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Xie K, Cui C, Li X, Yuan Y, Wang Z, Zeng L. MRI-Based Clinical-Imaging-Radiomics Nomogram Model for Discriminating Between Benign and Malignant Solid Pulmonary Nodules or Masses. Acad Radiol 2024:S1076-6332(24)00207-1. [PMID: 38644089 DOI: 10.1016/j.acra.2024.03.042] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/29/2024] [Revised: 03/29/2024] [Accepted: 03/30/2024] [Indexed: 04/23/2024]
Abstract
RATIONALE AND OBJECTIVES Pulmonary nodules or masses are highly prevalent worldwide, and differential diagnosis of benign and malignant lesions remains difficult. Magnetic resonance imaging (MRI) can provide functional and metabolic information of pulmonary lesions. This study aimed to establish a nomogram model based on clinical features, imaging features, and multi-sequence MRI radiomics to identify benign and malignant solid pulmonary nodules or masses. MATERIALS AND METHODS A total of 145 eligible patients (76 male; mean age, 58.4 years ± 13.7 [SD]) with solid pulmonary nodules or masses were retrospectively analyzed. The patients were randomized into two groups (training cohort, n = 102; validation cohort, n = 43). The nomogram was used for predicting malignant pulmonary lesions. The diagnostic performance of different models was evaluated by receiver operating characteristic (ROC) curve analysis. RESULTS Of these patients, 95 patients were diagnosed with benign lesions and 50 with malignant lesions. Multivariate analysis showed that age, DWI value, LSR value, and ADC value were independent predictors of malignant lesions. Among the radiomics models, the multi-sequence MRI-based model (T1WI+T2WI+ADC) achieved the best diagnosis performance with AUCs of 0.858 (95%CI: 0.775, 0.919) and 0.774 (95%CI: 0.621, 0.887) for the training and validation cohorts, respectively. Combining multi-sequence radiomics, clinical and imaging features, the predictive efficacy of the clinical-imaging-radiomics model was significantly better than the clinical model, imaging model and radiomics model (all P < 0.05). CONCLUSION The MRI-based clinical-imaging-radiomics model is helpful to differentiate benign and malignant solid pulmonary nodules or masses, and may be useful for precision medicine of pulmonary diseases.
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Affiliation(s)
- Kexin Xie
- Department of Radiology, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, Jiangsu 210002, China
| | - Can Cui
- Department of Radiology, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, Jiangsu 210002, China
| | - Xiaoqing Li
- Department of Radiology, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, Jiangsu 210002, China
| | - Yongfeng Yuan
- Department of Radiology, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, Jiangsu 210002, China
| | - Zhongqiu Wang
- Department of Radiology, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, Jiangsu 210002, China
| | - Liang Zeng
- Department of Radiology, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, Jiangsu 210002, China.
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Lee DH, Lee JM, Lee CH, Afat S, Othman A. Image Quality and Diagnostic Performance of Low-Dose Liver CT with Deep Learning Reconstruction versus Standard-Dose CT. Radiol Artif Intell 2024; 6:e230192. [PMID: 38231025 PMCID: PMC10982822 DOI: 10.1148/ryai.230192] [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: 05/31/2023] [Revised: 11/13/2023] [Accepted: 01/02/2024] [Indexed: 01/18/2024]
Abstract
Purpose To compare the image quality and diagnostic capability in detecting malignant liver tumors of low-dose CT (LDCT, 33% dose) with deep learning-based denoising (DLD) and standard-dose CT (SDCT, 100% dose) with model-based iterative reconstruction (MBIR). Materials and Methods In this prospective, multicenter, noninferiority study, individuals referred for liver CT scans were enrolled from three tertiary referral hospitals between February 2021 and August 2022. All liver CT scans were conducted using a dual-source scanner with the dose split into tubes A (67% dose) and B (33% dose). Blended images from tubes A and B were created using MBIR to produce SDCT images, whereas LDCT images used data from tube B and were reconstructed with DLD. The noise in liver images was measured and compared between imaging techniques. The diagnostic performance of each technique in detecting malignant liver tumors was evaluated by three independent radiologists using jackknife alternative free-response receiver operating characteristic analysis. Noninferiority of LDCT compared with SDCT was declared when the lower limit of the 95% CI for the difference in figure of merit (FOM) was greater than -0.10. Results A total of 296 participants (196 men, 100 women; mean age, 60.5 years ± 13.3 [SD]) were included. The mean noise level in the liver was significantly lower for LDCT (10.1) compared with SDCT (10.7) (P < .001). Diagnostic performance was assessed in 246 participants (108 malignant tumors in 90 participants). The reader-averaged FOM was 0.880 for SDCT and 0.875 for LDCT (P = .35). The difference fell within the noninferiority margin (difference, -0.005 [95% CI: -0.024, 0.012]). Conclusion Compared with SDCT with MBIR, LDCT using 33% of the standard radiation dose had reduced image noise and comparable diagnostic performance in detecting malignant liver tumors. Keywords: CT, Abdomen/GI, Liver, Comparative Studies, Diagnosis, Reconstruction Algorithms Clinical trial registration no. NCT05804799 © RSNA, 2024 Supplemental material is available for this article.
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Affiliation(s)
- Dong Ho Lee
- From the Departments of Radiology of Seoul National University
Hospital, Seoul, South Korea (D.H.L., J.M.L.); Seoul National University
Hospital, Seoul National University College of Medicine, 101 Daehak-ro,
Jongno-gu, Seoul 03080, South Korea (D.H.L., J.M.L.); Korea University Guro
Hospital, Korea University Medicine, Seoul, South Korea (C.H.L.); and
Tübingen University Hospital, Tübingen, Germany (S.A.,
A.O.)
| | - Jeong Min Lee
- From the Departments of Radiology of Seoul National University
Hospital, Seoul, South Korea (D.H.L., J.M.L.); Seoul National University
Hospital, Seoul National University College of Medicine, 101 Daehak-ro,
Jongno-gu, Seoul 03080, South Korea (D.H.L., J.M.L.); Korea University Guro
Hospital, Korea University Medicine, Seoul, South Korea (C.H.L.); and
Tübingen University Hospital, Tübingen, Germany (S.A.,
A.O.)
| | - Chang Hee Lee
- From the Departments of Radiology of Seoul National University
Hospital, Seoul, South Korea (D.H.L., J.M.L.); Seoul National University
Hospital, Seoul National University College of Medicine, 101 Daehak-ro,
Jongno-gu, Seoul 03080, South Korea (D.H.L., J.M.L.); Korea University Guro
Hospital, Korea University Medicine, Seoul, South Korea (C.H.L.); and
Tübingen University Hospital, Tübingen, Germany (S.A.,
A.O.)
| | - Saif Afat
- From the Departments of Radiology of Seoul National University
Hospital, Seoul, South Korea (D.H.L., J.M.L.); Seoul National University
Hospital, Seoul National University College of Medicine, 101 Daehak-ro,
Jongno-gu, Seoul 03080, South Korea (D.H.L., J.M.L.); Korea University Guro
Hospital, Korea University Medicine, Seoul, South Korea (C.H.L.); and
Tübingen University Hospital, Tübingen, Germany (S.A.,
A.O.)
| | - Ahmed Othman
- From the Departments of Radiology of Seoul National University
Hospital, Seoul, South Korea (D.H.L., J.M.L.); Seoul National University
Hospital, Seoul National University College of Medicine, 101 Daehak-ro,
Jongno-gu, Seoul 03080, South Korea (D.H.L., J.M.L.); Korea University Guro
Hospital, Korea University Medicine, Seoul, South Korea (C.H.L.); and
Tübingen University Hospital, Tübingen, Germany (S.A.,
A.O.)
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Salman R, Nguyen HN, Sher AC, Hallam K, Seghers VJ, Sammer MBK. Diagnostic performance of artificial intelligence for pediatric pulmonary nodule detection on chest computed tomography: comparison of simulated lower radiation doses. Eur J Pediatr 2023; 182:5159-5165. [PMID: 37698612 DOI: 10.1007/s00431-023-05194-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/11/2023] [Revised: 08/31/2023] [Accepted: 09/05/2023] [Indexed: 09/13/2023]
Abstract
The combination of low dose CT and AI performance in the pediatric population has not been explored. Understanding this relationship is relevant for pediatric patients given the potential radiation risks. Here, the objective was to determine the diagnostic performance of commercially available Computer Aided Detection (CAD) for pulmonary nodules in pediatric patients at simulated lower radiation doses. Retrospective chart review of 30 sequential patients between 12-18 years old who underwent a chest CT on the Siemens SOMATOM Force from December 20, 2021, to April 12, 2022. Simulated lower doses at 75%, 50%, and 25% were reconstructed in lung kernel at 3 mm slice thickness using ReconCT and imported to Syngo CT Lung CAD software for analysis. Two pediatric radiologists reviewed the full dose CTs to determine the reference read. Two other pediatric radiologists compared the Lung CAD results at 100% dose and each simulated lower dose level to the reference on a nodule by nodule basis. The sensitivity (Sn), positive predictive value (PPV), and McNemar test were used for comparison of Lung CAD performance based on dose. As reference standard, 109 nodules were identified by the two radiologists. At 100%, and simulated 75%, 50%, and 25% doses, lung CAD detected 60, 62, 58, and 62 nodules, respectively; 28, 28, 29, and 26 were true positive (Sn = 26%, 26%, 27%, 24%), 30, 32, 27, and 34 were false positive (PPV = 48%, 47%, 52%, 43%). No statistically significance difference of Lung CAD performance at different doses was found, with p-values of 1.0, 1.0, and 0.7 at simulated 75%, 50%, and 25% doses compared to standard dose. CONCLUSION The Lung CAD shows low sensitivity at all simulated lower doses for the detection of pulmonary nodules in this pediatric population. However, radiation dose may be reduced from standard without further compromise to the Lung CAD performance. WHAT IS KNOWN • High diagnostic performance of Lung CAD for detection of pulmonary nodules in adults. • Several imaging techniques are applied to reduce pediatric radiation dose. WHAT IS NEW • Low sensitivity at all simulated lower doses for the detection of pulmonary nodules in our pediatric population. • Radiation dose may be reduced from standard without further compromise to the Lung CAD performance.
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Affiliation(s)
- Rida Salman
- Edward B. Singleton Department of Radiology, Division of Body Imaging, Texas Children's Hospital and Baylor College of Medicine, 6701 Fannin St. Suite 470, Houston, TX, 77030, USA
| | - HaiThuy N Nguyen
- Department of Radiology, Children's Hospital Los Angeles and Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Andrew C Sher
- Edward B. Singleton Department of Radiology, Division of Body Imaging, Texas Children's Hospital and Baylor College of Medicine, 6701 Fannin St. Suite 470, Houston, TX, 77030, USA
| | - Kristina Hallam
- CT R&D Collaborations, Siemens Healthineers, Malvern, PA, USA
| | - Victor J Seghers
- Edward B. Singleton Department of Radiology, Division of Body Imaging, Texas Children's Hospital and Baylor College of Medicine, 6701 Fannin St. Suite 470, Houston, TX, 77030, USA
| | - Marla B K Sammer
- Edward B. Singleton Department of Radiology, Division of Body Imaging, Texas Children's Hospital and Baylor College of Medicine, 6701 Fannin St. Suite 470, Houston, TX, 77030, USA.
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Lāce E, Mohammadian R, Āboltiņš A, Sosārs D, Apine I. Trade-off between the radiation parameters and image quality using iterative reconstruction techniques in head computed tomography: a phantom study. Acta Radiol 2023; 64:2618-2626. [PMID: 37469141 DOI: 10.1177/02841851231185347] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/21/2023]
Abstract
BACKGROUND Iterative reconstruction techniques (IRTs) are commonly used in computed tomography (CT) and help to reduce image noise. PURPOSE To determine the minimum radiation dose while preserving image quality in head CT using IRTs. MATERIAL AND METHODS The anthropomorphic phantom was used to scan nine head CT image series with varied radiation parameters. CT dose parameters, including volume CT dose index (CTDIvol [in mGy]) and dose length product (DLP [in mGy/cm]), were recorded for each scan series. Different noise levels (iDoseL1-6) were used in IRT reconstructions for soft and bone tissues. In total, 15 measurements were taken from five regions of interest (ROI) with an area of 10 mm2. The signal-to-noise ratio (SNR) and noise values obtained at different ROIs were compared among various reconstruction methods with repeated measures of statistical analysis. RESULTS In the head CT scan, applying IRT iDoseL5 had the lowest noise and highest SNR for soft tissue (P < 0.05), and increased iDose can decrease CT dose by 54.6% without compromising image quality. While for bone tissue reconstruction, no clear association was found between the level of iDose and noise. However, when CTDIvol is >20 mGy, iDoseL4 is slightly superior to other reconstruction methods (P < 0.065). CONCLUSION Using IRTs in head CTs reduces radiation dose while maintaining image quality. IDoseL5 provided optimal balance for soft tissue.
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Affiliation(s)
- Elīza Lāce
- Department of Radiology, Riga Stradin's University, Riga, Latvia
| | - Reza Mohammadian
- Department of Radiology, Riga Stradin's University, Riga, Latvia
| | - Ainārs Āboltiņš
- Department of Radiology, Children's Clinical University Hospital, Riga, Latvia
| | - Dāvis Sosārs
- Department of Radiology, Children's Clinical University Hospital, Riga, Latvia
| | - Ilze Apine
- Department of Radiology, Riga Stradin's University, Riga, Latvia
- Department of Radiology, Children's Clinical University Hospital, Riga, Latvia
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Koo SA, Jung Y, Um KA, Kim TH, Kim JY, Park CH. Clinical Feasibility of Deep Learning-Based Image Reconstruction on Coronary Computed Tomography Angiography. J Clin Med 2023; 12:jcm12103501. [PMID: 37240607 DOI: 10.3390/jcm12103501] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2023] [Revised: 04/24/2023] [Accepted: 05/14/2023] [Indexed: 05/28/2023] Open
Abstract
This study evaluated the feasibility of deep-learning-based image reconstruction (DLIR) on coronary computed tomography angiography (CCTA). By using a 20 cm water phantom, the noise reduction ratio and noise power spectrum were evaluated according to the different reconstruction methods. Then 46 patients who underwent CCTA were retrospectively enrolled. CCTA was performed using the 16 cm coverage axial volume scan technique. All CT images were reconstructed using filtered back projection (FBP); three model-based iterative reconstructions (MBIR) of 40%, 60%, and 80%; and three DLIR algorithms: low (L), medium (M), and high (H). Quantitative and qualitative image qualities of CCTA were compared according to the reconstruction methods. In the phantom study, the noise reduction ratios of MBIR-40%, MBIR-60%, MBIR-80%, DLIR-L, DLIR-M, and DLIR-H were 26.7 ± 0.2%, 39.5 ± 0.5%, 51.7 ± 0.4%, 33.1 ± 0.8%, 43.2 ± 0.8%, and 53.5 ± 0.1%, respectively. The pattern of the noise power spectrum of the DLIR images was more similar to FBP images than MBIR images. In a CCTA study, CCTA yielded a significantly lower noise index with DLIR-H reconstruction than with the other reconstruction methods. DLIR-H showed a higher SNR and CNR than MBIR (p < 0.05). The qualitative image quality of CCTA with DLIR-H was significantly higher than that of MBIR-80% or FBP. The DLIR algorithm was feasible and yielded a better image quality than the FBP or MBIR algorithms on CCTA.
