Citations 3
Response Assessment in Pediatric Neuro-Oncology Symposium, Pediatric Society of Neuro-Oncology proceedings: Current status and future initiatives
Fangusaro, Jason, Warren, Katherine, Hargrave, Darren, Gampel, Bradley , Baxter, Patricia A, Perreault, Sébastien , Vézina, Gilbert , Mueller, Sabine, Kram, David E, Erker, Craig, Stuckert, Austin J. , Kazerooni, Anahita Fathi, Mahdi, Jasia , Leary, Sarah, Susan, N., Prados, Michael, Mankad, Kshitij, Salloum, Ralph , Reddy, A. O., Dhall, Girish, Lai, Holly, Rameh, Vanessa , Jaju, Alok , Laughlin, Suzanne , Green, Adam L. , Hwang, Eugene I., Silvera, V Michelle, Ho, Chang Y, Nabavizadeh, Ali, Kline, Cassie , Raju, Praveen, Shivaram, Avula, Kann, Benjamin H, Mirsky, Prof David M, Fangusaro, Jason , Warren, Katherine N, Hargrave, Darren R. , Robinson, Giles , Baxter, Patricia Ann , Mueller, Sabine , Takami, Hirokazu , Kram, David E. , Erker, Craig , Foreman, Nicholas K. , Kazerooni, Anahita Fathi , Leary, Sarah , Chi, Susan N , Prados, Michael D. , Tamrazi, Benita , Mankad, Kshitij , Gonçalves, Fabrício Guimarães , Hansford, Jordan R. , Reddy, Alyssa , Bhatia, Aashim , Bag, Asim Kumar , Wright, Jason N. , Bartels, Ute , Kilburn, Lindsay Baker , Robison, Nathan John , Mangum, Ross , Yeo, Kee Kiat , Lassaletta, Álvaro , Ho, Chang Yueh , Nabavizadeh, Ali , Margol, Ashley , Cohen, Kenneth J. , Avula, Shivaram , Kann, Benjamin H.
Neuro-Oncology Pediatrics | February 18, 2026 | Volume: 2 | Issue: 1 | Pages: No page available
Abstract Response Assessment in Pediatric Neuro-Oncology (RAPNO) is an international working group dedicated to developing standardized recommendations for response assessment in children with central nervous system tumors enrolled on clinical trials. This standardization facilitates easier and more reliable comparison of responses across trials. Since the first RAPNO publication in 2013, response guidelines have been issued for medulloblastoma (MB), low-grade glioma (LGG), high-grade glioma (HGG), diffuse intrinsic pontine glioma, ependymoma, and craniopharyngioma. Many of these guidelines have already been incorporated into clinical trials to evaluate their effectiveness and accuracy. RAPNO has always been predicated on the idea that these consensus recommendations will require updates over time as they are applied in practice given technological advancements, evolving treatment approaches, and growing knowledge of disease pathology. A half-day RAPNO symposium sponsored by the Society of Neuro-Oncology was held in San Diego, California, United States, on May 15, 2025. This event coincided with the 8th Biennial Pediatric Society of Neuro-Oncology meeting. The main objectives were to identify ongoing RAPNO challenges, discuss potential updates, and plan future initiatives across 3 specific groups: (1) LGG/Craniopharyngioma, (2) HGG/diffuse midline glioma (DMG)/Ependymoma, and (3) MB and other seeding tumors. This manuscript reviews the symposium proceedings and highlights key topics and challenges discussed, as well as outlining future RAPNO initiatives.
