Literature DB >> 24994547

Pilot study: Evaluation of dual-energy computed tomography measurement strategies for positron emission tomography correlation in pancreatic adenocarcinoma.

Jorge Oldan1, Miao He, Teresa Wu, Alvin C Silva, Jing Li, J Ross Mitchell, William M Pavlicek, Michael C Roarke, Amy K Hara.   

Abstract

We sought to determine whether dual-energy computed tomography (DECT) measurements correlate with positron emission tomography (PET) standardized uptake values (SUVs) in pancreatic adenocarcinoma, and to determine the optimal DECT imaging variables and modeling strategy to produce the highest correlation with maximum SUV (SUVmax). We reviewed 25 patients with unresectable pancreatic adenocarcinoma seen at Mayo Clinic, Scottsdale, Arizona, who had PET-computed tomography (PET/CT) and enhanced DECT performed the same week between March 25, 2010 and December 9, 2011. For each examination, DECT measurements were taken using one of three methods: (1) average values of three tumor regions of interest (ROIs) (method 1); (2) one ROI in the area of highest subjective DECT enhancement (method 2); and (3) one ROI in the area corresponding to PET SUVmax (method 3). There were 133 DECT variables using method 1, and 89 using the other methods. Univariate and multivariate analysis regression models were used to identify important correlations between DECT variables and PET SUVmax. Both R2 and adjusted R2 were calculated for the multivariate model to compensate for the increased number of predictors. The average SUVmax was 5 (range, 1.8-12.0). Multivariate analysis of DECT imaging variables outperformed univariate analysis (r = 0.91; R2 = 0.82; adjusted R2 = 0.75 vs. r < 0.58; adjusted R2 < 0.34). Method 3 had the highest correlation with PET SUVmax (R2 = 0.82), followed by method 1 (R2 = 0.79) and method 2 R2 = 0.57). DECT thus has clinical potential as a surrogate for, or as a complement to, PET in patients with pancreatic adenocarcinoma.

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Year:  2014        PMID: 24994547      PMCID: PMC4391069          DOI: 10.1007/s10278-014-9707-y

Source DB:  PubMed          Journal:  J Digit Imaging        ISSN: 0897-1889            Impact factor:   4.056


  21 in total

1.  Computed tomography in the evaluation of patients with suspected carcinoma of the pancreas.

Authors:  P F Sheedy; D H Stephens; R R Hattery; R L MacCarty
Journal:  Radiology       Date:  1977-09       Impact factor: 11.105

2.  Optimal interpretation of FDG PET in the diagnosis, staging and management of pancreatic carcinoma.

Authors:  D Delbeke; D M Rose; W C Chapman; C W Pinson; J K Wright; R D Beauchamp; Y Shyr; S D Leach
Journal:  J Nucl Med       Date:  1999-11       Impact factor: 10.057

3.  Imaging features of pancreatic neoplasms.

Authors:  P R Ros; K J Mortelé
Journal:  JBR-BTR       Date:  2001

4.  Pancreatic dual-source dual-energy CT: is it time to discard unenhanced imaging?

Authors:  Achille Mileto; Silvio Mazziotti; Michele Gaeta; Antonio Bottari; Fabrizio Zimbaro; Claudio Giardina; Giorgio Ascenti
Journal:  Clin Radiol       Date:  2011-11-16       Impact factor: 2.350

5.  Contribution of 18F-fluorodeoxyglucose positron emission tomography to the diagnosis of early pancreatic carcinoma.

Authors:  Satoru Seo; Ryuichiro Doi; Takafumi Machimoto; Kazuhiro Kami; Toshihiko Masui; Etsuro Hatano; Kohei Ogawa; Tatsuya Higashi; Shinji Uemoto
Journal:  J Hepatobiliary Pancreat Surg       Date:  2008-11-07

6.  Computed tomography of the pancreas.

Authors:  J R Haaga; R J Alfidi; M G Zelch; T F Meany; M Boller; L Gonzalez; G L Jelden
Journal:  Radiology       Date:  1976-09       Impact factor: 11.105

7.  Dual-energy CT in patients suspected of having renal masses: can virtual nonenhanced images replace true nonenhanced images?

Authors:  Anno Graser; Thorsten R C Johnson; Elizabeth M Hecht; Christoph R Becker; Christianne Leidecker; Michael Staehler; Christian G Stief; Henriette Hildebrandt; Myrna C B Godoy; Myra E Finn; Flora Stepansky; Maximilian F Reiser; Michael Macari
Journal:  Radiology       Date:  2009-06-01       Impact factor: 11.105

8.  Automated radiation targeting in head-and-neck cancer using region-based texture analysis of PET and CT images.

Authors:  Huan Yu; Curtis Caldwell; Katherine Mah; Ian Poon; Judith Balogh; Robert MacKenzie; Nader Khaouam; Romeo Tirona
Journal:  Int J Radiat Oncol Biol Phys       Date:  2009-08-14       Impact factor: 7.038

9.  Dual energy CT characterization of urinary calculi: initial in vitro and clinical experience.

Authors:  Anno Graser; Thorsten R C Johnson; Markus Bader; Michael Staehler; Nicolas Haseke; Konstantin Nikolaou; Maximilian F Reiser; Christian G Stief; Christoph R Becker
Journal:  Invest Radiol       Date:  2008-02       Impact factor: 6.016

10.  T2 MRI texture analysis is a sensitive measure of tissue injury and recovery resulting from acute inflammatory lesions in multiple sclerosis.

Authors:  Yunyan Zhang; Hongmei Zhu; J R Mitchell; Fiona Costello; Luanne M Metz
Journal:  Neuroimage       Date:  2009-04-08       Impact factor: 6.556

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  4 in total

1.  Spectral multi-energy CT texture analysis with machine learning for tissue classification: an investigation using classification of benign parotid tumours as a testing paradigm.

Authors:  Eiman Al Ajmi; Behzad Forghani; Caroline Reinhold; Maryam Bayat; Reza Forghani
Journal:  Eur Radiol       Date:  2018-01-02       Impact factor: 5.315

Review 2.  Dual energy CT applications in pancreatic pathologies.

Authors:  Elizabeth George; Jeremy R Wortman; Urvi P Fulwadhva; Jennifer W Uyeda; Aaron D Sodickson
Journal:  Br J Radiol       Date:  2017-09-22       Impact factor: 3.039

3.  Dual-Energy CT Texture Analysis With Machine Learning for the Evaluation and Characterization of Cervical Lymphadenopathy.

Authors:  Matthew Seidler; Behzad Forghani; Caroline Reinhold; Almudena Pérez-Lara; Griselda Romero-Sanchez; Nikesh Muthukrishnan; Julian L Wichmann; Gabriel Melki; Eugene Yu; Reza Forghani
Journal:  Comput Struct Biotechnol J       Date:  2019-07-16       Impact factor: 7.271

Review 4.  Improving radiation physics, tumor visualisation, and treatment quantification in radiotherapy with spectral or dual-energy CT.

Authors:  Matthijs Ferdinand Kruis
Journal:  J Appl Clin Med Phys       Date:  2021-11-07       Impact factor: 2.102

  4 in total

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