Citations

Purpose: During diagnostic cerebral angiography, catheter navigation requires manual contrast “puff” injections, while subsequent 2D/3D runs often use automated power injectors. Using power injectors for navigation puffs has not been described. We present a closed-circuit dual-port injector system (Nemoto Press Duo Elite) that integrates both navigation puff delivery and diagnostic run injection into a single automated platform, eliminating all manual tableside contrast handling. A foot pedal interface enables operator-controlled puff timing, potentially reducing contrast waste and air embolism risk while improving single-operator ergonomics with future remote robotic implications.Materials and Methods: This retrospective comparative cohort study compared 19 consecutive patients undergoing diagnostic cerebral angiography with foot pedal-controlled puff injections (June–July 2023) to 19 historical controls using manual hand injections (May 2021). Both groups used 90% contrast concentration. Fluoroscopy time, radiation dose, contrast utilization, and safety outcomes were compared.Results: Groups were demographically matched (mean age 52.1±14.2 vs. 50.2±12.9 years; 73.7% female). All 38 procedures achieved diagnostic adequacy with no complications. The foot pedal group demonstrated significantly shorter procedure time per vessel (11.5±4.4 vs. 18.9±10.5 min/vessel, P=0.010) with no significant differences in fluoroscopy time (P=0.171), radiation dose (P=0.690), or contrast delivered (88.7±30.9 vs. 88.2±42.5 mL, P=0.966). A trend toward improved contrast efficiency was observed (23.4±9.4 vs. 27.4±10.4 mL/vessel, P=0.226). Despite undergoing significantly more 3D rotational runs (1.3±1.0 vs. 0.6±0.7, P=0.030), the foot pedal group maintained comparable safety metrics, strengthening the non-inferiority findings.Conclusion: A closed-circuit dual-port injector system integrating automated navigation puff delivery with diagnostic run injection demonstrates non-inferiority to manual injection for diagnostic cerebral angiography, with shorter procedure time per vessel (39% reduction, P=0.010), though interpretation is limited by differences in indication distribution. By eliminating manual tableside contrast handling, this approach enables precise digital contrast accounting and reduces air embolism risk, establishing a foundation for remote and robotic angiography applications.

Abstract This review explores the pivotal role of preanalytical variables in bringing liquid biopsy approaches into the clinic for brain tumors. Preanalytical variables encompass a range of critical issues, from blood sample collection and handling to the impact of tumor heterogeneity and patient-specific factors. These variables introduce challenges such as false positives, false negatives, and variability in the analysis of tumor signals, which can hinder the diagnostic and prognostic utility of liquid biopsies. Understanding the nuances of preanalytical variables is essential for the successful implementation of liquid biopsy in clinical settings. This paper delves into strategies aimed at mitigating the influence of preanalytical variables by emphasizing the importance of standardized sample collection protocols, optimized sample processing and storage, quality control measures, and the integration of multiple liquid biopsy modalities.

Abstract The Human Phenotype Ontology (HPO) is a widely used resource that comprehensively organizes and defines the phenotypic features of human disease, enabling computational inference and supporting genomic and phenotypic analyses through semantic similarity and machine learning algorithms. The HPO has widespread applications in clinical diagnostics and translational research, including genomic diagnostics, gene-disease discovery, and cohort analytics. In recent years, groups around the world have developed translations of the HPO from English to other languages, and the HPO browser has been internationalized, allowing users to view HPO term labels and in many cases synonyms and definitions in ten languages in addition to English. Since our last report, a total of 2239 new HPO terms and 49235 new HPO annotations were developed, many in collaboration with external groups in the fields of psychiatry, arthrogryposis, immunology and cardiology. The Medical Action Ontology (MAxO) is a new effort to model treatments and other measures taken for clinical management. Finally, the HPO consortium is contributing to efforts to integrate the HPO and the GA4GH Phenopacket Schema into electronic health records (EHRs) with the goal of more standardized and computable integration of rare disease data in EHRs.

