Dual-energy CT-based iodine quantification for differentiating pulmonary artery sarcoma from pulmonary thromboembolism: a pilot study

Chang, Suyon; Hur, Jin; Im, Dong Jin; Suh, Young Joo; Hong, Yoo Jin; Lee, Hye Jeong; Kim, Young Jin; Choi, Byoung Wook

doi:10.1007/s00330-015-4140-2

Cited by 31 publications

(18 citation statements)

References 40 publications

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“…Also, quantification of myocardial perfusion parameters, or iodine content, may possibly enable detection of subclinical CAD, in which blood supply is reduced but yet without gross perfusion defects. The added value of DECT using iodine quantification is not only shown for cardiac imaging but several studies have shown added value in oncological imaging, differentiating between renal masses and cysts or assessing treatment response [ 17 – 19 ].…”

Section: Discussionmentioning

confidence: 99%

Accuracy of iodine quantification using dual energy CT in latest generation dual source and dual layer CT

et al. 2017

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ObjectiveTo determine the accuracy of iodine quantification with dual energy computed tomography (DECT) in two high-end CT systems with different spectral imaging techniques.MethodsFive tubes with different iodine concentrations (0, 5, 10, 15, 20 mg/ml) were analysed in an anthropomorphic thoracic phantom. Adding two phantom rings simulated increased patient size. For third-generation dual source CT (DSCT), tube voltage combinations of 150Sn and 70, 80, 90, 100 kVp were analysed. For dual layer CT (DLCT), 120 and 140 kVp were used. Scans were repeated three times. Median normalized values and interquartile ranges (IQRs) were calculated for all kVp settings and phantom sizes.ResultsCorrelation between measured and known iodine concentrations was excellent for both systems (R = 0.999–1.000, p < 0.0001). For DSCT, median measurement errors ranged from −0.5% (IQR −2.0, 2.0%) at 150Sn/70 kVp and −2.3% (IQR −4.0, −0.1%) at 150Sn/80 kVp to −4.0% (IQR −6.0, −2.8%) at 150Sn/90 kVp. For DLCT, median measurement errors ranged from −3.3% (IQR −4.9, −1.5%) at 140 kVp to −4.6% (IQR −6.0, −3.6%) at 120 kVp. Larger phantom sizes increased variability of iodine measurements (p < 0.05).ConclusionIodine concentration can be accurately quantified with state-of-the-art DECT systems from two vendors. The lowest absolute errors were found for DSCT using the 150Sn/70 kVp or 150Sn/80 kVp combinations, which was slightly more accurate than 140 kVp in DLCT.Key Points• High-end CT scanners allow accurate iodine quantification using different DECT techniques.• Lowest measurement error was found in scans with largest photon energy separation.• Dual-source CT quantified iodine slightly more accurately than dual layer CT.

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Section: Discussionmentioning

confidence: 99%

Accuracy of iodine quantification using dual energy CT in latest generation dual source and dual layer CT

et al. 2017

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“…The recent technical advance of dual‐energy CT (DECT) has provided the material‐specific imaging, also known as material decomposition, which can separate several numbers of substances, such as water, iodine, calcium, uric acid, and fat . Especially, quantitative information for iodine distribution, among the DECT‐based material decomposition techniques, has been considered a promising tool for lesion characterization to distinguish not only malignancy from benignity but also hyperdense cystic lesions or hematomas from enhancing lesions . In the head and neck region, several studies showed iodine concentration (IC) could be useful in CT imaging of cervical lymph nodes or patients with underlying neck malignancy .…”

Section: Introductionmentioning

confidence: 99%

“…[7][8][9][10] Especially, quantitative information for iodine distribution, among the DECT-based material decomposition techniques, has been considered a promising tool for lesion characterization to distinguish not only malignancy from benignity but also hyperdense cystic lesions or hematomas from enhancing lesions. 7,8,[10][11][12][13][14][15][16][17][18] In the head and neck region, several studies showed iodine concentration (IC) could be useful in CT imaging of cervical lymph nodes or patients with underlying neck malignancy. [19][20][21][22] Until now, a few studies have evaluated IC of thyroid nodules using the DECT data sets to find the malignancy or intranodular hemorrhage; however, they decided the individual CT images for quantification without the detailed topographic knowledge based on ultrasound, which is widely considered as reference imaging modality to assess thyroid nodule.…”

Section: Introductionmentioning

confidence: 99%

Dual‐energy CT iodine quantification for characterizing focal thyroid lesions

Lee

Seo

et al. 2018

Head & Neck

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Background To determine the usefulness of dual‐energy CT (DECT) iodine quantification to classify the focal thyroid lesions. Methods We retrospectively enrolled a total of 76 cytopathologically confirmed focal thyroid lesions (mean size: 1.9 cm). After drawing a region of interest on the DECT‐derived iodine maps, the obtained iodine concentration values of thyroid nodules (IC_N) and normalized IC_N were compared between 3 groups: papillary thyroid carcinoma (PTC), benign nodule, and cyst. Results From all lesions, 46, 17, and 13 were assigned to the PTC, benign nodule, and cyst groups. IC_N was the highest in the benign nodule, lower in the PTC, and the lowest in the cyst (median [interquartile range]: 4.3 [3.13‐5.48], 3.15 [2.29‐4.01], 0.60 [0.33‐0.88], all P < .001). Similarly, the normalized IC_N values were all statistically different from each other (P < .05).The multi‐class area under the curves using the optimal cutoff values were 0.931 for IC_N and 0.918, 0.920 for normalized IC, respectively. Conclusion DECT iodine quantification could be helpful to classify the focal thyroid lesions.

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“…96,97 DECT has also shown significant promise in the study of Chronic thromboembolic pulmonary hypertension 3998 as well as in distinguishing tumor embolism from thromboembolism. 99 …”

Section: Dual Energy Computed Tomographymentioning

confidence: 99%

Diagnosis of Deep Venous Thrombosis and Pulmonary Embolism

Rahaghi

Minhas

Heresi

2018

Clinics in Chest Medicine

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Imaging continues to be the modality of choice for the diagnosis of venous thromboembolic disease, particularly when incorporated into diagnostic algorithms. Improvement in imaging techniques as well as new imaging modalities and processing methods have improved diagnostic accuracy and additionally are being leveraged in prognostication and decision making for choice of intervention. In this article, we review the role of imaging in diagnosis and prognostication of venous thromboembolism. We also discuss emerging imaging approaches that may in the near future find clinical usefulness in improving diagnosis and prognostication as well as differentiating disease phenotypes.

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Dual-energy CT-based iodine quantification for differentiating pulmonary artery sarcoma from pulmonary thromboembolism: a pilot study

Abstract: • DECT can be useful for differentiation of PAS and PTE. • With quantitative analysis, DECT offers tissue characterisation by detecting lesion parameter increases. • The patients without predisposing factors for PTE can be candidates for DECT.

Cited by 31 publications

References 40 publications

Accuracy of iodine quantification using dual energy CT in latest generation dual source and dual layer CT

Accuracy of iodine quantification using dual energy CT in latest generation dual source and dual layer CT

Dual‐energy CT iodine quantification for characterizing focal thyroid lesions

Diagnosis of Deep Venous Thrombosis and Pulmonary Embolism

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