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Igarashi K, Imai K, Matsushima S, Yamauchi-Kawaura C, Fujii K. Development and validation of the effective CNR analysis method for evaluating the contrast resolution of CT images. Phys Eng Sci Med 2024; 47:717-727. [PMID: 38451464 PMCID: PMC11166862 DOI: 10.1007/s13246-024-01400-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2023] [Accepted: 02/04/2024] [Indexed: 03/08/2024]
Abstract
Contrast resolution is an important index for evaluating the signal detectability of computed tomographic (CT) images. Recently, various noise reduction algorithms, such as iterative reconstruction (IR) and deep learning reconstruction (DLR), have been proposed to reduce the image noise in CT images. However, these algorithms cause changes in the image noise texture and blurred image signals in CT images. Furthermore, the contrast-to-noise ratio (CNR) cannot be accurately evaluated in CT images reconstructed using noise reduction methods. Therefore, in this study, we devised a new method, namely, "effective CNR analysis," for evaluating the contrast resolution of CT images. We verified whether the proposed algorithm could evaluate the effective contrast resolution based on the signal detectability of CT images. The findings showed that the effective CNR values obtained using the proposed method correlated well with the subjective visual impressions of CT images. To investigate whether signal detectability was appropriately evaluated using effective CNR analysis, the conventional CNR analysis method was compared with the proposed method. The CNRs of the IR and DLR images calculated using conventional CNR analysis were 13.2 and 10.7, respectively. By contrast, those calculated using the effective CNR analysis were estimated to be 0.7 and 1.1, respectively. Considering that the signal visibility of DLR images was superior to that of IR images, our proposed effective CNR analysis was shown to be appropriate for evaluating the contrast resolution of CT images.
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Affiliation(s)
- Kengo Igarashi
- Department of Integrated Health Sciences, Nagoya University Graduate School of Medicine, 1-1-20, Daiko-Minami, Higashi-ku, Nagoya, Aichi, 461-8673, Japan.
| | - Kuniharu Imai
- Department of Integrated Health Sciences, Nagoya University Graduate School of Medicine, 1-1-20, Daiko-Minami, Higashi-ku, Nagoya, Aichi, 461-8673, Japan
| | - Shigeru Matsushima
- Department of Integrated Health Sciences, Nagoya University Graduate School of Medicine, 1-1-20, Daiko-Minami, Higashi-ku, Nagoya, Aichi, 461-8673, Japan
| | - Chiyo Yamauchi-Kawaura
- Department of Integrated Health Sciences, Nagoya University Graduate School of Medicine, 1-1-20, Daiko-Minami, Higashi-ku, Nagoya, Aichi, 461-8673, Japan
| | - Keisuke Fujii
- Department of Integrated Health Sciences, Nagoya University Graduate School of Medicine, 1-1-20, Daiko-Minami, Higashi-ku, Nagoya, Aichi, 461-8673, Japan
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Mohammadinejad P, Khandelwal A, Inoue A, Takahashi H, Yalon M, Long Z, Halaweish AF, Leng S, Yu L, Lee YS, McCollough CH, Fletcher JG. Utility of an automatic adaptive iterative metal artifact reduction AiMAR algorithm in improving CT imaging of patients with hip prostheses evaluated for suspected bladder malignancy. Abdom Radiol (NY) 2022; 47:2158-2167. [PMID: 35320381 DOI: 10.1007/s00261-022-03475-8] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2021] [Revised: 02/22/2022] [Accepted: 02/23/2022] [Indexed: 11/25/2022]
Abstract
PURPOSE To compare the utility of a novel metal artifact reduction algorithm to standard imaging in improving visualization of key structures, diagnostic confidence, and patient-level confidence in malignancy in patients with suspected bladder cancer. METHODS Patients with hip implants undergoing CT urography for suspected bladder malignancy were enrolled. Images were reconstructed using 3 methods: (1) Filtered Back Projection (FBP), (2) Iterative Metal Artifact Reduction (iMAR), and (3) Adaptive Iterative Metal Artifact Reduction (AiMAR) strength 4. In multiple reading sessions, three radiologists graded visualization of critical anatomic structures and artifact severity (6-point scales, lower scores desirable), and diagnostic confidence in blinded fashion. They also graded patient-level confidence in malignancy based on imaging findings in each patient. RESULTS Thirty-two patients (8 females) with a mean age of 74.5 ± 8.5 years were included. The median (range) visualization scores for FBP, iMAR, and AiMAR were 3.6 (1.1-4.9), 1.6 (0.3-2.8), and 1.6 (0.3-2.6), respectively. Both iMAR and AiMAR had anatomic visualization and artifact scores better than FBP (P < 0.001 for both) and similar to each other (P > 0.05). Structures with the most improvement in visualization score with the use of metal artifact reduction algorithms included the obturator internus muscle, internal and external iliac nodal chains, and vagina. iMAR and AiMAR improved diagnostic confidence (P < 0.001) and patient-level confidence in malignancy (P ≤ 0.24). CONCLUSION For patients with hip prostheses and suspected bladder malignancy, the use of iMAR or AiMAR was shown to significantly reduce metal artifacts, thus improving diagnostic confidence and patient-level confidence in malignancy.
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Affiliation(s)
- Payam Mohammadinejad
- Department of Radiology, Mayo Clinic, 200 First St SW, Rochester, MN, 55905, USA
| | - Ashish Khandelwal
- Department of Radiology, Mayo Clinic, 200 First St SW, Rochester, MN, 55905, USA
| | - Akitoshi Inoue
- Department of Radiology, Mayo Clinic, 200 First St SW, Rochester, MN, 55905, USA
| | - Hiroaki Takahashi
- Department of Radiology, Mayo Clinic, 200 First St SW, Rochester, MN, 55905, USA
| | - Mariana Yalon
- Department of Radiology, Mayo Clinic, 200 First St SW, Rochester, MN, 55905, USA
| | - Zaiyang Long
- Department of Radiology, Mayo Clinic, 200 First St SW, Rochester, MN, 55905, USA
| | - Ahmed F Halaweish
- Siemens Medical Solutions USA, 40 Liberty Boulevard, Malvern, PA, 19355, USA
| | - Shuai Leng
- Department of Radiology, Mayo Clinic, 200 First St SW, Rochester, MN, 55905, USA
| | - Lifeng Yu
- Department of Radiology, Mayo Clinic, 200 First St SW, Rochester, MN, 55905, USA
| | - Yong S Lee
- Department of Radiology, Mayo Clinic, 200 First St SW, Rochester, MN, 55905, USA
| | - Cynthia H McCollough
- Department of Radiology, Mayo Clinic, 200 First St SW, Rochester, MN, 55905, USA
| | - Joel G Fletcher
- Department of Radiology, Mayo Clinic, 200 First St SW, Rochester, MN, 55905, USA.
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Fletcher JG, Levin DL, Sykes AMG, Lindell RM, White DB, Kuzo RS, Suresh V, Yu L, Leng S, Holmes DR, Inoue A, Johnson MP, Carter RE, McCollough CH. Observer Performance for Detection of Pulmonary Nodules at Chest CT over a Large Range of Radiation Dose Levels. Radiology 2020; 297:699-707. [PMID: 32990514 DOI: 10.1148/radiol.2020200969] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
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.
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Affiliation(s)
- Joel G Fletcher
- From the Department of Radiology (J.G.F., D.L.L., A.M.G.S., R.M.L., D.B.W., R.S.K., V.S., L.Y., S.L., A.I., C.H.M.), Department of Physiology and Biomedical Engineering (D.R.H.), and Department of Health Science Research (M.P.J.), Mayo Clinic, 200 First St SW, Rochester, MN 55905; and Department of Health Science Research, Mayo Clinic, Jacksonville, Fla (R.E.C.)
| | - David L Levin
- From the Department of Radiology (J.G.F., D.L.L., A.M.G.S., R.M.L., D.B.W., R.S.K., V.S., L.Y., S.L., A.I., C.H.M.), Department of Physiology and Biomedical Engineering (D.R.H.), and Department of Health Science Research (M.P.J.), Mayo Clinic, 200 First St SW, Rochester, MN 55905; and Department of Health Science Research, Mayo Clinic, Jacksonville, Fla (R.E.C.)
| | - Anne-Marie G Sykes
- From the Department of Radiology (J.G.F., D.L.L., A.M.G.S., R.M.L., D.B.W., R.S.K., V.S., L.Y., S.L., A.I., C.H.M.), Department of Physiology and Biomedical Engineering (D.R.H.), and Department of Health Science Research (M.P.J.), Mayo Clinic, 200 First St SW, Rochester, MN 55905; and Department of Health Science Research, Mayo Clinic, Jacksonville, Fla (R.E.C.)
