Patra, Devi P.

OBJECTIVE Endovascular intracranial aneurysm (IA) management has significantly evolved over the last 2 decades. Despite these advancements, the aneurysm recanalization rate after coil embolization remains a concern. Statins have been found to affect vascular repair and remodeling; therefore, the authors hypothesized that patients receiving statin therapy at the time of coil embolization would have lower aneurysm recurrence and retreatment rates compared with patients not receiving statin therapy. METHODS A post hoc analysis was conducted of the primary data from patients enrolled in the Hydrogel Endovascular Aneurysm Treatment Trial focusing on the impact of statin use on the recurrence rates of 3- to 14-mm IAs after endovascular coiling. The primary outcome measured included aneurysm recurrence over 18–24 months using the Raymond-Roy Occlusion Classification. Secondary outcomes included major and minor recurrence rates and retreatment rates. Propensity score matching based on patient and aneurysm characteristics was performed to mitigate selection bias. RESULTS A total of 577 patients with data on statin use were eligible for this analysis. Of these, 178 (30.8%) patients were using statins and 399 (69.2%) were not. After propensity score matching, 156 (39.2%) patients were included in the statin group and 242 (60.8%) in the nonstatin group. The recurrence rate was 3.8% (6/156) in the statin group and 10.7% (26/242) in the nonstatin group (p = 0.013). In a subgroup analysis, statin use significantly reduced recurrence in patients with unruptured aneurysms (1.6% vs 9.7%, p = 0.005), but not in those with ruptured aneurysms (12.5% vs 13.6%, p = 0.876). CONCLUSIONS Statin use was associated with a reduced rate of aneurysm recurrence in patients who underwent endovascular coiling for IAs with a decreased rate of retreatment during the follow-up period. Statins are a relatively low-risk treatment and may be an effective therapy to reduce recanalization of IAs, although further prospective studies are warranted to validate these findings.

Abstract The intra- and inter-patient heterogeneity in high-grade glioma (HGG) continues to contribute to its poor prognosis. Clinical biopsies are often harvested from limited regions and typically are not image localized. Thus, they fail to capture the diversity within tumor regions, immune expression or normal cell abundances that play key roles in tumor development. It is important to gain an understanding of these subpopulation ecologies, their spatial resolution, and interactions between them that may then be exploited for future therapeutic benefit. Further, these may differ by patient characteristics such as sex, age at diagnosis and treatment status. Using an ongoing image-localized biopsy collection protocol, we have so far evaluated the bulk transcriptomics of 202 multi-regional biopsies from 58 patients to characterize HGG heterogeneity. These samples were processed through Monocle, a reverse graph embedding algorithm that groups samples into states and orders them along developmental trajectories. Deconvolution methods were previously used to predict relative abundances of 7 normal, 6 glioma, and 5 immune cell subpopulations for each sample, which we have now overlaid on the Monocle graph. Monocle classified HGG into 4 main states along a three-pronged trajectory. These states reveal distinct population ecologies with associated enriched gene pathways. We also note significant immune pathway enrichments that differ between state and patient-reported sex. Together, these algorithms reveal a simple transcriptomic trajectory that helps us understand the development and evolution of HGG. Characterizing the in vivo diversity within and between high grade gliomas is important for understanding prognosis, stratifying future treatments and ultimately improving patient outcome.

AbstractThe study objective was to compare the length of stay (LOS) and the proportion of one-night admissions before and after the implementation of an endocrine monitoring protocol following endoscopic transsphenoidal surgery (ETSS) for pituitary adenoma.Patients who underwent transsphenoidal pituitary adenoma resection between July 1, 2018, and September 9, 2022, were identified, and divided into two cohorts before and after the implementation of the monitoring protocol. The overall LOS and number of nights of admission were recorded. Readmission within 30 days after surgery was also recorded. The number of outpatient laboratory tests performed and the time to the first test were also noted.Thirty patients were identified in the preprotocol group and 60 in the postprotocol group. The average admission length in the preprotocol group was significantly longer than the average admission length in the postprotocol group (2.4 vs. 1.7 days, p = 0.004). The percentage of one-night admissions increased from 13 to 57% (p < 0.001). There were no significant differences in readmission rates between the two groups (p = 0.681). The number of laboratory encounters increased from a mean of 1.38 to 2.40 (p = 0.030), while the time to the first test decreased from a mean of 3.43 to 2.36 days (p = 0.049).Patients admitted after ETSS for pituitary adenoma had shorter hospital stay and greater proportion of one-night admission with the implementation of an endocrine monitoring protocol. The all-cause readmission rate was not statistically different between the two groups. Through aggressive outpatient laboratory monitoring, one-night admission for ETSS may be feasible.

