Differences In Iodine Concentration Research Articles

Quantitative determination of iodine content in iodized table salt marketed in Jordan as an indicator of compliance with national salt iodization standards: A cross-sectional study

Iodine deficiency (ID) is a significant global public health issue, particularly affecting low-income countries. The iodization of salt is a widely adopted method to prevent iodine deficiency. This study aimed to assess the iodine content of iodized salt at the market level in various cities within the Hashemite Kingdom of Jordan (HKJ). We collected 152 salt samples from 24 different brands across three cities in Jordan: Amman, Zarqa, and Mafraq. The analysis was conducted using a titration method. The mean iodine content in salt samples varied by city, with values of 5.45 ppm in Mafraq, 10.33 ppm in Amman, and 13.22 ppm in Zarqa, ranging from 0 to 36 ppm. Significant differences in iodine concentration were observed within the same city across different brands (P ≤ 0.05). Additionally, variations were noted in iodine content for samples from the same brand collected in different cities, and even among samples from the same brand at the same location. Of the 152 samples evaluated, an average of 76.5% had iodine levels below the 15 ppm recommended by UNICEF. There was considerable variation in mean iodine content among brands, cities, and even within samples of the same brand. This indicates that the salt iodization process requires ongoing monitoring, and the government should enhance efforts to oversee the iodization process and improve the accessibility and utilization of iodized salt.

The value of CT-based energy imaging to discriminate dominant side lesions in primary aldosteronism.

The current clinical discrimination of the dominant side of primary aldosteronism (PA) mainly relies on invasive adrenal venous sampling (AVS) examination. This study investigated the feasibility of dual-energy CT energy imaging parameters as a novel biomarker in identifying bilateral adrenal dominant lesions. Fifty PA patients with bilateral lesions who underwent CT and AVS of the adrenal glands at Shaanxi Provincial People's Hospital from October 2019 to June 2021 were retrospectively analyzed. Forty-eight patients had successful bilateral blood collection and two failed right-sided blood collection due to venous variation. Forty patients who were classified based on AVS underwent unilateral adrenalectomy and pathological findings confirmed adenoma in all cases. Quantitative dual-energy CT parameters were measured for all adrenal lesions, and the differences in dual-energy CT energy spectrum imaging parameters between the dominant and nondominant adrenal lesions were compared. Among forty-eight PA patients with bilateral lesions, forty patients with preoperative AVS-determined lesions on the dominant side underwent unilateral adrenalectomy, and eight patients without the dominant side were treated with medication. The iodine concentration difference (ICD) in the arteriovenous phase was more significant in the 40 cases of primary aldosteronism with dominant adrenal lesions than in the nondominant adrenal lesions (1.18 ± 0.45 vs 0.41 ± 0.42). The NICAP was higher in the dominant adrenal lesions than in the non-dominant lesions (0.39 ± 0.39 vs 0.14 ± 0.05). The sensitivity and specificity of the diagnosis of the dominant adrenal lesion were 88.2% and 82.4% using the ICD of 0.68 as the threshold value. Conventional CT has lower diagnostic value for dominant adrenal lesions, and CT-based energy imaging can be a new assessment method as a complement to AVS in identifying bilateral dominant adrenal lesions.

Dual-source dual-energy computed tomography-derived quantitative parameters combined with machine learning for the differential diagnosis of benign and malignant thyroid nodules.

This study aimed to investigate the ability of quantitative parameter-derived dual-source dual-energy computed tomography (DS-DECT) combined with machine learning to distinguish between benign and malignant thyroid nodules. Patients with thyroid nodules and pathological surgical results who underwent preoperative DS-DECT were selected. Quantitative parameter-derived DS-DECT was applied to classify benign and malignant nodules. Then, machine learning and binary logistic regression analysis models were constructed using the DS-DECT quantitative parameters to distinguish between benign and malignant nodules. The receiver operating characteristic curve was used to assess the diagnostic performance. The DeLong test was used to compare the diagnostic efficacy. One hundred and thirty patients with 139 confirmed thyroid nodules were involved in the study. The malignant group had a significantly higher iodine concentrationnodule (arterial phase) (P=0.001), normalized iodine concentration (arterial phase) (P=0.002), iodine concentration difference (P<0.001), spectral curve slope (nonenhancement) (P=0.007), spectral curve slope (arterial phase) (P=0.001), effective atomic number (nonenhancement) (P<0.001), and effective atomic number (arterial phase) (P=0.039) than the benign group. The binary logistic regression analysis model had an AUC (area under the curve) of 0.76, a sensitivity of 0.821, and a specificity of 0.667. The machine learning model had an AUC of 0.86, a sensitivity of 0.822, specificity of 0.791 in the training cohort, an AUC of 0.84, a sensitivity of 0.727, and specificity of 0.750 in the testing cohort. Multiple quantitative parameters of DS-DECT combined with machine learning could differentiate between benign and malignant thyroid nodules.