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Affiliation(s)
- Seul Ah Koo
- Department of Radiology and The Research Institute of Radiological Science, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul 06273, Republic of Korea
| | - Yunsub Jung
- Research Team, GE Healthcare Korea, Seoul 04637, Republic of Korea
| | - Kyoung A Um
- Research Team, GE Healthcare Korea, Seoul 04637, Republic of Korea
| | - Tae Hoon Kim
- Department of Radiology and The Research Institute of Radiological Science, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul 06273, Republic of Korea
| | - Ji Young Kim
- Department of Radiology and The Research Institute of Radiological Science, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul 06273, Republic of Korea
| | - Chul Hwan Park
- Department of Radiology and The Research Institute of Radiological Science, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul 06273, Republic of Korea
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Jaworska J, Buda N, Kwaśniewicz P, Komorowska-Piotrowska A, Sands D. Lung Ultrasound in the Evaluation of Lung Disease Severity in Children with Clinically Stable Cystic Fibrosis: A Prospective Cross-Sectional Study. J Clin Med 2023; 12:jcm12093086. [PMID: 37176526 PMCID: PMC10179222 DOI: 10.3390/jcm12093086] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2023] [Revised: 04/07/2023] [Accepted: 04/13/2023] [Indexed: 05/15/2023] Open
Abstract
With the increasing longevity of cystic fibrosis (CF), there is a growing need to minimise exposure to ionising radiation in patients who undergo regular imaging tests while monitoring the course of the lung disease. This study aimed to define the role of lung ultrasounds (LUS) in the evaluation of lung disease severity in children with clinically stable CF. LUS was performed on 131 patients aged 5 weeks to 18 years (study group) and in 32 healthy children of an equivalent age range (control group). Additionally, an interobserver study was performed on 38 patients from the study group. In CF patients, the following ultrasound signs were identified: I-lines; Z-lines; single, numerous and confluent B-lines; Am-lines; small and major consolidations; pleural line abnormalities and small amounts of pleural fluid. The obtained results were evaluated against an original ultrasound score. LUS results were correlated with the results of chest X-ray (CXR) [very high], pulmonary function tests (PFTs) [high] and microbiological status [significant]. The interobserver study showed very good agreement between investigators. We conclude that LUS is a useful test in the evaluation of CF lung disease severity compared to routinely used methods. With appropriate standardisation, LUS is highly reproducible.
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Affiliation(s)
- Joanna Jaworska
- Cystic Fibrosis Department, Institute of Mother and Child, 01-211 Warsaw, Poland
| | - Natalia Buda
- Department of Internal Medicine, Connective Tissue Diseases and Geriatrics, Medical University of Gdansk, 80-214 Gdansk, Poland
| | - Piotr Kwaśniewicz
- Department of Diagnostic Imaging, Institute of Mother and Child, 01-211 Warsaw, Poland
| | | | - Dorota Sands
- Cystic Fibrosis Department, Institute of Mother and Child, 01-211 Warsaw, Poland
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Significant CT dose reduction of 2-[ 18F]FDG PET/CT in pretreatment pediatric lymphoma without compromising the diagnostic and staging efficacy. Eur Radiol 2023; 33:2248-2257. [PMID: 36166086 DOI: 10.1007/s00330-022-09145-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2022] [Revised: 08/29/2022] [Accepted: 09/05/2022] [Indexed: 11/04/2022]
Abstract
OBJECTIVES To compare the diagnostic and staging efficacy of PET/diagnostic-level CT (PET/DxCT) and PET/low-dose CT (PET/LDCT) in pretreatment pediatric lymphoma patients and to estimate the reduction of the CT effective dose in the PET/CT scan. METHODS One hundred and five pediatric patients who underwent total-body PET/CT examination were enrolled and divided into the DxCT group (n = 47) and LDCT group (n = 58) according to their dose levels. The sensitivity, specificity, PPV, and NPV of PET/DxCT and PET/LDCT for detecting the involvement of lymph node, spleen, bone marrow, and other extranodal organs in pretreatment lymphoma were compared. ROC analysis was performed to evaluate the integral efficiency. The staging accuracies based on PET/DxCT and PET/LDCT were also evaluated. Dosimetry was calculated for DxCT and LDCT, and the reduction in the effective dose was estimated. RESULTS In the diagnosis of nodal, splenic, bone marrow, and other extranodal involvement, the differences in sensitivity, specificity, PPV, and NPV between PET/LDCT and PET/DxCT were not significant (all p values ∈ [0.332, 1.000]). Both modalities had accuracies above 90% and the ROC analysis indicated good or high efficiency in diagnosing all patterns of lymphoma involvement. PET/LDCT and PET/DxCT each had a staging accuracy of 89.7% and 89.4%, respectively. LDCT had a comparable image quality score with DxCT, with a significant increase in noise (p < 0.001) and a 66.1% reduction in effective dose. CONCLUSIONS PET/LDCT allowed for a 66.1% CT effective dose reduction compared to PET/DxCT in pediatric lymphoma patients without compromising the diagnostic and staging efficacy. KEY POINTS • Pediatric lymphoma patients can benefit from a reduced effective dose of PET/CT. • This retrospective study showed that the diagnostic and staging efficacies of PET/low-dose CT are comparable to those of PET/diagnostic-level CT, both with satisfactory efficiency in diagnosing all patterns of lymphoma involvement. • PET/low-dose CT allowed for a 66.1% CT effective dose reduction compared to PET/diagnostic-level CT.
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Zhou S, Yu L, Jin M. Texture transformer super-resolution for low-dose computed tomography. Biomed Phys Eng Express 2022; 8:10.1088/2057-1976/ac9da7. [PMID: 36301699 PMCID: PMC9707552 DOI: 10.1088/2057-1976/ac9da7] [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: 09/01/2022] [Accepted: 10/26/2022] [Indexed: 11/11/2022]
Abstract
Computed tomography (CT) is widely used to diagnose many diseases. Low-dose CT has been actively pursued to lower the ionizing radiation risk. A relatively smoother kernel is typically used in low-dose CT to suppress image noise, which may sacrifice spatial resolution. In this work, we propose a texture transformer network to simultaneously reduce image noise and improve spatial resolution in CT images. This network, referred to as Texture Transformer for Super Resolution (TTSR), is a reference-based deep-learning image super-resolution method built upon a generative adversarial network (GAN). The noisy low-resolution CT (LRCT) image and the routine-dose high-resolution (HRCT) image are severed as the query and key in a transformer, respectively. Image translation is optimized through deep neural network (DNN) texture extraction, correlation embedding, and attention-based texture transfer and synthesis to achieve joint feature learning between LRCT and HRCT images for super-resolution CT (SRCT) images. To evaluate SRCT performance, we use the data from both simulations of the XCAT phantom program and the real patient data. Peak signal-to-noise ratio (PSNR), structural similarity index measure (SSIM), and feature similarity (FSIM) index are used as quantitative metrics. For comparison of SRCT performance, the cubic spline interpolation, SRGAN (a GAN super-resolution with an additional content loss), and GAN-CIRCLE (a GAN super-resolution with cycle consistency) were used. Compared to the other two methods, TTSR can restore more details in SRCT images and achieve better PSNR, SSIM, and FSIM for both simulation and real-patient data. In addition, we show that TTSR can yield better image quality and demand much less computation time than high-resolution low-dose CT images denoised by block-matching and 3D filtering (BM3D) and GAN-CIRCLE. In summary, the proposed TTSR method based on texture transformer and attention mechanism provides an effective and efficient tool to improve spatial resolution and suppress noise of low-dose CT images.
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Affiliation(s)
- Shiwei Zhou
- Department of Physics, University of Texas at Arlington, TX 76019, United States of America
| | - Lifeng Yu
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, United States of America
| | - Mingwu Jin
- Department of Physics, University of Texas at Arlington, TX 76019, United States of America
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Dillman JR, Somasundaram E, Brady SL, He L. Current and emerging artificial intelligence applications for pediatric abdominal imaging. Pediatr Radiol 2022; 52:2139-2148. [PMID: 33844048 DOI: 10.1007/s00247-021-05057-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/27/2020] [Revised: 01/25/2021] [Accepted: 03/16/2021] [Indexed: 12/12/2022]
Abstract
Artificial intelligence (AI) uses computers to mimic cognitive functions of the human brain, allowing inferences to be made from generally large datasets. Traditional machine learning (e.g., decision tree analysis, support vector machines) and deep learning (e.g., convolutional neural networks) are two commonly employed AI approaches both outside and within the field of medicine. Such techniques can be used to evaluate medical images for the purposes of automated detection and segmentation, classification tasks (including diagnosis, lesion or tissue characterization, and prediction), and image reconstruction. In this review article we highlight recent literature describing current and emerging AI methods applied to abdominal imaging (e.g., CT, MRI and US) and suggest potential future applications of AI in the pediatric population.
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Affiliation(s)
- Jonathan R Dillman
- Department of Radiology, Cincinnati Children's Hospital Medical Center, 3333 Burnet Ave., Cincinnati, OH, 45229, USA. .,Department of Radiology, University of Cincinnati College of Medicine, Cincinnati, OH, USA.
| | - Elan Somasundaram
- Department of Radiology, Cincinnati Children's Hospital Medical Center, 3333 Burnet Ave., Cincinnati, OH, 45229, USA.,Department of Radiology, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - Samuel L Brady
- Department of Radiology, Cincinnati Children's Hospital Medical Center, 3333 Burnet Ave., Cincinnati, OH, 45229, USA.,Department of Radiology, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - Lili He
- Department of Radiology, Cincinnati Children's Hospital Medical Center, 3333 Burnet Ave., Cincinnati, OH, 45229, USA.,Department of Radiology, University of Cincinnati College of Medicine, Cincinnati, OH, USA
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Leder NI, Popić J, Knežević Ž, Vidjak V. EFFICIENCY OF BREAST SHIELDING DEVICE IN OUT-OF-PLANE COMPUTERIZED TOMOGRAPHY IMAGING OF THE ABDOMEN - PRELIMINARY RESULTS. Acta Clin Croat 2022; 61:257-264. [PMID: 36818926 PMCID: PMC9934029 DOI: 10.20471/acc.2022.61.02.12] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2020] [Accepted: 01/14/2021] [Indexed: 02/09/2023] Open
Abstract
The dose absorbed by sensitive breast glandular tissue in abdominal computed tomography examinations, even when the breasts are outside the primary imaging beam, is still significant. Several studies have explored using breast shielding with a protective lead sheet or a bra. Since the source of radiation in computed tomography rotates by 360° around the patient, we made a custom-tailored shielding device that wraps around the entire thorax. The hypothesis is that such a custom-tailored breast shielding device provides significantly better dose reduction. Study participants were female patients with no anatomic anomalies. Entrance surface doses were measured using thermoluminescence dosimeters placed on the skin of the breast in the control group without shielding and on the surface and below the shielding device in the group with anterior shielding and the group with the new device. As expected, according to literature data, doses measured at breast level were above the threshold that epidemiological studies determine as an increased risk of breast cancer development although they were not in the primary imaging plane. Preliminary results of our study showed that average dose reduction was 42% with conventional anterior shielding and 57% with wrapped shielding compared to the doses measured with no shielding.
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Son W, Kim M, Hwang JY, Kim YW, Park C, Choo KS, Kim TU, Jang JY. Comparison of a Deep Learning-Based Reconstruction Algorithm with Filtered Back Projection and Iterative Reconstruction Algorithms for Pediatric Abdominopelvic CT. Korean J Radiol 2022; 23:752-762. [PMID: 35695313 PMCID: PMC9240291 DOI: 10.3348/kjr.2021.0466] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2021] [Revised: 02/26/2022] [Accepted: 03/29/2022] [Indexed: 11/15/2022] Open
Abstract
Objective To compare a deep learning-based reconstruction (DLR) algorithm for pediatric abdominopelvic computed tomography (CT) with filtered back projection (FBP) and iterative reconstruction (IR) algorithms. Materials and Methods Post-contrast abdominopelvic CT scans obtained from 120 pediatric patients (mean age ± standard deviation, 8.7 ± 5.2 years; 60 males) between May 2020 and October 2020 were evaluated in this retrospective study. Images were reconstructed using FBP, a hybrid IR algorithm (ASiR-V) with blending factors of 50% and 100% (AV50 and AV100, respectively), and a DLR algorithm (TrueFidelity) with three strength levels (low, medium, and high). Noise power spectrum (NPS) and edge rise distance (ERD) were used to evaluate noise characteristics and spatial resolution, respectively. Image noise, edge definition, overall image quality, lesion detectability and conspicuity, and artifacts were qualitatively scored by two pediatric radiologists, and the scores of the two reviewers were averaged. A repeated-measures analysis of variance followed by the Bonferroni post-hoc test was used to compare NPS and ERD among the six reconstruction methods. The Friedman rank sum test followed by the Nemenyi-Wilcoxon-Wilcox all-pairs test was used to compare the results of the qualitative visual analysis among the six reconstruction methods. Results The NPS noise magnitude of AV100 was significantly lower than that of the DLR, whereas the NPS peak of AV100 was significantly higher than that of the high- and medium-strength DLR (p < 0.001). The NPS average spatial frequencies were higher for DLR than for ASiR-V (p < 0.001). ERD was shorter with DLR than with ASiR-V and FBP (p < 0.001). Qualitative visual analysis revealed better overall image quality with high-strength DLR than with ASiR-V (p < 0.001). Conclusion For pediatric abdominopelvic CT, the DLR algorithm may provide improved noise characteristics and better spatial resolution than the hybrid IR algorithm.
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Affiliation(s)
- Wookon Son
- Department of Radiology, Pusan National University Yangsan Hospital, Yangsan, Korea
| | - MinWoo Kim
- School of Biomedical Convergence Engineering, Pusan National University, Busan, Korea
| | - Jae-Yeon Hwang
- Department of Radiology, Pusan National University Yangsan Hospital, Yangsan, Korea.,Research Institute for Convergence of Biomedical Science and Technology, Pusan National University Yangsan Hospital, College of Medicine, Pusan National University, Yangsan, Korea.
| | - Yong-Woo Kim
- Department of Radiology, Pusan National University Yangsan Hospital, Yangsan, Korea
| | - Chankue Park
- Department of Radiology, Pusan National University Yangsan Hospital, Yangsan, Korea
| | - Ki Seok Choo
- Department of Radiology, Pusan National University Yangsan Hospital, Yangsan, Korea
| | - Tae Un Kim
- Department of Radiology, Pusan National University Yangsan Hospital, Yangsan, Korea
| | - Joo Yeon Jang
- Department of Radiology, Pusan National University Yangsan Hospital, Yangsan, Korea
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12
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Simma L, Fornaro J, Stahr N, Lehner M, Roos JE, Lima TVM. Optimising whole body computed tomography doses for paediatric trauma patients: a Swiss retrospective analysis. JOURNAL OF RADIOLOGICAL PROTECTION : OFFICIAL JOURNAL OF THE SOCIETY FOR RADIOLOGICAL PROTECTION 2022; 42:021521. [PMID: 35354135 DOI: 10.1088/1361-6498/ac6274] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/03/2022] [Accepted: 03/30/2022] [Indexed: 06/14/2023]
Abstract
We aimed to evaluate the impact of a low-dose whole-body computed tomography (WBCT) protocol on radiation doses in paediatric major trauma patients. Retrospective cohort study of paediatric trauma patients (<16 years) at a national level 1 paediatric trauma centre (PTC) over a 6 year period prior and post introduction of a low-dose WBCT protocol (2014-2019). Demographic data, patient characteristics, CT device, and exposure information including scan range, dose-length product, and volume CT dose index were collected. Effective dose (ED) and exposure parameters were compared before and after protocol introduction. Forty-eight patients underwent WBCT during the study period. Prior to introduction of the low-dose protocol (n= 18), the ED was 20.6 mSv (median 20.1 ± 5.3 mSv [range 12.5-30.7]). After introduction of the low-dose WBCT protocol (n= 30), mean ED was 4.8 mSv (median 2.6 ± 5.0 [range: 0.8-19.1]). This resulted in a reduction of 77% in mean ED (pvalue <0.001). Significant radiation dose reduction of 77% can be achieved with low-dose WBCT protocols in PTCs.
