| 1. |
Tsukasa Kojima, Yuzo Yamasaki, Yuko Matsuura, Ryoji Mikayama, Takashi Shirasaka, Masatoshi Kondo, Takeshi Kamitani, Toyoyuki Kato, Kousei Ishigami, Hidetake Yabuuchi, The Feasibility of Deep Learning-Based Reconstruction for Low-Tube-Voltage CT Angiography for Transcatheter Aortic Valve Implantation., Journal of computer assisted tomography, 10.1097/RCT.0000000000001525, 2023.08, OBJECTIVE: The purpose of this study is to evaluate the efficacy of deep learning reconstruction (DLR) on low-tube-voltage computed tomographic angiography (CTA) for transcatheter aortic valve implantation (TAVI). METHODS: We enrolled 30 patients who underwent TAVI-CT on a 320-row CT scanner. Electrocardiogram-gated coronary CTA (CCTA) was performed at 100 kV, followed by nongated aortoiliac CTA at 80 kV using a single bolus of contrast material. We used hybrid-iterative reconstruction (HIR), model-based IR (MBIR), and DLR to reconstruct these images. The contrast-to-noise ratios (CNRs) were calculated. Five-point scales were used for the overall image quality analysis. The diameter of the aortic annulus was measured in each reconstructed image, and we compared the interobserver and intraobserver agreements. RESULTS: In the CCTA, the CNR and image quality score for DLR were significantly higher than those for HIR and MBIR (P 0.89). CONCLUSIONS: In low tube voltage TAVI-CT, DLR provides higher image quality than HIR, and DLR provides higher image quality than MBIR in CCTA and is visually comparable to MBIR in aortoiliac CTA.. |
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Yuna Katsuyama, Tsukasa Kojima, Takashi Shirasaka, Masatoshi Kondo, Toyoyuki Kato, Characteristics of the deep learning-based virtual monochromatic image with fast kilovolt-switching CT: a phantom study., Radiological physics and technology, 10.1007/s12194-022-00695-x, 16, 1, 77-84, 2023.03, PURPOSE: We assessed the physical properties of virtual monochromatic images (VMIs) obtained with different energy levels in various contrast settings and radiation doses using deep learning-based spectral computed tomography (DL-Spectral CT) and compared the results with those from single-energy CT (SECT) imaging. MATERIALS AND METHODS: A Catphan® 600 phantom was scanned by DL-Spectral CT at various radiation doses. We reconstructed the VMIs obtained at 50, 70, and 100 keV. SECT (120 kVp) images were acquired at the same radiation doses. The standard deviations of the CT number and noise power spectrum (NPS) were calculated for noise characterization. We evaluated the spatial resolution by determining the 10% task-based transfer function (TTF) level, and we assessed the task-based detectability index (d'). RESULTS: Regardless of the radiation dose, the noise was the lowest at 70 keV VMI. The NPS showed that the noise amplitude at all spatial frequencies was the lowest among other VMI and 120 kVp images. The spatial resolution was higher for 70 keV VMI compared to the other VMIs, except for high-contrast objects. The d' of 70 keV VMI was the highest among the VMI and 120 kVp images at all radiation doses and contrast settings. The d' of the 70 keV VMIs at the minimum dose was higher than that at the maximum dose in any other image. CONCLUSION: The physical properties of the DL-Spectral CT VMIs varied with the energy level. The 70 keV VMI had the highest detectability by far among the VMI and 120-kVp images. DL-Spectral CT may be useful to reduce radiation doses.. |
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Tsukasa Kojima, Takashi Shirasaka, Yuzo Yamasaki, Masatoshi Kondo, Hiroshi Hamasaki, Ryoji Mikayama, Yuki Sakai, Toyoyuki Kato, Akihiro Nishie, Kousei Ishigami, Hidetake Yabuuchi, Importance of the heart rate in ultra-high-resolution coronary CT angiography with 0.35 s gantry rotation time, JAPANESE JOURNAL OF RADIOLOGY, 10.1007/s11604-022-01265-2, 40, 8, 781-790, 2022.04, Purpose We investigated the effects of the heart rate (HR) on the motion artifact in coronary computed tomography angiography (CCTA) with ultra-high-resolution-CT (U-HRCT), and we clarified the upper limit of optimal HR in CCTA with U-HRCT in a comparison with conventional-resolution-CT (CRCT) on a cardiac phantom and in patients with CCTA.Materials and methods A pulsating cardiac phantom equipped with coronary models was scanned at static and HR simulations of 40-90 beats/min (bpm) at 10-bpm intervals using U-HRCT and CRCT, respectively. The sharpness and lumen diameter of the coronary model were quantitatively compared between U-HRCT and CRCT stratified by HR in the phantom study. We also assessed the visual inspections of clinical images in CCTA with U-HRCT.Results At the HRs 60 bpm, the inverse was shown. For the image sharpness, the U-HRCT was significantly superior to the CRCT (p |
