Threshold-dependent iodine imaging and spectral separation in a whole-body photon-counting CT system

Sawall, Stefan; Klein, Laura; Wehrse, E.; Rotkopf, Lukas T.; Amato, Carlo; Maier, Joscha; Ziener, Christian H.; Heinze, Sarah; Kachelrieß, Marc

doi:10.1007/s00330-021-07786-0

Cited by 9 publications

(8 citation statements)

References 33 publications

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“…Finally, as previously said, the PCD-CT system offers 3 different scan modes that were evaluated in the current study: the HR-mode (a micropixel mode, currently used at 120 kVp and optimized for lung imaging on non–contrast-enhanced CT) and the 2 Quantum modes (Q and Q+). Although the HR-mode is best for lung imaging on noncontrast CT, the latter 2 have their biggest advantages in contrast enhanced CT, because these modes allow for spectral imaging 49–53 . In this current study on non–contrast-enhanced CT, spectral imaging played a minor role.…”

Section: Discussionmentioning

confidence: 69%

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First Performance Evaluation of an Artificial Intelligence-Based Computer-Aided Detection System for Pulmonary Nodule Evaluation in Dual-Source Photon-Counting Detector CT at Different Low-Dose Levels

Jungblut

Blüthgen²,

Polacin³

et al. 2021

Invest Radiol

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Objective: The aim of this study was to evaluate the image quality (IQ) and performance of an artificial intelligence (AI)-based computer-aided detection (CAD) system in photon-counting detector computed tomography (PCD-CT) for pulmonary nodule evaluation at different low-dose levels. Materials and Methods: An anthropomorphic chest-phantom containing 14 pulmonary nodules of different sizes (range, 3-12 mm) was imaged on a PCD-CT and on a conventional energy-integrating detector CT (EID-CT). Scans were performed with each of the 3 vendor-specific scanning modes (QuantumPlus [Q+], Quantum [Q], and High Resolution [HR]) at decreasing matched radiation dose levels (volume computed tomography dose index ranging from 1.79 to 0.31 mGy) by adapting IQ levels from 30 to 5. Image noise was measured manually in the chest wall at 8 different locations. Subjective IQ was evaluated by 2 readers in consensus. Nodule detection and volumetry were performed using a commercially available AI-CAD system. Results: Subjective IQ was superior in PCD-CT compared with EID-CT (P < 0.001), and objective image noise was similar in the Q+ and Q-mode (P > 0.05) and superior in the HR-mode (PCD 55.8 ± 11.7 HU vs EID 74.8 ± 5.4 HU; P = 0.01). High resolution showed the lowest image noise values among PCD modes (P = 0.01). Overall, the AI-CAD system delivered comparable results for lung nodule detection and volumetry between PCD-and dose-matched EID-CT (P = 0.08-1.00), with a mean sensitivity of 95% for PCD-CT and of 86% for dose-matched EID-CT in the lowest evaluated dose level (IQ5). Q+ and Q-mode showed higher false-positive rates than EID-CT at lower-dose levels (IQ10 and IQ5). The HR-mode showed a sensitivity of 100% with a false-positive rate of 1 even at the lowest evaluated dose level (IQ5; CDTI vol , 0.41 mGy). Conclusions: Photon-counting detector CTwas superior to dose-matched EID-CT in subjective IQ while showing comparable to lower objective image noise. Fully automatized AI-aided nodule detection and volumetry are feasible in PCD-CT, but attention has to be paid to false-positive findings.

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Section: Discussionmentioning

confidence: 69%

“…Although the HR-mode is best for lung imaging on noncontrast CT, the latter 2 have their biggest advantages in contrast enhanced CT, because these modes allow for spectral imaging. [49][50][51][52][53] In this current study on non-contrast-enhanced CT, spectral imaging played a minor role.…”

Section: Discussionmentioning

confidence: 84%

First Performance Evaluation of an Artificial Intelligence-Based Computer-Aided Detection System for Pulmonary Nodule Evaluation in Dual-Source Photon-Counting Detector CT at Different Low-Dose Levels

Jungblut

Blüthgen²,

Polacin³

et al. 2021

Invest Radiol

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“…The spectral distortion was included in Equation ( 1) as described by Schlomka et al, 11 and it was used to generate the theoretically expected photon counts for each energy bin and calculate the likelihood. The following fan-beam geometry was considered to mimic an existing PCD-CT system [44][45][46] : The distance from source to center was 59.5 cm, the center to detector 49 cm, and the PCD with 0.9-mm detector pitch. The total number of views was 1000 per 2𝜋.…”

Section: Scan Conditionsmentioning

confidence: 99%

Likelihood‐based bilateral filters for pre‐estimated basis sinograms using photon‐counting CT