Quantitative dual-energy CT for evaluating hepatocellular carcinoma after transarterial chemoembolization

We aimed to investigate the role of the quantitative parameters of dual-energy computed tomography (DECT) in evaluating patients with hepatocellular carcinoma (HCC) treated by transarterial chemoembolization (TACE). We retrospectively identified 80 HCC patients (mean age, 56 years; 61 men) treated by TACE who received contrast-enhanced DECT and were retreated by TACE within 7 days between November 2018 and December 2019. Taking digital subtraction angiography (DSA) and CT images as reference standard, two readers measured and calculated the values of normalized iodine concentration at arterial phase (NICAP), normalized iodine concentration at portal venous phase (NICPP), iodine concentration difference (ICD), arterial iodine fraction (AIF) and slope of the spectral Hounsfield unit curve (λHu) by placing matched regions of interests (ROIs) within the tumor active area (TAA), adjacent normal hepatic parenchyma (ANHP) and tumor necrotic area (TNA). Differences between the parameters were analyzed by the Kruskal–Wallis H test. Receiver operating characteristic analysis of the parameters performance in differentiating the three tissues types was performed. AIF exhibited a good performance in distinguishing TAA (0.93 ± 0.31) and ANHP (0.18 ± 0.14), the areas under the receiver operating characteristic curve (AUC) was 0.989, while the λHu exhibited an excellent performance in distinguishing TAA (3.32 ± 1.24) and TNA (0.29 ± 0.27), with an AUC of 1.000. In conclusion, quantitative DECT can be effectively used to evaluate the tumor viability in HCC patients treated by TACE.

Gastrointestinal Applications of Iodine Quantification Using Dual-Energy CT: A Systematic Review.

Dual-energy computed tomography (DECT) can estimate tissue vascularity and perfusion via iodine quantification. The aim of this systematic review was to outline current and emerging clinical applications of iodine quantification within the gastrointestinal tract using DECT. The search was conducted with three databases: EMBASE, Pubmed and The Cochrane Library. This identified 449 studies after duplicate removal. From a total of 570 selected studies, 30 studies were enrolled for the systematic review. The studies were categorized into four main topics: gastric tumors (12 studies), colorectal tumors (8 studies), Crohn’s disease (4 studies) and miscellaneous applications (6 studies). Findings included a significant difference in iodine concentration (IC) measurements in perigastric fat between T1–3 vs. T4 stage gastric cancer, poorly and well differentiated gastric and colorectal cancer, responders vs. non-responders following chemo- or chemoradiotherapy treatment among cancer patients, and a positive correlation between IC and Crohn’s disease activity. In conclusion, iodine quantification with DECT may be used preoperatively in cancer imaging as well as for monitoring treatment response. Future studies are warranted to evaluate the capabilities and limitations of DECT in splanchnic flow.

