1
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Alan N, Zenkin S, Lavadi RS, Legarreta AD, Hudson JS, Fields DP, Agarwal N, Mamindla P, Ak M, Peddagangireddy V, Puccio L, Buell TJ, Hamilton DK, Kanter AS, Okonkwo DO, Zinn PO, Colen RR. Associating T1-Weighted and T2-Weighted Magnetic Resonance Imaging Radiomic Signatures With Preoperative Symptom Severity in Patients With Cervical Spondylotic Myelopathy. World Neurosurg 2024; 184:e137-e143. [PMID: 38253177 DOI: 10.1016/j.wneu.2024.01.072] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2023] [Accepted: 01/14/2024] [Indexed: 01/24/2024]
Abstract
BACKGROUND Preoperative symptom severity in cervical spondylotic myelopathy (CSM) can be variable. Radiomic signatures could provide an imaging biomarker for symptom severity in CSM. This study utilizes radiomic signatures of T1-weighted and T2-weighted magnetic resonance imaging images to correlate with preoperative symptom severity based on modified Japanese Orthopaedic Association (mJOA) scores for patients with CSM. METHODS Sixty-two patients with CSM were identified. Preoperative T1-weighted and T2-weighted magnetic resonance imaging images for each patient were segmented from C2-C7. A total of 205 texture features were extracted from each volume of interest. After feature normalization, each second-order feature was further subdivided to yield a total of 400 features from each volume of interest for analysis. Supervised machine learning was used to build radiomic models. RESULTS The patient cohort had a median mJOA preoperative score of 13; of which, 30 patients had a score of >13 (low severity) and 32 patients had a score of ≤13 (high severity). Radiomic analysis of T2-weighted imaging resulted in 4 radiomic signatures that correlated with preoperative mJOA with a sensitivity, specificity, and accuracy of 78%, 89%, and 83%, respectively (P < 0.004). The area under the curve value for the ROC curves were 0.69, 0.70, and 0.77 for models generated by independent T1 texture features, T1 and T2 texture features in combination, and independent T2 texture features, respectively. CONCLUSIONS Radiomic models correlate with preoperative mJOA scores using T2 texture features in patients with CSM. This may serve as a surrogate, objective imaging biomarker to measure the preoperative functional status of patients.
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Affiliation(s)
- Nima Alan
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, California.
| | - Serafettin Zenkin
- Department of Radiology, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania
| | - Raj Swaroop Lavadi
- Department of Neurological Surgery, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Andrew D Legarreta
- Department of Neurological Surgery, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Joseph S Hudson
- Department of Neurological Surgery, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Daryl P Fields
- Department of Neurological Surgery, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Nitin Agarwal
- Department of Neurological Surgery, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania; Department of Neurological Surgery, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania
| | - Priyadarshini Mamindla
- Department of Radiology, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania
| | - Murat Ak
- Department of Radiology, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania
| | - Vishal Peddagangireddy
- Department of Radiology, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania
| | - Lauren Puccio
- Department of Neurological Surgery, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Thomas J Buell
- Department of Neurological Surgery, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - D Kojo Hamilton
- Department of Neurological Surgery, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Adam S Kanter
- Department of Neurosurgery, Hoag Neurosciences Institute, Newport Beach, California
| | - David O Okonkwo
- Department of Neurological Surgery, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Pascal O Zinn
- Department of Neurological Surgery, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Rivka R Colen
- Department of Radiology, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania; Hillman Cancer Center, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania
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Alswang JM, Mbuguje EM, Chan SM, Ak M, Naif A, Rukundo I, Minja F, Newsome J, Ramalingam V, Laage Gaupp FM. Creating a Sustainable Foundation for Interventional Radiology Services and Training in Sub-Saharan Africa: Five-Year Update on the Road2IR Initiative. J Vasc Interv Radiol 2024:S1051-0443(24)00236-7. [PMID: 38513756 DOI: 10.1016/j.jvir.2024.03.015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Revised: 02/14/2024] [Accepted: 03/11/2024] [Indexed: 03/23/2024] Open
Abstract
PURPOSE To evaluate the growth and quality of an IR training model designed for resource-constrained settings and implemented in Tanzania, as well as its overall potential to increase access to minimally invasive procedures across the region. MATERIALS AND METHODS IR training in Tanzania began in 10/2018 through monthly deployment of visiting teaching teams for hands-on training combined with in-person and remote lectures. A competency-based two-year Master of Science (MSc) in IR curriculum was inaugurated at the nation's main teaching hospital in 10/2019, graduating its first two classes in 2021 and 2022. Procedural data, demographics, and clinical outcomes were collected and analyzed throughout the duration of this program. RESULTS From 10/2018 to 7/2022, 1,595 procedures were performed in Tanzania: 1,236 non-vascular and 359 vascular, all with local fellows as primary operators. 97.2% were technically successful, 95.2% were without complication, and 28.9% were performed independently by Tanzanian fellows and faculty with no difference in complication and technical success rates (p=0.63 and 0.90, respectively), irrespective of procedural class. Ten IR physicians graduated from this program during the study period, followed by another three per year going forward. Partner training programs in Uganda and Rwanda mirroring this model commenced in 2023 and 2024, respectively. CONCLUSION The reported training model offers a practical and effective solution to meet many of the challenges associated with the lack of access to IR in sub-Saharan Africa.
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Affiliation(s)
| | - Erick M Mbuguje
- Department of Radiology, Muhimbili National Hospital, Dar Es Salaam, Tanzania
| | - Shin Mei Chan
- Department of Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, CA
| | - Murat Ak
- University of Pittsburgh Hillman Cancer Center, Pittsburgh, PA
| | - Azza Naif
- Department of Radiology, Muhimbili National Hospital, Dar Es Salaam, Tanzania
| | - Ivan Rukundo
- Department of Radiology, Rwanda Military Hospital, Kigali, Rwanda
| | - Frank Minja
- Department of Radiology, Emory University School of Medicine, Atlanta, GA
| | - Janice Newsome
- Department of Radiology, Emory University School of Medicine, Atlanta, GA
| | - Vijay Ramalingam
- Division of Vascular and Interventional Radiology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA
| | - Fabian M Laage Gaupp
- Section of Interventional Radiology, Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT
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de Miguel-Perez D, Ak M, Mamindla P, Russo A, Zenkin S, Ak N, Peddagangireddy V, Lara-Mejia L, Gunasekaran M, Cardona AF, Naing A, Hirsch FR, Arrieta O, Colen RR, Rolfo C. Validation of a multiomic model of plasma extracellular vesicle PD-L1 and radiomics for prediction of response to immunotherapy in NSCLC. J Exp Clin Cancer Res 2024; 43:81. [PMID: 38486328 PMCID: PMC10941547 DOI: 10.1186/s13046-024-02997-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2024] [Accepted: 02/27/2024] [Indexed: 03/17/2024] Open
Abstract
BACKGROUND Immune-checkpoint inhibitors (ICIs) have showed unprecedent efficacy in the treatment of patients with advanced non-small cell lung cancer (NSCLC). However, not all patients manifest clinical benefit due to the lack of reliable predictive biomarkers. We showed preliminary data on the predictive role of the combination of radiomics and plasma extracellular vesicle (EV) PD-L1 to predict durable response to ICIs. MAIN BODY Here, we validated this model in a prospective cohort of patients receiving ICIs plus chemotherapy and compared it with patients undergoing chemotherapy alone. This multiparametric model showed high sensitivity and specificity at identifying non-responders to ICIs and outperformed tissue PD-L1, being directly correlated with tumor change. SHORT CONCLUSION These findings indicate that the combination of radiomics and EV PD-L1 dynamics is a minimally invasive and promising biomarker for the stratification of patients to receive ICIs.
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Affiliation(s)
- Diego de Miguel-Perez
- Center for Thoracic Oncology, Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, Mount Sinai, 1470 Madison Ave, New York, NY, 10029, USA
- Marlene and Stewart Greenebaum Comprehensive Cancer Center, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Murat Ak
- University of Pittsburgh Medical Center, Pittsburgh, PA, USA
- Hillman Cancer Center, University of Pittsburgh Medical Center, Pittsburgh, PA, USA
| | | | - Alessandro Russo
- Marlene and Stewart Greenebaum Comprehensive Cancer Center, University of Maryland School of Medicine, Baltimore, MD, USA
- Medical Oncology Unit, A.O. Papardo & Department of Human Pathology, University of Messina, Messina, Italy
| | | | - Nursima Ak
- University of Pittsburgh Medical Center, Pittsburgh, PA, USA
- Hillman Cancer Center, University of Pittsburgh Medical Center, Pittsburgh, PA, USA
| | - Vishal Peddagangireddy
- University of Pittsburgh Medical Center, Pittsburgh, PA, USA
- Hillman Cancer Center, University of Pittsburgh Medical Center, Pittsburgh, PA, USA
| | - Luis Lara-Mejia
- Thoracic Oncology Unit, Instituto Nacional de Cancerología (INCan), Mexico City, Mexico
| | - Muthukumar Gunasekaran
- Marlene and Stewart Greenebaum Comprehensive Cancer Center, University of Maryland School of Medicine, Baltimore, MD, USA
- Departments of Surgery and Pediatrics, Feinberg School of Medicine, Ann and Robert H. Lurie Children's Hospital of Chicago, Northwestern University, Chicago, IL, USA
| | - Andres F Cardona
- Molecular Oncology and Biology Systems Research Group (Fox G), Universidad El Bosque, Bogota, Colombia
| | - Aung Naing
- Departments of Investigational Cancer Therapeutics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Fred R Hirsch
- Center for Thoracic Oncology, Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, Mount Sinai, 1470 Madison Ave, New York, NY, 10029, USA
| | - Oscar Arrieta
- Thoracic Oncology Unit, Instituto Nacional de Cancerología (INCan), Mexico City, Mexico
| | - Rivka R Colen
- University of Pittsburgh Medical Center, Pittsburgh, PA, USA
- Hillman Cancer Center, University of Pittsburgh Medical Center, Pittsburgh, PA, USA
| | - Christian Rolfo
- Center for Thoracic Oncology, Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, Mount Sinai, 1470 Madison Ave, New York, NY, 10029, USA.
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Aksoy H, Gökahmetoğlu G, Ak M, Aksoy Ü. Subcutaneous wound infiltration of ketamine is superior to bupivacaine in terms of pain perception and opioid consumption after cesarean section: a double-blinded randomized placebo-controlled clinical trial. Eur Rev Med Pharmacol Sci 2023; 27:8860-8867. [PMID: 37782194 DOI: 10.26355/eurrev_202309_33806] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 10/03/2023]
Abstract
OBJECTIVE The aim of the present study was to evaluate the analgesic efficiency of SC ketamine, either alone or in combination with bupivacaine, following CS by means of postoperative pain and opioid need. PATIENTS AND METHODS One hundred and twenty women were allocated into 4 groups in this prospective, double-blind, placebo-controlled, randomized trial. Group K (Ketamine, n=30) received SC 1 mg/kg ketamine. Group B (Bupivacaine, n=30) received SC 20 mL bupivacaine 0.5%. Group KB (Ketamine+Bupivacaine, n=30) received SC ketamine 1 mg/kg plus SC 20 mL bupivacaine 0.5%. Group P (Placebo, n=30) received SC 30 mL 0.9% saline (placebo). RESULTS VAS scores at resting and on coughing and analgesic consumptions were compared. Visual analogue scale (VAS) pain scores at rest and coughing, at 15 and 60 minutes, and 2, 6 and 12 hours, and total opioid necessity were measured. VAS scores at rest in Group P were higher than in Group KB at the 6th hour, while lower in Group K and Group KB than in Groups B or P at the 12th hour. Patients receiving placebo had higher coughing VAS scores than those receiving ketamine or ketamine+bupivacaine at 2nd, 6th and 12th hours. Patients in Groups P and B required higher doses of morphine than those in groups K or KB. CONCLUSIONS Subcutaneous ketamine, either alone or in combination with bupivacaine, provides a better postoperative pain relief and reduces postoperative opioid consumption when compared to use of bupivacaine alone.
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Affiliation(s)
- H Aksoy
- Department of Obstetrics and Gynecology, Kayseri City Hospital, Kayseri, Turkey.
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5
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Aksoy H, Ak M, Gökahmetoğlu G, Aksoy Ü. The comparison of intraincisional bupivacaine infiltration and intravenous paracetamol administration for pain alleviation after cesarean section: a double-blinded randomized placebo controlled clinical trial. Eur Rev Med Pharmacol Sci 2023; 27:3467-3474. [PMID: 37140296 DOI: 10.26355/eurrev_202304_32117] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 05/05/2023]
Abstract
OBJECTIVE This study aimed to compare the analgesic effect of subcutaneous (SC) bupivacaine and intravenous (IV) paracetamol on postoperative pain and opioid requisites in patients undergoing cesarean delivery. PATIENTS AND METHODS One hundred and five women were allocated into 3 groups in this prospective, double-blind, placebo-controlled, randomized trial. Group 1 received SC bupivacaine, Group 2 received IV paracetamol following surgery and every 6 hours for 24 hours in the postoperative period, Group 3 received SC 0.9% saline and IV 0.9% saline at similar periods. Visual analogue scale (VAS) pain scores at rest and coughing, at 15 and 60 minutes, and 2, 6 and 12 hours, and total opioid necessity were measured. RESULTS VAS scores at rest were higher in placebo group than in bupivacaine and paracetamol groups at 15 minutes (p=0.047) and 2 hours (p=0.004). VAS scores at coughing were higher in placebo group than in bupivacaine and paracetamol groups at 2 hour (p=0.001) and 6 hours (p=0.018). Placebo group needed higher (p<0.001) doses of morphine than paracetamol or bupivacaine groups. CONCLUSIONS Intravenous paracetamol decreases pain scores similar to SC bupivacaine in the postoperative period compared to placebo. Patients taking bupivacaine or paracetamol need fewer opioids than placebo.
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Affiliation(s)
- H Aksoy
- Department of Obstetrics and Gynecology, Department of Anesthesiology and Reanimation, Kayseri City Hospital, Kayseri, Turkey.
