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2. Joint EANM/EANO/RANO/SNMMI practice guideline/procedure standards for diagnostics and therapy (theranostics) of meningiomas using radiolabeled somatostatin receptor ligands: version 1.0

Author

Albert, Nathalie L., Preusser, Matthias, Traub-Weidinger, Tatjana, Tolboom, Nelleke, Law, Ian, Palmer, Joshua D., Guedj, Eric, Furtner, Julia, Fraioli, Francesco, Huang, Raymond Y., Johnson, Derek R., Deroose, Christophe M., Herrmann, Ken, Vogelbaum, Michael, Chang, Susan, Tonn, Joerg-Christian, Weller, Michael, Wen, Patrick Y., van den Bent, Martin J., Verger, Antoine, Ivanidze, Jana, and Galldiks, Norbert

Published
2024
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3. Stereotactic Radiosurgery for Women Older than 65 with Breast Cancer Brain Metastases.

Author

Upadhyay, Rituraj, Klamer, Brett, Perlow, Haley, White, Julia, Bazan, Jose, Jhawar, Sachin, Blakaj, Dukagjin, Grecula, John, Arnett, Andrea, Mestres-Villanueva, Mariella, Healy, Erin, Thomas, Evan, Chakravarti, Arnab, Raval, Raju, Lustberg, Maryam, Williams, Nicole, Palmer, Joshua, and Beyer, Sasha

Subjects
breast cancer, geriatric cancer, oligometastases, radiation therapy, stereotactic radiosurgery
Abstract

BACKGROUND: Breast cancer is the second most common cause of brain metastases (BM). Despite increasing incidence of BM in older women, there are limited data on the optimal management of BM in this age group. In this study, we assessed the survival outcomes and treatment patterns of older breast cancer patients ≥65 years old with BM compared to younger patients at our institution. METHODS: An IRB-approved single-institutional retrospective review of biopsy-proven breast cancer patients with BM treated with 1- to 5-fraction stereotactic radiation therapy (SRS) from 2015 to 2020 was performed. Primary endpoint was intracranial progression-free survival (PFS) defined as the time interval between the end of SRS to the date of the first CNS progression. Secondary endpoints were overall survival (OS) from the end of SRS and radiation treatment patterns. Kaplan-Meier estimates and Cox proportional hazard regression method were used for survival analyses. RESULTS: A total of 112 metastatic breast cancer patients with BMs were included of which 24 were ≥65 years old and 88 were

Published
2023

4. Targeted gene expression profiling predicts meningioma outcomes and radiotherapy responses

Author

Chen, William C, Choudhury, Abrar, Youngblood, Mark W, Polley, Mei-Yin C, Lucas, Calixto-Hope G, Mirchia, Kanish, Maas, Sybren LN, Suwala, Abigail K, Won, Minhee, Bayley, James C, Harmanci, Akdes S, Harmanci, Arif O, Klisch, Tiemo J, Nguyen, Minh P, Vasudevan, Harish N, McCortney, Kathleen, Yu, Theresa J, Bhave, Varun, Lam, Tai-Chung, Pu, Jenny Kan-Suen, Li, Lai-Fung, Leung, Gilberto Ka-Kit, Chan, Jason W, Perlow, Haley K, Palmer, Joshua D, Haberler, Christine, Berghoff, Anna S, Preusser, Matthias, Nicolaides, Theodore P, Mawrin, Christian, Agnihotri, Sameer, Resnick, Adam, Rood, Brian R, Chew, Jessica, Young, Jacob S, Boreta, Lauren, Braunstein, Steve E, Schulte, Jessica, Butowski, Nicholas, Santagata, Sandro, Spetzler, David, Bush, Nancy Ann Oberheim, Villanueva-Meyer, Javier E, Chandler, James P, Solomon, David A, Rogers, C Leland, Pugh, Stephanie L, Mehta, Minesh P, Sneed, Penny K, Berger, Mitchel S, Horbinski, Craig M, McDermott, Michael W, Perry, Arie, Bi, Wenya Linda, Patel, Akash J, Sahm, Felix, Magill, Stephen T, and Raleigh, David R

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Oncology and Carcinogenesis, Cancer, Clinical Research, Brain Disorders, Brain Cancer, Rare Diseases, 4.2 Evaluation of markers and technologies, Detection, screening and diagnosis, Humans, Biomarkers, Gene Expression Profiling, Meningeal Neoplasms, Meningioma, Neoplasm Recurrence, Local, Prospective Studies, Medical and Health Sciences, Immunology, Biomedical and clinical sciences, Health sciences
Abstract

Surgery is the mainstay of treatment for meningioma, the most common primary intracranial tumor, but improvements in meningioma risk stratification are needed and indications for postoperative radiotherapy are controversial. Here we develop a targeted gene expression biomarker that predicts meningioma outcomes and radiotherapy responses. Using a discovery cohort of 173 meningiomas, we developed a 34-gene expression risk score and performed clinical and analytical validation of this biomarker on independent meningiomas from 12 institutions across 3 continents (N = 1,856), including 103 meningiomas from a prospective clinical trial. The gene expression biomarker improved discrimination of outcomes compared with all other systems tested (N = 9) in the clinical validation cohort for local recurrence (5-year area under the curve (AUC) 0.81) and overall survival (5-year AUC 0.80). The increase in AUC compared with the standard of care, World Health Organization 2021 grade, was 0.11 for local recurrence (95% confidence interval 0.07 to 0.17, P

Published
2023

5. Prediction of Rapid Early Progression and Survival Risk with Pre-Radiation MRI in WHO Grade 4 Glioma Patients

Author

Farzana, Walia, Basree, Mustafa M, Diawara, Norou, Shboul, Zeina A., Dubey, Sagel, Lockhart, Marie M, Hamza, Mohamed, Palmer, Joshua D., and Iftekharuddin, Khan M.

Subjects
Computer Science - Machine Learning
Abstract

Recent clinical research describes a subset of glioblastoma patients that exhibit REP prior to start of radiation therapy. Current literature has thus far described this population using clinicopathologic features. To our knowledge, this study is the first to investigate the potential of conventional ra-diomics, sophisticated multi-resolution fractal texture features, and different molecular features (MGMT, IDH mutations) as a diagnostic and prognostic tool for prediction of REP from non-REP cases using computational and statistical modeling methods. Radiation-planning T1 post-contrast (T1C) MRI sequences of 70 patients are analyzed. Ensemble method with 5-fold cross validation over 1000 iterations offers AUC of 0.793 with standard deviation of 0.082 for REP and non-REP classification. In addition, copula-based modeling under dependent censoring (where a subset of the patients may not be followed up until death) identifies significant features (p-value <0.05) for survival probability and prognostic grouping of patient cases. The prediction of survival for the patients cohort produces precision of 0.881 with standard deviation of 0.056. The prognostic index (PI) calculated using the fused features suggests that 84.62% of REP cases fall under the bad prognostic group, suggesting potentiality of fused features to predict a higher percentage of REP cases. The experimental result further shows that mul-ti-resolution fractal texture features perform better than conventional radiomics features for REP and survival outcomes.