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Affiliation(s)
- Leopold Simma
- Emergency Department, Children's Hospital Lucerne, Spitalstrasse, CH-6000 Lucerne, Switzerland
- Emergency Department, University Children's Hospital Zurich, University of Zurich, Steinwiessstrasse 75, Zurich, CH 8032, Switzerland
| | - Juergen Fornaro
- Institute of Radiology and Nuclear Medicine, Cantonal Hospital Lucerne, Spitalstrasse, CH-6000 Lucerne, Switzerland
| | - Nikolai Stahr
- Institute of Radiology and Nuclear Medicine, Cantonal Hospital Lucerne, Spitalstrasse, CH-6000 Lucerne, Switzerland
- Pediatric Radiology Department, Children's Hospital Lucerne, Spitalstrasse, CH-6000 Lucerne, Switzerland
| | - Markus Lehner
- Pediatric Surgery Department, Children's Hospital Lucerne, Spitalstrasse, CH-6000 Lucerne, Switzerland
| | - Justus E Roos
- Institute of Radiology and Nuclear Medicine, Cantonal Hospital Lucerne, Spitalstrasse, CH-6000 Lucerne, Switzerland
| | - Thiago Viana Miranda Lima
- Institute of Radiology and Nuclear Medicine, Cantonal Hospital Lucerne, Spitalstrasse, CH-6000 Lucerne, Switzerland
- Institute of Radiation Physics, Lausanne University Hospital, University of Lausanne, Lausanne, Switzerland
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13
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Barreto IL, Tuna IS, Rajderkar DA, Ching JA, Governale LS. Pediatric craniosynostosis computed tomography: an institutional experience in reducing radiation dose while maintaining diagnostic image quality. Pediatr Radiol 2022; 52:85-96. [PMID: 34731286 DOI: 10.1007/s00247-021-05205-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/09/2021] [Revised: 07/15/2021] [Accepted: 09/09/2021] [Indexed: 11/25/2022]
Abstract
BACKGROUND Children with craniosynostosis may undergo multiple computed tomography (CT) examinations for diagnosis and post-treatment follow-up, resulting in cumulative radiation exposure. OBJECTIVE To reduce the risks associated with radiation exposure, we evaluated the compliance, radiation dose reduction and clinical image quality of a lower-dose CT protocol for pediatric craniosynostosis implemented at our institution. MATERIALS AND METHODS The standard of care at our institution was modified to replace pediatric head CT protocols with a lower-dose CT protocol utilizing 100 kV, 5 mAs and iterative reconstruction. Study-ordered, protocol-utilized and radiation-dose indices were collected for studies performed with routine pediatric brain protocols (n=22) and with the lower-dose CT protocol (n=135). Two pediatric neuroradiologists evaluated image quality in a subset (n=50) of the lower-dose CT studies by scoring visualization of cranial structures, confidence of diagnosis and the need for more radiation dose. RESULTS During the 30-month period, the lower-dose CT protocol had high compliance, with 2/137 studies performed with routine brain protocols. With the lower-dose CT protocol, volume CT dose index (CTDIvol) was 1.1 mGy for all patients (0-9 years old) and effective dose ranged from 0.06 to 0.22 mSv, comparable to a 4-view skull radiography examination. CTDIvol was reduced by 98% and effective dose was reduced up to 67-fold. Confidence in diagnosing craniosynostosis was high and more radiation dose was considered unnecessary in all studies (n=50) by both radiologists. CONCLUSION Replacing the routine pediatric brain CT protocol with a lower-dose CT craniosynostosis protocol substantially reduced radiation exposure without compromising image quality or diagnostic confidence.
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Affiliation(s)
- Izabella L Barreto
- Division of Medical Physics, Department of Radiology, University of Florida, P.O. Box 100374, Gainesville, FL, 32610, USA.
| | - Ibrahim S Tuna
- Department of Radiology, University of Florida, Gainesville, FL, USA
| | | | - Jessica A Ching
- Division of Plastic and Reconstructive Surgery, Department of Surgery, University of Florida, Gainesville, FL, USA.,Craniofacial Center, UF Health Shands Children's Hospital, Gainesville, FL, USA
| | - Lance S Governale
- Craniofacial Center, UF Health Shands Children's Hospital, Gainesville, FL, USA.,Division of Pediatric Neurosurgery, Department of Neurosurgery, University of Florida, Gainesville, FL, USA
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14
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Image quality in liver CT: low-dose deep learning vs standard-dose model-based iterative reconstructions. Eur Radiol 2021; 32:2865-2874. [PMID: 34821967 DOI: 10.1007/s00330-021-08380-0] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2021] [Revised: 09/15/2021] [Accepted: 10/04/2021] [Indexed: 10/19/2022]
Abstract
OBJECTIVES To compare the overall image quality and detectability of significant (malignant and pre-malignant) liver lesions of low-dose liver CT (LDCT, 33.3% dose) using deep learning denoising (DLD) to standard-dose CT (SDCT, 100% dose) using model-based iterative reconstruction (MBIR). METHODS In this retrospective study, CT images of 80 patients with hepatic focal lesions were included. For noninferiority analysis of overall image quality, a margin of - 0.5 points (scored in a 5-point scale) for the difference between scan protocols was pre-defined. Other quantitative or qualitative image quality assessments were performed. Additionally, detectability of significant liver lesions was compared, with 64 pairs of CT, using the jackknife alternative free-response ROC analysis, with noninferior margin defined by the lower limit of 95% confidence interval (CI) of the difference of figure-of-merit less than - 0.1. RESULTS The mean overall image quality scores with LDCT and SDCT were 3.77 ± 0.38 and 3.94 ± 0.34, respectively, demonstrating a difference of - 0.17 (95% CI: - 0.21 to - 0.12), which did not cross the predefined noninferiority margin of - 0.5. Furthermore, LDCT showed significantly superior quantitative results of liver lesion contrast to noise ratio (p < 0.05). However, although LDCT scored higher than the average score in qualitative image quality assessments, they were significantly lower than those of SDCT (p < 0.05). Figure-of-merit for lesion detection was 0.859 for LDCT and 0.878 for SDCT, showing noninferiority (difference: - 0.019, 95% CI: - 0.058 to 0.021). CONCLUSION LDCT using DLD with 67% radiation dose reduction showed non-inferior overall image quality and lesion detectability, compared to SDCT. KEY POINTS • Low-dose liver CT using deep learning denoising (DLD), at 67% dose reduction, provided non-inferior overall image quality compared to standard-dose CT using model-based iterative reconstruction (MBIR). • Low-dose CT using DLD showed significantly less noise and higher CNR lesion to liver than standard-dose CT using MBIR and demonstrated at least average image quality score among all readers, albeit with lower scores than standard-dose CT using MBIR. • Low-dose liver CT showed noninferior detectability for malignant and pre-malignant liver lesions, compared to standard-dose CT.
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15
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Larsson J, Båth M, Thilander-Klang A. FREQUENCY RESPONSE AND DISTORTION PROPERTIES OF RECONSTRUCTION ALGORITHMS IN COMPUTED TOMOGRAPHY. RADIATION PROTECTION DOSIMETRY 2021; 195:416-425. [PMID: 33954785 PMCID: PMC8507449 DOI: 10.1093/rpd/ncab058] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/30/2020] [Revised: 03/19/2021] [Accepted: 03/26/2021] [Indexed: 06/12/2023]
Abstract
Denoising reconstruction techniques can introduce nonlinear properties into computed tomography (CT) systems. These nonlinear algorithms introduce distortion which affects the assessment of the resolution of the system. The purpose of the present study was to decouple and investigate amplitude modulation and waveform distortion in reconstruction algorithms in CT. The methodology developed by Wells, J. R. and Dobbins, J. T. III [Frequency response and distortion properties of nonlinear image processing algorithms and the importance of imaging context. Med. Phys. 40, 091906 (2013)] was adapted to CT reconstruction algorithms. The CT simulating program ASTRA Toolbox© for MATLAB™ was used for the reconstruction of the sinusoidal wave functions. Filtered back projection and the simultaneous iterative reconstruction technique were investigated with simple nonlinear mechanisms: a median filter and a non-negative constraint, respectively. The native reconstruction algorithms were not free from nonlinear waveform distortion, however, none of the metrics showed any dependence on the contrast-to-noise ratio (CNR). Furthermore, the algorithms including nonlinear mechanisms showed a clear and specific CNR dependence, indicating the necessity for distortion analysis in nonlinear CT reconstruction.
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Affiliation(s)
| | - Magnus Båth
- Department of Radiation Physics, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg SE-413 45, Sweden
- Department of Medical Physics and Biomedical Engineering, Sahlgrenska University Hospital, Gothenburg SE-413 45, Sweden
| | - Anne Thilander-Klang
- Department of Radiation Physics, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg SE-413 45, Sweden
- Department of Medical Physics and Biomedical Engineering, Sahlgrenska University Hospital, Gothenburg SE-413 45, Sweden
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Noda Y, Iritani Y, Kawai N, Miyoshi T, Ishihara T, Hyodo F, Matsuo M. Deep learning image reconstruction for pancreatic low-dose computed tomography: comparison with hybrid iterative reconstruction. Abdom Radiol (NY) 2021; 46:4238-4244. [PMID: 33973060 DOI: 10.1007/s00261-021-03111-x] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2021] [Revised: 04/12/2021] [Accepted: 04/27/2021] [Indexed: 12/12/2022]
Abstract
PURPOSE To evaluate image quality, image noise, and conspicuity of pancreatic ductal adenocarcinoma (PDAC) in pancreatic low-dose computed tomography (LDCT) reconstructed using deep learning image reconstruction (DLIR) and compare with those of images reconstructed using hybrid iterative reconstruction (IR). METHODS Our institutional review board approved this prospective study. Written informed consent was obtained from all patients. Twenty-eight consecutive patients with PDAC undergoing chemotherapy (14 men and 14 women; mean age, 68.4 years) underwent pancreatic LDCT for therapy evaluation. The LDCT images were reconstructed using 40% adaptive statistical iterative reconstruction-Veo (hybrid-IR) and DLIR at medium and high levels (DLIR-M and DLIR-H). The image noise, diagnostic acceptability, and conspicuity of PDAC were qualitatively assessed using a 5-point scale. CT numbers of the abdominal aorta, portal vein, pancreas, PDAC, background noise, signal-to-noise ratio (SNR) of the anatomical structures, and tumor-to-pancreas contrast-to-noise ratio (CNR) were calculated. Qualitative and quantitative parameters were compared between the hybrid-IR, DLIR-M, and DLIR-H images. RESULTS CT dose-index volumes and dose-length product in pancreatic LDCT were 2.3 ± 1.0 mGy and 74.9 ± 37.0 mGy•cm, respectively. The image noise, diagnostic acceptability, and conspicuity of PDAC were significantly better in DLIR-H than those in hybrid-IR and DLIR-M (all P < 0.001). The background noise was significantly lower in the DLIR-H images (P < 0.001) and resulted in improved SNRs (P < 0.001) and CNR (P < 0.001) compared with those in the hybrid-IR and DLIR-M images. CONCLUSION DLIR significantly reduced image noise and improved image quality in pancreatic LDCT images compared with hybrid-IR.
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17
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Seah J, Brady Z, Ewert K, Law M. Artificial intelligence in medical imaging: implications for patient radiation safety. Br J Radiol 2021; 94:20210406. [PMID: 33989035 DOI: 10.1259/bjr.20210406] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
Artificial intelligence, including deep learning, is currently revolutionising the field of medical imaging, with far reaching implications for almost every facet of diagnostic imaging, including patient radiation safety. This paper introduces basic concepts in deep learning and provides an overview of its recent history and its application in tomographic reconstruction as well as other applications in medical imaging to reduce patient radiation dose, as well as a brief description of previous tomographic reconstruction techniques. This review also describes the commonly used deep learning techniques as applied to tomographic reconstruction and draws parallels to current reconstruction techniques. Finally, this paper reviews some of the estimated dose reductions in CT and positron emission tomography in the recent literature enabled by deep learning, as well as some of the potential problems that may be encountered such as the obscuration of pathology, and highlights the need for additional clinical reader studies from the imaging community.
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Affiliation(s)
- Jarrel Seah
- Department of Radiology, Alfred Health, Melbourne, Australia.,Department of Neuroscience, Monash University, Melbourne, Australia.,Annalise.AI, Sydney, Australia
| | - Zoe Brady
- Department of Radiology, Alfred Health, Melbourne, Australia.,Department of Neuroscience, Monash University, Melbourne, Australia
| | - Kyle Ewert
- Department of Radiology, Alfred Health, Melbourne, Australia
| | - Meng Law
- Department of Radiology, Alfred Health, Melbourne, Australia.,Department of Neuroscience, Monash University, Melbourne, Australia.,Department of Electrical and Computer Systems Engineering, Monash University, Melbourne, Australia
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18
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Facchini G, Ceccarelli L, Tomà P, Bartoloni A. Recent Imaging Advancements for Lung Metastases in Children with Sarcoma. Curr Med Imaging 2021; 17:236-243. [PMID: 33371858 DOI: 10.2174/1573405616666201228125657] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2020] [Revised: 11/19/2020] [Accepted: 12/07/2020] [Indexed: 11/22/2022]
Abstract
In children and adolescents affected by musculoskeletal sarcomas (both soft tissue and bone sarcomas), the presence of lung metastases is a frequent complication, that should be known since the patient's prognosis, as management, and treatment depend on it. During the staging phase, the detection of lung metastases should be sensitive and specific, and it should be carried out by minimizing the radiation exposure. To deal with this problem, imaging has reached important goals in recent years, thanks to the development of cone-beam CT or low-dose computed tomography, with some new iterative reconstruction methods, such as Veo and ASIR. Imaging is also fundamental for the possibility to perform lung biopsies under CT guidance, with less morbidity, less time-consumption, and shorter recovery time, compared to surgical biopsies.Moreover, important results have also been demonstrated in the treatment of lung metastases, due to the improvement of new mini-invasive image-guided percutaneous thermal ablation procedures, which proved to be safe and effective also in young patients.
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Affiliation(s)
- Giancarlo Facchini
- Diagnostic and Interventional Radiology, IRCCS Istituto Ortopedico Rizzoli, Bologna, Italy
| | - Luca Ceccarelli
- Diagnostic and Interventional Radiology, IRCCS Istituto Ortopedico Rizzoli, Bologna, Italy
| | - Paolo Tomà
- Department of Imaging, IRCCS Ospedale Pediatrico Bambino Gesu, Rome, Italy
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Liu H, Wingert A, Wang J, Zhang J, Wang X, Sun J, Chen F, Khalid SG, Jiang J, Zheng D. Extraction of Coronary Atherosclerotic Plaques From Computed Tomography Imaging: A Review of Recent Methods. Front Cardiovasc Med 2021; 8:597568. [PMID: 33644127 PMCID: PMC7903898 DOI: 10.3389/fcvm.2021.597568] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2020] [Accepted: 01/18/2021] [Indexed: 12/21/2022] Open
Abstract
Background: Atherosclerotic plaques are the major cause of coronary artery disease (CAD). Currently, computed tomography (CT) is the most commonly applied imaging technique in the diagnosis of CAD. However, the accurate extraction of coronary plaque geometry from CT images is still challenging. Summary of Review: In this review, we focused on the methods in recent studies on the CT-based coronary plaque extraction. According to the dimension of plaque extraction method, the studies were categorized into two-dimensional (2D) and three-dimensional (3D) ones. In each category, the studies were analyzed in terms of data, methods, and evaluation. We summarized the merits and limitations of current methods, as well as the future directions for efficient and accurate extraction of coronary plaques using CT imaging. Conclusion: The methodological innovations are important for more accurate CT-based assessment of coronary plaques in clinical applications. The large-scale studies, de-blooming algorithms, more standardized datasets, and more detailed classification of non-calcified plaques could improve the accuracy of coronary plaque extraction from CT images. More multidimensional geometric parameters can be derived from the 3D geometry of coronary plaques. Additionally, machine learning and automatic 3D reconstruction could improve the efficiency of coronary plaque extraction in future studies.