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Alswang J, Mbuguje E, Ak M, Naif A, Rukundo I, Chan S, Minja F, Newsome J, Ramalingam V, Gaupp FL. Abstract No. 104 Five-Year Update on the Tanzania IR Initiative: Creating a Sustainable Foundation for IR Services and Training in Sub-Saharan Africa. J Vasc Interv Radiol 2023. [DOI: 10.1016/j.jvir.2022.12.153] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/27/2023] Open
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Pati S, Baid U, Edwards B, Sheller M, Wang SH, Reina GA, Foley P, Gruzdev A, Karkada D, Davatzikos C, Sako C, Ghodasara S, Bilello M, Mohan S, Vollmuth P, Brugnara G, Preetha CJ, Sahm F, Maier-Hein K, Zenk M, Bendszus M, Wick W, Calabrese E, Rudie J, Villanueva-Meyer J, Cha S, Ingalhalikar M, Jadhav M, Pandey U, Saini J, Garrett J, Larson M, Jeraj R, Currie S, Frood R, Fatania K, Huang RY, Chang K, Balaña C, Capellades J, Puig J, Trenkler J, Pichler J, Necker G, Haunschmidt A, Meckel S, Shukla G, Liem S, Alexander GS, Lombardo J, Palmer JD, Flanders AE, Dicker AP, Sair HI, Jones CK, Venkataraman A, Jiang M, So TY, Chen C, Heng PA, Dou Q, Kozubek M, Lux F, Michálek J, Matula P, Keřkovský M, Kopřivová T, Dostál M, Vybíhal V, Vogelbaum MA, Mitchell JR, Farinhas J, Maldjian JA, Yogananda CGB, Pinho MC, Reddy D, Holcomb J, Wagner BC, Ellingson BM, Cloughesy TF, Raymond C, Oughourlian T, Hagiwara A, Wang C, To MS, Bhardwaj S, Chong C, Agzarian M, Falcão AX, Martins SB, Teixeira BCA, Sprenger F, Menotti D, Lucio DR, LaMontagne P, Marcus D, Wiestler B, Kofler F, Ezhov I, Metz M, Jain R, Lee M, Lui YW, McKinley R, Slotboom J, Radojewski P, Meier R, Wiest R, Murcia D, Fu E, Haas R, Thompson J, Ormond DR, Badve C, Sloan AE, Vadmal V, Waite K, Colen RR, Pei L, Ak M, Srinivasan A, Bapuraj JR, Rao A, Wang N, Yoshiaki O, Moritani T, Turk S, Lee J, Prabhudesai S, Morón F, Mandel J, Kamnitsas K, Glocker B, Dixon LVM, Williams M, Zampakis P, Panagiotopoulos V, Tsiganos P, Alexiou S, Haliassos I, Zacharaki EI, Moustakas K, Kalogeropoulou C, Kardamakis DM, Choi YS, Lee SK, Chang JH, Ahn SS, Luo B, Poisson L, Wen N, Tiwari P, Verma R, Bareja R, Yadav I, Chen J, Kumar N, Smits M, van der Voort SR, Alafandi A, Incekara F, Wijnenga MMJ, Kapsas G, Gahrmann R, Schouten JW, Dubbink HJ, Vincent AJPE, van den Bent MJ, French PJ, Klein S, Yuan Y, Sharma S, Tseng TC, Adabi S, Niclou SP, Keunen O, Hau AC, Vallières M, Fortin D, Lepage M, Landman B, Ramadass K, Xu K, Chotai S, Chambless LB, Mistry A, Thompson RC, Gusev Y, Bhuvaneshwar K, Sayah A, Bencheqroun C, Belouali A, Madhavan S, Booth TC, Chelliah A, Modat M, Shuaib H, Dragos C, Abayazeed A, Kolodziej K, Hill M, Abbassy A, Gamal S, Mekhaimar M, Qayati M, Reyes M, Park JE, Yun J, Kim HS, Mahajan A, Muzi M, Benson S, Beets-Tan RGH, Teuwen J, Herrera-Trujillo A, Trujillo M, Escobar W, Abello A, Bernal J, Gómez J, Choi J, Baek S, Kim Y, Ismael H, Allen B, Buatti JM, Kotrotsou A, Li H, Weiss T, Weller M, Bink A, Pouymayou B, Shaykh HF, Saltz J, Prasanna P, Shrestha S, Mani KM, Payne D, Kurc T, Pelaez E, Franco-Maldonado H, Loayza F, Quevedo S, Guevara P, Torche E, Mendoza C, Vera F, Ríos E, López E, Velastin SA, Ogbole G, Soneye M, Oyekunle D, Odafe-Oyibotha O, Osobu B, Shu'aibu M, Dorcas A, Dako F, Simpson AL, Hamghalam M, Peoples JJ, Hu R, Tran A, Cutler D, Moraes FY, Boss MA, Gimpel J, Veettil DK, Schmidt K, Bialecki B, Marella S, Price C, Cimino L, Apgar C, Shah P, Menze B, Barnholtz-Sloan JS, Martin J, Bakas S. Author Correction: Federated learning enables big data for rare cancer boundary detection. Nat Commun 2023; 14:436. [PMID: 36702828 PMCID: PMC9879935 DOI: 10.1038/s41467-023-36188-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2023] Open
Affiliation(s)
- Sarthak Pati
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Informatics, Technical University of Munich, Munich, Bavaria, Germany
| | - Ujjwal Baid
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | | | | | | | | | | | | | | | - Christos Davatzikos
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Chiharu Sako
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Satyam Ghodasara
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Michel Bilello
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Suyash Mohan
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Philipp Vollmuth
- Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany
| | - Gianluca Brugnara
- Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany
| | | | - Felix Sahm
- Clinical Cooperation Unit Neuropathology, German Cancer Consortium (DKTK) within the German Cancer Research Center (DKFZ), Heidelberg, Germany
- Department of Neuropathology, Heidelberg University Hospital, Heidelberg, Germany
| | - Klaus Maier-Hein
- Division of Medical Image Computing, German Cancer Research Center, Heidelberg, Germany
- Pattern Analysis and Learning Group, Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany
| | - Maximilian Zenk
- Division of Medical Image Computing, German Cancer Research Center, Heidelberg, Germany
| | - Martin Bendszus
- Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany
| | - Wolfgang Wick
- Clinical Cooperation Unit Neuropathology, German Cancer Consortium (DKTK) within the German Cancer Research Center (DKFZ), Heidelberg, Germany
- Neurology Clinic, Heidelberg University Hospital, Heidelberg, Germany
| | - Evan Calabrese
- Department of Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
| | - Jeffrey Rudie
- Department of Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
| | - Javier Villanueva-Meyer
- Department of Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
| | - Soonmee Cha
- Department of Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
| | - Madhura Ingalhalikar
- Symbiosis Center for Medical Image Analysis, Symbiosis International University, Pune, Maharashtra, India
| | - Manali Jadhav
- Symbiosis Center for Medical Image Analysis, Symbiosis International University, Pune, Maharashtra, India
| | - Umang Pandey
- Symbiosis Center for Medical Image Analysis, Symbiosis International University, Pune, Maharashtra, India
| | - Jitender Saini
- Department of Neuroimaging and Interventional Radiology, National Institute of Mental Health and Neurosciences, Bangalore, Karnataka, India
| | - John Garrett
- Department of Radiology, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Department of Medical Physics, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
| | - Matthew Larson
- Department of Radiology, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
| | - Robert Jeraj
- Department of Radiology, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Department of Medical Physics, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
| | - Stuart Currie
- Leeds Teaching Hospitals Trust, Department of Radiology, Leeds, UK
| | - Russell Frood
- Leeds Teaching Hospitals Trust, Department of Radiology, Leeds, UK
| | - Kavi Fatania
- Leeds Teaching Hospitals Trust, Department of Radiology, Leeds, UK
| | - Raymond Y Huang
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Ken Chang
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
| | | | | | - Josep Puig
- Department of Radiology (IDI), Girona Biomedical Research Institute (IdIBGi), Josep Trueta University Hospital, Girona, Spain
| | - Johannes Trenkler
- Institute of Neuroradiology, Neuromed Campus (NMC), Kepler University Hospital Linz, Linz, Austria
| | - Josef Pichler
- Department of Neurooncology, Neuromed Campus (NMC), Kepler University Hospital Linz, Linz, Austria
| | - Georg Necker
- Institute of Neuroradiology, Neuromed Campus (NMC), Kepler University Hospital Linz, Linz, Austria
| | - Andreas Haunschmidt
- Institute of Neuroradiology, Neuromed Campus (NMC), Kepler University Hospital Linz, Linz, Austria
| | - Stephan Meckel
- Institute of Neuroradiology, Neuromed Campus (NMC), Kepler University Hospital Linz, Linz, Austria
- Institute of Diagnostic and Interventional Neuroradiology, RKH Klinikum Ludwigsburg, Ludwigsburg, Germany
| | - Gaurav Shukla
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA
- Department of Radiation Oncology, Christiana Care Health System, Philadelphia, PA, USA
| | - Spencer Liem
- Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, PA, USA
| | - Gregory S Alexander
- Department of Radiation Oncology, University of Maryland, Baltimore, MD, USA
| | - Joseph Lombardo
- Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, PA, USA
- Department of Radiation Oncology, Sidney Kimmel Cancer Center, Thomas Jefferson University, Philadelphia, PA, USA
| | - Joshua D Palmer
- Department of Radiation Oncology, The James Cancer Hospital and Solove Research Institute, The Ohio State University Comprehensive Cancer Center, Columbus, OH, USA
| | - Adam E Flanders
- Department of Radiology, Sidney Kimmel Cancer Center, Thomas Jefferson University, Philadelphia, PA, USA
| | - Adam P Dicker
- Department of Radiation Oncology, Sidney Kimmel Cancer Center, Thomas Jefferson University, Philadelphia, PA, USA
| | - Haris I Sair
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- The Malone Center for Engineering in Healthcare, The Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Craig K Jones
- The Malone Center for Engineering in Healthcare, The Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Archana Venkataraman
- Department of Electrical and Computer Engineering, Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Meirui Jiang
- The Chinese University of Hong Kong, Hong Kong, China
| | - Tiffany Y So
- The Chinese University of Hong Kong, Hong Kong, China
| | - Cheng Chen
- The Chinese University of Hong Kong, Hong Kong, China
| | | | - Qi Dou
- The Chinese University of Hong Kong, Hong Kong, China
| | - Michal Kozubek
- Centre for Biomedical Image Analysis, Faculty of Informatics, Masaryk University, Brno, Czech Republic
| | - Filip Lux
- Centre for Biomedical Image Analysis, Faculty of Informatics, Masaryk University, Brno, Czech Republic
| | - Jan Michálek
- Centre for Biomedical Image Analysis, Faculty of Informatics, Masaryk University, Brno, Czech Republic
| | - Petr Matula
- Centre for Biomedical Image Analysis, Faculty of Informatics, Masaryk University, Brno, Czech Republic
| | - Miloš Keřkovský
- Department of Radiology and Nuclear Medicine, Faculty of Medicine, Masaryk University, Brno and University Hospital Brno, Brno, Czech Republic
| | - Tereza Kopřivová
- Department of Radiology and Nuclear Medicine, Faculty of Medicine, Masaryk University, Brno and University Hospital Brno, Brno, Czech Republic
| | - Marek Dostál
- Department of Radiology and Nuclear Medicine, Faculty of Medicine, Masaryk University, Brno and University Hospital Brno, Brno, Czech Republic
- Department of Biophysics, Faculty of Medicine, Masaryk University, Brno, Czech Republic
| | - Václav Vybíhal
- Department of Neurosurgery, Faculty of Medicine, Masaryk University, Brno, and University Hospital and Czech Republic, Brno, Czech Republic
| | - Michael A Vogelbaum
- Department of Neuro Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
| | - J Ross Mitchell
- University of Alberta, Edmonton, AB, Canada
- Alberta Machine Intelligence Institute, Edmonton, AB, Canada
| | - Joaquim Farinhas
- Department of Radiology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
| | | | | | - Marco C Pinho
- University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Divya Reddy
- University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - James Holcomb
- University of Texas Southwestern Medical Center, Dallas, TX, USA
| | | | - Benjamin M Ellingson
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
- UCLA Neuro-Oncology Program, Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CaA, USA
| | - Timothy F Cloughesy
- UCLA Neuro-Oncology Program, Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CaA, USA
| | - Catalina Raymond
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Talia Oughourlian
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Akifumi Hagiwara
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Chencai Wang
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Minh-Son To
- College of Medicine and Public Health, Flinders University, Bedford Park, SA, Australia
- Division of Surgery and Perioperative Medicine, Flinders Medical Centre, Bedford Park, SA, Australia
| | - Sargam Bhardwaj
- College of Medicine and Public Health, Flinders University, Bedford Park, SA, Australia
| | - Chee Chong
- South Australia Medical Imaging, Flinders Medical Centre, Bedford Park, SA, Australia
| | - Marc Agzarian
- South Australia Medical Imaging, Flinders Medical Centre, Bedford Park, SA, Australia
- Department of Neurology, Baylor College of Medicine, Houston, TX, USA
| | | | | | - Bernardo C A Teixeira
- Instituto de Neurologia de Curitiba, Curitiba, Paraná, Brazil
- Department of Radiology, Hospital de Clínicas da Universidade Federal do Paraná, Curitiba, Paraná, Brazil
| | - Flávia Sprenger
- Department of Radiology, Hospital de Clínicas da Universidade Federal do Paraná, Curitiba, Paraná, Brazil
| | - David Menotti
- Department of Informatics, Universidade Federal do Paraná, Curitiba, Paraná, Brazil
| | - Diego R Lucio
- Department of Informatics, Universidade Federal do Paraná, Curitiba, Paraná, Brazil
| | - Pamela LaMontagne
- Department of Radiology, Washington University in St. Louis, St. Louis, MO, USA
| | - Daniel Marcus
- Department of Radiology, Washington University in St. Louis, St. Louis, MO, USA
| | - Benedikt Wiestler
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- TranslaTUM (Zentralinstitut für translationale Krebsforschung der Technischen Universität München), Klinikum rechts der Isar, Munich, Germany
| | - Florian Kofler
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- TranslaTUM (Zentralinstitut für translationale Krebsforschung der Technischen Universität München), Klinikum rechts der Isar, Munich, Germany
- Image-Based Biomedical Modeling, Department of Informatics, Technical University of Munich, Munich, Germany
| | - Ivan Ezhov
- Department of Informatics, Technical University of Munich, Munich, Bavaria, Germany
- TranslaTUM (Zentralinstitut für translationale Krebsforschung der Technischen Universität München), Klinikum rechts der Isar, Munich, Germany
- Image-Based Biomedical Modeling, Department of Informatics, Technical University of Munich, Munich, Germany
| | - Marie Metz
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Rajan Jain
- Department of Radiology, NYU Grossman School of Medicine, New York, NY, USA
- Department of Neurosurgery, NYU Grossman School of Medicine, New York, NY, USA
| | - Matthew Lee
- Department of Radiology, NYU Grossman School of Medicine, New York, NY, USA
| | - Yvonne W Lui
- Department of Radiology, NYU Grossman School of Medicine, New York, NY, USA
| | - Richard McKinley
- Support Center for Advanced Neuroimaging, University Institute of Diagnostic and Interventional Neuroradiology, University Hospital Bern, Inselspital, University of Bern, Bern, Switzerland
| | - Johannes Slotboom
- Support Center for Advanced Neuroimaging, University Institute of Diagnostic and Interventional Neuroradiology, University Hospital Bern, Inselspital, University of Bern, Bern, Switzerland
| | - Piotr Radojewski
- Support Center for Advanced Neuroimaging, University Institute of Diagnostic and Interventional Neuroradiology, University Hospital Bern, Inselspital, University of Bern, Bern, Switzerland
| | - Raphael Meier
- Support Center for Advanced Neuroimaging, University Institute of Diagnostic and Interventional Neuroradiology, University Hospital Bern, Inselspital, University of Bern, Bern, Switzerland
| | - Roland Wiest
- Support Center for Advanced Neuroimaging, University Institute of Diagnostic and Interventional Neuroradiology, University Hospital Bern, Inselspital, University of Bern, Bern, Switzerland
| | - Derrick Murcia
- Department of Neurosurgery, Anschutz Medical Campus, University of Colorado, Aurora, CO, USA
| | - Eric Fu
- Department of Neurosurgery, Anschutz Medical Campus, University of Colorado, Aurora, CO, USA
| | - Rourke Haas
- Department of Neurosurgery, Anschutz Medical Campus, University of Colorado, Aurora, CO, USA
| | - John Thompson
- Department of Neurosurgery, Anschutz Medical Campus, University of Colorado, Aurora, CO, USA
| | - David Ryan Ormond
- Department of Neurosurgery, Anschutz Medical Campus, University of Colorado, Aurora, CO, USA
| | - Chaitra Badve
- Department of Radiology, University Hospitals Cleveland, Cleveland, OH, USA
| | - Andrew E Sloan
- Department of Neurological Surgery, University Hospitals-Seidman Cancer Center, Cleveland, OH, USA
- Case Comprehensive Cancer Center, Cleveland, OH, USA
- Department of Neurosurgery, Case Western Reserve University School of Medicine, Cleveland, OH, USA
| | - Vachan Vadmal
- Department of Neurosurgery, Case Western Reserve University School of Medicine, Cleveland, OH, USA
| | - Kristin Waite
- National Cancer Institute, National Institute of Health, Division of Cancer Epidemiology and Genetics, Bethesda, MD, USA
| | - Rivka R Colen
- Department of Radiology, Neuroradiology Division, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Diagnostic Radiology, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Linmin Pei
- University of Pittsburgh Medical Center, Pittsburgh, PA, USA
| | - Murat Ak
- Department of Radiology, Neuroradiology Division, University of Pittsburgh, Pittsburgh, PA, USA
| | - Ashok Srinivasan
- Department of Neuroradiology, University of Michigan, Ann Arbor, MI, USA
| | - J Rajiv Bapuraj
- Department of Neuroradiology, University of Michigan, Ann Arbor, MI, USA
| | - Arvind Rao
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Nicholas Wang
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Ota Yoshiaki
- Department of Neuroradiology, University of Michigan, Ann Arbor, MI, USA
| | - Toshio Moritani
- Department of Neuroradiology, University of Michigan, Ann Arbor, MI, USA
| | - Sevcan Turk
- Department of Neuroradiology, University of Michigan, Ann Arbor, MI, USA
| | - Joonsang Lee
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Snehal Prabhudesai
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Fanny Morón
- Department of Radiology, Baylor College of Medicine, Houston, TX, USA
| | - Jacob Mandel
- Department of Neurology, Baylor College of Medicine, Houston, TX, USA
| | - Konstantinos Kamnitsas
- Department of Computing, Imperial College London, London, UK
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, UK
| | - Ben Glocker
- Department of Computing, Imperial College London, London, UK
| | - Luke V M Dixon
- Department of Radiology, Imperial College NHS Healthcare Trust, London, UK
| | - Matthew Williams
- Computational Oncology Group, Institute for Global Health Innovation, Imperial College London, London, UK
| | - Peter Zampakis
- Department of NeuroRadiology, University of Patras, Patras, Greece
| | | | - Panagiotis Tsiganos
- Clinical Radiology Laboratory, Department of Medicine, University of Patras, Patras, Greece
| | - Sotiris Alexiou
- Department of Electrical and Computer Engineering, University of Patras, Patras, Greece
| | - Ilias Haliassos
- Department of Neuro-Oncology, University of Patras, Patras, Greece
| | - Evangelia I Zacharaki
- Department of Electrical and Computer Engineering, University of Patras, Patras, Greece
| | | | | | | | | | | | | | - Sung Soo Ahn
- Yonsei University College of Medicine, Seoul, Korea
| | - Bing Luo
- Department of Radiation Oncology, Henry Ford Health System, Detroit, MI, USA
| | - Laila Poisson
- Public Health Sciences, Henry Ford Health System, Detroit, MI, USA
| | - Ning Wen
- Department of Radiation Oncology, Henry Ford Health System, Detroit, MI, USA
- SJTU-Ruijin-UIH Institute for Medical Imaging Technology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 200025, Shanghai, China
| | | | - Ruchika Verma
- Alberta Machine Intelligence Institute, Edmonton, AB, Canada
- Case Western Reserve University, Cleveland, OH, USA
| | - Rohan Bareja
- Case Western Reserve University, Cleveland, OH, USA
| | - Ipsa Yadav
- Case Western Reserve University, Cleveland, OH, USA
| | | | - Neeraj Kumar
- University of Alberta, Edmonton, AB, Canada
- Alberta Machine Intelligence Institute, Edmonton, AB, Canada
| | - Marion Smits
- Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Sebastian R van der Voort
- Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Ahmed Alafandi
- Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Fatih Incekara
- Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
- Department of Neurosurgery, Brain Tumor Center, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Maarten M J Wijnenga
- Department of Neurology, Brain Tumor Center, Erasmus MC Cancer Institute, Rotterdam, Netherlands
| | - Georgios Kapsas
- Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Renske Gahrmann
- Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Joost W Schouten
- Department of Neurosurgery, Brain Tumor Center, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Hendrikus J Dubbink
- Department of Pathology, Brain Tumor Center, Erasmus MC Cancer Institute, Rotterdam, Netherlands
| | - Arnaud J P E Vincent
- Department of Neurosurgery, Brain Tumor Center, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Martin J van den Bent
- Department of Neurology, Brain Tumor Center, Erasmus MC Cancer Institute, Rotterdam, Netherlands
| | - Pim J French
- Department of Neurology, Brain Tumor Center, Erasmus MC Cancer Institute, Rotterdam, Netherlands
| | - Stefan Klein
