Pelvic bone CT: can tin-filtered ultra-low-dose CT and virtual radiographs be used as alternative for standard CT and digital radiographs?

Abstract Objectives To compare ultra-low-dose CT (ULD-CT) of the osseous pelvis with tin filtration to standard clinical CT (CT), and to assess the quality of computed virtual pelvic radiographs (VRs). Methods CT protocols were optimized in a phantom and three pelvic cadavers. Thirty prospectively included patients received both standard CT (automated tube voltage selection and current modulation) and tin-filtered ULD-CT of the pelvis (Sn140kV/50mAs). VRs of ULD-CT data were computed using an adapted cone beam–based projection algorithm and were compared to digital radiographs (DRs) of the pelvis. CT and DR dose parameters and quantitative and qualitative measures (1 = worst, 4 = best) were compared. CT and ULD-CT were assessed for osseous pathologies. Results Dose reduction of ULD-CT was 84% compared to CT, with a median effective dose of 0.38 mSv (quartile 1–3: 0.37–0.4 mSv) versus 2.31 mSv (1.82–3.58 mSv; p < .001), respectively. Mean dose of DR was 0.37 mSv (± 0.14 mSv). The median signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of bone were significantly higher for CT (64.3 and 21.5, respectively) compared to ULD-CT (50.4 and 18.8; p ≤ .01), while ULD-CT was significantly more dose efficient (figure of merit (FOM) 927.6) than CT (FOM 167.6; p < .001). Both CT and ULD-CT were of good image quality with excellent depiction of anatomy, with a median score of 4 (4–4) for both methods (p = .1). Agreement was perfect between both methods regarding the prevalence of assessed osseous pathologies (p > .99). VRs were successfully calculated and were equivalent to DRs. Conclusion Tin-filtered ULD-CT of the pelvis at a dose equivalent to standard radiographs is adequate for assessing bone anatomy and osseous pathologies and had a markedly superior dose efficiency than standard CT. Key Points • Ultra-low-dose pelvic CT with tin filtration (0.38 mSv) can be performed at a dose of digital radiographs (0.37 mSv), with a dose reduction of 84% compared to standard CT (2.31 mSv). • Tin-filtered ultra-low-dose CT had lower SNR and CNR and higher image noise than standard CT, but showed clear depiction of anatomy and accurate detection of osseous pathologies. • Virtual pelvic radiographs were successfully calculated from ultra-low-dose CT data and were equivalent to digital radiographs.

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Ultra-Low-Dose CT of the Thorax Using Iterative Reconstruction: Evaluation of Image Quality and Radiation Dose Reduction

American Journal of Roentgenology ◽

10.2214/ajr.14.13629 ◽

2015 ◽

Vol 204 (6) ◽

pp. 1197-1202 ◽

Cited By ~ 61

Author(s):

Yookyung Kim ◽

Yoon Kyung Kim ◽

Bo Eun Lee ◽

Seok Jeong Lee ◽

Yon Ju Ryu ◽

...

Keyword(s):

Image Quality ◽

Radiation Dose ◽

Dose Reduction ◽

Iterative Reconstruction ◽

Low Dose ◽

Radiation Dose Reduction ◽

Low Dose Ct

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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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Lesion Detection Performance: Comparative Analysis of Low-Dose CT Data of the Chest on Two Hybrid Imaging Systems

Journal of Nuclear Medicine Technology ◽

10.2967/jnmt.114.147447 ◽

2015 ◽

Vol 43 (1) ◽

pp. 47-52 ◽

Cited By ~ 1

Author(s):

M. Jessop ◽

J. D. Thompson ◽

J. Coward ◽

A. Sanderud ◽

J. Jorge ◽

...

Keyword(s):

Comparative Analysis ◽

Low Dose ◽

Hybrid Imaging ◽

Detection Performance ◽

Lesion Detection ◽

Imaging Systems ◽

Low Dose Ct ◽

Ct Data ◽

Two Hybrid

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Preliminary study of dose reduction and image quality of adult pelvic low-dose CT scan with adaptive statistical iterative reconstruction

Acta Radiologica ◽

10.1177/0284185114552215 ◽

2015 ◽

Vol 56 (10) ◽

pp. 1222-1229 ◽

Cited By ~ 1

Author(s):

Wei Li ◽

Cheng-Qi Zhang ◽

Ai-Yin Li ◽

Kai Deng ◽

Hao Shi

Keyword(s):

Image Quality ◽

Ct Scan ◽

Dose Reduction ◽

Iterative Reconstruction ◽

Low Dose ◽

Adaptive Statistical Iterative Reconstruction ◽

Low Dose Ct ◽

Statistical Iterative Reconstruction ◽

Preliminary Study

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Non-Positive Corrections and Variance Models for Iterative Post-Log Reconstruction of Extremely Low-Dose CT Data

