Details of a Researcher - Hashiguchi, Akinori

Papers - Hashiguchi, Akinori

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Suppression of autophagy by CUB domain-containing protein 1 signaling is essential for anchorage-independent survival of lung cancer cells

Uekita, Takamasa, Fujii, Satoko, Miyazawa, Yuri, Hashiguchi, Akinori, Abe, Hitosi, Sakamoto, Michiie, Sakai, Ryuichi

CANCER SCIENCE (WILEY-BLACKWELL) 104 ( 7 ) 865 - 870 2013.07

Research paper (scientific journal), Joint Work, ISSN 1349-7006

CUB (C1r/C1s, urchin embryonic growth factor, BMP1) domain-containing protein 1 (CDCP1) has been implicated in promoting metastasis of cancer cells through several mechanisms, including the inhibition of anoikis, which is cell death triggered by the loss of extracellular matrix interactions. However, the mechanism inhibiting cell death regulated by CDCP1 remains elusive. Inhibition of CDCP1 expression using small interfering RNA (siRNA) induced the cell death of suspended cancer cells without cleaving caspase-3, a marker of apoptosis; cell death was not inhibited by a general caspase inhibitor, suggesting that the loss of CDCP1 induces caspase-independent cell death. In contrast, knockdown of CDCP1 as well as protein kinase C (PKC), a downstream effector of CDCP1, in a suspension culture of lung cancer cells resulted in marked induction of membranous microtubule-associated protein 1 light chain 3 (LC3)-II protein, a hallmark of autophagy, and caused the formation of an autophagosome structure visualized using green fluorescent protein-tagged LC3-II. Expression and phosphorylation of exogenous CDCP1 by Fyn kinase reduced the formation of autophagosomes and inhibited phosphorylation of CDCP1 by PP2, a Src kinase inhibitor or inhibited PKC by rottlerin, stimulating autophagosome formation. Moreover, death of suspended lung cancer cells induced by CDCP1 siRNA or by PKC siRNA was reduced by the autophagy inhibitor 3-methyladenine. CDCP1-PKC signaling plays a critical role in inhibiting autophagy, which is responsible for anoikis resistance of lung cancer cells.

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二期的根治手術を行った両側頸動脈小体腫瘍の1例

奥井, 文子, 冨田, 俊樹, 今西, 順久, 羽生, 昇, 佐藤, 陽一郎, 大塚, 邦憲, 小川, 郁, 橋口, 明典, 杜, ぶん林

頭頸部外科 (JAPAN SOCIETY FOR HEAD AND NECK SURGERY) 23 ( 1 ) 77 - 82 2013.06

Joint Work, ISSN 1349-581X

30歳男性の両側頸動脈小体腫瘍(左Shamblin I型、右Shamblin III型)に対し、二期的に根治手術を施行した。近医にてCT、MRIにより両側頸動脈小体腫瘍が疑われ、当院を紹介受診した。血管造影検査にて確定診断し、balloon Matas testは陰性であった。まずShamblin I型と思われた左側の手術を行い、頸動脈を温存し腫瘍を摘出した。5ヵ月後に行った右側の手術では、頸動脈分岐部を全周性に取り囲むShamblin III型であった。頸動脈分岐部を合併切除し、大伏在静脈により血行再建した。いずれも術前に栄養血管塞栓術を行った。血管造影検査と塞栓術を脳神経外科が、頸動脈再建術を血管外科が担当した。3科による集学的アプローチのもと、二期的に安全に両側腫瘍を摘出し得た症例を経験した。(著者抄録)

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Leukemia kidney infiltration can cause secondary polycythemia by activating hypoxia-inducible factor (HIF) pathway

Osumi, Tomoo, Awazu, Midori, Fujimura, Eriko, Yamazaki, Fumito, Hashiguchi, Akinori, Shimada, Hiroyuki