- Biomedical Imaging Group Rotterdam, Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Yading Yuan
- Department of Radiation Oncology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Sonam Sharma
- Department of Radiation Oncology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Tzu-Chi Tseng
- Department of Radiation Oncology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Saba Adabi
- Department of Radiation Oncology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Simone P Niclou
- NORLUX Neuro-Oncology Laboratory, Department of Cancer Research, Luxembourg Institute of Health, Luxembourg, Luxembourg
| | - Olivier Keunen
- Translation Radiomics, Department of Cancer Research, Luxembourg Institute of Health, Luxembourg, Luxembourg
| | - Ann-Christin Hau
- NORLUX Neuro-Oncology Laboratory, Department of Cancer Research, Luxembourg Institute of Health, Luxembourg, Luxembourg
- Luxembourg Center of Neuropathology, Laboratoire National De Santé, Luxembourg, Luxembourg
| | - Martin Vallières
- Department of Computer Science, Université de Sherbrooke, Sherbrooke, QC, Canada
- Centre de Recherche du Centre Hospitalière Universitaire de Sherbrooke, Sherbrooke, QC, Canada
| | - David Fortin
- Centre de Recherche du Centre Hospitalière Universitaire de Sherbrooke, Sherbrooke, QC, Canada
- Division of Neurosurgery and Neuro-Oncology, Faculty of Medicine and Health Science, Université de Sherbrooke, Sherbrooke, QC, Canada
| | - Martin Lepage
- Centre de Recherche du Centre Hospitalière Universitaire de Sherbrooke, Sherbrooke, QC, Canada
- Department of Nuclear Medicine and Radiobiology, Sherbrooke Molecular Imaging Centre, Université de Sherbrooke, Sherbrooke, QC, Canada
| | - Bennett Landman
- Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, USA
| | - Karthik Ramadass
- Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, USA
| | - Kaiwen Xu
- Department of Computer Science, Vanderbilt University, Nashville, TN, USA
| | - Silky Chotai
- Department of Neurosurgery, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Lola B Chambless
- Department of Neurosurgery, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Akshitkumar Mistry
- Department of Neurosurgery, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Reid C Thompson
- Department of Neurosurgery, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Yuriy Gusev
- Innovation Center for Biomedical Informatics (ICBI), Georgetown University, Washington, DC, USA
| | - Krithika Bhuvaneshwar
- Innovation Center for Biomedical Informatics (ICBI), Georgetown University, Washington, DC, USA
| | - Anousheh Sayah
- Division of Neuroradiology & Neurointerventional Radiology, Department of Radiology, MedStar Georgetown University Hospital, Washington, DC, USA
| | - Camelia Bencheqroun
- Innovation Center for Biomedical Informatics (ICBI), Georgetown University, Washington, DC, USA
| | - Anas Belouali
- Innovation Center for Biomedical Informatics (ICBI), Georgetown University, Washington, DC, USA
| | - Subha Madhavan
- Innovation Center for Biomedical Informatics (ICBI), Georgetown University, Washington, DC, USA
| | - Thomas C Booth
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
- Department of Neuroradiology, Ruskin Wing, King's College Hospital NHS Foundation Trust, London, UK
| | - Alysha Chelliah
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
| | - Marc Modat
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
| | - Haris Shuaib
- Stoke Mandeville Hospital, Mandeville Road, Aylesbury, UK
- Department of Biomedical and Molecular Sciences, Queen's University, Kingston, ON, Canada
| | - Carmen Dragos
- Stoke Mandeville Hospital, Mandeville Road, Aylesbury, UK
| | | | | | | | | | - Shady Gamal
- University of Cairo School of Medicine, Giza, Egypt
| | | | | | | | - Ji Eun Park
- Department of Radiology, Asan Medical Center, Seoul, South Korea
| | - Jihye Yun
- Department of Radiology, Asan Medical Center, Seoul, South Korea
| | - Ho Sung Kim
- Department of Radiology, Asan Medical Center, Seoul, South Korea
| | - Abhishek Mahajan
- The Clatterbridge Cancer Centre NHS Foundation Trust Pembroke Place, Liverpool, UK
| | - Mark Muzi
- Department of Radiology, University of Washington, Seattle, WA, USA
| | - Sean Benson
- Netherlands Cancer Institute, Amsterdam, Netherlands
| | - Regina G H Beets-Tan
- Department of Radiology, Netherlands Cancer Institute, Amsterdam, Netherlands
- GROW School of Oncology and Developmental Biology, Maastricht, Netherlands
| | - Jonas Teuwen
- Netherlands Cancer Institute, Amsterdam, Netherlands
| | | | | | - William Escobar
- Clínica Imbanaco Grupo Quirón Salud, Cali, Colombia
- Universidad del Valle, Cali, Colombia
| | | | - Jose Bernal
- Universidad del Valle, Cali, Colombia
- The University of Edinburgh, Edinburgh, UK
| | | | - Joseph Choi
- Department of Industrial and Systems Engineering, University of Iowa, Iowa, USA
| | - Stephen Baek
- Department of Industrial and Systems Engineering, Department of Radiation Oncology, University of Iowa, Iowa City, IA, USA
| | - Yusung Kim
- Department of Radiation Oncology, University of Iowa, Iowa City, IA, USA
| | - Heba Ismael
- Department of Radiation Oncology, University of Iowa, Iowa City, IA, USA
| | - Bryan Allen
- Department of Radiation Oncology, University of Iowa, Iowa City, IA, USA
| | - John M Buatti
- Department of Radiation Oncology, University of Iowa, Iowa City, IA, USA
| | | | - Hongwei Li
- Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland
| | - Tobias Weiss
- Department of Neurology, Clinical Neuroscience Center, University Hospital Zurich and University of Zurich, Zurich, Switzerland
| | - Michael Weller
- Department of Neurology, Clinical Neuroscience Center, University Hospital Zurich and University of Zurich, Zurich, Switzerland
| | - Andrea Bink
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich and University of Zurich, Zurich, Switzerland
| | - Bertrand Pouymayou
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich and University of Zurich, Zurich, Switzerland
| | | | - Joel Saltz
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, New York, USA
| | - Prateek Prasanna
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, New York, USA
| | - Sampurna Shrestha
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, New York, USA
| | - Kartik M Mani
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, New York, USA
- Department of Radiation Oncology, Stony Brook University, Stony Brook, NY, USA
| | - David Payne
- Department of Radiology, Stony Brook University, Stony Brook, NY, USA
| | - Tahsin Kurc
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, New York, USA
- Scientific Data Group, Oak Ridge National Laboratory, Oak Ridge, TN, USA
| | - Enrique Pelaez
- Escuela Superior Politecnica del Litoral, Guayaquil, Guayas, Ecuador
| | | | - Francis Loayza
- Escuela Superior Politecnica del Litoral, Guayaquil, Guayas, Ecuador
| | | | | | | | | | - Franco Vera
- Universidad de Concepción, Concepción, Biobío, Chile
| | - Elvis Ríos
- Universidad de Concepción, Concepción, Biobío, Chile
| | - Eduardo López
- Universidad de Concepción, Concepción, Biobío, Chile
| | - Sergio A Velastin
- School of Electronic Engineering and Computer Science, Queen Mary University of London, London, UK
| | - Godwin Ogbole
- Department of Radiology, University College Hospital Ibadan, Oyo, Nigeria
| | - Mayowa Soneye
- Department of Radiology, University College Hospital Ibadan, Oyo, Nigeria
| | - Dotun Oyekunle
- Department of Radiology, University College Hospital Ibadan, Oyo, Nigeria
| | | | - Babatunde Osobu
- Department of Radiology, University College Hospital Ibadan, Oyo, Nigeria
| | - Mustapha Shu'aibu
- Department of Radiology, Muhammad Abdullahi Wase Teaching Hospital, Kano, Nigeria
| | - Adeleye Dorcas
- Department of Radiology, Obafemi Awolowo University Ile-Ife, Ile-Ife, Osun, Nigeria
| | - Farouk Dako
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Center for Global Health, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Amber L Simpson
- Department of Biomedical and Molecular Sciences, Queen's University, Kingston, ON, Canada
- School of Computing, Queen's University, Kingston, ON, Canada
| | - Mohammad Hamghalam
- School of Computing, Queen's University, Kingston, ON, Canada
- Department of Electrical Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran
| | - Jacob J Peoples
- School of Computing, Queen's University, Kingston, ON, Canada
| | - Ricky Hu
- School of Computing, Queen's University, Kingston, ON, Canada
| | - Anh Tran
- School of Computing, Queen's University, Kingston, ON, Canada
| | - Danielle Cutler
- The Faculty of Arts & Sciences, Queen's University, Kingston, ON, Canada
| | - Fabio Y Moraes
- Department of Oncology, Queen's University, Kingston, ON, Canada
| | - Michael A Boss
- Center for Research and Innovation, American College of Radiology, Philadelphia, PA, USA
| | - James Gimpel
- Center for Research and Innovation, American College of Radiology, Philadelphia, PA, USA
| | - Deepak Kattil Veettil
- Center for Research and Innovation, American College of Radiology, Philadelphia, PA, USA
| | - Kendall Schmidt
- Data Science Institute, American College of Radiology, Reston, VA, USA
| | - Brian Bialecki
- Data Science Institute, American College of Radiology, Reston, VA, USA
| | - Sailaja Marella
- Center for Research and Innovation, American College of Radiology, Philadelphia, PA, USA
| | - Cynthia Price
- Center for Research and Innovation, American College of Radiology, Philadelphia, PA, USA
| | - Lisa Cimino
- Center for Research and Innovation, American College of Radiology, Philadelphia, PA, USA
| | - Charles Apgar
- Center for Research and Innovation, American College of Radiology, Philadelphia, PA, USA
| | | | - Bjoern Menze
- Department of Informatics, Technical University of Munich, Munich, Bavaria, Germany
- Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland
| | - Jill S Barnholtz-Sloan
- National Cancer Institute, National Institute of Health, Division of Cancer Epidemiology and Genetics, Bethesda, MD, USA
- Center for Biomedical Informatics and Information Technology, National Cancer Institute (NCI), National Institute of Health, Bethesda, MD, USA
| | | | - Spyridon Bakas
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA.
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
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Pati S, Baid U, Edwards B, Sheller M, Wang SH, Reina GA, Foley P, Gruzdev A, Karkada D, Davatzikos C, Sako C, Ghodasara S, Bilello M, Mohan S, Vollmuth P, Brugnara G, Preetha CJ, Sahm F, Maier-Hein K, Zenk M, Bendszus M, Wick W, Calabrese E, Rudie J, Villanueva-Meyer J, Cha S, Ingalhalikar M, Jadhav M, Pandey U, Saini J, Garrett J, Larson M, Jeraj R, Currie S, Frood R, Fatania K, Huang RY, Chang K, Balaña C, Capellades J, Puig J, Trenkler J, Pichler J, Necker G, Haunschmidt A, Meckel S, Shukla G, Liem S, Alexander GS, Lombardo J, Palmer JD, Flanders AE, Dicker AP, Sair HI, Jones CK, Venkataraman A, Jiang M, So TY, Chen C, Heng PA, Dou Q, Kozubek M, Lux F, Michálek J, Matula P, Keřkovský M, Kopřivová T, Dostál M, Vybíhal V, Vogelbaum MA, Mitchell JR, Farinhas J, Maldjian JA, Yogananda CGB, Pinho MC, Reddy D, Holcomb J, Wagner BC, Ellingson BM, Cloughesy TF, Raymond C, Oughourlian T, Hagiwara A, Wang C, To MS, Bhardwaj S, Chong C, Agzarian M, Falcão AX, Martins SB, Teixeira BCA, Sprenger F, Menotti D, Lucio DR, LaMontagne P, Marcus D, Wiestler B, Kofler F, Ezhov I, Metz M, Jain R, Lee M, Lui YW, McKinley R, Slotboom J, Radojewski P, Meier R, Wiest R, Murcia D, Fu E, Haas R, Thompson J, Ormond DR, Badve C, Sloan AE, Vadmal V, Waite K, Colen RR, Pei L, Ak M, Srinivasan A, Bapuraj JR, Rao A, Wang N, Yoshiaki O, Moritani T, Turk S, Lee J, Prabhudesai S, Morón F, Mandel J, Kamnitsas K, Glocker B, Dixon LVM, Williams M, Zampakis P, Panagiotopoulos V, Tsiganos P, Alexiou S, Haliassos I, Zacharaki EI, Moustakas K, Kalogeropoulou C, Kardamakis DM, Choi YS, Lee SK, Chang JH, Ahn SS, Luo B, Poisson L, Wen N, Tiwari P, Verma R, Bareja R, Yadav I, Chen J, Kumar N, Smits M, van der Voort SR, Alafandi A, Incekara F, Wijnenga MMJ, Kapsas G, Gahrmann R, Schouten JW, Dubbink HJ, Vincent AJPE, van den Bent MJ, French PJ, Klein S, Yuan Y, Sharma S, Tseng TC, Adabi S, Niclou SP, Keunen O, Hau AC, Vallières M, Fortin D, Lepage M, Landman B, Ramadass K, Xu K, Chotai S, Chambless LB, Mistry A, Thompson RC, Gusev Y, Bhuvaneshwar K, Sayah A, Bencheqroun C, Belouali A, Madhavan S, Booth TC, Chelliah A, Modat M, Shuaib H, Dragos C, Abayazeed A, Kolodziej K, Hill M, Abbassy A, Gamal S, Mekhaimar M, Qayati M, Reyes M, Park JE, Yun J, Kim HS, Mahajan A, Muzi M, Benson S, Beets-Tan RGH, Teuwen J, Herrera-Trujillo A, Trujillo M, Escobar W, Abello A, Bernal J, Gómez J, Choi J, Baek S, Kim Y, Ismael H, Allen B, Buatti JM, Kotrotsou A, Li H, Weiss T, Weller M, Bink A, Pouymayou B, Shaykh HF, Saltz J, Prasanna P, Shrestha S, Mani KM, Payne D, Kurc T, Pelaez E, Franco-Maldonado H, Loayza F, Quevedo S, Guevara P, Torche E, Mendoza C, Vera F, Ríos E, López E, Velastin SA, Ogbole G, Soneye M, Oyekunle D, Odafe-Oyibotha O, Osobu B, Shu'aibu M, Dorcas A, Dako F, Simpson AL, Hamghalam M, Peoples JJ, Hu R, Tran A, Cutler D, Moraes FY, Boss MA, Gimpel J, Veettil DK, Schmidt K, Bialecki B, Marella S, Price C, Cimino L, Apgar C, Shah P, Menze B, Barnholtz-Sloan JS, Martin J, Bakas S. Federated learning enables big data for rare cancer boundary detection. Nat Commun 2022; 13:7346. [PMID: 36470898 PMCID: PMC9722782 DOI: 10.1038/s41467-022-33407-5] [Citation(s) in RCA: 43] [Impact Index Per Article: 21.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2022] [Accepted: 09/16/2022] [Indexed: 12/12/2022] Open
Abstract
Although machine learning (ML) has shown promise across disciplines, out-of-sample generalizability is concerning. This is currently addressed by sharing multi-site data, but such centralization is challenging/infeasible to scale due to various limitations. Federated ML (FL) provides an alternative paradigm for accurate and generalizable ML, by only sharing numerical model updates. Here we present the largest FL study to-date, involving data from 71 sites across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, reporting the largest such dataset in the literature (n = 6, 314). We demonstrate a 33% delineation improvement for the surgically targetable tumor, and 23% for the complete tumor extent, over a publicly trained model. We anticipate our study to: 1) enable more healthcare studies informed by large diverse data, ensuring meaningful results for rare diseases and underrepresented populations, 2) facilitate further analyses for glioblastoma by releasing our consensus model, and 3) demonstrate the FL effectiveness at such scale and task-complexity as a paradigm shift for multi-site collaborations, alleviating the need for data-sharing.
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Affiliation(s)
- Sarthak Pati
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Informatics, Technical University of Munich, Munich, Bavaria, Germany
| | - Ujjwal Baid
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | | | | | | | | | | | | | | | - Christos Davatzikos
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Chiharu Sako
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Satyam Ghodasara
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Michel Bilello
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Suyash Mohan
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Philipp Vollmuth
- Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany
| | - Gianluca Brugnara
- Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany
| | | | - Felix Sahm
- Clinical Cooperation Unit Neuropathology, German Cancer Consortium (DKTK) within the German Cancer Research Center (DKFZ), Heidelberg, Germany
- Department of Neuropathology, Heidelberg University Hospital, Heidelberg, Germany
| | - Klaus Maier-Hein
- Division of Medical Image Computing, German Cancer Research Center, Heidelberg, Germany
- Pattern Analysis and Learning Group, Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany
| | - Maximilian Zenk
- Division of Medical Image Computing, German Cancer Research Center, Heidelberg, Germany
| | - Martin Bendszus
- Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany
| | - Wolfgang Wick
- Clinical Cooperation Unit Neuropathology, German Cancer Consortium (DKTK) within the German Cancer Research Center (DKFZ), Heidelberg, Germany
- Neurology Clinic, Heidelberg University Hospital, Heidelberg, Germany
| | - Evan Calabrese
- Department of Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
| | - Jeffrey Rudie
- Department of Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
| | - Javier Villanueva-Meyer
- Department of Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
| | - Soonmee Cha
- Department of Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
| | - Madhura Ingalhalikar
- Symbiosis Center for Medical Image Analysis, Symbiosis International University, Pune, Maharashtra, India
| | - Manali Jadhav
- Symbiosis Center for Medical Image Analysis, Symbiosis International University, Pune, Maharashtra, India
| | - Umang Pandey
- Symbiosis Center for Medical Image Analysis, Symbiosis International University, Pune, Maharashtra, India
| | - Jitender Saini
- Department of Neuroimaging and Interventional Radiology, National Institute of Mental Health and Neurosciences, Bangalore, Karnataka, India
| | - John Garrett
- Department of Radiology, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Department of Medical Physics, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
| | - Matthew Larson
- Department of Radiology, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
| | - Robert Jeraj
- Department of Radiology, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Department of Medical Physics, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
| | - Stuart Currie
- Leeds Teaching Hospitals Trust, Department of Radiology, Leeds, UK
| | - Russell Frood
- Leeds Teaching Hospitals Trust, Department of Radiology, Leeds, UK
| | - Kavi Fatania
- Leeds Teaching Hospitals Trust, Department of Radiology, Leeds, UK
| | - Raymond Y Huang
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Ken Chang
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
| | | | | | - Josep Puig
- Department of Radiology (IDI), Girona Biomedical Research Institute (IdIBGi), Josep Trueta University Hospital, Girona, Spain
| | - Johannes Trenkler
- Institute of Neuroradiology, Neuromed Campus (NMC), Kepler University Hospital Linz, Linz, Austria
| | - Josef Pichler
- Department of Neurooncology, Neuromed Campus (NMC), Kepler University Hospital Linz, Linz, Austria
| | - Georg Necker
- Institute of Neuroradiology, Neuromed Campus (NMC), Kepler University Hospital Linz, Linz, Austria
| | - Andreas Haunschmidt
- Institute of Neuroradiology, Neuromed Campus (NMC), Kepler University Hospital Linz, Linz, Austria
| | - Stephan Meckel
- Institute of Neuroradiology, Neuromed Campus (NMC), Kepler University Hospital Linz, Linz, Austria
- Institute of Diagnostic and Interventional Neuroradiology, RKH Klinikum Ludwigsburg, Ludwigsburg, Germany
| | - Gaurav Shukla
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA
- Department of Radiation Oncology, Christiana Care Health System, Philadelphia, PA, USA
| | - Spencer Liem
- Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, PA, USA
| | - Gregory S Alexander
- Department of Radiation Oncology, University of Maryland, Baltimore, MD, USA
| | - Joseph Lombardo
- Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, PA, USA
- Department of Radiation Oncology, Sidney Kimmel Cancer Center, Thomas Jefferson University, Philadelphia, PA, USA
| | - Joshua D Palmer
- Department of Radiation Oncology, The James Cancer Hospital and Solove Research Institute, The Ohio State University Comprehensive Cancer Center, Columbus, OH, USA
| | - Adam E Flanders
- Department of Radiology, Sidney Kimmel Cancer Center, Thomas Jefferson University, Philadelphia, PA, USA
| | - Adam P Dicker
- Department of Radiation Oncology, Sidney Kimmel Cancer Center, Thomas Jefferson University, Philadelphia, PA, USA
| | - Haris I Sair
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- The Malone Center for Engineering in Healthcare, The Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Craig K Jones
- The Malone Center for Engineering in Healthcare, The Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Archana Venkataraman
- Department of Electrical and Computer Engineering, Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Meirui Jiang
- The Chinese University of Hong Kong, Hong Kong, China
| | - Tiffany Y So
- The Chinese University of Hong Kong, Hong Kong, China
| | - Cheng Chen
- The Chinese University of Hong Kong, Hong Kong, China
| | | | - Qi Dou
- The Chinese University of Hong Kong, Hong Kong, China
| | - Michal Kozubek
- Centre for Biomedical Image Analysis, Faculty of Informatics, Masaryk University, Brno, Czech Republic
| | - Filip Lux
- Centre for Biomedical Image Analysis, Faculty of Informatics, Masaryk University, Brno, Czech Republic
| | - Jan Michálek
- Centre for Biomedical Image Analysis, Faculty of Informatics, Masaryk University, Brno, Czech Republic
| | - Petr Matula
- Centre for Biomedical Image Analysis, Faculty of Informatics, Masaryk University, Brno, Czech Republic
| | - Miloš Keřkovský
- Department of Radiology and Nuclear Medicine, Faculty of Medicine, Masaryk University, Brno and University Hospital Brno, Brno, Czech Republic