AbstractRadioenhancing nanoparticles (NPs) are being evaluated in ongoing clinical trials for various cancers including head and neck, lung, esophagus, pancreas, prostate, and soft tissue sarcoma. Supported by decades of preclinical investigation and recent randomized trial data establishing clinical activity, these agents are poised to influence future multimodality treatment paradigms involving radiotherapy. Although the physical interactions between NPs and ionizing radiation are well characterized, less is known about how these agents modify the tumor microenvironment, particularly regarding tumor immunogenicity. In this review, we describe the key multidisciplinary considerations related to radiation, surgery, immunology, and pathology for designing radioenhancing NP clinical trials.This article is categorized under: Therapeutic Approaches and Drug Discovery > Nanomedicine for Oncologic Disease

Abstract Therapeutic advances for glioblastoma have been minimal over the past 2 decades. In light of the multitude of recent phase III trials that have failed to meet their primary endpoints following promising preclinical and early-phase programs, a Society for Neuro-Oncology Think Tank was held in November 2020 to prioritize areas for improvement in the conduct of glioblastoma clinical trials. Here, we review the literature, identify challenges related to clinical trial eligibility criteria and trial design in glioblastoma, and provide recommendations from the Think Tank. In addition, we provide a data-driven context with which to frame this discussion by analyzing key study design features of adult glioblastoma clinical trials listed on ClinicalTrials.gov as “recruiting” or “not yet recruiting” as of February 2021.

Abstract Immunotherapy has revolutionized treatment for many hard-to-treat cancers but has yet to produce significant improvement in outcomes for patients with glioblastoma. This reflects the multiple and unique mechanisms of immune evasion and escape in this highly heterogeneous tumor. Glioblastoma engenders profound local and systemic immunosuppression and is remarkably effective at inducing T-cell dysfunction, posing a challenge to any immunotherapy-based approach. To overcome these mechanisms, multiple disparate modes of immune-oriented therapy will be required. However, designing trials that can evaluate these combinatorial approaches requires careful consideration. In this review, we explore the immunotherapy resistance mechanisms that have been encountered to date and how combinatorial approaches may address these. We also describe the unique aspects of trial design in both preclinical and clinical settings and consider endpoints and markers of response best suited for an intervention involving multiple agents.

With rapid advances in our understanding of cancer, there is an expanding number of potential novel combination therapies, including novel–novel combinations. Identifying which combinations are appropriate and in which subpopulations are among the most difficult questions in medical research. We conducted a Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA)-guided systematic review of trials of novel–novel combination therapies involving immunotherapies or molecular targeted therapies in advanced solid tumors. A MEDLINE search was conducted using a modified Cochrane Highly Sensitive Search Strategy for published clinical trials between July 1, 2017, and June 30, 2020, in the top-ranked medical and oncology journals. Trials were evaluated according to a criterion adapted from previously published Food and Drug Administration guidance and other key considerations in designing trials of combinations. This included the presence of a strong biological rationale, the use of a new established or emerging predictive biomarker prospectively incorporated into the clinical trial design, appropriate comparator arms of monotherapy or supportive external data sources and a primary endpoint demonstrating a clinically meaningful benefit. Of 32 identified trials, there were 11 (34%) trials of the novel–novel combination of anti-programmed death 1 (PD-1)/programmed death ligand 1 (PD-L1) and anti-cytotoxic T lymphocyte-associated antigen-4 (CTLA-4) therapy, and 10 (31%) trials of anti-PD-1/PD-L1 and anti-vascular endothelial growth factor (VEGF) combination therapy. 20 (62.5%) trials were phase II trials, while 12 (37.5%) were phase III trials. Most (72%) trials lacked significant preclinical evidence supporting the development of the combination in the given indication. A majority of trials (69%) were conducted in biomarker unselected populations or used pre-existing biomarkers within the given indication for patient selection. Most studies (66%) were considered to have appropriate comparator arms or had supportive external data sources such as prior studies of monotherapy. All studies were evaluated as selecting a clinically meaningful primary endpoint. In conclusion, designing trials to evaluate novel–novel combination therapies presents numerous challenges to demonstrate efficacy in a comprehensive manner. A greater understanding of biological rationale for combinations and incorporating predictive biomarkers may improve effective evaluation of combination therapies. Innovative statistical methods and increasing use of external data to support combination approaches are potential strategies that may improve the efficiency of trial design. Designing trials to evaluate novel–novel combination therapies presents numerous challenges to demonstrate efficacy in a comprehensive manner. A greater understanding of biological rationale for combinations and incorporating predictive biomarkers may improve effective evaluation of combination therapies. Innovative statistical methods and increasing use of external data to support combination approaches are potential strategies that may improve the efficiency of trial design.