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Ino Y.,National Cancer Center Research Institute | Yamazaki-Itoh R.,National Cancer Center Research Institute | Shimada K.,National Cancer Center Hospital | Iwasaki M.,National Cancer Center Research Center for Cancer Prevention and Screening | And 3 more authors.
British Journal of Cancer | Year: 2013

Background:The host immune reaction is represented by immune/inflammatory cell infiltrates. Here we systematically analysed tumour-infiltrating immune/inflammatory cells in pancreatic ductal carcinoma (PDC) and evaluated their clinicopathological impact.Methods:Using immunohistochemistry, we examined tumour-infiltrating CD68 + pan-macrophages, HLA-DR + CD68 + M1 macrophages (M1), CD163 + or CD204 + M2 macrophages (M2), CD66b + neutrophils (Neu), CD4 + T cells (CD4 + T), CD8 + T cells (CD8 + T), and FOXP3 + CD4 + regulatory T cells (Treg) in 212 cases of PDC, and conducted correlation and survival analyses using the Kaplan-Meier method and Cox proportional hazards model.Results:Higher levels of tumour-infiltrating pan-macrophages, M2, Neu, or the ratio of Tregs to CD4 + T (%Treg) were significantly associated with shorter survival, whereas higher levels of tumour-infiltrating CD4 + T, CD8 + T, or the ratio of M1 to pan-macrophages (%M1) were significantly associated with longer survival. Survival analysis of pairs of these variables revealed that some of the resulting patient groups had exclusively longer survival. We then connected the apparently related factors, and two significant variables emerged: tumour-infiltrating CD4 + T high /CD8 + T high /%Treg low and tumour-infiltrating %M1 high /M2 low. Multivariate survival analysis revealed that these variables were significantly correlated with longer survival and had a higher hazard ratio.Conclusion:Tumour-infiltrating CD4 + T high /CD8 + T high /%Treg low and %M1 high /M2 low are independent prognosticators useful for evaluating the immune microenvironment of PDC. © 2013 Cancer Research UK. Source


Kawata Y.,Tokushima University | Niki N.,Tokushima University | Umetani K.,Japan Synchrotron Radiation Research Institute | Nakano Y.,Shiga University of Medical Science | And 3 more authors.
Progress in Biomedical Optics and Imaging - Proceedings of SPIE | Year: 2013

Small pulmonary vessel networks (arteriole and venule) provide a significant insight into understanding the alveolated structure in the human acinus. However, automatic extraction of small pulmonary vessels is a challenge due to the presence of abundant complexities in the networks. We thereby introduce a stochastic framework, a particle filter, to track small vessels running inside alveolar walls in human acinus using synchrotron radiation micro CT (SRμCT) images. We formulated vessel tracking using a non-linear sate space which captures both smoothness of the trajectories and intensity coherence along vessel orientations. In the particle filter scheme, we computed the proposal distribution by using the orientation distribution function (ODF), which is estimated as the combination of three different profiles; appearance, directional, and medialness profiles. To model the posterior distribution, we obtained voxels inside cylindrical tube which encapsulated a local vessel part. We constructed the prior distribution using the von Mises-Fisher (vMF) distribution on a unit sphere. At the same time, we detected branches of a vessel by analyzing the dominance of local vessel orientations through the vMF mean shift algorithm. Given a seed point, the method is able to locate the optimal vessel networks inside alveolar walls. Applying the method to the SRμCT images of the human lung acini, we demonstrate its potential usefulness to extract the trajectories of small pulmonary vessels running inside the alveolar walls. © 2013 SPIE. Source


Kawata Y.,Tokushima University | Niki N.,Tokushima University | Ohmatsu H.,Tokushima University | Kusumoto M.,National Cancer Center Hospital East | And 4 more authors.
Medical Physics | Year: 2012