| | - Tereza Kopřivová
- Department of Radiology and Nuclear Medicine, Faculty of Medicine, Masaryk University, Brno and University Hospital Brno, Brno, Czech Republic
| | - Marek Dostál
- Department of Radiology and Nuclear Medicine, Faculty of Medicine, Masaryk University, Brno and University Hospital Brno, Brno, Czech Republic
- Department of Biophysics, Faculty of Medicine, Masaryk University, Brno, Czech Republic
| | - Václav Vybíhal
- Department of Neurosurgery, Faculty of Medicine, Masaryk University, Brno, and University Hospital and Czech Republic, Brno, Czech Republic
| | - Michael A Vogelbaum
- Department of Neuro Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
| | - J Ross Mitchell
- University of Alberta, Edmonton, AB, Canada
- Alberta Machine Intelligence Institute, Edmonton, AB, Canada
| | - Joaquim Farinhas
- Department of Radiology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
| | | | | | - Marco C Pinho
- University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Divya Reddy
- University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - James Holcomb
- University of Texas Southwestern Medical Center, Dallas, TX, USA
| | | | - Benjamin M Ellingson
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
- UCLA Neuro-Oncology Program, Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CaA, USA
| | - Timothy F Cloughesy
- UCLA Neuro-Oncology Program, Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CaA, USA
| | - Catalina Raymond
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Talia Oughourlian
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Akifumi Hagiwara
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Chencai Wang
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Minh-Son To
- College of Medicine and Public Health, Flinders University, Bedford Park, SA, Australia
- Division of Surgery and Perioperative Medicine, Flinders Medical Centre, Bedford Park, SA, Australia
| | - Sargam Bhardwaj
- College of Medicine and Public Health, Flinders University, Bedford Park, SA, Australia
| | - Chee Chong
- South Australia Medical Imaging, Flinders Medical Centre, Bedford Park, SA, Australia
| | - Marc Agzarian
- South Australia Medical Imaging, Flinders Medical Centre, Bedford Park, SA, Australia
- Department of Neurology, Baylor College of Medicine, Houston, TX, USA
| | | | | | - Bernardo C A Teixeira
- Instituto de Neurologia de Curitiba, Curitiba, Paraná, Brazil
- Department of Radiology, Hospital de Clínicas da Universidade Federal do Paraná, Curitiba, Paraná, Brazil
| | - Flávia Sprenger
- Department of Radiology, Hospital de Clínicas da Universidade Federal do Paraná, Curitiba, Paraná, Brazil
| | - David Menotti
- Department of Informatics, Universidade Federal do Paraná, Curitiba, Paraná, Brazil
| | - Diego R Lucio
- Department of Informatics, Universidade Federal do Paraná, Curitiba, Paraná, Brazil
| | - Pamela LaMontagne
- Department of Radiology, Washington University in St. Louis, St. Louis, MO, USA
| | - Daniel Marcus
- Department of Radiology, Washington University in St. Louis, St. Louis, MO, USA
| | - Benedikt Wiestler
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- TranslaTUM (Zentralinstitut für translationale Krebsforschung der Technischen Universität München), Klinikum rechts der Isar, Munich, Germany
| | - Florian Kofler
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- TranslaTUM (Zentralinstitut für translationale Krebsforschung der Technischen Universität München), Klinikum rechts der Isar, Munich, Germany
- Image-Based Biomedical Modeling, Department of Informatics, Technical University of Munich, Munich, Germany
| | - Ivan Ezhov
- Department of Informatics, Technical University of Munich, Munich, Bavaria, Germany
- TranslaTUM (Zentralinstitut für translationale Krebsforschung der Technischen Universität München), Klinikum rechts der Isar, Munich, Germany
- Image-Based Biomedical Modeling, Department of Informatics, Technical University of Munich, Munich, Germany
| | - Marie Metz
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Rajan Jain
- Department of Radiology, NYU Grossman School of Medicine, New York, NY, USA
- Department of Neurosurgery, NYU Grossman School of Medicine, New York, NY, USA
| | - Matthew Lee
- Department of Radiology, NYU Grossman School of Medicine, New York, NY, USA
| | - Yvonne W Lui
- Department of Radiology, NYU Grossman School of Medicine, New York, NY, USA
| | - Richard McKinley
- Support Center for Advanced Neuroimaging, University Institute of Diagnostic and Interventional Neuroradiology, University Hospital Bern, Inselspital, University of Bern, Bern, Switzerland
| | - Johannes Slotboom
- Support Center for Advanced Neuroimaging, University Institute of Diagnostic and Interventional Neuroradiology, University Hospital Bern, Inselspital, University of Bern, Bern, Switzerland
| | - Piotr Radojewski
- Support Center for Advanced Neuroimaging, University Institute of Diagnostic and Interventional Neuroradiology, University Hospital Bern, Inselspital, University of Bern, Bern, Switzerland
| | - Raphael Meier
- Support Center for Advanced Neuroimaging, University Institute of Diagnostic and Interventional Neuroradiology, University Hospital Bern, Inselspital, University of Bern, Bern, Switzerland
| | - Roland Wiest
- Support Center for Advanced Neuroimaging, University Institute of Diagnostic and Interventional Neuroradiology, University Hospital Bern, Inselspital, University of Bern, Bern, Switzerland
| | - Derrick Murcia
- Department of Neurosurgery, Anschutz Medical Campus, University of Colorado, Aurora, CO, USA
| | - Eric Fu
- Department of Neurosurgery, Anschutz Medical Campus, University of Colorado, Aurora, CO, USA
| | - Rourke Haas
- Department of Neurosurgery, Anschutz Medical Campus, University of Colorado, Aurora, CO, USA
| | - John Thompson
- Department of Neurosurgery, Anschutz Medical Campus, University of Colorado, Aurora, CO, USA
| | - David Ryan Ormond
- Department of Neurosurgery, Anschutz Medical Campus, University of Colorado, Aurora, CO, USA
| | - Chaitra Badve
- Department of Radiology, University Hospitals Cleveland, Cleveland, OH, USA
| | - Andrew E Sloan
- Department of Neurological Surgery, University Hospitals-Seidman Cancer Center, Cleveland, OH, USA
- Case Comprehensive Cancer Center, Cleveland, OH, USA
- Department of Neurosurgery, Case Western Reserve University School of Medicine, Cleveland, OH, USA
| | - Vachan Vadmal
- Department of Neurosurgery, Case Western Reserve University School of Medicine, Cleveland, OH, USA
| | - Kristin Waite
- National Cancer Institute, National Institute of Health, Division of Cancer Epidemiology and Genetics, Bethesda, MD, USA
| | - Rivka R Colen
- Department of Radiology, Neuroradiology Division, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Diagnostic Radiology, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Linmin Pei
- University of Pittsburgh Medical Center, Pittsburgh, PA, USA
| | - Murat Ak
- Department of Radiology, Neuroradiology Division, University of Pittsburgh, Pittsburgh, PA, USA
| | - Ashok Srinivasan
- Department of Neuroradiology, University of Michigan, Ann Arbor, MI, USA
| | - J Rajiv Bapuraj
- Department of Neuroradiology, University of Michigan, Ann Arbor, MI, USA
| | - Arvind Rao
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Nicholas Wang
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Ota Yoshiaki
- Department of Neuroradiology, University of Michigan, Ann Arbor, MI, USA
| | - Toshio Moritani
- Department of Neuroradiology, University of Michigan, Ann Arbor, MI, USA
| | - Sevcan Turk
- Department of Neuroradiology, University of Michigan, Ann Arbor, MI, USA
| | - Joonsang Lee
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Snehal Prabhudesai
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Fanny Morón
- Department of Radiology, Baylor College of Medicine, Houston, TX, USA
| | - Jacob Mandel
- Department of Neurology, Baylor College of Medicine, Houston, TX, USA
| | - Konstantinos Kamnitsas
- Department of Computing, Imperial College London, London, UK
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, UK
| | - Ben Glocker
- Department of Computing, Imperial College London, London, UK
| | - Luke V M Dixon
- Department of Radiology, Imperial College NHS Healthcare Trust, London, UK
| | - Matthew Williams
- Computational Oncology Group, Institute for Global Health Innovation, Imperial College London, London, UK
| | - Peter Zampakis
- Department of NeuroRadiology, University of Patras, Patras, Greece
| | | | - Panagiotis Tsiganos
- Clinical Radiology Laboratory, Department of Medicine, University of Patras, Patras, Greece
| | - Sotiris Alexiou
- Department of Electrical and Computer Engineering, University of Patras, Patras, Greece
| | - Ilias Haliassos
- Department of Neuro-Oncology, University of Patras, Patras, Greece
| | - Evangelia I Zacharaki
- Department of Electrical and Computer Engineering, University of Patras, Patras, Greece
| | | | | | | | | | | | | | - Sung Soo Ahn
- Yonsei University College of Medicine, Seoul, Korea
| | - Bing Luo
- Department of Radiation Oncology, Henry Ford Health System, Detroit, MI, USA
| | - Laila Poisson
- Public Health Sciences, Henry Ford Health System, Detroit, MI, USA
| | - Ning Wen
- Department of Radiation Oncology, Henry Ford Health System, Detroit, MI, USA
- SJTU-Ruijin-UIH Institute for Medical Imaging Technology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 200025, Shanghai, China
| | | | - Ruchika Verma
- Alberta Machine Intelligence Institute, Edmonton, AB, Canada
- Case Western Reserve University, Cleveland, OH, USA
| | - Rohan Bareja
- Case Western Reserve University, Cleveland, OH, USA
| | - Ipsa Yadav
- Case Western Reserve University, Cleveland, OH, USA
| | | | - Neeraj Kumar
- University of Alberta, Edmonton, AB, Canada
- Alberta Machine Intelligence Institute, Edmonton, AB, Canada
| | - Marion Smits
- Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Sebastian R van der Voort
- Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Ahmed Alafandi
- Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Fatih Incekara
- Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
- Department of Neurosurgery, Brain Tumor Center, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Maarten M J Wijnenga
- Department of Neurology, Brain Tumor Center, Erasmus MC Cancer Institute, Rotterdam, Netherlands
| | - Georgios Kapsas
- Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Renske Gahrmann
- Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Joost W Schouten
- Department of Neurosurgery, Brain Tumor Center, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Hendrikus J Dubbink
- Department of Pathology, Brain Tumor Center, Erasmus MC Cancer Institute, Rotterdam, Netherlands
| | - Arnaud J P E Vincent
- Department of Neurosurgery, Brain Tumor Center, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Martin J van den Bent
- Department of Neurology, Brain Tumor Center, Erasmus MC Cancer Institute, Rotterdam, Netherlands
| | - Pim J French
- Department of Neurology, Brain Tumor Center, Erasmus MC Cancer Institute, Rotterdam, Netherlands
| | - Stefan Klein
- Biomedical Imaging Group Rotterdam, Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Yading Yuan
- Department of Radiation Oncology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Sonam Sharma
- Department of Radiation Oncology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Tzu-Chi Tseng
- Department of Radiation Oncology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Saba Adabi
- Department of Radiation Oncology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Simone P Niclou
- NORLUX Neuro-Oncology Laboratory, Department of Cancer Research, Luxembourg Institute of Health, Luxembourg, Luxembourg
| | - Olivier Keunen
- Translation Radiomics, Department of Cancer Research, Luxembourg Institute of Health, Luxembourg, Luxembourg
| | - Ann-Christin Hau
- NORLUX Neuro-Oncology Laboratory, Department of Cancer Research, Luxembourg Institute of Health, Luxembourg, Luxembourg
- Luxembourg Center of Neuropathology, Laboratoire National De Santé, Luxembourg, Luxembourg
| | - Martin Vallières
- Department of Computer Science, Université de Sherbrooke, Sherbrooke, QC, Canada
- Centre de Recherche du Centre Hospitalière Universitaire de Sherbrooke, Sherbrooke, QC, Canada
| | - David Fortin
- Centre de Recherche du Centre Hospitalière Universitaire de Sherbrooke, Sherbrooke, QC, Canada
- Division of Neurosurgery and Neuro-Oncology, Faculty of Medicine and Health Science, Université de Sherbrooke, Sherbrooke, QC, Canada
| | - Martin Lepage
- Centre de Recherche du Centre Hospitalière Universitaire de Sherbrooke, Sherbrooke, QC, Canada
- Department of Nuclear Medicine and Radiobiology, Sherbrooke Molecular Imaging Centre, Université de Sherbrooke, Sherbrooke, QC, Canada
| | - Bennett Landman
- Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, USA
| | - Karthik Ramadass
- Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, USA
| | - Kaiwen Xu
- Department of Computer Science, Vanderbilt University, Nashville, TN, USA
| | - Silky Chotai
- Department of Neurosurgery, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Lola B Chambless
- Department of Neurosurgery, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Akshitkumar Mistry
- Department of Neurosurgery, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Reid C Thompson
- Department of Neurosurgery, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Yuriy Gusev
- Innovation Center for Biomedical Informatics (ICBI), Georgetown University, Washington, DC, USA
| | - Krithika Bhuvaneshwar
- Innovation Center for Biomedical Informatics (ICBI), Georgetown University, Washington, DC, USA
| | - Anousheh Sayah
- Division of Neuroradiology & Neurointerventional Radiology, Department of Radiology, MedStar Georgetown University Hospital, Washington, DC, USA
| | - Camelia Bencheqroun
- Innovation Center for Biomedical Informatics (ICBI), Georgetown University, Washington, DC, USA
| | - Anas Belouali
- Innovation Center for Biomedical Informatics (ICBI), Georgetown University, Washington, DC, USA
| | - Subha Madhavan
- Innovation Center for Biomedical Informatics (ICBI), Georgetown University, Washington, DC, USA
| | - Thomas C Booth
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
- Department of Neuroradiology, Ruskin Wing, King's College Hospital NHS Foundation Trust, London, UK
| | - Alysha Chelliah
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
| | - Marc Modat
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
| | - Haris Shuaib
- Stoke Mandeville Hospital, Mandeville Road, Aylesbury, UK
- Department of Biomedical and Molecular Sciences, Queen's University, Kingston, ON, Canada
| | - Carmen Dragos
- Stoke Mandeville Hospital, Mandeville Road, Aylesbury, UK
| | | | | | | | | | - Shady Gamal
- University of Cairo School of Medicine, Giza, Egypt
| | | | | | | | - Ji Eun Park
- Department of Radiology, Asan Medical Center, Seoul, South Korea
| | - Jihye Yun
- Department of Radiology, Asan Medical Center, Seoul, South Korea
| | - Ho Sung Kim
- Department of Radiology, Asan Medical Center, Seoul, South Korea
| | - Abhishek Mahajan
- The Clatterbridge Cancer Centre NHS Foundation Trust Pembroke Place, Liverpool, UK
| | - Mark Muzi
- Department of Radiology, University of Washington, Seattle, WA, USA
| | - Sean Benson
- Netherlands Cancer Institute, Amsterdam, Netherlands
| | - Regina G H Beets-Tan
- Department of Radiology, Netherlands Cancer Institute, Amsterdam, Netherlands
- GROW School of Oncology and Developmental Biology, Maastricht, Netherlands
| | - Jonas Teuwen
- Netherlands Cancer Institute, Amsterdam, Netherlands
| | | | | | - William Escobar
- Clínica Imbanaco Grupo Quirón Salud, Cali, Colombia
- Universidad del Valle, Cali, Colombia
| | | | - Jose Bernal
- Universidad del Valle, Cali, Colombia
- The University of Edinburgh, Edinburgh, UK
| | | | - Joseph Choi
- Department of Industrial and Systems Engineering, University of Iowa, Iowa, USA
| | - Stephen Baek
- Department of Industrial and Systems Engineering, Department of Radiation Oncology, University of Iowa, Iowa City, IA, USA
| | - Yusung Kim
- Department of Radiation Oncology, University of Iowa, Iowa City, IA, USA
| | - Heba Ismael
- Department of Radiation Oncology, University of Iowa, Iowa City, IA, USA
| | - Bryan Allen
- Department of Radiation Oncology, University of Iowa, Iowa City, IA, USA
| | - John M Buatti
- Department of Radiation Oncology, University of Iowa, Iowa City, IA, USA
| | | | - Hongwei Li
- Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland
| | - Tobias Weiss
- Department of Neurology, Clinical Neuroscience Center, University Hospital Zurich and University of Zurich, Zurich, Switzerland
| | - Michael Weller
- Department of Neurology, Clinical Neuroscience Center, University Hospital Zurich and University of Zurich, Zurich, Switzerland
| | - Andrea Bink
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich and University of Zurich, Zurich, Switzerland
| | - Bertrand Pouymayou
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich and University of Zurich, Zurich, Switzerland
| | | | - Joel Saltz
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, New York, USA
| | - Prateek Prasanna
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, New York, USA
| | - Sampurna Shrestha
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, New York, USA
| | - Kartik M Mani
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, New York, USA
- Department of Radiation Oncology, Stony Brook University, Stony Brook, NY, USA
| | - David Payne
- Department of Radiology, Stony Brook University, Stony Brook, NY, USA
| | - Tahsin Kurc
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, New York, USA
- Scientific Data Group, Oak Ridge National Laboratory, Oak Ridge, TN, USA
| | - Enrique Pelaez
- Escuela Superior Politecnica del Litoral, Guayaquil, Guayas, Ecuador
| | | | - Francis Loayza
- Escuela Superior Politecnica del Litoral, Guayaquil, Guayas, Ecuador
| | | | | | | | | | - Franco Vera
- Universidad de Concepción, Concepción, Biobío, Chile
| | - Elvis Ríos
- Universidad de Concepción, Concepción, Biobío, Chile
| | - Eduardo López
- Universidad de Concepción, Concepción, Biobío, Chile
| | - Sergio A Velastin
- School of Electronic Engineering and Computer Science, Queen Mary University of London, London, UK
| | - Godwin Ogbole
- Department of Radiology, University College Hospital Ibadan, Oyo, Nigeria
| | - Mayowa Soneye
- Department of Radiology, University College Hospital Ibadan, Oyo, Nigeria
| | - Dotun Oyekunle
- Department of Radiology, University College Hospital Ibadan, Oyo, Nigeria
| | | | - Babatunde Osobu
- Department of Radiology, University College Hospital Ibadan, Oyo, Nigeria
| | - Mustapha Shu'aibu
- Department of Radiology, Muhammad Abdullahi Wase Teaching Hospital, Kano, Nigeria
| | - Adeleye Dorcas
- Department of Radiology, Obafemi Awolowo University Ile-Ife, Ile-Ife, Osun, Nigeria
| | - Farouk Dako
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Center for Global Health, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Amber L Simpson
- Department of Biomedical and Molecular Sciences, Queen's University, Kingston, ON, Canada
- School of Computing, Queen's University, Kingston, ON, Canada
| | - Mohammad Hamghalam
- School of Computing, Queen's University, Kingston, ON, Canada
- Department of Electrical Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran
| | - Jacob J Peoples
- School of Computing, Queen's University, Kingston, ON, Canada
| | - Ricky Hu
- School of Computing, Queen's University, Kingston, ON, Canada
| | - Anh Tran
- School of Computing, Queen's University, Kingston, ON, Canada
| | - Danielle Cutler
- The Faculty of Arts & Sciences, Queen's University, Kingston, ON, Canada
| | - Fabio Y Moraes
- Department of Oncology, Queen's University, Kingston, ON, Canada
| | - Michael A Boss
- Center for Research and Innovation, American College of Radiology, Philadelphia, PA, USA
| | - James Gimpel
- Center for Research and Innovation, American College of Radiology, Philadelphia, PA, USA
| | - Deepak Kattil Veettil
- Center for Research and Innovation, American College of Radiology, Philadelphia, PA, USA
| | - Kendall Schmidt
- Data Science Institute, American College of Radiology, Reston, VA, USA
| | - Brian Bialecki
- Data Science Institute, American College of Radiology, Reston, VA, USA
| | - Sailaja Marella
- Center for Research and Innovation, American College of Radiology, Philadelphia, PA, USA
| | - Cynthia Price
- Center for Research and Innovation, American College of Radiology, Philadelphia, PA, USA
| | - Lisa Cimino
- Center for Research and Innovation, American College of Radiology, Philadelphia, PA, USA
| | - Charles Apgar
- Center for Research and Innovation, American College of Radiology, Philadelphia, PA, USA
| | | | - Bjoern Menze
- Department of Informatics, Technical University of Munich, Munich, Bavaria, Germany
- Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland
| | - Jill S Barnholtz-Sloan
- National Cancer Institute, National Institute of Health, Division of Cancer Epidemiology and Genetics, Bethesda, MD, USA
- Center for Biomedical Informatics and Information Technology, National Cancer Institute (NCI), National Institute of Health, Bethesda, MD, USA
| | | | - Spyridon Bakas
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA.