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Affiliation(s)
- Haipeng Liu
- Research Centre for Intelligent Healthcare, Coventry University, Coventry, United Kingdom.,Faculty of Health, Education, Medicine, and Social Care, Anglia Ruskin University, Chelmsford, United Kingdom
| | - Aleksandra Wingert
- Faculty of Health, Education, Medicine, and Social Care, Anglia Ruskin University, Chelmsford, United Kingdom
| | - Jian'an Wang
- Department of Cardiology, School of Medicine, The Second Affiliated Hospital, Zhejiang University, Hangzhou, China
| | - Jucheng Zhang
- Department of Clinical Engineering, School of Medicine, The Second Affiliated Hospital, Zhejiang University, Hangzhou, China
| | - Xinhong Wang
- Department of Radiology, School of Medicine, The Second Affiliated Hospital, Zhejiang University, Hangzhou, China
| | - Jianzhong Sun
- Department of Radiology, School of Medicine, The Second Affiliated Hospital, Zhejiang University, Hangzhou, China
| | - Fei Chen
- Department of Electrical and Electronic Engineering, Southern University of Science and Technology, Shenzhen, China
| | - Syed Ghufran Khalid
- Research Centre for Intelligent Healthcare, Coventry University, Coventry, United Kingdom
| | - Jun Jiang
- Department of Cardiology, School of Medicine, The Second Affiliated Hospital, Zhejiang University, Hangzhou, China
| | - Dingchang Zheng
- Research Centre for Intelligent Healthcare, Coventry University, Coventry, United Kingdom
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20
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Muhammad N, Sabarudin A, Ismail N, Karim M. A systematic review and meta-analysis of radiation dose exposure from computed tomography examination of thorax-abdomen-pelvic regions among paediatric population. Radiat Phys Chem Oxf Engl 1993 2021. [DOI: 10.1016/j.radphyschem.2020.109148] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
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21
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Franck C, Zhang G, Deak P, Zanca F. Preserving image texture while reducing radiation dose with a deep learning image reconstruction algorithm in chest CT: A phantom study. Phys Med 2021; 81:86-93. [PMID: 33445125 DOI: 10.1016/j.ejmp.2020.12.005] [Citation(s) in RCA: 33] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/03/2020] [Revised: 11/23/2020] [Accepted: 12/05/2020] [Indexed: 02/03/2023] Open
Abstract
PURPOSE To assess whether a deep learning image reconstruction algorithm (TrueFidelity) can preserve the image texture of conventional filtered back projection (FBP) at reduced dose levels attained by ASIR-V in chest CT. METHODS Phantom images were acquired using a clinical chest protocol (7.6 mGy) and two levels of dose reduction (60% and 80%). Images were reconstructed with FBP, ASIR-V (50% and 100% blending) and TrueFidelity (low (DL-L), medium (DL-M) and high (DL-H) strength). Noise (SD), noise power spectrum (NPS) and task-based transfer function (TTF) were calculated. Noise texture was quantitatively compared by computing root-mean-square deviations (RMSD) of NPS with respect to FBP. Four experienced readers performed a contrast-detail evaluation. The dose reducing potential of TrueFidelity compared to ASIR-V was assessed by fitting SD and contrast-detail as a function of dose. RESULTS DL-M and DL-H reduced noise and NPS area compared to FBP and 50% ASIR-V, at all dose levels. At 7.6 mGy, NPS of ASIR-V 50/100% was shifted towards lower frequencies (fpeak = 0.22/0.13 mm-1, RMSD = 0.14/0.38), with respect to FBP (fpeak = 0.30 mm-1). Marginal difference was observed for TrueFidelity: fpeak = 0.33/0.30/0.30 mm-1 and RMSD = 0.03/0.04/0.07 for L/M/H strength. Values of TTF50% were independent of DL strength and higher compared to FBP and ASIR-V, at all dose and contrast levels. Contrast-detail was highest for DL-H at all doses. Compared to 50% ASIR-V, DL-H had an estimated dose reducing potential of 50% on average, without impairing noise, texture and detectability. CONCLUSIONS TrueFidelity preserves the image texture of FBP, while outperforming ASIR-V in terms of noise, spatial resolution and detectability at lower doses.
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Affiliation(s)
- Caro Franck
- Department of Radiology, University Hospital Antwerp, Drie Eikenstraat 655, 2650 Edegem, Belgium; mVISION, Faculty of Medicine and Health Sciences, University of Antwerp, Drie Eikenstraat 655, 2650 Edegem, Belgium.
| | - Guozhi Zhang
- Department of Radiology, KU Leuven University Hospitals Leuven, Leuven, Belgium
| | - Paul Deak
- GE Healthcare, Glattbrugg, Switzerland
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22
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Hamaguchi N, Fujima N, Hamaguchi A, Kodera S. Improved Depictions of the Anterior Choroidal Artery and Thalamoperforating Arteries on 3D-CTA Images Using Model-based Iterative Reconstruction. Acad Radiol 2021; 28:e14-e19. [PMID: 32037258 DOI: 10.1016/j.acra.2020.01.010] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2019] [Revised: 12/31/2019] [Accepted: 01/01/2020] [Indexed: 11/25/2022]
Abstract
RATIONALE AND OBJECTIVES To evaluate the depictability of intracranial small arteries using high-resolution CTA with model-based iterative reconstruction (MBIR). MATERIALS AND METHODS We retrospectively analyzed 21 patients who underwent brain 3D-CTA. Axial and volume-rendered (VR) images were reconstructed from the 3D-CTA raw data using adaptive statistical image reconstruction (ASIR) and MBIR. As a quantitative assessment, intra-arterial CT values of the ICA and contrast-to-noise ratio were measured to evaluate vessel enhancement. Additionally, CT values and standard deviations (SDs) of CT values and signal to noise ratio in white matter parenchyma were measured to evaluate background noise. As a qualitative assessment, the degree of vessel depictability in the anterior choroidal artery (AchoA) and the perforating branches of thalamoperforating arteries (TPA) on VR images using two different reconstruction algorithms was visually evaluated using a 3-point grading system. RESULTS The CT value of the ICA [605.27± 89.76 Hounsfield units (HU)] was significantly increased and the SD value (i.e., image noise) of the white matter parenchyma [6.79 ± 0.81(HU)] was decreased on MBIR compared with ASIR [546.76 ± 85.27 (HU)] and [8.04 ± 1.08 HU)] (p <.05 for all). Contrast-to-noise ratio of ICA [84.48 ± 20.17] and signal to noise ratio of white matter [6.18 ± 0.75] with MBIR were significantly higher than ASIR [65.98 ± 13.08] and [5.28 ± 0.78] (p < 0.05 for all). In addition, depictions of the AchoA and TPA on VR images were significantly improved using MBIR compared with ASIR (p < 0.05). CONCLUSION MBIR allows depiction of small intracranial arteries such as AchoA and TPA with better visibility than ASIR without increasing the dose of radiation and the amount of contrast agent.
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23
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Brady SL, Trout AT, Somasundaram E, Anton CG, Li Y, Dillman JR. Improving Image Quality and Reducing Radiation Dose for Pediatric CT by Using Deep Learning Reconstruction. Radiology 2020; 298:180-188. [PMID: 33201790 DOI: 10.1148/radiol.2020202317] [Citation(s) in RCA: 77] [Impact Index Per Article: 19.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Background CT deep learning reconstruction (DLR) algorithms have been developed to remove image noise. How the DLR affects image quality and radiation dose reduction has yet to be fully investigated. Purpose To investigate a DLR algorithm's dose reduction and image quality improvement for pediatric CT. Materials and Methods DLR was compared with filtered back projection (FBP), statistical-based iterative reconstruction (SBIR), and model-based iterative reconstruction (MBIR) in a retrospective study by using data from CT examinations of pediatric patients (February to December 2018). A comparison of object detectability for 15 objects (diameter, 0.5-10 mm) at four contrast difference levels (50, 150, 250, and 350 HU) was performed by using a non-prewhitening-matched mathematical observer model with eye filter (d'NPWE), task transfer function, and noise power spectrum analysis. Object detectability was assessed by using area under the curve analysis. Three pediatric radiologists performed an observer study to assess anatomic structures with low object-to-background signal and contrast to noise in the azygos vein, right hepatic vein, common bile duct, and superior mesenteric artery. Observers rated from 1 to 10 (worst to best) for edge definition, quantum noise level, and object conspicuity. Analysis of variance and Tukey honest significant difference post hoc tests were used to analyze differences between reconstruction algorithms. Results Images from 19 patients (mean age, 11 years ± 5 [standard deviation]; 10 female patients) were evaluated. Compared with FBP, SBIR, and MBIR, DLR demonstrated improved object detectability by 51% (16.5 of 10.9), 18% (16.5 of 13.9), and 11% (16.5 of 14.8), respectively. DLR reduced image noise without noise texture effects seen with MBIR. Radiologist ratings were 7 ± 1 (DLR), 6.2 ± 1 (MBIR), 6.2 ± 1 (SBIR), and 4.6 ± 1 (FBP); two-way analysis of variance showed a difference on the basis of reconstruction type (P < .001). Radiologists consistently preferred DLR images (intraclass correlation coefficient, 0.89; 95% CI: 0.83, 0.93). DLR demonstrated 52% (1 of 2.1) greater dose reduction than SBIR. Conclusion The DLR algorithm improved image quality and dose reduction without sacrificing noise texture and spatial resolution. © RSNA, 2020 Online supplemental material is available for this article.
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Affiliation(s)
- Samuel L Brady
- From the Department of Radiology, Cincinnati Children's Hospital Medical Center, 3333, Burnet Ave, Cincinnati, OH 45329; and Department of Radiology, University of Cincinnati Medical School, Cincinnati, Ohio
| | - Andrew T Trout
- From the Department of Radiology, Cincinnati Children's Hospital Medical Center, 3333, Burnet Ave, Cincinnati, OH 45329; and Department of Radiology, University of Cincinnati Medical School, Cincinnati, Ohio
| | - Elanchezhian Somasundaram
- From the Department of Radiology, Cincinnati Children's Hospital Medical Center, 3333, Burnet Ave, Cincinnati, OH 45329; and Department of Radiology, University of Cincinnati Medical School, Cincinnati, Ohio
| | - Christopher G Anton
- From the Department of Radiology, Cincinnati Children's Hospital Medical Center, 3333, Burnet Ave, Cincinnati, OH 45329; and Department of Radiology, University of Cincinnati Medical School, Cincinnati, Ohio
| | - Yinan Li
- From the Department of Radiology, Cincinnati Children's Hospital Medical Center, 3333, Burnet Ave, Cincinnati, OH 45329; and Department of Radiology, University of Cincinnati Medical School, Cincinnati, Ohio
| | - Jonathan R Dillman
- From the Department of Radiology, Cincinnati Children's Hospital Medical Center, 3333, Burnet Ave, Cincinnati, OH 45329; and Department of Radiology, University of Cincinnati Medical School, Cincinnati, Ohio
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Kiriki M, Muraoka R, Maeda K, Ikeuchi Y, Aoyama S, Nakano S, Kotoura N. [Effects of Iterative Reconstruction on Image Quality of Pediatric Body Computed Tomography Images]. Nihon Hoshasen Gijutsu Gakkai Zasshi 2020; 76:1035-1043. [PMID: 33087649 DOI: 10.6009/jjrt.2020_jsrt_76.10.1035] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
This study evaluated the effects of three types of hybrid iterative reconstruction (IR) on image quality of pediatric body computed tomography images. The image quality components evaluated were noise power spectrum (NPS), task-based modulation transfer function (TTF), and system performance function (SPF). As the IR strength was increased while reducing the radiation dose, the NPS increased in a low-frequency range and the TTF decreased in low-contrast regions. In the low-contrast regions, the calculated SPF decreased over the entire frequency range. Alternatively, in the high-contrast regions, the SPF decreased in the low-frequency regions and increased in the high-frequency regions. The radiation dose reduction using the hybrid IR resulted in the deterioration of the image quality in the low-contrast regions and changes in the spatial frequency characteristics in the high-contrast regions.
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Affiliation(s)
- Masato Kiriki
- Department of Radiological Technology, Hyogo College of Medicine College Hospital
| | - Rina Muraoka
- Department of Radiological Technology, Hyogo College of Medicine College Hospital
| | - Katsuhiko Maeda
- Department of Radiological Technology, Hyogo College of Medicine College Hospital
| | - Yoko Ikeuchi
- Department of Radiological Technology, Hyogo College of Medicine College Hospital
| | - Shuhei Aoyama
- Department of Radiological Technology, Hyogo College of Medicine College Hospital
| | - Shinya Nakano
- Department of Radiological Technology, Hyogo College of Medicine College Hospital
| | - Noriko Kotoura
- Department of Radiological Technology, Hyogo College of Medicine College Hospital
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Kubo Y, Ito K, Sone M, Nagasawa H, Onishi Y, Umakoshi N, Hasegawa T, Akimoto T, Kusumoto M. Diagnostic Value of Model-Based Iterative Reconstruction Combined with a Metal Artifact Reduction Algorithm during CT of the Oral Cavity. AJNR Am J Neuroradiol 2020; 41:2132-2138. [PMID: 32972957 DOI: 10.3174/ajnr.a6767] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2020] [Accepted: 07/07/2020] [Indexed: 12/28/2022]
Abstract
BACKGROUND AND PURPOSE Metal artifacts reduce the quality of CT images and increase the difficulty of interpretation. This study compared the ability of model-based iterative reconstruction and hybrid iterative reconstruction to improve CT image quality in patients with metallic dental artifacts when both techniques were combined with a metal artifact reduction algorithm. MATERIALS AND METHODS This retrospective clinical study included 40 patients (men, 31; women, 9; mean age, 62.9 ± 12.3 years) with oral and oropharyngeal cancer who had metallic dental fillings or implants and underwent contrast-enhanced ultra-high-resolution CT of the neck. Axial CT images were reconstructed using hybrid iterative reconstruction and model-based iterative reconstruction, and the metal artifact reduction algorithm was applied to all images. Finally, hybrid iterative reconstruction + metal artifact reduction algorithms and model-based iterative reconstruction + metal artifact reduction algorithm data were obtained. In the quantitative analysis, SDs were measured in ROIs over the apex of the tongue (metal artifacts) and nuchal muscle (no metal artifacts) and were used to calculate the metal artifact indexes. In a qualitative analysis, 3 radiologists blinded to the patients' conditions assessed the image-quality scores of metal artifact reduction and structural depictions. RESULTS Hybrid iterative reconstruction + metal artifact reduction algorithms and model-based iterative reconstruction + metal artifact reduction algorithms yielded significantly different metal artifact indexes of 82.2 and 73.6, respectively (95% CI, 2.6-14.7; P < .01). The latter algorithms resulted in significant reduction in metal artifacts and significantly improved structural depictions(P < .01). CONCLUSIONS Model-based iterative reconstruction + metal artifact reduction algorithms significantly reduced the artifacts and improved the image quality of structural depictions on neck CT images.
