Hersh, David S.

BACKGROUND AND OBJECTIVES: Myelomeningocele is defined by the presence of a fluid-filled sac that contains the neural placode and cerebrospinal fluid (CSF) at the level of the spinal defect. Alternatively, the term myeloschisis is used when the neural placode is not contained within a CSF-filled sac. While both are eligible for prenatal closure, few studies have characterized the impact of the type of lesion on postnatal outcomes. This study compares the outcomes of these 2 types of open spinal dysraphism using data from the Fetal Myelomeningocele Consortium registry sponsored by the North American Fetal Therapy Network. METHODS: The prospective observational Fetal Myelomeningocele Consortium registry was used to extract deidentified data corresponding to patients who underwent fetal closure of myelomeningocele vs myeloschisis. Demographics, operative characteristics, perioperative complications, and postnatal outcomes were collected. RESULTS: A total of 1327 patients were identified, including 991 (74.7%) with myelomeningocele and 336 (25.3%) with myeloschisis. Compared with myelomeningocele, myeloschisis was associated with lower rates of prenatal talipes (11% vs 24%, P < .001) and higher rates of favorable prenatal movement (94% vs 86%, P < .001). Postnatally, myeloschisis conferred higher rates of leg movement (97% vs 90%, P = .002) and an increased likelihood of ambulation in the household (10.4% vs 4.1%, P = .009) and outside (7.2% vs 1.9%, P = .004) at 1 year. However, myeloschisis was also linked to greater use of skin patches during closure (49% vs 27%, P < .001), higher CSF leak rates among those with wound dehiscence (26% vs 8%, P = .014), and more frequent CSF diversion and tethered cord surgeries at follow-up. CONCLUSION: Myeloschisis and myelomeningocele demonstrate distinct clinical profiles. Although patients with myeloschisis may have favorable motor outcomes, they are also characterized by higher rates of CSF leakage, CSF diversion, and tethered cord surgery. These findings highlight the need for lesion-specific prognostication and may inform surgical planning and parental counseling in the context of prenatal spina bifida closure.

BACKGROUND AND OBJECTIVES: The Management of Myelomeningocele Study established a role for maternal-fetal surgery for myelomeningocele (MMC) but was limited to patients with a maternal body mass index (BMI) less than 35 kg/m 2 . However, as the rate of obesity has increased globally, some centers have extended the Management of Myelomeningocele Study criteria to include patients with a BMI of 35 to 40 kg/m 2 . We used the Fetal MMC Consortium registry to analyze the complications associated with maternal-fetal surgery in patients with a maternal BMI < 35 kg/m 2 compared with 35 to 40 kg/m 2 . METHODS: The prospective observational Fetal MMC Consortium registry sponsored by the North American Fetal Therapy Network was used to extract deidentified “maternal complication” and “fetal/neonatal complication” data sets, corresponding to patients with complete entries related to maternal or fetal/neonatal complications, respectively. Demographics, clinical characteristics, and complications were recorded. Propensity score matching was conducted with a 2:1 algorithm, and outcomes were compared between patients with BMI < 35 kg/m 2 and those with BMI 35 to 40 kg/m 2 . RESULTS: Propensity score matching resulted in 156 patients with BMI < 35 kg/m 2 and 78 patients with BMI 35 to 40 kg/m 2 in the “maternal complication” data set, and 130 patients with BMI < 35 kg/m 2 and 65 patients with BMI 35 to 40 kg/m 2 in the “fetal/neonatal complication” data set. No significant differences in the median number of maternal (2.0 vs 2.0; P = .257) or median number of fetal/neonatal (1.0 vs 1.0; P = .409) complications were observed between the 2 cohorts. Furthermore, prematurity rates did not differ significantly between the BMI < 35 and BMI 35 to 40 cohorts. CONCLUSION: Maternal-fetal surgery for open neural tube defect closure is not associated with increased risks among patients with a maternal BMI of 35 to 40 kg/m 2 . Extending the initial inclusion criteria for prenatal MMC closure has the potential to expand access to patients with a higher risk for open neural tube defects.

