Efficacy of stereotactic radiosurgery as single or combined therapy for brain metastasis: A systematic review and meta-analysis.

To determine the efficacy of stereotactic radiosurgery (SRS) in treating patients with brain metastases (BMs), a network meta-analysis (NMA) of randomized controlled trials (RCTs) and a direct comparison of cohort studies were performed. Relevant literature regarding the effectiveness of SRS alone and in combination with whole-brain radiotherapy (WBRT) and surgery was retrieved using systematic database searches up to April 2019. The patterns of overall survival (OS), one-year OS, progression-free survival (PFS), one-year local brain control (LBC), one-year distant brain control (DBC), neurological death (ND), and complication rate were analyzed. A total of 18 RCTs and 37 cohorts were included in the meta-analysis. Our data revealed that SRS carried a better OS than SRS+WBRT (p = 0.048) and WBRT (p = 0.041). Also, SRS+WBRT demonstrated a significantly improved PFS, LBC, and DBC compared to WBRT alone and SRS alone. Finally, SRS achieved the same LBC as high as surgery, but intracranial relapse occurred considerably more frequently in the absence of WBRT. However, there were not any significant differences in ND and toxicities between SRS and other groups. Therefore, SRS alone may be a better alternative since increased patient survival may outweigh the increased risk of brain tumor recurrence associated with it.

Stereotactic radiosurgery with immune checkpoint inhibitors for brain metastases: a meta-analysis study.

BACKGROUND: Immune checkpoint inhibitors (ICIs) are an emerging tool in the treatment of brain metastases (BMs), Stereotactic radiosurgery (SRS), traditionally used for BMs, elicits an immune brain response and can act synergistically with ICIs. We aim to investigate the efficacy of ICI administered with SRS and determine the impact of timing on BM response. METHODS: A systematical search was performed to identify potential studies concerning BMs managed with SRS alone or with SRS + ICI with relative timing administration (ICI concurrent with SRS, ICI nonconcurrent with SRS, SRS before ICI, SRS after ICI). The overall survival (OS), 12-month OS, local progression-free survival (LPFS), 12-month local brain control (LBC), distant progression-free survival (DPFS), 12-month distant brain control (DBC), and adverse events (intracranial hemorrhage, radionecrosis) were analyzed using the random-effects model. RESULTS: A total of 16 retrospective studies with 1356 BM patients were included. Compared to nonconcurrent therapy, concurrent therapy revealed a significantly longer OS (HR= 1.43; p = 0.008) and 12-months LBC (HR = 1.91; p = 0.04), a similar 12-months DBC (HR = 1.12; p = 0.547) and higher complication rate (R = 0.77; p = 0.346). Concurrent therapy leads to a significantly higher OS compared to ICI before SRS (HR = 2.55; p = 0.0003). CONCLUSION: The combination of SRS with ICI improves patients' clinical and radiological outcomes. The effectiveness of the combination is subject to the identification of an optimal therapeutic window.

Deep learning approaches for automated classification and segmentation of head and neck cancers and brain tumors in magnetic resonance images: a meta-analysis study.

PURPOSE: Deep learning (DL) has led to widespread changes in automated segmentation and classification for medical purposes. This study is an attempt to use statistical methods to analyze studies related to segmentation and classification of head and neck cancers (HNCs) and brain tumors in MRI images. METHODS: PubMed, Web of Science, Embase, and Scopus were searched to retrieve related studies published from January 2016 to January 2020. Studies that evaluated the performance of DL-based models in the segmentation, and/or classification and/or grading of HNCs and/or brain tumors were included. Selected studies for each analysis were statistically evaluated based on the diagnostic performance metrics. RESULTS: The search results retrieved 1,664 related studies, of which 30 studies were eligible for meta-analysis. The overall performance of DL models for the complete tumor in terms of the pooled Dice score, sensitivity, and specificity was 0.8965 (95% confidence interval (95% CI): 0.76-0.9994), 0.9132 (95% CI: 0.71-0.994) and 0.9164 (95% CI: 0.78-1.00), respectively. The DL methods achieved the highest performance for classifying three types of glioma, meningioma, and pituitary tumors with overall accuracies of 96.01%, 99.73%, and 96.58%, respectively. Stratification of glioma tumors by high and low grading revealed overall accuracies of 94.32% and 94.23% for the DL methods, respectively. CONCLUSION: Based on the obtained results, we can acknowledge the significant ability of DL methods in the mentioned applications. Poor reporting in these studies challenges the analysis process, so it is recommended that future studies report comprehensive results based on different metrics.

A Review on the Biodistribution, Pharmacokinetics and Toxicity of Bismuth-Based Nanomaterials.

Here, bismuth-based nanomaterials (Bi-based NMs) are introduced as promising theranostic agents to enhance image contrast as well as for the therapeutic gain for numerous diseases. However, understanding the interaction of such novel developed nanoparticles (NPs) within a biological environment is a requisite for the translation of any promising agent from the lab bench to the clinic. This interaction delineates the fate of NPs after circulation in the body. In an ideal setting, a nano-based therapeutic agent should be eliminated via the renal clearance pathway, meanwhile it should have specific targeting to a diseased organ to reach an effective dose and also to overcome off-targeting. Due to their clearance pathway, biodistribution patterns and pharmacokinetics (PK), Bi-based NMs have been found to play a determinative role to pass clinical approval and they have been investigated extensively in vivo to date. In this review, we expansively discuss the possible toxicity induced by Bi-based NMs on cells or organs, as well as biodistribution profiles, PK and the clearance pathways in animal models. A low cytotoxicity of Bi-based NMs has been found in vitro and in vivo, and along with their long-term biodistribution and proper renal clearance in animal models, the translation of Bi-based NMs to the clinic as a useful novel theranostic agent is promising to improve numerous medical applications.