Published
2023

6. The Brain Tumor Segmentation (BraTS) Challenge: Local Synthesis of Healthy Brain Tissue via Inpainting

Author

Kofler, Florian, Meissen, Felix, Steinbauer, Felix, Graf, Robert, Ehrlich, Stefan K, Reinke, Annika, Oswald, Eva, Waldmannstetter, Diana, Hoelzl, Florian, Horvath, Izabela, Turgut, Oezguen, Shit, Suprosanna, Bukas, Christina, Yang, Kaiyuan, Paetzold, Johannes C., de da Rosa, Ezequiel, Mekki, Isra, Vinayahalingam, Shankeeth, Kassem, Hasan, Zhang, Juexin, Chen, Ke, Weng, Ying, Durrer, Alicia, Cattin, Philippe C., Wolleb, Julia, Sadique, M. S., Rahman, M. M., Farzana, W., Temtam, A., Iftekharuddin, K. M., Adewole, Maruf, Anwar, Syed Muhammad, Baid, Ujjwal, Janas, Anastasia, Kazerooni, Anahita Fathi, LaBella, Dominic, Li, Hongwei Bran, Moawad, Ahmed W, Conte, Gian-Marco, Farahani, Keyvan, Eddy, James, Sheller, Micah, Pati, Sarthak, Karagyris, Alexandros, Aristizabal, Alejandro, Bergquist, Timothy, Chung, Verena, Shinohara, Russell Takeshi, Dako, Farouk, Wiggins, Walter, Reitman, Zachary, Wang, Chunhao, Liu, Xinyang, Jiang, Zhifan, Johanson, Elaine, Meier, Zeke, Familiar, Ariana, Davatzikos, Christos, Freymann, John, Kirby, Justin, Bilello, Michel, Fathallah-Shaykh, Hassan M, Wiest, Roland, Kirschke, Jan, Colen, Rivka R, Kotrotsou, Aikaterini, Lamontagne, Pamela, Marcus, Daniel, Milchenko, Mikhail, Nazeri, Arash, Weber, Marc-André, Mahajan, Abhishek, Mohan, Suyash, Mongan, John, Hess, Christopher, Cha, Soonmee, Villanueva-Meyer, Javier, Colak, Errol, Crivellaro, Priscila, Jakab, Andras, Fatade, Abiodun, Omidiji, Olubukola, Lagos, Rachel Akinola, Olatunji, O O, Khanna, Goldey, Kirkpatrick, John, Alonso-Basanta, Michelle, Rashid, Arif, Bornhorst, Miriam, Nabavizadeh, Ali, Lepore, Natasha, Palmer, Joshua, Porras, Antonio, Albrecht, Jake, Anazodo, Udunna, Aboian, Mariam, Calabrese, Evan, Rudie, Jeffrey David, Linguraru, Marius George, Iglesias, Juan Eugenio, Van Leemput, Koen, Bakas, Spyridon, Wiestler, Benedikt, Ezhov, Ivan, Piraud, Marie, and Menze, Bjoern H

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning
Abstract

A myriad of algorithms for the automatic analysis of brain MR images is available to support clinicians in their decision-making. For brain tumor patients, the image acquisition time series typically starts with an already pathological scan. This poses problems, as many algorithms are designed to analyze healthy brains and provide no guarantee for images featuring lesions. Examples include, but are not limited to, algorithms for brain anatomy parcellation, tissue segmentation, and brain extraction. To solve this dilemma, we introduce the BraTS inpainting challenge. Here, the participants explore inpainting techniques to synthesize healthy brain scans from lesioned ones. The following manuscript contains the task formulation, dataset, and submission procedure. Later, it will be updated to summarize the findings of the challenge. The challenge is organized as part of the ASNR-BraTS MICCAI challenge., Comment: 14 pages, 6 figures

Published
2023

7. Association of partial T2-FLAIR mismatch sign and isocitrate dehydrogenase mutation in WHO grade 4 gliomas: results from the ReSPOND consortium.

Author

Lee, Matthew, Patel, Sohil, Mohan, Suyash, Akbari, Hamed, Bakas, Spyridon, Nasrallah, MacLean, Calabrese, Evan, Rudie, Jeffrey, LaMontagne, Pamela, Marcus, Daniel, Colen, Rivka, Balana, Carmen, Choi, Yoon, Badve, Chaitra, Barnholtz-Sloan, Jill, Sloan, Andrew, Booth, Thomas, Palmer, Joshua, Dicker, Adam, Flanders, Adam, Shi, Wenyin, Griffith, Brent, Poisson, Laila, Chakravarti, Arnab, Mahajan, Abhishek, Chang, Susan, Orringer, Daniel, Davatzikos, Christos, Jain, Rajan, and Villanueva-Meyer, Javier

Subjects
Astrocytoma, Glioblastoma, Isocitrate dehydrogenase, Magnetic resonance imaging, T2-FLAIR mismatch, Adult, Humans, Isocitrate Dehydrogenase, Brain Neoplasms, Retrospective Studies, Glioma, Magnetic Resonance Imaging, Mutation, World Health Organization
Abstract

PURPOSE: While the T2-FLAIR mismatch sign is highly specific for isocitrate dehydrogenase (IDH)-mutant, 1p/19q-noncodeleted astrocytomas among lower-grade gliomas, its utility in WHO grade 4 gliomas is not well-studied. We derived the partial T2-FLAIR mismatch sign as an imaging biomarker for IDH mutation in WHO grade 4 gliomas. METHODS: Preoperative MRI scans of adult WHO grade 4 glioma patients (n = 2165) from the multi-institutional ReSPOND (Radiomics Signatures for PrecisiON Diagnostics) consortium were analyzed. Diagnostic performance of the partial T2-FLAIR mismatch sign was evaluated. Subset analyses were performed to assess associations of imaging markers with overall survival (OS). RESULTS: One hundred twenty-one (5.6%) of 2165 grade 4 gliomas were IDH-mutant. Partial T2-FLAIR mismatch was present in 40 (1.8%) cases, 32 of which were IDH-mutant, yielding 26.4% sensitivity, 99.6% specificity, 80.0% positive predictive value, and 95.8% negative predictive value. Multivariate logistic regression demonstrated IDH mutation was significantly associated with partial T2-FLAIR mismatch (odds ratio [OR] 5.715, 95% CI [1.896, 17.221], p = 0.002), younger age (OR 0.911 [0.895, 0.927], p