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Ryoji Mikayama, Takashi Shirasaka, Tsukasa Kojima, Yuki Sakai, Hidetake Yabuuchi, Masatoshi Kondo, Toyoyuki Kato, Deep-learning reconstruction for ultra-low-dose lung CT: Volumetric measurement accuracy and reproducibility of artificial ground-glass nodules in a phantom study., The British journal of radiology, 10.1259/bjr.20210915, 95, 1130, 20210915-20210915, 2022.02, OBJECTIVES: The lung nodule volume determined by CT is used for nodule diagnoses and monitoring tumor responses to therapy. Increased image noise on low-dose CT degrades the measurement accuracy of the lung nodule volume. We compared the volumetric accuracy among deep-learning reconstruction (DLR), model-based iterative reconstruction (MBIR), and hybrid iterative reconstruction (HIR) at an ultra-low-dose setting. METHODS: Artificial ground-glass nodules (6 mm and 10 mm diameters, -660 HU) placed at the lung-apex and the middle-lung field in chest phantom were scanned by 320-row CT with the ultra-low-dose setting of 6.3 mAs. Each scan data set was reconstructed by DLR, MBIR, and HIR. The volumes of nodules were measured semi-automatically, and the absolute percent volumetric error (APEvol) was calculated. The APEvol provided by each reconstruction were compared by the Tukey-Kramer method. Inter- and intraobserver variabilities were evaluated by a Bland-Altman analysis with limits of agreements. RESULTS: DLR provided a lower APEvol compared to MBIR and HIR. The APEvol of DLR (1.36%) was significantly lower than those of the HIR (8.01%, p = 0.0022) and MBIR (7.30%, p = 0.0053) on a 10-mm-diameter middle-lung nodule. DLR showed narrower limits of agreement compared to MBIR and HIR in the inter- and intraobserver agreement of the volumetric measurement. CONCLUSIONS: DLR showed higher accuracy compared to MBIR and HIR for the volumetric measurement of artificial ground-glass nodules by ultra-low-dose CT. ADVANCES IN KNOWLEDGE: DLR with ultra-low-dose setting allows a reduction of dose exposure, maintaining accuracy for the volumetry of lung nodule, especially in patients which deserve a long-term follow-up.. |
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Yuki Sakai, Erina Kitamoto, Kazutoshi Okamura, Shinya Takarabe, Takashi Shirasaka, Ryoji Mikayama, Masatoshi Kondo, Masato Tatsumi, Tsukasa Kojima, Toyoyuki Kato, Kazunori Yoshiura, Low-radiation dose scan protocol for preoperative imaging for dental implant surgery using deep learning-based reconstruction in multidetector CT., Oral radiology, 10.1007/s11282-021-00584-w, 38, 4, 517-526, 2022.01, OBJECTIVES: This study aimed to investigate the impact of a deep learning-based reconstruction (DLR) technique on image quality and reduction of radiation exposure, and to propose a low-dose multidetector-row computed tomography (MDCT) scan protocol for preoperative imaging for dental implant surgery. METHODS: The PB-1 phantom and a Catphan phantom 600 were scanned using volumetric scanning with a 320-row MDCT scanner. All scans were performed with a tube voltage of 120 kV, and the tube current varied from 120 to 60 to 40 to 30 mA. Images of the mandible were reconstructed using DLR. Additionally, images acquired with the 120-mA protocol were reconstructed using filtered back projection as a reference. Two observers independently graded the image quality of the mandible images using a 4-point scale (4, superior to reference; 1, unacceptable). The system performance function (SPF) was calculated to comprehensively evaluate image quality. The Wilcoxon signed-rank test was employed for statistical analysis, with statistical significance set at p value |