OBJECTIVE Neurosurgeon scientists play a unique role in advancing neuroscience research. While previous publications have explored trends in federal and foundation funding among neurosurgeons, funding is often dominated by neurosurgical oncologists and functional neurosurgeons. Less is known about the research efforts of pediatric neurosurgeons. The aim of this study was to survey the members of the American Society of Pediatric Neurosurgeons (ASPN) to provide an overview of past research experience, current involvement, funding, and research priorities among pediatric neurosurgeons, and to gather insights that could shape future efforts to advance pediatric neurosurgical research. METHODS A survey was developed using the REDCap platform and distributed to all ASPN members via email. Survey questions used branching logic and were organized into 5 sections: 1) demographics, 2) research experience during training, 3) research experience as an attending physician, 4) research priorities, and 5) multicenter consortiums. RESULTS One hundred thirty-nine respondents completed more than half of the survey, for an overall response rate of 52.1%. Most respondents (96.4%) participated in research during their training, but only 38.1% had received a grant during training. In contrast, 83.9% of respondents were actively engaged in research as an attending physician, and 48.7% reported active funding (60.7% federal, 41.8% from foundations, and 42.9% internal). Furthermore, 74.8% of respondents reported being a member of a multicenter research consortium, and 82.4% agreed that multicenter research is important. Seventy percent of respondents agreed that the ASPN should facilitate multicenter consortium-based pediatric neurosurgical research, offering free-text responses with the following suggestions: 1) set aside time at the annual meeting to discuss multicenter research (22.9%); 2) encourage collaboration and facilitate networking (42.9%); 3) provide centralized core services such as a data coordinator and biostatistician (12.9%); and 4) provide training, education, and mentoring (7.1%). CONCLUSIONS The survey provided a cross-sectional analysis of the pediatric neurosurgical research landscape, highlighting the current state of research experience, funding, and the perspectives of pediatric neurosurgeons regarding research priorities. Despite the challenges, there is clear recognition of the importance of multicenter research collaboration. These findings reinforce the ongoing necessity of organized initiatives to support pediatric neurosurgical research and offer actionable insights into how organized pediatric neurosurgery can contribute to this critical endeavor.

OBJECTIVE Sagittal craniosynostosis is the most common form of craniosynostosis and typically results in scaphocephaly, which is characterized by biparietal narrowing, compensatory frontal bossing, and an occipital prominence. The cephalic index (CI) is a simple metric for quantifying the degree of cranial narrowing and is often used to diagnose sagittal craniosynostosis. However, patients with variant forms of sagittal craniosynostosis may present with a "normal" CI, depending on the part of the suture that is closed. As machine learning (ML) algorithms are developed to assist in the diagnosis of cranial deformities, metrics that reflect the other phenotypic features of sagittal craniosynostosis are needed. In this study the authors sought to describe the posterior arc angle (PAA), a measurement of biparietal narrowing that is obtained with 2D photographs, and elucidate the role of PAA as an adjuvant to the CI in characterizing scaphocephaly and the potential relevance of PAA in new ML model development. METHODS The authors retrospectively reviewed 1013 craniofacial patients treated during the period from 2006 to 2021. Orthogonal top-down photographs were used to calculate the CI and PAA. Distribution densities, receiver operating characteristic (ROC) curves, and chi-square analyses were used to describe the relative predictive utility of each method for sagittal craniosynostosis. RESULTS In total, 1001 patients underwent paired CI and PAA measurements and a clinical head shape diagnosis (sagittal craniosynostosis, n = 122; other cranial deformity, n = 565; normocephalic, n = 314). The area under the ROC curve (AUC) for the CI was 98.5% (95% confidence interval 97.8%–99.2%, p < 0.001), with an optimum specificity of 92.6% and sensitivity of 93.4%. The PAA had an AUC of 97.4% (95% confidence interval 96.0%–98.8%, p < 0.001) with an optimum specificity of 94.9% and sensitivity of 90.2%. In 6 of 122 (4.9%) cases of sagittal craniosynostosis, the PAA was abnormal while the CI was normal. This means that adding a PAA cutoff branch to a partition model increases the detection of sagittal craniosynostosis. CONCLUSIONS Both CI and PAA are excellent discriminators for sagittal craniosynostosis. Using an accuracy-optimized partition model, the addition of the PAA to the CI increased model sensitivity compared to using the CI alone. Using a model that incorporates both CI and PAA could assist in the early identification and treatment of sagittal craniosynostosis via automated and semiautomated algorithms that utilize tree-based ML models.

