456. Improvement of Image Quality in Digital Angiography : The 5th report : Evaluate of image noise

Objectives: To investigate the impact of total variation regularized expectation maximization (TVREM) reconstruction on the image quality of 68Ga-PSMA-11 PET/CT using phantom and patient data. Methods: Images of a phantom with small hot sphere inserts and 20 prostate cancer patients were acquired with a digital PET/CT using list-mode and reconstructed with ordered subset expectation maximization (OSEM) and TVREM with seven penalisation factors between 0.01 and 0.42 for 2 and 3 minutes-per-bed (m/b) acquisition. The contrast recovery (CR) and background variability (BV) of the phantom, image noise of the liver, and SUVmax of the lesions were measured. Qualitative image quality was scored by two radiologists using a 5-point scale (1-poor, 5-excellent). Results: The performance of CR, BV, and image noise, and the gain of SUVmax was higher for TVREM 2 m/b groups with the penalization of 0.07 to 0.28 compared to OSEM 3 m/b group (all p < 0.05). The image noise of OSEM 3 m/b group was equivalent to TVREM 2 and 3 m/b groups with a penalization of 0.14 and 0.07, while lesions’ SUVmax increased 15 and 20%. The highest qualitative score was attained at the penalization of 0.21 (3.30 ± 0.66) for TVREM 2 m/b groups and the penalization 0.14 (3.80 ± 0.41) for 3 m/b group that equal to or greater than OSEM 3 m/b group (2.90 ± 0.45, p = 0.2 and p < 0.001). Conclusions: TVREM improves lesion contrast and reduces image noise, which allows shorter acquisition with preserved image quality for PSMA PET/CT. Advances in knowledge: TVREM reconstruction with optimized penalization factors can generate higher quality PSMA-PET images for prostate cancer diagnosis.

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Application of deep learning image reconstruction algorithm to improve image quality in CT angiography of children with Takayasu arteritis

Journal of X-Ray Science and Technology ◽

10.3233/xst-211033 ◽

2021 ◽

pp. 1-8

Author(s):

Jihang Sun ◽

Haoyan Li ◽

Haiyun Li ◽

Michelle Li ◽

Yingzi Gao ◽

...

Keyword(s):

Deep Learning ◽

Image Reconstruction ◽

Image Quality ◽

Ct Angiography ◽

Takayasu Arteritis ◽

Image Noise ◽

Diagnostic Confidence ◽

Ct Number ◽

Laboratory Test Results ◽

Significant Difference

BACKGROUND: The inflammatory indexes of children with Takayasu arteritis (TAK) usually tend to be normal immediately after treatment, therefore, CT angiography (CTA) has become an important method to evaluate the status of TAK and sometime is even more sensitive than laboratory test results. OBJECTIVE: To evaluate image quality improvement in CTA of children diagnosed with TAK using a deep learning image reconstruction (DLIR) in comparison to other image reconstruction algorithms. METHODS: hirty-two TAK patients (9.14±4.51 years old) underwent neck, chest and abdominal CTA using 100 kVp were enrolled. Images were reconstructed at 0.625 mm slice thickness using Filtered Back-Projection (FBP), 50%adaptive statistical iterative reconstruction-V (ASIR-V), 100%ASIR-V and DLIR with high setting (DLIR-H). CT number and standard deviation (SD) of the descending aorta and back muscle were measured and contrast-to-noise ratio (CNR) for aorta was calculated. The vessel visualization, overall image noise and diagnostic confidence were evaluated using a 5-point scale (5, excellent; 3, acceptable) by 2 observers. RESULTS: There was no significant difference in CT number across images reconstructed using different algorithms. Image noise values (in HU) were 31.36±6.01, 24.96±4.69, 18.46±3.91 and 15.58±3.65, and CNR values for aorta were 11.93±2.12, 15.66±2.37, 22.54±3.34 and 24.02±4.55 using FBP, 50%ASIR-V, 100%ASIR-V and DLIR-H, respectively. The 100%ASIR-V and DLIR-H images had similar noise and CNR (all P > 0.05), and both had lower noise and higher CNR than FBP and 50%ASIR-V images (all P < 0.05). The subjective evaluation suggested that all images were diagnostic for large arteries, however, only 50%ASIR-V and DLIR-H met the diagnostic requirement for small arteries (3.03±0.18 and 3.53±0.51). CONCLUSION: DLIR-H improves CTA image quality and diagnostic confidence for TAK patients compared with 50%ASIR-V, and best balances image noise and spatial resolution compared with 100%ASIR-V.