EUROPEAN JOURNAL OF PEDIATRICS (SPRINGER) 172 ( 6 ) 829 - 832 2013.06

Research paper (scientific journal), Joint Work, ISSN 0340-6199

Secondary polycythemia with increased production of erythropoietin (EPO) is known to occur in kidney diseases such as hydronephrosis and cystic disease, but the mechanism remains unclear. We report an 18-year-old female with isolated renal relapse of acute lymphoblastic leukemia accompanied by polycythemia. At the relapse, she presented with bilateral nephromegaly, mild renal dysfunction, and erythrocytosis with increased serum EPO levels up to 52.1 mIU/mL (9.1-32.8). Renal biopsy demonstrated diffuse lymphoblastic infiltration. The expression of hypoxia-inducible factor (HIF)-1 alpha, which is undetectable in normal kidney, was observed in the renal tubule epithelium compressed by lymphoblastic cells. These findings suggest that erythrocytosis was caused by renal ischemia due to leukemic infiltration. Polycythemia probably became apparent because of the lack of leukemic involvement of the bone marrow. With chemotherapy, the serum EPO level rapidly decreased to normal range accompanied by the normalization of kidney size and function. Renal leukemic infiltration may enhance EPO production, although not recognized in the majority of cases because of bone marrow involvement. C onclusion: Our case has clarified the mechanism of previously reported polycythemia associated with renal diseases as renal ischemia. Furthermore, we have added renal ischemia resulting from tumor infiltration to the list of causes of secondary polycythemia.

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Quantification of collagen and elastic fibers using whole-slide images of liver biopsy specimens

Abe, Tokiya, Hashiguchi, Akinori, Yamazaki, Ken, Ebinuma, Hirotoshi, Saito, Hidetsugu, Kumada, Hiromitsu, Izumi, Namiki, Masaki, Naohiko, Sakamoto, Michiie

PATHOLOGY INTERNATIONAL (WILEY-BLACKWELL) 63 ( 6 ) 305 - 310 2013.06

Research paper (scientific journal), Joint Work, ISSN 1320-5463

Histological evaluation of fibrosis after a liver biopsy is crucial for evaluating the pathology of patients with chronic liver disease. Previous studies have reported quantitative analyses of fibrosis using images of collagen-stained sections. However, analysis of these studies requires manual selection of the region of interest. In addition, the quantification of elastic fibers is not considered. The present study was conducted in order to measure both the collagen and elastic fiber area ratios using Elastica van Gieson-stained whole-slide images (WSIs) of liver biopsy specimens. High-resolution WSIs provide precise color classification, enabling accurate detection of even fine collagen and elastic fibers. To minimize the influence of pre-existing fibrous tissue, median area ratios of the collagen and elastic fibers were independently calculated from the image tiles of the WSIs. These median area ratios were highly concordant with area ratios after the pre-existing fibrous tissues were manually trimmed from the WSI. Further, these median area ratios were correlated with liver stiffness as measured by transient elastography (collagen: r=0.73 [P<0.01], elastic: r=0.53 [P<0.01]). Our approach to quantifying liver fibrosis will serve as an effective tool to evaluate liver diseases in routine practice.

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CTガイド下腎生検にて診断し得た無症候性IgG4関連疾患の一例

寺西悠, 矢澤聰, 小坂威雄, 水野隆一, 菊地栄次, 長田浩彦, 浅沼宏, 宮嶋哲, 中川健, 中塚誠之, 橋口明典, 向井万起男, 大家基嗣

泌尿器外科 (医学図書出版(株)) 26 ( 臨増 ) 761 - 761 2013.05

Joint Work, ISSN 0914-6180

定量的病理診断に向けた病理画像解析技術

山口, 雅浩, 長橋, 宏, 坂元, 亨宇, 橋口, 明典, 齋藤, 彰, 小林, 直樹

電子情報通信学会論文誌D: 情報・システム (The Institute of Electronics, Information and Communication Engineers) 96 ( 4 ) 782 - 789 2013.04

Joint Work, ISSN 1880-4535

ディジタルスライド(バーチャルスライド、Whole Slide Imagingとも呼ばれる)技術の進歩に伴い、病理診断のディジタル化が期待されている。ディジタル技術の導入により、従来の病理医の視覚に頼る定性的/半定量的な診断から、画像計測・認識技術に基づいた定量的病理診断が可能になる。本論文では、筆者らが研究・開発に取り組んでいる病理画像認識、高精度画像解析、色補正などの技術を例示し、定量的病理診断の確立に向けた課題などについて議論を行う。(著者抄録)

