多模态MRI影像组学在脑胶质瘤中的应用进展

影像组学在肿瘤的诊断、预后评估, 以及评价肿瘤对治疗的反应等方面均发挥着关键作用。多模态磁共振成像(MRI)影像组学可以将肿瘤的影像组学表现与其分子表型联系起来, 在脑胶质瘤的分级和治疗反应的预测和预后方面具有更大的优势。它利用常规和先进技术将脑肿瘤与非肿瘤性病变进行区分, 可用于脑胶质瘤的诊断和脑胶质瘤与脑转移瘤的鉴别;半自动和自动化的肿瘤分割技术也被开发用于评估脑胶质瘤的复发情况。主要对多模态MRI影像组学在预测胶质瘤重要分子生物学标志物、胶质瘤分级诊断、与脑转移瘤的鉴别诊断及评估术后复发方面的研究进展进行综述。     

胶质瘤血管新生及其调控机制

体内外研究表明实体性肿瘤的生长是依赖血管的,其直径一旦超过2 mm,若没有新生的血管供血则肿瘤的生长就会停止。胶质瘤是人体内血管化程度最高恶性的肿瘤之一。胶质瘤的血管发生与其他实体性肿瘤血管发生一样,由血管形成及血管新生两种方式构成：前者由内皮祖细胞或者血管母细胞形成新的血管;而后者是由组织中既存的成熟血管的内皮细胞发生增殖和游走形成小血管。血管新生是肿瘤血管生成的主要形式,胶质瘤血管新生的机制研究以及抑制其血管生成是胶质瘤治疗的一个新途径,成为近年来的研究热点,本文就胶质瘤血管新生及其调控机制作一综述。     

恶性胶质瘤生物学标志物的研究进展

当前恶性胶质瘤的诊断主要依靠影像学方法,以病理学检测确定肿瘤分期及恶性度.因为传统的手术、放疗和化疗的治疗方案效果不理想,近年来以胶质瘤相关分子标志物进行鉴别分类并评估其预后成为研究热点.肿瘤标志物在监测肿瘤的复发与转移,临床诊断与治疗等方面具有很高的应用价值,同时为研究肿瘤的发生与发展机制提供了新的方法.     

胶质瘤血管内皮生长因子表达的调节

近年来血管内皮生长因子 (ｖａｓｃｕｌａｒｅｎｄｏｔｈｅｌｉａｌｇｒｏｗｔｈｆａｃｔｏｒ,ＶＥＧＦ)调节肿瘤血管生成的作用已越来越受到关注〔1〕。胶质瘤是人体最富于血管的肿瘤之一 ,而且血管内皮细胞增生程度随胶质瘤恶性增高而更加明显。ＶＥＧＦ作为内皮细胞增生的主要调节者 ,对胶质瘤血管生成、恶性进展、远处转移有显著作用。原位杂交技术检测正常脑组织及不同分级胶质瘤组织ＶＥＧＦｍＲＮＡ ,结果显示ＶＥＧＦｍＲＮＡ在高分级胶质瘤表达较低分级明显为高 ,而在正常脑组织未表达 ,提示ＶＥＧＦ的表达与胶质瘤组织分级有关。…     

妇科肿瘤影像学进展

妇科肿瘤严重威胁着妇女健康,随着影像学设备软硬件的不断进步,一些影像检查手段已经可以对肿瘤进行早期诊断及鉴别诊断,可以有效改善预后。文章就PET-CT、MRI弥散加权成像及全身弥散成像在妇科肿瘤的早期诊断、分期、复发、疗效评价等临床应用作一综述。另外,介绍妇科肿瘤在分子影像学领域的研究现状,各类分子成像手段、成像方式及目前的研究进展。     

裸鼠胃癌模型的相位衬度微血管成像

目的肿瘤血管生成与肿瘤的发生、发展等各个环节密切相关,并显著影响肿瘤的生物学行为和预后。本研究的目的在于使用相位衬度成像技术三维地、全面地观察肿瘤微血管形态。方法使用原位接种肿瘤组织块方法,建立裸鼠胃癌原位模型。实验样本分为正常组和肿瘤组。对得到的相位衬度图像进行增强、血管分割、三维重建,并且计算三维微血管密度参数。结果相位衬度成像可显示胃癌组织的微血管形态。对照组微血管密度低于胃癌组的肿瘤表面区域(P0.001),证明肿瘤微血管更加丰富。结论相位衬度成像可以更全面地显示肿瘤微血管的生成情况,有助于对胃癌的恶性程度、转移潜力等进行评估,并对治疗方案的选择、判断预后和评估抗肿瘤血管药物疗效具有重要意义。     