Journal of the Korean Physical Society ◽

10.3938/jkps.77.177 ◽

2020 ◽

Vol 77 (2) ◽

pp. 177-185

Author(s):

Soo Mee Kim ◽

Tzu-Cheng Lee ◽

Paul E. Kinahan

Keyword(s):

Low Dose ◽

Low Dose Ct ◽

Ct Data

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Ultra-low-dose CT for extremities in an acute setting: initial experience with 203 subjects

Skeletal Radiology ◽

10.1007/s00256-019-03309-7 ◽

2019 ◽

Vol 49 (4) ◽

pp. 531-539 ◽

Cited By ~ 6

Author(s):

Zlatan Alagic ◽

Robert Bujila ◽

Anders Enocson ◽

Subhash Srivastava ◽

Seppo K. Koskinen

Keyword(s):

Radiation Dose ◽

Digital Radiography ◽

Preliminary Report ◽

Low Dose ◽

Fracture Detection ◽

Acute Setting ◽

Low Dose Ct ◽

Digital Radiographs ◽

Examination Time ◽

The Mean

Abstract Objective The purpose of this study was to assess if ultra-low-dose CT is a useful clinical alternative to digital radiographs in the evaluation of acute wrist and ankle fractures. Materials and methods An ultra-low-dose protocol was designed on a 256-slice multi-detector CT. Patients from the emergency department were evaluated prospectively. After initial digital radiographs, an ultra-low-dose CT was performed. Two readers independently analyzed the images. Also, the radiation dose, examination time, and time to preliminary report was compared between digital radiographs and CT. Results In 207 extremities, digital radiography and ultra-low-dose CT detected 73 and 109 fractures, respectively (p < 0.001). The odds ratio for fracture detection with ultra-low-dose CT vs. digital radiography was 2.0 (95% CI, 1.4–3.0). CT detected additional fracture-related findings in 33 cases (15.9%) and confirmed or ruled out suspected fractures in 19 cases (9.2%). The mean effective dose was comparable between ultra-low-dose CT and digital radiography (0.59 ± 0.33 μSv, 95% CI 0.47–0.59 vs. 0.53 ± 0.43 μSv, 95% CI 0.54–0.64). The mean combined examination time plus time to preliminary report was shorter for ultra-low-dose CT compared to digital radiography (7.6 ± 2.5 min, 95% CI 7.1–8.1 vs. 9.8 ± 4.7 min, 95% CI 8.8–10.7) (p = 0.002). The recommended treatment changed in 34 (16.4%) extremities. Conclusions Ultra-low-dose CT is a useful alternative to digital radiography for imaging the peripheral skeleton in the acute setting as it detects significantly more fractures and provides additional clinically important information, at a comparable radiation dose. It also provides faster combined examination and reporting times.

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Machine Learning Facilitates Hotspot Classification in PSMA-PET/CT with Nuclear Medicine Specialist Accuracy

Diagnostics ◽

10.3390/diagnostics10090622 ◽

2020 ◽

Vol 10 (9) ◽

pp. 622

Author(s):

Sobhan Moazemi ◽

Zain Khurshid ◽

Annette Erle ◽

Susanne Lütje ◽

Markus Essler ◽

...

Keyword(s):

Machine Learning ◽

Positron Emission Tomography ◽

Low Dose ◽

Emission Tomography ◽

Textural Features ◽

Low Dose Ct ◽

Positron Emission ◽

Psma Pet ◽

Pet Ct ◽

Ct Data

Gallium-68 prostate-specific membrane antigen positron emission tomography (68Ga-PSMA-PET) is a highly sensitive method to detect prostate cancer (PC) metastases. Visual discrimination between malignant and physiologic/unspecific tracer accumulation by a nuclear medicine (NM) specialist is essential for image interpretation. In the future, automated machine learning (ML)-based tools will assist physicians in image analysis. The aim of this work was to develop a tool for analysis of 68Ga-PSMA-PET images and to compare its efficacy to that of human readers. Five different ML methods were compared and tested on multiple positron emission tomography/computed tomography (PET/CT) data-sets. Forty textural features extracted from both PET- and low-dose CT data were analyzed. In total, 2419 hotspots from 72 patients were included. Comparing results from human readers to those of ML-based analyses, up to 98% area under the curve (AUC), 94% sensitivity (SE), and 89% specificity (SP) were achieved. Interestingly, textural features assessed in native low-dose CT increased the accuracy significantly. Thus, ML based on 68Ga-PSMA-PET/CT radiomics features can classify hotspots with high precision, comparable to that of experienced NM physicians. Additionally, the superiority of multimodal ML-based analysis considering all PET and low-dose CT features was shown. Morphological features seemed to be of special additional importance even though they were extracted from native low-dose CTs.

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