Computed Tomography 2.0

Lell, Michael; Kachelrieß, Marc

doi:10.1097/rli.0000000000000995

Cited by 20 publications

(3 citation statements)

References 151 publications

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“…Drawing from clinical experiences during the COVID-19 pandemic, however, the detection and characterization of subtle findings in different forms of lung disease, such as ground glass opacities, pulmonary nodules, airway wall thickening, or interstitial pneumonia patterns, might benefit from applying the full FOV UHR mode without dose penalty 1,6,16 . Particularly, with up to 30% of the patients undergoing multiple lung CT examinations within a month, 3 the dose-saving potential of the small pixel effect in ultra-low dose examinations should not be underestimated 29 …”

Section: Discussionmentioning

confidence: 99%

Investigating the Small Pixel Effect in Ultra-High Resolution Photon-Counting CT of the Lung

et al. 2024

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Objectives The aim of this study was to investigate potential benefits of ultra-high resolution (UHR) over standard resolution scan mode in ultra-low dose photon-counting detector CT (PCD-CT) of the lung. Materials and Methods Six cadaveric specimens were examined with 5 dose settings using tin prefiltration, each in UHR (120 × 0.2 mm) and standard mode (144 × 0.4 mm), on a first-generation PCD-CT scanner. Image quality was evaluated quantitatively by noise comparisons in the trachea and both main bronchi. In addition, 16 readers (14 radiologists and 2 internal medicine physicians) independently completed a browser-based pairwise forced-choice comparison task for assessment of subjective image quality. The Kendall rank coefficient (W) was calculated to assess interrater agreement, and Pearson's correlation coefficient (r) was used to analyze the relationship between noise measurements and image quality rankings. Results Across all dose levels, image noise in UHR mode was lower than in standard mode for scan protocols matched by CTDIvol (P < 0.001). UHR examinations exhibited noise levels comparable to the next higher dose setting in standard mode (P ≥ 0.275). Subjective ranking of protocols based on 5760 pairwise tests showed high interrater agreement (W = 0.99; P ≤ 0.001) with UHR images being preferred by readers in the majority of comparisons. Irrespective of scan mode, a substantial indirect correlation was observed between image noise and subjective image quality ranking (r = −0.97; P ≤ 0.001). Conclusions In PCD-CT of the lung, UHR scan mode reduces image noise considerably over standard resolution acquisition. Originating from the smaller detector element size in fan direction, the small pixel effect allows for superior image quality in ultra-low dose examinations with considerable potential for radiation dose reduction.

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Section: Discussionmentioning

confidence: 99%

Investigating the Small Pixel Effect in Ultra-High Resolution Photon-Counting CT of the Lung

et al. 2024

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“…Later, achieving detailed visualization became a primary focus. Nowadays, there is access to various state-of-the-art scanners, but the introduction of the latest photon-counting scanners has reinvigorated the quest for further advancements without necessarily increasing radiation, as seen with conventional scanners [4]. This technology holds potential for new and exciting clinical applications [5].…”

Section: Introductionmentioning

confidence: 99%

Photon Counting Computed Tomography for Accurate Cribriform Plate (Lamina Cribrosa) Imaging in Adult Patients

Klempka,

Ackermann,

Clausen

et al. 2024

Tomography

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Detailed visualization of the cribriform plate is challenging due to its intricate structure. This study investigates how computed tomography (CT) with a novel photon counting (PC) detector enhance cribriform plate visualization compared to traditionally used energy-integrated detectors in patients. A total of 40 patients were included in a retrospective analysis, with half of them undergoing PC CT (Naeotom Alpha Siemens Healthineers, Forchheim, Germany) and the other half undergoing CT scans using an energy-integrated detector (Somatom Sensation 64, Siemens, Forchheim, Germany) in which the cribriform plate was visualized with a temporal bone protocol. Both groups of scans were evaluated for signal-to-noise ratio, radiation dose, the imaging quality of the whole scan overall, and, separately, the cribriform plate and the clarity of volume rendering reconstructions. Two independent observers conducted a qualitative analysis using a Likert scale. The results consistently demonstrated excellent imaging of the cribriform plate with the PC CT scanner, surpassing traditional technology. The visualization provided by PC CT allowed for precise anatomical assessment of the cribriform plate on multiplanar reconstructions and volume rendering imaging with reduced radiation dose (by approximately 50% per slice) and higher signal-to-noise ratio (by approximately 75%). In conclusion, photon-counting technology provides the possibility of better imaging of the cribriform plate in adult patients. This enhanced imaging could be utilized in skull base-associated pathologies, such as cerebrospinal fluid leaks, to visualize them more reliably for precise treatment.

