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

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.

80-kVp hepatic CT to reduce contrast medium dose in azotemic patients: a feasibility study

2019 ◽  
Vol 61 (4) ◽  
pp. 441-449
Author(s):  
Fredrik Holmquist ◽  
Marcus Söderberg ◽  
Ulf Nyman ◽  
Tobias Fält ◽  
Roger Siemund ◽  
...  
Keyword(s):  
Body Mass Index ◽  
Glomerular Filtration Rate ◽  
Image Quality ◽  
Contrast Medium ◽  
Glomerular Filtration ◽  
Body Mass ◽  
Filtration Rate ◽  
Image Noise ◽  
Subjective Image Quality ◽  
Noise Ratio

Background Low peak kilovoltage (kVp) computed tomography (CT) may be used to reduce contrast medium doses in patients at risk of contrast medium-induced acute kidney injury if image noise can be controlled by increasing X-ray tube loading (mAs). Purpose To evaluate objective and subjective image quality in 80-kVp CT with reduced contrast medium dose and compensated mAs for unchanged image noise in patients with estimated glomerular filtration rate <45 mL/min compared with the standard 120-kVp protocol. Material and Methods 80-kVp CT with 300 mg I/kg in 40 patients (body mass index 18–32 kg/m2, glomerular filtration rate <45 mL/min) and 120-kVp CT with 500 mg I/kg in 40 patients (body mass index = 17–30 kg/m2, glomerular filtration rate ≥45 mL/min) was compared on mean hepatic attenuation, image noise, contrast medium enhancement, signal-to-noise ratio, contrast-to-noise ratio, effective radiation dose, and subjective image quality. Results There were no significant differences regarding median hepatic post-contrast attenuation, image noise, contrast medium enhancement, signal-to-noise ratio, contrast-to-noise ratio, or effective dose between the 80-kVp and 120-kVp cohorts: 114/110 HU; 14/14 HU; 57/53 HU; 8.0/7.4; 3.8/3.5; and 5.3/5.9 mSv, respectively. However, subjective image visual grading showed statistically significantly inferior scores for 80 kVp for six of eight items. After exclusion of seven inferior examinations not caused by the chosen kVp technique, only three items showed inferior scores for 80 kVp. Only 5% of gradings regarding overall image quality were <3 of 5 points. Conclusion Despite lower subjective image quality, objective data indicate that 80-kVp CT with reduced contrast medium doses and compensated mAs may have the potential to provide satisfactory diagnostic quality in patients with body mass index <30 kg/m2, which could benefit patients at risk of contrast medium-induced acute kidney injury.

Application of low-dose CT combined with model-based iterative reconstruction algorithm in oncologic patients during follow-up: dose reduction and image quality

2021 ◽  
pp. 20201223
Author(s):  
Davide Ippolito ◽  
Cesare Maino ◽  
Anna Pecorelli ◽  
Ilaria Salemi ◽  
Davide Gandola ◽  
...  
Keyword(s):  
Image Quality ◽  
Radiation Dose ◽  
Dose Reduction ◽  
Iterative Reconstruction ◽  
Low Dose ◽  
Ct Images ◽  
Ct Attenuation ◽  
Oncologic Patients ◽  
Attenuation Values

Objectives: To compare image quality and radiation dose of CT images reconstructed with model-based iterative reconstruction (MBIR) and hybrid-iterative (HIR) algorithm in oncologic patients. Methods: 125 oncologic patients underwent both contrast-enhanced low- (100 kV), and standard (120 kV) dose CT, were enrolled. Image quality was assessed by using a 4-point Likert scale. CT attenuation values, expressed in Hounsfield unit (HU), were recorded within a regions of interest (ROI) of liver, spleen, paraspinal muscle, aortic lumen, and subcutaneous fat tissue. Image noise, expressed as standard deviation (SD), signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were calculated. Radiation dose were analyzed. Paired Student’s t-test was used to compare all continuous variables. Results: The overall median score assessed as image quality for CT images with the MBIR algorithm was significantly higher in comparison with HIR [4 (range 3–4) vs 3 (3-4), p = 0.017]. CT attenuation values and SD were significantly higher and lower, respectively, in all anatomic districts in images reconstructed with MBIR in comparison with HIR ones (all p < 0.001). SNR and CNR values were higher in CT images reconstructed with MBIR, reaching a significant difference in all districts (all p < 0.001). Radiation dose were significantly lower in the MBIR group compared with the HIR group (p < 0.001). Conclusions: MBIR combined with low-kV setting allows an important dose reduction in whole-body CT imaging, reaching a better image quality both qualitatively and quantitatively. Advances in knowledge: MBIR with low-dose approach allows a reduction of dose exposure, maintaining high image quality, especially in patients which deserve a longlasting follow-up.