Purpose: Quantification of the CT appearance of non-small cell lung cancer (NSCLC) is of interest in a number of clinical and investigational applications. The purpose of this work is to present a quantitative five-category (, , and ) classification method based on CT histogram analysis of NSCLC and to determine the prognostic value of this quantitative classification. Methods: Institutional review board approval and informed consent were obtained at the National Cancer Center Hospital. A total of 454 patients with NSCLC (maximum lesion size of 3 cm) were enrolled. Each lesion was measured using multidetector CT at the same tube voltage, reconstruction interval, beam collimation, and reconstructed slice thickness. Two observers segmented NSCLC nodules from the CT images by using a semi-automated three-dimensional technique. The two observers classified NSCLCs into one of five categories from the visual assessment of CT histograms obtained from each nodule segmentation result. Interobserver variability in the classification was computed with Cohen's statistic. Any disagreements were resolved by consensus between the two observers to define the gold standard of the classification. Using a classification and regression tree (CART), the authors obtained a decision tree for a quantitative five-category classification. To assess the impact of the nodule segmentation on the classification, the variability in classifications obtained by two decision trees for the nodule segmentation results was also calculated with the Cohen's statistic. The authors calculated the association of recurrence with prognostic factors including classification, sex, age, tumor diameter, smoking status, disease stage, histological type, lymphatic permeation, and vascular invasion using both univariate and multivariate Cox regression analyses. Results: The values for interobserver agreement of the classification using two nodule segmentation results were 0.921 (P 0.001) and 0.903 (P 0.001), respectively. The values for the variability in the classification task using two decision trees were 0.981 (P 0.001) and 0.981 (P 0.001), respectively. All the NSCLCs were classified into one of five categories (type , n 8; type , n 38; type , n 103; type , n 112; type , n 193) by using a decision tree. Using a multivariate Cox regression analysis, the classification (hazard ratio 5.64; P 0.008) and disease stage (hazard ratio 8.33; P 0.001) were identified as being associated with an increased recurrence risk. Conclusions: The quantitative five-category classifier presented here has the potential to provide an objective classification of NSCLC nodules that is strongly correlated with prognostic factors. © 2012 American Association of Physicists in Medicine. Source


Kawata Y.,Tokushima University | Hosokawa T.,Tokushima University | Nikia N.,Tokushima University | Umetani K.,Japan Synchrotron Radiation Research Institute | And 4 more authors.
Progress in Biomedical Optics and Imaging - Proceedings of SPIE | Year: 2011

The recognition of abnormalities relative to the lobular anatomy has become increasingly important in the diagnosis and differential diagnosis of lung abnormalities at clinical routines of CT examinations. This paper aims for a 3-D microstructural analysis of the pulmonary acinus with isotropic spatial resolution in the range of several micrometers by using micro CT. Previously, we demonstrated the ability of synchrotron radiation micro CT (SRμCT) using offset scan mode in microstructural analysis of the whole part of the secondary pulmonary lobule. In this paper, we present a semiautomatic method to segment the acinar and subacinar airspaces from the secondary pulmonary lobule imaged by the SRμCT. The method began with a segmentation of the tissues such as pleural surface, interlobular septa, alveola wall, or vessel using threshold technique and 3-D connected component analysis. Follow-on stages then constructed 3-D air space separated by tissues and represented branching patterns of airways and airspaces distal to the terminal bronchiole. Finally, a graph-partitioning approach isolated acini whose stems were interactively defined as the terminal bronchiole in the secondary pulmonary lobule. Additionally, the isolated acinar airspace was segmented into subacini in which the airway was considered as the stem using the graph-partitioning approach. Results demonstrate that the proposed method can extract several acinar airspaces from the 3-D SRμCT image of secondary pulmonary lobule and that the extracted acinar airspace enable an accurate quantitative description of the anatomy of the human acinus for interpretation of the basic unit of pulmonary structure and function.© 2011 SPIE. Source


Kawata Y.,Tokushima University | Kageyama K.,Tokushima University | Niki N.,Tokushima University | Umetani K.,Japan Synchrotron Radiation Research Institute | And 4 more authors.
Progress in Biomedical Optics and Imaging - Proceedings of SPIE | Year: 2010

The recognition of abnormalities relative to the lobular anatomy has become increasingly important in the diagnosis and differential diagnosis of lung abnormalities at clinical routines of CT examinations. The purpose of this study is to analyze microstructure of the lobular anatomy with isotropic spatial resolution in the range of several micrometers to quantitatively describe relation between the architectures and abnormalities. Recent commercial micro CT scanners play a vital role in imaging the lung micro-architectures. However, only a limited number of attempts have been conducted because of difficulties to image the secondary pulmonary lobule beyond the scan field of view and the limited contrast lung parenchyma. This paper demonstrates the ability of synchrotron radiation micro CT (SRμCT) using offset scan mode in microstructural analysis of the secondary pulmonary lobule. The inflated and fixed lung specimen was imaged with resolution of 5.87x5.87x5.87 μm 3 by using offset scan mode of the SRμCT (15 keV) at the synchrotron radiation facility (SPring-8). The 3-D SRμCT image which was stacked 2624 slices (each slice:7287x7287 voxels) covered the secondary pulmonary lobule being included in the lung specimen. A proper threshold value for appropriate segmentation was interactively determined to the volume of interest representing the secondary pulmonary lobule. Following transformation of the segmented binary image to a skeletonized surface representation, each voxel was classified as a curve, surface, or junction. The interlobular septa region was extracted interactively by using the voxel classification result which offered geometrical information. Each component of lobular airway, artery, and vein were extracted by using a seeding technique, considering equal attenuation values and connectivity. The resulting volumetric image from the SRμCT using offset scan mode made 3-D microstructural analysis of the lobular anatomy possible. © 2010 Copyright SPIE - The International Society for Optical Engineering. Source

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