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Takashi Shirasaka, Tsukasa Kojima, Yoshinori Funama, Yuki Sakai, Masatoshi Kondo, Ryoji Mikayama, Hiroshi Hamasaki, Toyoyuki Kato, Yasuhiro Ushijima, Yoshiki Asayama, Akihiro Nishie, Image quality improvement with deep learning-based reconstruction on abdominal ultrahigh-resolution CT: A phantom study., Journal of applied clinical medical physics, 10.1002/acm2.13318, 22, 7, 286-296, 2021.07, PURPOSE: In an ultrahigh-resolution CT (U-HRCT), deep learning-based reconstruction (DLR) is expected to drastically reduce image noise without degrading spatial resolution. We assessed a new algorithm's effect on image quality at different radiation doses assuming an abdominal CT protocol. METHODS: For the normal-sized abdominal models, a Catphan 600 was scanned by U-HRCT with 100%, 50%, and 25% radiation doses. In all acquisitions, DLR was compared to model-based iterative reconstruction (MBIR), filtered back projection (FBP), and hybrid iterative reconstruction (HIR). For the quantitative assessment, we compared image noise, which was defined as the standard deviation of the CT number, and spatial resolution among all reconstruction algorithms. RESULTS: Deep learning-based reconstruction yielded lower image noise than FBP and HIR at each radiation dose. DLR yielded higher image noise than MBIR at the 100% and 50% radiation doses (100%, 50%, DLR: 15.4, 16.9 vs MBIR: 10.2, 15.6 Hounsfield units: HU). However, at the 25% radiation dose, the image noise in DLR was lower than that in MBIR (16.7 vs. 26.6 HU). The spatial frequency at 10% of the modulation transfer function (MTF) in DLR was 1.0 cycles/mm, slightly lower than that in MBIR (1.05 cycles/mm) at the 100% radiation dose. Even when the radiation dose decreased, the spatial frequency at 10% of the MTF of DLR did not change significantly (50% and 25% doses, 0.98 and 0.99 cycles/mm, respectively). CONCLUSION: Deep learning-based reconstruction performs more consistently at decreasing dose in abdominal ultrahigh-resolution CT compared to all other commercially available reconstruction algorithms evaluated.. |
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Yuki Sakai, Erina Kitamoto, Kazutoshi Okamura, Masato Tatsumi, Takashi Shirasaka, Ryoji Mikayama, Masatoshi Kondo, Hiroshi Hamasaki, Toyoyuki Kato, Kazunori Yoshiura, Metal artefact reduction in the oral cavity using deep learning reconstruction algorithm in ultra-high-resolution computed tomography: a phantom study., Dento maxillo facial radiology, 10.1259/dmfr.20200553, 50, 7, 20200553-20200553, 2021.04, OBJECTIVES: This study aimed to improve the impact of the metal artefact reduction (MAR) algorithm for the oral cavity by assessing the effect of acquisition and reconstruction parameters on an ultra-high-resolution CT (UHRCT) scanner. METHODS: The mandible tooth phantom with and without the lesion was scanned using super-high-resolution, high-resolution (HR), and normal-resolution (NR) modes. Images were reconstructed with deep learning-based reconstruction (DLR) and hybrid iterative reconstruction (HIR) using the MAR algorithm. Two dental radiologists independently graded the degree of metal artefact (1, very severe; 5, minimum) and lesion shape reproducibility (1, slight; 5, almost perfect). The signal-to-artefact ratio (SAR), accuracy of the CT number of the lesion, and image noise were calculated quantitatively. The Tukey-Kramer method with a p-value of less than 0.05 was used to determine statistical significance. RESULTS: The HRDLR visual score was better than the NRHIR score in terms of degree of metal artefact (4.6 ± 0.5 and 2.6 ± 0.5, p |
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Tsukasa Kojima, Takashi Shirasaka, Masatoshi Kondo, Toyoyuki Kato, Akihiro Nishie, Kousei Ishigami, Hidetake Yabuuchi, A novel fast kilovoltage switching dual-energy CT with deep learning: Accuracy of CT number on virtual monochromatic imaging and iodine quantification., Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB), 10.1016/j.ejmp.2020.12.018, 81, 253-261, 2021.01, PURPOSE: A novel fast kilovoltage switching dual-energy CT with deep learning [Deep learning based-spectral CT (DL-Spectral CT)], which generates a complete sinogram for each kilovolt using deep learning views that complement the measured views at each energy, was commercialized in 2020. The purpose of this study was to evaluate the accuracy of CT numbers in virtual monochromatic images (VMIs) and iodine quantifications at various radiation doses using DL-Spectral CT. MATERIALS AND METHODS: Two multi-energy phantoms (large and small) using several rods representing different materials (iodine, calcium, blood, and adipose) were scanned by DL-Spectral CT at varying radiation doses. Images were reconstructed using three reconstruction parameters (body, lung, bone). The absolute percentage errors (APEs) for CT numbers on VMIs at 50, 70, and 100 keV and iodine quantification were compared among different radiation dose protocols. RESULTS: The APEs of the CT numbers on VMIs were |
