Computer-aided diagnosis of human brain tumor through MRI: A survey and a new algorithm

Computer-aided detection/diagnosis (CAD) systems can enhance the diagnostic capabilities of physicians and reduce the time required for accurate diagnosis. The objective of this paper is to review the recent published segmentation and classification techniques and their state-of-the-art for the human brain magnetic resonance images (MRI). The review reveals the CAD systems of human brain MRI images are still an open problem. In the light of this review we proposed a hybrid intelligent machine learning technique for computer-aided detection system for automatic detection of brain tumor through magnetic resonance images. The proposed technique is based on the following computational methods; the feedback pulse-coupled neural network for image segmentation, the discrete wavelet transform for features extraction, the principal component analysis for reducing the dimensionality of the wavelet coefficients, and the feed forward back-propagation neural network to classify inputs into normal or abnormal. The experiments were carried out on 101 images consisting of 14 normal and 87 abnormal (malignant and benign tumors) from a real human brain MRI dataset. The classification accuracy on both training and test images is 99% which was significantly good. Moreover, the proposed technique demonstrates its effectiveness compared with the other machine learning recently published techniques. The results revealed that the proposed hybrid approach is accurate and fast and robust. Finally, possible future directions are suggested.     

The chicken model of spontaneous ovarian cancer

The chicken is a unique experimental model for studying the spontaneous onset and progression of ovarian cancer (OVC). The prevalence of OVC in chickens can range from 5 to 35% depending on age, genetic strain, reproductive history, and diet. Furthermore, the chicken presents epidemiological, morphological, and molecular traits that are similar to human OVC making it a relevant experimental model for translation research. Similarities to humans include associated increased risk of OVC with the number of ovulations, common histopathological subtypes including high-grade serous, and molecular-level markers or pathways such as CA-125 expression and p53 mutation frequency.  Collectively, the similarities between chicken and human OVC combined with a tightly controlled genetic background and predictable onset window provides an outstanding experimental model for studying the early events and progression of spontaneous OVC tumors under controlled environmental conditions. This review will cover the existing literature on OVC in the chicken and highlight potential opportunities for further exploitation (e.g. biomarkers, prevention, treatment, and genomics).     

亲和型生物传感器对TNF-α/sTNFR-I相互作用的研究

应用亲和型生物传感器—Asys生物传感器实时监测不同浓度的肿瘤坏死因子-α(TNF-α)与可溶性肿瘤坏死因子受体-I(sTNFR-I)的亲和反应过程,并应用FASTfit软件对数据进行分析。结果表明:sTNFR-I以2.25 ng/mm2的密度固定于样品池敏感基片表面,TNF-α可与其发生特异性、浓度依赖性亲和反应,应用FASTfit软件进行数据拟合,并计算其反应的动力学常数,其反应符合二级动力学方程,结合速率常数kass=4.21×104L.mol-1.s-1,解离速率常数kd iss=2.12×10-2s-1,则解离平衡常数kD=5.05×10-7mol.L-1,结合平衡常数kA=1.99×106L.mol-1。应用IAsys传感器可实时监测结合和解离反应过程,操作简便、快速,是研究TNF-α和sTNFR相互作用动力学的有效方法。     

Detection and diagnosis of meningioma brain tumor using ANFIS classifier

Tumors are formed in brain due to the uncontrolled development of cells. These tumors can be cured if it is timely detected and by proper medication. This article proposes a computer‐aided automatic detection and diagnosis of meningioma brain tumors in brain images using Adaptive Neuro Fuzzy Inference System (ANFIS) classifier. The proposed system consists of feature extraction, classification, and segmentation and diagnosis sections. In this article, Grey level Co‐occurrence Matric (GLCM) and Grid features are extracted from the brain image and these features are classified using ANFIS classifier into normal or abnormal. Then, morphological operations are used to segment the abnormal regions in brain image. Based on the location of these abnormal regions in brain tissues, the segmented tumor regions are diagnosed.     