Clinical value of quantitative parameters by spectral CT in parotid gland tumor

This study aimed to investigate the value of normalized iodine concentration (NIC), spectral attenuation curve slope (SACS), area under curve (AUC), and iodine concentration difference (ICD) generated from spectral CT in the assessment of parotid gland tumors. Ninety-two patients with pathologically confirmed parotid gland tumors underwent arterial phase- and venous phase-enhanced CT in spectral CT. The patients were divided into the pleomor-phic adenoma group (group A), Warthin tumor group (group B), basal cell tumor group (group C), and malignant tumor group (group D). The SACS, AUC, NIC, ICD were measured and analyzed. Statistical analyses were performed by one-way ANOVA, and statistical significance was set at P<0.05. SACS(AP), AUC(AP), and NIC(AP) in group A were lower than those in other groups; SACS(VP) and AUC(VP) in group C were higher than those in other groups; NIC(AP) and NIC(VP) in group D were higher than those in other groups; and ICD in group B was a positive number. The difference in SACS(AP) and AUC(AP) in groups B and C, SACS(VP) and AUC(VP) in groups C and D, and ICD in groups A and C were not statistically significant. By contrast, the diffe-rence between the other groups was statistically significant (P<0.05). The difference in NIC(AP) between groups A and B and groups C and D and the difference in NIC(VP) between groups A and C, groups A and D, and groups B and C were statistically significant (P=0.005, 0.025, 0.002, 0.038, and 0.049, respectively). Multi-quantitative parameters from spectral CT might be helpful in differentiating various types of parotid gland tumors.

Spectral Computed Tomography Imaging in the Differential Diagnosis of Lung Cancer and Inflammatory Myofibroblastic Tumor.

The aim of this study was to explore the value of spectral computed tomography (CT) imaging in differentiating lung cancer from inflammatory myofibroblastic tumor (IMT). One hundred twelve patients with 96 lung cancers and 16 IMTs underwent spectral CT during arterial phase (AP) and venous phase (VP). The normalized iodine concentration in AP (NICAP) and VP (NICVP), slope of spectral Hounsfield unit curve in AP (λAP) and VP (λVP), and normalized iodine concentration difference between AP and VP (ICD) were calculated. The 2-sample t test compared quantitative parameters. Two readers qualitatively assessed lesion types according to imaging features. Receiver operating characteristic curves were generated to calculate sensitivity and specificity. Sensitivity and specificity of the qualitative and quantitative studies were compared. The patients with IMT had significantly higher NICAP, NICVP, λAP, λVP, and ICD than did the patients with lung cancer (P < 0.05). The threshold NICVP of 0.425 would yield the highest sensitivity and specificity of 92.7% and 81.3%, respectively, for differentiating lung cancer from IMT. The logistic regression model produced from combining quantitative parameters NICAP, NICVP, λAP, and λVP provided a sensitivity and specificity of 100% and 81.3%, respectively, for differentiating lung cancer from IMT. Spectral CT imaging with the quantitative analysis may help to increase the accuracy of differentiating lung cancer from IMT.

How accurate and precise are CT based measurements of iodine concentration? A comparison of the minimum detectable concentration difference among single source and dual source dual energy CT in a phantom study.

To assess the impact of scan- and patient-related factors on the error and the minimum detectable difference in iodine concentration among different generations of single-source (SS) fast kV-switching and dual-source (DS) dual-energy CT (DECT). Lesions having eight different iodine concentrations (0.2-4 mgI/mL) were emulated in a 3D-printed phantom of medium and large size. Each combination of concentration and size was scanned in dual-energy mode on four different SS and DS DECTs. Radiation doses were 7 and 10 mGy (medium size) and 10, 13, and 16 mGy (large size). Iodine maps were reconstructed with filtered back projection (FBP) and vendor-specific iterative reconstruction algorithms (IRs). Absolute error of iodine quantification (E) was measured. Multivariate regression models determined the influence of CT scanner, iodine concentration, phantom size, radiation dose, and reconstruction algorithm on E. The minimum detectable difference in iodine concentration (ICmin) under the same imaging conditions (intra-conditional) and among different imaging conditions (inter-conditional) was calculated. The error was significantly lower in current than in previous DECT generations (p < 0.001). For all CT scanner conditions, the error was significantly higher with increasing phantom size and decreasing radiation dose (p < 0.001). Iodine concentration only significantly affected the error for SS DECT (p < 0.001). ICmin depended on patient- and scan-related factors and ranged from 0.4 to 1.5 mgI/mL. Patient- and scan-related factors have a significant impact on the error and minimum detectable difference in iodine concentration within and among SS fast kV-switching and DS DECT. • Patient- and scan-related factors have a significant impact on the error and minimum detectable difference in dual-energy CT-based iodine quantification. • Third-generation DECTs outperformed second-generation scanners for both single-source and dual-source dual-energy CT. • The minimum intra- and inter-conditional detectable difference in iodine concentration ranged from 0.4 to 1.5 mg iodine/mL.

