Literature DB >> 27755394

Clinical evaluation of a block sequential regularized expectation maximization reconstruction algorithm in 18F-FDG PET/CT studies.

Bert-Ram Sah1, Paul Stolzmann, Gaspar Delso, Scott D Wollenweber, Martin Hüllner, Yahya A Hakami, Marcelo A Queiroz, Felipe de Galiza Barbosa, Gustav K von Schulthess, Carsten Pietsch, Patrick Veit-Haibach.   

Abstract

PURPOSE: To investigate the clinical performance of a block sequential regularized expectation maximization (BSREM) penalized likelihood reconstruction algorithm in oncologic PET/computed tomography (CT) studies.
METHODS: A total of 410 reconstructions of 41 fluorine-18 fluorodeoxyglucose-PET/CT studies of 41 patients with a total of 2010 lesions were analyzed by two experienced nuclear medicine physicians. Images were reconstructed with BSREM (with four different β values) or ordered subset expectation maximization (OSEM) algorithm with/without time-of-flight (TOF/non-TOF) corrections. OSEM reconstruction postfiltering was 4.0 mm full-width at half-maximum; BSREM did not use postfiltering. Evaluation of general image quality was performed with a five-point scale using maximum intensity projections. Artifacts (category 1), image sharpness (category 2), noise (category 3), and lesion detectability (category 4) were analyzed using a four-point scale. Size and maximum standardized uptake value (SUVmax) of lesions were measured by a third reader not involved in the image evaluation.
RESULTS: BSREM-TOF reconstructions showed the best results in all categories, independent of different body compartments. In all categories, BSREM non-TOF reconstructions were significantly better than OSEM non-TOF reconstructions (P<0.001). In almost all categories, BSREM non-TOF reconstruction was comparable to or better than the OSEM-TOF algorithm (P<0.001 for general image quality, image sharpness, noise, and P=1.0 for artifact). Only in lesion detectability was OSEM-TOF significantly better than BSREM non-TOF (P<0.001). Both BSREM-TOF and BSREM non-TOF showed a decreasing SUVmax with increasing β values (P<0.001) and TOF reconstructions showed a significantly higher SUVmax than non-TOF reconstructions (P<0.001).
CONCLUSION: The BSREM reconstruction algorithm showed a relevant improvement compared with OSEM reconstruction in PET/CT studies in all evaluated categories. BSREM might be used in clinical routine in conjunction with TOF to achieve better/higher image quality and lesion detectability or in PET/CT-systems without TOF-capability for enhancement of overall image quality as well.

Entities:  

Mesh:

Substances:

Year:  2017        PMID: 27755394     DOI: 10.1097/MNM.0000000000000604

Source DB:  PubMed          Journal:  Nucl Med Commun        ISSN: 0143-3636            Impact factor:   1.690


  20 in total

1.  Improving perfusion defect detection with respiratory motion correction in cardiac SPECT at standard and reduced doses.

Authors:  Chao Song; Yongyi Yang; Albert Juan Ramon; Miles N Wernick; P Hendrik Pretorius; Karen L Johnson; Piotr J Slomka; Michael A King
Journal:  J Nucl Cardiol       Date:  2018-07-30       Impact factor: 5.952

2.  Standard OSEM vs. regularized PET image reconstruction: qualitative and quantitative comparison using phantom data and various clinical radiopharmaceuticals.

Authors:  Judit Lantos; Erik S Mittra; Craig S Levin; Andrei Iagaru
Journal:  Am J Nucl Med Mol Imaging       Date:  2018-04-25

3.  Quantitative and Qualitative Improvement of Low-Count [68Ga]Citrate and [90Y]Microspheres PET Image Reconstructions Using Block Sequential Regularized Expectation Maximization Algorithm.

Authors:  Youngho Seo; Mohammad Mehdi Khalighi; Kristen A Wangerin; Timothy W Deller; Yung-Hua Wang; Salma Jivan; Maureen P Kohi; Rahul Aggarwal; Robert R Flavell; Spencer C Behr; Michael J Evans
Journal:  Mol Imaging Biol       Date:  2020-02       Impact factor: 3.488

4.  Performance evaluation of the Q.Clear reconstruction framework versus conventional reconstruction algorithms for quantitative brain PET-MR studies.

Authors:  Daniela Ribeiro; William Hallett; Adriana A S Tavares
Journal:  EJNMMI Phys       Date:  2021-05-07

5.  Can Q.Clear reconstruction be used to improve [68 Ga]Ga-DOTANOC PET/CT image quality in overweight NEN patients?

Authors:  Lucia Zanoni; Giulia Argalia; Emilia Fortunati; Claudio Malizia; Vincenzo Allegri; Diletta Calabrò; Simona Civollani; Davide Campana; Stefano Fanti; Valentina Ambrosini
Journal:  Eur J Nucl Med Mol Imaging       Date:  2021-10-25       Impact factor: 9.236

6.  Quantitative performance and optimal regularization parameter in block sequential regularized expectation maximization reconstructions in clinical 68Ga-PSMA PET/MR.

Authors:  Edwin E G W Ter Voert; Urs J Muehlematter; Gaspar Delso; Daniele A Pizzuto; Julian Müller; Hannes W Nagel; Irene A Burger
Journal:  EJNMMI Res       Date:  2018-07-27       Impact factor: 3.138

7.  Performance characteristics of silicon photomultiplier based 15-cm AFOV TOF PET/CT.

Authors:  Delphine Vandendriessche; Jorge Uribe; Hugo Bertin; Frank De Geeter
Journal:  EJNMMI Phys       Date:  2019-05-10

8.  Usefulness of respiratory-gated PET acquisition during delayed 18F-FDG PET/CT scanning for patients with liver metastases.

Authors:  Shota Watanabe; Kohei Hanaoka; Hayato Kaida; Tomoko Hyodo; Minoru Yamada; Masakatsu Tsurusaki; Kazunari Ishii
Journal:  Asia Ocean J Nucl Med Biol       Date:  2021

9.  Optimization of [18F]PSMA-1007 PET-CT using regularized reconstruction in patients with prostate cancer.

Authors:  Elin Trägårdh; David Minarik; Gustav Brolin; Ulrika Bitzén; Berit Olsson; Jenny Oddstig
Journal:  EJNMMI Phys       Date:  2020-05-12

10.  Impact of a Bayesian penalized likelihood reconstruction algorithm on image quality in novel digital PET/CT: clinical implications for the assessment of lung tumors.

Authors:  Michael Messerli; Paul Stolzmann; Michèle Egger-Sigg; Josephine Trinckauf; Stefano D'Aguanno; Irene A Burger; Gustav K von Schulthess; Philipp A Kaufmann; Martin W Huellner
Journal:  EJNMMI Phys       Date:  2018-09-26
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.