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“…tic tool in daily clinical practice, 1,2 and advances in the technology are ongoing. 3 A drawback of CT is the use of ionizing radiation, exposure to which may become high, in particular when accumulating from multiple scans. [4][5][6] Radiation dose optimization is necessary and even mandatory: radiation exposure per CT scan needs to be reduced while maintaining sufficient diagnostic image quality (IQ).…”

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confidence: 99%

A New Algorithm for Automatically Calculating Noise, Spatial Resolution, and Contrast Image Quality Metrics

et al. 2023

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ObjectivesThe aims of this study were to develop a proof-of-concept computer algorithm to automatically determine noise, spatial resolution, and contrast-related image quality (IQ) metrics in abdominal portal venous phase computed tomography (CT) imaging and to assess agreement between resulting objective IQ metrics and subjective radiologist IQ ratings.Materials and MethodsAn algorithm was developed to calculate noise, spatial resolution, and contrast IQ parameters. The algorithm was subsequently used on 2 datasets of anthropomorphic phantom CT scans, acquired on 2 different scanners (n = 57 each), and on 1 dataset of patient abdominal CT scans (n = 510). These datasets include a range of high to low IQ: in the phantom dataset, this was achieved through varying scanner settings (tube voltage, tube current, reconstruction algorithm); in the patient dataset, lower IQ images were obtained by reconstructing 30 consecutive portal venous phase scans as if they had been acquired at lower mAs. Five noise, 1 spatial, and 13 contrast parameters were computed for the phantom datasets; for the patient dataset, 5 noise, 1 spatial, and 18 contrast parameters were computed. Subjective IQ rating was done using a 5-point Likert scale: 2 radiologists rated a single phantom dataset each, and another 2 radiologists rated the patient dataset in consensus. General agreement between IQ metrics and subjective IQ scores was assessed using Pearson correlation analysis. Likert scores were grouped into 2 categories, “insufficient” (scores 1–2) and “sufficient” (scores 3–5), and differences in computed IQ metrics between these categories were assessed using the Mann-Whitney U test.ResultsThe algorithm was able to automatically calculate all IQ metrics for 100% of the included scans. Significant correlations with subjective radiologist ratings were found for 4 of 5 noise (R2 range = 0.55–0.70), 1 of 1 spatial resolution (R2 = 0.21 and 0.26), and 10 of 13 contrast (R2 range = 0.11–0.73) parameters in the phantom datasets and for 4 of 5 noise (R2 range = 0.019–0.096), 1 of 1 spatial resolution (R2 = 0.11), and 16 of 18 contrast (R2 range = 0.008–0.116) parameters in the patient dataset. Computed metrics that significantly differed between “insufficient” and “sufficient” categories were 4 of 5 noise, 1 of 1 spatial resolution, 9 and 10 of 13 contrast parameters for phantom the datasets and 3 of 5 noise, 1 of 1 spatial resolution, and 10 of 18 contrast parameters for the patient dataset.ConclusionThe developed algorithm was able to successfully calculate objective noise, spatial resolution, and contrast IQ metrics of both phantom and clinical abdominal CT scans. Furthermore, multiple calculated IQ metrics of all 3 categories were in agreement with subjective radiologist IQ ratings and significantly differed between “insufficient” and “sufficient” IQ scans. These results demonstrate the feasibility and potential of algorithm-determined objective IQ. Such an algorithm should be applicable to any scan and may help in optimization and quality control...

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Computed Tomography 2.0

Cited by 20 publications

References 151 publications

Investigating the Small Pixel Effect in Ultra-High Resolution Photon-Counting CT of the Lung

Investigating the Small Pixel Effect in Ultra-High Resolution Photon-Counting CT of the Lung

Photon Counting Computed Tomography for Accurate Cribriform Plate (Lamina Cribrosa) Imaging in Adult Patients

A New Algorithm for Automatically Calculating Noise, Spatial Resolution, and Contrast Image Quality Metrics

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