病理学病理デジタル画像技術の進歩デジタル病理学、パソロジー・インフォマティクス

橋口, 明典

医学のあゆみ 244 ( 6 ) 560 - 562 2013.02

Joint Work, ISSN 0039-2359

A histologic classification of IgA nephropathy for predicting long-term prognosis: emphasis on end-stage renal disease

Kawamura, Tetsuya, Joh, Kensuke, Okonogi, Hideo, Koike, Kentaro, Utsunomiya, Yasunori, Miyazaki, Yoichi, Matsushima, Masato, Yoshimura, Mitsuhiro, Horikoshi, Satoshi, Suzuki, Yusuke, Furusu, Akira, Yasuda, Takashi, Shirai, Sayuri, Shibata, Takanori, Endoh, Masayuki, Hattori, Motoshi, Akioka, Yuko, Katafuchi, Ritsuko, Hashiguchi, Akinori, Kimura, Kenjiro, Matsuo, Seiichi, Tomino, Yasuhiko

JOURNAL OF NEPHROLOGY 26 ( 2 ) 350 - 357 2013.01

Research paper (scientific journal), Joint Work, ISSN 1121-8428

A multicenter case-control study on IgA nephropathy (IgAN) was conducted to develop an evidence-based clinicopathologic classification of IgAN for predicting long-term renal outcome. Methods: Two hundred and eighty-seven patients including those with isolated hematuria or very mild proteinuria were enrolled. During a median follow-up of 9.3 years after biopsy, 49 patients (17%) progressed to end stage renal disease (ESRD). The associations between pathological variables and the need for chronic dialysis was examined by multivariate logistic regression analysis separately in patients who required dialysis earlier than 5 years (Early Progressors) and those who required dialysis within 5 to 10 years (Late Progressors) after biopsy. Results: Independent pathological variables predicting progression to ESRD were global sclerosis, segmental sclerosis and fibrous crescents for Early Progressors, and global sclerosis and cellular/fibrocellular crescents for Late Progressors. Four histological grades, HG 1, HG 2, HG 3 and HG 4, were established corresponding to &lt
25%, 25-49%, 50-74% and ≥75% of glomeruli exhibiting cellular or fibrocellular crescents, global sclerosis, segmental sclerosis or fibrous crescents. Eleven (7%) patients in HG 1, 12 (16%) in HG 2, 13 (31%) in HG 3 and 13 (68%) in HG 4 progressed to ESRD. Multivariate logistic analysis revealed that the risk of progression to ESRD was significantly higher in HG 2, 3 and 4 than in HG 1 (odds ratio, 2.4, 5.7 and 27.6 vs. 1.0). Conclusions: Our evidence-based histologic classification can identify the magnitude of the risk of progression to ESRD and is useful for predicting longterm renal outcome in IgAN. © 2012 Società Italiana di Nefrologia.

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Second-line chemotherapy for refractory small cell neuroendocrine carcinoma of the esophagus that relapsed after complete remission with irinotecan plus cisplatin therapy: Case report and review of the literature

Funakoshi, Shinsuke, Hashiguchi, Akinori, Teramoto, Kana, Miyata, Naoteru, Kurita, Satoshi, Adachi, Masayuki, Hamamoto, Yasuo, Higuchi, Hajime, Takaishi, Hiromasa, Hibi, Toshifumi

ONCOLOGY LETTERS (SPANDIDOS PUBL LTD) 5 ( 1 ) 117 - 122 2013.01

Research paper (scientific journal), Joint Work, ISSN 1792-1074

Small cell esophageal carcinoma is a type of small cell neuroendocrine carcinoma (SCNEC). SCNEC follows an aggressive clinical course and has a poor prognosis despite multidisciplinary therapies. A standard therapeutic strategy, including surgery, radiation and first-/second-line chemotherapy, has not yet been established for SCNEC. We present a case of SCNEC of the esophagus. A 66-year-old male with SCNEC as extensive disease was treated with 60 mg/m(2) cisplatin on day 1 plus 60 mg/m(2) irinotecan on days 1,8 and 15 every 4 weeks (IP) with successful complete remission. After the sixth course of IP, increasing pro-gastrin-releasing peptide (ProGRP) and nonspecific enolase (NSE) levels and intense fluorodeoxyglucose (FDG) avidity in a lymph node around the celiac artery (SUVmax, 8.3) indicated a refractory relapse of the disease. The patient was treated with three courses of amrubicin (AMR, 35 mg/m(2)) administered intravenously for 3 consecutive days every 3 weeks as a second-line chemotherapy. The ProGRP and NSE levels returned to the normal range I month after the initiation of second-line chemotherapy. However, the ProGRP and NSE levels were elevated after the third course of AMR, and PET-CT revealed progressive disease with liver metastasis and extended lymph node metastasis. As the patient remained asymptomatic, paclitaxel (100 mg/m(2)) was started as third-line chemotherapy. Patients with SCNEC of the esophagus with extensive disease should be treated with aggressive chemotherapy rather than surgery or radiation monotherapy. In the present case, tumor markers such as ProGRP and NSE were predictive of relapse and PET-CT was used to detect relapse. Further research is required to identify and exploit promising agents for resistant SCNEC.