A fully automatic method for biological target volume segmentation of brain metastases

Leksell Gamma Knife is a mini‐invasive technique to obtain a complete destruction of cerebral lesions delivering a single high dose radiation beam. Positron Emission Tomography (PET) imaging is increasingly utilized for radiation treatment planning. Nevertheless, lesion volume delineation in PET datasets is challenging because of the low spatial resolution and high noise level of PET images. Nowadays, the biological target volume (BTV) is manually contoured on PET studies. This procedure is time expensive and operator‐dependent. In this article, a fully automatic algorithm for the BTV delineation based on random walks (RW) on graphs is proposed. The results are compared with the outcomes of the original RW method, 40% thresholding method, region growing method, and fuzzy c‐means clustering method. To validate the effectiveness of the proposed approach in a clinical environment, BTV segmentation on 18 patients with cerebral metastases is performed. Experimental results show that the segmentation algorithm is accurate and has real‐time performance satisfying the physician requirements in a radiotherapy environment.     

磁场和磁性材料在肿瘤治疗中的应用

首先详细介绍了恒定磁场、脉冲磁场、磁性药物微球和磁性微波吸收剂在肿瘤治疗中的原理和现状,然后分析了磁场和磁性材料在肿瘤治疗中的应用前景。     

Cytotoxicity Effects of Different Surfactant Molecules Conjugated to Carbon Nanotubes on Human Astrocytoma Cells

Phase contrast and epifluorescence microscopy were utilized to monitor morphological changes in human astrocytoma cells during a time-course exposure to single-walled carbon nanotube (SWCNT) conjugates with different surfactants and to investigate sub-cellular distribution of the nanotube conjugates, respectively. Experimental results demonstrate that cytotoxicity of the nanotube/surfactant conjugates is related to the toxicity of surfactant molecules attached on the nanotube surfaces. Both sodium dodecyl sulfate (SDS) and sodium dodecylbenzene sulfonate (SDBS) are toxic to cells. Exposure to CNT/SDS conjugates (0.5 mg/mL) for less than 5 min caused changes in cell morphology resulting in a distinctly spherical shape compared to untreated cells. In contrast, sodium cholate (SC) and CNT/SC did not affect cell morphology, proliferation, or growth. These data indicate that SC is an environmentally friendly surfactant for the purification and dispersion of SWCNTs. Epifluorescence microscopy analysis of CNT/DNA conjugates revealed distribution in the cytoplasm of cells and did not show adverse effects on cell morphology, proliferation, or viability during a 72-h incubation. These observations suggest that the SWCNTs could be used as non-viral vectors for diagnostic and therapeutic molecules across the blood–brain barrier to the brain and the central nervous system.     

Neurocognitive status in long-term survivors of childhood CNS malignancies: A report from the Childhood Cancer Survivor Study.

To assess neurocognitive functioning in adult survivors of childhood Central Nervous System (CNS) malignancy, a large group of CNS malignancy survivors were compared to survivors of non-CNS malignancy and siblings without cancer on a self-report instrument (CCSS-NCQ) assessing four factors, Task Efficiency, Emotional Regulation, Organization and Memory. Additional multiple linear regressions were used to assess the contribution of demographic, illness, and treatment variables to reported neurocognitive functioning in CNS malignancy survivors and the relationship of reported neurocognitive functioning to socioeconomic indicators. Survivors of CNS malignancy reported significantly greater neurocognitive impairment on all CCSS-NCQ factors than non-CNS cancer survivors or siblings (p     

中子俘获治疗的进展

近十多年来中子俘获治疗的实验和临床研究取得了令人满意的结果，这是由于中子束的质量提高和新的用于中子俘获治疗的化合物合成成功。此外，中子俘获的生物物理学研究将是今后的重点之一。本文就这３方面及中子俘获治疗的新方案、设想、发展规划等加以介绍。     

MULTI-REGION MODELS FOR DESCRIBING OXYGEN TENSION PROFILES IN HUMAN TUMORS

Multi-region simultaneous diffusion-reaction models are presented for describing oxygen tension profiles in human tumors. The models characterize the spherical tumor mass as either two regions, a central core of necrosis surrounded by a viable layer, or three regions where the viable layer is divided into a hypoxic region surrounded by a well-oxygenated rim. Estimates for the model parameters are based on steady-state clinical measurements obtained in-vivo in humans via a microelectrode—CT scanning technique developed and performed at the Fox Chase Cancer Center. Models employing linear kinetic rate forms for oxygen consumption via cell respiration accurately reproduce the oxygen tension profiles in the ten different carcinoma and sarcoma investigated. Large tumors (7.0 cm in diameter or larger) which typically outgrow their blood supply have sharp profiles that are accurately represented by a two-region model. Conversely, small tumors (4.8 cm in diameter or less)which have a relatively high degree of vascularity require a three-region model to accurately reproduce their oxygen tension profiles.