BACKGROUND: Smoking and observed growth of intracranial aneurysms are known risk factors for rupture. The mechanism by which smoking increases this risk is not completely elucidated. Furthermore, an association between smoking and aneurysm growth has not been clearly defined in the literature. We hypothesize that smoking is associated with aneurysm growth, which, in turn, may serve as one of the mechanisms by which smoking drives rupture risk. METHODS: We report a systematic review of the literature in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2020 guidelines. Using the R software, we performed a meta-analysis to investigate the association between smoking and the growth of unruptured intracranial aneurysms. Studies on familial aneurysms and genetic syndromes known to increase the risk of aneurysms were excluded. RESULTS: Eighteen observational studies were included with a total of 3535 patients and 4289 aneurysms with a mean follow-up period ranging from 17 to 226 months. The mean age among the studies ranged from 38.4 to 73.9 years; 74% of patients were female. Ever-smoking status (odds ratio, 1.10 [95% CI, 0.87–1.38]) and current smoking status (odds ratio, 1.43 [95% CI, 0.84–2.43]) did not show a statistically significant association with growth of intracranial aneurysms. Patients currently smoking did not have a statistically significant association with the growth of intracranial aneurysms (odds ratio, 1.18 [95% CI, 0.72–1.93]) compared with patients without a smoking history. No significant association was found in patients who previously smoked compared with patients who never smoked (odds ratio, 1.46 [95% CI, 0.88–2.43]). CONCLUSIONS: Smoking is not clearly associated with the growth of unruptured intracranial aneurysms, despite trends being observed, there is no statistical association. The mechanism by which smoking increases rupture risk might not be growth. In patients for whom observation is recommended, the absence of growth over time in the setting of smoking history does not, therefore, imply protection from rupture.

Abstract High-grade glioma continues to have dismal survival owing in part to its intra- and inter-patient heterogeneity. Standard clinical protocol collects tumor samples with the aim of providing or confirming a diagnosis and determining the status of a few key genes (e.g. IDH1, MGMT). However, this protocol is unable to capture the diversity within tumor regions, immune expression or normal cell abundances that play key roles in the development of the disease. To overcome this, during surgery we collect image-localized multi-regional biopsies to characterize this disease heterogeneity. Data collection is ongoing, and we currently have 202 samples from 58 patients with available bulk RNA-Seq. With a single-cell reference dataset from Columbia University, we used CIBERSORTx, a deconvolution method, to predict relative abundances of 7 normal, 6 glioma, and 5 immune cell subpopulations for each sample. We used Cox proportional hazard models with first-order statistics (mean, minimum, maximum) of abundances within patients to determine whether these are prognostic, then used TCGA RNA-Seq data to validate these findings. We found that one glioma proneural subtype was significantly beneficial for patient survival relative to other glioma subtypes across all statistics (and showed significance in TCGA). Proliferative and mesenchymal glioma subtypes also showed significance for one or two of the calculated statistics. Oligodendrocyte progenitor cell abundances were consistently significantly beneficial for patient survival in our cohort, while an increased abundance of abnormal (reactive) astrocytes is associated with poor prognosis. We also ran these analyses within invasive margin and core tumor regions to determine location-specific population abundances associated with patient survival. In conclusion, understanding the in vivo diversity of cellular subpopulations within high grade glioma is important for treatment stratification and patient benefit.

Abstract AIMS High-grade glioma continues to have dismal survival with current standard-of-care treatment, owing in part to its intra- and inter-patient heterogeneity. Typical diagnostic biopsies are taken from the dense tumor core to determine the presence of abnormal cells and the status of a few key genes (e.g. IDH1, MGMT). However, the tumor core is typically resected, leaving behind possibly genetically, transcriptomically and/or phenotypically distinct invasive margins that repopulate the disease. As these remaining populations are the ones ultimately being treated, it is important to know their compositional differences from the tumor core. We aim to identify the phenotypic niches defined by the relative composition of key cellular populations and understand their variation amongst patients. METHOD We have established an image-localized research biopsy study, that samples from both the invasive margin and tumor core. From this protocol, we currently have 202 samples from 58 patients with available bulk RNA-Seq, collected between Mayo Clinic and Barrow Neurological Institute. Using a single-cell reference dataset from our collaborators at Columbia University, we used CIBERSORTx, a deconvolution method, to predict relative abundances of 7 normal, 6 glioma, and 5 immune cell states for each sample. RESULTS We find that these cell state abundances connect to patient survival and show regional differences. For example, proneural glioma states were higher in invasive regions, whereas proliferative and mesenchymal states were higher in the tumor core. CONCLUSIONS Our analysis demonstrates a need to characterize the residual tissue following glioma resection to better understand the recurrent disease.