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Miftahuddin D, Prayitno AG, Hariyanto AP, Gani MRA, Endarko E. Evaluation of low-dose pediatric chest CT examination using in-house developed various age-size pediatric chest phantoms. Eur J Radiol 2024; 177:111599. [PMID: 38970995 DOI: 10.1016/j.ejrad.2024.111599] [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] [Received: 02/08/2024] [Revised: 04/03/2024] [Accepted: 07/01/2024] [Indexed: 07/08/2024]
Abstract
PURPOSE This study aims to develop Various Age-size Pediatric Chest Phantoms (VAPC) to evaluate low-dose protocol that approximates clinical conditions achieved by low organ-specific doses and optimal image quality among the challenges of pediatric size variations. METHODS Three original pediatric data aged 1, 4, and 7 years were used as a reference for developing VAPC phantoms. Six protocols, namely standard dose (STD) and low dose (low mA and low kV) reconstructed using Filtered Back Projection (FBP) and iterative reconstruction (IR) algorithms, were investigated. This study directly measured the lungs, heart, and spinal cord dose using LD-V1 film. Linearity, Modulation Transfer Function (MTF), Contrast to Noise Ratio (CNR), and Noise Power Spectrum (NPS) were evaluated to assess the CT image quality of the VAPC phantom. RESULTS This study found that the mean organ-specific dose was higher than CTDIvol. A Comparison of mean lung doses showed VAPC phantom 1 (y.o.) received 74.8% and 137.2% more doses than 4 (y.o.) and 7 (y.o.), respectively. Low kV produces a lower organ dose than low mA. The linearity of CT numbers is not biased at low doses. Differences in age measures significantly influenced organ-specific dose, MTF, CNR, and NPS. CONCLUSION Smaller pediatrics are still exposed to higher doses at low-dose examinations, whereas larger pediatrics have lower contrast resolution and increased image noise. CT number linearity is unbiased. The combination of low kV with FBP produces higher spatial resolution, while low mA with IR effectively reduces noise to detect low-contrast objects better.
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Affiliation(s)
- Dafa Miftahuddin
- Department of Physics, Institut Teknologi Sepuluh Nopember, Kampus ITS - Sukolilo Surabaya 600111, East Java, Indonesia
| | - Audiena Gelung Prayitno
- Department of Physics, Institut Teknologi Sepuluh Nopember, Kampus ITS - Sukolilo Surabaya 600111, East Java, Indonesia
| | - Aditya Prayugo Hariyanto
- Department of Physics, Institut Teknologi Sepuluh Nopember, Kampus ITS - Sukolilo Surabaya 600111, East Java, Indonesia
| | - M Roslan A Gani
- Department of Radiology, Dharmais Hospital National Cancer Center, Jakarta 11420, Indonesia
| | - Endarko Endarko
- Department of Physics, Institut Teknologi Sepuluh Nopember, Kampus ITS - Sukolilo Surabaya 600111, East Java, Indonesia.
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Asahara T, Hayashi H, Maeda T, Goto S, Kobayashi D, Nishigami R, Lee C, Ando M, Kanazawa Y, Imajo S, Yamashita K, Higashino K. A wearable active-type X-ray dosimeter having novel functions to derive both incident direction and absolute exposure dose. Radiat Phys Chem Oxf Engl 1993 2023. [DOI: 10.1016/j.radphyschem.2023.110932] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/08/2023]
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"Image quality evaluation of the Precise image CT deep learning reconstruction algorithm compared to Filtered Back-projection and iDose 4: a phantom study at different dose levels". Phys Med 2023; 106:102517. [PMID: 36669326 DOI: 10.1016/j.ejmp.2022.102517] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/25/2022] [Revised: 12/08/2022] [Accepted: 12/27/2022] [Indexed: 01/19/2023] Open
Abstract
PURPOSE To characterize the performance of the Precise Image (PI) deep learning reconstruction (DLR) algorithm for abdominal Computed Tomography (CT) imaging. METHODS CT images of the Catphan-600 phantom (equipped with an external annulus) were acquired using an abdominal protocol at four dose levels and reconstructed using FBP, iDose4 (levels 2,5) and PI ('Soft Tissue' definition, levels 'Sharper','Sharp','Standard','Smooth','Smoother'). Image noise, image non-uniformity, noise power spectrum (NPS), target transfer function (TTF), detectability index (d'), CT numbers accuracy and image histograms were analyzed. RESULTS The behavior of the PI algorithm depended strongly on the selected level of reconstruction. The phantom analysis suggested that the PI image noise decreased linearly by varying the level of reconstruction from Sharper to Smoother, expressing a noise reduction up to 80% with respect to FBP. Additionally, the non-uniformity decreased, the histograms became narrower, and d' values increased as PI reconstruction levels changed from Sharper to Smoother. PI had no significant impact on the average CT number of different contrast objects. The conventional FBP NPS was deeply altered only by Smooth and Smoother levels of reconstruction. Furthermore, spatial resolution was found to be dose- and contrast-dependent, but in each analyzed condition it was greater than or comparable to FBP and iDose4 TTFs. CONCLUSIONS The PI algorithm can reduce image noise with respect to FBP and iDose4; spatial resolution, CT numbers and image uniformity are generally preserved by the algorithm but changes in NPS for the Smooth and Smoother levels need to be considered in protocols implementation.
