Citations 2
Burden of Central Nervous System Cancer in the United States, 1990-2021
Collaborators, GBD 2021 US CNS Cancer, Han, Hyun Jin , Kim, Yun Seo , Park, Seoyeon , Shin, Jae Il , Kim, Min Seo , Areda, Demelash, Tork, Mohammad Amin Bayat , Bilgin, Gokce Belge , Chennapragada, Suma Sri , Dean, Frances , Deekonda, Sindhura, Ding, Xueting, E’mar, Abdel Rahman, Elhadi, Muhammed, Fazeli, Patrick , Fisher, James L. , Fotouhi, Maryam , Gholamrezanezhad, Ali , Ida, Fidelia , Jani, Chinmay , Kalani, Rizwan , Kazemi, Foad , Keshwani, Ariz, Khosla, Atulya Aman , Lim, Stephen S , Murray, Christopher J L , Naik, Gurudatta , Nguyen, Dang Tuan , Penberthy, Louise, Pestell, Richard G. , Prabhu, Disha , Ramasamy, Shakthi Kumaran, Sabet, Cameron John, Şenol, Yiğit Can , Sham, Sunder, Solanki, Ranjan , Tanwar, Manoj , Amirikah, Mike Tuffour, Verma, Anjul, Yon, Dong Keon, Yon, Dong Keon , Shin, Jae I L , Senol, Yigit Can , Collaborators, GBD 2021 US CNS Cancer, Moon, Ju Hyung , Kim, Yong Bae , Ababneh, Hazim , Abu‐Zaid, Ahmed , Arul, Santhosh , Azzam, Ahmed Y , Bardhan, Mainak , Behnam, Babak , Bhardwaj, Prarthna V , Bhuyan, Soumitra Sudip , Lomer, Nima Broomand , Chen, Mengxuan , Dai, Xiaochen , Doshi, Ojas Prakashbhai , Fares, Jawad , Iwu, Chidozie Declan , Jalloh, Mohamed, Kankam, Samuel Berchi , Mehboob, Riffat , Meštrović, Tomislav , Mokdad, Ali H. , Natto, Zuhair S. , Nguyen, Dang, Nugen, Fred , Orscelik, Atakan , Parikh, Romil R , Puvvula, Jagadeesh , Ramasamy, Shakthi Kumaran, Sabet, Cameron John , Schumacher, Austin E , Sherchan, Samendra , Simegn, Gizeaddis Lamesgin , Singh, Jasvinder A. , Srichawla, Bahadar Singh , Taiba, Jabeen , Yunusa, Ismaeel , Zheng, David X. , Park, Keun Young
JAMA Neurology | November 3, 2025 | Volume: 83 | Issue: 1 | Pages: 35
Importance Primary brain and central nervous system cancer (collectively referred to as CNS cancer) comprises 2% of all human cancers and poses significant health and economic challenges in the United States. Objective To analyze CNS cancer burden in the US, stratified by time, location (state and division), sex, age group, and Sociodemographic Index (SDI). Design, Setting, and Participants This cross-sectional study involved a repeated analysis of Global Burden of Disease Study (GBD) 2021 data in 2024. Using data from 183 sources, CNS cancer metrics in the US were estimated across states and years. US CNS cancer metrics across all sexes and age groups were included in the GBD. Exposure CNS cancer diagnosis. Main Outcomes and Measures Overall and age-standardized estimates of the incidence, prevalence, mortality, disability-adjusted life-years (DALYs), years of life lost, and years lived with disability per 100 000 population, including 95% uncertainty intervals (UIs), and time trends. Results In 2021, for all age groups and sexes across the US, there were 31 780 incident cases (95% UI, 29971.1 to 32843.9). Age-standardized incidence, DALYs, and mortality rates per 100 000 population were 6.91 (95% UI, 6.58 to 7.12), 134.38 (95% UI, 129.83 to 137.95), and 4.1 (95% UI, 3.87 to 4.22), respectively. Despite no significant change observed in the overall incidence between 1990 and 2021, DALY and mortality rates decreased by 15.77% (95% UI, −17.75% to −13.68%) and 8.41% (95% UI, −11.09% to −6.22%), respectively. Substantial geographic variability was noted. Mississippi, Alabama, Kentucky, and Kansas (West North Central and East South Central divisions) and West Virginia faced persistently high burdens over the past 30 years. Sex differences were evident; disease burden was consistently higher in males compared with females. Age-specific estimates showed a bimodal distribution: the youngest group (<5 years) showed a significant decrease in incidence rate (−34.42% to −11.56%), whereas older age groups (>70 years) experienced increasing trends. DALYs and mortality rates were negatively correlated with SDI (ρ = −0.6860 and ρ = −0.6391; P < .001). Conclusions and Relevance These findings provide valuable insights into the CNS cancer burden across the US by age, sex, location, and SDI, enabling better public health status assessments, health care policy restructuring, and resource redistribution for improved care.
