Hyunkee Hong

Relative accuracy of CT and MRI in the differentiation of benign from malignant pancreatic cystic lesions.

AIMS To assess the diagnostic accuracies of multidetector computed tomography (MDCT) and magnetic resonance imaging (MRI) for differentiating benign from malignant lesions and suggesting the specific diagnoses for pancreatic cystic lesions, and to assess whether review of both MDCT and MRI is beneficial. MATERIALS AND METHODS Patients with various neoplastic and non-neoplastic pancreatic cystic lesions that were identifiable by biopsy or surgery, who underwent both MRI and MDCT (n=63), were retrospectively reviewed by three reviewers. The likelihood of malignancy was recorded on a five-point scale, and a specific diagnosis was given. ROC analysis was performed and the sensitivity, specificity for the characterization of malignancy, and the accuracy of specific diagnoses were calculated. RESULTS MDCT and MRI yielded comparable results for the characterization of malignancy (Az: 0.639, 0.735, 0.806 for MDCT and 0.732, 0.753, 0.792 for MRI, for each reviewer). The accuracies of specific diagnosis based on MDCT or MRI were 61.9 versus 55.6% for reviewer 1; 76.2 versus 76.2% for reviewer 2; and 65.1 versus 61.9% for reviewer 3. There was a trend toward better prediction of malignancy (Az: 0.787, 0.745, 0.849 for each reviewer), and better accuracy in suggesting a specific diagnosis (77.8, 73, and 73% for each reviewer) for MDCT+MRI over MDCT or MRI alone, although it was statistically significant for one reviewer in the comparison of MDCT versus MDCT+MRI for the prediction of malignancy, and MRI versus MDCT for suggesting a specific diagnosis. CONCLUSIONS MDCT and MRI have equivalent accuracy for characterizing pancreatic cystic lesions as benign or malignant, and suggesting a specific diagnosis. Combined review of MDCT and MRI was not significantly better but may have the potential to improve diagnostic accuracy in equivocal cases.

Investigation of Simultaneous Effects of Aerosol Properties and Aerosol Peak Height on the Air Mass Factors for Space-Borne NO2 Retrievals

We investigate the simultaneous effects of aerosol peak height (APH), aerosol properties, measurement geometry, and other factors on the air mass factor for NO2 retrieval at sites with high NO2 concentration. A comparison of the effects of high and low surface reflectance reveals that NO2 air mass factor (AMF) values over a snowy surface (surface reflectance 0.8) are generally higher than those over a deciduous forest surface (surface reflectance 0.05). Under high aerosol optical depth (AOD) conditions, the aerosol shielding effect over a high-albedo surface is revealed to reduce the path-length of light at the surface, whereas high single scattering albedo (SSA) conditions (e.g., SSA = 0.95) lead to an increase in the aerosol albedo effect, which results in an increased AMF over areas with low surface reflectance. We also conducted an in-depth study of the APH effect on AMF. For an AOD of 0.1 and half width (HW) of 5 km, NO2 AMF decreases by 29% from 1.36 to 0.96 as APH changes from 0 to 2 km. In the case of high-AOD conditions (0.9) and HW of 5 km, the NO2 AMF decreases by 240% from 1.85 to 0.54 as APH changes from 0 to 2 km. The AMF variation due to error in the model input parameters (e.g., AOD, SSA, aerosol shape, and APH) is also examined. When APH is 0 km with an AOD of 0.4, SSA of 0.88, and surface reflectance of 0.05, a 30% error in AOD induces an AMF error of between 4.85% and −3.67%, an SSA error of 0.04 leads to NO2 VCD errors of between 4.46% and −4.77%, and a 30% error in AOD induces an AMF error of between −9.53% and 8.35% with an APH of 3 km. In addition to AOD and SSA, APH is an important factor in calculating AMF, due to the 2 km error in APH under high-SZA conditions, which leads to an NO2 VCD error of over 60%. Aerosol shape is also found to have a measureable effect on AMF under high-AOD and small relative azimuth angle (RAA) conditions. The diurnal effect of the NO2 profile is also examined and discussed.

Estimation of Surface NO2 Volume Mixing Ratio in Four Metropolitan Cities in Korea Using Multiple Regression Models with OMI and AIRS Data

Surface NO2 volume mixing ratio (VMR) at a specific time (13:45 Local time) (NO2 VMRST) and monthly mean surface NO2 VMR (NO2 VMRM) are estimated for the first time using three regression models with Ozone Monitoring Instrument (OMI) data in four metropolitan cities in South Korea: Seoul, Gyeonggi, Daejeon, and Gwangju. Relationships between the surface NO2 VMR obtained from in situ measurements (NO2 VMRIn-situ) and tropospheric NO2 vertical column density obtained from OMI from 2007 to 2013 were developed using regression models that also include boundary layer height (BLH) from Atmospheric Infrared Sounder (AIRS) and surface pressure, temperature, dew point, and wind speed and direction. The performance of the regression models is evaluated via comparison with the NO2 VMRIn-situ for two validation years (2006 and 2014). Of the three regression models, a multiple regression model shows the best performance in estimating NO2 VMRST and NO2 VMRM. In the validation period, the average correlation coefficient (R), slope, mean bias (MB), mean absolute error (MAE), root mean square error (RMSE), and percent difference between NO2 VMRIn-situ and NO2 VMRST estimated by the multiple regression model are 0.66, 0.41, −1.36 ppbv, 6.89 ppbv, 8.98 ppbv, and 31.50%, respectively, while the average corresponding values for the other two models are 0.75, 0.41, −1.40 ppbv, 3.59 ppbv, 4.72 ppbv, and 16.59%, respectively. All three models have similar performance for NO2 VMRM, with average R, slope, MB, MAE, RMSE, and percent difference between NO2 VMRIn-situ and NO2 VMRM of 0.74, 0.49, −1.90 ppbv, 3.93 ppbv, 5.05 ppbv, and 18.76%, respectively.