Published
2023

8. Comparison of first-line radiosurgery for small-cell and non-small cell lung cancer brain metastases (CROSS-FIRE).

Author

Rusthoven, Chad, Staley, Alyse, Gao, Dexiang, Yomo, Shoji, Bernhardt, Denise, Wandrey, Narine, El Shafie, Rami, Kraemer, Anna, Padilla, Oscar, Chiang, Veronica, Faramand, Andrew, Palmer, Joshua, Zacharia, Brad, Wegner, Rodney, Hattangadi-Gluth, Jona, Levy, Antonin, Bernstein, Kenneth, Mathieu, David, Cagney, Daniel, Chan, Michael, Grills, Inga, Lee, Cheng-Chia, Sheehan, Jason, Kluwe, Christien, Patel, Samir, Halasz, Lia, Andratschke, Nicolaus, Deibert, Christopher, Verma, Vivek, Trifiletti, Daniel, Cifarelli, Christopher, Debus, Jürgen, Combs, Stephanie, Sato, Yasunori, Higuchi, Yoshinori, Aoyagi, Kyoko, Brown, Paul, Alami, Vida, Niranjan, Ajay, Lunsford, L, Kondziolka, Douglas, Camidge, D, Kavanagh, Brian, Robin, Tyler, Serizawa, Toru, Yamamoto, Masaaki, and Braunstein, Steve

Subjects
Humans, Carcinoma, Non-Small-Cell Lung, Lung Neoplasms, Retrospective Studies, Radiosurgery, Prospective Studies, Small Cell Lung Carcinoma, ErbB Receptors, Brain Neoplasms
Abstract

INTRODUCTION: Historical reservations regarding stereotactic radiosurgery (SRS) for small-cell lung cancer (SCLC) brain metastases include concerns for short-interval and diffuse central nervous system (CNS) progression, poor prognoses, and increased neurological mortality specific to SCLC histology. We compared SRS outcomes for SCLC and non-small cell lung cancer (NSCLC) where SRS is well established. METHODS: Multicenter first-line SRS outcomes for SCLC and NSCLC from 2000 to 2022 were retrospectively collected (n = 892 SCLC, n = 4785 NSCLC). Data from the prospective Japanese Leksell Gamma Knife Society (JLGK0901) clinical trial of first-line SRS were analyzed as a comparison cohort (n = 98 SCLC, n = 814 NSCLC). Overall survival (OS) and CNS progression were analyzed using Cox proportional hazard and Fine-Gray models, respectively, with multivariable adjustment for cofactors including age, sex, performance status, year, extracranial disease status, and brain metastasis number and volume. Mutation-stratified analyses were performed in propensity score-matched retrospective cohorts of epidermal growth factor receptor (EGFR) and anaplastic lymphoma kinase (ALK) positive NSCLC, mutation-negative NSCLC, and SCLC. RESULTS: OS was superior for patients with NSCLC compared to SCLC in the retrospective dataset (median OS = 10.5 vs 8.6 months; P

Published
2023

11. Feasibility of the Audio-Visual Assisted Therapeutic Ambience in Radiotherapy (AVATAR) System for Anesthesia Avoidance in Pediatric Patients: A Multicenter Trial.

Author

Gutkin, Paulina M, Skinner, Lawrie, Jiang, Alice, Donaldson, Sarah S, Loo, Billy W, Oh, Justin, Wang, Yi Peng, von Eyben, Rie, Snyder, John, Bredfeldt, Jeremy S, Breneman, John C, Constine, Louis S, Faught, Austin M, Haas-Kogan, Daphne, Holmes, Jordan A, Krasin, Matthew, Larkin, Charlene, Marcus, Karen J, Maxim, Peter G, McClelland, Shearwood, Murphy, Blair, Palmer, Joshua D, Perkins, Stephanie M, Shen, Colette J, Terezakis, Stephanie, Bush, Karl, and Hiniker, Susan M

Subjects
Pediatric, Clinical Research, Clinical Trials and Supportive Activities, Management of diseases and conditions, 7.1 Individual care needs, Other Physical Sciences, Clinical Sciences, Oncology and Carcinogenesis, Oncology & Carcinogenesis
Abstract

PurposeThe Audio-Visual Assisted Therapeutic Ambience in Radiotherapy (AVATAR) system was the first published radiation therapy (RT)-compatible system to reduce the need for pediatric anesthesia through video-based distraction. We evaluated the feasibility of AVATAR implementation and effects on anesthesia use, quality of life, and anxiety in a multicenter pediatric trial.Methods and materialsPediatric patients 3 to 10 years of age preparing to undergo RT at 10 institutions were prospectively enrolled. Children able to undergo at least 1 fraction of RT using AVATAR without anesthesia were considered successful (S). Patients requiring anesthesia for their entire treatment course were nonsuccessful (NS). The PedsQL3.0 Cancer Module (PedsQL) survey assessed quality of life and was administered to the patient and guardian at RT simulation, midway through RT, and at final treatment. The modified Yale Preoperative Anxiety Scale (mYPAS) assessed anxiety and was performed at the same 3 time points. Success was evaluated using the χ2 test. PedsQL and mYPAS scores were assessed using mixed effects models with time points evaluated as fixed effects and a random intercept on the subject.ResultsEighty-one children were included; median age was 7 years. AVATAR was successful at all 10 institutions and with photon and proton RT. There were 63 (78%) S patients; anesthesia was avoided for a median of 20 fractions per patient. Success differed by age (P = .04) and private versus public insurance (P < .001). Both patient (P = .008) and parent (P = .006) PedsQL scores significantly improved over the course of RT for patients aged 5 to 7. Anxiety in the treatment room decreased for both S and NS patients over RT course (P < .001), by age (P < .001), and by S versus NS patients (P < .001).ConclusionsIn this 10-center prospective trial, anesthesia avoidance with AVATAR was 78% in children aged 3 to 10 years, higher than among age-matched historical controls (49%; P < .001). AVATAR implementation is feasible across multiple institutions and should be further studied and made available to patients who may benefit from video-based distraction.

Published
2023

12. Efficacy and Safety of Stereotactic Body Radiation Therapy for Pediatric Malignancies: The LITE-SABR Systematic Review and Meta-Analysis.

Author

Singh, Raj, Valluri, Anisha, Didwania, Prabhanjan, Lehrer, Eric, Baliga, Sujith, Hiniker, Susan, Braunstein, Steve, Murphy, Erin, Lazarev, Stanislav, Tinkle, Christopher, Terezakis, Stephanie, and Palmer, Joshua