| | - Rebecca M Lindell
- From the Department of Radiology (J.G.F., D.L.L., A.M.G.S., R.M.L., D.B.W., R.S.K., V.S., L.Y., S.L., A.I., C.H.M.), Department of Physiology and Biomedical Engineering (D.R.H.), and Department of Health Science Research (M.P.J.), Mayo Clinic, 200 First St SW, Rochester, MN 55905; and Department of Health Science Research, Mayo Clinic, Jacksonville, Fla (R.E.C.)
| | - Darin B White
- From the Department of Radiology (J.G.F., D.L.L., A.M.G.S., R.M.L., D.B.W., R.S.K., V.S., L.Y., S.L., A.I., C.H.M.), Department of Physiology and Biomedical Engineering (D.R.H.), and Department of Health Science Research (M.P.J.), Mayo Clinic, 200 First St SW, Rochester, MN 55905; and Department of Health Science Research, Mayo Clinic, Jacksonville, Fla (R.E.C.)
| | - Ronald S Kuzo
- From the Department of Radiology (J.G.F., D.L.L., A.M.G.S., R.M.L., D.B.W., R.S.K., V.S., L.Y., S.L., A.I., C.H.M.), Department of Physiology and Biomedical Engineering (D.R.H.), and Department of Health Science Research (M.P.J.), Mayo Clinic, 200 First St SW, Rochester, MN 55905; and Department of Health Science Research, Mayo Clinic, Jacksonville, Fla (R.E.C.)
| | - Vighnesh Suresh
- From the Department of Radiology (J.G.F., D.L.L., A.M.G.S., R.M.L., D.B.W., R.S.K., V.S., L.Y., S.L., A.I., C.H.M.), Department of Physiology and Biomedical Engineering (D.R.H.), and Department of Health Science Research (M.P.J.), Mayo Clinic, 200 First St SW, Rochester, MN 55905; and Department of Health Science Research, Mayo Clinic, Jacksonville, Fla (R.E.C.)
| | - Lifeng Yu
- From the Department of Radiology (J.G.F., D.L.L., A.M.G.S., R.M.L., D.B.W., R.S.K., V.S., L.Y., S.L., A.I., C.H.M.), Department of Physiology and Biomedical Engineering (D.R.H.), and Department of Health Science Research (M.P.J.), Mayo Clinic, 200 First St SW, Rochester, MN 55905; and Department of Health Science Research, Mayo Clinic, Jacksonville, Fla (R.E.C.)
| | - Shuai Leng
- From the Department of Radiology (J.G.F., D.L.L., A.M.G.S., R.M.L., D.B.W., R.S.K., V.S., L.Y., S.L., A.I., C.H.M.), Department of Physiology and Biomedical Engineering (D.R.H.), and Department of Health Science Research (M.P.J.), Mayo Clinic, 200 First St SW, Rochester, MN 55905; and Department of Health Science Research, Mayo Clinic, Jacksonville, Fla (R.E.C.)
| | - David R Holmes
- From the Department of Radiology (J.G.F., D.L.L., A.M.G.S., R.M.L., D.B.W., R.S.K., V.S., L.Y., S.L., A.I., C.H.M.), Department of Physiology and Biomedical Engineering (D.R.H.), and Department of Health Science Research (M.P.J.), Mayo Clinic, 200 First St SW, Rochester, MN 55905; and Department of Health Science Research, Mayo Clinic, Jacksonville, Fla (R.E.C.)
| | - Akitoshi Inoue
- From the Department of Radiology (J.G.F., D.L.L., A.M.G.S., R.M.L., D.B.W., R.S.K., V.S., L.Y., S.L., A.I., C.H.M.), Department of Physiology and Biomedical Engineering (D.R.H.), and Department of Health Science Research (M.P.J.), Mayo Clinic, 200 First St SW, Rochester, MN 55905; and Department of Health Science Research, Mayo Clinic, Jacksonville, Fla (R.E.C.)
| | - Matthew P Johnson
- From the Department of Radiology (J.G.F., D.L.L., A.M.G.S., R.M.L., D.B.W., R.S.K., V.S., L.Y., S.L., A.I., C.H.M.), Department of Physiology and Biomedical Engineering (D.R.H.), and Department of Health Science Research (M.P.J.), Mayo Clinic, 200 First St SW, Rochester, MN 55905; and Department of Health Science Research, Mayo Clinic, Jacksonville, Fla (R.E.C.)
| | - Rickey E Carter
- From the Department of Radiology (J.G.F., D.L.L., A.M.G.S., R.M.L., D.B.W., R.S.K., V.S., L.Y., S.L., A.I., C.H.M.), Department of Physiology and Biomedical Engineering (D.R.H.), and Department of Health Science Research (M.P.J.), Mayo Clinic, 200 First St SW, Rochester, MN 55905; and Department of Health Science Research, Mayo Clinic, Jacksonville, Fla (R.E.C.)
| | - Cynthia H McCollough
- From the Department of Radiology (J.G.F., D.L.L., A.M.G.S., R.M.L., D.B.W., R.S.K., V.S., L.Y., S.L., A.I., C.H.M.), Department of Physiology and Biomedical Engineering (D.R.H.), and Department of Health Science Research (M.P.J.), Mayo Clinic, 200 First St SW, Rochester, MN 55905; and Department of Health Science Research, Mayo Clinic, Jacksonville, Fla (R.E.C.)
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Mileto A, Guimaraes LS, McCollough CH, Fletcher JG, Yu L. State of the Art in Abdominal CT: The Limits of Iterative Reconstruction Algorithms. Radiology 2019; 293:491-503. [DOI: 10.1148/radiol.2019191422] [Citation(s) in RCA: 77] [Impact Index Per Article: 15.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Affiliation(s)
- Achille Mileto
- From the Department of Radiology, University of Washington School of Medicine, Seattle, Wash (A.M.); Joint Department of Medical Imaging, Sinai Health System, University of Toronto, Toronto, Ontario, Canada (L.S.G.); and Department of Radiology, Mayo Clinic, 200 First St SW, Rochester, MN 55905 (C.H.M., J.G.F., L.Y.)
| | - Luis S. Guimaraes
- From the Department of Radiology, University of Washington School of Medicine, Seattle, Wash (A.M.); Joint Department of Medical Imaging, Sinai Health System, University of Toronto, Toronto, Ontario, Canada (L.S.G.); and Department of Radiology, Mayo Clinic, 200 First St SW, Rochester, MN 55905 (C.H.M., J.G.F., L.Y.)
| | - Cynthia H. McCollough
- From the Department of Radiology, University of Washington School of Medicine, Seattle, Wash (A.M.); Joint Department of Medical Imaging, Sinai Health System, University of Toronto, Toronto, Ontario, Canada (L.S.G.); and Department of Radiology, Mayo Clinic, 200 First St SW, Rochester, MN 55905 (C.H.M., J.G.F., L.Y.)
| | - Joel G. Fletcher
- From the Department of Radiology, University of Washington School of Medicine, Seattle, Wash (A.M.); Joint Department of Medical Imaging, Sinai Health System, University of Toronto, Toronto, Ontario, Canada (L.S.G.); and Department of Radiology, Mayo Clinic, 200 First St SW, Rochester, MN 55905 (C.H.M., J.G.F., L.Y.)
| | - Lifeng Yu
- From the Department of Radiology, University of Washington School of Medicine, Seattle, Wash (A.M.); Joint Department of Medical Imaging, Sinai Health System, University of Toronto, Toronto, Ontario, Canada (L.S.G.); and Department of Radiology, Mayo Clinic, 200 First St SW, Rochester, MN 55905 (C.H.M., J.G.F., L.Y.)
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Reducing radiation dose for multi-phase contrast-enhanced dual energy renal CT: pilot study evaluating prior iterative reconstruction. Abdom Radiol (NY) 2019; 44:3350-3358. [PMID: 31422439 DOI: 10.1007/s00261-019-02150-9] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
Abstract
PURPOSE Prior iterative reconstruction (PIR) uses spatial information from one phase of enhancement to reduce image noise in other phases. We sought to determine if PIR could reduce radiation dose while preserving observer performance and CT number at multi-phase dual energy (DE) renal CT. METHODS CT projection data from multi-phase DE renal CT examinations were collected. Images corresponding to 40% radiation dose were reconstructed using validated noise insertion and PIR. Three genitourinary radiologists examined routine and 40% dose PIR images. Probability of malignancy was assessed [from 0 to 100] with malignancy assumed at probability ≥ 75. Observer performance was compared on a per patient and per lesion level. CT number accuracy was measured. RESULTS Twenty-three patients had 49 renal lesions (11 solid renal neoplasms). CT number was nearly identical between techniques (mean CT number difference: unenhanced 2 ± 2 HU; enhanced 4 ± 4 HU). AUC for malignancy was similar between multi-phase routine dose DE and lower dose PIR images [per patient: 0.950 vs. 0.916 (p = 0.356); per lesion: 0.931 vs. 0.884 (p = 0.304)]. Per patient sensitivity was also similar (78% routine dose vs. 82% lower dose [p ≥ 0.99]), as was specificity (91% routine dose vs. 93% lower dose PIR [p > 0.99]), with similar findings on a per lesion level. Subjective image quality was also similar (p = 0.34). CONCLUSIONS Prior iterative reconstruction is a new reconstruction method for multi-phase CT examinations that promises to facilitate radiation dose reduction by over 50% for multi-phase DE renal CT exams without compromising CT number or observer performance.