Retrieval Accuracy of HCHO Vertical Column Density from Ground-Based Direct-Sun Measurement and First HCHO Column Measurement Using Pandora

In the present study, we investigate the effects of signal to noise (SNR), slit function (FWHM), and aerosol optical depth (AOD) on the accuracy of formaldehyde (HCHO) vertical column density (HCHOVCD) using the ground-based direct-sun synthetic radiance based on differential optical absorption spectroscopy (DOAS). We found that the effect of SNR on HCHO retrieval accuracy is larger than those of FWHM and AOD. When SNR = 650 (1300), FWHM = 0.6, and AOD = 0.2, the absolute percentage difference (APD) between the true HCHOVCD values and those retrieved ranges from 54 (30%) to 5% (1%) for the HCHOVCD of 5.0 × 1015 and 1.1 × 1017 molecules cm−2, respectively. Interestingly, the maximum AOD effect on the HCHO accuracy was found for the HCHOVCD of 3.0 × 1016 molecules cm−2. In addition, we carried out the first ground-based direct-sun measurements in the ultraviolet (UV) wavelength range to retrieve the HCHOVCD using Pandora in Seoul. The HCHOVCD was low at 12:00 p.m. local time (LT) in all seasons, whereas it was high in the morning (10:00 a.m. LT) and late afternoon (4:00 p.m. LT), except in winter. The maximum HCHOVCD values were 2.68 × 1016, 3.19 × 1016, 2.00 × 1016, and 1.63 × 1016 molecules cm−2 at 10:00 a.m. LT in spring, 10:00 a.m. LT in summer, 1:00 p.m. LT in autumn, and 9:00 a.m. LT in winter, respectively. The minimum values of Pandora HCHOVCD were 1.63 × 1016, 2.23 × 1016, 1.26 × 1016, and 0.82 × 1016 molecules cm−2 at around 1:45 p.m. LT in spring, summer, autumn, and winter, respectively. This seasonal pattern of high values in summer and low values in winter implies that photo-oxidation plays an important role in HCHO production. The correlation coefficient (R) between the monthly HCHOVCD values from Pandora and those from the Ozone Monitoring Instrument (OMI) is 0.61, and the slope is 1.25.

The effects of aerosol on the retrieval accuracy of NO2 slant column density

We investigate the effects of aerosol optical depth (AOD), single scattering albedo (SSA), aerosol peak height (APH), measurement geometry (solar zenith angle (SZA) and viewing zenith angle (VZA)), relative azimuth angle, and surface reflectance on the accuracy of NO2 slant column density using synthetic radiance. High AOD and APH are found to decrease NO2 SCD retrieval accuracy. In moderately polluted (5 × 1015 molecules cm−2 2 × 1016 molecules cm−2), even high AOD and APH values are found to have a negligible effect on NO2 SCD precision. In high AOD and APH conditions in clean NO2 regions, the R between true NO2 SCDs and those retrieved increases from 0.53 to 0.58 via co-adding four pixels spatially, showing the improvement in accuracy of NO2 SCD retrieval. In addition, the high SZA and VZA are also found to decrease the accuracy of the NO2 SCD retrieval.

First comparison of OMI‐DOAS total ozone using ground‐based observations at a megacity site in East Asia: Causes of discrepancy and improvement in OMI‐DOAS total ozone during summer

This study compares, for the first time, the total ozone columns derived from the Ozone Monitoring Instrument-Differential Optical Absorption Spectroscopy (OMI-DOAS algorithm) (TOCs-OMI) with those obtained from ground-based Brewer and Dobson spectrophotometers (TOCs-Ground) in Seoul, a megacity in northeast Asia, over the 3 years between 2008 and 2010. We found a seasonal mean underestimation of 2.68% (maximum 18.33% on a single day) in TOCs-OMI when compared with TOCs-Ground from Seoul, particularly during the summer seasons (June, July, and August) of our study period: 20 of the 30 days when this underestimation of TOCs-OMI was greatest occurred during the summer. The causes of such large underestimations in summer TOCs-OMI were investigated, and we found that the ghost column densities (GCDs) used in the current OMI-DOAS algorithm did not fully account for the tropospheric ozone amounts below the cloud top in Seoul, particularly during the summer season when surface ozone is enhanced due to active photochemical reactions. We propose the use of New TOCs-OMI based on New GCDs that were calculated using ozonesonde data for the limited number of days when such data were available. The mean bias errors (MBE) against the TOCs-Ground of the New TOCs-OMI and original TOCs-OMI were −0.60% and −2.16%, respectively, which demonstrates the greater accuracy of the New TOCs-OMI. To increase the amount of New TOCs-OMI data available for comparison with the TOCs-Ground data, the regression equation for the relationship between the ozonesonde data and OMI-DOAS cloud pressure data was used to increase the availability of New GCD data for each measurement date that TOCs-OMI data were available for. This procedure reduced the MBE of the original TOCs-OMI by 1.29%, 1.67%, and 1.29% in June, July, and August, respectively. The present study demonstrates that the underestimation of GCDs is one of the major causes of the underestimation of TOCs-OMI during the summer season and suggests that improvements could be achieved using the proposed correction for these GCDs.