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Affiliation(s)
- Y Kubo
- From the Department of Diagnostic Radiology (Y.K., K.I., M.S., H.N., Y.O., N.U., T.H., M.K.), National Cancer Center Hospital, Tokyo, Japan .,Department of Cancer Medicine (Y.K., T.A.), Jikei University Graduate School of Medicine, Tokyo, Japan
| | - K Ito
- From the Department of Diagnostic Radiology (Y.K., K.I., M.S., H.N., Y.O., N.U., T.H., M.K.), National Cancer Center Hospital, Tokyo, Japan
| | - M Sone
- From the Department of Diagnostic Radiology (Y.K., K.I., M.S., H.N., Y.O., N.U., T.H., M.K.), National Cancer Center Hospital, Tokyo, Japan
| | - H Nagasawa
- From the Department of Diagnostic Radiology (Y.K., K.I., M.S., H.N., Y.O., N.U., T.H., M.K.), National Cancer Center Hospital, Tokyo, Japan
| | - Y Onishi
- From the Department of Diagnostic Radiology (Y.K., K.I., M.S., H.N., Y.O., N.U., T.H., M.K.), National Cancer Center Hospital, Tokyo, Japan
| | - N Umakoshi
- From the Department of Diagnostic Radiology (Y.K., K.I., M.S., H.N., Y.O., N.U., T.H., M.K.), National Cancer Center Hospital, Tokyo, Japan
| | - T Hasegawa
- From the Department of Diagnostic Radiology (Y.K., K.I., M.S., H.N., Y.O., N.U., T.H., M.K.), National Cancer Center Hospital, Tokyo, Japan
| | - T Akimoto
- Department of Cancer Medicine (Y.K., T.A.), Jikei University Graduate School of Medicine, Tokyo, Japan.,Division of Radiation Oncology and Particle Therapy (T.A.), National Cancer Center Hospital East, Kashiwa, Japan
| | - M Kusumoto
- From the Department of Diagnostic Radiology (Y.K., K.I., M.S., H.N., Y.O., N.U., T.H., M.K.), National Cancer Center Hospital, Tokyo, Japan
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Park C, Choo KS, Kim JH, Nam KJ, Lee JW, Kim JY. Image Quality and Radiation Dose in CT Venography Using Model-Based Iterative Reconstruction at 80 kVp versus Adaptive Statistical Iterative Reconstruction-V at 70 kVp. Korean J Radiol 2020; 20:1167-1175. [PMID: 31270980 PMCID: PMC6609434 DOI: 10.3348/kjr.2018.0897] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2018] [Accepted: 03/17/2019] [Indexed: 12/26/2022] Open
Abstract
Objective To compare the objective and subjective image quality indicators and radiation doses of computed tomography (CT) venography performed using model-based iterative reconstruction (MBIR) at 80 kVp and adaptive statistical iterative reconstruction (ASIR)-V at 70 kVp. Materials and Methods Eighty-three patients who had undergone CT venography of the lower extremities with MBIR at 80 kVp (Group A; 21 men and 20 women; mean age, 55.5 years) or ASIR-V at 70 kVp (Group B; 18 men and 24 women; mean age, 57.3 years) were enrolled. Two radiologists retrospectively evaluated the objective (vascular enhancement, image noise, signal-to-noise ratio [SNR], contrast-to-noise ratio [CNR]) and subjective (quantum mottle, delineation of contour, venous enhancement) image quality indicators at the inferior vena cava and femoral and popliteal veins. Clinical information, radiation dose, reconstruction time, and objective and subjective image quality indicators were compared between groups A and B. Results Vascular enhancement, SNR, and CNR were significantly greater in Group B than in Group A (p ≤ 0.015). Image noise was significantly lower in Group B (p ≤ 0.021), and all subjective image quality indicators, except for delineation of vein contours, were significantly better in Group B (p ≤ 0.021). Mean reconstruction time was significantly shorter in Group B than in Group A (1 min 43 s vs. 131 min 1 s; p < 0.001). Clinical information and radiation dose were not significantly different between the two groups. Conclusion CT venography using ASIR-V at 70 kVp was better than MBIR at 80 kVp in terms of image quality and reconstruction time at similar radiation doses.
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Affiliation(s)
- Chankue Park
- Department of Radiology, Pusan National University Yangsan Hospital, Yangsan, Korea
| | - Ki Seok Choo
- Department of Radiology, Pusan National University Yangsan Hospital, Yangsan, Korea.
| | - Jin Hyeok Kim
- Department of Radiology, Pusan National University Yangsan Hospital, Yangsan, Korea
| | - Kyung Jin Nam
- Department of Radiology, Pusan National University Yangsan Hospital, Yangsan, Korea
| | - Ji Won Lee
- Department of Radiology, Pusan National University Hospital, Busan, Korea
| | - Jin You Kim
- Department of Radiology, Pusan National University Hospital, Busan, Korea
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Tugwell-Allsup J, Owen BW, England A. Low-dose chest CT and the impact on nodule visibility. Radiography (Lond) 2020; 27:24-30. [PMID: 32499090 DOI: 10.1016/j.radi.2020.05.004] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2020] [Revised: 05/07/2020] [Accepted: 05/08/2020] [Indexed: 11/16/2022]
Abstract
INTRODUCTION The need to continually optimise CT protocols is essential to ensure the lowest possible radiation dose for the clinical task and individual patient. The aim of this study was to explore the effect of reducing effective mAs on nodule detection and radiation dose across six scanners. METHODS An anthropomorphic chest phantom was scanned using a low-dose chest CT protocol, with the effective mAs lowered to the lowest permissible level. All other acquisition parameters remained consistent. Images were evaluated by five radiologists to determine their sensitivity in detecting six simulated nodules within the phantom. Image noise was calculated together with DLP. RESULTS The lowest possible mAs achievable ranged from 7 to 19 mAs. The two highest mAs setting (17 mAs + 19 mAs) had kV modulation enabled (100 kV instead of 120 kV) which consequently resulted in a higher nodule detection rate. Overall nodule detection averaged at 91% (range 80-97%). Out of a possible 180 nodules, 16 were missed, with 12 of those 16 being the same nodule. Noise was double for the Somatom Sensation scanner when compared to the others; however, this scanner did not have iterative reconstruction and it was installed over 10 years ago. There was a strong correlation between image noise and scanner age. CONCLUSION This study highlighted that nodules can be detected at very low effective mAs (<20 mAs) but only when other acquisition parameters are optimised i.e. iterative reconstruction and kV modulation. Nodule detection rates were affected by nodule location and image noise. IMPLICATIONS FOR PRACTICE This study consolidates previous findings on how to successfully optimise low-dose chest CT. It also highlights the difficulty with standardisation owing to factors such as scanner age and different vendor attributes.
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Affiliation(s)
- J Tugwell-Allsup
- Betsi Cadwaladr University Health Board, Bangor, Gwynedd, Wales, LL57 2PW, UK.
| | - B W Owen
- Betsi Cadwaladr University Health Board, Bangor, Gwynedd, Wales, LL57 2PW, UK.
| | - A England
- School of Health Sciences, Salford University, Manchester, M6 6PU, UK.
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Rubert N, Southard R, Hamman SM, Robison R. Evaluation of low-contrast detectability for iterative reconstruction in pediatric abdominal computed tomography: a phantom study. Pediatr Radiol 2020; 50:345-356. [PMID: 31705156 DOI: 10.1007/s00247-019-04561-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/26/2019] [Revised: 09/23/2019] [Accepted: 10/16/2019] [Indexed: 12/20/2022]
Abstract
BACKGROUND Iterative reconstruction is offered by all vendors to achieve similar or better CT image quality at lower doses than images reconstructed with filtered back-projection. OBJECTIVE The purpose of this study was to investigate the dose-reduction potential for pediatric abdominal CT imaging when using either a commercially available hybrid or a commercially available model-based iterative reconstruction algorithm from a single manufacturer. MATERIALS AND METHODS A phantom containing four low-contrast inserts and a uniform background with total attenuation equivalent to the abdomen of an average 8-year-old child was imaged on a CT scanner (IQon; Philips Healthcare, Cleveland, OH). We reconstructed images using both hybrid iterative reconstruction (iDose4) and model-based iterative reconstruction (Iterative Model Reconstruction). The four low-contrast inserts had circular cross-section with diameters of 3 mm, 5 mm, 7 mm and 10 mm and contrasts of 14 Hounsfield units (HU), 7 HU, 5 HU and 3 HU, respectively. Helical scans with identical kilovoltage (kV), pitch, rotation time, and collimation were repeated on the phantom at volume CT dose index (CTDIvol) of 2.0 milligrays (mGy), 3.0 mGy, 4.5 mGy and 6.0 mGy. We measured the contrast-to-noise ratio (CNR) in each rod across scans. Additionally, we collected sub-images containing each rod and sub-images containing the background and used them in two-alternative forced choice observer experiments with four observers (two radiologists and two physicists). We calculated the dose-reduction potential of both iterative reconstruction algorithms relative to a scan performed at 6 mGy and reconstructed with filtered back-projection. RESULTS We calculated dose-reduction potential by either matching average equal observer performance in the two-alternative forced choice experiments or matching CNR. When matching CNR, the dose-reduction potential was 34% to 45% for hybrid iterative reconstruction and 89% to 95% for model-based iterative reconstruction. When matching average observer performance, the dose-reduction potential was 9% to 30% for hybrid iterative reconstruction and 57% to 74% for model-based iterative reconstruction. The range in dose-reduction potential depended on the rod size and contrast level. CONCLUSION Observer performance in this phantom study indicates that the dose-reduction potential indicated by an observer study is less than that of CNR; extrapolating the results to clinical studies suggests that the dose-reduction potential would also be less.
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Affiliation(s)
- Nicholas Rubert
- Department of Radiology, Phoenix Children's Hospital, 1919 E. Thomas Road, Phoenix, AZ, 85016, USA.
| | - Richard Southard
- Department of Radiology, Phoenix Children's Hospital, 1919 E. Thomas Road, Phoenix, AZ, 85016, USA.,College of Medicine, University of Arizona, Phoenix, AZ, USA
| | - Susan M Hamman
- Section of Pediatric Radiology, C. S. Mott Children's Hospital, Department of Radiology, University of Michigan Health System, Ann Arbor, MI, USA
| | - Ryan Robison
- Department of Radiology, Phoenix Children's Hospital, 1919 E. Thomas Road, Phoenix, AZ, 85016, USA.,College of Nursing and Health Innovation, Arizona State University, Phoenix, AZ, USA
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Impact of Patient Size and Radiation Dose on Accuracy and Precision of Iodine Quantification and Virtual Noncontrast Values in Dual-layer Detector CT-A Phantom Study. Acad Radiol 2020; 27:409-420. [PMID: 30987872 DOI: 10.1016/j.acra.2019.02.013] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2018] [Revised: 01/26/2019] [Accepted: 02/08/2019] [Indexed: 12/14/2022]
Abstract
RATIONALE AND OBJECTIVES Iodine quantification (IQ) and virtual noncontrast (VNC) images produced by dual-energy CT (DECT) can be used for various clinical applications. We investigate the performance of dual-layer DECT (DLDECT) in different phantom sizes and varying radiation doses and tube voltages, including a low-dose pediatric setting. MATERIALS AND METHODS Three phantom sizes (simulating a 10-year-old child, an average, and a large-sized adult) were scanned with iodine solution inserts with concentrations ranging 0-32 mg/ml, using the DLDECT. Each phantom size was scanned with CTDIvol 2-15 mGy at 120 and 140 kVp. The smallest phantom underwent additional scans with CTDIvol 0.9-1.8 mGy. All scans were repeated 3 times. Each iodine insert was analyzed using VNC and IQ images for accuracy and precision, by comparison to known values. RESULTS For scans from 2 to 15 mGy mean VNC attenuation and IQ error in the iodine inserts in the small, medium, and large phantoms was 1.2 HU ± 3.2, -1.2 HU ± 14.9, 2.6 HU ± 23.6; and +0.1 mg/cc ± 0.4, -0.9 mg/cc ± 0.9, and -1.8 mg/cc ± 1.8, respectively. In this dose range, there were no significant differences (p ≥ 0.05) in mean VNC attenuation or IQ accuracy in each phantom size, while IQ was significantly less precise in the small phantom at 2 mGy and 10 mGy (p < 0.05). Scans with CTDIvol 0.9-1.8 mGy in the small phantom showed a limited, but statistically significantly lower VNC attenuation precision and IQ accuracy (-0.5 HU ± 5.3 and -0.3 mg/cc ± 0.5, respectively) compared to higher dose scans in the same phantom size. CONCLUSION Performance of iodine quantification and subtraction by VNC images in DLDECT is largely dose independent, with the primary factor being patient size. Low-dose pediatric scan protocols have a significant, but limited impact on IQ and VNC attenuation values.
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Tamura A, Nakayama M, Ota Y, Kamata M, Hirota Y, Sone M, Hamano M, Tanaka R, Yoshioka K. Feasibility of thin-slice abdominal CT in overweight patients using a vendor neutral image-based denoising algorithm: Assessment of image noise, contrast, and quality. PLoS One 2019; 14:e0226521. [PMID: 31846490 PMCID: PMC6917298 DOI: 10.1371/journal.pone.0226521] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2019] [Accepted: 11/26/2019] [Indexed: 11/19/2022] Open
Abstract
The purpose of this study was to investigate whether the novel image-based noise reduction software (NRS) improves image quality, and to assess the feasibility of using this software in combination with hybrid iterative reconstruction (IR) in image quality on thin-slice abdominal CT. In this retrospective study, 54 patients who underwent dynamic liver CT between April and July 2017 and had a body mass index higher than 25 kg/m2 were included. Three image sets of each patient were reconstructed as follows: hybrid IR images with 1-mm slice thickness (group A), hybrid IR images with 5-mm slice thickness (group B), and hybrid IR images with 1-mm slice thickness denoised using NRS (group C). The mean image noise and contrast-to-noise ratio relative to the muscle of the aorta and liver were assessed. Subjective image quality was evaluated by two radiologists for sharpness, noise, contrast, and overall quality using 5-point scales. The mean image noise was significantly lower in group C than in group A (p < 0.01), but no significant difference was observed between groups B and C. The contrast-to-noise ratio was significantly higher in group C than in group A (p < 0.01 and p = 0.01, respectively). Subjective image quality was also significantly higher in group C than in group A (p < 0.01), in terms of noise and overall quality, but not in terms of sharpness and contrast (p = 0.65 and 0.07, respectively). The contrast of images in group C was greater than that in group A, but this difference was not significant. Compared with hybrid IR alone, the novel NRS combined with a hybrid IR could result in significant noise reduction without sacrificing image quality on CT. This combined approach will likely be particularly useful for thin-slice abdominal CT examinations of overweight patients.
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Affiliation(s)
- Akio Tamura
- Department of Radiology, Iwate Medical University School of Medicine, Morioka, Japan
- * E-mail:
| | - Manabu Nakayama
- Department of Radiology, Iwate Medical University School of Medicine, Morioka, Japan
| | - Yoshitaka Ota
- Division of Central Radiology, Iwate Medical University Hospital, Morioka, Japan
| | - Masayoshi Kamata
- Division of Central Radiology, Iwate Medical University Hospital, Morioka, Japan
| | - Yasuyuki Hirota
- Division of Central Radiology, Iwate Medical University Hospital, Morioka, Japan
| | - Misato Sone
- Department of Radiology, Iwate Medical University School of Medicine, Morioka, Japan
| | - Makoto Hamano
- Department of Radiology, Iwate Medical University School of Medicine, Morioka, Japan
| | - Ryoichi Tanaka
- Division of Dental Radiology, Department of General Dentistry, Iwate Medical University School of Dentistry, Morioka, Japan
| | - Kunihiro Yoshioka
- Department of Radiology, Iwate Medical University School of Medicine, Morioka, Japan
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Moloney F, Twomey M, James K, Kavanagh RG, Fama D, O'Neill S, Grey TM, Moore N, Murphy MJ, O'Connor OJ, Maher MM. A phantom study of the performance of model-based iterative reconstruction in low-dose chest and abdominal CT: When are benefits maximized? Radiography (Lond) 2019; 24:345-351. [PMID: 30292504 DOI: 10.1016/j.radi.2018.04.010] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2018] [Revised: 03/26/2018] [Accepted: 04/23/2018] [Indexed: 01/09/2023]
Abstract
INTRODUCTION The aim of this study was to assess and compare the effects of CT image reconstruction techniques on low-dose CT image quality using phantoms. METHODS Anthropomorphic torso and spatial/contrast-resolution phantoms were scanned at decreasing tube currents between 400 and 10 mA. CT thorax and abdomen/pelvis series were reconstructed with filtered back projection (FBP) alone, combined 40% adaptive statistical iterative reconstruction & FBP (ASIR40), and model-based iterative reconstruction (MBIR) [(resolution-preference 05 (RP05) and RP20 in the thorax and RP05 and noise-reduction 05 (NR05) in the abdomen)]. Two readers rated image quality quantitatively and qualitatively. RESULTS In thoracic CT, objective image noise on MBIR RP05 data sets outperformed FBP at 200, 100, 50 and 10 mA and outperformed ASIR40 at 50 and 10 mA (p < 0.001). MBIR RP20 outperformed FBP at 50 and 10 mA and outperformed ASIR40 at 10 mA (p < 0.001). Compared with both FBP and ASIR40, MBIR RP05 demonstrated significantly better signal-to-noise ratio (SNR) at 10 mA. In abdomino-pelvic CT, MBIR RP05 and NR05 outperformed FBP and ASIR at all tube current levels for objective image noise. NR05 demonstrated greater SNR at 200, 100, 50 and 10 mA and RP05 demonstrated greater SNR at 50 and 10 mA compared with both FBP and ASIR. MBIR images demonstrated better subjective image quality scores. Spatial resolution, low-contrast detectability and contrast-to-noise ratio (CNR) were comparable between image reconstruction techniques. CONCLUSION CTs reconstructed with MBIR have lower image noise and improved image quality compared with FBP and ASIR. These effects increase with reduced radiation exposure confirming optimal use for low-dose CT imaging.
