Sacit Bulent Omay, Yu-Ning Chen, Joao Paulo Almeida, Armando Saul Ruiz-Treviño, John A. Boockvar, Philip E. Stieg, Jeffrey P. Greenfield, Mark M. Souweidane, Ashutosh Kacker, David J. Pisapia, Vijay K. Anand and Theodore H. Schwartz
Exome sequencing studies have recently demonstrated that papillary craniopharyngiomas (PCPs) and adamantinomatous craniopharyngiomas (ACPs) have distinct genetic origins, each primarily driven by mutually exclusive alterations: either BRAF (V600E), observed in 95% of PCPs, or CTNNB1, observed in 75%–96% of ACPs. How the presence of these molecular signatures, or their absence, correlates with clinical, radiographic, and outcome variables is unknown.
The pathology records for patients who underwent surgery for craniopharyngiomas between May 2000 and March 2015 at Weill Cornell Medical College were reviewed. Craniopharyngiomas were identified and classified as PCP or ACP. Patients were placed into 1 of 3 groups based on their genomic mutations: BRAF mutation only, CTNNB1 mutation only, and tumors with neither of these mutations detected (not detected [ND]). Demographic, radiological, and clinical variables were collected, and their correlation with each genomic group was tested.
Histology correlated strongly with mutation group. All BRAF tumors with mutations were PCPs, and all CTNNB1 with mutations and ND tumors were ACPs. Preoperative and postoperative clinical symptoms and radiographic features did not correlate with any mutation group. There was a statistically significant relationship (p = 0.0323) between the age group (pediatric vs adult) and the mutation groups. The ND group tumors were more likely to involve the sella (p = 0.0065).
The mutation signature in craniopharyngioma is highly predictive of histology. The subgroup of tumors in which these 2 mutations are not detected is more likely to occur in children, be located in the sella, and be of ACP histology.
Swathi Chidambaram, Susan C. Pannullo, Michelle Roytman, David J. Pisapia, Benjamin Liechty, Rajiv S. Magge, Rohan Ramakrishna, Philip E. Stieg, Theodore H. Schwartz and Jana Ivanidze
There is a need for advanced imaging biomarkers to improve radiation treatment planning and response assessment. T1-weighted dynamic contrast-enhanced perfusion MRI (DCE MRI) allows quantitative assessment of tissue perfusion and blood-brain barrier dysfunction and has entered clinical practice in the management of primary and secondary brain neoplasms. The authors sought to retrospectively investigate DCE MRI parameters in meningiomas treated with resection and adjuvant radiation therapy using volumetric segmentation.
A retrospective review of more than 300 patients with meningiomas resected between January 2015 and December 2018 identified 14 eligible patients with 18 meningiomas who underwent resection and adjuvant radiotherapy. Patients were excluded if they did not undergo adjuvant radiation therapy or DCE MRI. Demographic and clinical characteristics were obtained and compared to DCE perfusion metrics, including mean plasma volume (v
p), extracellular volume (v
e), volume transfer constant (K
trans), rate constant (k
ep), and wash-in rate of contrast into the tissue, which were derived from volumetric analysis of the enhancing volumes of interest.
The mean patient age was 64 years (range 49–86 years), and 50% of patients (7/14) were female. The average tumor volume was 8.07 cm3 (range 0.21–27.89 cm3). The median Ki-67 in the cohort was 15%. When stratified by median Ki-67, patients with Ki-67 greater than 15% had lower median v
p (0.02 vs 0.10, p = 0.002), and lower median wash-in rate (1.27 vs 4.08 sec−1, p = 0.04) than patients with Ki-67 of 15% or below. Logistic regression analysis demonstrated a statistically significant, moderate positive correlation between v
e and time to progression (r = 0.49, p < 0.05). Furthermore, there was a moderate positive correlation between K
trans and time to progression, which approached, but did not reach, statistical significance (r = 0.48, p = 0.05).
This study demonstrates a potential role for DCE MRI in the preoperative characterization and stratification of meningiomas, laying the foundation for future prospective studies incorporating DCE as a biomarker in meningioma diagnosis and treatment planning.