肿瘤超声分子显像研究进展

掌握肿瘤细胞发生、发展与凋亡的在体活动规律,十分有利于对肿瘤的早期诊治和疗效评估.超声分子成像能够实现在分子水平对肿瘤细胞进行无创、动态、实时、定量观察,并可结合其它分子成像技术,对不同影像信息进行必要的融合,弥补各自的不足.提供既具备高质量的解剖结构定位图像,又具备良好分子水平显像功能的复合图像,为肿瘤的分子影像研究带来革命性的飞跃.本文就超声分子成像技术及其在肿瘤分子显像方面的应用研究作一综述.     

原发性中枢神经系统淋巴瘤VEGF、MVD与影像学对比研究

目的 :分析原发性中枢神经系统淋巴瘤 (PCNSL)的VEGF表达分布和测量其微血管密度 (MVD) ,旨在提高PCNSL早期诊断率和判断预后 ,同时为影像学提供理论依据。方法 :对 2 2例PCNSL临床 (包括影像学 )病理资料分析 ,同时行VEGF及CD34免疫组化标记 ,并测量MVD ,以 12例胶质瘤作为对照。结果 :2 2例PCNSL中单发者 17例 (占 77 2 7% ) ;多发者 4例 ,共有病灶 10处 ;1例为弥漫浸润型。肿瘤位于脑白质深部者 15例 (占 5 5 5 6 % )、脑表面及灰白质交界区者 8例、胼胝体者4例。CT示肿瘤为边界清楚的高密度结节或肿块。组织病理学示瘤细胞弥漫分布 ,瘤细胞大小较一致 ,胞质少 ,核大 ,可见瘤细胞围绕血管呈“袖套样”浸润。淋巴瘤MVD值 (2 1 8± 11 6 )与恶性胶质瘤组 (44 4± 16 8)的差异有非常显著性 (t =3 374 ,P <0 0 1)。VEGF表达无特异性 ,与对照组比较无统计学意义。结论 :病理学基础决定了影像学的特征。血管生成活性的不同 ,有助于PCNSL与恶性胶质瘤的鉴别 ,并对其预后的判断有一定帮助 ,VEGF可能是恶性肿瘤重要的促血管生成因子 ,但对于鉴别诊断无特异性。     

脑胶质瘤中Id1与VEGF的表达及其与肿瘤血管生成的关系

目的研究分化抑制因子(Id1)与血管内皮生长因子(VEGF)在正常脑组织、低级别脑胶质瘤和高级别脑胶质瘤组织中的表达情况,探讨其在肿瘤发生及肿瘤血管生成中的作用。方法应用免疫组织化学SABC法分别检测正常脑组织、低级别脑胶质瘤和高级别脑胶质瘤组织中Id1和VEGF的蛋白表达;分析Id1表达水平与脑胶质瘤临床病理特征的关系以及Id1与VEGF表达水平的相关性。结果 Id1阳性表达率在正常脑组织、低级别脑胶质瘤和高级别脑胶质瘤组织中分别为0%、72.0%和90.9%,差异有统计学意义(P0.01);VEGF在正常脑组织、低级别脑胶质瘤和高级别脑胶质瘤中的阳性率分别为25.0%、60.0%和81.8%,差异有统计学意义(P0.05);并且Id1与VEGF的表达呈正相关(r=0.320,P0.05)。结论 Id-1和VEGF的表达呈正相关,在胶质瘤血管生成过程中起协同作用;Id1的表达与胶质瘤病理分级密切相关,可作为抗肿瘤血管生成治疗的新靶点,也可作为胶质瘤的一种肿瘤标记物为其早期诊断提供帮助。     

