Literature DB >> 22374400

Solitary pulmonary nodules differentiated by dynamic F-18 FDG PET in a region with high prevalence of granulomatous disease.

Yu-Erh Huang1, Hung-I Lu, Feng-Yuan Liu, Yu-Jie Huang, Meng-Chih Lin, Chih-Feng Chen, Pei-Wen Wang.   

Abstract

This study determined whether dynamic F-18 FDG PET imaging could differentiate benign from malignant solitary pulmonary nodules (SPNs). Histopathologically confirmed SPNs (10-35 mm), 24 malignant and 10 benign, from 34 patients were studied through both dynamic and static F-18 FDG PET imaging of all patients. Volumes of interest (VOIs) were placed over the pulmonary nodules using a 50% maximum pixel value threshold. The arterial input function was estimated from a left ventricle-defined VOI. Based on Patlak analysis, we calculated the net FDG phosphorylation rate (K(i)) and glucose metabolic rate (MRGlu) of each nodule. The slope values of the time-activity curves (TACs) of the nodules were also determined. Based on the static PET images, maximum and mean standardized uptake values (SUV(max) and SUV(mean), respectively) were calculated. Benign and malignant SPNs had significantly different values for SUV(max), SUV(mean), K(i), MRGlu, and TAC slope, with area under the receiver operating characteristic curves distinguishing benign from malignant nodules. McNemar's test of marginal homogeneity found all the predictors helpful to detect malignant nodules (all, p > 0.05), and combining K(i) and MRGlu, which were generated by dynamic study, yielded a higher specificity of 90%, and a sensitivity of 79%. Among the 10 benign nodules, static SUV imaging correctly classified seven, while dynamic F-18 PET imaging correctly classified nine. Dynamic F-18 FDG PET imaging is valuable in differentiating benign from malignant SPNs, particularly for granulomatous disease.

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Year:  2012        PMID: 22374400     DOI: 10.1269/jrr.11089

Source DB:  PubMed          Journal:  J Radiat Res        ISSN: 0449-3060            Impact factor:   2.724


  10 in total

1.  The flip-flop fungus sign: an FDG PET/CT sign of benignity.

Authors:  Alex A Nagelschneider; Stephen M Broski; William P Holland; David E Midthun; Anne-Marie Sykes; Val J Lowe; Patrick J Peller; Geoffrey B Johnson
Journal:  Am J Nucl Med Mol Imaging       Date:  2017-11-01

2.  Prone position [18F]FDG PET/CT to reduce respiratory motion artefacts in the evaluation of lung nodules.

Authors:  Hyung Ju Lee; Hye Joo Son; Mijin Yun; Jung Won Moon; Yoo Na Kim; Ji Young Woo; Suk Hyun Lee
Journal:  Eur Radiol       Date:  2021-04-14       Impact factor: 5.315

3.  Dual-Time-Point FDG PET/CT to Distinguish Coccidioidal Pulmonary Nodules from Those Due to Malignancy.

Authors:  Ahmed K Pasha; Travis K Walsh; Neil M Ampel
Journal:  Lung       Date:  2015-07-23       Impact factor: 2.584

4.  Positron emission tomography in the evaluation of pulmonary nodules among patients living in a coccidioidal endemic region.

Authors:  Nathaniel Reyes; Oluwole O Onadeko; Maria Del Carmen Luraschi-Monjagatta; Kenneth S Knox; Margaret A Rennels; Travis Kent Walsh; Neil M Ampel
Journal:  Lung       Date:  2014-05-07       Impact factor: 2.584

5.  Usefulness of dynamic fluorodeoxyglucose positron emission tomography/computed tomography in diagnosing pulmonary arteriovenous malformation mimicking a lung tumour.

Authors:  Serkan Gungor; Halil İbrahim Yakar
Journal:  Interact Cardiovasc Thorac Surg       Date:  2021-10-04

6.  The value of 18F-FDG-PET/CT in the diagnosis of solitary pulmonary nodules: A meta-analysis.

Authors:  Zhen-Zhen Li; Ya-Liang Huang; Hong-Jun Song; You-Juan Wang; Yan Huang
Journal:  Medicine (Baltimore)       Date:  2018-03       Impact factor: 1.889

7.  The value of 18F-FDG PET/CT in the diagnosis of different size of solitary pulmonary nodules.

Authors:  Kun Tang; Ling Wang; Jie Lin; XiangWu Zheng; Yiwei Wu
Journal:  Medicine (Baltimore)       Date:  2019-03       Impact factor: 1.817

8.  Differentiation Between Malignant and Benign Pulmonary Nodules by Using Automated Three-Dimensional High-Resolution Representation Learning With Fluorodeoxyglucose Positron Emission Tomography-Computed Tomography.

Authors:  Yung-Chi Lai; Kuo-Chen Wu; Neng-Chuan Tseng; Yi-Jin Chen; Chao-Jen Chang; Kuo-Yang Yen; Chia-Hung Kao
Journal:  Front Med (Lausanne)       Date:  2022-03-18

9.  Comparison between a dual-time-window protocol and other simplified protocols for dynamic total-body 18F-FDG PET imaging.

Authors:  Zhenguo Wang; Yaping Wu; Xiaochen Li; Yan Bai; Hongzhao Chen; Jie Ding; Chushu Shen; Zhanli Hu; Dong Liang; Xin Liu; Hairong Zheng; Yongfeng Yang; Yun Zhou; Meiyun Wang; Tao Sun
Journal:  EJNMMI Phys       Date:  2022-09-14

10.  FDG PET/CT evaluation of pathologically proven pulmonary lesions in an area of high endemic granulomatous disease.

Authors:  Ronnie Sebro; Carina Mari Aparici; Miguel Hernandez-Pampaloni
Journal:  Ann Nucl Med       Date:  2013-02-12       Impact factor: 2.668

  10 in total

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