Abstract

PURPOSE: Limited data are currently available on clinical outcomes after stereotactic body radiation therapy (SBRT) for pediatric and adolescent and young adult (AYA) patients with cancer. We aimed to perform a systematic review and study-level meta-analysis to characterize associated local control (LC), progression-free survival (PFS), overall survival, and toxicity after SBRT. METHODS AND MATERIALS: Relevant studies were queried using a Population, Intervention, Control, Outcomes, Study Design (PICOS)/Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA)/Meta-analysis of Observational Studies in Epidemiology (MOOSE) selection criteria. Primary outcomes were 1-year and 2-year LC as well as incidence of acute and late grade 3 to 5 toxicities, with secondary outcomes of 1-year overall survival and 1-year PFS. Outcome effect sizes were estimated with weighted random effects meta-analyses. Mixed-effects weighted regression models were performed to examine potential correlations between biologically effective dose (BED10), LC, and toxicity incidence. RESULTS: Across 9 published studies, we identified 142 pediatric and AYA patients with 217 lesions that were treated with SBRT. Estimated 1-year and 2-year LC rates were 83.5% (95% confidence interval, 70.9%-96.2%) and 74.0% (95% CI, 64.6%-83.4%), respectively, with an estimated acute and late grade 3 to 5 toxicity rate of 2.9% (95% CI, 0.4%-5.4%; all grade 3). The estimated 1-year OS and PFS rates were 75.4% (95% CI, 54.5%-96.3%) and 27.1% (95% CI, 17.3%-37.0%), respectively. On meta-regression, higher BED10 was correlated with improved 2-year LC with every 10 Gy10 increase in BED10 associated with a 5% improvement in 2-year LC (P = .02) in sarcoma-predominant cohorts. CONCLUSIONS: SBRT provided durable LC for pediatric and AYA patients with cancer with minimal severe toxicities. Dose escalation may result in improved LC for sarcoma-predominant cohorts without a subsequent increase in toxicity. However, further investigations with patient-level data and prospective inquiries are indicated to better define the role of SBRT based on patient and tumor-specific characteristics.

Published
2023

13. Radiotherapy for meningiomas

Author

Chen, William C, Perlow, Haley K, Choudhury, Abrar, Nguyen, Minh P, Mirchia, Kanish, Youngblood, Mark W, Lucas, Calixto-Hope G, Palmer, Joshua D, Magill, Stephen T, and Raleigh, David R

Subjects
Rare Diseases, Neurosciences, Genetics, Brain Cancer, Brain Disorders, Human Genome, Cancer, Evaluation of treatments and therapeutic interventions, 6.5 Radiotherapy and other non-invasive therapies, Humans, Meningioma, Meningeal Neoplasms, Radiotherapy, Adjuvant, Radiation, Radiotherapy, Atypical, Anaplastic, Molecular, DOTATATE, Oncology and Carcinogenesis, Oncology & Carcinogenesis
Abstract

Meningiomas are the most common primary central nervous system neoplasm. Despite promising recent progress in elucidating the genomic landscape and underlying biology of these histologically, molecularly, and clinically diverse tumors, the mainstays of meningioma treatment remain maximal safe resection and radiation therapy. The aim of this review of meningioma radiotherapy is to provide a concise summary of the history, current evidence, and future for application of radiotherapy in meningioma treatment.

Published
2022

14. Federated Learning Enables Big Data for Rare Cancer Boundary Detection

Author

Pati, Sarthak, Baid, Ujjwal, Edwards, Brandon, Sheller, Micah, Wang, Shih-Han, Reina, G Anthony, Foley, Patrick, Gruzdev, Alexey, Karkada, Deepthi, Davatzikos, Christos, Sako, Chiharu, Ghodasara, Satyam, Bilello, Michel, Mohan, Suyash, Vollmuth, Philipp, Brugnara, Gianluca, Preetha, Chandrakanth J, Sahm, Felix, Maier-Hein, Klaus, Zenk, Maximilian, Bendszus, Martin, Wick, Wolfgang, Calabrese, Evan, Rudie, Jeffrey, Villanueva-Meyer, Javier, Cha, Soonmee, Ingalhalikar, Madhura, Jadhav, Manali, Pandey, Umang, Saini, Jitender, Garrett, John, Larson, Matthew, Jeraj, Robert, Currie, Stuart, Frood, Russell, Fatania, Kavi, Huang, Raymond Y, Chang, Ken, Balana, Carmen, Capellades, Jaume, Puig, Josep, Trenkler, Johannes, Pichler, Josef, Necker, Georg, Haunschmidt, Andreas, Meckel, Stephan, Shukla, Gaurav, Liem, Spencer, Alexander, Gregory S, Lombardo, Joseph, Palmer, Joshua D, Flanders, Adam E, Dicker, Adam P, Sair, Haris I, Jones, Craig K, Venkataraman, Archana, Jiang, Meirui, So, Tiffany Y, Chen, Cheng, Heng, Pheng Ann, Dou, Qi, Kozubek, Michal, Lux, Filip, Michálek, Jan, Matula, Petr, Keřkovský, Miloš, Kopřivová, Tereza, Dostál, Marek, Vybíhal, Václav, Vogelbaum, Michael A, Mitchell, J Ross, Farinhas, Joaquim, Maldjian, Joseph A, Yogananda, Chandan Ganesh Bangalore, Pinho, Marco C, Reddy, Divya, Holcomb, James, Wagner, Benjamin C, Ellingson, Benjamin M, Cloughesy, Timothy F, Raymond, Catalina, Oughourlian, Talia, Hagiwara, Akifumi, Wang, Chencai, To, Minh-Son, Bhardwaj, Sargam, Chong, Chee, Agzarian, Marc, Falcão, Alexandre Xavier, Martins, Samuel B, Teixeira, Bernardo C A, Sprenger, Flávia, Menotti, David, Lucio, Diego R, LaMontagne, Pamela, Marcus, Daniel, Wiestler, Benedikt, Kofler, Florian, Ezhov, Ivan, Metz, Marie, Jain, Rajan, Lee, Matthew, Lui, Yvonne W, McKinley, Richard, Slotboom, Johannes, Radojewski, Piotr, Meier, Raphael, Wiest, Roland, Murcia, Derrick, Fu, Eric, Haas, Rourke, Thompson, John, Ormond, David Ryan, Badve, Chaitra, Sloan, Andrew E, Vadmal, Vachan, Waite, Kristin, Colen, Rivka R, Pei, Linmin, Ak, Murat, Srinivasan, Ashok, Bapuraj, J Rajiv, Rao, Arvind, Wang, Nicholas, Yoshiaki, Ota, Moritani, Toshio, Turk, Sevcan, Lee, Joonsang, Prabhudesai, Snehal, Morón, Fanny, Mandel, Jacob, Kamnitsas, Konstantinos, Glocker, Ben, Dixon, Luke V M, Williams, Matthew, Zampakis, Peter, Panagiotopoulos, Vasileios, Tsiganos, Panagiotis, Alexiou, Sotiris, Haliassos, Ilias, Zacharaki, Evangelia I, Moustakas, Konstantinos, Kalogeropoulou, Christina, Kardamakis, Dimitrios M, Choi, Yoon Seong, Lee, Seung-Koo, Chang, Jong Hee, Ahn, Sung Soo, Luo, Bing, Poisson, Laila, Wen, Ning, Tiwari, Pallavi, Verma, Ruchika, Bareja, Rohan, Yadav, Ipsa, Chen, Jonathan, Kumar, Neeraj, Smits, Marion, van der Voort, Sebastian R, Alafandi, Ahmed, Incekara, Fatih, Wijnenga, Maarten MJ, Kapsas, Georgios, Gahrmann, Renske, Schouten, Joost W, Dubbink, Hendrikus J, Vincent, Arnaud JPE, Bent, Martin J van den, French, Pim J, Klein, Stefan, Yuan, Yading, Sharma, Sonam, Tseng, Tzu-Chi, Adabi, Saba, Niclou, Simone P, Keunen, Olivier, Hau, Ann-Christin, Vallières, Martin, Fortin, David, Lepage, Martin, Landman, Bennett, Ramadass, Karthik, Xu, Kaiwen, Chotai, Silky, Chambless, Lola B, Mistry, Akshitkumar, Thompson, Reid C, Gusev, Yuriy, Bhuvaneshwar, Krithika, Sayah, Anousheh, Bencheqroun, Camelia, Belouali, Anas, Madhavan, Subha, Booth, Thomas C, Chelliah, Alysha, Modat, Marc, Shuaib, Haris, Dragos, Carmen, Abayazeed, Aly, Kolodziej, Kenneth, Hill, Michael, Abbassy, Ahmed, Gamal, Shady, Mekhaimar, Mahmoud, Qayati, Mohamed, Reyes, Mauricio, Park, Ji Eun, Yun, Jihye, Kim, Ho Sung, Mahajan, Abhishek, Muzi, Mark, Benson, Sean, Beets-Tan, Regina G H, Teuwen, Jonas, Herrera-Trujillo, Alejandro, Trujillo, Maria, Escobar, William, Abello, Ana, Bernal, Jose, Gómez, Jhon, Choi, Joseph, Baek, Stephen, Kim, Yusung, Ismael, Heba, Allen, Bryan, Buatti, John M, Kotrotsou, Aikaterini, Li, Hongwei, Weiss, Tobias, Weller, Michael, Bink, Andrea, Pouymayou, Bertrand, Shaykh, Hassan F, Saltz, Joel, Prasanna, Prateek, Shrestha, Sampurna, Mani, Kartik M, Payne, David, Kurc, Tahsin, Pelaez, Enrique, Franco-Maldonado, Heydy, Loayza, Francis, Quevedo, Sebastian, Guevara, Pamela, Torche, Esteban, Mendoza, Cristobal, Vera, Franco, Ríos, Elvis, López, Eduardo, Velastin, Sergio A, Ogbole, Godwin, Oyekunle, Dotun, Odafe-Oyibotha, Olubunmi, Osobu, Babatunde, Shu'aibu, Mustapha, Dorcas, Adeleye, Soneye, Mayowa, Dako, Farouk, Simpson, Amber L, Hamghalam, Mohammad, Peoples, Jacob J, Hu, Ricky, Tran, Anh, Cutler, Danielle, Moraes, Fabio Y, Boss, Michael A, Gimpel, James, Veettil, Deepak Kattil, Schmidt, Kendall, Bialecki, Brian, Marella, Sailaja, Price, Cynthia, Cimino, Lisa, Apgar, Charles, Shah, Prashant, Menze, Bjoern, Barnholtz-Sloan, Jill S, Martin, Jason, and Bakas, Spyridon

