Cell membrane dynamics based on membrane morphology and fluidity are critical for cancer metastasis. We imaged the membrane dynamics of tumor cells in mice with a high spatial precision of < 9 nm under a confocal microscope. A metastasis-promoting factor on the cell membrane, protease-activated receptor 1 (PAR1), was labeled with quantum dots (QDs) conjugated with an anti-PAR1 antibody (PAR1 ab-QDs). Movements of cancer cells and PAR1 were clearly observed in tumors. We found that the tumor cells showed increases in membrane fluidity (over 1000-fold) and formed local pseudopodia in the process of metastasis, suggesting that membrane fluidity and morphological changes are critical for metastasis. Moreover, to estimate the PAR1-expression level in breast cancer tissues of human epidermal growth factor receptor 2 (HER2)-negative patients, user-friendly immunohistochemistry with high quantitative sensitivity was developed using autofluorescence-subtracted images and single-particle quantum dot imaging of PAR1 ab-QDs. The immunohistochemistry showed that PAR1 expression correlated strongly with relapse-free survival in HER2-negative breast cancer patients. Thus, this result suggests that our new method to diagnose PAR1 expression levels by immunohistochemistry with PAR1 ab-QDs may facilitate clinical decisions in HER2-negative patients.
Recent reports indicate that 90% of cancer deaths is caused by cancer metastasis. Cancer metastasis occurs in the body when so-called circulating tumor cells (CTCs) migrate from one place to another. Hence the identification of CTCs provides an opportunity to detect cancer before metastasis. Unfortunately, conventional optical microscopy is incapable of detecting CTCs from the patients' blood because of their extreme rareness (only a few in a billion blood cells). This technological problem can be solved by high-throughput image cytometry—a technique that integrates microfluidics and optical time-stretch imaging. Its ultra-high throughput (up to 100,000 cells/s) and high specificity make it possible to capture the few target cells from a large heterogeneous population with high efficiency. In addition to its ability to provide morphological information, it can be readily integrated with a simultaneous multi-color fluorescence detector for the acquisition of chemical characteristics of the target cells. In this review article, we discuss the principles of optical time-stretch imaging and its application to cancer detection.
Recently, it has been important to understand the tumor microenvironment for invasion and metastasis of cancer. We could analyze the cancer cell dynamics multi-dimensionally by intravital imaging without disturbing their microenvironment. Therefore, many attempts have been made to understand the behavior of cancer cells together with their microenvironment using this technique and to clarify the related molecules and pathology. Here we present our latest data on cancer cell dynamics, and discuss the applications of this novel methodology for future studied in the field of cancer.
The aim of this review is to introduce history, basis and current status of in vivo diagnostic imaging technologies, and discuss future directions of in vivo cancer molecular imaging research and development especially toward practical and useful clinical applications. I focus on two concepts; multiplexed imaging and activatable probes, for improving specificity and sensitivity of the molecular imaging technology. Additionally, I introduce a newly developed super-specific cancer therapy, near infrared photo-immunotherapy, which is evolved from the bio-imaging technology that based on integrated multidisciplinary sciences.
Main advantages of the optical imaging technique achieving high spatio-temporal resolution, non-radiation, less cytotoxicity and low cost with small devices as compared to conventional clinical imaging techniques such as CT, MRI and PET. In particular, near infrared (NIR) fluorescence imaging enables us to visualize deep portion of tissues due to the excellent penetration in vivo. We developed a NIR fluorophore-conjugated anti-Carcinoembryonic antigen (CEA) antibody for mice bearing tumor of CEA expressing cells, and demonstrated in vivo optical imaging by two-photon excitation microscopy. In the result, CEA-expressing cancer cells were specifically detected in vivo. In preclinical applications, the lymph node micrometastasis was also successfully visualized by two-photon excitation microscopy. These results suggest that two-photon excitation microscopy in combination with the immunoconjugated NIR fluorescence probe could be widely adapted to cancer detection in clinical settings or various cancer metastasis model to reveal the mechanism of cancer metastasis and to visualize microenvironment which may consist of cancer cells and stroma cells.