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Computational grading of hepatocellular carcinoma using multifractal feature description

Atupelage, Chamidu, Nagahashi, Hiroshi, Yamaguchi, Masahiro, Abe, Tokiya, Hashiguchi, Akinori, Sakamoto, Michiie

COMPUTERIZED MEDICAL IMAGING AND GRAPHICS (PERGAMON-ELSEVIER SCIENCE LTD) 37 ( 1 ) 61 - 71 2013.01

Research paper (scientific journal), Joint Work, ISSN 0895-6111

Cancer grading has become an important topic in the field of image interpretation-based computer aided diagnosis systems. This paper proposes a novel feature descriptor to observe the characteristics of histopathological textures in a discriminative manner. The proposed feature descriptor utilizes fractal geometric analysis with four multifractal measures to construct an eight dimensional feature space. The proposed method employed a bag-of-feature-based classification model to discriminate a set of hepatocellular carcinoma images into five categories according to Edmondson and Steiner's grading system. Three feature selection methods were utilized to obtain the most discriminative features of codeword dictionary (codebook). Furthermore, we incorporated four other textural feature descriptors: Gabor-filters, LM-filters, local binary patterns, and Haralick, to obtain a benchmark of the accuracy of the classification. Two experiments were performed: (i) classifying non-neoplastic tissues and tumors and (ii) grading the hepatocellular carcinoma images into five classes. Experimental results indicated the significance of the multifractal features for describing the histopathological image texture because it outperformed other four feature descriptors. We graded a given ROI image by defining a threshold-based majority-voting rule and obtained an average correct classification rate around 95% for five classes classification. (c) 2012 Elsevier Ltd. All rights reserved.

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What is the Most Effective Tool for Detecting Prostate Cancer using a Standard MR Scanner?

Osugi, Kei, Tanimoto, Akihiro, Nakashima, Jun, Shinoda, Kazunobu, Hashiguchi, Akinori, Oya, Mototsugu, Jinzaki, Masahiro, Kuribayashi, Sachio

MAGNETIC RESONANCE IN MEDICAL SCIENCES (JPN SOC MAGNETIC RESONANCE IN MEDICINE) 12 ( 4 ) 271 - 280 2013

Research paper (scientific journal), Joint Work, ISSN 1347-3182

Purpose: We aimed to determine which of the following magnetic resonance (MR) imaging sequences is most effective for detecting prostate cancer: T-2-weighted (T2W), dynamic contrast-enhanced (DCE) T-1-weighted (TOW), or diffusion-weighted (DWI) imaging or apparent diffusion coefficient (ADC) mapping.
Materials and Methods: We included 37 male patients with prostate cancer who underwent MR imaging before radical prostatectomy in this retrospective study. Sixty-four foci (>5 mm in size; 35 in the peripheral zone [PZ], 29 in the transitional zone [TZ]) were histopathologically determined to be prostate cancer. We determined the capacity of T2W, DCE-T1W, DWI, ADC mapping alone, and the combination of ADC mapping with DWI, and conventional MR sequences to detect prostate cancer, including their sensitivity and positive predictive value (PPV), with reference to the results obtained in histopathological examinations of whole-mount sections.
Results: In the PZ, sensitivities were 31.4% (T2W), 37.1% (DCE-T1W), 51.4% (DWI), and 71.4% (ADC mapping); PPVs were 78.6% (T2W), 92.9% (DCE-T1W), 94.7% (DWI), and 96.0% (ADC mapping). Sensitivity was significantly higher of ADC mapping than other sequences. In the TZ, sensitivities were 55.1% (T2W), 44.8% (DCE-T1W), 82.8% (DWI), and 89.7% (ADC mapping); PPVs were 64.0% (T2W), 46.4% (DCE-T1W), 70.6% (DWI), and 72.2% (ADC mapping). Sensitivity was significantly higher of ADC mapping and DWI than conventional MR imaging, but there was no significant correlation between DWI/ADC mapping and T2W/DCE-T1W with respect to PPVs. Combining sequences did not improve sensitivity; only the PPV in the TZ improved when ADC mapping was combined with DCE-T1W.
Conclusion: ADC mapping is the most effective standard MR imaging tool for detecting prostate cancer. The addition of DCE-T1W may improve the PPV of ADC mapping for diagnosing cancer in the TZ.