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Schwartz FR, Vinson EN, Spritzer CE, Colglazier R, Samei E, French RJ, Said N, Waldman L, McCrum E. Prospective Multireader Evaluation of Photon-counting CT for Multiple Myeloma Screening. Radiol Imaging Cancer 2022; 4:e220073. [PMID: 36399038 PMCID: PMC9713593 DOI: 10.1148/rycan.220073] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2022] [Revised: 08/31/2022] [Accepted: 10/26/2022] [Indexed: 05/27/2023]
Abstract
Purpose To determine whether photon-counting CT (PCCT) acquisition of whole-body CT images provides similar quantitative image quality and reader satisfaction for multiple myeloma screening at lower radiation doses than does standard energy-integrating detector (EID) CT. Materials and Methods Patients with monoclonal gammopathy of undetermined significance prospectively underwent clinical noncontrast whole-body CT with EID and same-day PCCT (August-December 2021). Five axial scan locations were evaluated by seven radiologists, with 11% (eight of 70) of images including osteolytic lesions. Images were shown in randomized order, and each reader rated the following: discernibility of the osseous cortex and osseous trabeculae, perceived image noise level, and diagnostic confidence. Presence of lytic osseous lesions was indicated. Contrast-to-noise ratio (CNR) and signal-to-noise ratio (SNR) were calculated. Comparisons were made using paired t tests and mixed linear effects models. Results Seven participants (four women) were included (mean age, 66 years ± 9 [SD]; body mass index, 30.1 kg/m2 ± 5.2). Mean cortical definition, trabecular definition, image noise, and image quality scores were 83, 67, 75, and 78 versus 84, 66, 74, and 76 for EID and PCCT, respectively (P = .65, .11, .26, and .11, respectively). PCCT helped identify more lesions (79% [22 of 28]) than did EID (64% [18 of 28]). CNRs and SNRs were similar between modalities. PCCT had lower radiation doses than EID (volume CT dose index: EID, 11.37 ± 2.8 vs PCCT, 1.8 ± 0.6 [P = .06]; dose-length product: EID, 1654.1 ± 409.6 vs PCCT, 253.4 ± 89.6 [P = .05]). Conclusion This pilot investigation suggests that PCCT affords similar quantitative and qualitative scores as EID at significantly lower radiation doses. Keywords: CT, CT-Spectral, Skeletal-Axial, Spine, Hematologic Diseases, Whole-Body Imaging, Comparative Studies Supplemental material is available for this article. © RSNA, 2022.
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Takegami K, Hayashi H, Maeda T, Lee C, Nishigami R, Asahara T, Goto S, Kobayashi D, Ando M, Kanazawa Y, Yamashita K, Higashino K, Murakami S, Konishi T, Maki M. Thyroid dose reduction shield with the generation of less artifacts used for fast chest CT examination. Radiat Phys Chem Oxf Engl 1993 2022. [DOI: 10.1016/j.radphyschem.2022.110635] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
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Lenfant M, Comby PO, Guillen K, Galissot F, Haioun K, Thay A, Chevallier O, Ricolfi F, Loffroy R. Deep Learning-Based Reconstruction vs. Iterative Reconstruction for Quality of Low-Dose Head-and-Neck CT Angiography with Different Tube-Voltage Protocols in Emergency-Department Patients. Diagnostics (Basel) 2022; 12:1287. [PMID: 35626442 PMCID: PMC9142122 DOI: 10.3390/diagnostics12051287] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2022] [Revised: 05/18/2022] [Accepted: 05/19/2022] [Indexed: 11/20/2022] Open
Abstract
Objective: To compare the image quality of computed tomography angiography of the supra-aortic arteries (CTSA) at different tube voltages in low doses settings with deep learning-based image reconstruction (DLR) vs. hybrid iterative reconstruction (H-IR). Methods: We retrospectively reviewed 102 patients who underwent CTSA systematically reconstructed with both DLR and H-IR. We assessed the image quality both quantitatively and qualitatively at 11 arterial segmental levels and 3 regional levels. Radiation-dose parameters were recorded and the effective dose was calculated. Eighty-six patients were eligible for analysis Of these patients, 27 were imaged with 120 kVp, 30 with 100 kVp, and 29 with 80 kVp. Results: The effective dose in 120 kVp, 100 kVp and 80 kVp was 1.5 ± 0.4 mSv, 1.1 ± 0.3 mSv and 0.68 ± 0.1 mSv, respectively (p < 0.01). Comparing 80 kVp + DLR vs. 120 and 100 kVp + H-IR CT scans, the mean overall arterial attenuation was about 64% and 34% higher (625.9 ± 118.5 HU vs. 382.3 ± 98.6 HU and 468 ± 118.5 HU; p < 0.01) without a significant difference in terms of image noise (17.7 ± 4.9 HU vs. 17.5 ± 5.2; p = 0.7 and 18.1 ± 5.4; p = 0.3) and signal-to-ratio increased by 59% and 33%, respectively (37.9 ± 12.3 vs. 23.8 ± 9.7 and 28.4 ± 12.5). This protocol also provided superior image quality in terms of qualitative parameters, compared to standard-kVp protocols with H-IR. Highest subjective image-quality grades for vascular segments close to the aorta were obtained with the 100 kVp + DLR protocol. Conclusions: DLR significantly reduced image noise and improved the overall image quality of CTSA with both low and standard tube voltages and at all vascular segments. CT that was acquired with 80 kVp and reconstructed with DLR yielded better overall image quality compared to higher kVp values with H-IR, while reducing the radiation dose by half, but it has limitations for arteries that are close to the aortic arch.