Subjects
Computer Science - Machine Learning, Electrical Engineering and Systems Science - Image and Video Processing
Abstract

Although machine learning (ML) has shown promise in numerous domains, there are concerns about generalizability to out-of-sample data. This is currently addressed by centrally sharing ample, and importantly diverse, data from multiple sites. However, such centralization is challenging to scale (or even not feasible) due to various limitations. Federated ML (FL) provides an alternative to train accurate and generalizable ML models, by only sharing numerical model updates. Here we present findings from the largest FL study to-date, involving data from 71 healthcare institutions across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, utilizing the largest dataset of such patients ever used in the literature (25,256 MRI scans from 6,314 patients). We demonstrate a 33% improvement over a publicly trained model to delineate the surgically targetable tumor, and 23% improvement over the tumor's entire extent. We anticipate our study to: 1) enable more studies in healthcare informed by large and diverse data, ensuring meaningful results for rare diseases and underrepresented populations, 2) facilitate further quantitative analyses for glioblastoma via performance optimization of our consensus model for eventual public release, and 3) demonstrate the effectiveness of FL at such scale and task complexity as a paradigm shift for multi-site collaborations, alleviating the need for data sharing., Comment: federated learning, deep learning, convolutional neural network, segmentation, brain tumor, glioma, glioblastoma, FeTS, BraTS

Published
2022
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15. Immune checkpoint inhibition and single fraction stereotactic radiosurgery in brain metastases from non-small cell lung cancer: an international multicenter study of 395 patients

Author

Lehrer, Eric J., Khosla, Atulya A., Ozair, Ahmad, Gurewitz, Jason, Bernstein, Kenneth, Kondziolka, Douglas, Niranjan, Ajay, Wei, Zhishuo, Lunsford, L. Dade, Mathieu, David, Trudel, Claire, Deibert, Christopher P., Malouff, Timothy D., Ruiz-Garcia, Henry, Peterson, Jennifer L., Patel, Samir, Bonney, Phillip, Hwang, Lindsay, Yu, Cheng, Zada, Gabriel, Picozzi, Piero, Franzini, Andrea, Attuati, Luca, Prasad, Rahul N., Raval, Raju R., Palmer, Joshua D., Lee, Cheng-chia, Yang, Huai-che, Fakhoury, Kareem R., Rusthoven, Chad G., Dickstein, Daniel R., Sheehan, Jason P., Trifiletti, Daniel M., and Ahluwalia, Manmeet S.

Published
2023
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17. Salvage Stereotactic Radiosurgery for Recurrent WHO Grade 2 and 3 Meningiomas: A Multicenter Study (STORM)

Author

Gallitto, Matthew, Sedor, Geoffrey, Lee, Albert, Pasetsky, Jared, Kinslow, Connor J., Santos, Genesis De Los, Obiri-Yeboah, Derrick, Kshettry, Varun R., Helis, Corbin A., Chan, Michael D., Beckham, Thomas H., McGovern, Susan L., Matsui, Jennifer, Palmer, Joshua D., Bell, Jonathan B., Mellon, Eric A., Lakomy, David, Huang, Jiayi, Boor, Ian, Rusthoven, Chad G., Sisti, Michael B., and Wang, Tony J.C.