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Evaluation of three-dimensional iterative image reconstruction in virtual monochromatic imaging at 40 kilo-electron volts: phantom and clinical studies to assess the image noise and image quality in comparison with other reconstruction techniques

British Journal of Radiology ◽

10.1259/bjr.20190675 ◽

2020 ◽

Vol 93 (1110) ◽

pp. 20190675

Author(s):

Takuya Ishikawa ◽

Shigeru Suzuki ◽

Yoshiaki Katada ◽

Tomoko Takayanagi ◽

Rika Fukui ◽

...

Keyword(s):

Clinical Study ◽

Image Reconstruction ◽

Image Quality ◽

Three Dimensional ◽

Image Noise ◽

Reconstruction Technique ◽

Iterative Image Reconstruction ◽

Virtual Monochromatic Imaging ◽

Monochromatic Imaging

Objective: The purpose of this study was to evaluate the image quality in virtual monochromatic imaging (VMI) at 40 kilo-electron volts (keV) with three-dimensional iterative image reconstruction (3D-IIR). Methods: A phantom study and clinical study (31 patients) were performed with dual-energy CT (DECT). VMI at 40 keV was obtained and the images were reconstructed using filtered back projection (FBP), 50% adaptive statistical iterative reconstruction (ASiR), and 3D-IIR. We conducted subjective and objective evaluations of the image quality with each reconstruction technique. Results: The image contrast-to-noise ratio and image noise in both the clinical and phantom studies were significantly better with 3D-IIR than with 50% ASiR, and with 50% ASiR than with FBP (all, p < 0.05). The standard deviation and noise power spectra of the reconstructed images decreased in the order of 3D-IIR to 50% ASiR to FBP, while the modulation transfer function was maintained across the three reconstruction techniques. In most subjective evaluations in the clinical study, the image quality was significantly better with 3D-IIR than with 50% ASiR, and with 50% ASiR than with FBP (all, p < 0.001). Regarding the diagnostic acceptability, all images using 3D-IIR were evaluated as being fully or probably acceptable. Conclusions: The quality of VMI at 40 keV is improved by 3D-IIR, which allows the image noise to be reduced and structural details to be maintained. Advances in knowledge: The improvement of the image quality of VMI at 40 keV by 3D-IIR may increase the subjective acceptance in the clinical setting.

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Influence of a novel deep-learning based reconstruction software on the objective and subjective image quality in low-dose abdominal computed tomography

British Journal of Radiology ◽

10.1259/bjr.20200677 ◽

2021 ◽

Vol 94 (1117) ◽

pp. 20200677

Author(s):

Andrea Steuwe ◽

Marie Weber ◽

Oliver Thomas Bethge ◽

Christin Rademacher ◽

Matthias Boschheidgen ◽

...

Keyword(s):

Deep Learning ◽

Image Quality ◽

Dose Reduction ◽

Low Dose ◽

Ct Images ◽

Image Noise ◽

The Novel ◽

Subjective Image Quality ◽

Image Information ◽

Noise Ratio

Objectives: Modern reconstruction and post-processing software aims at reducing image noise in CT images, potentially allowing for a reduction of the employed radiation exposure. This study aimed at assessing the influence of a novel deep-learning based software on the subjective and objective image quality compared to two traditional methods [filtered back-projection (FBP), iterative reconstruction (IR)]. Methods: In this institutional review board-approved retrospective study, abdominal low-dose CT images of 27 patients (mean age 38 ± 12 years, volumetric CT dose index 2.9 ± 1.8 mGy) were reconstructed with IR, FBP and, furthermore, post-processed using a novel software. For the three reconstructions, qualitative and quantitative image quality was evaluated by means of CT numbers, noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) in six different ROIs. Additionally, the reconstructions were compared using SNR, peak SNR, root mean square error and mean absolute error to assess structural differences. Results: On average, CT numbers varied within 1 Hounsfield unit (HU) for the three assessed methods in the assessed ROIs. In soft tissue, image noise was up to 42% lower compared to FBP and up to 27% lower to IR when applying the novel software. Consequently, SNR and CNR were highest with the novel software. For both IR and the novel software, subjective image quality was equal but higher than the image quality of FBP-images. Conclusion: The assessed software reduces image noise while maintaining image information, even in comparison to IR, allowing for a potential dose reduction of approximately 20% in abdominal CT imaging. Advances in knowledge: The assessed software reduces image noise by up to 27% compared to IR and 48% compared to FBP while maintaining the image information. The reduced image noise allows for a potential dose reduction of approximately 20% in abdominal imaging.

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Image noise-based dose adaptation in dynamic volume CT of the heart: dose and image quality optimisation in comparison with BMI-based dose adaptation

European Radiology ◽

10.1007/s00330-013-2980-1 ◽

2013 ◽

Vol 24 (1) ◽

pp. 86-94 ◽

Cited By ~ 6

Author(s):

Devang Odedra ◽

Joerg Blobel ◽

Saad AlHumayyd ◽

Miranda Durand ◽

Laura Jimenez-Juan ◽

...