scholarly journals Iterative reconstruction improves image quality and reduces radiation dose in trauma protocols; A human cadaver study

2021 ◽  
Vol 10 (10) ◽  
pp. 205846012110553
Author(s):  
Johannes Clemens Godt ◽  
Cathrine K Johansen ◽  
Anne Catrine T Martinsen ◽  
Anselm Schulz ◽  
Helga M Brøgger ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Image Quality ◽  
Dose Reduction ◽  
Iterative Reconstruction ◽  
Low Dose ◽  
Human Cadaver ◽  
Full Dose ◽  
Significant Difference ◽  
Noise Ratio ◽  
Dose Levels

Background Radiation-related cancer risk is an object of concern in CT of trauma patients, as these represent a young population. Different radiation reducing methods, including iterative reconstruction (IR), and spilt bolus techniques have been introduced in the recent years in different large scale trauma centers. Purpose To compare image quality in human cadaver exposed to thoracoabdominal computed tomography using IR and standard filtered back-projection (FBP) at different dose levels. Material and methods Ten cadavers were scanned at full dose and a dose reduction in CTDIvol of 5 mGy (low dose 1) and 7.5 mGy (low dose 2) on a Siemens Definition Flash 128-slice computed tomography scanner. Low dose images were reconstructed with FBP and Sinogram affirmed iterative reconstruction (SAFIRE) level 2 and 4. Quantitative image quality was analyzed by comparison of contrast-to-noise ratio (CNR) and signal-to-noise ratio (SNR). Qualitative image quality was evaluated by use of visual grading regression (VGR) by four radiologists. Results Readers preferred SAFIRE reconstructed images over FBP at a dose reduction of 40% (low dose 1) and 56% (low dose 2), with significant difference in overall impression of image quality. CNR and SNR showed significant improvement for images reconstructed with SAFIRE 2 and 4 compared to FBP at both low dose levels. Conclusions Iterative image reconstruction, SAFIRE 2 and 4, resulted in equal or improved image quality at a dose reduction of up to 56% compared to full dose FBP and may be used a strong radiation reduction tool in the young trauma population.

scholarly journals Image quality and lesion detectability in low-dose paediatric 18F-FDG scans using total-body PET/CT

2021 ◽  
Author(s):  
Ying-Ying Hu ◽  
Yu-Mo Zhao ◽  
Tao Chen ◽  
Wei-Guang Zhang ◽  
Lin-Hao Wang ◽  
...  
Keyword(s):  
Image Quality ◽  
Dose Reduction ◽  
Low Dose ◽  
Subjective Image Quality ◽  
Full Dose ◽  
Lesion Detectability ◽  
Paediatric Patients ◽  
Pet Ct ◽  
Total Body ◽  
Lesion Conspicuity

Abstract Purpose: To investigate the effects of dose reduction on image quality and lesion detectability of oncological 18F-FDG total-body PET/CT in paediatric oncological patients, and explore the minimum threshold of administered tracer activity.Methods: A total of 33 paediatric patients (weight, 8.5–58.5 kg; age 0.8–17.6 years) underwent total-body PET/CT using uEXPLORER scanner with an 18F-FDG administered dose of 3.7 MBq/kg and an acquisition time of 600 s were retrospectively enrolled. Low-dose images (0.12 – 1.85 MBq/kg) were simulated by truncating the list-mode PET data to reducing count density. Subjective image quality was rated on a 5-point scale. Semi-quantitative uptake metrics for low-dose images were assessed using region-of-interest (ROI) analysis of healthy liver and suspected lesions and were compared to full-dose images. The micro-lesion detectability was compared among the dose-dependent PET images.Results: Our analysis shows that sufficient subjective image quality and lesion conspicuity could be maintained down to 1/30th (0.12 MBq/kg) of the administered dose of 18F-FDG, where good image quality scores were given to 1/2- and 1/10- dose groups. The image noise was significantly more deranged than the overall quality and lesion conspicuity in 1/30- to 1/10-dose groups (all P < 0.05). With reduced doses, quantitative analysis of ROIs showed that SUVmax and SD in the liver increased gradually (P < 0.05), but SUVmax in the lesions and lesion-to-background ratio (LBR) showed no significant deviation down to 1/30-dose. 100% of the 18F-FDG-avid micro-lesions identified in full-dose images were localised down to 1/15-dose images; while 97% of the lesion were localized in 1/30-dose images.Conclusion: The total-body PET/CT might significantly decrease the administered dose upon maintaining the image quality and diagnostic performance of micro-lesions in paediatric patients. Data suggests that using total-body PET/CT, optimal image quality could be achieved with an administered dose-reduction down to 1/10-dose (0.37 MBq/kg).