BraTS-PEDs: Results of the Multi-Consortium International Pediatric Brain Tumor Segmentation Challenge 2023
Kazerooni, Anahita Fathi , Khalili, Nastaran, Liu, Xinyang , Jiang, Zhifan , Pavaine, Julija , Jones, Blaise V. , Sheth, Nakul , McAllister, Aaron S. , Tu, Wenxin , Rodriguez, Andres Fernandez, Shaikh, Ibraheem S , Sanchez-Montano, Mariana , Lai, Hollie Anne , Adewole, Maruf , Albrecht, Jake, Anazodo, Udunna, Anwar, Syed Muhammed, Aristizábal, Alejandro , Baid, Ujjwal , Bergquist, Timothy , Conte, Gian-Marco, Eddy, James A. , Ezhov, Ivan , Gandhi, Deep , Gottipati, Anurag , Haldar, Shuvanjan, Janas, Anastasia , Elaine, Elaine, Karargyris, Alexandros , Kassem, Hasan, Khalili, Neda , Maleki, Nazanin , Meier, Zeke, Saluja, Rachit , Sheller, Micah , Shinohara, Russell Takeshi, Viswanathan, Karthik , Wang, Chunhao , Storm, Phillip B. , Packer, Roger, Hummel, Trent R. , Hoffman, Lindsey M. , Nabavizadeh, Ali , Ware, Jeffrey B., Rood, Brian , Resnick, Adam J., Linguraru, Marius George , Khalili, Nastaran, Haldar, Debanjan , Zapaishchykova, Anna , Shah, Lubdha M. , Prabhu, Sanjay P. , Nandolia, Khanak , Anderson, Hannah, Bagheri, Sina , Borja, Austin J. , Calabrese, Evan , Chung, Verena , Familiar, Ariana , Farahani, Keyvan , Iglesias, Juan Eugenio , Kofler, Florian , LaBella, Dominic , Leemput, Koen Van , Li, Hongwei , Meier, Zeke, Menze, Bjoern H. , Moawad, Ahmed W. , Pati, Sarthak , Piraud, Marie , Poussaint, Tina Young , Reitman, Zachary J. , Rudie, Jeffrey D. , Shinohara, Russell Taki , Wiestler, Benedikt , Wiggins, Walter F. , Davatzikos, Christos , Bornhorst, Miriam , Blank, Peter M K de , Aboian, Mariam , Kann, Benjamin H. , Bakas, Spyridon , Vossough, Arastoo
Machine Learning for Biomedical Imaging | June 26, 2025 | Volume: 3 | Issue: June 2025 | Pages: 72-87
Pediatric central nervous system tumors are the leading cause of cancer-related deaths in children. The five-year survival rate for high-grade glioma in children is less than 20%. The development of new treatments is dependent upon multi-institutional collaborative clinical trials requiring reproducible and accurate centralized response assessment. We present the results of the BraTS-PEDs 2023 challenge, the first Brain Tumor Segmentation (BraTS) challenge focused on pediatric brain tumors. This challenge utilized data acquired from multiple international consortia dedicated to pediatric neuro-oncology and clinical trials. BraTS-PEDs 2023 aimed to evaluate volumetric segmentation algorithms for pediatric brain gliomas from magnetic resonance imaging using standardized quantitative performance evaluation metrics employed across the BraTS 2023 challenges. The top-performing AI approaches for pediatric tumor analysis included ensembles of nnU-Net and Swin UNETR, Auto3DSeg, or nnU-Net with a self-supervised framework. The BraTS-PEDs 2023 challenge fostered collaboration between clinicians (neuro-oncologists, neuroradiologists) and AI/imaging scientists, promoting faster data sharing and the development of automated volumetric analysis techniques. These advancements could significantly benefit clinical trials and improve the care of children with brain tumors.
Artificial Intelligence Measured Tumor Burden and Pre‐Treatment Circulating Tumor DNA in Human Papilloma Virus‐Associated Oropharynx Cancer
Bakhtiar, Mina , Ye, Zezhong , Schoenfeld, Jonathan D. , Mohammadi, Homan , Kann, Benjamin H. , Guenette, Jeffrey P. , Rettig, Eleni M. , Hanna, Glenn J.
Head & Neck | May 5, 2025 | Volume: 47 | Issue: 10 | Pages: 2641-2649
ABSTRACTBackgroundArtificial intelligence (AI)‐based imaging analysis and circulating tumor‐associated DNA (ctDNA) are both being used diagnostically in HPV‐driven oropharynx squamous cell carcinoma (HPV‐OPSCC). We evaluated associations between AI‐measured tumor burden and ctDNA.MethodsWe analyzed 170 patients treated definitively for HPV‐OPSCC. All had pre‐treatment serum tumor‐tissue modified viral (TTMV) ctDNA levels. An AI algorithm measured tumor and lymph nodes on CT scans. Linear regressions detected associations between ctDNA (fragments/mL) and automated volumes, clinical tumor (T) and nodal (N) stage, and disease factors.ResultsAutomated tumor volume (coeff = 39.43, p < 0.001), nodal volume (coeff = 39.54, p < 0.001), T stage (coeff = 1031.09, p = 0.009), and N stage (coeff = 1840, p = 0.018) were associated with ctDNA. On multivariable analysis, tumor (coeff = 34.79, p = 0.001) and nodal volumes (coeff = 24.68, p = 0.022) were associated with ctDNA; T and N stage were not.ConclusionsAutomated volumetrics are independently and more strongly associated with ctDNA, compared with clinical stage. Automated volumetrics provide a practical correlate to ctDNA.