| 9. |
Yuki Sakai, Kazutoshi Okamura, Erina Kitamoto, Yukiko N Kami, Takashi Shirasaka, Ryoji Mikayama, Masato Tatsumi, Masatoshi Kondo, Toyoyuki Kato, Kazunori Yoshiura, Improved scan method for dental imaging using multidetector computed tomography: a phantom study., Dento maxillo facial radiology, 10.1259/dmfr.20190462, 49, 6, 20190462-20190462, 2020.09, OBJECTIVES: This study aimed to propose an improved scan method to shorten irradiation time and reduce radiation exposure. METHODS: The maxilla of a human head CT phantom and a Catphan phantom were used for qualitative and quantitative assessment, respectively. The phantoms were scanned by a 160-row multidetector CT scanner using volumetric and helical scanning. In volumetric scanning, the tube current varied from 120 to 60 to 30 to 20 mA with a tube voltage of 120 kV. Images were reconstructed with a bone kernel using iterative reconstruction (IR) and filtered back projection. As a reference protocol, helical scanning was performed using our clinical setting with 120 kV. Two dental radiologists independently graded the quality of dental images using a 4-point scale (4, superior to reference; 1, unacceptable). For the quantitative assessment, we assessed the system performance from each scan. RESULTS: There was no significant difference between the image quality of volumetric scanning using the 60 mA protocol reconstructed with IR and that of the reference (3.08 and 3.00, p = 0.3388). The system performance values at 1.0 cycles/mm of volumetric scanning and 60 mA protocol reconstructed with IR and reference were 0.0038 and 0.0041, respectively. The effective dose of volumetric scanning using the 60 mA protocol was 51.8 µSv, which is a 64.2% reduction to that of the reference. CONCLUSIONS: We proposed an improved scan method resulting in a 64.2% reduction of radiation dose with one-fourth of irradiation time by combining volumetric scanning and IR technique in multidetector CT.. |
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Seiichiro Takao, Akihiro Nishie, Yoshiki Asayama, Kousei Ishigami, Yasuhiro Ushijima, Daisuke Kakihara, Tomohiro Nakayama, Nobuhiro Fujita, Koichiro Morita, Keisuke Ishimatsu, Tomoharu Yoshizumi, Toru Ikegami, Masatoshi Kondo, Hiroshi Honda, Improved visualization of a fine intrahepatic biliary duct on drip infusion cholangiography-computed tomography: Impact of knowledge-based iterative model reconstruction., Hepatology research : the official journal of the Japan Society of Hepatology, 10.1111/hepr.13477, 50, 5, 629-634, 2020.05, AIM: The purpose of this study was to investigate the visualization of fine biliary ducts with knowledge-based iterative model reconstruction (IMR) in low-dose drip infusion computed tomography (CT) cholangiography (DIC-CT) as compared with filtered back projection (FBP) and hybrid iterative reconstruction (iDose4 ). METHODS: A total of 38 patients underwent DIC-CT for living donor liver transplantation. CT was performed approximately 20 min after the end of the infusion of meglumine iotroxate (100 mL). Images were reconstructed using FBP, iDose4 , and IMR, and 1-mm slice images at fixed window level and width were prepared for assessment. Two reviewers independently evaluated the quality of visualization of the fine biliary ducts of the caudate lobe (B1) using a 5-point scale. The visualization scores of three reconstructed images were compared using the Kruskal-Wallis test and Mann-Whitney U-test. RESULTS: For reviewer 1, the visualization score of IMR was significantly higher than that of FBP (P = 0.012), and tended to be higher than that of iDose4 (P = 0.078). For reviewer 2, the visualization score of IMR was significantly higher than those of both FBP and iDose4 (P |