scholarly journals Deep Learning Versus Iterative Reconstruction for CT Pulmonary Angiography in the Emergency Setting: Improved Image Quality and Reduced Radiation Dose

Diagnostics ◽  
2020 ◽  
Vol 10 (8) ◽  
pp. 558
Author(s):  
Marc Lenfant ◽  
Olivier Chevallier ◽  
Pierre-Olivier Comby ◽  
Grégory Secco ◽  
Karim Haioun ◽  
...  
Keyword(s):  
Deep Learning ◽  
Image Quality ◽  
Radiation Dose ◽  
Iterative Reconstruction ◽  
Noise Signal ◽  
Pulmonary Angiography ◽  
Image Noise ◽  
Emergency Setting ◽  
Dose Length Product ◽  
Noise Ratio

To compare image quality and the radiation dose of computed tomography pulmonary angiography (CTPA) subjected to the first deep learning-based image reconstruction (DLR) (50%) algorithm, with images subjected to the hybrid-iterative reconstruction (IR) technique (50%). One hundred forty patients who underwent CTPA for suspected pulmonary embolism (PE) between 2018 and 2019 were retrospectively reviewed. Image quality was assessed quantitatively (image noise, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR)) and qualitatively (on a 5-point scale). Radiation dose parameters (CT dose index, CTDIvol; and dose-length product, DLP) were also recorded. Ninety-three patients were finally analyzed, 48 with hybrid-IR and 45 with DLR images. The image noise was significantly lower and the SNR (24.4 ± 5.9 vs. 20.7 ± 6.1) and CNR (21.8 ± 5.8 vs. 18.6 ± 6.0) were significantly higher on DLR than hybrid-IR images (p < 0.01). DLR images received a significantly higher score than hybrid-IR images for image quality, with both soft (4.4 ± 0.7 vs. 3.8 ± 0.8) and lung (4.1 ± 0.7 vs. 3.6 ± 0.9) filters (p < 0.01). No difference in diagnostic confidence level for PE between both techniques was found. CTDIvol (4.8 ± 1.4 vs. 4.0 ± 1.2 mGy) and DLP (157.9 ± 44.9 vs. 130.8 ± 41.2 mGy∙cm) were lower on DLR than hybrid-IR images. DLR both significantly improved the image quality and reduced the radiation dose of CTPA examinations as compared to the hybrid-IR technique.

Diagnostic performance and image quality of deep learning image reconstruction (DLIR) on unenhanced low-dose abdominal CT for urolithiasis

2021 ◽  
pp. 028418512110358
Author(s):  
Aurélien Delabie ◽  
Roger Bouzerar ◽  
Raphaël Pichois ◽  
Xavier Desdoit ◽  
Jérémie Vial ◽  
...  
Keyword(s):  
Deep Learning ◽  
Image Reconstruction ◽  
Image Quality ◽  
Low Dose ◽  
Signal To Noise Ratio ◽  
Intraclass Correlation ◽  
Reconstruction Algorithm ◽  
Urinary Stones ◽  
Abdominopelvic Ct ◽  
Noise Ratio