The effect of a multi-material artifact reduction algorithm in a wide-detector CT system to reduce the beam hardening artifacts in CT imaging

Objective To investigate the effect of the multi-material artifact reduction (MMAR) algorithm of wide-detector CT system in reducing the beam hardening artifacts in brain CT imaging. Methods Nine tubes with various iodine concentrations (0.1-16.0 mgI/ml) were placed in a uniform phantom filled with soft-tissue equivalent material. The phantom was scanned using different combinations of the tube voltage and current as follows: 80 kV/530 mA, 100 kV/295 mA, 120 kV/190 mA and 140 kV/135 mA. The scanning was performed using the GE Discovery 750 and GE Revolution CT scanners, respectively. The CT values and standard deviations of the uniform areas between tubes were measured. The artifact index(AI) was calculated by using the standard deviation value outside the tubes as background noise. The artifact index values under different kV/mA combinations with different scanners were compared. CT brain images of 36 patients (n=18 on Discovery CT and n=18 on Revolution CT) were randomly selected. CT values of normal brain tissue and dark bands areas in the posterior fossa were measured for each case. The AI was calculated for these cases as for the phantom study. Paired t test was performed for phantom data analysis, and independent t test was performed for the clinical cases data analysis. Results The average AI values with Revolution CT(4.96±1.39, 4.80±1.57, 4.56±1.45, 4.76±1.57) were smaller than those of Discovery 750 (11.90±6.61, 11.17±5.61, 8.85±4.59, 8.77±3.85) under different tube voltage settings (t=3.714, 4.186, 3.745, 4.634, P<0.001) . The higher the iodine concentration difference between tube pairs was, the higher the artifact index;As for clinical data, the difference in AI values between Revolution CT(2.31±0.95) and Discovery 750(3.91±1.32) was found statistically significant (t=4.066, P<0.001) . Conclusion The multi-material artifact reduction algorithm implemented on the wide-detector Revolution CT scanner can significantly reduce beam hardening artifacts. Key words: Beam hardening artifacts; Tomography, X-ray computed; Multi-material artifact reduction

Pancreatic ductal adenocarcinoma and chronic mass-forming pancreatitis: Differentiation with dual-energy MDCT in spectral imaging mode

ObjectiveTo investigate the value of dual-energy MDCT in spectral imaging in the differential diagnosis of chronic mass-forming chronic pancreatitis (CMFP) and pancreatic ductal adenocarcinoma (PDAC) during the arterial phase (AP) and the pancreatic parenchymal phase (PP). Materials and methodsThirty five consecutive patients with CMFP (n=15) or PDAC (n=20) underwent dual-energy MDCT in spectral imaging during AP and PP. Iodine concentrations were derived from iodine-based material-decomposition CT images and normalized to the iodine concentration in the aorta. The difference in iodine concentration between the AP and PP, contrast-to-noise ratio (CNR) and the slope K of the spectrum curve were calculated. ResultsNormalized iodine concentrations (NICs) in patients with CMFP differed significantly from those in patients with PDAC during two double phases (mean NIC, 0.26±0.04mg/mL vs. 0.53±0.02mg/mL, p=0.0001; 0.07±0.02mg/mL vs. 0.28±0.04mg/mL, p=0.0002, respectively). There were significant differences in the value of the slope K of the spectrum curve in two groups during AP and PP (KCMFP=3.27±0.70 vs. KPDAC=1.35±0.41, P=0.001, and KCMFP=3.70±0.17 vs. KPDAC=2.16±0.70, p=0.003, respectively). CNRs at low energy levels (40–70keV) were higher than those at high energy levels (80–40keV). ConclusionIndividual patient CNR-optimized energy level images and the NIC can be used to improve the sensitivity and the specificity for differentiating CMFP from PDAC by use of dual-energy MDCT in spectral imaging with fast tube voltage switching.

