Ultra-low dose chest CT with silver filter and deep learning reconstruction significantly reduces radiation dose and retains quantitative information in the investigation and monitoring of lymphangioleiomyomatosis (LAM).

PURPOSE: Frequent CT scans to quantify lung involvement in cystic lung disease increases radiation exposure. Beam shaping energy filters can optimize imaging properties at lower radiation dosages. The aim of this study is to investigate whether use of SilverBeam filter and deep learning reconstruction algorithm allows for reduced radiation dose chest CT scanning in patients with lymphangioleiomyomatosis (LAM). MATERIAL AND METHODS: In a single-center prospective study, 60 consecutive patients with LAM underwent chest CT at standard and ultra-low radiation doses. Standard dose scan was performed with standard copper filter and ultra-low dose scan was performed with SilverBeam filter. Scans were reconstructed using a soft tissue kernel with deep learning reconstruction (AiCE) technique and using a soft tissue kernel with hybrid iterative reconstruction (AIDR3D). Cyst scores were quantified by semi-automated software. Signal-to-noise ratio (SNR) was calculated for each reconstruction. Data were analyzed by linear correlation, paired t-test, and Bland-Altman plots. RESULTS: Patients averaged 49.4 years and 100% were female with mean BMI 26.6 ± 6.1 kg/m2. Cyst score measured by AiCE reconstruction with SilverBeam filter correlated well with that of AIDR3D reconstruction with standard filter, with a 1.5% difference, and allowed for an 85.5% median radiation dosage reduction (0.33 mSv vs. 2.27 mSv, respectively, p < 0.001). Compared to standard filter with AIDR3D, SNR for SilverBeam AiCE images was slightly lower (3.2 vs. 3.1, respectively, p = 0.005). CONCLUSION: SilverBeam filter with deep learning reconstruction reduces radiation dosage of chest CT, while maintaining accuracy of cyst quantification as well as image quality in cystic lung disease. CLINICAL RELEVANCE STATEMENT: Radiation dosage from chest CT can be significantly reduced without sacrificing image quality by using silver filter in combination with a deep learning reconstructive algorithm. KEY POINTS: • Deep learning reconstruction in chest CT had no significant effect on cyst quantification when compared to conventional hybrid iterative reconstruction. • SilverBeam filter reduced radiation dosage by 85.5% compared to standard dose chest CT. • SilverBeam filter in coordination with deep learning reconstruction maintained image quality and diagnostic accuracy for cyst quantification when compared to standard dose CT with hybrid iterative reconstruction.

Prototype Ultrahigh-Resolution Computed Tomography for Chest Imaging: Initial Human Experience.

OBJECTIVE: The objective of this study was to evaluate a prototype, ultrahigh-resolution computed tomography offering higher reconstruction matrix (1024 × 1024) and spatial resolution (0.15 mm) for chest imaging. METHODS: Higher (1024) matrix reconstruction enabled by ultrahigh-resolution computed tomography scanner (128-detector rows; detector width, 0.25 mm; spatial resolution, 0.15 mm) was compared with conventional (512) reconstruction with image quality grading on a Likert scale (1, excellent; 5, nondiagnostic) for image noise, artifacts, contrast, small detail, lesion conspicuity, image sharpness, and diagnostic confidence. Image noise and signal-to-noise ratio were quantified. RESULTS: Diagnostic image quality was achieved for all scans on 101 patients. The 1024 reconstruction demonstrated increased image noise (20.2 ± 4.0 vs 17.2 ± 3.8, P < 0.001) and a worse noise rating (1.98 ± 0.63 vs 1.75 ± 0.61, P < 0.001) but performed significantly better than conventional 512 matrix with fewer artifacts (1.37 ± 0.43 vs 1.50 ± 0.48, P < 0.001), better contrast (1.50 ± 0.56 vs 1.62 ± 0.57, P < 0.001), small detail detection (1.06 ± 0.19 vs 2.02 ± 0.22, P < 0.001), lesion conspicuity (1.08 ± 0.23 vs 2.02 ± 0.24, P < 0.001), sharpness (1.09 ± 0.24 vs 2.02 ± 0.28, P < 0.001), and overall diagnostic confidence (1.09 ± 0.25 vs 1.18 ± 0.34, P < 0.001). CONCLUSIONS: Ultrahigh-resolution computed tomography enabled a higher reconstruction matrix and improved image quality compared with conventional matrix reconstruction, with a minor increase in noise.

3D Landmark scout imaging accurately assesses presence and extent of coronary calcification with lower radiation exposure.