Background Patients with urolithiasis undergo radiation overexposure from computed tomography (CT) scans. Improvement of image reconstruction is necessary for radiation dose reduction. Purpose To evaluate a deep learning-based reconstruction algorithm for CT (DLIR) in the detection of urolithiasis at low-dose non-enhanced abdominopelvic CT. Material and Methods A total of 75 patients who underwent low-dose abdominopelvic CT for urolithiasis were retrospectively included. Each examination included three reconstructions: DLIR; filtered back projection (FBP); and hybrid iterative reconstruction (IR; ASiR-V 70%). Image quality was subjectively and objectively assessed using attenuation and noise measurements in order to calculate the signal-to-noise ratio (SNR), absolute contrast, and contrast-to-noise ratio (CNR). Attenuation of the largest stones were also compared. Detectability of urinary stones was assessed by two observers. Results Image noise was significantly reduced with DLIR: 7.2 versus 17 and 22 for ASiR-V 70% and FBP, respectively. Similarly, SNR and CNR were also higher compared to the standard reconstructions. When the structures had close attenuation values, contrast was lower with DLIR compared to ASiR-V. Attenuation of stones was also lowered in the DLIR series. Subjective image quality was significantly higher with DLIR. The detectability of all stones and stones >3 mm was excellent with DLIR for the two observers (intraclass correlation [ICC] = 0.93 vs. 0.96 and 0.95 vs. 0.99). For smaller stones (<3 mm), results were different (ICC = 0.77 vs. 0.86). Conclusion For low-dose abdominopelvic CT, DLIR reconstruction exhibited image quality superior to ASiR-V and FBP as well as an excellent detection of urinary stones.

A feasibility study of realizing low-dose abdominal CT using deep learning image reconstruction algorithm

2021 ◽  
pp. 1-12
Author(s):  
Lu-Lu Li ◽  
Huang Wang ◽  
Jian Song ◽  
Jin Shang ◽  
Xiao-Ying Zhao ◽  
...  
Keyword(s):  
Deep Learning ◽  
Image Reconstruction ◽  
Image Quality ◽  
Radiation Dose ◽  
Low Dose ◽  
Standard Dose ◽  
Image Noise ◽  
Arterial Phase ◽  
Abdominal Ct ◽  
Reconstruction Methods

OBJECTIVES: To explore the feasibility of achieving diagnostic images in low-dose abdominal CT using a Deep Learning Image Reconstruction (DLIR) algorithm. METHODS: Prospectively enrolled 47 patients requiring contrast-enhanced abdominal CT scans. The late-arterial phase scan was added and acquired using lower-dose mode (tube current range, 175–545 mA; 80 kVp for patients with BMI ≤24 kg/m2 and 100 kVp for patients with BMI >  24 kg/m2) and reconstructed with DLIR at medium setting (DLIR-M) and high setting (DLIR-H), ASIR-V at 0% (FBP), 40% and 80% strength. Both the quantitative measurement and qualitative analysis of the five types of reconstruction methods were compared. In addition, radiation dose and image quality between the early-arterial phase ASIR-V images using standard-dose and the late-arterial phase DLIR images using low-dose were compared. RESULTS: For the late-arterial phase, all five reconstructions had similar CT value (P >  0.05). DLIR-H, DLIR-M and ASIR-V80% images significantly reduced the image noise and improved the image contrast noise ratio, compared with the standard ASIR-V40% images (P <  0.05). ASIR-V80% images had undesirable image characteristics with obvious “waxy” artifacts, while DLIR-H images maintained high spatial resolution and had the highest subjective image quality. Compared with the early-arterial scans, the late-arterial phase scans significantly reduced the radiation dose (P <  0.05), while the DLIR-H images exhibited lower image noise and good display of the specific image details of lesions. CONCLUSIONS: DLIR algorithm improves image quality under low-dose scan condition and may be used to reduce the radiation dose without adversely affecting the image quality.

scholarly journals Superior objective and subjective image quality of deep learning reconstruction for low-dose abdominal CT imaging in comparison with model-based iterative reconstruction and filtered back projection

2021 ◽  
Vol 94 (1123) ◽  
pp. 20201357
Author(s):  
Akio Tamura ◽  
Eisuke Mukaida ◽  
Yoshitaka Ota ◽  
Masayoshi Kamata ◽  
Shun Abe ◽  
...  
Keyword(s):  
Deep Learning ◽  
Image Quality ◽  
Abdominal Aorta ◽  
Low Dose ◽  
Image Noise ◽  
Obese Patients ◽  
Back Projection ◽  
Hepatic Parenchyma ◽  
Abdominal Ct

