Objective image characterization of a spectral CT scanner with dual-layer detector

Ozguner, Orhan; Dhanantwari, Amar; Halliburton, Sandra S.; Wen, Gezheng; Utrup, S.; Jordan, David W.

doi:10.1088/1361-6560/aa9e1b

Cited by 45 publications

(21 citation statements)

References 43 publications

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“…However, the mean CT energy spectrum was not known exactly and had to be approximated. Based on preliminary experiments, 72 keV were used for 120 kVp imaging, which was in good agreement with previous dual energy CT studies, where 120 kVp single energy images yielded similar HU values as 70–75 kVe monochromatic images 13–16 . Calculated HU values were in excellent agreement with measured values, confirming the validity of the calculation model.…”

Section: Discussionsupporting

confidence: 84%

Development of a method to create uniform phantoms for task‐based assessment of CT image quality

Conzelmann

Schwarz

Hamm

et al. 2020

J Applied Clin Med Phys

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Purpose To develop a customized method to produce uniform phantoms for task‐based assessment of CT image quality. Methods Contrasts between polymethyl methacrylate (PMMA) and fructose solutions of different concentrations (240, 250, 260, 280, 290, 300, 310, 320, 330, and 340 mg/mL) were calculated. A phantom was produced by laser cutting PMMA slabs to the shape of a patient’s neck. An opening of 10 mm diameter was cut into the left parapharyngeal space. An angioplasty balloon was inserted and filled with the fructose solutions to simulate low‐contrast lesions. The phantom was scanned with six tube currents. Images were reconstructed with filtered back projection (FBP) and adaptive iterative dose reduction 3D (AIDR 3D). Calculated and measured contrasts were compared. The phantom was evaluated in a detectability experiment using images with 4 and 20 HU lesion contrast. Results Low‐contrast lesions of 4, 9, 11, 13, 18, 20, 24, 30, 35, and 37 HU contrast were simulated. Calculated and measured contrasts correlated excellently (r = 0.998; 95% confidence interval: 0.991 to 1). The mean ± SD difference was 0.41 ± 2.32 HU (P < 0.0001). Detection accuracy and reader confidence were 62.9 ± 18.2% and 1.58 ± 0.68 for 4 HU lesion contrast and 99.6 ± 1.3% and 4.27 ± 0.92 for 20 HU lesion contrast (P < 0.0001), confirming that the method produced lesions at the threshold of detectability. Conclusion A cost‐effective and flexible approach was developed to create uniform phantoms with low‐contrast signals. The method should facilitate access to customized phantoms for task‐based image quality assessment.

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Section: Discussionsupporting

confidence: 84%

Development of a method to create uniform phantoms for task‐based assessment of CT image quality

Conzelmann

Schwarz

Hamm

et al. 2020

J Applied Clin Med Phys

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“…The latest dual-layer spectral detector CT (SDCT) acquires homologous, in-phase, and temporally synchronized photons from a single source, thereby enabling energysensitive projection data to be obtained simultaneously. The system applies anti-correlated noise suppression and an iterative algorithm, thus reducing image noise and improving image quality (10)(11)(12). Another advantage that SDCT has over other types of dual-energy CT is that it can generate all spectral datasets without the need to pre-set dual-energy protocols, thereby efficient clinical workflow (13)(14)(15)(16).…”

Section: Introductionmentioning

confidence: 99%

The application of dual-layer spectral detector computed tomography in solitary pulmonary nodule identification

