Dual-layer detector spectral CT—a new supplementary method for preoperative evaluation of glioma

Li, Yingying; Zhang, Zhe; Xiaochen, Wang; Lü, Xiaomei; Ji, Nan; Shengjun, Sun

doi:10.1016/j.ejrad.2021.109649

Cited by 6 publications

(12 citation statements)

References 34 publications

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“…As shown in Table 3 and Figure 2A , we found that among all the spectral parameters, NID had the highest diagnostic efficiency in the arterial phase, and the NID of poorly-differentiated adenocarcinoma was lower than that of well–moderately-differentiated adenocarcinoma; that is, the iodine uptake rate of well–moderately-differentiated adenocarcinoma is higher than that of poorly-differentiated adenocarcinoma. In this regard, our results are consistent with previous studies ( 13 , 19 , 20 , 21 ). However, some research results are inconsistent with our conclusions ( 7 , 9 , 10 ).…”

Section: Discussionsupporting

confidence: 94%

“…As shown in Table 4 and Figure 3 , although the enhancement degree of traditional CT can also reflect the blood supply of tumors, and all spectral parameters significantly positively correlate with the enhancement degree of CT, spectral parameters are more effective in predicting the differentiation degree of LUAD. Furthermore, it has been shown that DLCT may reduce the influence of beam hardening and improve measurement accuracy ( 21 ), which further confirms that spectral parameters have better diagnostic efficiency than CT increment number and can better reflect the pathological characteristics of LUAD.…”

Section: Discussionmentioning

confidence: 73%

“…Liu et al reported that spectral quantitative parameters can be used to evaluate the pathological grading of esophageal squamous cell carcinoma (13). Yingying et al showed that the DLCT technology can be used as a supplementary method to provide more information for preoperative grading of gliomas and the prognosis of patients (21). As shown in Table 3 and Figure 2A, we found that among all the spectral parameters, NID had the highest diagnostic efficiency in the arterial phase, and the NID of poorly-differentiated adenocarcinoma was lower than that of well-moderatelydifferentiated adenocarcinoma; that is, the iodine uptake rate of well-moderately-differentiated adenocarcinoma is higher than that of poorly-differentiated adenocarcinoma.…”

Section: Compared With the Venous Phase Arterial Phase Spectralmentioning

confidence: 99%

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Dual-layer spectral detector computed tomography parameters can improve diagnostic efficiency of lung adenocarcinoma grading

Mu¹,

Meng²,

Guo³

et al. 2022

Quant Imaging Med Surg

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Background: It is difficult to distinguish the pathological grade of lung adenocarcinoma (LUAD) with traditional computed tomography (CT). The aim of this study was to assess tumor differentiation by duallayer spectral detector CT combined with morphological parameters. Methods:In this prospective study, a total of 67 patients with pathologically diagnosed LUAD were enrolled: 39 patients in the well-and moderately-differentiated group (14 and 25 patients, respectively) and 28 patients in the poorly-differentiated group. Morphological parameters, non-enhanced CT number, double-enhanced CT number, effective atomic number, monoenergetic CT images (40 and 70 keV), iodine density, and thoracic aorta iodine density of tumors were measured. The slope of the spectral curve and normalized iodine density were calculated. The diagnostic efficiency of the spectral parameters alone, and the combined spectral and morphological parameters were obtained by statistical analysis. Results:The morphological signs of LUAD (the vessel convergence sign, bronchus encapsulated air sign, and liquefactive necrosis) were higher in the poorly-differentiated group than in the well-moderatelydifferentiated group (57.1% vs. 30.8%, 40.0%; 60.7% vs. 28.2%, 32.0%; 64.3% vs. 28.2%, 24.0%; all P<0.05). There were significant differences in normalized iodine density (arterial phase: 0.10±0.04 vs. 0.12±0.05, 0.13±0.04; venous phase: 0.31±0.07 vs. 0.39±0.17, 0.40±0.17) among the poorly-differentiated group and moderately-differentiated group as well as the well-differentiated group (all P<0.05). Receiver operating characteristic (ROC) curves of the poorly-differentiated group and well-moderately-differentiated group showed that the normalized iodine density had the best diagnostic efficiency in the arterial phase, with an area under the curve (AUC) of 0.817, sensitivity of 92.9%, and specificity of 82.1% (P<0.001). The AUC increased to 0.916 when the morphological parameters were included, and sensitivity and specificity were 96.4% and 82.1% (P<0.001), respectively. Conclusions:The parameters of dual-layer spectral detector CT can help discriminate the pathological grade of LUAD. Among the spectral parameters, the normalized iodine density in the arterial phase has the best diagnostic efficiency, and the combination of spectral and morphological parameters improves the pathological grading of LUAD.