Quantitative parameters in iodine overlay image based on dual-source dual-energy computed tomography in differentiating benign and malignant thyroid nodules

Objective To investigate the application of quantitative parameters associated with iodine concentration derived from iodine overlay image by dual-source dual-energy computed tomographic (CT) in differentiating benign and malignant thyroid nodules. Methods Seventy-eight patients (total 112 nodules, including 64 benign and 48 malignant nodules) with thyroid nodules who underwent plain scan (PS), arterial phase (AP) and venous phase (VP) enhanced scan by DSCT (80 kVp/Sn140 kVp) were analyzed retrospectively. Iodine overlay images were obtained by the dual energy post-processing software. The mean iodine concentrations in the normal thyroid parenchyma (ICThy), the lesion (ICLes), and the carotid artery(ICCar) of PS, AP and VP were measured from iodine overlay images. The iodine concentration difference (ICD), the iodine concentration difference-to-normal parenchyma ratio (ICDNR) and the normalized iodine concentration ratio (NIC) were calculated. The two-sample t test was performed to compare quantitative parameters between the benign and malignant nodules. ROC curve with quantitative parameters of three phases was used to analyze the diagnostic efficiency of ICD, ICDNR, NIC and ICles. Results During PS, mean ICDNR, ICD and ICLes of malignant nodules were respectively 1.04 ± 0.95, (2.20 ± 1.82) mg/ml, (-0.04±1.65) mg/ml, ICDNR, ICD and ICLes of benign nodules were respectively 0.04 ± 0.41, (0.35 ± 0.97) mg/ml, (2.19 ± 0.55) mg/ml. ICDNR and ICD of malignant nodules were higher than benign nodules (t'=6.63, 6.39, P< 0.05), while ICles of malignant nodules were lower than benign nodules (t=10.13, P< 0.05). During AP, mean ICDNR, ICD, ICLes of malignant nodules were 0.39 ± 0.29, (2.23 ± 1.77) mg/ml, (3.81 ± 1.50) mg/ml, and benign nodules were 0.49 ± 0.22, (2.97 ± 1.91) mg/ml, (3.17± 1.64) mg/ml, respectively. ICDNR, ICD of malignant nodules were lower than benign nodules (t'=2.08, t=2.12; P< 0.05),while ICles of malignant nodules were higher than benign nodules (t=2.12, P< 0.05). During VP, mean NIC of the malignant and benign nodules were 0.45 ± 0.21, 0.58 ± 0.37, respectively. NIC of malignant nodules were lower than benign nodules (t'=2.35, P< 0.05). AUC of ICDNR during PS was 0.892, the sensitivity was 83.3% and the specificity were 90.5%. Conclusion Quantitative parameters associated with iodine concentration by dual-source dual-energy CT may increase the efficiency and accuracy in differentiating benign and malignant thyroid nodules. Key words: Thyroid nodule; Iodine concentration; Tomography, X-ray computed

Imaging of acute superior mesenteric artery embolus using spectral CT in a canine model.

To explore the diagnostic value of single-source dual-energy spectral CT (sDECT) imaging in an acute superior mesenteric artery embolus (SMAE) canine model. Pre-contrast and double-phase contrast-enhanced sDECT were performed before and after embolization in eight SMAE dog models. Monochromatic images of embolized intestine with the best contrast-to-noise ratio (CNR) were obtained and compared with the polychromatic images. CT parameters including attenuation value, iodine content, water content and thickness of the embolized intestinal segments were obtained, and normalized difference in iodine concentration (NDIC) was calculated. The CNR in pre-contrast, arterial phase and portal venous phase at 4 h after embolization was 1.11 ± 1.23, 13.50 ± 1.54 and 10.63 ± 3.75, respectively, significantly higher than those of the polychromatic images (p < 0.05). The iodine-based images clearly revealed the embolized intestinal segments, which were highly consistent with the gross findings. The difference in attenuation values between the embolization area and non-embolization area in the monochromatic images was 105.06 ± 35.35 HU, higher than that in the polychromatic images (p < 0.001). The attenuation values and NDIC were significantly decreased at 2 h after embolization, relatively increased at 4 h and gradually decreased at 6 and 8 h. The changing pattern of thickness was similar to that of NDIC over time after embolization. sDECT can provide the optimal monochromatic images and allow increased detection rates of lesions. sDECT is a very promising tool for quantitative diagnosis of SMAE. Our research provides more quantitative parameters for the assessment of SMAE by sDECT.