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
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9
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Ak M, Demır MB. Disrupted redox balance in utero-placenteal junction may be the main culprit in the occurrence of abruptio placenta. Eur Rev Med Pharmacol Sci 2022; 26:8887-8892. [PMID: 36524508 DOI: 10.26355/eurrev_202212_30562] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
OBJECTIVE To determine the oxidant/antioxidant balance and proinflammatory status in amniotic fluids collected during cesarean section of patients diagnosed with abruptio placenta. PATIENTS AND METHODS Twenty-five patients diagnosed with ablatio placenta with intact membranes who went to emergency cesarean section were included in the study. A diagnosis of AP was made in those who had at least one of the following criteria or, in suspicious cases, two findings. (i) Antepartum hemorrhage starting after 20 weeks of gestation, (ii) presence of retroplacental hematoma on ultrasonography, (iii) severe fetal distress or death, (iv) localized or diffuse uterine tenderness or pain. The control group consisted of 25 patients who presented for delivery, who were not diagnosed with AP, and whose membranes were intact. NF-κB, total oxidant capacity (TOC), total antioxidant capacity (TAC), and oxidative stress index (TOC/TAC=OSI) levels were measured in amniotic fluids collected during cesarean section from both groups. RESULTS Amniotic fluid TAS values of the AP group were significantly lower than the healthy controls (1.14±0.33 vs. 9.05.±3.40, p<0.01). Amniotic fluid TOS values were significantly increased in the AP group (36.1±8.10 vs. 11.4±2.77, p<0.02). OSI values were significantly higher in the AP group (31.6±9.03 vs. 1.26±0.02, p<0.01). Amniotic fluid NF-κB expression of the AP group was approximately 5 times higher than the control group (10.4±2.56 ng/mL vs. 1.86±0.30 ng/mL, p<0.01). High blood pressure and smoking history were significantly higher in the AP group. Gestational age and fetal birth weight of the AP group were lower than the control group. CONCLUSIONS Since the increase in amniotic fluid oxidant capacity and proinflammatory cytokine synthesis cannot be neutralized by the antioxidant system, hypoxic cell damage may lead to premature separation of the placenta.
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Affiliation(s)
- M Ak
- Department of Obstetrics and Gynecology, Kayseri City Training and Research Hospital, Kayseri, Turkey.
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10
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Akbari H, Mohan S, Garcia J, Kazerooni AF, Sako C, Bakas S, Bilello M, Bagley S, Baid U, Brem S, Lustig R, Nasrallah M, O'Rourke D, Barnholtz-Sloan J, Badve C, Sloan A, Jain R, Lee M, Chakravarti A, Palmer J, Taylor W, Cepeda S, Dicker A, Flanders A, Shi W, Shukla G, Calabrese E, Rudie J, Villanueva-Meyer J, LaMontagne P, Marcus D, Balana C, Capellades J, Puig J, Ak M, Colen R, Ahn SS, Chang JH, Choi YS, Lee SK, Griffith B, Poisson L, Rogers L, Booth T, Mahajan A, Wiestler B, Davatzikos C. NIMG-67. MULTI-PARAMETRIC MRI-BASED MACHINE LEARNING ANALYSIS FOR PREDICTION OF NEOPLASTIC INFILTRATION AND RECURRENCE IN PATIENTS WITH GLIOBLASTOMA: UPDATES FROM THE MULTI-INSTITUTIONAL RESPOND CONSORTIUM. Neuro Oncol 2022. [PMCID: PMC9661087 DOI: 10.1093/neuonc/noac209.685] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
Abstract
PURPOSE
Glioblastoma is extremely infiltrative with malignant cells extending beyond the enhancing rim where recurrence inevitably occurs, despite aggressive multimodal therapy. We hypothesize that important characteristics of peritumoral tissue heterogeneity captured and analyzed by multi-parametric MRI and artificial intelligence (AI) methods are generalizable in the updated multi-institutional ReSPOND (Radiomics Signatures for PrecisiON Diagnostics) consortium and predictive of neoplastic infiltration and future recurrence.
METHODS
We used the most recent update of the ReSPOND consortium to evaluate and further refine generalizability of our methods with different scanners and acquisition settings. 179 de novo glioblastoma patients with available T1, T1Gd, T2, T2-FLAIR, and ADC sequences at pre-resection baseline and after complete resection with subsequent pathology-confirmed recurrence were included. To establish generalizability of the predictive models, training and testing of the refined AI model was performed through Leave-One-Institution-Out-Cross-Validation schema. The multi-institutional cohort consisted of the Hospital of the University of Pennsylvania (UPenn, 124), Case Western Reserve University/University Hospitals (CWRU/UH, 27), New York University (NYU, 13), Ohio State University (OSU, 13), and University Hospital Río Hortega (RH, 2). Features extracted from pre-resection MRI were used to build the model predicting the spatial pattern of subsequent tumor recurrence. These predictions were evaluated against regions of pathology-confirmed post-resection recurrence.
RESULTS
Our model predicted the locations that later harbored tumor recurrence with overall odds ratio (99% CI)/AUC (99% CI), 12.0(11.8-12.2)/0.80(0.76-0.85), and per institute, CWRU/UH, 11.0(10.7-11.3)/0.80 (0.64-0.97); NYU, 7.0(6.7-7.3)/0.78(0.56-1.00); OSU, 18.3(17.5-19.1)/0.83(0.54-1.00); RH, 40.0(35.3-45.5)/0.93(0.00-1.00); UPenn, 8.00(7.7-8.3)/0.80(0.75-0.84).
CONCLUSION
This study provides extensive multi-institutional validated evidence that machine learning tools can identify peritumoral neoplastic infiltration and predict location of future recurrence, by decrypting the MRI signal heterogeneity in peritumoral tissue. Our analyses leveraged the unique dataset of the ReSPOND consortium, which aims to develop and validate AI-based biomarkers for individualized prediction and prognostication and establish generalizability in a multi-institutional setting.
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Affiliation(s)
- Hamed Akbari
- University of Pennsylvania , Philadelphia, PA , USA
| | - Suyash Mohan
- Center for Biomedical Image Computing and Analytics, Department of Radiology, Perelman School of Medicine, University of Pennsylvania , Philadelphia, PA , USA
| | - Jose Garcia
- University of Pennsylvania , Philadelphia , USA
| | | | - Chiharu Sako
- Center for Biomedical Image Computing and Analytics and Department of Radiology, Perelman School of Medicine, University of Pennsylvania , Philadelphia , USA
| | - Spyridon Bakas
- Center for Biomedical Image Computing and Analytics, Department of Radiology, and Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania , Philadelphia, PA , USA
| | | | - Stephen Bagley
- Hospital of the University of Pennsylvania , Philadelphia, PA , USA
| | - Ujjwal Baid
- University of Pennsylvania , Philadelphia , USA
| | - Steven Brem
- Hospital of the University of Pennsylvania , Philadelphia , USA
| | - Robert Lustig
- Hospital of the University of Pennsylvania , Philadelphia , USA
| | - MacLean Nasrallah
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania , Philadelphia, PA , USA
| | - Donald O'Rourke
- Department of Neurosurgery, Perelman School of Medicine, University of Pennsylvania , Philadelphia , USA
| | - Jill Barnholtz-Sloan
- Center for Biomedical Informatics and Information Technology and Division of Cancer Epidemiology and Genetics, National Cancer Institute , Bethesda, MD , USA
| | - Chaitra Badve
- Department of Radiology, Case Western Reserve University and University Hospitals Cleveland Medical Center , Cleveland , USA
| | - Andrew Sloan
- Department of Pathology and Department of Neurosurgery, Case Western Reserve University and University Hospitals Cleveland Medical Center; Seidman Cancer Center and Case Comprehensive Cancer Center , Cleveland , USA
| | - Rajan Jain
- Department of Radiology, NYU Grossman School of Medicine , New York, NY , USA
| | - Matthew Lee
- Department of Radiology, NYU Grossman School of Medicine , New York, NY , USA
| | - Arnab Chakravarti
- Department of Radiation Oncology, Ohio State University Wexner Medical Center , Columbus, OH , USA
| | - Joshua Palmer
- The Department of Radiation Oncology, The James Cancer Hospital, Ohio State University Wexner Medical Center , Columbus, OH , USA
| | | | | | - Adam Dicker
- Department of Radiation Oncology, Sidney Kimmel Cancer Center, Thomas Jefferson University , Philadelphia, PA , USA
| | - Adam Flanders
- Department of Radiology, Sidney Kimmel Cancer Center, Thomas Jefferson University , Philadelphia, PA , USA
| | - Wenyin Shi
- Department of Radiation Oncology, Thomas Jefferson University Hospital , Philadelphia, PA , USA
| | - Gaurav Shukla
- Department of Radiation Oncology, Christiana Care Health System , Philadelphia , USA
| | - Evan Calabrese
- University of California, San Francisco , San Francisco , USA
| | - Jeffrey Rudie
- University of California, San Francisco , San Francisco , USA
| | | | | | - Daniel Marcus
- Department of Radiology, Washington University School of Medicine , St. Louis, MO , USA
| | - Carmen Balana
- Medical Oncology Department, Catalan Institute of Oncology , Barcelona , Spain
| | - Jaume Capellades
- Department of Medical Imaging Consorci MAR Parc de Salut , Barcelona , Spain
| | - Josep Puig
- Department of Radiology (IDI) and Girona Biomedical Research Institute (IDIBGI), Hospital Universitari de Girona Dr Josep Trueta, , Girona , Spain
| | - Murat Ak
- University of Pittsburgh , Pittsburgh , USA
| | - Rivka Colen
- Department of Radiology, University of Pittsburgh , Pittsburgh, PA , USA
| | - Sung Soo Ahn
- Yonsei University College of Medicine , Seoul , Republic of Korea
| | - Jong Hee Chang
- Severance Hospital, Yonsei University College of Medicine , Seoul , Republic of Korea
| | - Yoon Seong Choi
- Department of Radiology, Yonsei University College of Medicine , Seoul , Republic of Korea
| | - Seung-Koo Lee
- Yonsei University College of Medicine , Seoul , Republic of Korea
| | - Brent Griffith
- Department of Radiology, Henry Ford Health System , Detroit, MI , USA
| | - Laila Poisson
- Department of Public Health Sciences, Center for Bioinformatics, Henry Ford Health System , Detroit, MI , USA
| | - Lisa Rogers
- Department of Neurosurgery, Henry Ford Health , Detroit , USA
| | - Thomas Booth
- School of Biomedical Engineering and Imaging Sciences, King’s College , London , United Kingdom
| | - Abhishek Mahajan
- Department of Imaging, The Clatterbridge Cancer Centre NHS Foundation Trust , London , United Kingdom
| | - Benedikt Wiestler
- Department of Neuroradiology, Technical University of Munich , Munich , Germany
| | - Christos Davatzikos
- Center for Biomedical Image Computing and Analytics and Department of Radiology, Perelman School of Medicine, University of Pennsylvania , Philadelphia, PA , USA
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11
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Akbari H, Bakas S, Sako C, Kazerooni AF, Villanueva-Meyer J, Garcia J, Bagley S, Baid U, Bilello M, Brem S, Lustig R, Mohan S, Nasrallah M, O'Rourke D, Calabrese E, Rudie J, LaMontagne P, Marcus D, Balana C, Capellades J, Puig J, Barnholtz-Sloan J, Badve C, Sloan A, Ak M, Colen R, Ahn SS, Chang JH, Choi YS, Lee SK, Dicker A, Flanders A, Shi W, Shukla G, Griffith B, Poisson L, Rogers L, Booth T, Jain R, Lee M, Mahajan A, Chakravarti A, Palmer J, Taylor W, Cepeda S, Wiestler B, Davatzikos C. NIMG-33. PROGNOSTIC STRATIFICATION OF DE NOVO GLIOBLASTOMA PATIENTS ACROSS 22 GEOGRAPHICALLY DISTINCT INSTITUTIONS: UPDATES FROM THE RESPOND CONSORTIUM. Neuro Oncol 2022. [PMCID: PMC9661084 DOI: 10.1093/neuonc/noac209.651] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
Abstract
PURPOSE
Glioblastoma, IDH-wildtype, is the most common primary malignant adult brain tumor with median overall survival (OS) of ~14 months, with little improvement over the last 20 years. We hypothesize that AI-based integration of quantitative tumor characteristics, independent of acquisition protocol and equipment, can reveal accurate generalizable prognostic stratification. We seek an AI-based OS predictor using routine clinically acquired MRI sequences, quantitatively evaluated across institutions of the ReSPOND (Radiomics Signatures for PrecisiON Diagnostics) consortium.
METHODS
We identified a retrospective cohort of 2,293 diffuse glioma (IDH-wildtype/-NOS/-NEC) patients from 22 geographically distinct institutions across 3 continents, with preoperative structural MRI scans. The entire tumor burden was automatically segmented into 3 sub-compartments, i.e., enhancing, necrotic, peritumoral T2-FLAIR abnormality. We developed our AI predictor by multivariate integration of i)patient age, ii)tumor sub-compartment volume normalized to brain volume, iii)spatial distribution characteristics (tumor location, distance to the ventricles, and laterality), and iv)morphologic descriptors (major axes’ length, axes’ ratio, extent, and number of tumors). The AI predictor returns a continuous value between 0-1, defining short-, intermediate-, and long-survivors based on thresholds on the 25th and 75th percentiles. Leave-One-Site-Out-Cross-Validation was used to assess the generalizability of our stratification. Kaplan-Meier survival curves were computed for OS analysis and evaluated by a Cox proportional hazards model for statistical significance and hazard ratios.
RESULTS
Survival analysis yielded a hazard ratio of 2.07 (95%CI, 2.06-2.08, p-value= 4.8e-102) for patient stratification into short-, intermediate-, and long-survivors. Pearson correlation between the predicted and actual OS yielded an R= 0.49.
CONCLUSION
Multivariate integration of visually quantified tumor characteristics, agnostic to acquisition protocol/equipment, yields an accurate OS surrogate index. Validation of our AI model in the largest centralized glioblastoma imaging dataset, from the ReSPOND consortium, supports its generalizability across diverse patient populations and acquisition settings, potentially contributing to equitable improvements of personalized patient care.
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Affiliation(s)
- Hamed Akbari
- University of Pennsylvania , Philadelphia, PA , USA
| | - Spyridon Bakas
- Center for Biomedical Image Computing and Analytics, Department of Radiology, and Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania , Philadelphia, PA , USA
| | - Chiharu Sako
- Center for Biomedical Image Computing and Analytics and Department of Radiology, Perelman School of Medicine, University of Pennsylvania , Philadelphia , USA
| | | | | | - Jose Garcia
- University of Pennsylvania , Philadelphia , USA
| | - Stephen Bagley
- Hospital of the University of Pennsylvania , Philadelphia, PA , USA
| | - Ujjwal Baid
- University of Pennsylvania , Philadelphia , USA
| | | | - Steven Brem
- Hospital of the University of Pennsylvania , Philadelphia , USA
| | - Robert Lustig
- Hospital of the University of Pennsylvania , Philadelphia , USA
| | - Suyash Mohan
- Center for Biomedical Image Computing and Analytics, Department of Radiology, Perelman School of Medicine, University of Pennsylvania , Philadelphia, PA , USA
| | - MacLean Nasrallah
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania , Philadelphia, PA , USA
| | - Donald O'Rourke
- Department of Neurosurgery, Perelman School of Medicine, University of Pennsylvania , Philadelphia , USA
| | - Evan Calabrese
- University of California, San Francisco , San Francisco , USA
| | - Jeffrey Rudie
- University of California, San Francisco , San Francisco , USA
| | | | - Daniel Marcus
- Department of Radiology, Washington University School of Medicine , St. Louis, MO , USA
| | - Carmen Balana
- Medical Oncology Department, Catalan Institute of Oncology , Barcelona , Spain
| | - Jaume Capellades
- Department of Medical Imaging Consorci MAR Parc de Salut , Barcelona , Spain
| | - Josep Puig
- Department of Radiology (IDI) and Girona Biomedical Research Institute (IDIBGI), Hospital Universitari de Girona Dr Josep Trueta, , Girona , Spain
| | - Jill Barnholtz-Sloan
- Center for Biomedical Informatics and Information Technology and Division of Cancer Epidemiology and Genetics, National Cancer Institute , Bethesda, MD , USA
| | - Chaitra Badve
- Department of Radiology, Case Western Reserve University and University Hospitals Cleveland Medical Center , Cleveland , USA
| | - Andrew Sloan
- Department of Pathology and Department of Neurosurgery, Case Western Reserve University and University Hospitals Cleveland Medical Center; Seidman Cancer Center and Case Comprehensive Cancer Center , Cleveland , USA
| | - Murat Ak
- University of Pittsburgh , Pittsburgh , USA
| | - Rivka Colen
- Department of Radiology, University of Pittsburgh , Pittsburgh, PA , USA
| | - Sung Soo Ahn
- Yonsei University College of Medicine , Seoul , Republic of Korea
| | - Jong Hee Chang
- Severance Hospital, Yonsei University College of Medicine , Seoul , Republic of Korea
| | - Yoon Seong Choi
- Department of Radiology, Yonsei University College of Medicine , Seoul , Republic of Korea
| | - Seung-Koo Lee
- Yonsei University College of Medicine , Seoul , Republic of Korea
| | - Adam Dicker
- Department of Radiation Oncology, Sidney Kimmel Cancer Center, Thomas Jefferson University , Philadelphia, PA , USA
| | - Adam Flanders
- Department of Radiology, Sidney Kimmel Cancer Center, Thomas Jefferson University , Philadelphia, PA , USA
| | - Wenyin Shi
- Department of Radiation Oncology, Thomas Jefferson University Hospital , Philadelphia, PA , USA
| | - Gaurav Shukla
- Department of Radiation Oncology, Christiana Care Health System , Philadelphia , USA
| | - Brent Griffith
- Department of Radiology, Henry Ford Health System , Detroit, MI , USA
| | - Laila Poisson
- Department of Public Health Sciences, Center for Bioinformatics, Henry Ford Health System , Detroit, MI , USA
| | - Lisa Rogers
- Department of Neurosurgery, Henry Ford Health , Detroit , USA
| | - Thomas Booth
- School of Biomedical Engineering and Imaging Sciences, King’s College , London , United Kingdom
| | - Rajan Jain
- Department of Radiology, NYU Grossman School of Medicine , New York, NY , USA
| | - Matthew Lee
- Department of Radiology, NYU Grossman School of Medicine , New York, NY , USA
| | - Abhishek Mahajan
- Department of Imaging, The Clatterbridge Cancer Centre NHS Foundation Trust , London , United Kingdom
| | - Arnab Chakravarti
- Department of Radiation Oncology, Ohio State University Wexner Medical Center , Columbus, OH , USA
| | - Joshua Palmer
- The Department of Radiation Oncology, The James Cancer Hospital, Ohio State University Wexner Medical Center , Columbus, OH , USA
| | | | | | - Benedikt Wiestler
- Department of Neuroradiology, Technical University of Munich , Munich , Germany
| | - Christos Davatzikos
- Center for Biomedical Image Computing and Analytics and Department of Radiology, Perelman School of Medicine, University of Pennsylvania , Philadelphia, PA , USA
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Burlando M, Maul JT, Salvi I, Simic D, Cozzani E, Ak M, Birkenmaier I, Parodi A. Psoriasis patients' characteristics associated with high PASI response to tildrakizumab: an international dual center study. Eur Rev Med Pharmacol Sci 2022; 26:6772-6776. [PMID: 36196725 DOI: 10.26355/eurrev_202209_29777] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
OBJECTIVE Heterogeneous real-world evidence can complement the more strictly regulated clinical trial data. A benefit of this is the wide range of backgrounds, comorbidities and characteristics that can give additional insights into treatments. Observational, retrospective studies can help to fill in the mosaic that makes up a treatments landscape. Tildrakizumab, an interleukin 23p19 inhibitor, is approved for the treatment of plaque psoriasis and has been shown to be a safe and efficacious therapy in clinical trials and emerging real-world evidence. We aimed at confirming the efficacy of tildrakizumab in patients with plaque psoriasis in a dual center setting and identifying patients' characteristics leading to better treatment response. PATIENTS AND METHODS Patients with moderate to severe plaque psoriasis, eligible for systemic biological treatment, and treated with tildrakizumab were included in the study and the routine clinical parameters - Psoriasis Area and Severity Index (PASI), Dermatology Life Quality Index (DLQI), and safety - were retrospectively analyzed. RESULTS The combined cohorts included 89 patients, of which 64% were naïve to biologic therapies. At the time of analysis efficacy assessment was available for 39 patients after 12 months of treatment, 73 patients after 36 weeks, 79 patients after 16 weeks and 82 patients after 4 weeks. PASI and DLQI decreased significantly over time, with 52/73 (71.2%) patients achieving PASI 100 after 36 weeks. No severe side-effects were recorded in association with tildrakizumab. CONCLUSIONS We confirmed the safety and efficacy of tildrakizumab in a real-world clinical setting. A higher proportion of patients naïve to biologics achieved a greater PASI response than patients who had previously been treated with biologics. The same was true for older patients and patients with a shorter history of disease.
