Use of a machine learning algorithm with a focus on spinopelvic parameters to predict development of symptomatic tethered cord after initial untethering surgery

OBJECTIVE

Among patients with a history of prior lipomyelomeningocele repair, an association between increased lumbosacral angle (LSA) and cord retethering has been described. The authors sought to build a predictive algorithm to determine which complex tethered cord patients will develop the symptoms of spinal cord retethering after initial surgical repair with a focus on spinopelvic parameters.

METHODS

An electronic medical record database was reviewed to identify patients with complex tethered cord (e.g., lipomyelomeningocele, lipomyeloschisis, myelocystocele) who underwent detethering before 12 months of age between January 1, 2008, and June 30, 2022. Descriptive statistics were used to characterize the patient population. The Caret package in R was used to develop a machine learning model that predicted symptom development by using spinopelvic parameters.

RESULTS

A total of 72 patients were identified (28/72 [38.9%] were male). The most commonly observed dysraphism was lipomyelomeningocele (41/72 [56.9%]). The mean ± SD age at index MRI was 2.1 ± 2.2 months, at which time 87.5% of patients (63/72) were asymptomatic. The mean ± SD lumbar lordosis at the time of index MRI was 23.8° ± 11.1°, LSA was 36.5° ± 12.3°, sacral inclination was 30.4° ± 11.3°, and sacral slope was 23.0° ± 10.5°. Overall, 39.6% (25/63) of previously asymptomatic patients developed new symptoms during the mean ± SD follow-up period of 44.9 ± 47.2 months. In the recursive partitioning model, patients whose LSA increased at a rate ≥ 5.84°/year remained asymptomatic, whereas those with slower rates of LSA change experienced neurological decline (sensitivity 77.5%, specificity 84.9%, positive predictive value 88.9%, and negative predictive value 70.9%).

CONCLUSIONS

This is the first study to build a machine learning algorithm to predict symptom development of spinal cord retethering after initial surgical repair. The authors found that, after initial surgery, patients who demonstrate a slower rate of LSA change per year may be at risk of developing neurological symptoms.

Abstract 3566: Expansion of the Pediatric Brain Tumor Atlas: Children's Brain Tumor Network, Kids First Data Resource and Childhood Cancer Data Initiative Open Science effort

Pediatric central nervous system (CNS) cancers are the leading disease-related cause of death in children and there is urgent need for curative therapeutic strategies for these tumors. To address the urgency, Children’s Brain Tumor Network (CBTN) has advanced an open science model to accelerate the research discovery for pediatric brain tumors. In first phase of Open Pediatric Brain Tumor Atlas (OpenPBTA) effort CBTN together with Pacific Pediatric Neuro-Oncology Consortium (PNOC) with support of Gabriella Miller Kids First Data Resource Center (KFDRC) created and comprehensively characterized over 1000 clinically annotated pediatric brain tumors.

In the second phase of the OpenPBTA effort, through resource awards and collaboration across KFDRC, the NCI Childhood Cancer Data Initiative (CCDI), NCI’s Clinical Proteomic Tumor Analysis Consortium (CPTAC), NCI Center for Cancer Research and additional partnered institutions and foundations, CBTN has expanded OpenPBTA to support high throughput molecular characterization for an additional 1900 pediatric brain tumor patients and their families. This includes the processing and characterization of over 8000 specimens across >50 brain tumor diagnoses. The cohort expansion builds on >1000 previously characterized samples with a portfolio of multimodal data including whole genome sequencing, RNA sequencing, miRNA sequencing, methylation sequencing, proteomics, lipidomics and/or metabolomics. Molecular data is linked to patient longitudinal clinical data, imaging data (MRIs and radiology reports), histology slide images, and pathology reports. To inform novel discovery and clinical implementation of genomic approaches for diagnostic/therapeutic purposes, the data is deposited the cloud-based research environment of the NCI’s CCDI and the KFDRC to provide near real-time integration, dissemination, processing, and sharing of associated petabyte-scale harmonized data. The approach leverages the DRC platform’s cloud-based computational environment in CAVATICA. Processed annotations are facilitated via CAVATICA-enabled shareable pipelines and can be explored through PedcBioPortal, a data visualization/analysis application further integrating additional public and deposited datasets. This expansion phase of OpenPBTA is released with no embargo period and provides one of the largest deeply characterized cohorts of pediatric brain tumor samples and associated clinical data for >3000 pediatric brain tumor patients. CBTN’s open-science, rapid-release model aims to advance novel biomarkers and therapeutic exploratory research, supporting new clinical trial development and accelerated discovery on behalf of changing the outcome for kids with brain tumors.