人脑星形细胞肿瘤IL-8的表达及其与血管生成的关系

目的：探讨IL-8,VEGF在脑胶质瘤中的表达及与血管生成的关系。方法：应用由45例人脑星形细胞肿瘤和6例正常脑组织组成的组织芯片，采用免疫组织化学技术分别进行IL-8，VEGF，CD34标记并进行半定量，观测在不同病理分级胶质瘤中的表达及与微血管密度（MVD）之间的关系。结果：6例正常脑组织中不表达IL-8，VEGF。45例脑胶质瘤中，27例IL-8呈阳性表达，32例VEGF呈阳性表达，Ⅲ，Ⅳ级脑胶质瘤中IL-8，VEGF的表达比Ⅰ级、Ⅱ级明显增强，IL-8，VEGF评分为强阳性的胶质瘤内MVD明显高于评分为阴性和阳性的MVD（P<0.01）。IL-8表达与MVD呈正相关（rs=0.64，P<0.01）。VEGF表达与MVD之间呈正相关（rs=0.44，P<0.01）。IL-8表达与VEGF表达之间亦呈正相关（rs=0.56，P<0.01）。结论：IL-8，VEGF的表达与胶质瘤病理分级、MVD密切相关，二者在胶质瘤的血管生成中可能相互关联、共同调节肿瘤血管生成。     

99Tcm-MIBI SPECT脑显像与MRI对脑胶质瘤术后残留的与复发的对比研究

目的 探讨99Tcm—MIBI SPECT脑显像与MRI对脑胶质瘤术后残留与复发的影像特征，并客观评价两种检查方法的优缺点及诊断价值。方法 对15例正常对照者，27例脑胶质瘤术后患者（其中术后残留7例，术后复发9例，无复发者11例）行99Tcm-MIBISPECT脑显像并同时行MRI显像．对其影像学特征进行分析比较。结果正常对照者。99Tcm-MIBI SPECT显像脑实质内无核素浓聚，MRI显像未见明显异常。胶质瘤术后组（7倒残留厦9倒复发者）99Tcm-MIBI SPECT脑显像均表现为核素浓聚，其它11例无复发者表现为无核素浓聚，MRI显像表现为真阳性者8例、真阴性者7例。假阳性者4例。假阴性者8例。99Tcm-MIBI SPECT脑显像诊断胶质瘤术后残留与复发的灵敏度、准确性和特异性分别为93，7％、96．3％和100％，MR分别为31.3％、44.4％和63．6％，两者比较灵敏度、准确性有差异（P〈0．05），特异性无差异（P〉0.05）。结论 99Tcm—MIBI SPECT、脑显像对早期发现胶质瘤残留覆术后复发比MRI更优越；对分析确定胶质瘤术后残留与复发的早期诊断与治疗具有重要价值。     

~(131)Ⅰ标记胶质瘤单克隆抗体SZ39在脑瘤患者体内分布及药代动力学研究

11例脑胶质瘤和其他颅内占位者,经静脉注射~(131)Ⅰ标记抗人脑胶质瘤单克隆抗体SZ39,0.7～2.9mCi/100～300μg蛋白。然后 通过手术组织标本放射性强度测定,肿瘤SPECT扫描及血尿标本分析,研究SZ39在脑胶质瘤患者体内分布及药代动力学参数。结果提示,SZ39可在人脑胶质瘤内浓集,为脑组织的1.9～4.8倍,平均3.2倍。SPECT可清晰显示肿瘤图像,而非胶质瘤性颅内占位,未见肿瘤显像。抗体在肿瘤内浓集可持续2周以上。血液中的半清除期T1/2快相为1.6h,慢相为39h。所有患者临床观察无明显不良反应。以上初步研究结果显示,SZ39有进一步用于临床诊断与治疗的前景。     

Assessment of therapeutic response and treatment planning for brain tumors using metabolic and physiological MRI

MRI is routinely used for diagnosis, treatment planning and assessment of response to therapy for patients with glioma. Gliomas are spatially heterogeneous and infiltrative lesions that are quite variable in terms of their response to therapy. Patients classified as having low-grade histology have a median overall survival of 7 years or more, but need to be monitored carefully to make sure that their tumor does not upgrade to a more malignant phenotype. Patients with the most aggressive grade IV histology have a median overall survival of 12-15 months and often undergo multiple surgeries and adjuvant therapies in an attempt to control their disease. Despite improvements in the spatial resolution and sensitivity of anatomic images, there remain considerable ambiguities in the interpretation of changes in the size of the gadolinium-enhancing lesion on T(1) -weighted images as a measure of treatment response, and in differentiating between treatment effects and infiltrating tumor within the larger T(2) lesion. The planning of focal therapies, such as surgery, radiation and targeted drug delivery, as well as a more reliable assessment of the response to therapy, would benefit considerably from the integration of metabolic and physiological imaging techniques into routine clinical MR examinations. Advanced methods that have been shown to provide valuable data for patients with glioma are diffusion, perfusion and spectroscopic imaging. Multiparametric examinations that include the acquisition of such data are able to assess tumor cellularity, hypoxia, disruption of normal tissue architecture, changes in vascular density and vessel permeability, in addition to the standard measures of changes in the volume of enhancing and nonenhancing anatomic lesions. This is particularly critical for the interpretation of the results of Phase I and Phase II clinical trials of novel therapies, which are increasingly including agents that are designed to have anti-angiogenic and anti-proliferative properties as opposed to having a direct effect on tumor cell viability.     