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Grajo JR, Sahani DV. Dual-Energy CT of the Abdomen and Pelvis: Radiation Dose Considerations. J Am Coll Radiol 2018; 15:1128-1132. [DOI: 10.1016/j.jacr.2017.08.012] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2017] [Revised: 08/05/2017] [Accepted: 08/14/2017] [Indexed: 12/12/2022]
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Favazza CP, Ferrero A, Yu L, Leng S, McMillan KL, McCollough CH. Use of a channelized Hotelling observer to assess CT image quality and optimize dose reduction for iteratively reconstructed images. J Med Imaging (Bellingham) 2017; 4:031213. [PMID: 28983493 DOI: 10.1117/1.jmi.4.3.031213] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2017] [Accepted: 09/18/2017] [Indexed: 11/14/2022] Open
Abstract
The use of iterative reconstruction (IR) algorithms in CT generally decreases image noise and enables dose reduction. However, the amount of dose reduction possible using IR without sacrificing diagnostic performance is difficult to assess with conventional image quality metrics. Through this investigation, achievable dose reduction using a commercially available IR algorithm without loss of low contrast spatial resolution was determined with a channelized Hotelling observer (CHO) model and used to optimize a clinical abdomen/pelvis exam protocol. A phantom containing 21 low contrast disks-three different contrast levels and seven different diameters-was imaged at different dose levels. Images were created with filtered backprojection (FBP) and IR. The CHO was tasked with detecting the low contrast disks. CHO performance indicated dose could be reduced by 22% to 25% without compromising low contrast detectability (as compared to full-dose FBP images) whereas 50% or more dose reduction significantly reduced detection performance. Importantly, default settings for the scanner and protocol investigated reduced dose by upward of 75%. Subsequently, CHO-based protocol changes to the default protocol yielded images of higher quality and doses more consistent with values from a larger, dose-optimized scanner fleet. CHO assessment provided objective data to successfully optimize a clinical CT acquisition protocol.
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Affiliation(s)
| | - Andrea Ferrero
- Mayo Clinic, Department of Radiology, Rochester, Minnesota, United States
| | - Lifeng Yu
- Mayo Clinic, Department of Radiology, Rochester, Minnesota, United States
| | - Shuai Leng
- Mayo Clinic, Department of Radiology, Rochester, Minnesota, United States
| | - Kyle L McMillan
- Mayo Clinic, Department of Radiology, Rochester, Minnesota, United States
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Fletcher JG, Yu L, Fidler JL, Levin DL, DeLone DR, Hough DM, Takahashi N, Venkatesh SK, Sykes AMG, White D, Lindell RM, Kotsenas AL, Campeau NG, Lehman VT, Bartley AC, Leng S, Holmes DR, Toledano AY, Carter RE, McCollough CH. Estimation of Observer Performance for Reduced Radiation Dose Levels in CT: Eliminating Reduced Dose Levels That Are Too Low Is the First Step. Acad Radiol 2017; 24:876-890. [PMID: 28262519 PMCID: PMC6481673 DOI: 10.1016/j.acra.2016.12.017] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2016] [Revised: 12/23/2016] [Accepted: 12/26/2016] [Indexed: 12/20/2022]
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.
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Affiliation(s)
- Joel G Fletcher
- Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN 55905.
| | - Lifeng Yu
- Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN 55905
| | - Jeff L Fidler
- Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN 55905
| | - David L Levin
- Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN 55905
| | - David R DeLone
- Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN 55905
| | - David M Hough
- Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN 55905
| | - Naoki Takahashi
- Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN 55905
| | | | - Anne-Marie G Sykes
- Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN 55905
| | - Darin White
- Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN 55905
| | - Rebecca M Lindell
- Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN 55905
| | - Amy L Kotsenas
- Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN 55905
| | - Norbert G Campeau
- Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN 55905
| | - Vance T Lehman
- Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN 55905
| | - Adam C Bartley
- Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota
| | - Shuai Leng
- Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN 55905
| | - David R Holmes
- Department of Physiology and Biomedical Engineering, Mayo Clinic, Rochester, Minnesota
| | | | - Rickey E Carter
- Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota
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Goenka AH, Herts BR, Dong F, Obuchowski NA, Primak AN, Karim W, Baker ME. Image Noise, CNR, and Detectability of Low-Contrast, Low-Attenuation Liver Lesions in a Phantom: Effects of Radiation Exposure, Phantom Size, Integrated Circuit Detector, and Iterative Reconstruction. Radiology 2016; 280:475-82. [DOI: 10.1148/radiol.2016151621] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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MacDougall RD, Kleinman PL, Callahan MJ. Size-based protocol optimization using automatic tube current modulation and automatic kV selection in computed tomography. J Appl Clin Med Phys 2016; 17:328-341. [PMID: 26894344 PMCID: PMC5690190 DOI: 10.1120/jacmp.v17i1.5756] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2015] [Revised: 08/19/2015] [Accepted: 08/14/2015] [Indexed: 11/23/2022] Open
Abstract
Size-based diagnostic reference ranges (DRRs) for contrast-enhanced pediatric abdominal computed tomography (CT) have been published in order to establish practical upper and lower limits of CTDI, DLP, and SSDE. Based on these DRRs, guidelines for establishing size-based SSDE target levels from the SSDE of a standard adult by applying a linear correction factor have been published and provide a great reference for dose optimization initiatives. The necessary step of designing manufacturer-specific CT protocols to achieve established SSDE targets is the responsibility of the Qualified Medical Physicist. The task is straightforward if fixed-mA protocols are used, however, more difficult when automatic exposure control (AEC) and automatic kV selection are considered. In such cases, the physicist must deduce the operation of AEC algorithms from technical documentation or through testing, using a wide range of phantom sizes. Our study presents the results of such testing using anthropomorphic phantoms ranging in size from the newborn to the obese adult. The effect of each user-controlled parameter was modeled for a single-manufacturer AEC algorithm (Siemens CARE Dose4D) and automatic kV selection algorithm (Siemens CARE kV). Based on the results presented in this study, a process for designing mA-modulated, pediatric abdominal CT protocols that achieve user-defined SSDE and kV targets is described.
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Ehman EC, Yu L, Manduca A, Hara AK, Shiung MM, Jondal D, Lake DS, Paden RG, Blezek DJ, Bruesewitz MR, McCollough CH, Hough DM, Fletcher JG. Methods for clinical evaluation of noise reduction techniques in abdominopelvic CT. Radiographics 2015; 34:849-62. [PMID: 25019428 DOI: 10.1148/rg.344135128] [Citation(s) in RCA: 93] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
Most noise reduction methods involve nonlinear processes, and objective evaluation of image quality can be challenging, since image noise cannot be fully characterized on the sole basis of the noise level at computed tomography (CT). Noise spatial correlation (or noise texture) is closely related to the detection and characterization of low-contrast objects and may be quantified by analyzing the noise power spectrum. High-contrast spatial resolution can be measured using the modulation transfer function and section sensitivity profile and is generally unaffected by noise reduction. Detectability of low-contrast lesions can be evaluated subjectively at varying dose levels using phantoms containing low-contrast objects. Clinical applications with inherent high-contrast abnormalities (eg, CT for renal calculi, CT enterography) permit larger dose reductions with denoising techniques. In low-contrast tasks such as detection of metastases in solid organs, dose reduction is substantially more limited by loss of lesion conspicuity due to loss of low-contrast spatial resolution and coarsening of noise texture. Existing noise reduction strategies for dose reduction have a substantial impact on lowering the radiation dose at CT. To preserve the diagnostic benefit of CT examination, thoughtful utilization of these strategies must be based on the inherent lesion-to-background contrast and the anatomy of interest. The authors provide an overview of existing noise reduction strategies for low-dose abdominopelvic CT, including analytic reconstruction, image and projection space denoising, and iterative reconstruction; review qualitative and quantitative tools for evaluating these strategies; and discuss the strengths and limitations of individual noise reduction methods.
