Iodine quantification to characterize primary lesions, metastatic and non-metastatic lymph nodes in lung cancers by dual energy computed tomography: An initial experience

Abstract Background To explore the ability of Dual-energy CT (DECT) to differentiate metastatic from non-metastatic lymph nodes in colorectal cancer (CRC). Methods Seventy-one patients with primary CRC underwent contrast-enhanced DECT imaging before surgery. The colorectal specimen was scanned after surgery, and lymph nodes were matched to the pathology report. The DECT quantitative parameters were analyzed: dual-energy curve slope value(λHU), standardized iodine concentration (n△HU), iodine water ratio (nIWR), electron density value (nρeff), and effective atom-number (nZ), for the metastatic and non-metastatic lymph node differentiation. Also, sensitivity and specificity analyses were performed by using receiver operating characteristic curve. Results One hundred and fifty lymph nodes including 66 non-metastatic and 84 metastatic lymph nodes were matched using the radiological-pathological correlation. Metastatic node had a significantly greater λHU, n△HU and nIWR values than non-metastatic node in both arterial and venous phases (P < 0.01). The AUC, sensitivity and specificity were 0.80, 80.30% and 65.48% for λHU; 0.86, 69.70% and 95.24% for n△HU; 0.88, 71.21% and 95.24% for nIWR in the arterial phase. No significant difference was found in electron density and effective Z value for differentiation. Conclusion Dual-energy CT quantitative parameters may be helpful in diagnosing metastatic lymph nodes of CRC.

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Deep neural network-assisted computed tomography diagnosis of metastatic lymph nodes from gastric cancer

Chinese Medical Journal ◽

10.1097/cm9.0000000000000532 ◽

2019 ◽

Vol 132 (23) ◽

pp. 2804-2811 ◽

Cited By ~ 5

Author(s):

Yuan Gao ◽

Zheng-Dong Zhang ◽

Shuo Li ◽

Yu-Ting Guo ◽

Qing-Yao Wu ◽

...

Keyword(s):

Neural Network ◽

Gastric Cancer ◽

Computed Tomography ◽

Lymph Nodes ◽

Deep Neural Network ◽

Metastatic Lymph Nodes ◽

Metastatic Lymph ◽

Computed Tomography Diagnosis

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Evaluation of locoregional invasiveness of small-sized non-small cell lung cancers by enhanced dual-energy computed tomography

Cancer Imaging ◽

10.1186/s40644-016-0077-1 ◽

2016 ◽

Vol 16 (1) ◽

Cited By ~ 13

Author(s):

Hironori Shimamoto ◽

Shingo Iwano ◽

Hiroyasu Umakoshi ◽

Koji Kawaguchi ◽

Shinji Naganawa

Keyword(s):

Computed Tomography ◽

Dual Energy ◽

Small Cell ◽

Small Cell Lung ◽

Lung Cancers ◽

Dual Energy Computed Tomography

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Accuracy of iodine quantification using dual-energy computed tomography with focus on low concentrations

Acta Radiologica ◽

10.1177/02841851211009462 ◽

2021 ◽

pp. 028418512110094

Author(s):

Anders Ahnfelt ◽

Pär Dahlman ◽

Monica Segelsjö ◽

Mats O Magnusson ◽

Anders Magnusson

Keyword(s):

Computed Tomography ◽

Dual Energy ◽

Slice Thickness ◽

Low Contrast ◽

Dual Energy Computed Tomography ◽

Low Concentrations ◽

Iodine Quantification ◽

Spectral Separation ◽

Relative Errors

Background Iodine quantification using dual-energy computed tomography (DECT) is helpful in characterizing, and follow-up after treatment of tumors. Some malignant masses, for instance papillary renal cell carcinomas (p-RCC), are hard to differentiate from benign lesions because of very low contrast enhancement. In these cases, iodine concentrations might be very low, and it is therefore important that iodine quantification is reliable even at low concentrations if this technique is used. Purpose To examine the accuracy of iodine quantification and to determine whether it is also accurate for low iodine concentrations. Material and Methods Twenty-six syringes with different iodine concentrations (0–30 mg I/mL) were scanned in a phantom model using a DECT scanner with two different kilovoltage and image reconstruction settings. Iodine concentrations were measured and compared to known concentration. Absolute and relative errors were calculated. Results For concentrations of 1 mg I/mL or higher, there was an excellent correlation between true and measured iodine concentrations for all settings (R = 0.999–1.000; P < 0.001). For concentrations <1.0 mg I/mL, the relative error was greater. Absolute and relative errors were smaller using tube voltages of 80/Sn140 kV than 100/Sn140 kV ( P < 0.01). Reconstructions using a 3.0-mm slice thickness had less variance between repeated acquisitions versus 0.6 mm ( P < 0.001). Conclusion Iodine quantification using DECT was in general very accurate, but for concentrations < 1.0 mg I/mL the technique was less reliable. Using a tube voltage with larger spectral separation was more accurate and the result was more reproducible using thicker image reconstructions.

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