Follow-up evaluation of radiation-induced DNA damage in CSF disseminated high-grade glioma using phospho-histone H2AX antibody

Cytological examination of cerebrospinal fluid (CSF) is used not only for the diagnosis of spinal disease, but also to assess the postoperative effect of treatment. We experienced a case of high-grade glioma in disseminated CSF, and retrospectively examined the clinical, pathological and cytological features. We further investigated radiation-induced DNA damage in glioma cells using phospho-Histone H2AX antibody. A five-year-old boy received a clinical diagnosis of optic nerve glioma, and was followed-up for three months after chemotherapy. Magnetic resonance imaging was repeated, revealing abnormalities in other brain areas. The pathological diagnosis was anaplastic astrocytoma. CSF dissemination was detected, and increases in the number and mitosis of tumor cells were observed in CSF cytology. After radiotherapy the tumor cells in CSF decreased markedly. On cytomorphologic and immunocytochemical evaluation post-irradiation, tumor cells showed vacuolation of both the nucleus and cytoplasm, degeneration of nuclear chromatin, and alteration of the phospho-Histone H2AX expression, compared with tumor cells before the irradiation. CSF cytology is an effective means of evaluating DNA damage in tumor cells after irradiation, and may be useful in assessing the therapeutic response.     

基于TensorMixup的脑胶质瘤全自动分割

脑胶质瘤及其子区域的全自动分割对临床脑胶质瘤患者的诊断、治疗与病情监控具有重要意义。本文改进传统Mixup方法,提出TensorMixup模型,并将其应用于三维U-Net脑胶质瘤分割任务。算法核心思想包括,首先从两位患者相同模态的核磁共振脑影像中分别获取肿瘤区域所在边界框的图像序列,并从获取的图像序列中选取尺寸为128×128×128体素的图像块,然后使用一个所有元素均独立采样于贝塔分布的张量,混合图像块的信息,接着将上述张量映射为矩阵,用于混合图像块的独热编码标签序列,从而合成新图像及其标注数据,最后使用合成数据训练模型,以提高模型的分割精度。在BraTs2019数据集的测试结果显示,本文算法在完整肿瘤、肿瘤核心与增强肿瘤区域的平均Dice值依次可达91.32%、85.67%与82.20%,证明使用TensorMixup进行脑胶质瘤分割,具有可行性与有效性。     

Precise glioma targeting of and penetration by aptamer and peptide dual-functioned nanoparticles

The treatment of a brain glioma is still one of the most difficult challenges in oncology. To effectively treat brain glioma and reduce the side effects, drugs must be transported across the blood brain barrier (BBB) and then targeted to the brain cancer cells because most anti-tumor drugs are highly toxic to the normal brain tissue. A cascade delivery strategy was developed to perform these two aims and to achieve enhanced and precisely targeted delivery. Herein, we utilize a phage-displayed TGN peptide and an AS1411 aptamer, which are specific targeting ligands of the BBB and cancer cells, respectively and we conjugate them with nanoparticles to establish the brain glioma cascade delivery system (AsTNP). In vitro cell uptake and three-dimensional tumor spheroid penetration studies demonstrated that the system could not only target endothelial and tumor cells but also penetrate the endothelial monolayers and tumor cells to reach the core of the tumor spheroids, which was extremely important but mostly ignored in glioma therapy. In vivo imaging further demonstrated that the AsTNP provided the highest tumor distribution and tumor/normal brain ratio. The distribution was also reconfirmed by fluorescent images of the brain slides. As a result, the docetaxel-loaded AsTNP presents the best anti-glioma effect with improved glioma bearing survival. In conclusion, the AsTNP could precisely target to the brain glioma, which was a valuable target for glioma imaging and therapy.     