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[Proposal of remission criteria for IgA nephropathy].

Matsuo S, Kawamura T, Suzuki Y, Joh K, Tomino Y, Horikoshi S, Nishino T, Yoshikawa N, Hattori M, Kimura K, Yasuda T, Shirai S, Shibata T, Yoshimura M, Utsunomiya Y, Endoh M, Sakamoto N, Matsushima M, Miyazaki Y, Yasuda Y, Yokoo T, Kagami S, Hataya H, Suzuki H, Matsuzaki K, Uchida S, Ito T, Shimizu A, Katafuchi R, Hisano S, Hashiguchi A

Nihon Jinzo Gakkai shi 55 ( 7 ) 1249 - 1254 2013

Joint Work, Accepted, ISSN 0385-2385

Computational Cell Classification Methodology for Hepatocellular Carcinoma

Chamidu Atupelage, Hiroshi Nagahashi, Fumikazu Kimura, Masahiro Yamaguchi, Tokiya Abe, Akinori Hashiguchi, Michiie Sakamoto

2013 INTERNATIONAL CONFERENCE ON ADVANCES IN ICT FOR EMERGING REGIONS (ICTER) (IEEE) 21 - 27 2013

Joint Work, Accepted, ISSN 2377-6854

Liver cancer is one of the frequent causes of death in the world. Hepatocellular carcinoma (HCC) is the most common histological type of primary liver cancer. HCC can be graded according to the malignancy of the tumors. Generally, a HCC grade is determined based on the characteristics of liver cell nuclei. This paper illustrates a methodology for classifying liver cell nuclei and grading HCC histological images quantitatively. The liver cell nuclei are classified in three consecutive tasks: nuclear segmentation, fibrous region detection, and nuclear classification. Each task utilizes the pixel-based textural features that are obtained through multifractal computation on digital images. First, the system segments every possible type of nuclei and excludes the nuclei within fibrous regions. Then, it classifies the rest of the nuclei to discriminate liver cell nuclei. For tumor grading, this method utilizes the following four categories of nuclear features: inner texture, geometry, spatial distribution, and surrounding texture. The proposed method was employed to classify a set of HCC histological images into five.

Automatic classification of hepatocellular carcinoma images based on nuclear and structural features

Tomoharu Kiyuna, Akira Saito, Atsushi Marugame, Yoshiko Yamashita, Maki Ogura, Eric Cosatto, Tokiya Abe, Akinori Hashiguchi, Michiie Sakamoto

MEDICAL IMAGING 2013: DIGITAL PATHOLOGY (SPIE-INT SOC OPTICAL ENGINEERING) 8676 2013

Joint Work, Accepted, ISSN 0277-786X

Diagnosis of hepatocellular carcinoma (HCC) on the basis of digital images is a challenging problem because, unlike gastrointestinal carcinoma, strong structural and morphological features are limited and sometimes absent from HCC images. In this study, we describe the classification of HCC images using statistical distributions of features obtained from image analysis of cell nuclei and hepatic trabeculae. Images of 130 hematoxylin-eosin (HE) stained histologic slides were captured at 20X by a slide scanner (Nanozoomer, Hamamatsu Photonics, Japan) and 1112 regions of interest (ROI) images were extracted for classification (551 negatives and 561 positives, including 113 well-differentiated positives). For a single nucleus, the following features were computed: area, perimeter, circularity, ellipticity, long and short axes of elliptic fit, contour complexity and gray level co-occurrence matrix (GLCM) texture features (angular second moment, contrast, homogeneity and entropy). In addition, distributions of nuclear density and hepatic trabecula thickness within an ROI were also extracted. To represent an ROI, statistical distributions (mean, standard deviation and percentiles) of these features were used. In total, 78 features were extracted for each ROI and a support vector machine (SVM) was trained to classify negative and positive ROIs. Experimental results using 5-fold cross validation show 90% sensitivity for an 87.8% specificity. The use of statistical distributions over a relatively large area makes the HCC classifier robust to occasional failures in the extraction of nuclear or hepatic trabecula features, thus providing stability to the system.

