Optimal PHASES Scoring for Risk Stratification of Surgically Treated Unruptured Aneurysms

OBJECTIVE

The PHASES (Population, Hypertension, Age, Size, Earlier subarachnoid hemorrhage, Site) score was developed to facilitate risk stratification for management of unruptured intracranial aneurysms (UIAs). This study aimed to identify the optimal PHASES score cutoff for predicting neurologic outcomes in patients with surgically treated aneurysms.

METHODS

All patients who underwent microneurosurgical treatment for UIA at a large quaternary center from January 1, 2014, to December 31, 2020, were retrospectively reviewed. Inclusion criteria included a modified Rankin Scale (mRS) score of ≤2 at admission. The primary outcome was 1-year mRS score, with a "poor" neurologic outcome defined as an mRS score >2.

RESULTS

In total, 375 patients were included in the analysis. The mean (SD) PHASES score for the entire study population was 4.47 (2.67). Of 375 patients, 116 (31%) had a PHASES score ≥6, which was found to maximize prediction of poor neurologic outcome. Patients with PHASES scores ≥6 had significantly higher rates of poor neurologic outcome than patients with PHASES scores <6 at discharge (58 [50%] vs. 90 [35%], P = 0.005) and follow-up (20 [17%] vs. 18 [6.9%], P = 0.002). After adjusting for age, Charlson Comorbidity Index score, nonsaccular aneurysm, and aneurysm size, PHASES score ≥6 remained a significant predictor of poor neurologic outcome at follow-up (odds ratio, 2.75; 95% confidence interval, 1.42-5.36, P = 0.003).

CONCLUSIONS

In this retrospective analysis, a PHASES score ≥6 was associated with significantly greater proportions of poor outcome, suggesting that awareness of this threshold in PHASES scoring could be useful in risk stratification and UIA management.

Hematologic and inflammatory predictors of outcome in patients with brain arteriovenous malformations

OBJECTIVE

This study investigated the prognostic value of admission blood counts for AVM outcomes and compared admission blood counts for patients with ruptured and unruptured AVMs.

METHODS

A retrospective analysis of patients who underwent surgical treatment for a ruptured cerebral AVM between February 1, 2014, and March 31, 2020, was conducted. The primary outcome was poor neurologic outcome, defined as a modified Rankin Scale score ≥2 in patients with unruptured AVMs or >2 in those with ruptured AVMs.

RESULTS

A total of 235 patients were included; 80 (34%) had ruptured AVMs. At admission, patients with ruptured AVMs had a significantly lower mean (SD) hemoglobin level (12.78 [2.07] g/dL vs 13.71 [1.60] g/dL, p<0.001), hematocrit (38.1% [5.9%] vs 40.7%[4.6%], p<0.001), lymphocyte count (16% [11%] vs 26% [10%], p<0.001), and absolute lymphocyte count (1.41 [0.72]×103/μL vs 1.79 [0.68]×103/μL, p<0.001), and they had a significantly higher mean (SD) white blood cell count (10.4 [3.8] vs 7.6 [2.3]×103/μL, p<0.001), absolute neutrophil count (7.8[3.8]×103/μL vs 5.0[2.5]×103/μL, p<0.001), and neutrophil count (74% [14%] vs 64% [13%], p<0.001). Among patients with unruptured AVMs, white blood cell count ≥6.4×103/μL and absolute neutrophil count ≥3.4×103/μL were associated with a favorable neurologic outcome, whereas hemoglobin level ≥13.4 g/dL was associated with an unfavorable outcome. Among patients with ruptured AVMs, hypertension was associated with a threefold increase in the odds of a poor neurologic outcome.

CONCLUSIONS

This study found that patients with ruptured and unruptured AVMs present with characteristic profiles of hematologic and inflammatory parameters evident in their admission blood work.

A critical moment in machine learning in medicine: on reproducible and interpretable learning

Over the past two decades, advances in computational power and data availability combined with increased accessibility to pre-trained models have led to an exponential rise in machine learning (ML) publications. While ML may have the potential to transform healthcare, this sharp increase in ML research output without focus on methodological rigor and standard reporting guidelines has fueled a reproducibility crisis. In addition, the rapidly growing complexity of these models compromises their interpretability, which currently impedes their successful and widespread clinical adoption. In medicine, where failure of such models may have severe implications for patients' health, the high requirements for accuracy, robustness, and interpretability confront ML researchers with a unique set of challenges. In this review, we discuss the semantics of reproducibility and interpretability, as well as related issues and challenges, and outline possible solutions to counteracting the "black box". To foster reproducibility, standard reporting guidelines need to be further developed and data or code sharing encouraged. Editors and reviewers may equally play a critical role by establishing high methodological standards and thus preventing the dissemination of low-quality ML publications. To foster interpretable learning, the use of simpler models more suitable for medical data can inform the clinician how results are generated based on input data. Model-agnostic explanation tools, sensitivity analysis, and hidden layer representations constitute further promising approaches to increase interpretability. Balancing model performance and interpretability are important to ensure clinical applicability. We have now reached a critical moment for ML in medicine, where addressing these issues and implementing appropriate solutions will be vital for the future evolution of the field.