It is revealed that circulating tumor cells (CTCs) are clinically significant in 2004 after the existence is firstly reported in 1869. CTCs are thought to be important because they play a role for cancer metastasis and they are expected to be utilized for prognostic prediction, monitoring and judgement of response to treatment, evaluation of drug efficacy, genetic analysis, and personalized medicine. However their extremely rareness poses a barrier to detect and research them. Although CTC detection systems are commercialized, they rely on their size or surface makers. We have developed optical phase-contrast 3-dimensional tomographic imaging flow cytometry which is intended for detecting CTCs among blood cells based on morphological difference inside cells. We report this imaging technology in comparison with X-ray CT.
To clarify whether use of a low-cost handy 3D scanner can alternate the primary step for making below knee prosthesis, we compared accuracy of 3D model with the handy 3D scanner with that from CT images. The accuracy of the 3D scanner was favorable. In such, we suggest that the handy 3D scanner might alternate the first step for making below knee prosthesis.
Compressed sensing is a technique that acquires less MRI signals than conventional reconstruction, and thus reduces scan times. Quality of MR image in compressed sensing depends strongly on the method used for the undersampling of phase-encoding. However, optimization of the image quality using an actual machine involves time and effort. The purpose of this work is to establish a relationship between the method of undersampling and the image quality in the Cartesian setup using a MRI simulator. This simulator enabled effective investigation on influence of three factors on the quality of image: ratio of the constantly selected central portion of phase-encoding to full phase-encoding in k-space, shape of a probability density function for randomly selecting phase-encoding, and randomness of the phase-encoding. The quality was estimated using RMSE, inclination, SSIM, and SNR. The results show that the image quality is decided by both the ratio of the central portion and the full width at half maximum (FWHM) of normal distribution for randomly selected phase-encodings and that randomness of phase-encoding exhibits less influence on the image quality and has a small positive correlation with the image quality.
Two types of rib primary bone tumor are observed, osteolytic and osteosclerotic. The osteolytic type destroys bone as it grows and has CT values lower than those of the liver and other organs. The osteosclerotic type protrudes from the bone surface, and because it has CT values similar to those of bone areas, borders between tumor and skeleton are difficult to distinguish, making separating the two areas difficult, and therefore presenting challenges in quantifying volumetric measurement and other operations. In this study, osteolytic/osteosclerotic evaluation and detection of tumors were conducted, and volumetric measurement conducted by means of left-right skeleton comparison. Volumetric measurement employing left-right volume skeleton comparison was used for osteosclerotic tumors; for osteolytic tumors, a tumor extraction technique is proposed that exhibits high precision superior to that of the conventional area expansion method, which accomplished through use of a discriminator that employs a support vector machine (SVM). Rib left-right symmetry was investigated using healthy cases. Osteolytic/osteosclerotic evaluation and detection of tumors and volumetric measurement were conducted using four osteolytic tumor cases and one osteosclerotic tumor case. Volumetric differences between corresponding left and right healthy ribs were kept within 10%, enabling acquisition of clear volumetric differences with symptomatic cases. Additionally, bone tumor volumes could be measured with almost no error by obtaining corresponding rib differentials, thereby demonstrating that tumor detection can be performed.
Recently, region-setting CT has been studied as an ROI imaging method. This technique can strongly reduce the radiation dose by limiting the irradiation field. For this reason, mathematical studies to reduce the truncation artifact have been conducted. However, no experimental studies have so far been performed. In this study, we developed a two-dimensional region-setting CT system and performed basic evaluations, such as those of its imaging properties. As an experimental system, we developed a micro-CT system with two-channel active collimators. In this way, truncated projection data only including selected region can be captured. Empty regions of the collimated projection data were corrected. Finally, the slice image was obtained by image reconstruction using the filtered back projection algorithm. In the experiments, the shape reproducibility and image quality of the reconstruction image were evaluated and were found to be similar to those of conventional scan images. In addition, radiation dose of the proposed method was reduced strongly. These results indicate that this system may be useful for the dose reduction of X-ray CT systems.
Computed tomography (CT) is one of the widely used imaging modalities to monitor the development and progression of lung cancer. Computer-aided detection/diagnosis (CADe/CADx) systems based on the multidisciplinary computational anatomy models support clinicians to detect early-stage cancers and decide risk-adaptive treatments. These CADe/CADx systems may have a large impact as imaging is routinely used in clinical practice, in all stages of diagnoses and treatment, providing an unprecedented opportunity to improve medical decision-support. This paper presents current status and issues of computer aided diagnosis for lung cancer CT screening.
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