Wen

Yue

Shang

et al. 2021

Quant Imaging Med Surg

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Background: Differentiating between malignant solitary pulmonary nodules (SPNs) and other lung diseases remains a substantial challenge. The latest generation of dual-energy computed tomography (CT), which realizes dual-energy technology at the detector level, has clinical potential for distinguishing lung cancer from other benign SPNs. This study aimed to evaluate the performance of dual-layer spectral detector CT (SDCT) for the differentiation of SPNs.Methods: Spectral images of 135 SPNs confirmed by pathology were retrospectively analyzed in both the arterial phase (AP) and the venous phase (VP). Patients were classified into two groups [the malignant group (n=93) and the benign group (n=42)], with the malignant group further divided into small cell lung cancer (SCLC, n=30) and non-small cell lung cancer (NSCLC, n=63) subtypes. The slope of the spectral Hounsfield Unit (HU) curve (λ HU ), normalized iodine concentration (NIC), CT values of 40 keV monochromatic images (CT 40keV ), and normalized arterial enhancement fraction (NAEF) in contrast-enhanced images were calculated and compared between the benign and malignant groups, as well as between the SCLC and NSCLC subgroups. ROC curve analysis was performed to assess the diagnostic performance of the above parameters. Seventy cases were randomly selected and independently measured by two radiologists, and intraclass correlation coefficient (ICC) and Bland-Altman analyses were performed to calculate the reliability of the measurements.Results: Except for NAEF (P=0.23), the values of the parameters were higher in the malignant group than in the benign group (all P<0.05). NIC, λ HU , and CT 40keV performed better in the VP (NIC VP , λ VPHU , and CT VP40keV ) (P<0.001), with an area under the ROC curve (AUC) of 0.93, 0.89, and 0.89 respectively. With respective cutoffs of 0.31, 1.83, and 141.00 HU, the accuracy of NIC VP , λ VPHU , and CT VP40keV was 91.11%, 85.19%, and 88.15%, respectively. In the subgroup differentiating NSCLC and SCLC, the diagnostic performances of NIC AP (AUC =0.89) were greater than other parameters. NIC AP had an accuracy of 86.02% when the cutoff was 0.14. ICC and Bland-Altman analyses indicated that the measurement of SDCT has great reproducibility.Conclusions: Quantitative measures from SDCT can help to differentiate benign from malignant SPNs and may help with the further subclassification of malignant cancer into SCLC and NSCLC.

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“…First, the conspicuous texture of low-energy virtual monochromatic images is problematic. A previous report showed that monochromatic images at 70 keV have similar texture to conventional CT images acquired at 120 kVp and the texture becomes noticeable on 50-keV images [17] . Therefore, conspicuous image texture as shown in case 3 ( Fig.…”

Section: Discussionmentioning

confidence: 80%

Reduced iodinated contrast media for abdominal imaging by dual-layer spectral detector computed tomography for patients with kidney disease

Saito¹,

Noda²,

Ogasawara³

et al. 2018

Radiology Case Reports

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Contrast-enhanced computed tomography using iodinated contrast media is useful for diagnosis of gastrointestinal diseases. However, contrast-induced nephropathy remains problematic for kidney diseases patients. Although current guidelines recommended the use of a minimal dose of contrast media necessary to obtain adequate images for diagnosis, obtaining adequate images with sufficient contrast enhancement is difficult with conventional computed tomography using reduced contrast media. Dual-layer spectral detector computed tomography enables the simultaneous acquisition of low- and high-energy data and the reconstruction of virtual monochromatic images ranging from 40 to 200 keV, retrospectively. Low-energy virtual monochromatic images can enhance the contrast of images, thereby facilitating reduced contrast media. In case 1, abdominal computed tomography angiography at 50 keV using 40% of the conventional dose of contrast media revealed the artery that was the source of diverticular bleeding in the ascending colon. In case 2, ischemia of the transverse colon was diagnosed by contrast-enhanced computed tomography and iodine-selective imaging using 40% of the conventional dose of contrast media. In case 3, advanced esophagogastric junctional cancer was staged and preoperative abdominal computed tomography angiography could be obtained with 30% of the conventional dose of contrast media. However, the texture of virtual monochromatic images may be a limitation at low energy.

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Objective image characterization of a spectral CT scanner with dual-layer detector

Cited by 45 publications

References 43 publications

Development of a method to create uniform phantoms for task‐based assessment of CT image quality

Development of a method to create uniform phantoms for task‐based assessment of CT image quality

The application of dual-layer spectral detector computed tomography in solitary pulmonary nodule identification

Reduced iodinated contrast media for abdominal imaging by dual-layer spectral detector computed tomography for patients with kidney disease

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