Value of quantitative iodine-based material decomposition images with gemstone spectral CT imaging in the follow-up of patients with hepatocellular carcinoma after TACE treatment

To investigate the value of quantitative iodine-based material decomposition images with gemstone spectral CT imaging in the follow-up of patients with hepatocellular carcinoma (HCC) after transcatheter arterial chemoebolization (TACE). Consecutive 32 HCC patients with previous TACE treatment were included in this study. For the follow-up, arterial phase (AP) and venous phase (VP) dual-phase CT scans were performed with a single-source dual-energy CT scanner (Discovery CT 750HD, GE Healthcare). Iodine concentrations were derived from iodine-based material-decomposition images in the liver parenchyma, tumors and coagulation necrosis (CN) areas. The iodine concentration difference (ICD) between the arterial-phase (AP) and venal-phase (VP) were quantitatively evaluated in different tissues.The lesion-to-normal parenchyma iodine concentration ratio (LNR) was calculated. ROC analysis was performed for the qualitative evaluation, and the area under ROC (Az) was calculated to represent the diagnostic ability of ICD and LNR. In all the 32 HCC patients, the region of interesting (ROI) for iodine concentrations included liver parenchyma (n=42), tumors (n=28) and coagulation necrosis (n=24). During the AP the iodine concentration of CNs (median value 0.088 µg/mm(3)) appeared significantly higher than that of the tumors (0.064 µg/mm(3), P=0.022) and liver parenchyma (0.048 µg/mm(3), P=0.005). But it showed no significant difference between liver parenchyma and tumors (P=0.454). During the VP the iodine concentration in hepatic parenchyma (median value 0.181 µg/mm(3)) was significantly higher than that in CNs (0.140 µg/mm(3), P=0.042). There was no significant difference between liver parenchyma and tumors, CNs and tumors (both P>0.05). The median value of ICD in CNs was 0.006 µg/mm(3), significantly lower than that of the HCC (0.201 µg/mm(3), P<0.001) and hepatic parenchyma (0.117 µg/mm(3), P<0.001). The ICDs in tumors and hepatic parenchyma showed no significant difference (P=0.829). During the AP, the LNR had no significant difference between CNs and tumors (a median value 1.805 vs. 1.310, P=0.389), and during the VP, the difference was also non-significant (the median value 0.647 vs. 0.713, P=0.660). The mean Az value of ICDs for evaluation of surviving tumor tissues was 0.804, whiles LNR measured a disappointing result in both AV images and VP images. Quantitative iodine-based material decomposition images with gemstone spectral CT imaging can improve the diagnostic efficacy of CT imaging for HCC patients after TACE treatment.

Stability of iodine during cooking: investigation on biofortified and not fortified vegetables

Biofortification of food crops through fertilization and salt iodization are key strategies for the prevention and control of iodine deficiency disorder. However, considerable losses of iodine can occur during processing. In this study, the stability of iodine in biofortified potatoes, carrots and tomatoes was evaluated during different domestic cooking procedures, as this matter was poorly discussed in literature. The stability of iodized salt during baking and boiling of carrots and potatoes not fortified was also investigated. All the adopted cooking procedures have proven to be suitable to preserve the iodine content in biofortified vegetables. During boiling test with iodized salt, neither potatoes nor carrots were able to absorb iodine added with salt, probably owing to the losses occurred during cooking. On the contrary, baking test on potatoes has not caused a significant degradation of iodized salt, and no significant differences in iodine concentration were detected before and after cooking.

Values of spectral CT imaging in differential diagnosis of hepatocellular carcinoma and focal nodular hyperplasia