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Affiliation(s)
- M Burlando
- Division of Dermatology, Department of Health and Science (DissaL), Policlinico San Martino Hospital, IRCCS, Genoa, Italy.
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13
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Ak M, Gumus S, Aghayev A, Chang CH, Fu B, Roberts MS, Woodard PK, Bae KT. The Resolution Rate of Pulmonary Embolism on CT Pulmonary Angiography: a Prospective Study. Eur J Radiol 2022; 155:110466. [PMID: 35986988 DOI: 10.1016/j.ejrad.2022.110466] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2022] [Revised: 07/25/2022] [Accepted: 08/06/2022] [Indexed: 11/29/2022]
Abstract
PURPOSE To prospectively assess the rate of clot resolution from CT pulmonary angiography (CTPA) in patients with acute pulmonary embolism (PE). MATERIALS AND METHODS This prospective cohort study included 290 patients (136 men, 154 women; mean age, 51.9 years) with acute PE. All patients had a CTPA at the presentation and had at least one follow-up within 6 months (mean 72.7 days). Sixty-four percent of patients had follow-up scans for research purposes within a pre-determined period (between 28 and 184 days; mean, 78.27 days) and 36 % had (between 2 and 184 days; mean, 62.78 days) for a clinical indication. The volume of each clot was measured using a semi-automated quantification program. The resolution rate was evaluated by interval-censored analysis. RESULTS The overall estimated probability of complete resolution was 42 % at 7 days, 56 % at 10 days, and 71 % at 45 days. Achieving complete resolution was significantly faster in patients with peripheral clots (HR: 1.78; CI: 1.05-3.03, p = 0.032) but slower in patients with consolidation and history of venous thromboembolism (VTE), (HR: 0.37; CI: 0.18-0.79, p = 0.01 and HR: 0.57; CI: 0.35-0.91, p = 0.019, respectively). Although the patients with cancer showed a faster resolution rate (HR: 1.67; CI: 1.05-2.68, p = 0.032), the mortality rate was significantly higher than non-cancer patients. CONCLUSION The resolution rate of clot burden in acute PE was associated with patients' clinical presentation variables and CTPA imaging biomarkers. This information may be incorporated into designing a prediction rule and determining the appropriate duration of anticoagulation therapy in patients with acute PE.
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Affiliation(s)
- M Ak
- Department of Radiology, University of Pittsburgh Medical Center, Pittsburgh, PA, United States
| | - S Gumus
- Department of Radiology, University of Pittsburgh Medical Center, Pittsburgh, PA, United States.
| | - A Aghayev
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States
| | - C H Chang
- Department of Medicine, School of Medicine, Department of Biostatistics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, United States
| | - B Fu
- Data and Statistical Sciences, Abbvie, Inc., Lake Bluff, IL, United States
| | - M S Roberts
- Department of Medicine, School of Medicine, Department of Biomedical Informatics, School of Medicine, University of Pittsburgh, Pittsburgh, PA, United States
| | - P K Woodard
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, MO, United States
| | - K T Bae
- Department of Radiology, University of Pittsburgh Medical Center, Pittsburgh, PA, United States
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14
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de Miguel-Perez D, Russo A, Arrieta O, Ak M, Barron F, Gunasekaran M, Mamindla P, Lara-Mejia L, Peterson CB, Er ME, Peddagangireddy V, Buemi F, Cooper B, Manca P, Lapidus RG, Hsia RC, Cardona AF, Naing A, Kaushal S, Hirsch FR, Mack PC, Serrano MJ, Adamo V, Colen RR, Rolfo C. Extracellular vesicle PD-L1 dynamics predict durable response to immune-checkpoint inhibitors and survival in patients with non-small cell lung cancer. J Exp Clin Cancer Res 2022; 41:186. [PMID: 35650597 PMCID: PMC9161571 DOI: 10.1186/s13046-022-02379-1] [Citation(s) in RCA: 31] [Impact Index Per Article: 15.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/20/2022] [Accepted: 05/02/2022] [Indexed: 12/26/2022]
Abstract
BACKGROUND Immune-checkpoint inhibitors (ICIs) changed the therapeutic landscape of patients with lung cancer. However, only a subset of them derived clinical benefit and evidenced the need to identify reliable predictive biomarkers. Liquid biopsy is the non-invasive and repeatable analysis of biological material in body fluids and a promising tool for cancer biomarkers discovery. In particular, there is growing evidence that extracellular vesicles (EVs) play an important role in tumor progression and in tumor-immune interactions. Thus, we evaluated whether extracellular vesicle PD-L1 expression could be used as a biomarker for prediction of durable treatment response and survival in patients with non-small cell lung cancer (NSCLC) undergoing treatment with ICIs. METHODS Dynamic changes in EV PD-L1 were analyzed in plasma samples collected before and at 9 ± 1 weeks during treatment in a retrospective and a prospective independent cohorts of 33 and 39 patients, respectively. RESULTS As a result, an increase in EV PD-L1 was observed in non-responders in comparison to responders and was an independent biomarker for shorter progression-free survival and overall survival. To the contrary, tissue PD-L1 expression, the commonly used biomarker, was not predictive neither for durable response nor survival. CONCLUSION These findings indicate that EV PD-L1 dynamics could be used to stratify patients with advanced NSCLC who would experience durable benefit from ICIs.
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Affiliation(s)
- Diego de Miguel-Perez
- Center for Thoracic Oncology, Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Marlene and Stewart Greenebaum Comprehensive Cancer Center, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Alessandro Russo
- Marlene and Stewart Greenebaum Comprehensive Cancer Center, University of Maryland School of Medicine, Baltimore, MD, USA.,Medical Oncology Unit, A.O. Papardo & Department of Human Pathology, University of Messina, Messina, Italy
| | - Oscar Arrieta
- Thoracic Oncology Unit, Instituto Nacional de Cancerología (INCan), Mexico City, Mexico
| | - Murat Ak
- Department of Radiology, University of Pittsburgh, Pittsburgh, PA, USA.,Hillman Cancer Center, University of Pittsburgh Medical Center, Pittsburgh, PA, USA
| | - Feliciano Barron
- Thoracic Oncology Unit, Instituto Nacional de Cancerología (INCan), Mexico City, Mexico
| | - Muthukumar Gunasekaran
- Marlene and Stewart Greenebaum Comprehensive Cancer Center, University of Maryland School of Medicine, Baltimore, MD, USA
| | | | - Luis Lara-Mejia
- Thoracic Oncology Unit, Instituto Nacional de Cancerología (INCan), Mexico City, Mexico
| | | | - Mehmet E Er
- Department of Radiology, University of Pittsburgh, Pittsburgh, PA, USA.,Hillman Cancer Center, University of Pittsburgh Medical Center, Pittsburgh, PA, USA
| | | | - Francesco Buemi
- Medical Oncology Unit, A.O. Papardo & Department of Human Pathology, University of Messina, Messina, Italy
| | - Brandon Cooper
- Marlene and Stewart Greenebaum Comprehensive Cancer Center, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Paolo Manca
- Fondazione IRCCS Istituto Nazionale Dei Tumori Di Milano, Milan, Italy
| | - Rena G Lapidus
- Marlene and Stewart Greenebaum Comprehensive Cancer Center, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Ru-Ching Hsia
- Marlene and Stewart Greenebaum Comprehensive Cancer Center, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Andres F Cardona
- Luis Carlos Sarmiento Angulo Cancer Treatment and Research Center (CTIC) / Foundation for Clinical and Applied Cancer Research (FICMAC) / Molecular Oncology and Biology Systems Research Group (Fox-G), Universidad El Bosque, Bogotá, Colombia
| | - Aung Naing
- Departments of Investigational Cancer Therapeutics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Sunjay Kaushal
- Marlene and Stewart Greenebaum Comprehensive Cancer Center, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Fred R Hirsch
- Center for Thoracic Oncology, Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Philip C Mack
- Center for Thoracic Oncology, Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Maria Jose Serrano
- GENYO Centre for Genomics and Oncological Research, Pfizer/ University of Granada/ Andalusian Regional Government, PTS Granada, Granada, Spain
| | - Vincenzo Adamo
- Medical Oncology Unit, A.O. Papardo & Department of Human Pathology, University of Messina, Messina, Italy
| | - Rivka R Colen
- Department of Radiology, University of Pittsburgh, Pittsburgh, PA, USA.,Hillman Cancer Center, University of Pittsburgh Medical Center, Pittsburgh, PA, USA
| | - Christian Rolfo
- Center for Thoracic Oncology, Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA. .,Marlene and Stewart Greenebaum Comprehensive Cancer Center, University of Maryland School of Medicine, Baltimore, MD, USA.
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Pease M, Ak M, Ayoub M, Mamindla P, Kamal A, Peddagangireddy V, Zinn PO, Moron F, Colen RR. 348 Multi-Center MRI Radiomic Texture Analysis Pre-Operatively Discriminates Between Primary Central Nervous System Lymphoma, Glioblastoma, and Brain Metastasis. Neurosurgery 2022. [DOI: 10.1227/neu.0000000000001880_348] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
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16
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Ak M, Eleneen Y, Ayoub M, Colen RR. Cancer Imaging in Immunotherapy. Adv Exp Med Biol 2022; 1342:431-447. [PMID: 34972979 DOI: 10.1007/978-3-030-79308-1_19] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Abstract
Immune therapeutics are revolutionizing cancer treatments. In tandem, new and confounding imaging characteristics have appeared that are distinct from those typically seen with conventional cytotoxic therapies. In fact, only 10% of patients on immunotherapy may show tumor shrinkage, typical of positive responses on conventional therapy. Conversely, those on immune therapies may initially demonstrate a delayed response, transient enlargement followed by tumor shrinkage, stable size, or the appearance of new lesions. Response Evaluation Criteria in Solid Tumors (RECIST) or WHO criteria, developed to identify early effects of cytotoxic agents, may not provide a complete evaluation of new emerging treatment response pattern of immunotherapeutic agents. Therefore, new imaging response criteria, such as the immune-related Response Evaluation Criteria in Solid Tumors (irRECIST), immune Response Evaluation Criteria in Solid Tumors (iRECIST), and immune-related Response Criteria (irRC), are proposed. However, FDA approval of emerging therapies including immunotherapies still relies on the current RECIST criteria. In this chapter, we review the traditional and new imaging response criteria for evaluation of solid tumors and briefly touch on some of the more commonly associated immunotherapy-induced adverse events.
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Affiliation(s)
- Murat Ak
- Department of Radiology, University of Pittsburgh, Pittsburgh, PA, USA.,Hillman Cancer Center, University of Pittsburgh Medical Center, Pittsburgh, PA, USA
| | - Yousra Eleneen
- Department of Radiology, University of Pittsburgh, Pittsburgh, PA, USA.,Hillman Cancer Center, University of Pittsburgh Medical Center, Pittsburgh, PA, USA
| | - Mira Ayoub
- Department of Radiology, University of Pittsburgh, Pittsburgh, PA, USA.,Hillman Cancer Center, University of Pittsburgh Medical Center, Pittsburgh, PA, USA
| | - Rivka R Colen
- Department of Radiology, University of Pittsburgh, Pittsburgh, PA, USA. .,Hillman Cancer Center, University of Pittsburgh Medical Center, Pittsburgh, PA, USA.
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17
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Akbari* H, Bakas* S, Sako* C, Kazerooni AF, Garcia JA, Bagley SJ, Mohan S, Ahn SS, Ak M, Alexander GS, Ali AS, Baid U, Bavde C, Bilello M, Brem S, Capellades J, Chang JH, Choi YS, Dicker AP, Fathallah-Shaykh H, Flanders AE, Griffith BD, LaMontagne P, Lee M, Lee SK, Liem S, Lombardo J, Lustig RA, Mahajan A, Milchenko M, Nasrallah M, Nazeri A, Puig J, Shukla G, Sloan A, Taylor W, Vadmal V, Waite K, Balana C, Booth TC, Cepeda S, Poisson L, Colen RR, Marcus DS, Palmer J, Jain R, Shi W, O’Rourke DM, Barnholtz-Sloan J, Davatzikos C. NIMG-39. RADIOMIC ANALYSIS FOR NON-INVASIVE IN VIVO PROGNOSTIC STRATIFICATION OF DE NOVO GLIOBLASTOMA PATIENTS: A MULTI-INSTITUTIONAL EVALUATION FOR GENERALIZABILITY IN THE RESPOND CONSORTIUM. Neuro Oncol 2021. [DOI: 10.1093/neuonc/noab196.538] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Abstract
PURPOSE
Multi-parametric MRI based radiomic signatures have highlighted the promise of artificial intelligence (AI) in neuro-oncology. However, inter-institution heterogeneity hinders generalization to data from unseen clinical institutions. To this end, we formulated the ReSPOND (Radiomics Signatures for PrecisiON Diagnostics) consortium for glioblastoma. Here, we seek non-invasive generalizable radiomic signatures from routine clinically-acquired MRI for prognostic stratification of glioblastoma patients.
METHODS
We identified a retrospective cohort of 606 patients with near/gross total tumor resection ( >90%), from 13 geographically-diverse institutions. All pre-operative structural MRI scans (T1,T1-Gd,T2,T2-FLAIR) were aligned to a common anatomical atlas. An automatic algorithm segmented the whole tumors (WTs) into 3 sub-compartments, i.e., enhancing (ET), necrotic core (NC), and peritumoral T2-FLAIR signal abnormality (ED). The combination of ET+NC defines the tumor core (TC). Quantitative radiomic features were extracted to generate our AI model to stratify patients into short- (< 14mts) and long-survivors ( >14mts). The model trained on 276 patients from a single institution was independently validated on 330 unseen patients from 12 left-out institutions, using the area-under-the-receiver-operating-characteristic-curve (AUC).
RESULTS
Each feature individually offered certain (limited but reproducible) value for identifying short-survivors: 1) TC closer to lateral ventricles (AUC=0.62); 2) larger ET/brain (AUC=0.61); 3) larger TC/brain (AUC=0.59); 4) larger WT/brain (AUC=0.55); 5) larger ET/WT (AUC=0.59); 6) smaller ED/WT (AUC=0.57); 7) larger ventricle deformations (AUC=0.6). Integrating all features and age, through a multivariate AI model, resulted in higher accuracy (AUC=0.7; 95% C.I.,0.64-0.77).
CONCLUSION
Prognostic stratification using basic radiomic features is highly reproducible across diverse institutions and patient populations. Multivariate integration yields relatively more accurate and generalizable radiomic signatures, across institutions. Our results offer promise for generalizable non-invasive in vivo signatures of survival prediction in patients with glioblastoma. Extracted features from clinically-acquired imaging, renders these signatures easier for clinical translation. Large-scale evaluation could contribute to improving patient management and treatment planning.
*Indicates equal authorship.
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Affiliation(s)
| | | | | | | | | | | | - Suyash Mohan
- University of Pennsylvania, Philadelphia, PA, USA
| | - Sung Soo Ahn
- Department of Radiology, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Murat Ak
- University of Pittsburgh, Pittsburgh, PA, USA
| | | | | | - Ujjwal Baid
- University of Pennsylvania, Philadelphia, PA, USA
| | - Chaitra Bavde
- Case Western Reserve University and University Hospitals of Cleveland, Cleveland, OH, USA
| | | | - Steven Brem
- University of Pennsylvania, Philadelphia, PA, USA
| | | | - Jong Hee Chang
- Department of Neurosurgery, Brain Tumor Center, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Yoon Seong Choi
- Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Adam P Dicker
- Thomas Jefferson University Hospital, Philadelphia, PA, USA
| | | | | | | | | | - Matthew Lee
- New York University Langone Health, New York, USA
| | - Seung-Koo Lee
- Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Spencer Liem
- Sidney Kimmel Cancer Center, Thomas Jefferson University, Philadelphia, USA
| | | | | | - Abhishek Mahajan
- Tata Memorial Centre, Homi Bhabha National Institute, Mumbai, India
| | | | | | - Arash Nazeri
- Washington University in St. Louis, Saint Louis, USA
| | - Josep Puig
- Research Unit (IDIR) Image Diagnosis Institute, Badalona, Spain
| | | | - Andrew Sloan
- UH Cleveland Medical Center & Seidman Cancer Center, Cleveland, OH, USA
| | - William Taylor
- The Ohio State University Wexner Medical Center, Columbus, OH, USA
| | - Vachan Vadmal
- Center for Biomedical Informatics and Information Technology and Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Kristin Waite
- Cleveland Center for Health Outcomes (CCHOR), Cleveland, OH, USA
| | - Carmen Balana
- Medical Oncology Department, Catalan Institute of Oncology (ICO), Badalona, Spain
| | - Thomas C Booth
- School of Biomedical Engineering & Imaging Sciences, King’s College London, London, UK
| | - Santiago Cepeda
- Department of Neurosurgery, University Hospital Río Hortega, Valladolid, Spain
| | | | | | | | - Joshua Palmer
- The James Cancer Hospital at the Ohio State University Wexner Medical Center, Columbus, OH, USA
| | - Rajan Jain
- New York University Langone Health, New York, NY, USA
| | - Wenyin Shi
- Department of Radiation Oncology, Thomas Jefferson University, Philadelphia, PA, USA
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18
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Akbari H, Mohan S, Garcia JA, Kazerooni AF, Sako C, Bakas S, Shukla G, Bagley SJ, Ahn SS, Ak M, Alexander GS, Ali AS, Baid U, Bavde C, Brem S, Capellades J, Chang JH, Choi YS, Dicker AP, Fathallah-Shaykh H, Flanders AE, Griffith BD, LaMontagne P, Lee M, Lee SK, Liem S, Lombardo J, Mahajan A, Milchenko M, Nazeri A, Puig J, Sloan A, Taylor W, Vadmal V, Waite K, Nasrallah M, Bilello M, Lustig RA, Balana C, Booth TC, Cepeda S, Poisson L, Colen RR, Marcus DS, Palmer J, Jain R, Shi W, O’Rourke DM, Barnholtz-Sloan J, Davatzikos C. NIMG-22. PREDICTION OF GLIOBLASTOMA CELLULAR INFILTRATION AND RECURRENCE USING MACHINE LEARNING AND MULTI-PARAMETRIC MRI ANALYSIS: RESULTS FROM THE MULTI-INSTITUTIONAL RESPOND CONSORTIUM. Neuro Oncol 2021. [DOI: 10.1093/neuonc/noab196.522] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Abstract
PURPOSE
Multi-parametric MRI and artificial intelligence (AI) methods were previously used to predict peritumoral neoplastic cell infiltration and risk of future recurrence in glioblastoma, in single-institution studies. We hypothesize that important characteristics of peritumoral tissue heterogeneity captured, engineered/selected, and quantified by these methods relate to predictions generalizable in the multi-institutional ReSPOND (Radiomics Signatures for PrecisiON Diagnostics) consortium.