BACKGROUND: Cardiac CT for coronary artery calcium (CAC) scoring exposes patients to 1 â€‹mSv of radiation. A new CT scout method utilizing ultra-low dose CT (3D Landmark) offers tomographic cross-sectional imaging, which provides axial images from which CAC can be estimated. The purpose of our study is to analyze the association between estimated CAC burden on 3D Landmark scout imaging vs dedicated ECG-gated CACS. METHODS: Consecutive patients over a 9-month period undergoing non-contrast ECG-gated CACS planned with 3D Landmark scout imaging were included. Extent of CAC on 3D Landmark scout imaging was scored from 0 to 3 (none, mild, moderate, severe). Agatston CACS was converted to an ordinal score from 0 to 3, corresponding to absent (0), mild (1-99), moderate (100-400), or severe (>400). Fischer's exact test, weighted kappa coefficient, and paired t-tests were used for analysis. RESULTS: Of 150 patients, 51.3% were female with mean age 49.0 â€‹± â€‹16.8 and BMI 28.6 â€‹± â€‹12.3. Sensitivity of 3D Landmark in identifying calcium was 96.2%, with specificity of 100%. There was strong interrater agreement between 3D Landmark calcium scoring and CACS, with weighted kappa coefficient 0.97 â€‹± â€‹0.01(CI 0.95-0.99). Radiation dose-length-product was significantly lower for 3D Landmark imaging vs. dedicated ECG-gated CACS (9.7 â€‹± â€‹3.6 vs 43.8 â€‹± â€‹26.4 â€‹mGy â€‹cm, p â€‹< â€‹0.001) despite longer scan length (465.0 â€‹± â€‹160.8 vs 123.0 â€‹± â€‹12.7 â€‹mm, respectively). CONCLUSION: Estimated coronary artery calcium on 3D Landmark scout images correlates strongly with Agatston CACS, demonstrating utility in assessing cardiovascular risk without introducing additional radiation or costs.

Reduced dose helical CT scout imaging on next generation wide volume CT system decreases scan length and overall radiation exposure.

Purpose: Traditional CT acquisition planning is based on scout projection images from planar anterior-posterior and lateral projections where the radiographer estimates organ locations. Alternatively, a new scout method utilizing ultra-low dose helical CT (3D Landmark Scan) offers cross-sectional imaging to identify anatomic structures in conjunction with artificial intelligence based Anatomic Landmark Detection (ALD) for automatic CT acquisition planning. The purpose of this study is to quantify changes in scan length and radiation dose of CT examinations planned using 3D Landmark Scan and ALD and performed on next generation wide volume CT versus examinations planned using traditional scout methods. We additionally aim to quantify changes in radiation dose reduction of scans planned with 3D Landmark Scan and performed on next generation wide volume CT. Methods: Single-center retrospective analysis of consecutive patients with prior CT scan of the same organ who underwent clinical CT using 3D Landmark Scan and automatic scan planning. Acquisition length and dose-length-product (DLP) were collected. Data was analyzed by paired t-tests. Results: 104 total CT examinations (48.1 % chest, 15.4 % abdomen, 36.5 % chest/abdomen/pelvis) on 61 individual consecutive patients at a single center were retrospectively analyzed. 79.8 % of scans using 3D Landmark Scan had reduction in acquisition length compared to the respective prior acquisition. Median acquisition length using 3D Landmark Scan was 26.7 mm shorter than that using traditional scout methods (p < 0.001) with a 23.3 % median total radiation dose reduction (245.6 (IQR 150.0-400.8) mGy cm vs 320.3 (IQR 184.1-547.9) mGy cm). CT dose index similarly was overall decreased for scans planned with 3D Landmark and ALD and performed on next generation CT versus traditional methods (4.85 (IQR 3.8-7) mGy vs. 6.70 (IQR 4.43-9.18) mGy, respectively, p < 0.001). Conclusion: Scout imaging using reduced dose 3D Landmark Scan images and Anatomic Landmark Detection reduces acquisition range in chest, abdomen, and chest/abdomen/pelvis CT scans. This technology, in combination with next generation wide volume CT reduces total radiation dose.

Performance of single-energy metal artifact reduction in cardiac computed tomography: A clinical and phantom study.