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A role of image processing technology for pathological image - A research project for quantitative pathology

Kobayashi, N., Sakamoto, M., Hashiguchi, A., Yamaguchi, M., Nagahashi, H., Saito, A.

Journal of the Institute of Image Electronics Engineers of Japan 42 ( 2 ) 2013

Joint Work, Accepted

An algorithm to evaluate the number of trabecular cell layers using nucleus arrangement applied to hepatocellular carcinoma

Hideki Komagata, Naoki Kobayashi, Ayako Katoh, Yasuka Ohnuki, Masahiro Ishikawa, Kazuma Shinoda, Masahiro Yamaguchi, Tokiya Abe, Akinori Hashiguchi, Michiie Sakamoto

MEDICAL IMAGING 2013: DIGITAL PATHOLOGY (SPIE-INT SOC OPTICAL ENGINEERING) 8676 2013

Joint Work, Accepted, ISSN 0277-786X

Recent advances in information technology have improved pathological virtual-slide technology and diagnostic support system studies of pathological images. Diagnostic support systems utilize quantitative indices determined by image processing. In previous studies on diagnostic support systems, carcinomatous areas of breast or lung have been recognized by the feature quantities of nuclear sizes, complexities, and internuclear distances based on graph theory, among other features. Improving recognition accuracy is important for the addition of new feature quantities. We focused on hepatocellular carcinoma (HCC) and investigated new feature quantities of histological images of HCC. One of the most important histological features of HCC is the trabecular pattern. For diagnosing cancer, it is important to recognize the tumor cell trabeculae. We propose a new algorithm for calculating the number of cell layers in histological images of HCC in tissue sections stained by hematoxylin and eosin. For the calculation, we used a Delaunay diagram that was based on the median points of nuclei, deleted the sinusoid and fat droplet regions from the Delaunay diagram, and counted the Delaunay lines while applying a thinning algorithm. Moreover, we experimented with the calculation of the number of cell layers with our method for different histological grades of HCC. The number of cell layers discriminated tumor differentiations and Edmondson grades; therefore, our algorithm may serve as an index of HCC for diagnostic support systems.

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Color correction for automatic fibrosis quantification in liver biopsy specimens.

Yuri Murakami, Tokiya Abe, Akinori Hashiguchi, Masahiro Yamaguchi, Akira Saito, Michiie Sakamoto

Journal of pathology informatics 4 36 - 36 2013

Joint Work

CONTEXT: For a precise and objective quantification of liver fibrosis, quantitative evaluations through image analysis have been utilized. However, manual operations are required in most cases for extracting fiber areas because of color variation included in digital pathology images. AIMS: The purpose of this research is to propose a color correction method for whole slide images (WSIs) of Elastica van Gieson (EVG) stained liver biopsy tissue specimens and to realize automated operation of image analysis for fibrosis quantification. MATERIALS AND METHODS: Our experimental dataset consisted of 38 WSIs of liver biopsy specimens collected from 38 chronic viral hepatitis patients from multiple medical facilities, stained with EVG and scanned at ×20 using a Nano Zoomer 2.0 HT (Hamamatsu Photonics K.K., Hamamatsu, Japan). Color correction was performed by modifying the color distribution of a target WSI so as to fit to the reference, where the color distribution was modeled by a set of two triangle pyramids. Using color corrected WSIs; fibrosis quantification was performed based on tissue classification analysis. STATISTICAL ANALYSIS USED: Spearman's rank correlation coefficients were calculated between liver stiffness measured by transient elastography and median area ratio of collagen fibers calculated based on tissue classification results. RESULTS: Statistical analysis results showed a significant correlation r = 0.61-0.68 even when tissue classifiers were trained by using a subset of WSIs, while the correlation coefficients were reduced to r = 0.40-0.50 without color correction. CONCLUSIONS: Fibrosis quantification accompanied with the proposed color correction method could provide an objective evaluation tool for liver fibrosis, which complements semi-quantitative histologic evaluation systems.

