Bendok, Bernard R.

OBJECTIVE Chordomas are rare tumors from notochordal remnants and account for 1%–4% of all primary bone malignancies, often arising from the clivus and sacrum. Despite margin-negative resection and postoperative radiotherapy, chordomas often recur. Further, immunohistochemical (IHC) markers have not been assessed as predictive of chordoma recurrence. The authors aimed to identify the IHC markers that are predictive of postoperative long-term (≥ 1 year) chordoma recurrence by using trained multiple tree-based machine learning (ML) algorithms. METHODS The authors reviewed the records of patients who had undergone treatment for clival and spinal chordomas between January 2017 and June 2021 across the Mayo Clinic enterprise (Minnesota, Florida, and Arizona). Demographics, type of treatment, histopathology, and other relevant clinical factors were abstracted from each patient record. Decision tree and random forest classifiers were trained and tested to predict long-term recurrence based on unseen data using an 80/20 split. RESULTS One hundred fifty-one patients diagnosed and treated for chordomas were identified: 58 chordomas of the clivus, 48 chordomas of the mobile spine, and 45 chordomas sacrococcygeal in origin. Patients diagnosed with cervical chordomas were the oldest among all groups (58 ± 14 years, p = 0.009). Most patients were male (n = 91, 60.3%) and White (n = 139, 92.1%). Most patients underwent resection with or without radiation therapy (n = 129, 85.4%). Subtotal resection followed by radiation therapy (n = 51, 33.8%) was the most common treatment modality, followed by gross-total resection then radiation therapy (n = 43, 28.5%). Multivariate analysis showed that S100 and pan-cytokeratin are more likely to predict the increase in the risk of postoperative recurrence (OR 3.67, 95% CI 1.09–12.42, p= 0.03; and OR 3.74, 95% CI 0.05–2.21, p = 0.02, respectively). In the decision tree analysis, a clinical follow-up > 1897 days was found in 37% of encounters and a 90% chance of being classified for recurrence (accuracy = 77%). Random forest analysis (n = 500 trees) showed that patient age, type of surgical treatment, location of tumor, S100, pan-cytokeratin, and EMA are the factors predicting long-term recurrence. CONCLUSIONS The IHC and clinicopathological variables combined with tree-based ML tools successfully demonstrated a high capacity to identify recurrence patterns with an accuracy of 77%. S100, pan-cytokeratin, and EMA were the IHC drivers of recurrence. This shows the power of ML algorithms in analyzing and predicting outcomes of rare conditions of a small sample size.

Abstract High grade glioma (HGG) represents a group of devastating diseases with dismal prognosis. Surgical resection of the contrast enhancing (CE) region of HGG remains the mainstay of treatment, but recurrence inevitably arises from the unresected non-contrast enhancing (NE) region, surgically inaccessible due to cancer cell invasion into healthy brain tissue. Due to its critical role in recurrence, understanding of the NE region is central to the improvement of clinical outcomes. We reveal the biological characteristics of this region through image localized multi-regional sampling. We linked microenvironmental characteristics measured by multi-parametric MRI to genomic mutations and transcriptional phenotypes using mixed effect modeling which allowed us to control for individualized patient effects. We first confirmed that T2 is a significant indicator of IDH mutation status in the NE region, being the first description of such a relationship in a HGG cohort. We found the combination of EGFR amplification and CDKN2A homozygous loss was associated with a significantly lower mean diffusivity (MD) compared to double wild type tumors in the NE region, indicating the presence of greater cellular packing and proliferation in EGFR amplification/CDKN2A loss regions. Finally, using single cell pathway based tumor classifications, we showed that nK2, a DSC-MRI metric representing cell size heterogeneity, correlated positively with neuronal signature and negatively with glycolytic/plurimetabolic signature within the NE tumor, indicating that glycolytic/plurimetobolic tumors possessed a high amount of cell size heterogeneity compared to neuronal samples. This hypothesis was supported using digital reference object (DRO) modeling which confirmed that cell size and heterogeneity drove the differential nK2 signal between neuronal and glycolytic/plurimetabolic samples. We identified immune cell infiltrate as one possible mechanism of increased cell size heterogeneity using transcriptomic signature analysis which found more immune cell signatures within glycolytic/plurimetobolic tumors compared to neuronal. Collectively this study demonstrates the central role of multi-parametric MRI as a non-invasive measure of tumor biology and a tool for understanding the clinically critical NE region which can then inform new therapies targeting this region of HGG recurrence. Citation Format: Matthew Flick, Taylor Weiskittel, Kevin Meng-Lin, Fulvio D'Angelo, Francesca Caruso, Shannon Ensign, Mylan Blomquist, Luija Wang, Christopher Sereduk, Gustavo De Leon, Ashley Nespodzany, Javier Urcuyo, Ashlynn Gonzalez, Lee Curtin, Kyle Singleton, Aliya Anil, Natenael Simmineh, Erika Lewis, Teresa Noviello, Reyna Patel, Panwen Wang, Junwen Wang, Jennifer Eschbacher, Andrea Hawkins-Daarud, Pamela Jackson, Kris Smith, Peter Nakaji, Bernard Bendok, Richard Zimmerman, Chandan Krishna, Devi Patra, Naresh Patel, Mark Lyons, Matthew Neal, Kliment Donev, Maciej Mrugala, Alyx Porter, Scott Beeman, Yuxiang Zhou, Leslie Baxter, Christopher Plaisier, Jing Li, Hu Li, Anna Lasorella, Chad Quarles, Kristin Swanson, Michele Ceccarelli, Antonio Iavarone, Nhan Tran, Leland Hu. Multi-parametric MRI maps regional heterogeneity of high grade glioma phenotypes. [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 5621.