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Affiliation(s)
- Eric C Ehman
- From the Departments of Radiology (E.C.E., L.Y., A.M., M.M.S., D.J., M.R.B., C.H.M., D.M.H., J.G.F.) and Biomedical Engineering (D.S.L., D.J.B.), Mayo Clinic, 200 First St SW, Rochester, MN 55905; and Department of Radiology, Mayo Clinic, Scottsdale, Ariz (A.K.H., R.G.P.)
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Iterative Reconstruction Leads to Increased Subjective and Objective Image Quality in Cranial CT in Patients With Stroke. AJR Am J Roentgenol 2015; 205:618-22. [PMID: 26295650 DOI: 10.2214/ajr.15.14389] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
OBJECTIVE The purpose of this study was to determine whether iterative reconstruction improves the quality of cranial CT (CCT) images of stroke patients. MATERIALS AND METHODS Fifty-one CCT studies of patients with infarction performed with either a low (260 mAs; n = 21) or standard (340 mAs; n = 30) dose were reconstructed with both filtered back projection (FBP) and sinogram-affirmed iterative reconstruction (SAFIRE) with five strength levels (S1-S5). The resulting six image sets (one FBP and one each for SAFIRE levels S1-S5) were rated separately by two blinded radiologists in terms of conspicuity of infarcted areas on a 5-point scale. Noise and infarct-to-normal brain as well as medullary-to-cortical contrast-to-noise ratios (CNRs) were measured. Ratings, noise, and CNRs were intraindividually compared within the same dose group (Fisher exact test) and interindividually between the different dose groups (Wilcoxon-Mann-Whitney U test). RESULTS The strength level S4 showed the best conspicuity of infarcted areas. Compared with FBP, SAFIRE S4 statistically significantly (p < 0.01) reduced noise and improved CNRs without statistically significant differences in all subjective and objective criteria (p > 0.01) when the dose was reduced. Patients examined with a 260-mAs low-dose were exposed to a statistically significantly lower dose (1.77 vs 2.33 mSv; p < 0.01). CONCLUSION Iterative reconstruction (SAFIRE at strength level S4) leads to increased subjective and objective image quality in CCT and allows dose reduction (-24%) without losses in the demarcation of ischemic lesions.
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Bodelle B, Isler S, Scholtz JE, Frellesen C, Luboldt W, Vogl TJ, Beeres M. Benefits of sinogram-affirmed iterative reconstruction in 0.4 mSv ultra-low-dose CT of the upper abdomen following transarterial chemoembolisation: comparison to low-dose and standard-dose CT and filtered back projection technique. Clin Radiol 2015; 71:e11-5. [PMID: 26521185 DOI: 10.1016/j.crad.2015.10.001] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2015] [Revised: 09/30/2015] [Accepted: 10/01/2015] [Indexed: 12/16/2022]
Abstract
AIM To evaluate the advantage of sinogram-affirmed iterative reconstruction (SIR) compared to filtered back projection (FBP) in upper abdomen computed tomography (CT) after transarterial chemoembolisation (TACE) at different tube currents. MATERIALS AND METHODS The study was approved by the institutional review board. Written informed consent was obtained from all patients. Post-TACE CT was performed with different tube currents successively varied in four steps (180, 90, 45 and 23 mAs) with 40 patients per group (mean age: 60±12 years, range: 23-85 years, sex: 70 female, 90 male). The data were reconstructed with standard FBP and five different SIR strengths. Image quality was independently rated by two readers on a five-point scale. High (Lipiodol-to-liver) as well as low (liver-to-fat) contrast-to-noise ratios (CNRs) were intra-individually compared within one dose to determine the optimal strength (S1-S5) and inter-individually between different doses to determine the possibility of dose reduction using the Kruskal-Wallis test. RESULTS Subjective image quality and objective CNR analysis were concordant: intra-individually, SIR was significantly (p<0.001) superior to FBP. Inter-individually, regarding different doses (180 versus 23 ref mAs), there was no significant (p=1.00) difference when using S5 SIR at 23 mAs instead of FBP. CONCLUSION SIR allows for an 88% dose reduction from 3.43 to 0.4 mSv in unenhanced CT of the liver following TACE without subjective or objective loss in image quality.
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Affiliation(s)
- B Bodelle
- Department of Diagnostic and Interventional Radiology, Goethe University, Theodor-Stern-Kai 7, 60590 Frankfurt, Germany.
| | - S Isler
- Department of Diagnostic and Interventional Radiology, Goethe University, Theodor-Stern-Kai 7, 60590 Frankfurt, Germany
| | - J-E Scholtz
- Department of Diagnostic and Interventional Radiology, Goethe University, Theodor-Stern-Kai 7, 60590 Frankfurt, Germany
| | - C Frellesen
- Department of Diagnostic and Interventional Radiology, Goethe University, Theodor-Stern-Kai 7, 60590 Frankfurt, Germany
| | - W Luboldt
- Department of Diagnostic and Interventional Radiology, Goethe University, Theodor-Stern-Kai 7, 60590 Frankfurt, Germany
| | - T J Vogl
- Department of Diagnostic and Interventional Radiology, Goethe University, Theodor-Stern-Kai 7, 60590 Frankfurt, Germany
| | - M Beeres
- Department of Diagnostic and Interventional Radiology, Goethe University, Theodor-Stern-Kai 7, 60590 Frankfurt, Germany
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Moorin RE, Gibson DAJ, Forsyth RK, Fox R. The Impact of Iterative Reconstruction on Computed Tomography Radiation Dosimetry: Evaluation in a Routine Clinical Setting. PLoS One 2015; 10:e0138329. [PMID: 26381145 PMCID: PMC4575140 DOI: 10.1371/journal.pone.0138329] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2014] [Accepted: 08/28/2015] [Indexed: 01/31/2023] Open
Abstract
Purpose To evaluate the effect of introduction of iterative reconstruction as a mandated software upgrade on radiation dosimetry in routine clinical practice over a range of computed tomography examinations. Methods Random samples of scanning data were extracted from a centralised Picture Archiving Communication System pertaining to 10 commonly performed computed tomography examination types undertaken at two hospitals in Western Australia, before and after the introduction of iterative reconstruction. Changes in the mean dose length product and effective dose were evaluated along with estimations of associated changes to annual cancer incidence. Results We observed statistically significant reductions in the effective radiation dose for head computed tomography (22–27%) consistent with those reported in the literature. In contrast the reductions observed for non-contrast chest (37–47%); chest pulmonary embolism study (28%), chest/abdominal/pelvic study (16%) and thoracic spine (39%) computed tomography. Statistically significant reductions in radiation dose were not identified in angiographic computed tomography. Dose reductions translated to substantial lowering of the lifetime attributable risk, especially for younger females, and estimated numbers of incident cancers. Conclusion Reduction of CT dose is a priority Iterative reconstruction algorithms have the potential to significantly assist with dose reduction across a range of protocols. However, this reduction in dose is achieved via reductions in image noise. Fully realising the potential dose reduction of iterative reconstruction requires the adjustment of image factors and forgoing the noise reduction potential of the iterative algorithm. Our study has demonstrated a reduction in radiation dose for some scanning protocols, but not to the extent experimental studies had previously shown or in all protocols expected, raising questions about the extent to which iterative reconstruction achieves dose reduction in real world clinical practice.