Published
2024
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23. Author Correction: Federated learning enables big data for rare cancer boundary detection

Author

Pati, Sarthak, Baid, Ujjwal, Edwards, Brandon, Sheller, Micah, Wang, Shih-Han, Reina, G. Anthony, Foley, Patrick, Gruzdev, Alexey, Karkada, Deepthi, Davatzikos, Christos, Sako, Chiharu, Ghodasara, Satyam, Bilello, Michel, Mohan, Suyash, Vollmuth, Philipp, Brugnara, Gianluca, Preetha, Chandrakanth J., Sahm, Felix, Maier-Hein, Klaus, Zenk, Maximilian, Bendszus, Martin, Wick, Wolfgang, Calabrese, Evan, Rudie, Jeffrey, Villanueva-Meyer, Javier, Cha, Soonmee, Ingalhalikar, Madhura, Jadhav, Manali, Pandey, Umang, Saini, Jitender, Garrett, John, Larson, Matthew, Jeraj, Robert, Currie, Stuart, Frood, Russell, Fatania, Kavi, Huang, Raymond Y., Chang, Ken, Balaña, Carmen, Capellades, Jaume, Puig, Josep, Trenkler, Johannes, Pichler, Josef, Necker, Georg, Haunschmidt, Andreas, Meckel, Stephan, Shukla, Gaurav, Liem, Spencer, Alexander, Gregory S., Lombardo, Joseph, Palmer, Joshua D., Flanders, Adam E., Dicker, Adam P., Sair, Haris I., Jones, Craig K., Venkataraman, Archana, Jiang, Meirui, So, Tiffany Y., Chen, Cheng, Heng, Pheng Ann, Dou, Qi, Kozubek, Michal, Lux, Filip, Michálek, Jan, Matula, Petr, Keřkovský, Miloš, Kopřivová, Tereza, Dostál, Marek, Vybíhal, Václav, Vogelbaum, Michael A., Mitchell, J. Ross, Farinhas, Joaquim, Maldjian, Joseph A., Yogananda, Chandan Ganesh Bangalore, Pinho, Marco C., Reddy, Divya, Holcomb, James, Wagner, Benjamin C., Ellingson, Benjamin M., Cloughesy, Timothy F., Raymond, Catalina, Oughourlian, Talia, Hagiwara, Akifumi, Wang, Chencai, To, Minh-Son, Bhardwaj, Sargam, Chong, Chee, Agzarian, Marc, Falcão, Alexandre Xavier, Martins, Samuel B., Teixeira, Bernardo C. A., Sprenger, Flávia, Menotti, David, Lucio, Diego R., LaMontagne, Pamela, Marcus, Daniel, Wiestler, Benedikt, Kofler, Florian, Ezhov, Ivan, Metz, Marie, Jain, Rajan, Lee, Matthew, Lui, Yvonne W., McKinley, Richard, Slotboom, Johannes, Radojewski, Piotr, Meier, Raphael, Wiest, Roland, Murcia, Derrick, Fu, Eric, Haas, Rourke, Thompson, John, Ormond, David Ryan, Badve, Chaitra, Sloan, Andrew E., Vadmal, Vachan, Waite, Kristin, Colen, Rivka R., Pei, Linmin, Ak, Murat, Srinivasan, Ashok, Bapuraj, J. Rajiv, Rao, Arvind, Wang, Nicholas, Yoshiaki, Ota, Moritani, Toshio, Turk, Sevcan, Lee, Joonsang, Prabhudesai, Snehal, Morón, Fanny, Mandel, Jacob, Kamnitsas, Konstantinos, Glocker, Ben, Dixon, Luke V. M., Williams, Matthew, Zampakis, Peter, Panagiotopoulos, Vasileios, Tsiganos, Panagiotis, Alexiou, Sotiris, Haliassos, Ilias, Zacharaki, Evangelia I., Moustakas, Konstantinos, Kalogeropoulou, Christina, Kardamakis, Dimitrios M., Choi, Yoon Seong, Lee, Seung-Koo, Chang, Jong Hee, Ahn, Sung Soo, Luo, Bing, Poisson, Laila, Wen, Ning, Tiwari, Pallavi, Verma, Ruchika, Bareja, Rohan, Yadav, Ipsa, Chen, Jonathan, Kumar, Neeraj, Smits, Marion, van der Voort, Sebastian R., Alafandi, Ahmed, Incekara, Fatih, Wijnenga, Maarten M. J., Kapsas, Georgios, Gahrmann, Renske, Schouten, Joost W., Dubbink, Hendrikus J., Vincent, Arnaud J. P. E., van den Bent, Martin J., French, Pim J., Klein, Stefan, Yuan, Yading, Sharma, Sonam, Tseng, Tzu-Chi, Adabi, Saba, Niclou, Simone P., Keunen, Olivier, Hau, Ann-Christin, Vallières, Martin, Fortin, David, Lepage, Martin, Landman, Bennett, Ramadass, Karthik, Xu, Kaiwen, Chotai, Silky, Chambless, Lola B., Mistry, Akshitkumar, Thompson, Reid C., Gusev, Yuriy, Bhuvaneshwar, Krithika, Sayah, Anousheh, Bencheqroun, Camelia, Belouali, Anas, Madhavan, Subha, Booth, Thomas C., Chelliah, Alysha, Modat, Marc, Shuaib, Haris, Dragos, Carmen, Abayazeed, Aly, Kolodziej, Kenneth, Hill, Michael, Abbassy, Ahmed, Gamal, Shady, Mekhaimar, Mahmoud, Qayati, Mohamed, Reyes, Mauricio, Park, Ji Eun, Yun, Jihye, Kim, Ho Sung, Mahajan, Abhishek, Muzi, Mark, Benson, Sean, Beets-Tan, Regina G. H., Teuwen, Jonas, Herrera-Trujillo, Alejandro, Trujillo, Maria, Escobar, William, Abello, Ana, Bernal, Jose, Gómez, Jhon, Choi, Joseph, Baek, Stephen, Kim, Yusung, Ismael, Heba, Allen, Bryan, Buatti, John M., Kotrotsou, Aikaterini, Li, Hongwei, Weiss, Tobias, Weller, Michael, Bink, Andrea, Pouymayou, Bertrand, Shaykh, Hassan F., Saltz, Joel, Prasanna, Prateek, Shrestha, Sampurna, Mani, Kartik M., Payne, David, Kurc, Tahsin, Pelaez, Enrique, Franco-Maldonado, Heydy, Loayza, Francis, Quevedo, Sebastian, Guevara, Pamela, Torche, Esteban, Mendoza, Cristobal, Vera, Franco, Ríos, Elvis, López, Eduardo, Velastin, Sergio A., Ogbole, Godwin, Soneye, Mayowa, Oyekunle, Dotun, Odafe-Oyibotha, Olubunmi, Osobu, Babatunde, Shu’aibu, Mustapha, Dorcas, Adeleye, Dako, Farouk, Simpson, Amber L., Hamghalam, Mohammad, Peoples, Jacob J., Hu, Ricky, Tran, Anh, Cutler, Danielle, Moraes, Fabio Y., Boss, Michael A., Gimpel, James, Veettil, Deepak Kattil, Schmidt, Kendall, Bialecki, Brian, Marella, Sailaja, Price, Cynthia, Cimino, Lisa, Apgar, Charles, Shah, Prashant, Menze, Bjoern, Barnholtz-Sloan, Jill S., Martin, Jason, and Bakas, Spyridon

Published
2023
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26. Concurrent Lapatinib With Brain Radiation Therapy in Patients With HER2+ Breast Cancer With Brain Metastases: NRG Oncology–KROG/RTOG 1119 Phase 2 Randomized Trial

Author

Kim, In Ah, Winter, Kathryn A., Sperduto, Paul W., De Los Santos, Jennifer F., Peereboom, David M., Ogunleye, Tomi, Boulter, Daniel, Fritz, Joel M., Cho, Kwan Ho, Shin, Kyung Hwan, Zoberi, Imran, Choi, Serah, Palmer, Joshua D., Liem, Ben, Kim, Yong Bae, Anderson, Bethany M., Thakrar, Anupama W., Muanza, Thierry M., Kim, Michelle M., Choi, Doo Ho, Mehta, Minesh P., and White, Julia R.