The Brain Tumor Segmentation (BraTS-METS) Challenge 2023: Brain Metastasis Segmentation on Pre-treatment MRI
Janas, Anastasia , Baid, Ujjwal , Ramakrishnan, Divya , Saluja, Rachit , Ashraf, Nader, Maleki, Nazanin , Yordanov, Nikolay , Fehringer, Pascal, Gkampenis, Athanasios , Amiruddin, Raisa, Adewole, Maruf , Albrecht, Jake, Anazodo, Udunna, Anwar, Syed Muhammad, Bergquist, Timothy , Chiang, Veronica , Eddy, J. Mark , Ezhov, Ivan , Khalili, Nastaran, Jiang, Zhifan , Johanson, Elaine, Kazerooni, Anahita Fathi , Krantchev, Kiril, Linguraru, Marius George , Liu, Xinyang , Meier, Zeke, Moy, Harrison, Osenberg, Klara , Reitman, Zachary, Shinohara, Russell Takeshi, Wang, Chunhao , Shafique, Umber, Willms, Klara, Avesta, Arman , Bousabarah, Khaled , Chakrabarty, Satrajit , Gennaro, Nicolò , Holler, Wolfgang, Lost, Jan , Marcus, Daniel S. , Maresca, R, Merkaj, Sarah, Pedersen, Gabriel Cassinelli, Reppert, Marc von , Teytelboym, Oleg M., Tillmans, Niklas, Westerhoff, Malte , Youssef, Ayda , Pflüger, Irada, Perez-Carillo, Gloria J. Guzman, Memon, Fatima, Krycia, Mark, Patro, Satya Narayana , Petrović, Bojan , Schrickel, E. Brooke, Besada, Cristina , Chu, Sammy, Dusoi, Alexandru, Farage, Luciano , Fong, Amy, Gray, R. Ian, Krumpelman, Chase, Lincoln, Christie M. , Maros, Máté E. , Morón, Fanny , Nimchinsky, Esther A. , Patel, Uresh, Rohatgi, Saurabh , Sayah, Anousheh , Schwartz, Eric D. , Shiroishi, Mark S. , Valerie, Jewels, White, Matthew L. , Zohrabian, Vahe M. , Brüßeler, Melanie, Ghonim, Mohamed, Okar, Abdullah , Pasquini, L. , Soumala, Theodora, Taherzadeh, Mahsa , Vollmuth, Philipp, Foltyn, Martha , Abayazeed, Aly, Dellepiane, Francesco , Verdier, Maria Correia de , Al-Rubaiey, Sanaria, Ashraf, Kholod, Asla, Moamen M., Badawy, Mohamed , Lomer, Nima Broomand , Bukatz, Jan, Chen, Jim, Cimflová, Petra , Corr, Felix, Crawley, Alexis, Deptula, Lisa, Elakhdar, Tasneem, Shawali, Islam H., Frick, Alexandra, Haider, Muhammad Ammar , Hierro, Fátima , Jacobs, Sarah Maria, Hsieh, Kuang-chun Jim, Kersting, Katharina , Kida, Laura, Kollia, Sofia , Koukoulithras, Ioannis, Li, Xiao , Abouelatta, Ahmed, Mansour, Aya, Maria-Zamfirescu, Ruxandra-Catrinel, Marsiglia, Marcela , Mateo-Camacho, Yohana Sarahi , McArthur, Mark J., McDonnell, Olivia, McHugh, M, Moassefi, Mana , Morsi, Samah Mostafa, Munteanu, Alexander , Naqvi, Syed Raza, Nikanpour, Yalda , Alnoury, Mostafa , Nouh, Abdullah Mohamed Aly, Pappafava, Francesca, Patel, Markand D., Petrucci, S. , Rawie, Eric, Raymond, Scott B. , Roohani, Borna, Sabouhi, Sadeq, Sánchez‐García, Laura , Shaked, Zoe , Altes, Talissa A. , Isufi, Edvin , Dhemesh, Yaseen , Gass, Jaime, Thacker, Jonathan, Tarabishy, Abdul , Turner, Benjamin , Worede, Fikadu , Yousry, Sara, Lerebo, Wondwossen , Aristizábal, Alejandro , Karargyris, Alexandros , Kassem, Hasan , Sheller, Micah , Link, Katherine E. , Moawad, Ahmed W. , Ashraf, Nader, Jekel, Leon , Manteghinejad, Amirreza , Aneja, Sanjay , Anwar, Syed Muhammad, Chung, Verena , Conte, Gian Marco , Dako, Farouk , Eddy, James, Khalili, Nastaran, Farahani, Keyvan , Iglesias, Juan Eugenio , Kofler, Florian , LaBella, Dominic , Leemput, Koen Van , Li, Hongwei , Meier, Zeke, Menze, Bjoern H. , Piraud, Marie , Shinohara, Russell Taki , Wiestler, Benedikt , Wiggins, Walter F. , Kaur, Manpreet , LaMontagne, Pamela , Lin, MingDe , Maresca, Ryan, Petersen, Gabriel Cassinelli , Sotiras, Aristeidis , Godfrey, Devon , Floyd, Scott , Rauschecker, Andreas M. , Villanueva-Meyer, Javier E. , Cho, Jaeyoung , Bendszus, Martin , Brugnara, Gianluca , Cramer, Justin , Johnson, Derek R. , Kam, Anthony , Kwan, Benjamin Y. M. , Lai, Lillian M. , Lall, Neil , So, Tiffany Y. , Thompson, Gerard , Wu, Lei , Bansal, Anu , Barkhof, Frederik , Druzgal, T. Jason , Feltrin, Fabrício Stewan , Fung, Steve H. , Ikuta, Ichiro , Iv, Michael , Postma, Alida A. , Mahajan, Amit Kumar , Joyner, David , Létourneau‐Guillon, Laurent , Miller, Elka , Özsarlak, Ö. , Saha, Atin , Shih, Robert , Small, Juan E. , Tanwar, Manoj , Weinberg, Brent D. , Young, Robert J. , Azizova, Aynur , Ghonim, Mohanad , Ghonim, Mohamed, Sharifi, Yasaman , Singh, Gagandeep, Sollmann, Nico , Vollmuth, Philipp, Foltyn‐Dumitru, Martha , Malhotra, Ajay , Lohmann, Philipp , Pérez‐García, Víctor M. , Elhalawani, Hesham M. , Duarte Armindo, Rui , Asla, Moamen M., Bisschop, Jeroen , Faghani, Shahriar , Gulati, Vaibhav , Dahl, Rasmus Holmboe , McArthur, Mark, McHugh, Maire, Moassefi, Mana , Nandolia, Khanak , Petrucci, Samantha, Sanchez-Garcia, Laura M., Suthar, Pokhraj Prakashchandra , Vacca, Sebastiano , Vilanilam, George K. , Warren, Daniel, Weiss, David, Pati, Sarthak , Calabrese, Evan , Tahon, Nourel Hoda , Nada, Ayman , Velichko, Yury , Bakas, Spyridon , Rudie, Jeffrey D. , Aboian, Mariam
Machine Learning for Biomedical Imaging | June 26, 2025 | Volume: 3 | Issue: December 2025 | Pages: 204-247
The translation of AI-generated brain metastases (BM) segmentation into clinical practice relies heavily on diverse, high-quality annotated medical imaging datasets. The BraTS-METS 2023 challenge has gained momentum for testing and benchmarking algorithms using rigorously annotated internationally compiled real-world datasets. This study presents the results of the segmentation challenge and characterizes the challenging cases that impacted the performance of the winning algorithms. Untreated brain metastases on standard anatomic MRI sequences (T1, T2, FLAIR, T1PG) from eight contributed international datasets were annotated in stepwise method: published UNET algorithms, student, neuroradiologist, final approver neuroradiologist. Segmentations were ranked based on lesion-wise Dice and Hausdorff distance (HD95) scores. False positives (FP) and false negatives (FN) were rigorously penalized, receiving a score of 0 for Dice and a fixed penalty of 374 for HD95. The mean scores for the teams were calculated. Eight datasets comprising 1303 studies were annotated, with 402 studies (3076 lesions) released on Synapse as publicly available datasets to challenge competitors. Additionally, 31 studies (139 lesions) were held out for validation, and 59 studies (218 lesions) were used for testing. Segmentation accuracy was measured as rank across subjects, with the winning team achieving a LesionWise mean score of 7.9. The Dice score for the winning team was 0.65 ± 0.25. Common errors among the leading teams included false negatives for small lesions and misregistration of masks in space. The Dice scores and lesion detection rates of all algorithms diminished with decreasing tumor size, particularly for tumors smaller than 100 mm3. In conclusion, algorithms for BM segmentation require further refinement to balance high sensitivity in lesion detection with the minimization of false positives and negatives. The BraTS-METS 2023 challenge successfully curated well- annotated, diverse datasets and identified common errors, facilitating the translation of BM segmentation across varied environments and providing the tools for future development of personalized volumetric reports to patients undergoing BM treatment.