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Affiliation(s)
- Rachael E. Moorin
- School of Public Health, Curtin University, GPO Box U1987, Perth Western Australia, 6845, Australia
- School of Population Health, University of Western Australia, 35 Stirling Highway, Crawley, Perth Western Australia, 6009, Australia
- * E-mail:
| | - David A. J. Gibson
- School of Public Health, Curtin University, GPO Box U1987, Perth Western Australia, 6845, Australia
| | - Rene K. Forsyth
- Department of Medical Imaging Science, Curtin University, GPO Box U1987, Perth, Western Australia, 6845, Australia
| | - Richard Fox
- School of Physics, University of Western Australia, 35 Stirling Highway, Crawley, Perth Western Australia, 6009, Australia
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Geyer LL, Schoepf UJ, Meinel FG, Nance JW, Bastarrika G, Leipsic JA, Paul NS, Rengo M, Laghi A, De Cecco CN. State of the Art: Iterative CT Reconstruction Techniques. Radiology 2015. [PMID: 26203706 DOI: 10.1148/radiol.2015132766] [Citation(s) in RCA: 398] [Impact Index Per Article: 44.2] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
Affiliation(s)
- Lucas L Geyer
- From the Department of Radiology and Radiological Science, Medical University of South Carolina, Ashley River Tower, MSC 226, 25 Courtenay Dr, Charleston, SC 29425 (L.L.G., U.J.S., F.G.M., J.W.N., C.N.D.); Department of Radiology, Sunnybrook Health Sciences Centre, Toronto, Ont, Canada (G.B.); Department of Radiology, University of British Columbia, Vancouver, BC, Canada (J.A.L.); Department of Radiology, Toronto General Hospital, University of Toronto, Toronto, Ont, Canada (N.S.P.); and Department of Radiological Sciences, Oncology and Pathology, University of Rome Sapienza-Polo Pontino, Latina, Italy (M.R., A.L., C.N.D.)
| | - U Joseph Schoepf
- From the Department of Radiology and Radiological Science, Medical University of South Carolina, Ashley River Tower, MSC 226, 25 Courtenay Dr, Charleston, SC 29425 (L.L.G., U.J.S., F.G.M., J.W.N., C.N.D.); Department of Radiology, Sunnybrook Health Sciences Centre, Toronto, Ont, Canada (G.B.); Department of Radiology, University of British Columbia, Vancouver, BC, Canada (J.A.L.); Department of Radiology, Toronto General Hospital, University of Toronto, Toronto, Ont, Canada (N.S.P.); and Department of Radiological Sciences, Oncology and Pathology, University of Rome Sapienza-Polo Pontino, Latina, Italy (M.R., A.L., C.N.D.)
| | - Felix G Meinel
- From the Department of Radiology and Radiological Science, Medical University of South Carolina, Ashley River Tower, MSC 226, 25 Courtenay Dr, Charleston, SC 29425 (L.L.G., U.J.S., F.G.M., J.W.N., C.N.D.); Department of Radiology, Sunnybrook Health Sciences Centre, Toronto, Ont, Canada (G.B.); Department of Radiology, University of British Columbia, Vancouver, BC, Canada (J.A.L.); Department of Radiology, Toronto General Hospital, University of Toronto, Toronto, Ont, Canada (N.S.P.); and Department of Radiological Sciences, Oncology and Pathology, University of Rome Sapienza-Polo Pontino, Latina, Italy (M.R., A.L., C.N.D.)
| | - John W Nance
- From the Department of Radiology and Radiological Science, Medical University of South Carolina, Ashley River Tower, MSC 226, 25 Courtenay Dr, Charleston, SC 29425 (L.L.G., U.J.S., F.G.M., J.W.N., C.N.D.); Department of Radiology, Sunnybrook Health Sciences Centre, Toronto, Ont, Canada (G.B.); Department of Radiology, University of British Columbia, Vancouver, BC, Canada (J.A.L.); Department of Radiology, Toronto General Hospital, University of Toronto, Toronto, Ont, Canada (N.S.P.); and Department of Radiological Sciences, Oncology and Pathology, University of Rome Sapienza-Polo Pontino, Latina, Italy (M.R., A.L., C.N.D.)
| | - Gorka Bastarrika
- From the Department of Radiology and Radiological Science, Medical University of South Carolina, Ashley River Tower, MSC 226, 25 Courtenay Dr, Charleston, SC 29425 (L.L.G., U.J.S., F.G.M., J.W.N., C.N.D.); Department of Radiology, Sunnybrook Health Sciences Centre, Toronto, Ont, Canada (G.B.); Department of Radiology, University of British Columbia, Vancouver, BC, Canada (J.A.L.); Department of Radiology, Toronto General Hospital, University of Toronto, Toronto, Ont, Canada (N.S.P.); and Department of Radiological Sciences, Oncology and Pathology, University of Rome Sapienza-Polo Pontino, Latina, Italy (M.R., A.L., C.N.D.)
| | - Jonathon A Leipsic
- From the Department of Radiology and Radiological Science, Medical University of South Carolina, Ashley River Tower, MSC 226, 25 Courtenay Dr, Charleston, SC 29425 (L.L.G., U.J.S., F.G.M., J.W.N., C.N.D.); Department of Radiology, Sunnybrook Health Sciences Centre, Toronto, Ont, Canada (G.B.); Department of Radiology, University of British Columbia, Vancouver, BC, Canada (J.A.L.); Department of Radiology, Toronto General Hospital, University of Toronto, Toronto, Ont, Canada (N.S.P.); and Department of Radiological Sciences, Oncology and Pathology, University of Rome Sapienza-Polo Pontino, Latina, Italy (M.R., A.L., C.N.D.)
| | - Narinder S Paul
- From the Department of Radiology and Radiological Science, Medical University of South Carolina, Ashley River Tower, MSC 226, 25 Courtenay Dr, Charleston, SC 29425 (L.L.G., U.J.S., F.G.M., J.W.N., C.N.D.); Department of Radiology, Sunnybrook Health Sciences Centre, Toronto, Ont, Canada (G.B.); Department of Radiology, University of British Columbia, Vancouver, BC, Canada (J.A.L.); Department of Radiology, Toronto General Hospital, University of Toronto, Toronto, Ont, Canada (N.S.P.); and Department of Radiological Sciences, Oncology and Pathology, University of Rome Sapienza-Polo Pontino, Latina, Italy (M.R., A.L., C.N.D.)
| | - Marco Rengo
- From the Department of Radiology and Radiological Science, Medical University of South Carolina, Ashley River Tower, MSC 226, 25 Courtenay Dr, Charleston, SC 29425 (L.L.G., U.J.S., F.G.M., J.W.N., C.N.D.); Department of Radiology, Sunnybrook Health Sciences Centre, Toronto, Ont, Canada (G.B.); Department of Radiology, University of British Columbia, Vancouver, BC, Canada (J.A.L.); Department of Radiology, Toronto General Hospital, University of Toronto, Toronto, Ont, Canada (N.S.P.); and Department of Radiological Sciences, Oncology and Pathology, University of Rome Sapienza-Polo Pontino, Latina, Italy (M.R., A.L., C.N.D.)
| | - Andrea Laghi
- From the Department of Radiology and Radiological Science, Medical University of South Carolina, Ashley River Tower, MSC 226, 25 Courtenay Dr, Charleston, SC 29425 (L.L.G., U.J.S., F.G.M., J.W.N., C.N.D.); Department of Radiology, Sunnybrook Health Sciences Centre, Toronto, Ont, Canada (G.B.); Department of Radiology, University of British Columbia, Vancouver, BC, Canada (J.A.L.); Department of Radiology, Toronto General Hospital, University of Toronto, Toronto, Ont, Canada (N.S.P.); and Department of Radiological Sciences, Oncology and Pathology, University of Rome Sapienza-Polo Pontino, Latina, Italy (M.R., A.L., C.N.D.)
| | - Carlo N De Cecco
- From the Department of Radiology and Radiological Science, Medical University of South Carolina, Ashley River Tower, MSC 226, 25 Courtenay Dr, Charleston, SC 29425 (L.L.G., U.J.S., F.G.M., J.W.N., C.N.D.); Department of Radiology, Sunnybrook Health Sciences Centre, Toronto, Ont, Canada (G.B.); Department of Radiology, University of British Columbia, Vancouver, BC, Canada (J.A.L.); Department of Radiology, Toronto General Hospital, University of Toronto, Toronto, Ont, Canada (N.S.P.); and Department of Radiological Sciences, Oncology and Pathology, University of Rome Sapienza-Polo Pontino, Latina, Italy (M.R., A.L., C.N.D.)
