RESUMEN
Glioblastoma (GBM), a highly aggressive form of brain cancer, is considered one of the deadliest cancers, and even with the most advanced medical treatments, most affected patients have a poor prognosis. However, recent advances in nanotechnology offer promising avenues for the development of versatile therapeutic and diagnostic nanoplatforms that can deliver drugs to brain tumor sites through the blood-brain barrier (BBB). Despite these breakthroughs, the use of nanoplatforms in GBM therapy has been a subject of great controversy due to concerns over the biosafety of these nanoplatforms. In recent years, biomimetic nanoplatforms have gained unprecedented attention in the biomedical field. With advantages such as extended circulation times, and improved immune evasion and active targeting compared to conventional nanosystems, bionanoparticles have shown great potential for use in biomedical applications. In this prospective article, we endeavor to comprehensively review the application of bionanomaterials in the treatment of glioma, focusing on the rational design of multifunctional nanoplatforms to facilitate BBB infiltration, promote efficient accumulation in the tumor, enable precise tumor imaging, and achieve remarkable tumor suppression. Furthermore, we discuss the challenges and future trends in this field. Through careful design and optimization of nanoplatforms, researchers are paving the way toward safer and more effective therapies for GBM patients. The development of biomimetic nanoplatform applications for glioma therapy is a promising avenue for precision medicine, which could ultimately improve patient outcomes and quality of life.
Asunto(s)
Neoplasias Encefálicas , Glioblastoma , Glioma , Humanos , Sistemas de Liberación de Medicamentos/métodos , Estudios Prospectivos , Calidad de Vida , Glioma/tratamiento farmacológico , Glioblastoma/tratamiento farmacológico , Glioblastoma/patología , Neoplasias Encefálicas/tratamiento farmacológico , Neoplasias Encefálicas/patologíaRESUMEN
PURPOSE: To investigate the CT features of drug-resistant pulmonary tuberculosis (DR-PTB) and the diagnostic value of CT in DR-PTB diagnosis to provide imaging evidence for the timely detection of drug-resistant Mycobacterium tuberculosis. MATERIALS AND METHODS: A total of 1546 cases of pulmonary tuberculosis (PTB) with complete clinical data, chest CT images and defined drug sensitivity testing results were consecutively enrolled; 516 cases of DR-PTB were included in the drug-resistant group, and 1030 cases of drug-sensitive pulmonary tuberculosis (DS-PTB) were included in the drug-sensitivity group. Comparative analyses of clinical symptoms and imaging findings were conducted. Univariate and logistic regression analyses were performed, a regression equation model was developed, and the receiver operating characteristic (ROC) curve was constructed. RESULTS: In the univariate analysis, some features, including whole-lung involvement, multiple cavities, thick-walled cavities, collapsed lung, disseminated lesions along the bronchi, bronchiectasis, emphysema, atelectasis, calcification, proliferative lesions, encapsulated effusion, etc., were observed more frequently in the DR-PTB group than in the DS-PTB group, and the differences were statistically significant (p<0.05). Exudative lesions and pneumoconiosis were observed more frequently in the drug-sensitivity group than in the drug-resistant group (p<0.05). Logistic regression analysis indicated that whole-lung involvement, multiple cavities, thick-walled cavities, disseminated lesions along the bronchi, bronchiectasis, and emphysema were independent risk factors for DR-PTB, and exudative diseases were protective factors. The total prediction accuracy of the regression model was 80.6%, and the area under the ROC curve (AUC) was 82.6%. CONCLUSION: Chest CT manifestations of DR-PTB had certain characteristics that significantly indicated the possibility of drug resistance in tuberculosis patients, specifically when multifarious imaging findings, including multiple cavities, thick-walled cavities, disseminated lesions along the bronchi, whole-lung involvement, etc., coexisted simultaneously. These results may provide imaging evidence for timely drug resistance detection in suspected drug-resistant cases and contribute to the early diagnosis of DR-PTB.
RESUMEN
BACKGROUND: To explore the correlation of flash dual source computed tomography perfusion imaging (CTPI) and regional lymph node metastasis of non-small cell lung cancer (NSCLC), and to evaluate the value of CT perfusion parameters in predicting regional lymph node metastasis of NSCLC. METHODS: 120 consecutive patients with NSCLC confirmed by postoperative histopathology were underwent flash dual source CT perfusion imaging in pre-operation. The CT perfusion parameters of NSCLC, such as blood flow (BF), blood volume (BV), mean transit time (MTT) and permeability (PMB) were obtained by the image post-processing. Then microvessel density (MVD), luminal vascular number (LVN), luminal vascular area (LVA) and luminal vascular perimeter (LVP) of NSCLC were counted by immunohistochemistry. These cases were divided into group A (patients with lymph node metastasis, 58 cases) and group B (patients without lymph node metastasis, 62 cases) according to their pathological results. The CT perfusion parameters and the microvessel parameters were contrastively analysed between the two groups. Receiver operating characteristic (ROC) curve was used to assess the diagnostic efficiency of CT perfusion parameters in predicting regional lymph node metastasis of NSCLC in pre-operation. RESULTS: Group A presented significantly lower LVA, BF and higher MTT, PMB than Group B (P < 0.05), while BV, LVN, LVP and MVD were no significant difference (P > 0.05). Correlation analysis showed that BF was correlated with LVA and LVP (P < 0.05), while BV, MTT and PMB were not correlated with LVN, LVA and LVP (P > 0.05). All the perfusion parameters were not correlated with MVD. According to the ROC curve analysis, when BF < 85.16 ml/100 ml/min as a cutoff point to predict regional lymph node metastasis of NSCLC, the sensitivity, specificity, accuracy, positive predictive value and negative predictive value were 60.8, 81.7, 71.5, 75.6 and 69.5% respectively. CONCLUSION: Flash dual source CT perfusion imaging can non-invasively indicate the luminal vascular structure of tumor and BF can be used as one of the important indexes in predicting regional lymph node metastasis of NSCLC in pre-operation.