BACKGROUND: To investigate the performance of a reconstruction algorithm, single-energy metal artifact reduction (SEMAR), against standard reconstruction in cardiac computed tomography (CT) studies of patients with implanted metal and in a defibrillator lead phantom. METHODS: From a retrospective, cross-sectional clinical study with institutional review board approval of 118 patients with implanted metal, 122 cardiac CT studies from November 2009 to August 2016 performed on a 320-detector row scanner with standard and SEMAR reconstructions were included. The maximum beam hardening artifact radius, artifact attenuation variation surrounding the implanted metal, and image quality on a 4-point scale (1-no/minimal artifact to 4-severe artifact) were assessed for each reconstruction. A defibrillator lead phantom study was performed at different tube potentials and currents with both reconstruction methods. Maximum beam hardening artifact radius and average artifact attenuation variation were measured. RESULTS: In the clinical study, SEMAR markedly reduced the maximum beam hardening artifact radius by 77% (standard: 14.8 mm [IQR 9.7-22.2] vs. SEMAR: 3.4 mm [IQR 2.2-7.1], p < 0.0001) and artifact attenuation variation by 51% (standard: 130.0 HU [IQR 75.9-184.4] vs. SEMAR: 64.3 HU [IQR 48.2-89.2], p < 0.0001). Image quality improved with SEMAR (standard: 3 [IQR 2-3.5] vs. SEMAR: 2 [IQR 1-2.5], p < 0.0001). The defibrillator lead phantom study confirmed these results across varying tube potentials and currents. CONCLUSIONS: SEMAR reconstruction achieved superior image quality and markedly reduced maximum beam hardening artifact radius and artifact attenuation variation compared to standard reconstruction in 122 clinical cardiac CT studies of patients with implanted metal and in a defibrillator lead phantom study.

Reduced radiation dose with model based iterative reconstruction coronary artery calcium scoring.

Assessing coronary artery calcium (CAC) is a valuable tool for individualizing cardiac risk assessment. In CAC scanning, this technical report assesses the use of a true model-based iterative reconstruction algorithm using forward projected model-based iterative reconstruction ("FIRST") and assess whether FIRST allows for reduced radiation dose CAC scanning on 320-detector row computed tomography (320-CT). Here, 100 consecutive patients prospectively underwent reduced and standard dose scans. For the patients (59 ± 9 years, 61% male) stratified by Agatston categories 0, 1-10, 11-100, 101-400,> 400, agreement between reduced dose with FIRST versus standard dose with FBP was excellent at 81% (95% CI: 73-88%) with kappa 0.74 (95% CI: 0.64-0.85). Median radiation exposure was 75% lower for reduced (0.35 mSv) versus standard dose (1.37 mSv) scans. In conclusion, agreement was excellent for reduced dose with FIRST and standard dose with FBP in 320-detector row CT CAC imaging in well-established categories of cardiovascular risk. These methods make it possible to reduce radiation exposure by 75%.

Chest CT Scan at Radiation Dose of a Posteroanterior and Lateral Chest Radiograph Series: A Proof of Principle in Lymphangioleiomyomatosis.

BACKGROUND: Given the rising utilization of medical imaging and the risks of radiation, there is increased interest in reducing radiation exposure. The objective of this study was to evaluate, as a proof of principle, CT scans performed at radiation doses equivalent to that of a posteroanterior and lateral chest radiograph series in the cystic lung disease lymphangioleiomyomatosis (LAM). METHODS: From November 2016 to May 2018, 105 consecutive subjects with LAM received chest CT scans at standard and ultra-low radiation doses. Standard and ultra-low-dose images, respectively, were reconstructed with routine iterative and newer model-based iterative reconstruction. LAM severity can be quantified as cyst score (percentage of lung occupied by cysts), an ideal benchmark for validating CT scans performed at a reduced dose compared with a standard dose. Cyst scores were quantified using semi-automated software and evaluated by linear correlation and Bland-Altman analysis. RESULTS: Overall, ultra-low-dose CT scans represented a 96% dose reduction, with a median dose equivalent to 1 vs 22 posteroanterior and lateral chest radiograph series (0.14 mSv; 5th-95th percentile, 0.10-0.20 vs standard dose 3.4 mSv; 5th-95th percentile, 1.5-7.4; P < .0001). The mean difference in cyst scores between ultra-low- and standard-dose CT scans was 1.1% ± 2.0%, with a relative difference in cyst score of 11%. Linear correlation coefficient was excellent at 0.97 (P < .0001). CONCLUSIONS: In LAM chest CT scan at substantial radiation reduction to doses equivalent to that of a posteroanterior and lateral chest radiograph series provides cyst score quantification similar to that of standard-dose CT scan. TRIAL REGISTRY: ClinicalTrials.gov; Nos.: NCT00001465 and NCT00001532; URL: www.clinicaltrials.gov.