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Section: Discussionsupporting

confidence: 94%

Section: Discussionmentioning

confidence: 73%

Section: Compared With the Venous Phase Arterial Phase Spectralmentioning

confidence: 99%

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Dual-layer spectral detector computed tomography parameters can improve diagnostic efficiency of lung adenocarcinoma grading

Mu¹,

Meng²,

Guo³

et al. 2022

Quant Imaging Med Surg

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“…Tumor metabolism varies with the function and architecture of tumor blood vessels and therefore also between the different tumor entities [3,4]. For patients with brain tumors, Diagnostics 2022, 12, 2494 2 of 10 it is particularly important to determine the treatment scheme and evaluate the survival prognosis [5,6].…”

Section: Introductionmentioning

confidence: 99%

“…With the goal to provide this guide to treatment and survival estimation, current research in computed tomography (CT) and magnetic resonance imaging (MRI) aims to characterize brain tumors noninvasively [ 6 , 7 , 8 , 9 , 10 ]. For this purpose, texture and density features, radiomics and/or deep learning are used on imaging data in order to provide standardized in-depth information on tumor characteristics and tumor entity [ 6 , 11 , 12 , 13 , 14 ]. In clinical imaging, magnetic resonance imaging (MRI) with and without gadolinium-based contrast agents is the imaging method of choice.…”

Section: Introductionmentioning

confidence: 99%

Differentiation of Intracerebral Tumor Entities with Quantitative Contrast Attenuation and Iodine Mapping in Dual-Layer Computed Tomography

et al. 2022

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Purpose: To investigate if quantitative contrast enhancement and iodine mapping of common brain tumor (BT) entities may correctly differentiate between tumor etiologies in standardized stereotactic CT protocols. Material and Methods: A retrospective monocentric study of 139 consecutive standardized dual-layer dual-energy CT (dlDECT) scans conducted prior to the stereotactic needle biopsy of untreated primary brain tumor lesions. Attenuation of contrast-enhancing BT was derived from polyenergetic images as well as spectral iodine density maps (IDM) and their contrast-to-noise-ratios (CNR) were determined using ROI measures in contrast-enhancing BT and healthy contralateral white matter. The measures were correlated to histopathology regarding tumor entity, isocitrate dehydrogenase (IDH) and MGMT mutation status. Results: The cohort included 52 female and 76 male patients, mean age of 59.4 (±17.1) years. Brain lymphomas showed the highest attenuation (IDM CNR 3.28 ± 1,23), significantly higher than glioblastoma (2.37 ± 1.55, p < 0.005) and metastases (1.95 ± 1.14, p < 0.02), while the differences between glioblastomas and metastases were not significant. These strongly enhancing lesions differed from oligodendroglioma and astrocytoma (Grade II and III) that showed IDM CNR in the range of 1.22–1.27 (±0.45–0.82). Conventional attenuation measurements in DLCT data performed equally or slightly superior to iodine density measurements. Conclusion: Quantitative attenuation and iodine density measurements of contrast-enhancing brain tumors are feasible imaging biomarkers for the discrimination of cerebral tumor lesions but not specifically for single tumor entities. CNR based on simple HU measurements performed equally or slightly superior to iodine quantification.

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Dual-energy CT: A new frontier in oncology imaging

Wang,

Shen,

Zhang

et al. 2023

Meta-Radiology

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Dual-layer detector spectral CT—a new supplementary method for preoperative evaluation of glioma

Cited by 6 publications

References 34 publications

Dual-layer spectral detector computed tomography parameters can improve diagnostic efficiency of lung adenocarcinoma grading

Dual-layer spectral detector computed tomography parameters can improve diagnostic efficiency of lung adenocarcinoma grading

Differentiation of Intracerebral Tumor Entities with Quantitative Contrast Attenuation and Iodine Mapping in Dual-Layer Computed Tomography

Dual-energy CT: A new frontier in oncology imaging

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