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Affiliation(s)
- F Moloney
- Department of Radiology, Cork University Hospital, Cork, Ireland; College of Medicine & Health, University College Cork, Cork, Ireland
| | - M Twomey
- Department of Radiology, Cork University Hospital, Cork, Ireland; College of Medicine & Health, University College Cork, Cork, Ireland
| | - K James
- Department of Radiology, Cork University Hospital, Cork, Ireland; College of Medicine & Health, University College Cork, Cork, Ireland
| | - R G Kavanagh
- Department of Radiology, Cork University Hospital, Cork, Ireland; College of Medicine & Health, University College Cork, Cork, Ireland.
| | - D Fama
- Department of Radiology, Cork University Hospital, Cork, Ireland
| | - S O'Neill
- Department of Radiology, Cork University Hospital, Cork, Ireland; College of Medicine & Health, University College Cork, Cork, Ireland
| | - T M Grey
- Department of Radiology, Cork University Hospital, Cork, Ireland
| | - N Moore
- Department of Radiology, Cork University Hospital, Cork, Ireland; College of Medicine & Health, University College Cork, Cork, Ireland
| | - M J Murphy
- Department of Radiology, Cork University Hospital, Cork, Ireland
| | - O J O'Connor
- Department of Radiology, Cork University Hospital, Cork, Ireland; College of Medicine & Health, University College Cork, Cork, Ireland; APC Microbiome Ireland, University College Cork, Cork, Ireland
| | - M M Maher
- Department of Radiology, Cork University Hospital, Cork, Ireland; College of Medicine & Health, University College Cork, Cork, Ireland; APC Microbiome Ireland, University College Cork, Cork, Ireland
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Padole AM, Sagar P, Westra SJ, Lim R, Nimkin K, Kalra MK, Gee MS, Rehani MM. Development and validation of image quality scoring criteria (IQSC) for pediatric CT: a preliminary study. Insights Imaging 2019; 10:95. [PMID: 31549234 PMCID: PMC6757090 DOI: 10.1186/s13244-019-0769-8] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2019] [Accepted: 07/12/2019] [Indexed: 12/11/2022] Open
Abstract
OBJECTIVE To develop and assess the value and limitations of an image quality scoring criteria (IQSC) for pediatric CT exams. METHODS IQSC was developed for subjective assessment of image quality using the scoring scale from 0 to 4, with 0 indicating desired anatomy or features not seen, 3 for adequate image quality, and 4 depicting higher than needed image quality. Pediatric CT examinations from 30 separate patients were selected, five each for routine chest, routine abdomen, kidney stone, appendicitis, craniosynostosis, and ventriculoperitoneal (VP) shunt. Five board-certified pediatric radiologists independently performed image quality evaluation using the proposed IQSC. The kappa statistics were used to assess the interobserver variability. RESULTS All five radiologists gave a score of 3 to two-third (67%) of all CT exams, followed by a score of 4 for 29% of CT exams, and 2 for 4% exams. The median image quality scores for all exams were 3 and the interobserver agreement among five readers (acceptable image quality [scores 3 or 4] vs sub-optimal image quality ([scores 1 and 2]) was moderate to very good (kappa 0.4-1). For all five radiologists, the lesion detection was adequate for all CT exams. CONCLUSIONS The image quality scoring criteria covering routine and some clinical indication-based imaging scenarios for pediatric CT examinations has potential to offer a simple and practical tool for assessing image quality with a reasonable degree of interobserver agreement. A more extensive and multi-centric study is recommended to establish wider usefulness of these criteria.
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Affiliation(s)
- Atul M Padole
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 75 Cambridge Street, Suite 244, Boston, MA, 02114, USA
| | - Pallavi Sagar
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 75 Cambridge Street, Suite 244, Boston, MA, 02114, USA
| | - Sjirk J Westra
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 75 Cambridge Street, Suite 244, Boston, MA, 02114, USA
| | - Ruth Lim
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 75 Cambridge Street, Suite 244, Boston, MA, 02114, USA
| | - Katherine Nimkin
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 75 Cambridge Street, Suite 244, Boston, MA, 02114, USA
| | - Mannudeep K Kalra
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 75 Cambridge Street, Suite 244, Boston, MA, 02114, USA
| | - Michael S Gee
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 75 Cambridge Street, Suite 244, Boston, MA, 02114, USA
| | - Madan M Rehani
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 75 Cambridge Street, Suite 244, Boston, MA, 02114, USA.
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Zhang X, Uneri A, Webster Stayman J, Zygourakis CC, Lo SL, Theodore N, Siewerdsen JH. Known-component 3D image reconstruction for improved intraoperative imaging in spine surgery: A clinical pilot study. Med Phys 2019; 46:3483-3495. [PMID: 31180586 PMCID: PMC6692215 DOI: 10.1002/mp.13652] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2019] [Revised: 05/21/2019] [Accepted: 05/31/2019] [Indexed: 11/11/2022] Open
Abstract
PURPOSE Intraoperative imaging plays an increased role in support of surgical guidance and quality assurance for interventional approaches. However, image quality sufficient to detect complications and provide quantitative assessment of the surgical product is often confounded by image noise and artifacts. In this work, we translated a three-dimensional model-based image reconstruction (referred to as "Known-Component Reconstruction," KC-Recon) for the first time to clinical studies with the aim of resolving both limitations. METHODS KC-Recon builds upon a penalized weighted least-squares (PWLS) method by incorporating models of surgical instrumentation ("known components") within a joint image registration-reconstruction process to improve image quality. Under IRB approval, a clinical pilot study was conducted with 17 spine surgery patients imaged under informed consent using the O-arm cone-beam CT system (Medtronic, Littleton MA) before and after spinal instrumentation. Volumetric images were generated for each patient using KC-Recon in comparison to conventional filtered backprojection (FBP). Imaging performance prior to instrumentation ("preinstrumentation") was evaluated in terms of soft-tissue contrast-to-noise ratio (CNR) and spatial resolution. The quality of images obtained after the instrumentation ("postinstrumentation") was assessed by quantifying the magnitude of metal artifacts (blooming and streaks) arising from pedicle screws. The potential low-dose advantages of the algorithm were tested by simulating low-dose data (down to one-tenth of the dose of standard protocols) from images acquired at normal dose. RESULTS Preinstrumentation images (at normal clinical dose and matched resolution) exhibited an average 24.0% increase in soft-tissue CNR with KC-Recon compared to FBP (N = 16, P = 0.02), improving visualization of paraspinal muscles, major vessels, and other soft-tissues about the spine and abdomen. For a total of 72 screws in postinstrumentation images, KC-Recon yielded a significant reduction in metal artifacts: 66.3% reduction in overestimation of screw shaft width due to blooming (P < 0.0001) and reduction in streaks at the screw tip (65.8% increase in attenuation accuracy, P < 0.0001), enabling clearer depiction of the screw within the pedicle and vertebral body for an assessment of breach. Depending on the imaging task, dose reduction up to an order of magnitude appeared feasible while maintaining soft-tissue visibility and metal artifact reduction. CONCLUSIONS KC-Recon offers a promising means to improve visualization in the presence of surgical instrumentation and reduce patient dose in image-guided procedures. The improved soft-tissue visibility could facilitate the use of cone-beam CT to soft-tissue surgeries, and the ability to precisely quantify and visualize instrument placement could provide a valuable check against complications in the operating room (cf., postoperative CT).
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Affiliation(s)
- Xiaoxuan Zhang
- Department of Biomedical EngineeringJohns Hopkins UniversityBaltimoreMD21205USA
| | - Ali Uneri
- Department of Biomedical EngineeringJohns Hopkins UniversityBaltimoreMD21205USA
| | - J. Webster Stayman
- Department of Biomedical EngineeringJohns Hopkins UniversityBaltimoreMD21205USA
| | | | - Sheng‐fu L. Lo
- Department of NeurosurgeryJohns Hopkins Medical InstituteBaltimoreMD21287USA
| | - Nicholas Theodore
- Department of NeurosurgeryJohns Hopkins Medical InstituteBaltimoreMD21287USA
| | - Jeffrey H. Siewerdsen
- Department of Biomedical EngineeringJohns Hopkins UniversityBaltimoreMD21205USA
- Department of NeurosurgeryJohns Hopkins Medical InstituteBaltimoreMD21287USA
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Southard RN, Bardo DME, Temkit MH, Thorkelson MA, Augustyn RA, Martinot CA. Comparison of Iterative Model Reconstruction versus Filtered Back-Projection in Pediatric Emergency Head CT: Dose, Image Quality, and Image-Reconstruction Times. AJNR Am J Neuroradiol 2019; 40:866-871. [PMID: 30975652 DOI: 10.3174/ajnr.a6034] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2018] [Accepted: 02/27/2019] [Indexed: 11/07/2022]
Abstract
BACKGROUND AND PURPOSE Noncontrast CT of the head is the initial imaging test for traumatic brain injury, stroke, or suspected nonaccidental trauma. Low-dose head CT protocols using filtered back-projection are susceptible to increased noise and decreased image quality. Iterative reconstruction noise suppression allows the use of lower-dose techniques with maintained image quality. We review our experience with children undergoing emergency head CT examinations reconstructed using knowledge-based iterative model reconstruction versus standard filtered back-projection, comparing reconstruction times, radiation dose, and objective and subjective image quality. MATERIALS AND METHODS This was a retrospective study comparing 173 children scanned using standard age-based noncontrast head CT protocols reconstructed with filtered back-projection with 190 children scanned using low-dose protocols reconstructed with iterative model reconstruction. ROIs placed on the frontal white matter and thalamus yielded signal-to-noise and contrast-to-noise ratios. Volume CT dose index and study reconstruction times were recorded. Random subgroups of patients were selected for subjective image-quality review. RESULTS The volume CT dose index was significantly reduced in studies reconstructed with iterative model reconstruction compared with filtered back-projection, (mean, 24.4 ± 3.1 mGy versus 31.1 ± 6.0 mGy, P < .001), while the SNR and contrast-to-noise ratios improved 2-fold (P < .001). Radiologists graded iterative model reconstruction images as superior to filtered back-projection images for gray-white matter differentiation and anatomic detail (P < .001). The average reconstruction time of the filtered back-projection studies was 101 seconds, and with iterative model reconstruction, it was 147 seconds (P < .001), without a practical effect on work flow. CONCLUSIONS In children referred for emergency noncontrast head CT, optimized low-dose protocols with iterative model reconstruction allowed us to significantly reduce the relative dose, on average, 22% compared with filtered back-projection, with significantly improved objective and subjective image quality.
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Affiliation(s)
- R N Southard
- From the Departments of Medical Imaging (R.N.S., D.M.E.B., M.A.T., R.A.A., C.A.M.)
| | - D M E Bardo
- From the Departments of Medical Imaging (R.N.S., D.M.E.B., M.A.T., R.A.A., C.A.M.)
| | - M H Temkit
- Clinical Research (M.H.T.), Phoenix Children's Hospital, Phoenix Arizona
| | - M A Thorkelson
- From the Departments of Medical Imaging (R.N.S., D.M.E.B., M.A.T., R.A.A., C.A.M.)
| | - R A Augustyn
- From the Departments of Medical Imaging (R.N.S., D.M.E.B., M.A.T., R.A.A., C.A.M.)
| | - C A Martinot
- From the Departments of Medical Imaging (R.N.S., D.M.E.B., M.A.T., R.A.A., C.A.M.)
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Miller AR, Jackson D, Hui C, Deshpande S, Kuo E, Hamilton GS, Lau KK. Lung nodules are reliably detectable on ultra-low-dose CT utilising model-based iterative reconstruction with radiation equivalent to plain radiography. Clin Radiol 2019; 74:409.e17-409.e22. [PMID: 30832990 DOI: 10.1016/j.crad.2019.02.001] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2018] [Accepted: 02/06/2019] [Indexed: 12/21/2022]
Abstract
AIM To determine if ultra-low-dose (ULD) computed tomography (CT) utilising model-based iterative reconstruction (MBIR) with radiation equivalent to plain radiography allows the detection of lung nodules. MATERIALS AND METHODS Ninety-nine individuals undergoing surveillance of solid pulmonary nodules undertook a low-dose (LD) and ULD CT during the same sitting. Image pairs were read blinded, in random order, and independently by two experienced thoracic radiologists. With LD-CT as the reference standard, the number, size, and location of nodules was compared, and inter-rater agreement was established. RESULTS There was very good inter-rater agreement with regards nodules ≥4mm for both the LD- (k=0.931) and ULD-CT (k=0.869). One hundred and ninety-nine nodules were reported on the LD-CT by both radiologists and 196 reported on the ULD-CT, with no nodules reported only on the ULD-CT. This gives a sensitivity of 98.5% and specificity of 100% for ULD-CT with MBIR. The effective dose of radiation was significantly different between the two scans (p<0.0001), 1.67 mSv for the LD-CT and 0.13 mSv for the ULD-CT. CONCLUSION ULD-CT utilising MBIR and delivering radiation equivalent to plain radiography, allows detection of lung nodules with high sensitivity. The attendant 10-fold reduction in radiation may allow for dramatic reductions in cumulative radiation exposure.