METHODS
To support further development, generalization, and clinical translation of our proposed method, we trained the AI model on a retrospective cohort of 29 de novo glioblastoma patients from the Hospital of the University of Pennsylvania (UPenn) (Male/Female:20/9, age:22-78 years) followed by evaluation on a prospective multi-institutional cohort of 84 glioblastoma patients (Male/Female:51/33, age:34-89 years) from Case Western Reserve University/University Hospitals (CWRU/UH, 25), New York University (NYU, 13), Ohio State University (OSU, 13), University Hospital Río Hortega (RH, 2), and UPenn (31). Features extracted from pre-resection MRI (T1, T1-Gd, T2, T2-FLAIR, ADC) were used to build our model predicting the spatial pattern of subsequent tumor recurrence. These predictions were evaluated against regions of pathology-confirmed post-resection recurrence.
RESULTS
Our model predicted the locations that later harbored tumor recurrence with sensitivity 83%, AUC 0.83 (99% CI, 0.73-0.93), and odds ratio 7.23 (99% CI, 7.09-7.37) in the prospective cohort. Odds ratio (99% CI)/AUC(99% CI) per institute were: CWRU/UH, 7.8(7.6-8.1)/0.82(0.75-0.89); NYU, 3.5(3.3-3.6)/0.84(074-0.93); OSU, 7.9(7.6-8.3)/0.8(0.67-0.94); RH, 22.7(20-25.1)/0.94(0.27-1); UPenn, 7.1(6.8-7.3)/0.83(0.76-0.91).
CONCLUSION
This is the first study that provides relatively extensive multi-institutional validated evidence that AI can provide good predictions of peritumoral neoplastic cell infiltration and future recurrence, by dissecting the MRI signal heterogeneity in peritumoral tissue. Our analyses leveraged the unique dataset of the ReSPOND consortium, which aims to develop and evaluate AI-based biomarkers for individualized prediction and prognostication, by moving from single-institution studies to generalizable, well-validated multi-institutional predictive biomarkers.
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Affiliation(s)
- Hamed Akbari
- University of Pennsylvania, Philadelphia, PA, USA
| | - Suyash Mohan
- University of Pennsylvania, Philadelphia, PA, USA
| | | | | | - Chiharu Sako
- University of Pennsylvania, Philadelphia, PA, USA
| | | | | | | | - Sung Soo Ahn
- Department of Radiology, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Murat Ak
- University of Pittsburgh, Pittsburgh, PA, USA
| | | | - Ayesha S Ali
- Thomas Jefferson University, Philadelphia, PA, USA
| | - Ujjwal Baid
- University of Pennsylvania, Philadelphia, PA, USA
| | - Chaitra Bavde
- Case Western Reserve University and University Hospitals of Cleveland, Cleveland, OH, USA
| | - Steven Brem
- University of Pennsylvania, Philadelphia, PA, USA
| | | | - Jong Hee Chang
- Department of Neurosurgery, Brain Tumor Center, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Yoon Seong Choi
- Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Adam P Dicker
- Thomas Jefferson University Hospital, Philadelphia, PA, USA
| | | | | | | | | | - Matthew Lee
- New York University Langone Health, New York, NY, USA
| | - Seung-Koo Lee
- Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Spencer Liem
- Sidney Kimmel Cancer Center, Thomas Jefferson University, Philadelphia, PA, USA
| | | | - Abhishek Mahajan
- Tata Memorial Centre, Homi Bhabha National Institute, Mumbai, India
| | | | - Arash Nazeri
- Washington University in St. Louis, Saint Louis, WA, USA
| | - Josep Puig
- Research Unit (IDIR) Image Diagnosis Institute, Badalona, Spain
| | - Andrew Sloan
- UH Cleveland Medical Center & Seidman Cancer Center, Cleveland, OH, USA
| | - William Taylor
- The Ohio State University Wexner Medical Center, OH, USA
| | - Vachan Vadmal
- Center for Biomedical Informatics and Information Technology and Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Kristin Waite
- Cleveland Center for Health Outcomes (CCHOR), Cleveland, OH, USA
| | | | | | | | - Carmen Balana
- Medical Oncology Department, Catalan Institute of Oncology (ICO), Badalona, Spain
| | - Thomas C Booth
- School of Biomedical Engineering & Imaging Sciences, King’s College London, London, UK
| | - Santiago Cepeda
- Department of Neurosurgery, University Hospital Río Hortega, Valladolid, Spain
| | | | | | | | - Joshua Palmer
- The James Cancer Hospital at the Ohio State University Wexner Medical Center, Columbus, OH, USA
| | - Rajan Jain
- New York University Langone Health, New York, NY, USA
| | - Wenyin Shi
- Department of Radiation Oncology, Thomas Jefferson University, Philadelphia, PA, USA
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Ak M, Toll SA, Hein KZ, Colen RR, Khatua S. Evolving Role and Translation of Radiomics and Radiogenomics in Adult and Pediatric Neuro-Oncology. AJNR Am J Neuroradiol 2021; 43:792-801. [PMID: 34649914 DOI: 10.3174/ajnr.a7297] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2021] [Accepted: 07/19/2021] [Indexed: 12/24/2022]
Abstract
Exponential technologic advancements in imaging, high-performance computing, and artificial intelligence, in addition to increasing access to vast amounts of diverse data, have revolutionized the role of imaging in medicine. Radiomics is defined as a high-throughput feature-extraction method that unlocks microscale quantitative data hidden within standard-of-care medical imaging. Radiogenomics is defined as the linkage between imaging and genomics information. Multiple radiomics and radiogenomics studies performed on conventional and advanced neuro-oncology image modalities show that they have the potential to differentiate pseudoprogression from true progression, classify tumor subgroups, and predict recurrence, survival, and mutation status with high accuracy. In this article, we outline the technical steps involved in radiomics and radiogenomics analyses with the use of artificial intelligence methods and review current applications in adult and pediatric neuro-oncology.
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Affiliation(s)
- M Ak
- From the Department of Radiology (M.A., R.R.C.), University of Pittsburgh, Pittsburgh, Pennsylvania.,Hillman Cancer Center (M.A., R.R.C.), University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania
| | - S A Toll
- Department of Hematology-Oncology (S.A.T.), Children's Hospital of Michigan, Detroit, Michigan
| | - K Z Hein
- Department of Leukemia (K.Z.H.), The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - R R Colen
- From the Department of Radiology (M.A., R.R.C.), University of Pittsburgh, Pittsburgh, Pennsylvania.,Hillman Cancer Center (M.A., R.R.C.), University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania
| | - S Khatua
- Department of Pediatric Hematology-Oncology (S.K.), Mayo Clinic, Rochester, Minnesota.
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20
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Foster A, Nigam S, Tatum DS, Raphael I, Xu J, Kumar R, Plakseychuk E, Latoche JD, Vincze S, Li B, Giri R, McCarl LH, Edinger R, Ak M, Peddagangireddy V, Foley LM, Hitchens TK, Colen RR, Pollack IF, Panigrahy A, Magda D, Anderson CJ, Edwards WB, Kohanbash G. Novel theranostic agent for PET imaging and targeted radiopharmaceutical therapy of tumour-infiltrating immune cells in glioma. EBioMedicine 2021; 71:103571. [PMID: 34530385 PMCID: PMC8446777 DOI: 10.1016/j.ebiom.2021.103571] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2021] [Revised: 08/17/2021] [Accepted: 08/19/2021] [Indexed: 01/18/2023] Open
Abstract
BACKGROUND Malignant gliomas are deadly tumours with few therapeutic options. Although immunotherapy may be a promising therapeutic strategy for treating gliomas, a significant barrier is the CD11b+ tumour-associated myeloid cells (TAMCs), a heterogeneous glioma infiltrate comprising up to 40% of a glioma's cellular mass that inhibits anti-tumour T-cell function and promotes tumour progression. A theranostic approach uses a single molecule for targeted radiopharmaceutical therapy (TRT) and diagnostic imaging; however, there are few reports of theranostics targeting the tumour microenvironment. METHODS Utilizing a newly developed bifunctional chelator, Lumi804, an anti-CD11b antibody (αCD11b) was readily labelled with either Zr-89 or Lu-177, yielding functional radiolabelled conjugates for PET, SPECT, and TRT. FINDINGS 89Zr/177Lu-labeled Lumi804-αCD11b enabled non-invasive imaging of TAMCs in murine gliomas. Additionally, 177Lu-Lumi804-αCD11b treatment reduced TAMC populations in the spleen and tumour and improved the efficacy of checkpoint immunotherapy. INTERPRETATION 89Zr- and 177Lu-labeled Lumi804-αCD11b may be a promising theranostic pair for monitoring and reducing TAMCs in gliomas to improve immunotherapy responses. FUNDING A full list of funding bodies that contributed to this study can be found in the Acknowledgements section.
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Affiliation(s)
- Alexandra Foster
- Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Shubhanchi Nigam
- Department of Radiology, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - David S Tatum
- Lumiphore, Inc., 600 Bancroft Way Berkeley, CA 94710, USA
| | - Itay Raphael
- Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Jide Xu
- Lumiphore, Inc., 600 Bancroft Way Berkeley, CA 94710, USA
| | - Rajeev Kumar
- Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | | | - Joseph D Latoche
- Department of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Sarah Vincze
- Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Bo Li
- Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Rajan Giri
- Department of Biochemistry, University of Missouri, Columbia, MO, 65211, USA
| | - Lauren H McCarl
- Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Robert Edinger
- Department of Radiology, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Murat Ak
- Department of Radiology, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | | | - Lesley M Foley
- Animal Imaging Center, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - T Kevin Hitchens
- Animal Imaging Center, University of Pittsburgh, Pittsburgh, PA 15213, USA; Department of Neurobiology, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Rivka R Colen
- Department of Radiology, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Ian F Pollack
- Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Ashok Panigrahy
- Department of Radiology, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Darren Magda
- Lumiphore, Inc., 600 Bancroft Way Berkeley, CA 94710, USA.
| | - Carolyn J Anderson
- Department of Radiology, University of Pittsburgh, Pittsburgh, PA 15213, USA; Department of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA; Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA 15213, USA; Department of Pharmacology & Chemical Biology, University of Pittsburgh, Pittsburgh 15213, USA; Department of Chemistry, University of Pittsburgh, Pittsburgh, PA 15213, USA; Department of Chemistry, University of Missouri, Columbia, MO, 65211 USA.
| | - W Barry Edwards
- Department of Radiology, University of Pittsburgh, Pittsburgh, PA 15213, USA; Department of Biochemistry, University of Missouri, Columbia, MO, 65211, USA.
| | - Gary Kohanbash
- Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, PA 15213, USA; Department of Immunology, University of Pittsburgh, Pittsburgh, PA 15213, USA.
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21
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Colen RR, Rolfo C, Ak M, Ayoub M, Ahmed S, Elshafeey N, Mamindla P, Zinn PO, Ng C, Vikram R, Bakas S, Peterson CB, Rodon Ahnert J, Subbiah V, Karp DD, Stephen B, Hajjar J, Naing A. Author response to Cunha et al. J Immunother Cancer 2021; 9:jitc-2021-003299. [PMID: 34315823 PMCID: PMC8317086 DOI: 10.1136/jitc-2021-003299] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/08/2021] [Indexed: 11/04/2022] Open
Abstract
The need to identify biomarkers to predict immunotherapy response for rare cancers has been long overdue. We aimed to study this in our paper, 'Radiomics analysis for predicting pembrolizumab response in patients with advanced rare cancers'. In this response to the Letter to the Editor by Cunha et al, we explain and discuss the reasons behind choosing LASSO (Least Absolute Shrinkage and Selection Operator) and XGBoost (eXtreme Gradient Boosting) with LOOCV (Leave-One-Out Cross-Validation) as the feature selection and classifier method, respectively for our radiomics models. Also, we highlight what care was taken to avoid any overfitting on the models. Further, we checked for the multicollinearity of the features. Additionally, we performed 10-fold cross-validation instead of LOOCV to see the predictive performance of our radiomics models.
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Affiliation(s)
- Rivka R Colen
- Department of Radiology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA .,Department of Radiology, Hillman Cancer Center, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA
| | - Christian Rolfo
- Center for Thoracic Oncology at Tisch Cancer Institute, Mount Sinai Health System & Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Murat Ak
- Department of Radiology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.,Department of Radiology, Hillman Cancer Center, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA
| | - Mira Ayoub
- Department of Radiology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.,Department of Radiology, Hillman Cancer Center, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA
| | - Sara Ahmed
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Nabil Elshafeey
- Department of Breast Imaging, Diagnostic Radiology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Priyadarshini Mamindla
- Department of Radiology, Hillman Cancer Center, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA
| | - Pascal O Zinn
- Department of Neurosurgery, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA
| | - Chaan Ng
- Abdominal Imaging Department, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Raghu Vikram
- Abdominal Imaging Department, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Spyridon Bakas
- Department of Radiology, Pathology, and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Christine B Peterson
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Jordi Rodon Ahnert
- Investigational Cancer Therapeutics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Vivek Subbiah
- Investigational Cancer Therapeutics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Daniel D Karp
- Investigational Cancer Therapeutics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Bettzy Stephen
- Investigational Cancer Therapeutics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Joud Hajjar
- William T Shearer Center for Human Immunobiology, Texas Children's Hospital, Houston, Texas, USA.,Section of Immunology, Allergy and Retrovirology, Baylor College of Medicine, Houston, Texas, USA
| | - Aung Naing
- Investigational Cancer Therapeutics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
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22
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Yurtsever C, Ak M. Splenic Arteriovenous Fistula with Pseudoaneurysm. Journal of Gastrointestinal and Abdominal Radiology 2021. [DOI: 10.1055/s-0041-1726656] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/21/2022] Open
Affiliation(s)
- Cagri Yurtsever
- Department of Radiology, Sultan Abdulhamid Han Teaching Hospital, Istanbul, Turkey
| | - Murat Ak
- Department of Radiology, University of Pittsburgh, Pittsburgh, Pennsylvania, United States
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23
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Colen RR, Rolfo C, Ak M, Ayoub M, Ahmed S, Elshafeey N, Mamindla P, Zinn PO, Ng C, Vikram R, Bakas S, Peterson CB, Rodon Ahnert J, Subbiah V, Karp DD, Stephen B, Hajjar J, Naing A. Radiomics analysis for predicting pembrolizumab response in patients with advanced rare cancers. J Immunother Cancer 2021; 9:jitc-2020-001752. [PMID: 33849924 PMCID: PMC8051405 DOI: 10.1136/jitc-2020-001752] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/12/2021] [Indexed: 12/22/2022] Open
Abstract
BACKGROUND We present a radiomics-based model for predicting response to pembrolizumab in patients with advanced rare cancers. METHODS The study included 57 patients with advanced rare cancers who were enrolled in our phase II clinical trial of pembrolizumab. Tumor response was evaluated using Response Evaluation Criteria in Solid Tumors (RECIST) 1.1 and immune-related RECIST (irRECIST). Patients were categorized as 20 "controlled disease" (stable disease, partial response, or complete response) or 37 progressive disease). We used 3D-slicer to segment target lesions on standard-of-care, pretreatment contrast enhanced CT scans. We extracted 610 features (10 histogram-based features and 600 second-order texture features) from each volume of interest. Least absolute shrinkage and selection operator logistic regression was used to detect the most discriminatory features. Selected features were used to create a classification model, using XGBoost, for the prediction of tumor response to pembrolizumab. Leave-one-out cross-validation was performed to assess model performance. FINDINGS The 10 most relevant radiomics features were selected; XGBoost-based classification successfully differentiated between controlled disease (complete response, partial response, stable disease) and progressive disease with high accuracy, sensitivity, and specificity in patients assessed by RECIST (94.7%, 97.3%, and 90%, respectively; p<0.001) and in patients assessed by irRECIST (94.7%, 93.9%, and 95.8%, respectively; p<0.001). Additionally, the common features of the RECIST and irRECIST groups also highly predicted pembrolizumab response with accuracy, sensitivity, specificity, and p value of 94.7%, 97%, 90%, p<0.001% and 96%, 96%, 95%, p<0.001, respectively. CONCLUSION Our radiomics-based signature identified imaging differences that predicted pembrolizumab response in patients with advanced rare cancer. INTERPRETATION Our radiomics-based signature identified imaging differences that predicted pembrolizumab response in patients with advanced rare cancer.
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Affiliation(s)
- Rivka R Colen
- Department of Radiology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA .,Hillman Cancer Center, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA
| | - Christian Rolfo
- Department of Thoracic Medical Oncology, University of Maryland, Baltimore, Maryland, USA
| | - Murat Ak
- Department of Radiology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.,Hillman Cancer Center, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA
| | - Mira Ayoub
- Department of Radiology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.,Hillman Cancer Center, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA
| | - Sara Ahmed
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Nabil Elshafeey
- Department of Breast Imaging, Diagnostic Radiology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Priyadarshini Mamindla
- Hillman Cancer Center, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA
| | - Pascal O Zinn
- Department of Neurosurgery, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA
| | - Chaan Ng
- Abdominal Imaging Department, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Raghu Vikram
- Abdominal Imaging Department, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Spyridon Bakas
- Radiology, Pathology, and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Christine B Peterson
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Jordi Rodon Ahnert
- Department of Investigational Cancer Therapeutics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Vivek Subbiah
- Department of Investigational Cancer Therapeutics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Daniel D Karp
- Department of Investigational Cancer Therapeutics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Bettzy Stephen
- Department of Investigational Cancer Therapeutics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Joud Hajjar
- Section of Immunology, Allergy and Retrovirology, Baylor College of Medicine, Houston, Texas, USA.,William T Shearer Center for Human Immunobiology, Texas Children's Hospital, Houston, Texas, USA
| | - Aung Naing
- Department of Investigational Cancer Therapeutics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
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24
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Yurtsever C, Ak M, Cakir OF, Sonmez G. Imaging findings of a rare pararectal splenosis and literature review. Radiography (Lond) 2020; 27:748-750. [PMID: 33023811 DOI: 10.1016/j.radi.2020.09.017] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2020] [Revised: 09/17/2020] [Accepted: 09/20/2020] [Indexed: 10/23/2022]
Abstract
Pararectal splenosis is an extremely rare lesion caused by ectopic auto-transplantation of splenic tissue after splenic trauma or splenectomy. It is often asymptomatic and detected incidentally during radiologic evaluation. We present a 24-year-old male with pararectal splenosis. The patient had a history of splenectomy and presented with complaints of abdominal discomfort and chronic constipation. Contrast-enhanced computed tomography (CT) revealed multiple well-enhanced masses located in the abdominal cavity and one mass in pararectal area. Additionally, the pararectal lesion showed diffusion restriction on diffusion-weighted magnetic resonance imaging (DW-MRI). In this case report, we aim to highlight the significance of taking a detailed medical history; and using DW-MRI for diagnosis of splenosis by presenting a case in a rare location.