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Affiliation(s)
- Marc Lenfant
- Department of Neuroradiology and Emergency Radiology, François-Mitterrand University Hospital, 14 Rue 7 Paul Gaffarel, BP 77908, 21079 Dijon, France; (M.L.); (P.-O.C.); (F.G.); (F.R.)
- Imaging and Artificial Vision (ImViA) Laboratory-EA 7535, University of Bourgogne/Franche-Comté, 9 10 Avenue Alain Savary, BP 47870, 21078 Dijon, France; (K.G.); (O.C.)
| | - Pierre-Olivier Comby
- Department of Neuroradiology and Emergency Radiology, François-Mitterrand University Hospital, 14 Rue 7 Paul Gaffarel, BP 77908, 21079 Dijon, France; (M.L.); (P.-O.C.); (F.G.); (F.R.)
- Imaging and Artificial Vision (ImViA) Laboratory-EA 7535, University of Bourgogne/Franche-Comté, 9 10 Avenue Alain Savary, BP 47870, 21078 Dijon, France; (K.G.); (O.C.)
| | - Kevin Guillen
- Imaging and Artificial Vision (ImViA) Laboratory-EA 7535, University of Bourgogne/Franche-Comté, 9 10 Avenue Alain Savary, BP 47870, 21078 Dijon, France; (K.G.); (O.C.)
- Department of Vascular and Interventional Radiology, Image-Guided Therapy Center, François-Mitterrand 13 University Hospital, 14 Rue Paul Gaffarel, BP 77908, 21079 Dijon, France
| | - Felix Galissot
- Department of Neuroradiology and Emergency Radiology, François-Mitterrand University Hospital, 14 Rue 7 Paul Gaffarel, BP 77908, 21079 Dijon, France; (M.L.); (P.-O.C.); (F.G.); (F.R.)
| | - Karim Haioun
- Computed Tomography Division, Canon Medical Systems France, 24 Quai Gallieni, 92150 Suresnes, France; (K.H.); (A.T.)
| | - Anthony Thay
- Computed Tomography Division, Canon Medical Systems France, 24 Quai Gallieni, 92150 Suresnes, France; (K.H.); (A.T.)
| | - Olivier Chevallier
- Imaging and Artificial Vision (ImViA) Laboratory-EA 7535, University of Bourgogne/Franche-Comté, 9 10 Avenue Alain Savary, BP 47870, 21078 Dijon, France; (K.G.); (O.C.)
- Department of Vascular and Interventional Radiology, Image-Guided Therapy Center, François-Mitterrand 13 University Hospital, 14 Rue Paul Gaffarel, BP 77908, 21079 Dijon, France
| | - Frédéric Ricolfi
- Department of Neuroradiology and Emergency Radiology, François-Mitterrand University Hospital, 14 Rue 7 Paul Gaffarel, BP 77908, 21079 Dijon, France; (M.L.); (P.-O.C.); (F.G.); (F.R.)
| | - Romaric Loffroy
- Imaging and Artificial Vision (ImViA) Laboratory-EA 7535, University of Bourgogne/Franche-Comté, 9 10 Avenue Alain Savary, BP 47870, 21078 Dijon, France; (K.G.); (O.C.)
- Department of Vascular and Interventional Radiology, Image-Guided Therapy Center, François-Mitterrand 13 University Hospital, 14 Rue Paul Gaffarel, BP 77908, 21079 Dijon, France
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