Abstract Introduction: Extracranial vertebral artery aneurysms are rare complications from trauma and multiple diseases. However, the difference between clinical and surgical profiles is not well understood. Objective To investigate the clinical and interventional outcomes following extracranial vertebral artery aneurysms (VAA) treatment through a systematic review of the literature to date. Methods An electronic database search for full-text English articles was conducted following PRISMA guidelines. The search yielded results on clinical and surgical outcomes for extracranial VAAs. These results included patient-specific risk factors, indications, and techniques. Results Our literature search yielded 561 articles, of which 36 studies were qualified to be included in the analysis. A total of 55 patients with multiple various extracranial VAA incidents were included. The mean age of subjects was 42 years (ranging from 13 to 76 years), and most patients were males (71%, n = 39). Blunt trauma was the most frequent risk factor for extracranial VAA formation (35%, n = 19). The majority of aneurysms (60%) were dissecting in nature. The most common form of treatment for extracranial VAAs was a flow diverter (24%, n = 13). Overall, five (9%) patients had long-term adverse neurological complications following intervention with 5% (n = 3) mortality, 2% (n = 1) resulting in unilateral vocal cord paralysis, and 2% (n = 1) resulting in a positive Romberg sign. The mortality rate is 15.7% in the surgical group, whereas the endovascular treatment did not result in any mortality. Conclusion The endovascular approach is a safe and effective treatment of extracranial VAAs due to its relatively low overall complication rate and lack of resulting mortality. This contrasts with the surgical approach, which results in a higher rate of complications, recurrence, and mortality outcomes. An understanding of the factors and clinical outcomes associated with the incidence of extracranial VAAs is essential for the future improvement of patient outcomes.

Abstract INTRODUCTION Multiple meningiomas (MM) occurs in up to 18% of meningioma patients and progression data are scarce. The objective of this study is to explore the influence of number of lesions and clinical characteristics on progression-free survival (PFS) and time to a second intervention (TTSI) in patients with WHO grade 1 meningiomas. METHODS We retrospectively reviewed records of all adults diagnosed with a meningioma at our three main sites from January 2009 to May 2020. Progression was considered as time from diagnosis until radiographic progression of the originally resected meningioma. A secondary analysis was carried to evaluate the time from diagnosis to time of a second intervention. Univariable and multivariable analyses were conducted to assess whether number of lesions or any associated variables (age, sex, race, radiation, location, and extent of resection) had a significant impact on PFS and TTSI. RESULTS 838 patients were included. Log-rank test evaluating PFS and TTSI between single and multiple lesions showed significantly shorter progression for MM (p< 0.001 and p< 0.001, respectively). Multivariable Cox regression showed significantly inferior PFS on MM vs. single lesion (HR 2.262 [CI 95%, 1.392-3.677], p=0.001) and a significantly inferior TTSI for patients with MM vs. single meningioma (HR 2.377 [CI 95%, 1.617 – 3.494], p=0.001). When input as a continuous variable, PFS was significantly inferior for each additional meningioma (HR 1.350 [CI 95% 1.074-1.698], p=0.010) and TTSI is significantly inferior as well (HR 1.428 [CI 95% 1.189 – 1.716], p< 0.001). African-Americans had an inferior PFS when compared to Non-Hispanic White patients (HR 3.472 [CI 95% 1.083-11.129], p=0.036). CONCLUSION The PFS of meningiomas is influenced by the number of lesions present. Patients with MM are more prone to undergo a second intervention for progressive disease. Hence, a closer follow-up may be warranted in patients who present with multiple lesions.