Automated volumetric assessment of pituitary adenoma

PURPOSE

Assessment of pituitary adenoma (PA) volume and extent of resection (EOR) through manual segmentation is time-consuming and likely suffers from poor interrater agreement, especially postoperatively. Automated tumor segmentation and volumetry by use of deep learning techniques may provide more objective and quick volumetry.

METHODS

We developed an automated volumetry pipeline for pituitary adenoma. Preoperative and three-month postoperative T1-weighted, contrast-enhanced magnetic resonance imaging (MRI) with manual segmentations were used for model training. After adequate preprocessing, an ensemble of convolutional neural networks (CNNs) was trained and validated for preoperative and postoperative automated segmentation of tumor tissue. Generalization was evaluated on a separate holdout set.

RESULTS

In total, 193 image sets were used for training and 20 were held out for validation. At validation using the holdout set, our models (preoperative / postoperative) demonstrated a median Dice score of 0.71 (0.27) / 0 (0), a mean Jaccard score of 0.53 ± 0.21/0.030 ± 0.085 and a mean 95th percentile Hausdorff distance of 3.89 ± 1.96./12.199 ± 6.684. Pearson's correlation coefficient for volume correlation was 0.85 / 0.22 and -0.14 for extent of resection. Gross total resection was detected with a sensitivity of 66.67% and specificity of 36.36%.

CONCLUSIONS

Our volumetry pipeline demonstrated its ability to accurately segment pituitary adenomas. This is highly valuable for lesion detection and evaluation of progression of pituitary incidentalomas. Postoperatively, however, objective and precise detection of residual tumor remains less successful. Larger datasets, more diverse data, and more elaborate modeling could potentially improve performance.

Mortality After Microsurgical Treatment of Unruptured Intracranial Aneurysms in the Modern Era

BACKGROUND

The incidence of mortality after treatment of unruptured intracranial aneurysms (UIAs) has been described historically. However, many advances in microsurgical treatment have since emerged, and most available data are outdated. We analyzed the incidence of mortality after microsurgical treatment of patients with UIAs treated in the past decade.

METHODS

The medical records of all patients with UIAs who underwent elective treatment at our large quaternary center from January 1, 2014, to December 31, 2020, were reviewed retrospectively. We analyzed mortality at discharge and 1-year follow-up as the primary outcome using univariate to multivariable progression with P < 0.20 inclusion.

RESULTS

During the 7-year study period, 488 patients (mean [SD] age = 58 [12] years) had UIAs treated microsurgically. Of these patients, 61 (12.5%) had a prior subarachnoid hemorrhage. One patient (0.2%) with a dolichoectatic vertebrobasilar aneurysm died while hospitalized, and 7 other patients (8 total; 1.6%) were determined to have died at 1-year follow-up (1 trauma, 2 myocardial infarction, 2 cerebrovascular accident, 1 pulmonary embolism, and 1 subdural hematoma complicated by abscess). On univariate analysis, significant risk factors for mortality at follow-up included diabetes mellitus, preoperative anticoagulant or antiplatelet use, aneurysm calcification, nonsaccular aneurysm, and higher American Society of Anesthesiologists grades (all P < 0.03). On multivariable logistic regression analysis, only nonsaccular aneurysms and higher American Society of Anesthesiologists grades were predictors of mortality.

CONCLUSIONS

A low mortality rate is associated with recent microsurgical treatment of UIAs. However, nonsaccular aneurysms and higher American Society of Anesthesiologists grades appear to be predictors of mortality.