Objective To explore the application value of spectral CT multi-parameter imaging in the differential diagnosis of hepatocellular carcinoma (HCC) and focal nodular hyperplasia (FNH). Methods Forty-eight patients with hepatic lesions underwent gemstone spectral imaging (GSI) scans,including 32 HCC and 16 FNH,to obtain spectral serial images for the arterial phase and portal venous phase (PVP).The spectral parameters of lesions,normal hepatic tissue and the aorta were measured.Then,the lesion-liver contrast-to-noise ratio (CNR) in the different energy levels,normalized iodine concentration (NIC),the lesion-normal parenchyma iodine concentration ratio (LNR) and iodine concentration difference (ICD) between the arterial phase and the portal venous phase were calculated.The above measurement results were analyzed with two samples t test and ROC curve. Results The CNR of HCC and FNH in the different energy levels showed a certain regularity.In general,with the single photon energy increased,the CNR decreased except for some energy points.For HCC and FNH,the optimal CNR were 3.59±2.13 and 8.29±2.65,respectively,during the arterial phase and 1.80±0.42 and 1.06±0.34,respectively,during the portal venous phase.The NIC were 0.25±0.08 and 0.42±0.22,respectively,during the arterial phase and 0.52±0.14 and 0.86±0.18,respectively,during the portal venous phase.The LNR were 2.97±0.50 and 6.15±0.97,respectively,during the arterial phase and 0.99±0.19 and 1.22±0.26,respectively, during the portal venous phase.The ICD were (0.35±0.14) and (1.17±0.28) g/L,respectively.The NIC,LNR and ICD for HCC were less than FNH during the arterial phase and the portal venous phase.There were significant differences in NIC (t=-3.196,the arterial phase;t=-6.518,the portal venous phase),LNR (t=-12.911,the arterial phase; t=-3.260,the portal venous phase),and ICD (t=-2.754) between HCC and FNH (P<0.05).LNR in the arterial phase had the highest sensitivity and specificity of 100% and 100% in differentiating HCC from FNH. Conclusion The use of spectral CT with the quantitative analysis of iodine concentration might be helpful for increasing the efficiency of the detection and accuracy of diagnosis of HCC and FNH. Key words: Liver neoplasms; Tomography,X-ray computed; Diagnosis,differential

Differentiation of Small Hepatic Hemangioma from Small Hepatocellular Carcinoma: Recently Introduced Spectral CT Method

To investigate the usefulness of computed tomographic (CT) spectral imaging parameters in differentiating small (≤3 cm) hepatic hemangioma (HH) from small hepatocellular carcinoma (HCC), with or without cirrhosis, during the late arterial phase (AP) and portal venous phase (PVP). This prospective study was institutional review board approved, and written informed consent was obtained from all patients. The authors examined 49 patients (39 men, 10 women; 65 lesions) with CT spectral imaging during the AP and the PVP. Twenty-one patients had HH; nine, HCC with cirrhosis; and 19, HCC without cirrhosis. Iodine concentrations were derived from iodine-based material-decomposition CT images and normalized to the iodine concentration in the aorta. The difference in iodine concentration between the AP and PVP (ie, iodine concentration difference [ICD]) and the lesion-to-normal parenchyma ratio (LNR) were calculated. Two readers qualitatively assessed lesion types on the basis of conventional CT characteristics. Sensitivity and specificity were compared between the qualitative and quantitative studies. The two-sample t test was performed to compare quantitative parameters between HH and HCC. Normalized iodine concentrations (NICs) and LNRs in patients with HH differed significantly from those in patients with HCC and cirrhosis and those in patients with HCC without cirrhosis: Mean NICs were 0.47 mg/mL ± 0.24 (standard deviation) versus 0.23 mg/mL ± 0.10 and 0.23 mg/mL ± 0.08, respectively, during the AP and 0.83 mg/mL ± 0.38 versus 0.47 mg/mL ± 0.86 and 0.52 mg/mL ± 0.11, respectively, during the PVP. Mean LNRs were 5.87 ± 3.36 versus 2.56 ± 1.10 and 2.29 ± 0.87, respectively, during the AP and 2.01 ± 1.33 versus 0.96 ± 0.16 and 0.93 ± 0.26, respectively, during the PVP. The mean ICD for the HH group (1.37 mg/mL ± 0.84) was significantly higher than the mean ICDs for the HCC-cirrhosis (0.33 mg/mL ± 0.29) (P < .001) and HCC-no cirrhosis (0.82 mg/mL ± 0.99) (P = .03) groups. The combination of NIC and LNR had higher sensitivity and specificity compared with those of conventional qualitative CT image analysis during individual and combined phases. Use of spectral CT with fast tube voltage switching may increase the sensitivity for differentiating small hemangiomas from small HCCs in two-phase scanning.