Objective: This study aimed to conduct objective and subjective comparisons of image quality among abdominal computed tomography (CT) reconstructions with deep learning reconstruction (DLR) algorithms, model-based iterative reconstruction (MBIR), and filtered back projection (FBP). Methods: Datasets from consecutive patients who underwent low-dose liver CT were retrospectively identified. Images were reconstructed using DLR, MBIR, and FBP. Mean image noise and contrast-to-noise ratio (CNR) were calculated, and noise, artifacts, sharpness, and overall image quality were subjectively assessed. Dunnett’s test was used for statistical comparisons. Results: Ninety patients (67 ± 12.7 years; 63 males; mean body mass index [BMI], 25.5 kg/m2) were included. The mean noise in the abdominal aorta and hepatic parenchyma of DLR was lower than that in FBP and MBIR (p < .001). For FBP and MBIR, image noise was significantly higher for obese patients than for those with normal BMI. The CNR for the abdominal aorta and hepatic parenchyma was higher for DLR than for FBP and MBIR (p < .001). MBIR images were subjectively rated as superior to FBP images in terms of noise, artifacts, sharpness, and overall quality (p < .001). DLR images were rated as superior to MBIR images in terms of noise (p < .001) and overall quality (p = .03). Conclusions: Based on objective and subjective comparisons, the image quality of DLR was found to be superior to that of MBIR and FBP on low-dose abdominal CT. DLR was the only method for which image noise was not higher for obese patients than for those with a normal BMI. Advances in knowledge: This study provides previously unavailable information on the properties of DLR systems and their clinical utility.

scholarly journals Radiation Dose Reduction in Preprocedural CT Imaging for TAVI/TAVR Using a Novel 3-Phase Protocol: A Single Institution’s Experience

2020 ◽  
Vol 192 (12) ◽  
pp. 1174-1182 ◽  
Author(s):  
Seyd Shnayien ◽  
Keno Kyrill Bressem ◽  
Nick Lasse Beetz ◽  
Patrick Asbach ◽  
Bernd Hamm ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Image Quality ◽  
Aortic Valve ◽  
Radiation Dose ◽  
Phase Variable ◽  
The Novel ◽  
Subjective Image Quality ◽  
Transcatheter Aortic Valve ◽  
Noise Ratio ◽  
Spiral Scan

Purpose To retrospectively investigate the effectiveness of a novel 3-phase protocol for computed tomography (CT) before transcatheter aortic valve implantation/transcatheter aortic valve replacement (TAVI/TAVR) in terms of radiation dose and image quality. Materials and Methods A total of 107 nonrandomized patients (81 ± 7.4 years) scheduled for TAVI/TAVR underwent preprocedural CT on an 80-row CT scanner. 55 patients underwent a combined ECG-synchronized spiral scan of the chest and non-ECG-synchronized spiral scan of the abdomen/pelvis as recommended by the Society of Cardiovascular Computed Tomography (SCCT). 52 patients underwent an updated 3-phase variable helical pitch (vHP3) protocol combining a non-ECG-synchronized spiral scan of the upper thoracic aperture, followed by a prospective ECG-synchronized spiral scan of the heart, and a non-ECG-synchronized abdominal/pelvic spiral scan. The radiation dose was determined from an automatically generated protocol based on the CT dose index (CTDI). Objective image quality in terms of vessel attenuation and image noise was measured, and the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were calculated. Subjective image quality was evaluated using a 4-point scale and compared for interrater agreement using Cohen’s weighted kappa coefficient (κw). All data were compared and statistically analyzed. Results Use of the novel 3-phase vHP3 protocol reduced the dose-length product (DLP) from 1256.58 ± 619.05 mGy*cm to 790.90 ± 238.15 mGy*cm, reducing the effective dose (E) from 21.36 ± 10.52 mSv to 13.44 ± 4.05 mSv and size-specific dose estimates (SSDE) from 20.85 ± 7.29 mGy to 13.84 ± 2.94 mGy (p < 0.001). There were no significant differences in objective and subjective image quality between the two protocols and between the two readers. Conclusion The novel 3-phase vHP3 protocol significantly reduces the radiation dose of preprocedural TAVI/TAVR CT without a loss of image quality. Key Points:  Citation Format

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