Keyword(s):

Image Quality ◽

Image Noise ◽

Heart Dose ◽

Dose Adaptation ◽

Quality Optimisation ◽

Volume Ct ◽

Dynamic Volume Ct

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Impact of flexible body surface coil and patient table on PET quantification and image quality in integrated PET/MR

Nuklearmedizin ◽

10.3413/nukmed-0608-13-07 ◽

2014 ◽

Vol 53 (03) ◽

pp. 79-87 ◽

Cited By ~ 8

Author(s):

M. Souvatzoglou ◽

A. Martinez-Möller ◽

M. Schwaiger ◽

S. I. Ziegler ◽

S. Fürst ◽

...

Keyword(s):

Standard Deviation ◽

Image Quality ◽

Image Noise ◽

Ct Scanner ◽

Patient Study ◽

Surface Coils ◽

Scan Time ◽

Pet Ct ◽

Relative Standard ◽

Patient Table

SummaryThe surface coils of the Biograph mMR integrated PET/MR system were optimised for PET, but are otherwise unaccounted for. The patient table is still more massive than those of PET/CT devices. The goal was to assess those hardware effects on quantification, count statistics, image quality and scan time both with phantoms and in patients and to investigate their clinical relevance. Patients, material, methods: PET phantom data were acquired with and without the patient table. Image noise was expressed as relative standard deviation and compared to a state-of-the-art PET/CT scanner. Protocols of the phantom/patient study regarding the surface coils were similar. Thoraces/ab- domens of 11 patients were scanned with and without a coil (1 BP, 4 min). Mean uptake and standard deviation in a cubical VOI were derived and expressed as SUV. Results: The patient table reduced the number of true coincidences (trues) by 19% (PET/MR) and by 11% (PET/CT). The scan duration for the mMR had to be increased by approximately 30% to achieve a noise level comparable to that of the PET/CT. Decreased SUVs with coil observed in the phantom were confirmed by the patient study. By removing the coil, the mean liver SUV increased by (6 ± 2)%. With (+3 ± 14)%, the average change was similar in lesions, but exceeded 20% in almost one fifth of them. The number of trues grew by (6 ± 1)% for the patients and by 7% for the phantom. Conclusion: Due to the additional attenuation caused by MR hardware, PET scan durations would have to be increased compared to current PET/CTs to provide similar image noise levels. The effect of the coils is mostly in the order of statistical fluctuations. In tumour lesions, it is more pronounced and shows a larger variability. Therefore, coils should be included in the attenuation correction to ensure accurate quantification and thus comparability across PET/MR and PET/CT scanners and within patient populations.

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Ultra-low-dose lung screening CT with model-based iterative reconstruction: an assessment of image quality and lesion conspicuity

Acta Radiologica ◽

10.1177/0284185117726099 ◽

2017 ◽

Vol 59 (5) ◽

pp. 553-559 ◽

Cited By ~ 4

Author(s):

Yun Hye Ju ◽

Geewon Lee ◽

Ji Won Lee ◽

Seung Baek Hong ◽

Young Ju Suh ◽

...

Keyword(s):

Image Quality ◽

Radiation Dose ◽

Iterative Reconstruction ◽

Low Dose ◽

Image Noise ◽

Low Dose Ct ◽

Group 5 ◽

Lung Screening ◽

Lesion Conspicuity ◽

Group 1

Background Reducing radiation dose inevitably increases image noise, and thus, it is important in low-dose computed tomography (CT) to maintain image quality and lesion detection performance. Purpose To assess image quality and lesion conspicuity of ultra-low-dose CT with model-based iterative reconstruction (MBIR) and to determine a suitable protocol for lung screening CT. Material and Methods A total of 120 heavy smokers underwent lung screening CT and were randomly and equally assigned to one of five groups: group 1 = 120 kVp, 25 mAs, with FBP reconstruction; group 2 = 120 kVp, 10 mAs, with MBIR; group 3 = 100 kVp, 15 mAs, with MBIR; group 4 = 100 kVp, 10 mAs, with MBIR; and group 5 = 100 kVp, 5 mAs, with MBIR. Two radiologists evaluated intergroup differences with respect to radiation dose, image noise, image quality, and lesion conspicuity using the Kruskal–Wallis test and the Chi-square test. Results Effective doses were 61–87% lower in groups 2–5 than in group 1. Image noises in groups 1 and 5 were significantly higher than in the other groups ( P < 0.001). Overall image quality was best in group 1, but diagnostic acceptability of overall image qualities in groups 1–3 was not significantly different (all P values > 0.05). Lesion conspicuities were similar in groups 1–4, but were significantly poorer in group 5. Conclusion Lung screening CT with MBIR obtained at 100 kVp and 15 mAs enables a ∼60% reduction in radiation dose versus low-dose CT, while maintaining image quality and lesion conspicuity.

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