Lee

2023

Medical Physics

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Background Noise amplification in material decomposition is an issue for exploiting photon‐counting computed tomography (PCCT). Regularization techniques and neighborhood filters have been widely used, but degraded spatial resolution and bias are concerns. Purpose This paper proposes likelihood‐based bilateral filters that can be applied to pre‐estimated basis sinograms to reduce the noise while minimally affecting spatial resolution and accuracy. Methods The proposed method needs system models (e.g., incident spectrum, detector response) to calculate the likelihood. First, it performs maximum likelihood (ML)‐based estimation in the projection domain to obtain basis sinograms. The estimated basis sinograms suffer from severe noise but are asymptotically unbiased without degrading spatial resolution. Then it calculates the neighborhood likelihoods for a given measurement at the center pixel using the neighborhood estimates and designs the weights based on the distance of likelihoods. It is also analyzed in terms of statistical inference, and then two variations of the filter are introduced: one that requires the significance level instead of the empirical hyperparameter. The other is a measurement‐based filter, which can be applied when accurate estimates are given without the system models. The proposed methods were validated by analyzing the local property of noise and spatial resolution and the global trend of noise and bias using numerical thorax and abdominal phantoms for a two‐material decomposition (water and bone). They were compared to the conventional neighborhood filters and the model‐based iterative reconstruction with an edge‐preserving penalty applied in the basis images. Results The proposed method showed comparable or superior performance for the local and global properties to conventional methods in many cases. The thorax phantom: The full width at half maximum (FWHM) decreased by −2%–31% (−2 indicates that it increased by 2% compared to the best performance from conventional methods), and the global bias was reduced by 2%–19% compared to other methods for similar noise levels (local: 51% of the ML, global: 49%) in the water basis image. The FWHM decreased by 8%–31%, and the global bias was reduced by 9%–44% for similar noise levels (local: 44% of the ML, global: 36%) in the CT image at 65 keV. The abdominal phantom: The FWHM decreased by 10%–32%, and the global bias was reduced by 3%–35% compared to other methods for similar noise levels (local: 66% of the ML, global: 67%) in the water basis image. The FWHM decreased by up to −11%–47%, and the global bias was reduced by 13%–35% for similar noise levels (local: 71% of the ML, global: 70%) in the CT image at 60 keV. Conclusions This paper introduced the likelihood‐based bilateral filters as a post‐processing method applied to the ML‐based estimates of basis sinograms. The proposed filters effectively reduced the noise in the basis images and the synthesized monochromatic CT images. It showed the potential of using likelihood‐based filters ...

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“…This study demonstrated that PCD technology produces higher‐quality images at lower doses, but it was not quantitative in the sense that VMI levels were not compared. Liu et al 28 . provided a quantitative evaluation of multiple VMI levels between DE‐CT and PC‐CT Siemens scanners at low doses, reporting improved accuracy in a large phantom and a significant reduction in electronic background noise.…”

Section: Introductionmentioning

confidence: 99%

Quantitative performance of photon‐counting CT at low dose: Virtual monochromatic imaging and iodine quantification

et al. 2023

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BackgroundQuantitative imaging techniques, such as virtual monochromatic imaging (VMI) and iodine quantification (IQ), have proven valuable diagnostic methods in several specific clinical tasks such as tumor and tissue differentiation. Recently, a new generation of computed tomography (CT) scanners equipped with photon‐counting detectors (PCD) has reached clinical status.PurposeThis work aimed to investigate the performance of a new photon‐counting CT (PC‐CT) in low‐dose quantitative imaging tasks, comparing it to an earlier generation CT scanner with an energy‐integrating detector dual‐energy CT (DE‐CT). The accuracy and precision of the quantification across size, dose, material types (including low and high iodine concentrations), displacement from iso‐center, and solvent (tissue background) composition were explored.MethodsQuantitative analysis was performed on two clinical scanners, Siemens SOMATOM Force and NAEOTOM Alpha using a multi‐energy phantom with plastic inserts mimicking different iodine concentrations and tissue types. The tube configurations in the dual‐energy scanner were 80/150Sn kVp and 100/150Sn kVp, while for PC‐CT both tube voltages were set to either 120 or 140 kVp with photon‐counting energy thresholds set at 20/65 or 20/70 keV. The statistical significance of patient‐related parameters in quantitative measurements was examined using ANOVA and pairwise comparison with the posthoc Tukey honest significance test. Scanner bias was assessed in both quantitative tasks for relevant patient‐specific parameters.ResultsThe accuracy of IQ and VMI in the PC‐CT was comparable between standard and low radiation doses (p < 0.01). The patient size and tissue type significantly affect the accuracy of both quantitative imaging tasks in both scanners. The PC‐CT scanner outperforms the DE‐CT scanner in the IQ task in all cases. Iodine quantification bias in the PC‐CT (−0.9 ± 0.15 mg/mL) at low doses in our study was comparable to that of DE‐CT (range ‐2.6 to 1.5 mg/mL, published elsewhere) at a 1.7× higher dose, but the dose reduction severely biased DE‐CT (4.72 ± 0.22 mg/mL). The accuracy in Hounsfield units (HU) estimation was comparable for 70 and 100 keV virtual imaging between scanners, but PC‐CT was significantly underestimating virtual 40 keV HU values of dense materials in the phantom representing the extremely obese population.ConclusionsThe statistical analysis of our measurements reveals better IQ at lower radiation doses using new PC‐CT. Although VMI performance was mostly comparable between the scanners, the DE‐CT scanner quantitatively outperformed PC‐CT when estimating HU values in the specific case of very large phantoms and dense materials, benefiting from increased X‐ray tube potentials.

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Threshold-dependent iodine imaging and spectral separation in a whole-body photon-counting CT system

Cited by 9 publications

References 33 publications

First Performance Evaluation of an Artificial Intelligence-Based Computer-Aided Detection System for Pulmonary Nodule Evaluation in Dual-Source Photon-Counting Detector CT at Different Low-Dose Levels

First Performance Evaluation of an Artificial Intelligence-Based Computer-Aided Detection System for Pulmonary Nodule Evaluation in Dual-Source Photon-Counting Detector CT at Different Low-Dose Levels

Likelihood‐based bilateral filters for pre‐estimated basis sinograms using photon‐counting CT

Quantitative performance of photon‐counting CT at low dose: Virtual monochromatic imaging and iodine quantification

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