Estimation of Parameters of Parathyroid Glands Using Particle Swarm Optimization and Multivariate Generalized Gaussian Function Mixture

The paper introduces a fitting method for Single-Photon Emission Computed Tomography (SPECT) images of parathyroid glands using generalized Gaussian function for quantitative assessment of preoperative parathyroid SPECT/CT scintigraphy results in a large patient cohort. Parathyroid glands are very small for SPECT acquisition and the overlapping of 3D distributions was observed. The application of multivariate generalized Gaussian function mixture allows modeling, but results depend on the optimization algorithm. Particle Swarm Optimization (PSO) with global best, ring, and random neighborhood topologies were compared. The obtained results show benefits of random neighborhood topology that gives a smaller error for 3D position and the position estimation was improved by about 3% voxel size, but the most important is the reduction of processing time to a few minutes, compared to a few hours in relation to the random walk algorithm. Moreover, the frequency of obtaining low MSE values was more than two times higher for this topology. The presented method based on random neighborhood topology allows quantifying activity in a specific voxel in a short time and could be applied it in clinical practice.

[1]  B. Nguyen.  Parathyroid imaging with Tc-99m sestamibi planar and SPECT scintigraphy. , 1999, Radiographics : a review publication of the Radiological Society of North America, Inc.

[2]  Ho-Yyoung Lee,et al.  Efficacy of 99mTc-sestamibi SPECT/CT for minimally invasive parathyroidectomy: comparative study with 99mTc-sestamibi scintigraphy, SPECT, US and CT , 2012, Annals of Nuclear Medicine.

[3]  Barbara Webb,et al.  Swarm Intelligence: From Natural to Artificial Systems , 2002, Connect. Sci..

[4]  Riccardo Poli,et al.  Particle swarm optimization , 1995, Swarm Intelligence.

[5]  Conrad Sanderson,et al.  Armadillo: a template-based C++ library for linear algebra , 2016, J. Open Source Softw..

[6]  M. Petretta,et al.  Incremental Value of Sestamibi SPECT/CT Over Dual-Phase Planar Scintigraphy in Patients With Primary Hyperparathyroidism and Inconclusive Ultrasound , 2019, Front. Med..

[7]  O. N. Shevtsova,et al.  Mathematical Simulation of Transport Kinetics of Tumor-Imaging Radiopharmaceutical 99mTc-MIBI , 2017, Comput. Math. Methods Medicine.

[8]  Stefan Bruckner,et al.  Performing Maximum Intensity Projection with the Visualization Toolkit , 2002 .

[9]  Xiaodong Li,et al.  Erratum to "Niching Without Niching Parameters: Particle Swarm Optimization Using a Ring Topology" [Feb 10 150-169] , 2010, IEEE Trans. Evol. Comput..

[10]  Ana Cernea,et al.  Particle Swarm Optimization and Uncertainty Assessment in Inverse Problems , 2018, Entropy.

[11]  Jian Zhang,et al.  Efficient Volume Exploration Using the Gaussian Mixture Model , 2011, IEEE Transactions on Visualization and Computer Graphics.

[12]  Truong Q. Nguyen,et al.  Image Denoising with Generalized Gaussian Mixture Model Patch Priors , 2018, SIAM J. Imaging Sci..

[13]  C. Somboonporn,et al.  Diagnostic accuracy of planar, SPECT, and SPECT/CT parathyroid scintigraphy protocols in patients with hyperparathyroidism. , 2018, Nuclear medicine review. Central & Eastern Europe.

[14]  R. DeLellis,et al.  Parathyroid tumors and related disorders , 2011, Modern Pathology.

[15]  T. Vogl,et al.  Preoperative contrast-enhanced MRI of the parathyroid glands in hyperparathyroidism. , 2000, Investigative radiology.

[16]  K. Lhotta,et al.  Therapie des sekundären renalen Hyperparathyreoidismus – aktueller Stellenwert der Parathyreoidektomie , 2016, Wiener Medizinische Wochenschrift.

[17]  Maurice Clerc,et al.  Back to random topology , 2007 .

[18]  S. Lheureux,et al.  F18-choline, a novel PET tracer for parathyroid adenoma? , 2013, The Journal of clinical endocrinology and metabolism.

[19]  Jin Yong Sung,et al.  Parathyroid ultrasonography: the evolving role of the radiologist , 2015, Ultrasonography.

[20]  A. Elgazzar,et al.  Scintigraphic parathyroid imaging: concepts and new developments , 2015 .

[21]  Gerald Matz,et al.  PET image segmentation using a Gaussian mixture model and Markov random fields , 2015, EJNMMI Physics.

[22]  D. Steward,et al.  Essentials of parathyroid imaging , 2016 .

[23]  Xiaodong Li,et al.  Niching Without Niching Parameters: Particle Swarm Optimization Using a Ring Topology , 2010, IEEE Transactions on Evolutionary Computation.

