Literature DB >> 32990514

Observer Performance for Detection of Pulmonary Nodules at Chest CT over a Large Range of Radiation Dose Levels.

Joel G Fletcher1, David L Levin1, Anne-Marie G Sykes1, Rebecca M Lindell1, Darin B White1, Ronald S Kuzo1, Vighnesh Suresh1, Lifeng Yu1, Shuai Leng1, David R Holmes1, Akitoshi Inoue1, Matthew P Johnson1, Rickey E Carter1, Cynthia H McCollough1.   

Abstract

Background There is a wide variation in radiation dose levels that can be used with chest CT in order to detect indeterminate pulmonary nodules. Purpose To compare the performance of lower-radiation-dose chest CT with that of routine dose in the detection of indeterminate pulmonary nodules 5 mm or greater. Materials and Methods In this retrospective study, CT projection data from 83 routine-dose chest CT examinations performed in 83 patients (120 kV, 70 quality reference mAs [QRM]) were collected between November 2013 and April 2014. Reference indeterminate pulmonary nodules were identified by two nonreader thoracic radiologists. By using validated noise insertion, five lower-dose data sets were reconstructed with filtered back projection (FBP) or iterative reconstruction (IR; 30 QRM with FBP, 10 QRM with IR, 5 QRM with FBP, 5 QRM with IR, and 2.5 QRM with IR). Three thoracic radiologists circled pulmonary nodules, rating confidence that the nodule was a 5-mm-or-greater indeterminate pulmonary nodule, and graded image quality. Analysis was performed on a per-nodule basis by using jackknife alternative free-response receiver operating characteristic figure of merit (FOM) and noninferiority limit of -0.10. Results There were 66 indeterminate pulmonary nodules (mean size, 8.6 mm ± 3.4 [standard deviation]; 21 part-solid nodules) in 42 patients (mean age, 51 years ± 17; 21 men and 21 women). Compared with the FOM for routine-dose CT (size-specific dose estimate, 6.5 mGy ± 1.8; FOM, 0.86 [95% confidence interval: 0.80, 0.91]), FOM was noninferior for all lower-dose configurations except for 2.5 QRM with IR. The sensitivity for subsolid nodules at 70 QRM was 60% (range, 48%-72%) and was significantly worse at a dose of 5 QRM and lower, whether or not IR was used (P < .05). Diagnostic image quality decreased with decreasing dose (P < .001) and was better with IR at 5 QRM (P < .05). Conclusion CT images reconstructed at dose levels down to 10 quality reference mAs (size-specific dose estimate, 0.9 mGy) had noninferior performance compared with routine dose in depicting pulmonary nodules. Iterative reconstruction improved subjective image quality but not performance at low dose levels. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by White and Kazerooni in this issue.

Entities:  

Year:  2020        PMID: 32990514      PMCID: PMC7706885          DOI: 10.1148/radiol.2020200969

Source DB:  PubMed          Journal:  Radiology        ISSN: 0033-8419            Impact factor:   11.105


  42 in total

Review 1.  Solitary pulmonary nodules: Part II. Evaluation of the indeterminate nodule.

Authors:  J J Erasmus; H P McAdams; J E Connolly
Journal:  Radiographics       Date:  2000 Jan-Feb       Impact factor: 5.333

2.  Ultra-low-dose CT with model-based iterative reconstruction (MBIR): detection of ground-glass nodules in an anthropomorphic phantom study.

Authors:  Cristiano Rampinelli; Daniela Origgi; Vittoria Vecchi; Luigi Funicelli; Sara Raimondi; Paul Deak; Massimo Bellomi
Journal:  Radiol Med       Date:  2015-02-06       Impact factor: 3.469

3.  Low-Dose CT for Craniosynostosis: Preserving Diagnostic Benefit with Substantial Radiation Dose Reduction.

Authors:  J C Montoya; L J Eckel; D R DeLone; A L Kotsenas; F E Diehn; L Yu; A C Bartley; R E Carter; C H McCollough; J G Fletcher
Journal:  AJNR Am J Neuroradiol       Date:  2017-02-09       Impact factor: 3.825

4.  Pilot study of detection, radiologist confidence and image quality with sinogram-affirmed iterative reconstruction at half-routine dose level.

