The utility of three-dimensional computed tomography for prediction of tumor invasiveness in clinical stage IA lung adenocarcinoma

BackgroundIt is critical to have an accurate measurement of solid tumor size in order to predict the invasiveness of small lung adenocarcinomas. Some lesions cannot be measured accurately via High-resolution computed tomography (HRCT) due to their irregular shape and unclear borders. For this reason, we evaluated the relative efficacy of three-dimensional (3D) CT for predicting invasive adenocarcinoma.MethodsWe evaluated 195 patients with clinical stage IA adenocarcinomas, including 109 with lesions documented as invasive that were surgically resected at our institute during 2017. All lesions were categorized as either (I) lesions that were difficult to evaluate (i.e., hazy lesions; HL) or (II) more typical lesions (TL). The relationships between solid tumor size as determined by HRCT, solid tumor volume as determined by 3D CT and pathologic diagnosis were evaluated.ResultsFifty-seven patients (29%) were diagnosed with HL. We set the cut-off value for the solid volume at 225 mm³ as predictive for invasive adenocarcinoma. When evaluating all 195 patients as a group, the accuracy, sensitivity, and specificity based on the solid tumor volume were similar to those based on the solid tumor size. When we limit our analysis to the HL group, the specificity based on solid tumor volume (65.5%) was higher than that based on solid tumor size (44.8%) with a difference that approached statistical significance (P=0.070).Conclusions3D CT was equivalent to HRCT for predicting invasive adenocarcinoma and may be particularly useful for diagnosing lesions that are difficult to evaluate on HRCT.     

Reverse Monte Carlo modeling for local structures of noble metal nanoparticles using high-energy XRD and EXAFS

Reverse Monte Carlo (RMC) modeling based on the total structure factor S(Q) obtained from high-energy X-ray diffraction (HEXRD) and the k³χ(k) obtained from extended X-ray absorption fine structure (EXAFS) measurements was employed to determine the 3-dimensional (3D) atomic-scale structure of Pt, Pd, and Rh nanoparticles, with sizes less than 5 nm, synthesized by photoreduction. The total structure factor and Fourier-transformed PDF showed that the first nearest neighbor peak is in accordance with that obtained from conventional EXAFS analysis. RMC constructed 3D models were analyzed in terms of prime structural characteristics such as metal-to-metal bond lengths, first-shell coordination numbers and bond angle distributions. The first-shell coordination numbers and bond angle distributions for the RMC-simulated metal nanoparticles indicated a face-centered cubic (fcc) structure with appropriate number density. Modeling disorder effects in these RMC-simulated metal nanoparticles also revealed substantial differences in bond-length distributions for respective nanoparticles.

3-Dimensional atomic-scale structure of metal nanoparticles obtained by RMC-based simulations using HEXRD and EXAFS data.