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Iterative Reconstruction Techniques in Abdominopelvic CT: Technical Concepts and Clinical Implementation. AJR Am J Roentgenol 2015; 205:W19-31. [PMID: 26102414 DOI: 10.2214/ajr.14.13402] [Citation(s) in RCA: 47] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
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Fletcher JG, Yu L, Li Z, Manduca A, Blezek DJ, Hough DM, Venkatesh SK, Brickner GC, Cernigliaro JC, Hara AK, Fidler JL, Lake DS, Shiung M, Lewis D, Leng S, Augustine KE, Carter RE, Holmes DR, McCollough CH. Observer Performance in the Detection and Classification of Malignant Hepatic Nodules and Masses with CT Image-Space Denoising and Iterative Reconstruction. Radiology 2015; 276:465-78. [PMID: 26020436 DOI: 10.1148/radiol.2015141991] [Citation(s) in RCA: 48] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
PURPOSE To determine if lower-dose computed tomographic (CT) scans obtained with adaptive image-based noise reduction (adaptive nonlocal means [ANLM]) or iterative reconstruction (sinogram-affirmed iterative reconstruction [SAFIRE]) result in reduced observer performance in the detection of malignant hepatic nodules and masses compared with routine-dose scans obtained with filtered back projection (FBP). MATERIALS AND METHODS This study was approved by the institutional review board and was compliant with HIPAA. Informed consent was obtained from patients for the retrospective use of medical records for research purposes. CT projection data from 33 abdominal and 27 liver or pancreas CT examinations were collected (median volume CT dose index, 13.8 and 24.0 mGy, respectively). Hepatic malignancy was defined by progression or regression or with histopathologic findings. Lower-dose data were created by using a validated noise insertion method (10.4 mGy for abdominal CT and 14.6 mGy for liver or pancreas CT) and images reconstructed with FBP, ANLM, and SAFIRE. Four readers evaluated routine-dose FBP images and all lower-dose images, circumscribing liver lesions and selecting diagnosis. The jackknife free-response receiver operating characteristic figure of merit (FOM) was calculated on a per-malignant nodule or per-mass basis. Noninferiority was defined by the lower limit of the 95% confidence interval (CI) of the difference between lower-dose and routine-dose FOMs being less than -0.10. RESULTS Twenty-nine patients had 62 malignant hepatic nodules and masses. Estimated FOM differences between lower-dose FBP and lower-dose ANLM versus routine-dose FBP were noninferior (difference: -0.041 [95% CI: -0.090, 0.009] and -0.003 [95% CI: -0.052, 0.047], respectively). In patients with dedicated liver scans, lower-dose ANLM images were noninferior (difference: +0.015 [95% CI: -0.077, 0.106]), whereas lower-dose FBP images were not (difference -0.049 [95% CI: -0.140, 0.043]). In 37 patients with SAFIRE reconstructions, the three lower-dose alternatives were found to be noninferior to the routine-dose FBP. CONCLUSION At moderate levels of dose reduction, lower-dose FBP images without ANLM or SAFIRE were noninferior to routine-dose images for abdominal CT but not for liver or pancreas CT.
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Affiliation(s)
- Joel G Fletcher
- From the Departments of Radiology (J.G.F., L.Y., Z.L., D.M.H., S.K.V., J.L.F., M.S., D.L., S.L., C.H.M.), Physiology and Biomedical Engineering (A.M., D.S.L., K.E.A., D.R.H.), Information Technology (D.J.B.), and Biomedical Statistics and Informatics (R.E.C.), Mayo Clinic, 200 First St SW, Rochester, MN 55905; Department of Radiology, Mayo Clinic, Eau Claire, Wis (G.C.B.); Department of Radiology, Mayo Clinic, Jacksonville, Fla (J.C.C.); and Department of Radiology, Mayo Clinic, Scottsdale, Ariz (A.K.H.)
| | - Lifeng Yu
- From the Departments of Radiology (J.G.F., L.Y., Z.L., D.M.H., S.K.V., J.L.F., M.S., D.L., S.L., C.H.M.), Physiology and Biomedical Engineering (A.M., D.S.L., K.E.A., D.R.H.), Information Technology (D.J.B.), and Biomedical Statistics and Informatics (R.E.C.), Mayo Clinic, 200 First St SW, Rochester, MN 55905; Department of Radiology, Mayo Clinic, Eau Claire, Wis (G.C.B.); Department of Radiology, Mayo Clinic, Jacksonville, Fla (J.C.C.); and Department of Radiology, Mayo Clinic, Scottsdale, Ariz (A.K.H.)
| | - Zhoubo Li
- From the Departments of Radiology (J.G.F., L.Y., Z.L., D.M.H., S.K.V., J.L.F., M.S., D.L., S.L., C.H.M.), Physiology and Biomedical Engineering (A.M., D.S.L., K.E.A., D.R.H.), Information Technology (D.J.B.), and Biomedical Statistics and Informatics (R.E.C.), Mayo Clinic, 200 First St SW, Rochester, MN 55905; Department of Radiology, Mayo Clinic, Eau Claire, Wis (G.C.B.); Department of Radiology, Mayo Clinic, Jacksonville, Fla (J.C.C.); and Department of Radiology, Mayo Clinic, Scottsdale, Ariz (A.K.H.)
| | - Armando Manduca
- From the Departments of Radiology (J.G.F., L.Y., Z.L., D.M.H., S.K.V., J.L.F., M.S., D.L., S.L., C.H.M.), Physiology and Biomedical Engineering (A.M., D.S.L., K.E.A., D.R.H.), Information Technology (D.J.B.), and Biomedical Statistics and Informatics (R.E.C.), Mayo Clinic, 200 First St SW, Rochester, MN 55905; Department of Radiology, Mayo Clinic, Eau Claire, Wis (G.C.B.); Department of Radiology, Mayo Clinic, Jacksonville, Fla (J.C.C.); and Department of Radiology, Mayo Clinic, Scottsdale, Ariz (A.K.H.)
| | - Daniel J Blezek
- From the Departments of Radiology (J.G.F., L.Y., Z.L., D.M.H., S.K.V., J.L.F., M.S., D.L., S.L., C.H.M.), Physiology and Biomedical Engineering (A.M., D.S.L., K.E.A., D.R.H.), Information Technology (D.J.B.), and Biomedical Statistics and Informatics (R.E.C.), Mayo Clinic, 200 First St SW, Rochester, MN 55905; Department of Radiology, Mayo Clinic, Eau Claire, Wis (G.C.B.); Department of Radiology, Mayo Clinic, Jacksonville, Fla (J.C.C.); and Department of Radiology, Mayo Clinic, Scottsdale, Ariz (A.K.H.)
| | - David M Hough
- From the Departments of Radiology (J.G.F., L.Y., Z.L., D.M.H., S.K.V., J.L.F., M.S., D.L., S.L., C.H.M.), Physiology and Biomedical Engineering (A.M., D.S.L., K.E.A., D.R.H.), Information Technology (D.J.B.), and Biomedical Statistics and Informatics (R.E.C.), Mayo Clinic, 200 First St SW, Rochester, MN 55905; Department of Radiology, Mayo Clinic, Eau Claire, Wis (G.C.B.); Department of Radiology, Mayo Clinic, Jacksonville, Fla (J.C.C.); and Department of Radiology, Mayo Clinic, Scottsdale, Ariz (A.K.H.)
| | - Sudhakar K Venkatesh
- From the Departments of Radiology (J.G.F., L.Y., Z.L., D.M.H., S.K.V., J.L.F., M.S., D.L., S.L., C.H.M.), Physiology and Biomedical Engineering (A.M., D.S.L., K.E.A., D.R.H.), Information Technology (D.J.B.), and Biomedical Statistics and Informatics (R.E.C.), Mayo Clinic, 200 First St SW, Rochester, MN 55905; Department of Radiology, Mayo Clinic, Eau Claire, Wis (G.C.B.); Department of Radiology, Mayo Clinic, Jacksonville, Fla (J.C.C.); and Department of Radiology, Mayo Clinic, Scottsdale, Ariz (A.K.H.)
| | - Gregory C Brickner
- From the Departments of Radiology (J.G.F., L.Y., Z.L., D.M.H., S.K.V., J.L.F., M.S., D.L., S.L., C.H.M.), Physiology and Biomedical Engineering (A.M., D.S.L., K.E.A., D.R.H.), Information Technology (D.J.B.), and Biomedical Statistics and Informatics (R.E.C.), Mayo Clinic, 200 First St SW, Rochester, MN 55905; Department of Radiology, Mayo Clinic, Eau Claire, Wis (G.C.B.); Department of Radiology, Mayo Clinic, Jacksonville, Fla (J.C.C.); and Department of Radiology, Mayo Clinic, Scottsdale, Ariz (A.K.H.)
| | - Joseph C Cernigliaro
- From the Departments of Radiology (J.G.F., L.Y., Z.L., D.M.H., S.K.V., J.L.F., M.S., D.L., S.L., C.H.M.), Physiology and Biomedical Engineering (A.M., D.S.L., K.E.A., D.R.H.), Information Technology (D.J.B.), and Biomedical Statistics and Informatics (R.E.C.), Mayo Clinic, 200 First St SW, Rochester, MN 55905; Department of Radiology, Mayo Clinic, Eau Claire, Wis (G.C.B.); Department of Radiology, Mayo Clinic, Jacksonville, Fla (J.C.C.); and Department of Radiology, Mayo Clinic, Scottsdale, Ariz (A.K.H.)
| | - Amy K Hara
- From the Departments of Radiology (J.G.F., L.Y., Z.L., D.M.H., S.K.V., J.L.F., M.S., D.L., S.L., C.H.M.), Physiology and Biomedical Engineering (A.M., D.S.L., K.E.A., D.R.H.), Information Technology (D.J.B.), and Biomedical Statistics and Informatics (R.E.C.), Mayo Clinic, 200 First St SW, Rochester, MN 55905; Department of Radiology, Mayo Clinic, Eau Claire, Wis (G.C.B.); Department of Radiology, Mayo Clinic, Jacksonville, Fla (J.C.C.); and Department of Radiology, Mayo Clinic, Scottsdale, Ariz (A.K.H.)