Citation Format: Mateusz P. Koptyra, Komal Rahti, Yuankun Zhu, Bailey Farrow, Daniel Miller, Adam Kraya, Yiran Guo, Peter Madsen, Nicholas Van Kuren, Xiaoyan Huang, Miguel A. Brown, Jennifer L. Mason, Meen Chul Kim, Allison P. Heath, Brian M. Ennis, Bo Zhang, Jena V. Lilly, Jo Lynne Rokita, Christopher Friedman, Ximena P. Cuellar, Catherine A. Sullivan, Noel Coleman, Trang Duros, Thinh Q. Nguyen, Emmett C. Drake, Zeinab Helili, Beth A. Frenkel, Gerri R. Trooskin, Ariana Familiar, Karthik Viswanathan, Christopher M. Beck, Madison L. Hollawell, Valerie P. Baubet, Cassie Kline, Mariarita Santi, Tatiana S. Patton, Stephanie Stefankiewicz, Arya Kamnaa, Ryan A. Velasco, Dani Cardona, Phillip J. Storm, Adam C. Resnick, o/b/o Children's Brain Tumor Network. Expansion of the Pediatric Brain Tumor Atlas: Children's Brain Tumor Network, Kids First Data Resource and Childhood Cancer Data Initiative Open Science effort. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 3566.

Diffuse leptomeningeal glioneuronal tumor in a child masquerading as an intramedullary spinal pilocytic astrocytoma

Diffuse leptomeningeal glioneuronal tumor (DLGNT) occurs predominantly in children and is typically characterized by diffuse leptomeningeal lesions throughout the neuroaxis with focal segments of parenchymal involvement. Recent reports have identified cases without diffuse leptomeningeal involvement that retain classic glioneuronal features on histology. In this report, we present a case of a 4-year-old boy with a large cystic-solid intramedullary spinal cord lesion that on surgical biopsy revealed a biphasic astrocytic tumor with sparsely distributed eosinophilic granular bodies and Rosenthal fibers. Next-generation sequencing revealed a KIAA1549-BRAF fusion, 1p/19q codeletion, and lack of an IDH1 mutation. Methylation profiling demonstrated a calibrated class score of 0.98 for DLGNT and copy number loss of 1p. Despite the morphologic similarities to pilocytic astrocytoma and the lack of oligodendroglial/neuronal components or leptomeningeal dissemination, the molecular profile was definitive in classifying the tumor as DLGNT. This case highlights the importance of molecular and genetic testing in the characterization of pediatric central nervous system tumors.

Large scalp venous malformation in a pediatric patient managed with sclerotherapy and surgery: a case report and review of literature

BACKGROUND

Venous malformations (VMs) are slow-flow vascular anomalies present at birth that enlarge during adolescence, subsequently causing thrombosis, hemorrhage, and pain.

CASE PRESENTATION

We describe a case of an adolescent male presenting with a large scalp venous malformation. Given the size and location of the lesion, a hybrid approach employing both sclerotherapy and surgical resection was utilized. The VM was successfully removed without complication.

CONCLUSION

A hybrid approach is a safe and effective treatment consideration for immediate management of large venous malformation in higher-risk locations.