Published
2024
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27. Single-Fraction Versus Fractionated Preoperative Radiosurgery for Resected Brain Metastases: A PROPS-BM International Multicenter Cohort Study

Author

Prabhu, Roshan S., Akinyelu, Tobi, Vaslow, Zachary K., Matsui, Jennifer K., Haghighi, Neda, Dan, Tu, Mishra, Mark V., Murphy, Erin S., Boyles, Susan, Perlow, Haley K., Palmer, Joshua D., Udovicich, Cristian, Patel, Toral R., Wardak, Zabi, Woodworth, Graeme F., Ksendzovsky, Alexander, Yang, Kailin, Chao, Samuel T., Asher, Anthony L., and Burri, Stuart H.

Published
2024
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29. Advancing Beyond the Hippocampus to Preserve Cognition for Patients With Brain Metastases: Dosimetric Results From a Phase 2 Trial of Memory-Avoidance Whole Brain Radiation Therapy

Author

Perlow, Haley K., Nalin, Ansel P., Ritter, Alex R., Addington, Mark, Ward, Aubrie, Liu, Michal, Nappi, Collin, Blakaj, Dukagjin M., Beyer, Sasha J., Thomas, Evan M., Grecula, John C., Raval, Raju R., Kotecha, Rupesh, Boulter, Daniel, Dawson, Erica L., Zoller, Wesley, and Palmer, Joshua D.

Published
2024
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30. Rapid early progression (REP) of glioblastoma is an independent negative prognostic factor: Results from a systematic review and meta-analysis

Author

Waqar, Mueez, Roncaroli, Federico, Lehrer, Eric J, Palmer, Joshua D, Villanueva-Meyer, Javier, Braunstein, Steve, Hall, Emma, Aznar, Marianne, De Witt Hamer, Philip C, D’Urso, Pietro I, Trifiletti, Daniel, Quiñones-Hinojosa, Alfredo, Wesseling, Pieter, and Bors, Gerben R

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Oncology and Carcinogenesis, Brain Disorders, Cancer, Brain Cancer, Rare Diseases, Biomedical Imaging, extent of resection, glioblastoma, IDH, MGMT, prognosis, progression, recurrence, REP, survival
Abstract

BackgroundIn patients with newly diagnosed glioblastoma, rapid early progression (REP) refers to tumor regrowth between surgery and postoperative chemoradiotherapy. This systematic review and meta-analysis appraised previously published data on REP to better characterize and understand it.MethodsSystematic searches of MEDLINE, EMBASE and the Cochrane database from inception to October 21, 2021. Studies describing the incidence of REP-tumor growth between the postoperative MRI scan and pre-radiotherapy MRI scan in newly diagnosed glioblastoma were included. The primary outcome was REP incidence.ResultsFrom 1590 search results, 9 studies were included with 716 patients. The median age was 56.9 years (IQR 54.0-58.8 y). There was a male predominance with a median male-to-female ratio of 1.4 (IQR 1.1-1.5). The median number of days between MRI scans was 34 days (IQR 18-45 days). The mean incidence rate of REP was 45.9% (range 19.3%-72.0%) and significantly lower in studies employing functional imaging to define REP (P

Published
2022

32. Radiosurgery Society Case-Based Guide to Stereotactic Body Radiation Therapy for Challenging Cases of Spinal Metastases

Author

Aziz, Khaled, Koffler, Daniel, Vassantachart, April, Rattani, Abbas, Ankrah, Nii-Kwanchie, Gogineni, Emile, Andraos, Therese Y., Sahgal, Arjun, Vellayappan, Balamurugan, Dunne, Emma M., Siva, Shankar, Moraes, Fabio Y., Guckenberger, Matthias, Lubelski, Daniel, Chao, Samuel, Combs, Stephanie, Chang, Eric, Amin, Anubhav G., Foote, Matthew, Gibbs, Iris, Kim, Minsun, Palmer, Joshua, Lo, Simon, and Redmond, Kristin J.

Published
2024
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33. A Case-based Guide for World Health Organization (WHO) Grade 2 Meningioma Radiosurgery and Radiation Therapy from The Radiosurgery Society

Author

Vassantachart, April K., Ehret, Felix, Chen, Eric, Kumar, Ritesh, Gogineni, Emile, Andraos, Therese Y., Sahgal, Arjun, Redmond, Kristin J., Lo, Simon S., Chang, Eric L., Sheehan, Jason, Chao, Samuel T., Kim, Grace Gwe-Ya, Kresl, John J., Schulder, Michael, Palmer, Joshua D., Gibbs, Iris C., Santacroce, Antonio, and Shih, Helen A.

Published
2024
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35. Learning Spatially Structured Image Transformations Using Planar Neural Networks

Author

Michelson, Joel, Palmer, Joshua H., Dasari, Aneesha, and Kunda, Maithilee

Subjects
Computer Science - Machine Learning, Computer Science - Computer Vision and Pattern Recognition, Statistics - Machine Learning
Abstract

Learning image transformations is essential to the idea of mental simulation as a method of cognitive inference. We take a connectionist modeling approach, using planar neural networks to learn fundamental imagery transformations, like translation, rotation, and scaling, from perceptual experiences in the form of image sequences. We investigate how variations in network topology, training data, and image shape, among other factors, affect the efficiency and effectiveness of learning visual imagery transformations, including effectiveness of transfer to operating on new types of data.

Published
2019

36. The Pediatric Proton and Photon Therapy Comparison Cohort: Study Design for a Multicenter Retrospective Cohort to Investigate Subsequent Cancers After Pediatric Radiation Therapy

Author

Berrington de González, Amy, Gibson, Todd M., Lee, Choonsik, Albert, Paul S., Griffin, Keith T., Kitahara, Cari Meinhold, Liu, Danping, Mille, Matthew M., Shin, Jungwook, Bajaj, Benjamin V.M., Flood, Tristin E., Gallotto, Sara L., Paganetti, Harald, Ahmed, Safia K., Eaton, Bree R., Indelicato, Daniel J., Milgrom, Sarah A., Palmer, Joshua D., Baliga, Sujith, Poppe, Matthew M., Tsang, Derek S., Wong, Kenneth, and Yock, Torunn I.