SRS in Combination With Ipilimumab: A Promising New Dimension for Treating Melanoma Brain Metastases.

Dear Editor,I am writing to you in order to highlight some miscalculations in an article published in the journal of Technology in Cancer Research & Treatment, entitled; "SRS in Combination with Ipilimumab: A Promising New Dimension for Treating Melanoma Brain Metastases" by Khan, et al.1 These miscalculations changed the derived conclusion about median survival time, and adverse effects in the selected treatment groups. So, amending these miscalculations may help readers in future research decisions.

Accuracy of deep learning for automated detection of pneumonia using chest X-Ray images: A systematic review and meta-analysis.

BACKGROUND: Recently, deep learning (DL) algorithms have received widespread popularity in various medical diagnostics. This study aimed to evaluate the diagnostic performance of DL models in the detection and classifying of pneumonia using chest X-ray (CXR) images. METHODS: PubMed, Embase, Scopus, Web of Science, and Google Scholar were searched in order to retrieve all studies that implemented a DL algorithm for discriminating pneumonia patients from healthy controls using CXR images. We used bivariate linear mixed models to pool diagnostic estimates including sensitivity (SE), specificity (SP), positive likelihood ratio (PLR), negative likelihood ratio (NLR), and diagnostic odds ratio (DOR). Also, the area under receiver operating characteristics curves (AUC) of the included studies was used to estimate the diagnostic value. RESULTS: The pooled SE, SP, PLR, NLR, DOR and AUC for DL in discriminating pneumonia CXRs from controls were 0.98 (95% confidence interval (CI): 0.96-0.99), 0.94 (95% CI: 0.90-0.96), 15.35 (95% CI: 10.04-23.48), 0.02 (95% CI: 0.01-0.04), 718.13 (95% CI: 288.45-1787.93), and 0.99 (95% CI: 0.98-100), respectively. The pooled SE, SP, PLR, NLR, DOR and AUC for DL in discriminating bacterial from viral pneumonia using CXR radiographs were 0.89 (95% CI: 0.79-0.94), 0.89 (95% CI: 0.78-0.95), 8.34 (95% CI: 3.75-18.55), 0.13 (95% CI: 0.06-0.26), 66.14 (95% CI: 17.34-252.37), and 0.95 (0.93-0.97). CONCLUSION: DL indicated high accuracy performance in classifying pneumonia from normal CXR radiographs and also in distinguishing bacterial from viral pneumonia. However, major methodological concerns should be addressed in future studies for translating to the clinic.

Bismuth-Based Nanomaterials: Recent Advances in Tumor Targeting and Synergistic Cancer Therapy Techniques.

Despite all of the efforts in the field of cancer therapy, the heterogeneous properties of tumor cells induce an insufficient therapeutic outcome when treated with conventional monotherapies, necessitating a shift in cancer treatment from monotherapy to combination therapy for complete cancer treatment. Multifunctional bismuth (Bi)-based nanomaterials (NMs) with therapeutic functions hold great promise for the fields of cancer diagnosis and therapy based on their low toxicity, X-ray sensitive capabilities, high atomic number, near-infrared driven semiconductor properties, and low cost. Herein, a comprehensive review of recent advances in various medicinal aspects of Bi-based NMs is presented including: evaluation of in-tumor site accumulation, tumor targeting, and therapeutic performance, as well as the characteristics, benefits, and shortcomings of Bi-based NM-mediated major monotherapies. In addition, the cooperative enhancement mechanisms between two or more of these monotherapies are described in detail to address common challenges in cancer therapy, such as multidrug resistance, hypoxia, and metastasis. Finally, this review opens new insights into the design of multimodal synergistic therapies for potential future clinical applications of Bi-based NMs.

Iron oxide/bismuth oxide nanocomposites coated by graphene quantum dots: "Three-in-one" theranostic agents for simultaneous CT/MR imaging-guided in vitro photothermal therapy.

BACKGROUND: The all-in-one nanoprobes (NPs) have drawn biomedical attention in the cancer therapy field due to simultaneously combing the capabilities of therapeutic and diagnostic methods into a single nanoprobe. METHOD: In this study, we developed a theranostic probe based on superparamagnetic iron oxide (SPIO) and bismuth oxide (Bi2O3) with graphene quantum dots (GQDs) coating to investigate the physical properties for in vitro CT/MR dual-modal biomedical imaging and cancer-specific photothermal therapy (PTT). RESULT: The GQDs-Fe/Bi nanocomposites showed strong light absorbance profile with wide-band in the near-infrared region, without any sharp peak or decline. The highest photo-to-thermal conversion efficacy (η), was found to be 31.8% with the high photostability upon the irradiation of NIR 808-nm laser. The results of in vitro photothermal ablation of cancerous cells demonstrated that the cells significantly killed in the presence of NPs (∼53.4%) with a dose-dependent manner in comparison to only laser group (3.0%). In GQDs-Fe/Bi nanocomposites, Bi with a high atomic number (Z = 83) exhibited a superior X-ray attenuation capability (175%) than the clinical CT agent-used dotarem, also, SPIO with excellent magnetization property showed strong T2-relaxation shortening capability (r2 = 62.34 mM-1.s-1) as a contrast agent for CT/MR imaging. CONCLUSION: Our results demonstrate that the developed NPs can incorporate dual-modality imaging capability into a photo absorber for CT/MR imaging-guided tumor PTT.