A Survey of Urinary Iodine Concentration in South-east of Caspian Sea in Northern, Iran

The objective of this study was to evaluate the urinary iodine concentration in Gorgan located in northern Iran, which is a cosmopolitan society and on the basis of such determination the endemic goiter in the region could be estimated. The sample population were a total of 287 people (23.3% male, 76.7% female) referred to Danesh Medical Diagnostic Laboratory for the urinary iodine measurement, during 2004-05. Urinary iodine level was determined using acid digestion method. The results from this study indicated that 2.1, 3.8 and 9.8% of sample population had urinary iodine level of <2, 2-4.9 and 5-9.9 microg dL(-1), respectively which are defined as sever, moderate and mild iodine deficiency. Therefore 45 (15.7%) of the sample population in this study could be assessed for goiter prevalence, the mean differences of iodine concentration in male and female subjects were not significant. In conclusion, low urinary iodine of <10 microg dL(-1) concentration may help to give a direction for a further examination in the thyroid gland abnormalities.

Control of Spatial Xenon Oscillations in Pressurized Water Reactors Via the Kalman Filter

AbstractA direct control method is developed to control the spatial xenon oscillations in pressurized water reactors. The xenon and iodine concentration difference between the top and bottom halves of the core is estimated by using the extended Kalman filter (EKF), which is a closed-loop estimation method. The measurement equation used in the observer is the axial offset measurement equation, which reflects the xenon unbalanced effect on the axial offset. Meanwhile, some of the coefficients of the observer are estimated on-line to reduce estimation error resulting from model error, i.e., simplified xenon and iodine dynamics. Therefore, the estimation can be guaranteed to be accurate, and the success of the estimation does not greatly depend on the accuracy of the observer model. The predicted one-step ahead xenon concentration, by using the EKF, was used to calculate the possible axial offset variation, and then the control rod motion was calculated to compensate for it. The simulation results show that t...

Effect of viscosity and iodine concentration of nonionic radiographic contrast media on coronary arteriography in patients

To assess the influence of viscosity and iodine concentration, three matched and standardized left coronary arteriograms were obtained in 20 patients using iopamidol (isovue-370), ioversol (Optiray-320), and iohexol (Omnipaque-350). The order of contrast media was randomized and the administration of contrast was double-blinded. Quantitative densitometric angiographic evaluation of the coronary angiograms was performed in addition to independent operator qualitative assessment. The injection volume of iopamidol (5.4 ± 1.0 ml) was slightly but significantly less than that of ioversol and iohexol (5.6 ± 1.0 ml, 5.7 ± 1.0 ml, both p < 0.05). The calculated iodine concentration was also lower for ioversol (1.7 ± 0.32 gm) than for iopamidol (1.98 ± 0.35 gm) and iohexhol (1.9 ± 0.35 gm, both p < 0.05). There were significantly lower contrast syringe injection pressures for ioversol (6.6 ± 0.8 atm) than for iopamidol (7.5 ± 0.9 atm) and iohexol (7.2 ± 1.1 atm, both p < 0.05). The quantitative densitometric analysis failed to demonstrate significant differences among the contrast media with respect to image density parameters for any individual agent. All coronary angiograms were deemed of diagnostic quality. The data in this study indicated that although differences in iodine concentration exist among the three agents, operator compensation with more rapid contrast delivery (higher volume) and lower viscosity (lower injection pressure) produced equivalent image opacification during coronary angiography. Given the same incidence of adverse hemodynamic and clinical effects, selection of a low viscosity media theoretically provides an advantage during procedures using small diameter catheters or interventional procedures requiring contrast visualization through reduced catheter lumina.

Thyroid iodine concentration and total thyroid iodine in normal subjects and in endemic goitre subjects.

Thyroid iodine concentration and total thyroid iodine were determined by an automated technique by means of the ceric arsenious acid reaction in 42 males and 13 females. The thyroids were taken from autopsy material in a region with a low dietary intake. The accuracy of the method to estimate iodine was checked by neutron activation analysis. There was an excellent correlation between the iodine contents of thyroid specimens, when measured by chemical or by activation analysis. The mean iodine concentration was 1.86 mg/g dry weight and was found to be lower than in non-goitrous regions. In goitres, the mean iodine concentration was significantly lower, and the mean total thyroid of normal weight. There was no significant difference in iodine concentration and total iodine between males and females. The thyroid iodine concentration did not depend upon age in adults. The data were log normally distributed. It was established that mean iodine concentrations under 2 mg/g dry weight or 0.45 mg/g fresh weight are to be regarded as an important index of iodine deficiency.