 44(1), 58–66 (2003).
J. Y. Hesterman, M. A. Kupinski, E. Clarkson, and H. H. Barrett, “Hardware assessment using the multi-module, multi-resolution system (M3R): A signal-detection study,” Med. Phys. 34(7), 3034–3044 (2007).
NEMA N. U. 2–2012 Performance Measurements of Positron Emission Tomographs,Rosslyn, VA, 2013.
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The primary clinical role of positron emission tomography
imaging is the detection of anomalous regions of
18F-FDG uptake, which are often indicative of malignant lesions. The
goal of this work was to create a task-configurable fillable phantom for realistic
measurements of detectability in PET
imaging. Design goals included simplicity, adjustable feature
size, realistic size and contrast levels, and inclusion of a lumpy (i.e.,
The detection targets were hollow 3D-printed dodecahedral nylon features. The
exostructure sphere-like features created voids in a background of small, solid
non-porous plastic (acrylic) spheres inside a fillable tank. The features filled
at full concentration while the background concentration was reduced due to
filling only between the solid spheres.
Multiple iterations of feature size and phantom construction were used to
determine a configuration at the limit of detectability for a PET/CT
A full-scale design used a 20 cm uniform cylinder (head-size) filled with a fixed
pattern of features at a contrast of approximately 3:1. Known signal-present and
signal-absent PET sub-images were extracted from multiple scans of the same
phantom and with detectability in a challenging (i.e., useful) range. These
images enabled calculation and comparison of the quantitative
observer detectability metrics between scanner designs and image
reconstruction methods. The phantom design has several
advantages including filling simplicity, wall-less contrast features, the
control of the detectability range via feature size, and a clinically realistic
This phantom provides a practical method for testing and comparison of lesion
detectability as a function of imaging
acquisition parameters, and image reconstruction methods and
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