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Affiliation(s)
- A R Miller
- Monash Lung and Sleep, Monash Health, Clayton, Victoria, Australia; Monash University, Clayton, Victoria, Australia; General Medicine, Monash Health, Clayton, Victoria, Australia.
| | - D Jackson
- Monash Imaging, Monash Health, Clayton, Victoria, Australia
| | - C Hui
- Monash Imaging, Monash Health, Clayton, Victoria, Australia
| | - S Deshpande
- Monash Lung and Sleep, Monash Health, Clayton, Victoria, Australia
| | - E Kuo
- Monash Lung and Sleep, Monash Health, Clayton, Victoria, Australia
| | - G S Hamilton
- Monash Lung and Sleep, Monash Health, Clayton, Victoria, Australia; Monash University, Clayton, Victoria, Australia
| | - K K Lau
- General Medicine, Monash Health, Clayton, Victoria, Australia; Monash Imaging, Monash Health, Clayton, Victoria, Australia
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Tang S, Liu X, He L, Zhou Y, Cheng Z. Application of ASiR in combination with noise index in the chest CT examination of preschool-age children. Radiol Med 2019; 124:467-477. [DOI: 10.1007/s11547-018-00983-w] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2018] [Accepted: 12/20/2018] [Indexed: 12/26/2022]
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Barca P, Giannelli M, Fantacci ME, Caramella D. Computed tomography imaging with the Adaptive Statistical Iterative Reconstruction (ASIR) algorithm: dependence of image quality on the blending level of reconstruction. AUSTRALASIAN PHYSICAL & ENGINEERING SCIENCES IN MEDICINE 2018; 41:463-473. [DOI: 10.1007/s13246-018-0645-8] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/21/2017] [Accepted: 04/26/2018] [Indexed: 12/16/2022]
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Jeong YJ, Choo KS, Nam KJ, Lee JW, Kim JY, Jung HJ, Lim SJ. Image quality and radiation dose of CT venography with double dose reduction using model based iterative reconstruction: comparison with conventional CT venography using filtered back projection. Acta Radiol 2018; 59:546-552. [PMID: 28766981 DOI: 10.1177/0284185117725780] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Background Computed tomography venography (CTV) at low kVp using model-based iterative reconstruction (MBIR) can enhance vascular enhancement with noise reduction. Purpose To evaluate image qualities and radiation doses of CTV at 80 kVp using MBIR and a small iodine contrast media (CM) dose and to compare these with those of CTV performed using a conventional protocol. Material and Methods Sixty-five patients (mean age = 58.1 ± 7.2 years) that underwent CTV for the evaluation of deep vein thrombosis (DVT) and varicose veins were enrolled in this study. Patients were divided into two groups: Group A (35 patients, 80 kVp, MBIR, automatic tube current modulation, CM = 270 mg/mL, 100 mL) and Group B (30 patients, 100 kVp, filtered back projection [FBP], 120 fixed mA, CM = 370 mg/mL, 120 mL). Objective and subjective image qualities of inferior vena cava (IVC), femoral vein (FV), and popliteal vein (PV) were assessed and radiation doses were recorded. Results Mean vascular enhancement in group A was significantly lower than in group B ( P < 0.01). Noise in group A was significantly lower than in group B except for PV and contrast-to-noise ratio were not significantly different in the two groups ( P > 0.05). In addition, radiation dose in group A was significantly lower than in group B ( P < 0.001). Subjective image quality comparison revealed group A was statistically inferior to group B except for subjective image noise. Conclusion CTV at 80 kVp using MBIR with small iodine contrast dose provided acceptable image quality at a lower radiation dose than conventional CTV using FBP.
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Affiliation(s)
- Yeo-Jin Jeong
- Department of Radiology, Research Institute for Convergence of Biomedical Science and Technology, Pusan National University Hospital, Busan, Republic of Korea
| | - Ki Seok Choo
- Department of Radiology, Research Institute for Convergence of Biomedical Science and Technology, Pusan National University Hospital, Busan, Republic of Korea
| | - Kyung Jin Nam
- Department of Radiology, Research Institute for Convergence of Biomedical Science and Technology, Pusan National University Hospital, Busan, Republic of Korea
| | - Ji Won Lee
- Department of Radiology, Pusan National University Hospital, Pusan National University School of Medicine, Busan, Republic of Korea
| | - Jin You Kim
- Department of Radiology, Pusan National University Hospital, Pusan National University School of Medicine, Busan, Republic of Korea
| | - Hyuk Jae Jung
- Department of Vascular surgery, Pusan National University Yangsan Hospital, Pusan National University School of Medicine, Busan, Republic of Korea
| | - Soo Jin Lim
- Department of Cardiology, Kim Hae Gang-il Hospital, KyoungNam, Republic of Korea
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Tang H, Yu N, Jia Y, Yu Y, Duan H, Han D, Ma G, Ren C, He T. Assessment of noise reduction potential and image quality improvement of a new generation adaptive statistical iterative reconstruction (ASIR-V) in chest CT. Br J Radiol 2017; 91:20170521. [PMID: 29076347 DOI: 10.1259/bjr.20170521] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
OBJECTIVE To evaluate the image quality improvement and noise reduction in routine dose, non-enhanced chest CT imaging by using a new generation adaptive statistical iterative reconstruction (ASIR-V) in comparison with ASIR algorithm. METHODS 30 patients who underwent routine dose, non-enhanced chest CT using GE Discovery CT750HU (GE Healthcare, Waukesha, WI) were included. The scan parameters included tube voltage of 120 kVp, automatic tube current modulation to obtain a noise index of 14HU, rotation speed of 0.6 s, pitch of 1.375:1 and slice thickness of 5 mm. After scanning, all scans were reconstructed with the recommended level of 40%ASIR for comparison purpose and different percentages of ASIR-V from 10% to 100% in a 10% increment. The CT attenuation values and SD of the subcutaneous fat, back muscle and descending aorta were measured at the level of tracheal carina of all reconstructed images. The signal-to-noise ratio (SNR) was calculated with SD representing image noise. The subjective image quality was independently evaluated by two experienced radiologists. RESULTS For all ASIR-V images, the objective image noise (SD) of fat, muscle and aorta decreased and SNR increased along with increasing ASIR-V percentage. The SD of 30% ASIR-V to 100% ASIR-V was significantly lower than that of 40% ASIR (p < 0.05). In terms of subjective image evaluation, all ASIR-V reconstructions had good diagnostic acceptability. However, the 50% ASIR-V to 70% ASIR-V series showed significantly superior visibility of small structures when compared with the 40% ASIR and ASIR-V of other percentages (p < 0.05), and 60% ASIR-V was the best series of all ASIR-V images, with a highest subjective image quality. The image sharpness was significantly decreased in images reconstructed by 80% ASIR-V and higher. CONCLUSION In routine dose, non-enhanced chest CT, ASIR-V shows greater potential in reducing image noise and artefacts and maintaining image sharpness when compared to the recommended level of 40%ASIR algorithm. Combining both the objective and subjective evaluation of images, non-enhanced chest CT images reconstructed with 60% ASIR-V have the highest image quality. Advances in knowledge: This is the first clinical study to evaluate the clinical value of ASIR-V in the same patients using the same CT scanner in the non-enhanced chest CT scans. It suggests that ASIR-V provides the better image quality and higher diagnostic confidence in comparison with ASIR algorithm.
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Affiliation(s)
- Hui Tang
- 1 College of Medical Technology, Shaanxi University of Chinese Medicine, Xianyang, China
| | - Nan Yu
- 2 Department of Radiology, Affiliated Hospital of Shaanxi University of Traditional Chinese Medicine, Xianyang, China
| | - Yongjun Jia
- 2 Department of Radiology, Affiliated Hospital of Shaanxi University of Traditional Chinese Medicine, Xianyang, China
| | - Yong Yu
- 2 Department of Radiology, Affiliated Hospital of Shaanxi University of Traditional Chinese Medicine, Xianyang, China
| | - Haifeng Duan
- 2 Department of Radiology, Affiliated Hospital of Shaanxi University of Traditional Chinese Medicine, Xianyang, China
| | - Dong Han
- 2 Department of Radiology, Affiliated Hospital of Shaanxi University of Traditional Chinese Medicine, Xianyang, China
| | - Guangming Ma
- 2 Department of Radiology, Affiliated Hospital of Shaanxi University of Traditional Chinese Medicine, Xianyang, China
| | - Chenglong Ren
- 2 Department of Radiology, Affiliated Hospital of Shaanxi University of Traditional Chinese Medicine, Xianyang, China
| | - Taiping He
- 1 College of Medical Technology, Shaanxi University of Chinese Medicine, Xianyang, China.,2 Department of Radiology, Affiliated Hospital of Shaanxi University of Traditional Chinese Medicine, Xianyang, China
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Iterative Reconstructions in Reduced-Dose CT: Which Type Ensures Diagnostic Image Quality in Young Oncology Patients? Acad Radiol 2017; 24:1114-1124. [PMID: 28365232 DOI: 10.1016/j.acra.2017.02.012] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2016] [Revised: 02/24/2017] [Accepted: 02/24/2017] [Indexed: 12/11/2022]
Abstract
RATIONALE AND OBJECTIVES To compare adaptive statistical iterative reconstruction (ASIR) and model-based iterative reconstruction (MBIR) algorithms for reduced-dose computed tomography (CT). MATERIALS AND METHODS Forty-four young oncology patients (mean age 30 ± 9 years) were included. After routine thoraco-abdominal CT (dose 100%, average CTDIvol 9.1 ± 2.4 mGy, range 4.4-16.9 mGy), follow-up CT was acquired at 50% (average CTDIvol 4.5 ± 1.2 mGy, range 2.2-8.4 mGy) in 29 patients additionally at 20% dose (average CTDIvol 1.9 ± 0.5 mGy, range 0.9-3.4 mGy). Each reduced-dose CT was reconstructed using both ASIR and MBIR. Four radiologists (two juniors and two seniors) blinded to dose and technique read each set of CT images regarding objective and subjective image qualities (high- or low-contrast structures), subjective noise or pixilated appearance, diagnostic confidence, and lesion detection. RESULTS At all dose levels, objective image noise was significantly lower with MBIR than with ASIR (P < 0.001). The subjective image quality for low-contrast structures was significantly higher with MBIR than with ASIR (P < 0.001). Reduced-dose abdominal CT images of patients with higher body mass index (BMI) were read with significantly higher diagnostic confidence than images of slimmer patients (P < 0.001) and had higher subjective image quality, regardless of technique. Although MBIR images appeared significantly more pixilated than ASIR images, they were read with higher diagnostic confidence, especially by juniors (P < 0.001). CONCLUSIONS Reduced-dose CT during the follow-up of young oncology patients should be reconstructed with MBIR to ensure diagnostic quality. Elevated body mass index does not hamper the quality of reduced-dose CT.
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Reduced dose CT with model-based iterative reconstruction compared to standard dose CT of the chest, abdomen, and pelvis in oncology patients: intra-individual comparison study on image quality and lesion conspicuity. Abdom Radiol (NY) 2017; 42:2279-2288. [PMID: 28417170 DOI: 10.1007/s00261-017-1140-5] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
PURPOSE To compare image quality and lesion conspicuity of reduced dose (RD) CT with model-based iterative reconstruction (MBIR) compared to standard dose (SD) CT in patients undergoing oncological follow-up imaging. METHODS Forty-four cancer patients who had a staging SD CT within 12 months were prospectively included to undergo a weight-based RD CT with MBIR. Radiation dose was recorded and tissue attenuation and image noise of four tissue types were measured. Reproducibility of target lesion size measurements of up to 5 target lesions per patient were analyzed. Subjective image quality was evaluated for three readers independently utilizing 4- or 5-point Likert scales. RESULTS Median radiation dose reduction was 46% using RD CT (P < 0.01). Median image noise across all measured tissue types was lower (P < 0.01) in RD CT. Subjective image quality for RD CT was higher (P < 0.01) in regard to image noise and overall image quality; however, there was no statistically significant difference regarding image sharpness (P = 0.59). There were subjectively more artifacts on RD CT (P < 0.01). Lesion conspicuity was subjectively better in RD CT (P < 0.01). Repeated target lesion size measurements were highly reproducible both on SD CT (ICC = 0.987) and RD CT (ICC = 0.97). CONCLUSIONS RD CT imaging with MBIR provides diagnostic imaging quality and comparable lesion conspicuity on follow-up exams while allowing dose reduction by a median of 46% compared to SD CT imaging.
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Samei E, Li X, Frush DP. Size-based quality-informed framework for quantitative optimization of pediatric CT. J Med Imaging (Bellingham) 2017; 4:031209. [PMID: 28840168 DOI: 10.1117/1.jmi.4.3.031209] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2017] [Accepted: 07/06/2017] [Indexed: 11/14/2022] Open
Abstract
The purpose of this study was to formulate a systematic, evidence-based method to relate quantitative diagnostic performance to radiation dose, enabling a multidimensional system to optimize computed tomography imaging across pediatric populations. Based on two prior foundational studies, radiation dose was assessed in terms of organ doses, effective dose ([Formula: see text]), and risk index for 30 patients within nine color-coded pediatric age-size groups as a function of imaging parameters. The cases, supplemented with added noise and simulated lesions, were assessed in terms of nodule detection accuracy in an observer receiving operating characteristic study. The resulting continuous accuracy-dose relationships were used to optimize individual scan parameters. Before optimization, the nine protocols had a similar [Formula: see text] of [Formula: see text] with accuracy decreasing from 0.89 for the youngest patients to 0.67 for the oldest. After optimization, a consistent target accuracy of 0.83 was established for all patient categories with [Formula: see text] ranging from 1 to 10 mSv. Alternatively, isogradient operating points targeted a consistent ratio of accuracy-per-unit-dose across the patient categories. The developed model can be used to optimize individual scan parameters and provide for consistent diagnostic performance across the broad range of body sizes in children.
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Affiliation(s)
- Ehsan Samei
- Duke University Medical Center, Departments of Radiology, Physics, Biomedical Engineering, and Electrical and Computer Engineering, Carl E. Ravin Advanced Imaging Laboratories, Medical Physics Graduate Program, Durham, North Carolina, United States
| | - Xiang Li
- Cleveland Clinic, Imaging Institute, Section of Medical Physics, Cleveland, Ohio, United States
| | - Donald P Frush
- Duke University Medical Center, Division of Pediatric Radiology, Department of Radiology, Medical Physics Graduate Program, Durham, North Carolina, United States
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Telesmanich ME, Jensen CT, Enriquez JL, Wagner-Bartak NA, Liu X, Le O, Wei W, Chandler AG, Tamm EP. Third version of vendor-specific model-based iterativereconstruction (Veo 3.0): evaluation of CT image quality in the abdomen using new noise reduction presets and varied slice optimization. Br J Radiol 2017; 90:20170188. [PMID: 28707531 DOI: 10.1259/bjr.20170188] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022] Open
Abstract
OBJECTIVE To qualitatively and quantitatively compare abdominal CT images reconstructed with a newversion of model-based iterative reconstruction (Veo 3.0; GE Healthcare Waukesha, WI) utilizing varied presetsof resolution preference, noise reduction and slice optimization. METHODS This retrospective study was approved by our Institutional Review Board and was Health Insurance Portability and Accountability Act compliant. The raw datafrom 30 consecutive patients who had undergone CT abdomen scanning were used to reconstructfour clinical presets of 3.75mm axial images using Veo 3.0: 5% resolution preference (RP05n), 5%noise reduction (NR05) and 40% noise reduction (NR40) with new 3.75mm "sliceoptimization," as well as one set using RP05 with conventional 0.625mm "slice optimization" (RP05c). The images were reviewed by two independent readers in a blinded, randomized manner using a 5-point Likert scale as well as a 5-point comparative scale. Multiple two-dimensional circular regions of interest were defined for noise and contrast-to-noise ratio measurements. Line profiles were drawn across the 7 lp cm-1 bar pattern of the Catphan 600 phantom for evaluation of spatial resolution. RESULTS The NR05 image set was ranked as the best series in overall image quality (mean difference inrank 0.48, 95% CI [0.081-0.88], p = 0.01) and with specific reference to liver evaluation (meandifference 0.46, 95% CI [0.030-0.89], p = 0.03), when compared with the secondbest series ineach category. RP05n was ranked as the best for bone evaluation. NR40 was ranked assignificantly inferior across all assessed categories. Although the NR05 and RP05c image setshad nearly the same contrast-to-noise ratio and spatial resolution, NR05 was generally preferred. Image noise and spatial resolution increased along a spectrum with RP05n the highest and NR40the lowest. Compared to RP05n, the average noise was 21.01% lower for NR05, 26.88%lower for RP05c and 50.86% lower for NR40. CONCLUSION Veo 3.0 clinical presets allow for selection of image noise and spatial resolution balance; for contrast-enhanced CT evaluation of the abdomen, the 5% noise reduction preset with 3.75 mm slice optimization (NR05) was generally ranked superior qualitatively and, relative to other series, was in the middle of the spectrum with reference to image noise and spatial resolution. Advances in knowledge: To our knowledge, this is the first study of Veo 3.0 noise reduction presets and varied slice optimization. This study provides insight into the behaviour of slice optimization and documents the degree of noise reduction and spatial resolution changes that users can expect across various Veo 3.0 clinical presets. These results provide important parameters to guide preset selection for both clinical and research purposes.