Published
2023
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40. Modeling Visuospatial Reasoning Across 17 Different Tests on the Leiter Scale of Nonverbal Intelligence

Author

Ainooson, James, Michelson, Joel, Sanyal, Deepayan, Palmer, Joshua Palmer, and Kunda, Maithilee

Abstract

Understanding the computational mechanisms enabling visuospatial reasoning is important for studying human intelli-gence as well as for exploring the possibility of introducing human-like reasoning into artificial intelligence systems. Inour work, we investigate how a collection of primitive image processing operations can be combined into different co-herent strategies for solving a range of visuospatial reasoning tasks. We evaluate our approach on 20 subtests from theLeiter International Performance Scale-Revised (Leiter-R). Through our computational experiments, we show that withonly four primitive operations similarity, containment, rotation, and scaling we can form strategies that solve, to differentdegrees of success, at least portions of 17 of the 20 subtests. These results lay foundations for our future work to study howintelligent agents can learn and generalize strategies from simple task definitions in order to perform complex visuospatialreasoning tasks.

Published
2020

42. Fractionated pre-operative stereotactic radiotherapy for patients with brain metastases: a multi-institutional analysis

Author

Palmer, Joshua D., Perlow, Haley K., Matsui, Jennifer K., Ho, Cindy, Prasad, Rahul N., Liu, Kevin, Upadhyay, Rituraj, Klamer, Brett, Wang, Joshua, Damante, Mark, Ghose, Jayeeta, Blakaj, Dukagjin M., Beyer, Sasha, Grecula, John, Arnett, Andrea, Thomas, Evan, Chakravarti, Arnab, Lonser, Russell, Hardesty, Douglas, Prevedello, Daniel, Prabhu, Roshan, Elder, James B., and Raval, Raju R.

Published
2022
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43. Outcome Evaluation of Repeat Stereotactic Radiosurgery for Cerebral Arteriovenous Malformations

Author

Mantziaris, Georgios, Pikis, Stylianos, Dumot, Chloe, Dayawansa, Samantha, Liščák, Roman, May, Jaromir, Lee, Cheng-chia, Yang, Huai-che, Martinez Moreno, Nuria, Martinez Álvarez, Roberto, Lunsford, L. Dade, Niranjan, Ajay, Wei, Zhishuo, Srinivasan, Priyanka, Tang, Lilly W., Nabeel, Ahmed M., Reda, Wael A., Tawadros, Sameh R., Abdelkarim, Khaled, El-Shehaby, Amr M.N., Emad, Reem M., Hesham Elazzazi, Ahmed, Peker, Selcuk, Samanci, Yavuz, Padmanaban, Varun, Jareczek, Francis J., McInerney, James, Cockroft, Kevin M., Mathieu, David, Aldakhil, Salman, Alzate, Juan Diego, Kondziolka, Douglas, Tripathi, Manjul, Palmer, Joshua D., Upadhyay, Rituraj, Lin, Michelle, Zada, Gabriel, Yu, Cheng, Cifarelli, Christopher P., Cifarelli, Daniel T., Xu, Zhiyuan, and Sheehan, Jason P.

Published
2023
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46. Concurrent Administration of Immune Checkpoint Inhibitors and Single Fraction Stereotactic Radiosurgery in Patients With Non-Small Cell Lung Cancer, Melanoma, and Renal Cell Carcinoma Brain Metastases is Not Associated With an Increased Risk of Radiation Necrosis Over Nonconcurrent Treatment: An International Multicenter Study of 657 Patients

Author

Lehrer, Eric J., Kowalchuk, Roman O., Gurewitz, Jason, Bernstein, Kenneth, Kondziolka, Douglas, Niranjan, Ajay, Wei, Zhishuo, Lunsford, L. Dade, Fakhoury, Kareem R., Rusthoven, Chad G., Mathieu, David, Trudel, Claire, Malouff, Timothy D., Ruiz-Garcia, Henry, Bonney, Phillip, Hwang, Lindsay, Yu, Cheng, Zada, Gabriel, Patel, Samir, Deibert, Christopher P., Picozzi, Piero, Franzini, Andrea, Attuati, Luca, Prasad, Rahul N., Raval, Raju R., Palmer, Joshua D., Lee, Cheng-chia, Yang, Huai-che, Harmsen, William S., Jones, Brianna M., Sharma, Sonam, Ahluwalia, Manmeet S., Sheehan, Jason P., and Trifiletti, Daniel M.

Published
2023
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47. Local control and survival after stereotactic radiosurgery for colorectal cancer brain metastases: an international multicenter analysis

Author

Bin-Alamer, Othman, primary, Abou-Al-Shaar, Hussam, additional, Singh, Raj, additional, Mallela, Arka N., additional, Legarreta, Andrew, additional, Bowden, Greg, additional, Mathieu, David, additional, Perlow, Haley K., additional, Palmer, Joshua D., additional, Elhamdani, Shahed, additional, Shepard, Matthew, additional, Liang, Yun, additional, Nabeel, Ahmed M., additional, Reda, Wael A., additional, Tawadros, Sameh R., additional, Abdelkarim, Khaled, additional, El-Shehaby, Amr M. N., additional, Emad Eldin, Reem, additional, Elazzazi, Ahmed Hesham, additional, Warnick, Ronald E., additional, Gozal, Yair M., additional, Daly, Megan, additional, McShane, Brendan, additional, Addis-Jackson, Marcel, additional, Karthikeyan, Gokul, additional, Smith, Sian, additional, Picozzi, Piero, additional, Franzini, Andrea, additional, Kaisman-Elbaz, Tehila, additional, Yang, Huai-che, additional, Hess, Judith, additional, Templeton, Kelsey, additional, Zhang, Xiaoran, additional, Wei, Zhishuo, additional, Pikis, Stylianos, additional, Mantziaris, Georgios, additional, Simonova, Gabriela, additional, Liscak, Roman, additional, Peker, Selcuk, additional, Samanci, Yavuz, additional, Chiang, Veronica, additional, Kersh, Charles R., additional, Lee, Cheng-Chia, additional, Trifiletti, Daniel M., additional, Niranjan, Ajay, additional, Hadjipanayis, Constantinos G., additional, Lunsford, L. Dade, additional, and Sheehan, Jason P., additional

Published
2024
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49. Radiation Therapy for IDH-Mutant Grade 2 and Grade 3 Diffuse Glioma: An ASTRO Clinical Practice Guideline

Author

Halasz, Lia M., Attia, Albert, Bradfield, Lisa, Brat, Daniel J., Kirkpatrick, John P., Laack, Nadia N., Lalani, Nafisha, Lebow, Emily S., Liu, Arthur K., Niemeier, Heather M., Palmer, Joshua D., Peters, Katherine B., Sheehan, Jason, Thomas, Reena P., Vora, Sujay A., Wahl, Daniel R., Weiss, Stephanie E., Yeboa, D. Nana, Zhong, Jim, and Shih, Helen A.

Published
2022
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