Three-Dimensional (3D) Imaging of Tumor Angiogenesis and its Inhibition:  Evaluation of Tumor Vascular-Targeting Agent Efficacy in the DMBA-induced Rat Breast Cancer Model by Confocal Laser Scanning Microscopy (CLSM)

Itoh, Johbu; Yasumura, Kazuhiko; Ogawa, Kenji; Kawai, Kenji; Serizawa, Akihiko; Yamamoto, Yukito; Osamura, Yoshiyuki

doi:10.1267/ahc.36.27

Cited by 4 publications

(3 citation statements)

References 43 publications

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“…The residual errors X, Y and (X, Y) are computed as a sum of squared differences between the transformed coordinates of image 1 and the user chosen coordinates in image 2. The original residual error (X, Y) before any transformation was equal to 12 …”

Section: Transformation Modelmentioning

confidence: 99%

“…In order to demonstrate the issues related to selecting registration variables, we consider 3D volume reconstruction of blood vessels in histological sections of uveal melanoma 10 from paraffin-embedded serial sections labeled with antibodies to CD34 and laminin and studied by confocal laser scanning microscopy (CLSM) imagery 11,12 . The set of spatial tiles is acquired by CLSM and consists of images that came from (1) one cross section (same axial coordinate) in different lateral coordinates or (2) multiple cross sections of a 3D volume (different axial coordinates).…”

Section: Introductionmentioning

confidence: 99%

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Supporting registration decisions during 3D medical volume reconstructions

2006

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We propose a methodology for making optimal registration decisions during 3D volume reconstruction in terms of (a) anticipated accuracy of aligned images, (b) uncertainty of obtained results during the registration process, (c) algorithmic repeatability of alignment procedure, and (d) computational requirements. We researched and developed a web-enabled, web services based, data-driven, registration decision support system. The registration decisions include (1) image spatial size (image sub-area or entire image), (2) transformation model (e.g., rigid, affine or elastic), (3) invariant registration feature (intensity, morphology or a sequential combination of the two), (4) automation level (manual, semiautomated, or fully-automated), (5) evaluations of registration results (multiple metrics and methods for establishing ground truth), and (6) assessment of resources (computational resources and human expertise, geographically local or distributed). Our goal is to provide mechanisms for evaluating the tradeoffs of each registration decision in terms of the aforementioned impacts. First, we present a medical registration methodology for making registration decisions that lead to registration results with well-understood accuracy, uncertainty, consistency and computational complexity characteristics. Second, we have built software tools that enable geographically distributed researchers to optimize their data-driven registration decisions by using web services and supercomputing resources. The support developed for registration decisions about 3D volume reconstruction is available to the general community with the access to the NCSA supercomputing resources. We illustrate performance by considering 3D volume reconstruction of blood vessels in histological sections of uveal melanoma from serial fluorescent labeled paraffin sections labeled with antibodies to CD34 and laminin. The specimens are studied by fluorescence confocal laser scanning microscopy (CLSM) images.

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Section: Transformation Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Supporting registration decisions during 3D medical volume reconstructions

2006

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“…The 7,12-dimethylbenz[a]anthracene (DMBA)-induced rat mammary tumor has been frequently used as an experimental rat model of breast cancer [23], because this tumor is an estrogen-sensitive angiogenic tumor [20,24,27,29] and has similar reactivity to treatment for human breast cancer, such as anti-estrogen drugs and ovariectomy [30]. Malignant lesions of this mammary tumor are histopathologically classified as invasive ductal carcinoma, which consists almost completely of homogeneous tumor cells and has very few myoepithelial cells [43].…”

Section: Introductionmentioning

confidence: 99%

Characteristic Patterns of VEGF, Integrins, ER.ALPHA. and HER2 Immunoreactivity Suggest Two Tumor Cell Populations in DMBA-Induced Rat Mammary Tumor

Inoue

Kaidoh

Inoué

et al. 2005

Acta Histochem. Cytochem

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Functional molecular morphology of anterior pituitary cells, from hormone production to intracellular transport and secretion

et al. 2011

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Combined in situ hybridization (ISH) and immunohistochemistry (IHC) under electron microscopy (EM-ISH & IHC) has sufficient ultrastructural resolution to provide two-dimensional images of subcellular localization of pituitary hormone and its mRNA in a pituitary cell. The advantages of semiconductor nanocrystals (Quantum dots; Qdots) and confocal laser scanning microscopy (CLSM) enable us to obtain three-dimensional images of the subcellular localization of pituitary hormone and its mRNA. Both EM-ISH & IHC and ISH & IHC using Qdots and CLSM are useful for understanding the relationship between protein and mRNA simultaneously in two or three dimensions. CLSM observation of rab3B and SNARE proteins such as SNAP-25 and syntaxin revealed that both rab3B and SNARE system proteins play an important role and work together as the exocytotic machinery in anterior pituitary cells. Another important issue is the intracellular transport and secretion of pituitary hormone. An experimental pituitary cell line, the GH3 cell, in which growth hormone (GH) is linked to enhanced yellow fluorescein protein (EYFP), has been developed. This stable GH3 cell secretes GH linked to EYFP upon being stimulated by Ca(2+) influx or Ca(2+) release from storage. This GH3 cell is useful for real-time visualization of the intracellular transport and secretion of GH. These three methods enable us to visualize consecutively the processes of transcription, translation, transport, and secretion of pituitary hormone.

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Three-Dimensional (3D) Imaging of Tumor Angiogenesis and its Inhibition: Evaluation of Tumor Vascular-Targeting Agent Efficacy in the DMBA-induced Rat Breast Cancer Model by Confocal Laser Scanning Microscopy (CLSM)

Cited by 4 publications

References 43 publications

Supporting registration decisions during 3D medical volume reconstructions

Supporting registration decisions during 3D medical volume reconstructions

Characteristic Patterns of VEGF, Integrins, ER.ALPHA. and HER2 Immunoreactivity Suggest Two Tumor Cell Populations in DMBA-Induced Rat Mammary Tumor

Functional molecular morphology of anterior pituitary cells, from hormone production to intracellular transport and secretion

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