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Affiliation(s)
- Morgan E Telesmanich
- 1 Department of Diagnostic Radiology, Baylor College of Medicine , Houston , USA
| | - Corey T Jensen
- 2 Department of Diagnostic Radiology, The University of Texas MD Anderson Cancer Center , Houston , USA
| | - Jose L Enriquez
- 1 Department of Diagnostic Radiology, Baylor College of Medicine , Houston , USA
| | - Nicolaus A Wagner-Bartak
- 2 Department of Diagnostic Radiology, The University of Texas MD Anderson Cancer Center , Houston , USA
| | - Xinming Liu
- 3 Department of Imaging Physics, The University of Texas MD Anderson Cancer Center , Houston , USA
| | - Ott Le
- 2 Department of Diagnostic Radiology, The University of Texas MD Anderson Cancer Center , Houston , USA
| | - Wei Wei
- 4 Department of Biostatistics, The University of Texas MD Anderson Cancer Center , Houston , USA
| | - Adam G Chandler
- 3 Department of Imaging Physics, The University of Texas MD Anderson Cancer Center , Houston , USA.,5 Department of Molecular Imaging and Computed Tomography Research, GE Healthcare , Waukesha , USA
| | - Eric P Tamm
- 2 Department of Diagnostic Radiology, The University of Texas MD Anderson Cancer Center , Houston , USA
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Kim M, Chang K, Hwang J, Nam Y, Han D, Yoon J. RADIATION DOSE FOR PEDIATRIC AND YOUNG ADULT CT: A SURVEY TO ESTABLISH AGE-BASED REFERENCE LEVELS OF 2015-2016 IN KOREA. RADIATION PROTECTION DOSIMETRY 2017; 175:228-237. [PMID: 27886991 DOI: 10.1093/rpd/ncw289] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/03/2016] [Accepted: 10/14/2016] [Indexed: 06/06/2023]
Abstract
To assess the doses delivered to pediatric patients during computed tomography (CT) examinations of the brain, chest, high-resolution lung and abdomen, and to establish diagnostic reference levels (DRLs) for various age groups in Korea. Dose survey was done to the 19 hospitals performing CT on children, addressing the scan parameters, volume CT dose index (CTDIvol) and dose length product (DLP). Per five age group (0, 1, 2-5, 6-10, 11-17 y of age), the proposed DRLs for brain, chest, high-resolution lung and abdomen CT are, respectively, in terms of CTDIvol: 18, 23, 26, 31, 36 mGy; 2, 3, 4, 6, 8 mGy; 2, 3, 4, 5, 7 mGy; 3, 4, 5, 6, 9 mGy; and in terms of DLP: 260, 350, 420, 500, 620 mGy•cm; 50, 80, 100, 170, 340 mGy•cm; 30, 40, 60, 90, 280 mGy•cm; 70, 80, 200, 300, 500 mGy•cm. Compared with published DRLs our suggestion for pediatric CT dose is the lower end. However, an optimization process should be initiated to reduce the spread in patient dose among hospitals despite same CT protocols shown in the study. A major element of this process should be the establishment of institution performance standard and the use of built DRLs.
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Affiliation(s)
- MoonChan Kim
- Department of Radiology, Samsung Medical Center, Seoul, Korea
| | - KwangHyun Chang
- Department of Radiology, Samsung Medical Center, Seoul, Korea
| | - JeongHoon Hwang
- Department of Radiology, Samsung Medical Center, Seoul, Korea
| | - YoonChul Nam
- Department of Radiology, Samsung Medical Center, Seoul, Korea
| | - DongKyoon Han
- Department of Radiologic Science, Eulji University, KyungKi, Korea
| | - Joon Yoon
- Department of Radiologic Science, Dongnam Health College, KyungKi, Korea
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Buty M, Xu Z, Wu A, Gao M, Nelson C, Papadakis GZ, Teomete U, Celik H, Turkbey B, Choyke P, Mollura DJ, Bagci U, Folio LR. Quantitative Image Quality Comparison of Reduced- and Standard-Dose Dual-Energy Multiphase Chest, Abdomen, and Pelvis CT. ACTA ACUST UNITED AC 2017; 3:114-122. [PMID: 28856247 PMCID: PMC5573232 DOI: 10.18383/j.tom.2017.00002] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
We present a new image quality assessment method for determining whether reducing radiation dose impairs the image quality of computed tomography (CT) in qualitative and quantitative clinical analyses tasks. In this Institutional Review Board-exempt study, we conducted a review of 50 patients (male, 22; female, 28) who underwent reduced-dose CT scanning on the first follow-up after standard-dose multiphase CT scanning. Scans were for surveillance of von Hippel–Lindau disease (N = 26) and renal cell carcinoma (N = 10). We investigated density, morphometric, and structural differences between scans both at tissue (fat, bone) and organ levels (liver, heart, spleen, lung). To quantify structural variations caused by image quality differences, we propose using the following metrics: dice similarity coefficient, structural similarity index, Hausdorff distance, gradient magnitude similarity deviation, and weighted spectral distance. Pearson correlation coefficient and Welch 2-sample t test were used for quantitative comparisons of organ morphometry and to compare density distribution of tissue, respectively. For qualitative evaluation, 2-sided Kendall Tau test was used to assess agreement among readers. Both qualitative and quantitative evaluations were designed to examine significance of image differences for clinical tasks. Qualitative judgment served as an overall assessment, whereas detailed quantifications on structural consistency, intensity homogeneity, and texture similarity revealed more accurate and global difference estimations. Qualitative and quantitative results indicated no significant image quality degradation. Our study concludes that low(er)-dose CT scans can be routinely used because of no significant loss in quantitative image information compared with standard-dose CT scans.
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Affiliation(s)
- Mario Buty
- National Institutes of Health, Radiology and Imaging Sciences Bethesda, Maryland
| | - Ziyue Xu
- National Institutes of Health, Radiology and Imaging Sciences Bethesda, Maryland
| | - Aaron Wu
- National Institutes of Health, Radiology and Imaging Sciences Bethesda, Maryland
| | - Mingchen Gao
- National Institutes of Health, Radiology and Imaging Sciences Bethesda, Maryland
| | - Chelyse Nelson
- National Institutes of Health, Radiology and Imaging Sciences Bethesda, Maryland
| | - Georgios Z Papadakis
- National Institutes of Health, Radiology and Imaging Sciences Bethesda, Maryland
| | - Uygar Teomete
- Bluefield Regional Medical Center, Bluefield, West Virginia
| | - Haydar Celik
- National Institutes of Health, Radiology and Imaging Sciences Bethesda, Maryland
| | - Baris Turkbey
- National Institutes of Health, Radiology and Imaging Sciences Bethesda, Maryland
| | - Peter Choyke
- National Institutes of Health, Radiology and Imaging Sciences Bethesda, Maryland
| | - Daniel J Mollura
- National Institutes of Health, Radiology and Imaging Sciences Bethesda, Maryland
| | - Ulas Bagci
- Center for Research in Computer Vision, University of Central Florida, Orlando, Florida
| | - Les R Folio
- National Institutes of Health, Radiology and Imaging Sciences Bethesda, Maryland
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Pediatric chest CT at chest radiograph doses: when is the ultralow-dose chest CT clinically appropriate? Emerg Radiol 2017; 24:369-376. [PMID: 28289906 DOI: 10.1007/s10140-017-1487-5] [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: 11/11/2016] [Accepted: 02/07/2017] [Indexed: 10/20/2022]
Abstract
PURPOSE Computed tomography (CT) use in emergency departments represents a significant contribution to pediatric patients' exposure to ionizing radiation. Here, we evaluate whether ultralow-dose chest CT can be diagnostically adequate for other diagnoses and whether model-based iterative reconstruction (MBIR) can improve diagnostic adequacy compared to adaptive statistical iterative reconstruction (ASIR) at ultralow doses. METHODS Twenty children underwent chest CTs: 10 standard-dose reconstructed with ASIR and 10 ultralow-dose reconstructed with ASIR and MBIR. Four radiologists assessed images for their adequacy to exclude five hypothetical diagnoses: foreign body, fracture, lung metastasis, pulmonary infection, and interstitial lung disease. Additionally, pairwise comparison for subjective image quality was used to compare ultralow-dose chest CT with ASIR and MBIR. Radiation dose and objective image noise measures were obtained. RESULTS For exclusion of an airway foreign body, the adequacy of ultralow-dose CT was comparable to standard-dose (p = 0.6). For the remaining diagnoses, ultralow-dose CT was inferior to standard-dose (p = 0.03-<0.001). MBIR partially recovered the adequacy of ultralow-dose CT to exclude pulmonary infection (p = 0.017), but was suboptimal for the other diagnoses. Image noise was significantly lower with MBIR compared to ASIR in ultralow-dose CT (p < 0.001), although subjective preference showed only a slight advantage of MBIR (58 versus 42%). CONCLUSIONS Ultralow-dose chest CT may be adequate for airway assessment, but suboptimal for the evaluation parenchymal lung disease. Although MBIR improves objective and subjective image quality, it does not completely restore the diagnostic adequacy of ultralow-dose CT when compared to standard-dose CT.
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Evaluation of Abdominal Computed Tomography Image Quality Using a New Version of Vendor-Specific Model-Based Iterative Reconstruction. J Comput Assist Tomogr 2017; 41:67-74. [PMID: 27529683 DOI: 10.1097/rct.0000000000000472] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
PURPOSE To qualitatively and quantitatively compare abdominal computed tomography (CT) images reconstructed with a new version of model-based iterative reconstruction (Veo 3.0; GE Healthcare) to those created with Veo 2.0. MATERIALS AND METHODS This retrospective study was approved by our institutional review board and was Health Insurance Portability and Accountability Act compliant. The raw data from 29 consecutive patients who had undergone CT abdomen scanning was used to reconstruct 4 sets of 3.75-mm axial images: Veo 2.0, Veo 3.0 standard, Veo 3.0 5% resolution preference (RP), and Veo 3.0 20% RP. A slice thickness optimization of 3.75 mm and texture feature was selected for Veo 3.0 reconstructions.The images were reviewed by 3 independent readers in a blinded, randomized fashion using a 5-point Likert scale and 5-point comparative scale.Multiple 2-dimensional circular regions of interest were defined for noise and contrast-to-noise ratio measurements. Line profiles were drawn across the 7 lp/cm bar pattern of the CatPhan 600 phantom for spatial resolution evaluation. RESULTS The Veo 3.0 standard image set was scored better than Veo 2.0 in terms of artifacts (mean difference, 0.43; 95% confidence interval [95% CI], 0.25-0.6; P < 0.0001), overall image quality (mean difference, 0.87; 95% CI, 0.62-1.13; P < 0.0001) and qualitative resolution (mean difference, 0.9; 95% CI, 0.69-1.1; P < 0.0001). Although the Veo 3.0 standard and RP05 presets were preferred across most categories, the Veo 3.0 RP20 series ranked best for bone detail. Image noise and spatial resolution increased along a spectrum with Veo 2.0 the lowest and RP20 the highest. CONCLUSION Veo 3.0 enhances imaging evaluation relative to Veo 2.0; readers preferred Veo 3.0 image appearance despite the associated mild increases in image noise. These results provide suggested parameters to be used clinically and as a basis for future evaluations, such as focal lesion detection, in the oncology setting.
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Optimization of hybrid iterative reconstruction level and evaluation of image quality and radiation dose for pediatric cardiac computed tomography angiography. Pediatr Radiol 2017; 47:31-38. [PMID: 27637188 DOI: 10.1007/s00247-016-3698-4] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/05/2016] [Revised: 07/09/2016] [Accepted: 08/26/2016] [Indexed: 10/21/2022]
Abstract
BACKGROUND Hybrid iterative reconstruction can reduce image noise and produce better image quality compared with filtered back-projection (FBP), but few reports describe optimization of the iteration level. OBJECTIVE We optimized the iteration level of iDose4 and evaluated image quality for pediatric cardiac CT angiography. MATERIALS AND METHODS Children (n = 160) with congenital heart disease were enrolled and divided into full-dose (n = 84) and half-dose (n = 76) groups. Four series were reconstructed using FBP, and iDose4 levels 2, 4 and 6; we evaluated subjective quality of the series using a 5-grade scale and compared the series using a Kruskal-Wallis H test. For FBP and iDose4-optimal images, we compared contrast-to-noise ratios (CNR) and size-specific dose estimates (SSDE) using a Student's t-test. We also compared diagnostic-accuracy of each group using a Kruskal-Wallis H test. RESULTS Mean scores for iDose4 level 4 were the best in both dose groups (all P < 0.05). CNR was improved in both groups with iDose4 level 4 as compared with FBP. Mean decrease in SSDE was 53% in the half-dose group. Diagnostic accuracy for the four datasets were in the range 92.6-96.2% (no statistical difference). CONCLUSION iDose4 level 4 was optimal for both the full- and half-dose groups. Protocols with iDose4 level 4 allowed 53% reduction in SSDE without significantly affecting image quality and diagnostic accuracy.
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Cha MJ, Jeong WK, Choi D, Kim YK, Lim S, Choi SY, Lee WJ. Iterative reconstruction: comparison of techniques for reduced-dose liver computed tomography following transarterial chemoembolization for hepatocellular carcinoma. Acta Radiol 2016; 57:1429-1437. [PMID: 26792822 DOI: 10.1177/0284185115626472] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/14/2023]
Abstract
Background Adaptive statistical iterative reconstruction (ASIR) and model-based iterative reconstruction (MBIR) algorithms have the potential to reduce dose while maintaining image quality. Purpose To compare computed tomography (CT) image quality and diagnostic performance among three reconstruction techniques - ASIR, MBIR, and filtered back projection (FBP) - after transcatheter arterial chemoembolization (TACE) of hepatocellular carcinomas (HCC). Material and Methods Of 60 patients that underwent initial TACE for HCCs, half underwent dynamic liver CT with conventional scanning protocol, and the other half with dose reduction to approximately 60% of conventional exposure. All images were reconstructed using three algorithms: FBP, ASIR, and MBIR. For objective analysis, image noise and signal-to-noise ratio (SNR) were compared. For subjective analysis, three radiologists independently assessed image quality. Ability to detect viable HCCs was also evaluated. Results MBIR and ASIR produced images with less noise and higher SNR compared with FBP regardless of radiation dosage ( P < 0.017). However, in terms of subjective parameters, such as image blotchiness, artifacts, and overall quality, MBIR was inferior to FBP and ASIR ( P < 0.001). Regarding diagnostic performance, there were no significant differences among reviewers in the detection of viable HCCs depending on the reconstruction algorithm, regardless of the dose reduction protocol ( P > 0.017). Conclusion Although subjective evaluations suggest that MBIR images are of lower quality compared with FBP and ASIR regardless of radiation dosage, there were no significant differences among reconstruction algorithms in diagnosis of viable HCC after TACE.
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Affiliation(s)
- Min Jae Cha
- Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Woo Kyoung Jeong
- Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Dongil Choi
- Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Young Kon Kim
- Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Sanghyeok Lim
- Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
- Department of Radiology, Hanyang University College of Medicine, Hanyang University Guri Hospital, Gyeonggi-do, Republic of Korea
| | - Seo-Youn Choi
- Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
- Department of Radiology, Soonchunhyang University College of Medicine, Bucheon Hospital, Gyeonggi-do, Republic of Korea
| | - Won Jae Lee
- Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
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