| | - Jeff L Fidler
- From the Departments of Radiology (J.G.F., L.Y., Z.L., D.M.H., S.K.V., J.L.F., M.S., D.L., S.L., C.H.M.), Physiology and Biomedical Engineering (A.M., D.S.L., K.E.A., D.R.H.), Information Technology (D.J.B.), and Biomedical Statistics and Informatics (R.E.C.), Mayo Clinic, 200 First St SW, Rochester, MN 55905; Department of Radiology, Mayo Clinic, Eau Claire, Wis (G.C.B.); Department of Radiology, Mayo Clinic, Jacksonville, Fla (J.C.C.); and Department of Radiology, Mayo Clinic, Scottsdale, Ariz (A.K.H.)
| | - David S Lake
- From the Departments of Radiology (J.G.F., L.Y., Z.L., D.M.H., S.K.V., J.L.F., M.S., D.L., S.L., C.H.M.), Physiology and Biomedical Engineering (A.M., D.S.L., K.E.A., D.R.H.), Information Technology (D.J.B.), and Biomedical Statistics and Informatics (R.E.C.), Mayo Clinic, 200 First St SW, Rochester, MN 55905; Department of Radiology, Mayo Clinic, Eau Claire, Wis (G.C.B.); Department of Radiology, Mayo Clinic, Jacksonville, Fla (J.C.C.); and Department of Radiology, Mayo Clinic, Scottsdale, Ariz (A.K.H.)
| | - Maria Shiung
- From the Departments of Radiology (J.G.F., L.Y., Z.L., D.M.H., S.K.V., J.L.F., M.S., D.L., S.L., C.H.M.), Physiology and Biomedical Engineering (A.M., D.S.L., K.E.A., D.R.H.), Information Technology (D.J.B.), and Biomedical Statistics and Informatics (R.E.C.), Mayo Clinic, 200 First St SW, Rochester, MN 55905; Department of Radiology, Mayo Clinic, Eau Claire, Wis (G.C.B.); Department of Radiology, Mayo Clinic, Jacksonville, Fla (J.C.C.); and Department of Radiology, Mayo Clinic, Scottsdale, Ariz (A.K.H.)
| | - David Lewis
- From the Departments of Radiology (J.G.F., L.Y., Z.L., D.M.H., S.K.V., J.L.F., M.S., D.L., S.L., C.H.M.), Physiology and Biomedical Engineering (A.M., D.S.L., K.E.A., D.R.H.), Information Technology (D.J.B.), and Biomedical Statistics and Informatics (R.E.C.), Mayo Clinic, 200 First St SW, Rochester, MN 55905; Department of Radiology, Mayo Clinic, Eau Claire, Wis (G.C.B.); Department of Radiology, Mayo Clinic, Jacksonville, Fla (J.C.C.); and Department of Radiology, Mayo Clinic, Scottsdale, Ariz (A.K.H.)
| | - Shuai Leng
- From the Departments of Radiology (J.G.F., L.Y., Z.L., D.M.H., S.K.V., J.L.F., M.S., D.L., S.L., C.H.M.), Physiology and Biomedical Engineering (A.M., D.S.L., K.E.A., D.R.H.), Information Technology (D.J.B.), and Biomedical Statistics and Informatics (R.E.C.), Mayo Clinic, 200 First St SW, Rochester, MN 55905; Department of Radiology, Mayo Clinic, Eau Claire, Wis (G.C.B.); Department of Radiology, Mayo Clinic, Jacksonville, Fla (J.C.C.); and Department of Radiology, Mayo Clinic, Scottsdale, Ariz (A.K.H.)
| | - Kurt E Augustine
- From the Departments of Radiology (J.G.F., L.Y., Z.L., D.M.H., S.K.V., J.L.F., M.S., D.L., S.L., C.H.M.), Physiology and Biomedical Engineering (A.M., D.S.L., K.E.A., D.R.H.), Information Technology (D.J.B.), and Biomedical Statistics and Informatics (R.E.C.), Mayo Clinic, 200 First St SW, Rochester, MN 55905; Department of Radiology, Mayo Clinic, Eau Claire, Wis (G.C.B.); Department of Radiology, Mayo Clinic, Jacksonville, Fla (J.C.C.); and Department of Radiology, Mayo Clinic, Scottsdale, Ariz (A.K.H.)
| | - Rickey E Carter
- From the Departments of Radiology (J.G.F., L.Y., Z.L., D.M.H., S.K.V., J.L.F., M.S., D.L., S.L., C.H.M.), Physiology and Biomedical Engineering (A.M., D.S.L., K.E.A., D.R.H.), Information Technology (D.J.B.), and Biomedical Statistics and Informatics (R.E.C.), Mayo Clinic, 200 First St SW, Rochester, MN 55905; Department of Radiology, Mayo Clinic, Eau Claire, Wis (G.C.B.); Department of Radiology, Mayo Clinic, Jacksonville, Fla (J.C.C.); and Department of Radiology, Mayo Clinic, Scottsdale, Ariz (A.K.H.)
| | - David R Holmes
- From the Departments of Radiology (J.G.F., L.Y., Z.L., D.M.H., S.K.V., J.L.F., M.S., D.L., S.L., C.H.M.), Physiology and Biomedical Engineering (A.M., D.S.L., K.E.A., D.R.H.), Information Technology (D.J.B.), and Biomedical Statistics and Informatics (R.E.C.), Mayo Clinic, 200 First St SW, Rochester, MN 55905; Department of Radiology, Mayo Clinic, Eau Claire, Wis (G.C.B.); Department of Radiology, Mayo Clinic, Jacksonville, Fla (J.C.C.); and Department of Radiology, Mayo Clinic, Scottsdale, Ariz (A.K.H.)
| | - Cynthia H McCollough
- From the Departments of Radiology (J.G.F., L.Y., Z.L., D.M.H., S.K.V., J.L.F., M.S., D.L., S.L., C.H.M.), Physiology and Biomedical Engineering (A.M., D.S.L., K.E.A., D.R.H.), Information Technology (D.J.B.), and Biomedical Statistics and Informatics (R.E.C.), Mayo Clinic, 200 First St SW, Rochester, MN 55905; Department of Radiology, Mayo Clinic, Eau Claire, Wis (G.C.B.); Department of Radiology, Mayo Clinic, Jacksonville, Fla (J.C.C.); and Department of Radiology, Mayo Clinic, Scottsdale, Ariz (A.K.H.)
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Yu L, Vrieze TJ, Leng S, Fletcher JG, McCollough CH. Technical Note: Measuring contrast- and noise-dependent spatial resolution of an iterative reconstruction method in CT using ensemble averaging. Med Phys 2015; 42:2261-7. [PMID: 25979020 PMCID: PMC4401802 DOI: 10.1118/1.4916802] [Citation(s) in RCA: 50] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2014] [Revised: 01/14/2015] [Accepted: 03/15/2015] [Indexed: 12/23/2022] Open
Abstract
PURPOSE The spatial resolution of iterative reconstruction (IR) in computed tomography (CT) is contrast- and noise-dependent because of the nonlinear regularization. Due to the severe noise contamination, it is challenging to perform precise spatial-resolution measurements at very low-contrast levels. The purpose of this study was to measure the spatial resolution of a commercially available IR method using ensemble-averaged images acquired from repeated scans. METHODS A low-contrast phantom containing three rods (7, 14, and 21 HU below background) was scanned on a 128-slice CT scanner at three dose levels (CTDIvol = 16, 8, and 4 mGy). Images were reconstructed using two filtered-backprojection (FBP) kernels (B40 and B20) and a commercial IR method (sinogram affirmed iterative reconstruction, SAFIRE, Siemens Healthcare) with two strength settings (I40-3 and I40-5). The same scan was repeated 100 times at each dose level. The modulation transfer function (MTF) was calculated based on the edge profile measured on the ensemble-averaged images. RESULTS The spatial resolution of the two FBP kernels, B40 and B20, remained relatively constant across contrast and dose levels. However, the spatial resolution of the two IR kernels degraded relative to FBP as contrast or dose level decreased. For a given dose level at 16 mGy, the MTF50% value normalized to the B40 kernel decreased from 98.4% at 21 HU to 88.5% at 7 HU for I40-3 and from 97.6% to 82.1% for I40-5. At 21 HU, the relative MTF50% value decreased from 98.4% at 16 mGy to 90.7% at 4 mGy for I40-3 and from 97.6% to 85.6% for I40-5. CONCLUSIONS A simple technique using ensemble averaging from repeated CT scans can be used to measure the spatial resolution of IR techniques in CT at very low contrast levels. The evaluated IR method degraded the spatial resolution at low contrast and high noise levels.
