Literature DB >> 28262519

Estimation of Observer Performance for Reduced Radiation Dose Levels in CT: Eliminating Reduced Dose Levels That Are Too Low Is the First Step.

Joel G Fletcher1, Lifeng Yu2, Jeff L Fidler2, David L Levin2, David R DeLone2, David M Hough2, Naoki Takahashi2, Sudhakar K Venkatesh2, Anne-Marie G Sykes2, Darin White2, Rebecca M Lindell2, Amy L Kotsenas2, Norbert G Campeau2, Vance T Lehman2, Adam C Bartley3, Shuai Leng2, David R Holmes4, Alicia Y Toledano5, Rickey E Carter3, Cynthia H McCollough2.   

Abstract

RATIONALE AND
OBJECTIVES: This study aims to estimate observer performance for a range of dose levels for common computed tomography (CT) examinations (detection of liver metastases or pulmonary nodules, and cause of neurologic deficit) to prioritize noninferior dose levels for further analysis.
MATERIALS AND METHODS: Using CT data from 131 examinations (abdominal CT, 44; chest CT, 44; head CT, 43), CT images corresponding to 4%-100% of the routine clinical dose were reconstructed with filtered back projection or iterative reconstruction. Radiologists evaluated CT images, marking specified targets, providing confidence scores, and grading image quality. Noninferiority was assessed using reference standards, reader agreement rules, and jackknife alternative free-response receiver operating characteristic figures of merit. Reader agreement required that a majority of readers at lower dose identify target lesions seen by the majority of readers at routine dose.
RESULTS: Reader agreement identified dose levels lower than 50% and 4% to have inadequate performance for detection of hepatic metastases and pulmonary nodules, respectively, but could not exclude any low dose levels for head CT. Estimated differences in jackknife alternative free-response receiver operating characteristic figures of merit between routine and lower dose configurations found that only the lowest dose configurations tested (ie, 30%, 4%, and 10% of routine dose levels for abdominal, chest, and head CT examinations, respectively) did not meet criteria for noninferiority. At lower doses, subjective image quality declined before observer performance. Iterative reconstruction was only beneficial when filtered back projection did not result in noninferior performance.
CONCLUSION: Opportunity exists for substantial radiation dose reduction using existing CT technology for common diagnostic tasks.
Copyright © 2017 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  CT; iterative reconstruction; observer performance; radiation dose; radiation dose reduction

Mesh:

Year:  2017        PMID: 28262519      PMCID: PMC6481673          DOI: 10.1016/j.acra.2016.12.017

Source DB:  PubMed          Journal:  Acad Radiol        ISSN: 1076-6332            Impact factor:   3.173


  12 in total

1.  Evaluation of Lower-Dose Spiral Head CT for Detection of Intracranial Findings Causing Neurologic Deficits.

Authors:  J G Fletcher; D R DeLone; A L Kotsenas; N G Campeau; V T Lehman; L Yu; S Leng; D R Holmes; P K Edwards; M P Johnson; G J Michalak; R E Carter; C H McCollough
Journal:  AJNR Am J Neuroradiol       Date:  2019-10-24       Impact factor: 3.825

2.  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

3.  Individualized and Generalized Learner Models for Predicting Missed Hepatic Metastases.

Authors:  Parvathy Sudhir Pillai; Scott Hsieh; David Holmes; Rickey Carter; Joel G Fletcher; Cynthia McCollough
Journal:  Proc SPIE Int Soc Opt Eng       Date:  2022-04-04

4.  A 25-reader performance study for hepatic metastasis detection: lessons from unsupervised learning.

Authors:  Scott S Hsieh; Akitoshi Inoue; Parvathy Sudhir Pillai; Hao Gong; David R Holmes; David A Cook; Shuai Leng; Lifeng Yu; Rickey E Carter; Joel G Fletcher; Cynthia H McCollough
Journal:  Proc SPIE Int Soc Opt Eng       Date:  2022-04-04

5.  Deep-learning model observer for a low-contrast hepatic metastases localization task in computed tomography.

Authors:  Hao Gong; Joel G Fletcher; Jay P Heiken; Michael L Wells; Shuai Leng; Cynthia H McCollough; Lifeng Yu
Journal:  Med Phys       Date:  2021-12-01       Impact factor: 4.506

6.  Observer Performance with Varying Radiation Dose and Reconstruction Methods for Detection of Hepatic Metastases.

Authors:  Joel G Fletcher; Jeff L Fidler; Sudhakar K Venkatesh; David M Hough; Naoki Takahashi; Lifeng Yu; Matthew Johnson; Shuai Leng; David R Holmes; Rickey Carter; Cynthia H McCollough
Journal:  Radiology       Date:  2018-09-11       Impact factor: 11.105

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

Authors:  Joel G Fletcher; David L Levin; Anne-Marie G Sykes; Rebecca M Lindell; Darin B White; Ronald S Kuzo; Vighnesh Suresh; Lifeng Yu; Shuai Leng; David R Holmes; Akitoshi Inoue; Matthew P Johnson; Rickey E Carter; Cynthia H McCollough
Journal:  Radiology       Date:  2020-09-29       Impact factor: 11.105

8.  Reader Performance as a Function of Patient Size for the Detection of Hepatic Metastases.

Authors:  Hao Gong; Lifeng Yu; Shuai Leng; Joel G Fletcher; Cynthia H McCollough
Journal:  J Comput Assist Tomogr       Date:  2021 Nov-Dec 01       Impact factor: 1.826

9.  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

10.  Can iterative reconstruction algorithms replace tube loading compensation in low kVp hepatic CT? Subjective versus objective image quality.

Authors:  Fredrik Holmquist; Marcus Söderberg; Ulf Nyman; Tobias Fält; Roger Siemund; Mats Geijer
Journal:  Acta Radiol Open       Date:  2020-03-16
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