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Affiliation(s)
- C Yurtsever
- Department of Radiology, University of Health Sciences Sultan Abdulhamid Han Teaching Hospital Istanbul, Turkey
| | - M Ak
- Department of Radiology, University of Pittsburgh, Pittsburgh, PA, USA.
| | - O F Cakir
- Department of Radiology, University of Pittsburgh, Pittsburgh, PA, USA
| | - G Sonmez
- Department of Radiology, University of Health Sciences Sultan Abdulhamid Han Teaching Hospital Istanbul, Turkey
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25
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Ciftci T, Erbatur S, Ak M. Comparison of the effects of dexmedetomidine and remifentanil on potential extreme haemodynamic and respiratory response following mask ventilation and laryngoscopy in patients with mandibular fractures. Eur Rev Med Pharmacol Sci 2015; 19:4427-4433. [PMID: 26636533] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/05/2023]
Abstract
OBJECTIVE The safety profile and efficacy were compared for remifentanil and dexmedetomidine with respect to haemodynamic and respiratory response during mask ventilation and laryngoscopy in patients with mandibular fractures. PATIENTS AND METHODS Seventy patients undergoing elective mandibular fracture surgery were randomly assigned to the remifentanil group (Group R, n = 35) or the dexmedetomidine group (Group D, n = 35). The primary outcomes were preoperative pain scores caused by jaw movement; haemodynamic response; intubation score; and side effects, such as the incidence of oxygen desaturation and muscle rigidity. Other side effects, such as tachycardia, bradycardia, hypertension and hypotension, were also compared. RESULTS Preoperative pain scores caused by jaw movement were significantly high for both groups, but there were no statistically significant differences between the groups. The incidence of oxygen desaturation and muscle rigidity was significantly lower in Group D than in Group R (p = 0.025). No significant differences existed between the groups in terms of intubation score, haemodynamics, and other side effects (p > 0.05). DISCUSSION Dexmedetomidine and remifentanil had equal effectiveness on the control of haemodynamic response due to mask ventilation and intubation in patients with mandibular fractures. However, at the doses used in this study, dexmedetomidine had a significant advantage over remifentanil in terms of respiratory stability.
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Affiliation(s)
- T Ciftci
- Department of Anesthesiology and Reanimation, Dicle University Medical Faculty, Diyarbakır, Turkey.
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26
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Mallappa S, Sharma U, Ak M. P283 Histomorphological parameters of nipple areolar complex as a predictor in carcinoma breast. Breast 2015. [DOI: 10.1016/s0960-9776(15)70315-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022] Open
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27
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Erdem M, Akarsu S, Ünlü A, Alper M, Karaman D, Ak M. 2834 – Comparison of clinical and the sociodemographic characteristics of bipolar patients according to the presence of a history of depressive episode. Eur Psychiatry 2013. [DOI: 10.1016/s0924-9338(13)77418-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/29/2022] Open
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Erdem M, Akarsu S, Bolu A, Günay H, Garip B, Ak M, Zincir S. 2828 – Comparison of clinical and sociodemographic features of bipolar disorder according to gender. Eur Psychiatry 2013. [DOI: 10.1016/s0924-9338(13)77412-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/26/2022] Open
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29
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Erdem M, Akarsu S, Ak M, Bozkurt A, Özşahin A. 2829 – Clinical features in hospitalized bipolar patients. Eur Psychiatry 2013. [DOI: 10.1016/s0924-9338(13)77413-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/26/2022] Open
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31
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Karli R, Ak M, Karli A. A different placement of the stone; rhinolithiasis. Eur Rev Med Pharmacol Sci 2012; 16:1541-1545. [PMID: 23111967] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/01/2023]
Abstract
INTRODUCTION Rhinolithiasis is a rare disease and formed by mineralization in the nasal cavity. Precipitated calcareous material on intranasal foreign substances forms the rhinoliths. It is start time could have since childhood. MATERIALS AND METHODS In this article, we present eight cases of rhinolithiasis who admitted to our Clinic between January 2001 and December 2010 with unilateral chronic nasal discharge, nasal obstruction and oral malodor. CONCLUSIONS Rhinolithiasis mostly manifests itself with unilateral purulent rhinorrhea, nasal obstruction and facial pain symptoms. We aimed to discuss these entity with similar cases in the literature.
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Affiliation(s)
- R Karli
- Department of the Otolaryngology, Ondokuz Mayıs University Samsun, Turkey.
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32
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Dogan M, Kahraman AS, Firat C, Ak M, Yildirim O, Dogan DG. Multiple dural arteriovenous fistulas involving the cavernous sinus, transverse sinus, sigmoid sinus and spinal drainage: CT angiography findings in 14-year-old boy. Eur Rev Med Pharmacol Sci 2012; 16:1305-1306. [PMID: 23047518] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/01/2023]
Abstract
Dural arteriovenous fistulas (DAVF) are rare and constitute 10% to 15% of all intracranial arteriovenous malformations. Only few cases of DAVFs are reported in children. Here is the first case report describing CT angiographic findings in a 14 year old child having multiple DAVFs involving spinal canal, both cavernous and cerebral sinuses.
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Affiliation(s)
- M Dogan
- Department of Radiology, Inonu University School of Medicine, Malatya, Turkey.
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Lapsekili N, Yelboga Z, Ak M. P-52 - Screening adult attention deficit hyperactivity disorder in adults diagnosed with substance abuse disorder. Eur Psychiatry 2012. [DOI: 10.1016/s0924-9338(12)74219-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/28/2022] Open
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34
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Ak M, Yavuz F, Lapsekili N, Turkcapar H. P-1176 - Evaluating the caregivers of bipolar disorder patients with zarit burden interview. Eur Psychiatry 2012. [DOI: 10.1016/s0924-9338(12)75343-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/28/2022] Open
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35
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Samdanci ET, Firat C, Cakir E, Ak M, Sayin S, Nurkabul Z. The incidence of non-proliferative and precancerous lesions of reduction mammoplasty: evaluation of 273 cases. Eur Rev Med Pharmacol Sci 2011; 15:1207-1211. [PMID: 22165684] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 05/31/2023]
Abstract
BACKGROUND Reduction mammoplasty (RM) is one of the most commonly performed plastic surgery procedures to treat symptomatic macromasty or to correct asymmetry. Occult breast carcinomas were rarely defined in RM specimens. There are few studies aiming to define the incidence of non-proliferative and precancerous lesions. MATERIAL AND METHODS We evaluated the pathological findings of the RM specimens that have been submitted to our Center for the last 6 years (2005-2011). RESULTS A total of 273 cases with bilateral RM were enrolled to the study. Of them, 229 cases had pathological changes. Eight cases (2.9%) had atypical ductal/lobular hyperplasia. One case (0.3%) had lobular carcinoma in situ; however, no invasive breast carcinoma was detected. Other pathological findings included fibrocystic changes, fibrosis, adenosis, fibroadenoma (without complex features), mastitis and duct ectasia. CONCLUSIONS Pathological examination of the RM specimens is quite important to define the lesions precancerous of breast carcinoma. Unknown occult breast lesions could be identified and early interventions may be taken into account.
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Affiliation(s)
- E T Samdanci
- Plastic and Reconstructive Surgery Department, Inonu University School of Medicine, Malatya Turkey.
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36
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Yildirim A, Tarkuc S, Ak M, Toppare L. Syntheses of electroactive layers based on functionalized anthracene for electrochromic applications. Electrochim Acta 2008. [DOI: 10.1016/j.electacta.2008.02.026] [Citation(s) in RCA: 36] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
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Ozcirpici B, Sahinoz S, Ozgur S, Bozkurt AI, Sahinoz T, Ceylan A, Ilcin E, Saka G, Acemoglu H, Palanci Y, Ak M, Akkafa F. Vaccination coverage in the South-East Anatolian Project (SEAP) region and factors influencing low coverage. Public Health 2006; 120:145-54. [PMID: 16260009 DOI: 10.1016/j.puhe.2005.04.008] [Citation(s) in RCA: 23] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2004] [Revised: 01/31/2005] [Accepted: 04/06/2005] [Indexed: 11/22/2022]
Abstract
OBJECTIVES To determine the vaccination coverage of children living in the South-east Anatolian Project (SEAP) region; whether the vaccination coverage was similar to formal reports, other studies and other countries; and which factors influence vaccination, in order to indicate how vaccination coverage can be improved. STUDY DESIGN A descriptive cross-sectional study conducted in nine provinces of the SEAP region in order to determine public health problems and their causes. METHODS A population-based sample of 1150 houses was selected from rural and urban areas of the SEAP region and visited by the researchers. Questionnaires were applied in 2001 and 2002. RESULTS In the SEAP region, only 30% of children had received a complete set of vaccines. The vaccination coverage was 76.7% for Bacille Calmette-Guérin; 62.0% for the third doses of diphtheria, tetanus toxoid, pertussis and polio vaccine; 62.7% for measles; 44% for the third dose of hepatitis B vaccine in children aged 12-23 months; and 13.3% for the second dose of tetanus toxoid in women who gave birth in the last 5 years. In logistic regression analysis, residence type, number of siblings, birth interval, follow-up visits of midwives, and maternal level of education were found to influence whether children were completely vaccinated. CONCLUSIONS The findings of this study indicate that vaccination coverage is not acceptable in the SEAP region. Efforts must focus on family planning services, education of women, follow-up visits and strengthening health facilities, especially in rural regions, to improve vaccination.
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Affiliation(s)
- B Ozcirpici
- Faculty of Medicine, Department of Public Health, Gaziantep University, 27310 Gaziantep, Turkey.
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Döskaya M, Degirmenci A, Deirmenc A, Ciçek C, Ak M, Korkmaz M, Gürüz Y, Uner A. Behaviour of Toxoplasma gondii RH Ankara strain tachyzoites during continuous production in various cell lines. Parasitology 2005; 132:315-9. [PMID: 16318650 DOI: 10.1017/s0031182005009078] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2005] [Revised: 05/05/2005] [Accepted: 08/18/2005] [Indexed: 11/06/2022]
Abstract
Toxoplasma gondii is an obligate intracellular protozoan parasite. The objective of the present study was to examine the behaviour of Toxoplasma gondii RH Ankara strain tachyzoites in a cell culture environment. The study represents the first step in determining whether T. gondii RH Ankara strain tachyzoites, grown in cell culture, are of sufficient quality to allow cessation of in vivo tachyzoite production for diagnostic assays. In the present study, T. gondii RH Ankara strain tachyzoites were continuously produced in myeloma X63.Ag8.653, HeLa, Hep-2, and Vero cell cultures for 2 months. The average size of the tachyzoites was 3×5·7 μm prior to the first inoculation but after continuous production, a marked decrease was noted in average tachyzoite size. The smallest tachyzoite size, was 1×2·1 μm after 2 months, in myeloma cell cultures even though the yield of tachyzoites increased. With other cell cultures, tachyzoite yields were not as high as myeloma cell culture although decrease in size was less. The smallest decrease in tachyzoite size, averaging 2×3·8 μm after 2 months, was observed in tachyzoites produced in HeLa cell cultures. A virulence assay in small groups of BALB/c mice, using tachyzoites derived from cell cultures, was also conducted. The preliminary results of the virulence assay suggest that as the size of the tachyzoites decreased, the virulence in mice decreased. Future research will focus on the effect of the size of cell culture-derived T. gondii RH Ankara strain tachyzoites on the virulence, protein expression, and the reliability of diagnostic assays. Ultimately, the behaviour of tachyzoites from various T. gondii strains will be observed in cell culture to determine if size is altered.
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Affiliation(s)
- M Döskaya
- Department of Parasitology, Ege University Medical Faculty, 35100, Bornova/Izmir, Turkey.
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Ak M, Babaoğlu A, Dağci H, Türk M, Bayram S, Ertabaklar H, Ozcel MA, Uner A, Charoenvit Y, Kumar S, Hoffman SL. Production of monoclonal antibodies against a 19-kD recombinant Plasmodium vivax MSP1 for detection of P. vivax malaria in Turkey. ACTA ACUST UNITED AC 2004; 23:133-6. [PMID: 15165487 DOI: 10.1089/153685904774129748] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
Abstract
Plasmodium vivax malaria, which is transmitted to humans by mosquitoes, is one of the most important parasitic diseases in Turkey. The major protein on the surface of asexual erythrocytic stage merozoites of P. vivax (Pv) is 200 kD and called major merozoite surface protein-1 (PvMSP1). Polyclonal antibodies against the 19-kD C-terminal fragment of PvMSP1 (PvMSP1(19)) are protective in monkey models of P. vivax and associated with protection in field studies. In this research, monoclonal antibodies were produced against PvMSP1(19). A total of 214 IgG(1) antibody-releasing hybridomas were obtained and three monoclonal antibodies were produced (PvMSP1(19).1, PvMSP1(19).2, and PvMSP1(19).3) and selected for further study. They have now been purified from ascitic fluid on a Staphylococcus protein A affinity column. These are the first monoclonal antibodies produced against P. vivax in Turkey and the first monoclonal antibodies produced against this recombinant PvMSP1(19) in the world. The monoclonal antibodies will be used to study the epidemiology of P. vivax in patients with malaria in Turkey, and to develop better strategies for early diagnosis and treatment of the disease in our population.
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Affiliation(s)
- M Ak
- Department of Parasitology, Ege Univ. Med. Fac., Bornova, Izmir, Turkey.
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Donnez J, Polet R, Rabinovitz R, Ak M, Squifflet J, Nisolle M. Endometrial laser intrauterine thermotherapy: the first series of 100 patients observed for 1 year. Fertil Steril 2000; 74:791-6. [PMID: 11020525 DOI: 10.1016/s0015-0282(00)00715-9] [Citation(s) in RCA: 43] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Abstract
OBJECTIVE To describe a new instrument (GyneLase) that offers a new approach (endometrial laser intrauterine thermal therapy [ELITT]) to treatment of menorrhagia and to evaluate the efficacy of ELITT in the management of dysfunctional uterine bleeding. DESIGN Prospective study. SETTING University hospital. PATIENT(S) 100 premenopausal women with dysfunctional uterine bleeding were observed for 1 year. INTERVENTION(S) Intrauterine laser thermotherapy with a diode laser. MAIN OUTCOME MEASUREMENT(S) Amenorrhea rate after 1 year. RESULT(S) The amenorrhea rate after 1 year of follow-up was 71%, and the rate of amenorrhea/severe hypomenorrhea rate was >90%; these rates are much higher than those in the literature after such procedures as electrosurgery or intrauterine thermal balloon therapy. The ELITT procedure is an inherently safe and simple alternative, providing controlled and effective treatment of the entire endometrium. In contrast to traditional endometrial ablation using a neodymium yttrium-aluminum-garnet laser, the ELITT procedure does not require intensive training or hysteroscopic control; it is also far less risky, because the power used per unit area is 1,000 times lower. CONCLUSION(S) The ELITT procedure is a new nonhysteroscopic technique for endometrial ablation. The technique is very safe and offers the highest amenorrhea rate to date in the literature.
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Affiliation(s)
- J Donnez
- Department of Gynecology, Cliniques Universitaires St. Luc, Université Catholique de Louvain, Brussels, Belgium.
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Donnez J, Polet R, Squifflet J, Rabinovitz R, Levy U, Ak M, Nisolle M. Endometrial laser intrauterine thermo-therapy (ELITT): a revolutionary new approach to the elimination of menorrhagia. Curr Opin Obstet Gynecol 1999; 11:363-70. [PMID: 10498022 DOI: 10.1097/00001703-199908000-00002] [Citation(s) in RCA: 22] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
Various non-hysteroscopic procedures have been developed in the attempt to treat dysfunctional uterine bleeding that fails to respond to medical treatment efficiently and easily. Among these procedures is low-dose laser radiation of the endometrium with the diode source, which is characterized by the highest incidence of amenorrhea.
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Affiliation(s)
- J Donnez
- Université Catholique de Louvain, Cliniques Universitaires St Luc, Department of Gynecology, Brussels, Belgium.
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Abstract
Octreotide (Sandostatin 201-995) has an inhibitory effect on gastric, intestinal, and pancreatic secretions and hepatic and splachnic blood flow. We examined the effects of octreotide on bile flow and bile components in 10 patients with T-tube choledochostomy. A Fogarty balloon catheter was inserted distal to the T-tube of these patients for measurement of bile flow and bile components. Bile samples were obtained to analyze bile acid, phospholipid, lipoprotein, and cholesterol, and bile flow measurements were performed every 15 min for a period of 90 min before study and after normal saline and octreotide administrations. While octreotide had an inhibitory effect on bile flow, the concentrations of bile acid, phospholipid, and lipoprotein in bile were increased with octreotide.
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Affiliation(s)
- M Sahin
- Department of Surgery, University of Selcuk, School of Medicine, Konya, Turkey
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Ak M, Jones TR, Charoenvit Y, Kumar S, Kaslow DC, Maris D, Marwoto H, Masbar S, Hoffman SL. Humoral immune responses against Plasmodium vivax MSP1 in humans living in a malaria endemic area in Flores, Indonesia. Southeast Asian J Trop Med Public Health 1998; 29:685-91. [PMID: 10772546] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 02/16/2023]
Abstract
The aim of this study was to evaluate the relationship among age, parasitemia status, spleen size, hematocrit, and antibody levels to Plasmodium vivax merozoite surface protein 1 (MSP1) in individuals chronically exposed to P. vivax. Subjects were recruited from the population of three adjacent villages on the Island of Flores in Indonesia where malaria transmission is hyperendemic and tropical splenomegaly syndrome is highly prevalent. Subjects were evaluated for spleen size, hematocrit, presence of parasitemia, and presence of antibodies to a recombinant peptide consisting of 90 amino acids from the carboxy terminus of MSP1. Fifty-seven percent of 2-4 year olds, 45% of 5-9 years old, and 7% of > or = 15 years old were parasitemic; 99% of the > or = 15 years old had splenomegaly, and 31% of them had Hackett 4 or 5 spleens. The frequency of antibody positivity to MSP1 antigen in ELISA increased with age reaching a maximum of 89% in > or = 20 years old. The frequency of antibody positivity to MSPI also increased with spleen size, and with a decline in the prevalence of parasitemia.
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Affiliation(s)
- M Ak
- Ege University, Medical Faculty, Department of Parasitology, Bornova, Izmir, Turkey
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Ak M, Bower JH, Hoffman SL, Sedegah M, Lees A, Carter M, Beaudoin RL, Charoenvit Y. Monoclonal antibodies of three different immunoglobulin G isotypes produced by immunization with a synthetic peptide or native protein protect mice against challenge with Plasmodium yoelii sporozoites. Infect Immun 1993; 61:2493-7. [PMID: 8500885 PMCID: PMC280874 DOI: 10.1128/iai.61.6.2493-2497.1993] [Citation(s) in RCA: 19] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/31/2023] Open
Abstract
Passive transfer of monoclonal antibodies (MAbs) against malaria circumsporozoite (CS) proteins protects animals against malaria. Active immunization with synthetic or recombinant peptides induces a level of polyclonal antibodies to sporozoites comparable to those found after passive immunization but does not provide comparable protection. In the Plasmodium yoelii system, synthetic or recombinant peptide-induced antibodies have never been shown to protect. The current studies were designed to determine whether immunogen structure (native protein versus synthetic peptide) or immunoglobulin G (IgG) subclass of antibodies was responsible for the absolute differences between protective, passively transferred MAbs and nonprotective, actively induced polyclonal antibodies. In this study we produced two MAbs, QGP-S1 (IgG1) and QGP-S2 (IgG2b), by immunization with a synthetic peptide based on the P. yoelii CS major repeat, (QGPGAP)4, conjugated to keyhole limpet hemocyanin. These MAbs were compared tp NYS1 (IgG3), an anti-CS protein MAb previously produced by immunization with irradiated P. yoelii sporozoites, which recognizes (QGP GAP)2. QGP-S1 and QGP-S2 passively transferred protection. However, when compared with NYS1, there was a hierarchy of protection, NYS1 > QGP-S1 > QGP-S2. There was no correlation between antibody level at challenge as determined by immunofluorescent antibody test against sporozoites or enzyme-linked immunosorbent assay against (QGPGAP)2 or apparent antibody avidity for (QGPGAP)2 by sodium thiocyanate elution assay. The data demonstrate that a synthetic peptide can induce protective antibodies and that a specific antibody subclass is not required for protection. Work to determine whether antibody affinity or fine specificity can explain the hierarchy of protection among the MAbs is under way.
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Affiliation(s)
- M Ak
- Malaria Program, Naval Medical Research Institute, Bethesda, Maryland 20889-5055
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