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Automatic segmentation of hepatocellular structure from HE-stained liver tissue

Masahiro Ishikawa, Sercan Taha Ahi, Yuri Murakami, Fumikazu Kimura, Masahiro Yamaguchi, Tokiya Abe, Akinori Hashiguchi, Michiie Sakamoto

MEDICAL IMAGING 2013: DIGITAL PATHOLOGY (SPIE-INT SOC OPTICAL ENGINEERING) 8676 2013

Joint Work, Accepted, ISSN 0277-786X

The analysis of hepatic tissue structure is required for quantitative assessment of liver histology. Especially, a cord-like structure of liver cells, called trabecura, has important information in the diagnosis of hepatocellular carcinoma (HCC). However, the extraction of trabeculae is thought to be difficult because liver cells take on various colors and appearances depending on tissue conditions. In this paper, we propose an approach to extract trabeculae from images of hematoxyline and eosin stained liver tissue slide by extracting the rest of trabeculae: sinusoids and stromal area. The sinusoids are simply extracted based on the color information, where the image is corrected by an orientation selective filtering before segmentaion. The stromal area mainly consists of fiber, and often includes lymphocytes densely. Therefore, in the proposed method, fiber region and lymphocytes are extracted separately, then, stromal region is determined based on the extracted results. The determination of stroma is performed based on superpixels, to obtain precise boundaries. Once the regions of sinusoids and stroma are obtained, trabeculae can be segmented as the remaining region. The proposed method was applied to 10 test images of normal and HCC liver tissues, and the results were evaluated based on the manual segmentation. As a result, we confirmed that both sensitivity and specificity of the extraction of trabeculae reach around 90%.

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Classification of Prostate Histopathology Images Based on Multifractal Analysis

Atupelage, Chamidu, Nagahashi, Hiroshi, Yamaguchi, Masahiro, Abe, Tokiya, Hashiguchi, Akinori, Sakamoto, Michiie

IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS (IEICE-INST ELECTRONICS INFORMATION COMMUNICATIONS ENG) E95D ( 12 ) 3037 - 3045 2012.12

Research paper (scientific journal), Joint Work, Accepted, ISSN 0916-8532

Histopathology is a microscopic anatomical study of body tissues and widely used as a cancer diagnosing method. Generally, pathologists examine the structural deviation of cellular and sub-cellular components to diagnose the malignancy of body tissues. These judgments may often subjective to pathologists' skills and personal experiences. However, computational diagnosis tools may circumvent these limitations and improve the reliability of the diagnosis decisions. This paper proposes a prostate image classification method by extracting textural behavior using multifractal analysis. Fractal geometry is used to describe the complexity of self-similar structures as a non-integer exponent called fractal dimension. Natural complex structures (or images) are not self-similar, thus a single exponent (the fractal dimension) may not be adequate to describe the complexity of such structures. Multifractal analysis technique has been introduced to describe the complexity as a spectrum of fractal dimensions. Based on multifractal computation of digital imaging, we obtain two textural feature descriptors; i) local irregularity: alpha and ii) global regularity: f(alpha). We exploit these multifractal feature descriptors with a texton dictionary based classification model to discriminate cancer/non-cancer tissues of histopathology images of H&E stained prostate biopsy specimens. Moreover, we examine other three feature descriptors; Gabor filter bank, LM filter bank and Haralick features to benchmark the performance of the proposed method. Experiment results indicated that the performance of the proposed multifractal feature descriptor outperforms the other feature descriptors by achieving over 94% of correct classification accuracy.

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微小変化型ネフローゼ症候群を認めた多発性骨髄腫の1例

吉藤歩, 篠村裕之, 脇野修, 徳山博文, 橋口明典, 鷲田直輝, 林晃一, 伊藤裕

日本腎臓学会誌 ((一社)日本腎臓学会) 54 ( 6 ) 732 - 732 2012.08

Joint Work, ISSN 0385-2385

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