[24]  Martin J. Wainwright,et al.  Local Maxima in the Likelihood of Gaussian Mixture Models: Structural Results and Algorithmic Consequences , 2016, NIPS.

[25]  J. Lew,et al.  Role of SPECT and SPECT/CT in the Surgical Treatment of Primary Hyperparathyroidism , 2011, International journal of molecular imaging.

[26]  Yuhui Shi,et al.  Handbook of Swarm Intelligence: Concepts, Principles and Applications , 2011 .

[27]  Peter S. Pacheco.  Parallel programming with MPI , 1996 .

[28]  L L Yuan,et al.  Combined application of ultrasound and SPECT/CT has incremental value in detecting parathyroid tissue in SHPT patients. , 2016, Diagnostic and interventional imaging.

[29]  Ali Hamzeh,et al.  Scaling up the hybrid Particle Swarm Optimization algorithm for nominal data-sets , 2015, Intell. Data Anal..

[30]  Jian Guo,et al.  Topology Optimization of Particle Swarm Optimization , 2014, ICSI.

[31]  Maria H. Listewnik,et al.  CT-SPECT Analyzer - A Tool for CT and SPECT Data Fusion and Volumetric Visualization , 2017, IP&C.

[32]  Eric C Frey,et al.  A Monte Carlo and physical phantom evaluation of quantitative In-111 SPECT , 2005, Physics in medicine and biology.

[33]  K. Tomaszewski,et al.  The prevalence and anatomy of parathyroid glands: a meta-analysis with implications for parathyroid surgery , 2019, Langenbeck's Archives of Surgery.

[34]  K. Lhotta,et al.  Therapie des sekundären renalen Hyperparathyreoidismus – aktueller Stellenwert der Parathyreoidektomie , 2016, Wiener Medizinische Wochenschrift.

[35]  Sami Romdhani,et al.  Face Sample Synthesis , 2009, Encyclopedia of Biometrics.

[36]  Richard S. Lawson,et al.  Gamma Camera SPECT , 2013 .

[37]  A. Halevy,et al.  Low-radiation of technetium-99m-sestamibi and single-photon emission computed tomography/computed tomography to diagnose parathyroid lesions , 2019, World journal of nuclear medicine.

[38]  S. Vinnicombe,et al.  Breast imaging in the new era , 2004, Cancer imaging : the official publication of the International Cancer Imaging Society.

[39]  A. Scillitani,et al.  Imaging of the parathyroid glands in primary hyperparathyroidism. , 2016, European journal of endocrinology.

[40]  H. Takagi,et al.  Histopathology, pathophysiology, and indications for surgical treatment of renal hyperparathyroidism. , 1997, Seminars in surgical oncology.

[41]  Maria H. Listewnik,et al.  Multivariate generalized Gaussian function mixture for volume modeling of parathyroid glands , 2017, 2017 22nd International Conference on Methods and Models in Automation and Robotics (MMAR).

[42]  E. Aboagye,et al.  Highlights lecture EANM 2016: “Embracing molecular imaging and multi-modal imaging: a smart move for nuclear medicine towards personalized medicine” , 2017, European Journal of Nuclear Medicine and Molecular Imaging.

[43]  Barbara Chapman,et al.  Using OpenMP: Portable Shared Memory Parallel Programming (Scientific and Engineering Computation) , 2007 .

[44]  Zhi-hui Zhan,et al.  Topology selection for particle swarm optimization , 2016, Inf. Sci..

[45]  Eric C Frey,et al.  Model-based compensation for quantitative 123I brain SPECT imaging , 2006, Physics in medicine and biology.

[46]  Andrew Kettle,et al.  2009 EANM parathyroid guidelines , 2009, European Journal of Nuclear Medicine and Molecular Imaging.

[47]  Orazio Schillaci,et al.  Personalized medicine: a new option for nuclear medicine and molecular imaging in the third millennium , 2017, European Journal of Nuclear Medicine and Molecular Imaging.

[48]  B. Barraclough,et al.  Ultrasound of the Thyroid and Parathyroid Glands , 2000, World Journal of Surgery.

[49]  Eduard Gröller,et al.  Interactive High‐Quality Maximum Intensity Projection , 2000, Comput. Graph. Forum.

[50]  Euclid Seeram,et al.  Computed Tomography: Physical Principles, Instrumentation, and Quality Control , 2013 .

[51]  Kam L. Wong.  Analysis or synthesis , 1985 .

[52]  Hoai Bac Le,et al.  GPU Implementation of Extended Gaussian Mixture Model for Background Subtraction , 2010, 2010 IEEE RIVF International Conference on Computing & Communication Technologies, Research, Innovation, and Vision for the Future (RIVF).

[53]  B. C. Penney,et al.  A Gaussian mixture model for definition of lung tumor volumes in positron emission tomography. , 2007, Medical physics.