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Ryoji Mikayama, Takashi Shirasaka, Hidetake Yabuuchi, Yuki Sakai, Tsukasa Kojima, Masatoshi Kondo, Hideki Yoshikawa, Toyoyuki Kato, Effect of scan mode and focal spot size in airway dimension measurements for ultra-high-resolution computed tomography of chronic obstructive pulmonary disease: A COPDGene phantom study., Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB), 10.1016/j.ejmp.2019.12.025, 70, 102-108, 2020.02, PURPOSE: Quantitative evaluations of airway dimensions through computed tomography (CT) have revealed a good correlation with airflow limitation in chronic obstructive pulmonary disease. However, large inaccuracies have been known to occur in CT airway measurements. Ultra-high-resolution CT (UHRCT) might improve measurement accuracy using precise scan modes with minimal focal spot. We assessed the effects of scan mode and focal spot size on airway measurements in UHRCT. METHODS: COPDGene Ⅱ phantom, comprising a plastic tube mimicking human airway of inner diameter 3 mm, wall thickness 0.6 mm, and inclination 30 degrees was scanned at super high resolution (SHR, beam collimation of 0.25 mm × 160 rows) and high resolution (HR, beam collimation of 0.5 mm × 80 rows) modes using UHRCT. Each acquisition was performed both with small (0.4 × 0.5 mm) and large (0.6 × 1.3 mm) focal spots. The wall area percentage (WA%) was calculated as the percentage of total airway area occupied by the airway wall. Statistical analysis was performed to compare the WA% measurement errors for each scan mode and focal spot size. RESULTS: The WA% measurement errors in the SHR mode were 9.8% with a small focal spot and 18.8% with a large one. The measurement errors in the HR mode were 13.3% with a small focal spot and 21.4% with a large one. There were significant differences between each scan mode and focal spot size (p |
| 12. |
Shirasaka T, Nagao M, Yamasaki Y, Kojima T, Kondo M, Hamasaki H, Kamitani T, Kato T, Asayama Y, Low radiation dose and high image quality of 320-row coronary CT angiography using a small dose of contrast medium and refined scan timing prediction, Journal of Computer Assisted Tomography, 10.1097/RCT.0000000000000951, in press, 1, 7-12, 2019.09. |
| 13. |
Shirasaka T, Nagao M, Yamasaki Y, Kojima T, Kondo M, Shimomiya Y, Kamitani T, Honda H, Feasible scan timing for 320-row coronary CT angiography generated by the time to peak in the ascending aorta., Clinical imaging, 10.1016/j.clinimag.2019.01.005, 54, 153-158, 2019.03. |
| 14. |
Kojima T, Yamasaki Y, Kamitani T, Yabuuchi H, Shirasaka T, Shimomiya Y, Kondo M, Hamasaki H, Kato T, Nagao M, Honda H, Dynamic Coronary 320-Row CT Angiography Using Low-Dose Contrast and Temporal Maximum Intensity Projection: A Comparison with Standard Coronary CT Angiography, Cardiovascular Imaging Asia, 10.22468/cvia.2018.00213, 3, 1, 1-7, 2019.01. |
| 15. |
Kondo M, Nishie A, Fujita N, Morita K, Shirasaka T, Arimura H, Nakamura Y, Honda H., Impact of hybrid iterative reconstruction on unenhanced liver CT. , Br J Radiol., 10.1259/bjr.20150670, 2016.12. |
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N Sakai, H Yabuuchi, M Kondo, Y Matsuo, T Kamitani, M Nagao, M Jinnouchi, M Yonezawa, T Kojima, Y Yano, H Honda, Low-dose CT screening using hybrid iterative reconstruction: confidence ratings of diagnoses of simulated lesions other than lung cancer., The British journal of radiology, 10.1259/bjr.20150159, 88, 1053, 20150159-20150159, 2015.09, OBJECTIVE: To evaluate the confidence ratings of diagnoses of simulated lesions other than lung cancer on low-dose screening CT with hybrid iterative reconstruction (IR). METHODS: Simulated lesions (emphysema, mediastinal masses and interstitial pneumonia) in a chest phantom were scanned by a 320-row area detector CT. The scans were performed by 64-row and 160-row helical scans at various dose levels and were reconstructed by filtered back projection (FBP) and IR. Emphysema, honeycombing and reticular opacity were visually scored on a four-point scale by six thoracic radiologists. The ground-glass opacity as a percentage of total lung volume (%GGO), CT value and contrast-to-noise ratio (CNR) of mediastinal masses were calculated. These scores and values were compared between FBP and IR. Wilcoxon's signed-rank test was used (p |