OBJECTIVE Quantitative measurements of trigonocephaly can be used to characterize and track this phenotype, which is associated with metopic craniosynostosis. Traditionally, trigonocephaly metrics were extracted from CT scans; however, this method exposes patients to ionizing radiation. Three-dimensional optical scans are another option but are not routinely available in most outpatient settings. Recently, the authors developed semiautomated artificial intelligence algorithms that extract craniometric data from orthogonal 2D photographs. Although 2D photographs are safe, inexpensive, and straightforward to obtain, the accuracy of photograph-based craniometrics in comparison to CT and 3D optical scan correlates has not been established. In this study the authors compared the classification power of 2D photograph–based metrics of trigonocephaly with four CT-based metrics and one 3D optical scan–based metric in a heterogeneous series of patients who presented to an outpatient craniofacial clinic. METHODS In this study the authors performed retrospective craniometric analyses of patient 2D photographs, 3D optical scans, and CT scans. Imaging-derived craniometrics include the 2D photograph–based anterior arc angle (AAA2D-photo), anterior-posterior ratio (APR2D-photo), and anterior-middle ratio (AMR2D-photo); the CT-based anterior arc angle (AAACT), metopic index (MICT), endocranial-bifrontal angle (eBFACT), and interfrontal angle (IFACT); and the 3D optical scan–based anterior arc angle (AAA3D-optical). Receiver operating characteristics (ROCs) were used to identify craniometrics strongly descriptive of trigonocephaly. Interrater comparisons were made between paired trigonocephaly measurements obtained from photographs and either CT scans or 3D optical scans. RESULTS There were 13 photograph-based and CT-based pairs and 22 paired measurements from 2D photographs and 3D optical scans. AAA displayed the strongest classification capacity across all three imaging modalities. Significant agreement was observed between AAACT and AAA2D-photo (intraclass correlation coefficient [ICC] = 0.68 [95% CI 0.24–0.89], p = 0.0035), and AAA3D-optical and AAA2D-photo (ICC = 0.70 [95% CI 0.41–0.87], p < 0.0001). There was no significant correlation between APR2D-photo or AMR2D-photo and conventional CT-based metrics describing longitudinal width ratios (MICT). CONCLUSIONS Photograph-based craniometrics are powerful tools that can be used to quantify the severity of trigonocephaly and exhibit high concordance with standard measurements derived from CT scans and 3D optical scans. The authors developed and freely share a research-use application to calculate trigonocephaly metrics from 2D photographs. Given the availability of digital photography, lack of ionizing radiation, and low cost of photograph-based craniometric derivation, this technique may be useful to supplement routine ambulatory care and objectively track outcomes following treatment.

Glioblastoma (GBM) is a highly aggressive and lethal form of primary brain cancer. Numerous barriers exist to the effective treatment ofGBMincluding the tightly controlled interface between the bloodstream and central nervous system termed the ‘neurovascular unit,’ a narrow and tortuous tumor extracellular space containing a dense meshwork of proteins and glycosaminoglycans, and genomic heterogeneity and instability. A major goal ofGBMtherapy is achieving sustained drug delivery to glioma cells while minimizing toxicity to adjacent neurons and glia. Targeted nanotherapeutics have emerged as promising drug delivery systems with the potential to improve pharmacokinetic profiles and therapeutic efficacy. Some of the key cell surface molecules that have been identified asGBMtargets include the transferrin receptor, low‐density lipoprotein receptor‐related protein, αvβ3integrin, glucose transporter(s), glial fibrillary acidic protein, connexin 43, epidermal growth factor receptor (EGFR),EGFRvariantIII, interleukin‐13 receptor α chain variant 2, and fibroblast growth factor‐inducible factor 14. However, most targeted therapeutic formulations have yet to demonstrate improved efficacy related to disease progression or survival. Potential limitations to current targeted nanotherapeutics include: (1) adhesive interactions with nontarget structures, (2) low density or prevalence of the target, (3) lack of target specificity, and (4) genetic instability resulting in alterations of either the target itself or its expression level in response to treatment. In this review, we address these potential limitations in the context of the keyGBMtargets with the goal of advancing the understanding and development of targeted nanotherapeutics forGBM.WIREs Nanomed Nanobiotechnol2017, 9:e1439. doi: 10.1002/wnan.1439This article is categorized under:Therapeutic Approaches and Drug Discovery > Emerging TechnologiesTherapeutic Approaches and Drug Discovery > Nanomedicine for Neurological DiseaseTherapeutic Approaches and Drug Discovery > Nanomedicine for Oncologic Disease