The Site of Origin of Medulloblastoma: Surgical Observations Correlated to Molecular Groups

Developmental gene expression data from medulloblastoma (MB) suggest that WNT-MB originates from the region of the embryonic lower rhombic lip (LRL), whereas SHH-MB and non-WNT/non-SHH MB arise from cerebellar precursor matrix regions. This study aimed to analyze detailed intraoperative data with regard to the site of origin (STO) and compare these findings with the hypothesized regions of origin associated with the molecular group. A review of the institutional database identified 58 out of 72 pediatric patients who were operated for an MB at our department between 1996 and 2020 that had a detailed operative report and a surgical video as well as clinical and genetic classification data available for analysis. The STO was assessed based on intraoperative findings. Using the intraoperatively defined STO, "correct" prediction of molecular groups was feasible in 20% of WNT-MB, 60% of SHH-MB and 71% of non-WNT/non-SHH MB. The positive predictive values of the neurosurgical inspection to detect the molecular group were 0.21 (95% CI 0.08-0.48) for WNT-MB, 0.86 (95% CI 0.49-0.97) for SHH-MB and 0.73 (95% CI 0.57-0.85) for non-WNT/non-SHH MB. The present study demonstrated a limited predictive value of the intraoperatively observed STO for the prediction of the molecular group of MB.

SURG-02. The site of origin of medulloblastoma: Does the neurosurgical perspective support the current concept from molecular data?

BACKGROUND: Medulloblastoma (MB) are the most common malignant brain tumor in childhood. Developmental gene expression data supported by neuroradiological studies suggest that Wingless (WNT)-MB originate from the lower rhombic lip (LRL), Sonic-Hedgehog (SHH)-MB from the cerebellar hemispheres, and Group 3 and Group 4 MB from the cerebellar vermis. However, there is still insufficient evidence from a neurosurgical perspective supporting this proposed concept. METHODS: Clinical and molecular data from patients aged under 18 years at time of diagnosis who were operated on a histologically confirmed MB at the Department of Neurosurgery of the Medical University of Vienna between 1990 and 2020 were retrospectively analyzed. The location of the tumor origin was defined based on operative reports, surgical videos and preoperative imaging data by an experienced neurosurgeon blinded to the subgroup information. RESULTS: Sufficient data were available in 53 patients. In 28.6% (2 / 7) WNT-MB, 66.7% (6 / 9) SHH-MB and 70.3% (26 / 37) Group 3 and Group 4 MB, the intraoperatively defined site of origin corresponded well with the cellular origin suspected from the molecular subgroup. Within the WNT-subgroup, 57.1% (4 / 7) originated from the vermis, 28.6% (2 / 7) from the LRL and 14.3% (1 / 7) from the cerebellar hemisphere. The origin of SHH-MB was predominantly located in cerebellar hemispheres (66.7% (6 / 9)), while 33.3% (3 / 9) originated from the vermis. Of Group 3 and Group 4 MB, 70.3% (26 / 37) had their origin in the vermis and 29.7% (11 / 37) in the LRL.CONCLUSION: Our results indicate that there is a considerable level of inconsistency between the intraoperatively observed site of origin and the expected cellular origin based on the molecular subgroup, especially in WNT-MB. This discrepancy needs to be discussed when it comes to surgical decision-making accounting for risk stratification.

How can we optimize the long-term outcome in children with intracranial cavernous malformations? A single-center experience of 61 cases

The objective is to provide a treatment algorithm for pediatric patients with intracranial cavernous malformations (CMs) based on our experience. Patients < 18 years of age who were treated either surgically or conservatively at the authors' institution between 1982 and 2019 were retrospectively evaluated. A total of 61 pediatric patients were treated at the authors' institution: 39 with lobar CMs; 18 with deep CMs, including 12 in the brainstem and 6 in the basal ganglia; and 4 with CMs in the cerebellar hemispheres. Forty-two patients underwent surgery, and 19 were treated conservatively. The median follow-up time was 65 months (1-356 months). In surgically treated patients, lesions were larger (2.4 cm vs 0.9 cm, p < 0.001). In patients with lobar CMs, seizures were more common (72% vs 21%, p = 0.003) in the surgery group than in conservatively managed patients. In deep CMs, modified Rankin scale (mRS) was higher (4 vs 1, p = 0.003) in the surgery group than in conservatively treated patients. At the time of last follow-up, no differences in Wieser outcome class I were seen (86% vs 67%) in lobar CMs, and mRS scores had aligned between the treatment groups in deep CMs (1 vs 0). We encountered no new permanent neurological deficit at time of last follow-up. We propose a treatment algorithm according to lesion location and size, burden of symptoms, epilepsy workup, and further clinical course during observation. A conservative management is safe in pediatric patients with asymptomatic CMs. Gross total resection should be the aim in patients with symptomatic lobar CMs. A less aggressive approach with subtotal resection, when required to prevent neurological compromise, sustainably improves neurological outcome in patients with deep CMs.