Authors:  Joel G Fletcher; William R Krueger; David M Hough; James E Huprich; Jeff L Fidler; Jia Wang; Maria M Shiung; W Scott Harmsen; Katharine L Grant; Cynthia H McCollough
Journal:  J Comput Assist Tomogr       Date:  2013 Mar-Apr       Impact factor: 1.826

5.  Radiation dose associated with common computed tomography examinations and the associated lifetime attributable risk of cancer.

Authors:  Rebecca Smith-Bindman; Jafi Lipson; Ralph Marcus; Kwang-Pyo Kim; Mahadevappa Mahesh; Robert Gould; Amy Berrington de González; Diana L Miglioretti
Journal:  Arch Intern Med       Date:  2009-12-14

6.  Pilot study of radiation dose reduction for pediatric head CT in evaluation of ventricular size.

Authors:  S Gabriel; L J Eckel; D R DeLone; K N Krecke; P H Luetmer; C H McCollough; J G Fletcher; L Yu
Journal:  AJNR Am J Neuroradiol       Date:  2014-07-31       Impact factor: 3.825

7.  Correlation between model observer and human observer performance in CT imaging when lesion location is uncertain.

Authors:  Shuai Leng; Lifeng Yu; Yi Zhang; Rickey Carter; Alicia Y Toledano; Cynthia H McCollough
Journal:  Med Phys       Date:  2013-08       Impact factor: 4.071

8.  A feasibility study of pulmonary nodule detection by ultralow-dose CT with adaptive statistical iterative reconstruction-V technique.

Authors:  Kai Ye; Qiao Zhu; Meijiao Li; Yuliu Lu; Huishu Yuan
Journal:  Eur J Radiol       Date:  2019-09-07       Impact factor: 3.528

9.  Adaptive Statistical Iterative Reconstruction-Applied Ultra-Low-Dose CT with Radiography-Comparable Radiation Dose: Usefulness for Lung Nodule Detection.

Authors:  Hyun Jung Yoon; Myung Jin Chung; Hye Sun Hwang; Jung Won Moon; Kyung Soo Lee
Journal:  Korean J Radiol       Date:  2015-08-21       Impact factor: 3.500

10.  Radiation dose reduction for CT lung cancer screening using ASIR and MBIR: a phantom study.

Authors:  Kelsey B Mathieu; Hua Ai; Patricia S Fox; Myrna Cobos Barco Godoy; Reginald F Munden; Patricia M de Groot; Tinsu Pan
Journal:  J Appl Clin Med Phys       Date:  2014-03-06       Impact factor: 2.102

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  4 in total

1.  Deep-learning lesion and noise insertion for virtual clinical trial in Chest CT.

Authors:  Hao Gong; Jeffrey F Marsh; Jamison Thorne; Shuai Leng; Cynthia H McCollough; Joel G Fletcher; Lifeng Yu
Journal:  Proc SPIE Int Soc Opt Eng       Date:  2021-02-15

2.  Reproducibility of lung nodule radiomic features: Multivariable and univariable investigations that account for interactions between CT acquisition and reconstruction parameters.

Authors:  Nastaran Emaminejad; Muhammad Wasil Wahi-Anwar; Grace Hyun J Kim; William Hsu; Matthew Brown; Michael McNitt-Gray
Journal:  Med Phys       Date:  2021-04-13       Impact factor: 4.506

Review 3.  Innovations in thoracic imaging: CT, radiomics, AI and x-ray velocimetry.

Authors:  Rozemarijn Vliegenthart; Andreas Fouras; Colin Jacobs; Nickolas Papanikolaou
Journal:  Respirology       Date:  2022-08-14       Impact factor: 6.175

4.  Low-dose CT image and projection dataset.

Authors:  Taylor R Moen; Baiyu Chen; David R Holmes; Xinhui Duan; Zhicong Yu; Lifeng Yu; Shuai Leng; Joel G Fletcher; Cynthia H McCollough
Journal:  Med Phys       Date:  2020-12-16       Impact factor: 4.071

  4 in total

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