Imaging of cancer lipid metabolism in response to therapy

Lipids represent a diverse array of molecules essential to the cell's structure, defense, energy, and communication. Lipid metabolism can often become dysregulated during tumor development. During cancer therapy, targeted inhibition of cell proliferation can likewise cause widespread and drastic changes in lipid composition. Molecular imaging techniques have been developed to monitor altered lipid profiles as a biomarker for cancer diagnosis and treatment response. For decades, MRS has been the dominant non‐invasive technique for studying lipid metabolite levels. Recent insights into the oncogenic transformations driving changes in lipid metabolism have revealed new mechanisms and signaling molecules that can be exploited using optical imaging, mass spectrometry imaging, and positron emission tomography. These novel imaging modalities have provided researchers with a diverse toolbox to examine changes in lipids in response to a wide array of anticancer strategies including chemotherapy, radiation therapy, signal transduction inhibitors, gene therapy, immunotherapy, or a combination of these strategies. The understanding of lipid metabolism in response to cancer therapy continues to evolve as each therapeutic method emerges, and this review seeks to summarize the current field and areas of unmet needs.     

人工智能在中枢神经系统疾病影像诊断中的应用进展

人工智能（AI）技术应用于中枢神经系统疾病的诊断、分型以及预后，可显著提高医学影像信息的可信性和有效性，大幅提高神经系统疾病早期诊断的准确率，为医生选择合理的治疗方案提供定量的依据。本研究介绍了AI在中枢神经影像诊断中常用的学习算法、AI在中枢神经疾病影像诊断中的图像分割和特征提取中的应用；综述了AI在术前胶质瘤分级、预测基因突变状况以及胶质瘤术后复发鉴别的应用；并初步介绍了已用于临床工作的一些软件工具。     

Gene therapy and targeted toxins for glioma

The most common primary brain tumor in adults is glioblastoma. These tumors are highly invasive and aggressive with a mean survival time of 15-18 months from diagnosis to death. Current treatment modalities are unable to significantly prolong survival in patients diagnosed with glioblastoma. As such, glioma is an attractive target for developing novel therapeutic approaches utilizing gene therapy. This review will examine the available preclinical models for glioma including xenographs, syngeneic and genetic models. Several promising therapeutic targets are currently being pursued in pre-clinical investigations. These targets will be reviewed by mechanism of action, i.e., conditional cytotoxic, targeted toxins, oncolytic viruses, tumor suppressors/oncogenes, and immune stimulatory approaches. Preclinical gene therapy paradigms aim to determine which strategies will provide rapid tumor regression and long-term protection from recurrence. While a wide range of potential targets are being investigated preclinically, only the most efficacious are further transitioned into clinical trial paradigms. Clinical trials reported to date are summarized including results from conditionally cytotoxic, targeted toxins, oncolytic viruses and oncogene targeting approaches. Clinical trial results have not been as robust as preclinical models predicted; this could be due to the limitations of the GBM models employed. Once this is addressed, and we develop effective gene therapies in models that better replicate the clinical scenario, gene therapy will provide a powerful approach to treat and manage brain tumors.     

Gene therapy and targeted toxins for glioma

The most common primary brain tumor in adults is glioblastoma. These tumors are highly invasive and aggressive with a mean survival time of nine to twelve months from diagnosis to death. Current treatment modalities are unable to significantly prolong survival in patients diagnosed with glioblastoma. As such, glioma is an attractive target for developing novel therapeutic approaches utilizing gene therapy. This review will examine the available preclinical models for glioma including xenographs, syngeneic and genetic models. Several promising therapeutic targets are currently being pursued in pre-clinical investigations. These targets will be reviewed by mechanism of action, i.e., conditional cytotoxic, targeted toxins, oncolytic viruses, tumor suppressors/oncogenes, and immune stimulatory approaches. Preclinical gene therapy paradigms aim to determine which strategies will provide rapid tumor regression and long-term protection from recurrence. While a wide range of potential targets are being investigated preclinically, only the most efficacious are further transitioned into clinical trial paradigms. Clinical trials reported to date are summarized including results from conditionally cytotoxic, targeted toxins, oncolytic viruses and oncogene targeting approaches. Clinical trial results have not been as robust as preclinical models predicted, this could be due to the limitations of the GBM models employed. Once this is addressed, and we develop effective gene therapies in models that better replicate the clinical scenario, gene therapy will provide a powerful approach to treat and manage brain tumors.