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Affiliation(s)
- Lifeng Yu
- Department of Radiology, Mayo Clinic, Rochester, Minnesota 55905
| | - Thomas J Vrieze
- Department of Radiology, Mayo Clinic, Rochester, Minnesota 55905
| | - Shuai Leng
- Department of Radiology, Mayo Clinic, Rochester, Minnesota 55905
| | - Joel G Fletcher
- Department of Radiology, Mayo Clinic, Rochester, Minnesota 55905
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Half-dose abdominal CT with sinogram-affirmed iterative reconstruction technique in children - comparison with full-dose CT with filtered back projection. Pediatr Radiol 2015; 45:188-93. [PMID: 25030221 DOI: 10.1007/s00247-014-3105-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/12/2013] [Revised: 04/16/2014] [Accepted: 06/18/2014] [Indexed: 10/25/2022]
Abstract
BACKGROUND Iterative reconstruction can be helpful to reduce radiation dose while maintaining image quality. However, this technique has not been fully evaluated in children during abdominal CT. OBJECTIVE To compare objective and subjective image quality between half-dose images reconstructed with iterative reconstruction at iteration strength levels 1 to 5 (half-S1 to half-S5 studies) and full-dose images reconstructed with filtered back projection (full studies) in pediatric abdominal CT. MATERIALS AND METHODS Twenty-one children (M:F = 13:8; mean age 8.2 ± 5.7 years) underwent dual-source abdominal CT (mean effective dose 4.8 ± 2.1 mSv). The objective image quality was evaluated as noise. Subjective image quality analysis was performed comparing each half study to the full study for noise, sharpness, artifact and diagnostic acceptability. RESULTS Both objective and subjective image noise decreased with increasing iteration strength. Half-S4 and -S5 studies showed objective image noise similar to or lower than that of full studies. The half-S2 and -S3 studies produced the greatest sharpness and the half-S5 studies were the worst from a blocky appearance. Full and half studies did not differ in artifacts. Half-S3 studies showed the best diagnostic acceptability. CONCLUSION Half-S4 and -S5 studies objectively and half-S3 studies subjectively showed comparable image quality to full studies in pediatric abdominal CT.
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Low-Dose Pelvic Computed Tomography Using Adaptive Iterative Dose Reduction 3-Dimensional Algorithm. J Comput Assist Tomogr 2015; 39:629-34. [DOI: 10.1097/rct.0000000000000242] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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Yoon JH, Lee JM, Hur BY, Baek J, Shim H, Han JK, Choi BI. Influence of the adaptive iterative dose reduction 3D algorithm on the detectability of low-contrast lesions and radiation dose repeatability in abdominal computed tomography: a phantom study. ACTA ACUST UNITED AC 2014; 40:1843-52. [DOI: 10.1007/s00261-014-0333-4] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
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Effects of adaptive statistical iterative reconstruction on radiation dose reduction and diagnostic accuracy of pediatric abdominal CT. Pediatr Radiol 2014; 44:1541-7. [PMID: 25001398 DOI: 10.1007/s00247-014-3058-1] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/26/2013] [Revised: 04/08/2014] [Accepted: 05/14/2014] [Indexed: 10/25/2022]
Abstract
BACKGROUND Since children are more radio-sensitive than adults, there is a need to minimize radiation exposure during CT exams. OBJECTIVE To evaluate the effects of adaptive statistical iterative reconstruction (ASIR) on radiation dose reduction, image quality and diagnostic accuracy in pediatric abdominal CT. MATERIALS AND METHODS We retrospectively reviewed the abdominal CT examinations of 41 children (24 boys and 17 girls; mean age: 10 years) with a low-dose radiation protocol and reconstructed with ASIR (the ASIR group). We also reviewed routine-dose abdominal CT examinations of 41 age- and sex-matched controls reconstructed with filtered-back projection (control group). Image quality was assessed objectively as noise measured in the liver, spleen and aorta, as well as subjectively by three pediatric radiologists for diagnostic acceptability using a four-point scale. Radiation dose and objective image qualities of each group were compared with the paired t-test. Diagnostic accuracy was evaluated by reviewing follow-up imaging studies and medical records in 2012 and 2013. RESULTS There was 46.3% dose reduction of size-specific dose estimates in ASIR group (from 13.4 to 7.2 mGy) compared with the control group. Objective noise was higher in the liver, spleen and aorta of the ASIR group (P < 0.001). However, the subjective image quality was average or superior in 84-100% of studies. Only one image was subjectively rated as unacceptable by one reviewer. There was only one case with interpretational error in the control group and none in the ASIR group. CONCLUSION Use of the ASIR technique resulted in greater than a 45% reduction in radiation dose without impairing subjective image quality or diagnostic accuracy in pediatric abdominal CT, despite increased objective image noise.
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Kim JH, Kim MJ, Kim HY, Lee MJ. Radiation dose reduction and image quality in pediatric abdominal CT with kVp and mAs modulation and an iterative reconstruction technique. Clin Imaging 2014; 38:710-4. [DOI: 10.1016/j.clinimag.2014.05.008] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2014] [Revised: 05/15/2014] [Accepted: 05/19/2014] [Indexed: 10/25/2022]
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Goenka AH, Herts BR, Obuchowski NA, Primak AN, Dong F, Karim W, Baker ME. Effect of reduced radiation exposure and iterative reconstruction on detection of low-contrast low-attenuation lesions in an anthropomorphic liver phantom: an 18-reader study. Radiology 2014; 272:154-63. [PMID: 24620913 DOI: 10.1148/radiol.14131928] [Citation(s) in RCA: 71] [Impact Index Per Article: 7.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
PURPOSE To measure the effect of reduced radiation exposure on low-contrast low-attenuation liver lesion detection in an anthropomorphic abdominal phantom by using filtered back projection (FBP) and sinogram-affirmed iterative reconstruction. MATERIALS AND METHODS Eighteen radiologists blinded to phantom and study design interpreted randomized image data sets that contained 36 spherical simulated liver lesions of three sizes and three attenuation differences (5-mm diameter: 12, 18, and 24 HU less than the 90-HU background attenuation of the simulated liver insert; 10- and 15-mm diameter: 6, 12, and 18 HU less than the 90-HU background attenuation) scanned with four discrete exposure settings and reconstructed by using FBP and sinogram-affirmed iterative reconstruction. Response assessment included region-level lesion presence or absence on a five-point diagnostic confidence scale. Statistical evaluation included multireader multicase receiver operating characteristic curve analysis, with nonparametric methods and noninferiority analysis at a margin of -0.10. RESULTS Pooled accuracy at 75% exposure for both FBP and sinogram-affirmed iterative reconstruction was noninferior to 100% exposure (P = .002 and P < .001, respectively). Subsequent exposure reductions resulted in a significant decrease in accuracy. When the smallest (5-mm-diameter) lesions were excluded from analysis, sinogram-affirmed iterative reconstruction was superior to FBP at 100% exposure (P = .011), and sinogram-affirmed iterative reconstruction at 25% and 50% exposure reduction was noninferior to FBP at 100% exposure (P ≤ .013). Reader confidence was greater with sinogram-affirmed iterative reconstruction than with FBP for 10- and 15-mm lesions (2.94 vs 2.76 and 3.62 vs 3.52, respectively). CONCLUSION In this low-contrast low-attenuation liver lesion model, a 25% exposure reduction maintained noninferior diagnostic accuracy. However, detection was inferior with each subsequent exposure reduction, regardless of reconstruction method. Sinogram-affirmed iterative reconstruction and FBP performed equally well at modest exposure reduction (25%-50%). Readers had higher confidence levels with sinogram-affirmed iterative reconstruction for the 10- and 15-mm lesions.
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Affiliation(s)
- Ajit H Goenka
- From the Sections of Abdominal Imaging (A.H.G., B.R.H., W.K., M.E.B.) and Medical Physics (F.D.), Imaging Institute, and Department of Quantitative Health Sciences (N.A.O.), Cleveland Clinic Foundation, 9500 Euclid Ave, Mail Code L10, Cleveland, OH 44195; and Siemens Medical Solutions, Malvern, Pa (A.N.P.)
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Can Sinogram-Affirmed Iterative Reconstruction Improve the Detection of Small Hypervascular Liver Nodules With Dual-Energy CT? J Comput Assist Tomogr 2014; 38:693-9. [DOI: 10.1097/rct.0000000000000105] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
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