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403 results on '"Moran, Jean M."'

6. NCTN Assessment on Current Applications of Radiomics in Oncology

Author

Nie, Ke, Al-Hallaq, Hania, Li, X Allen, Benedict, Stanley H, Sohn, Jason W, Moran, Jean M, Fan, Yong, Huang, Mi, Knopp, Michael V, Michalski, Jeff M, Monroe, James, Obcemea, Ceferino, Tsien, Christina I, Solberg, Timothy, Wu, Jackie, Xia, Ping, Xiao, Ying, and El Naqa, Issam

Subjects
Biomedical and Clinical Sciences, Oncology and Carcinogenesis, Clinical Trials and Supportive Activities, Clinical Research, Cancer, 4.1 Discovery and preclinical testing of markers and technologies, Detection, screening and diagnosis, Good Health and Well Being, Decision Support Systems, Clinical, Genomics, Humans, Image Processing, Computer-Assisted, Logistic Models, Machine Learning, Magnetic Resonance Imaging, Neoplasms, Phantoms, Imaging, Pharmacokinetics, Phenotype, Positron-Emission Tomography, Radiation Oncology, Reproducibility of Results, Tomography, X-Ray Computed, Treatment Outcome, Other Physical Sciences, Clinical Sciences, Oncology & Carcinogenesis, Oncology and carcinogenesis, Theoretical and computational chemistry, Medical and biological physics
Abstract

Radiomics is a fast-growing research area based on converting standard-of-care imaging into quantitative minable data and building subsequent predictive models to personalize treatment. Radiomics has been proposed as a study objective in clinical trial concepts and a potential biomarker for stratifying patients across interventional treatment arms. In recognizing the growing importance of radiomics in oncology, a group of medical physicists and clinicians from NRG Oncology reviewed the current status of the field and identified critical issues, providing a general assessment and early recommendations for incorporation in oncology studies.

Published
2019

7. Machine learning and modeling: Data, validation, communication challenges.

Author

El Naqa, Issam, Ruan, Dan, Valdes, Gilmer, Dekker, Andre, McNutt, Todd, Ge, Yaorong, Wu, Q Jackie, Oh, Jung Hun, Thor, Maria, Smith, Wade, Rao, Arvind, Fuller, Clifton, Xiao, Ying, Manion, Frank, Schipper, Matthew, Mayo, Charles, Moran, Jean M, and Ten Haken, Randall

Subjects
Reproducibility of Results, Communication, Radiation Oncology, Medical Informatics, Databases, Factual, Machine Learning, big data, machine learning, radiation oncology, Networking and Information Technology R&D (NITRD), Bioengineering, Cancer, Other Physical Sciences, Biomedical Engineering, Oncology and Carcinogenesis, Nuclear Medicine & Medical Imaging
Abstract

With the era of big data, the utilization of machine learning algorithms in radiation oncology is rapidly growing with applications including: treatment response modeling, treatment planning, contouring, organ segmentation, image-guidance, motion tracking, quality assurance, and more. Despite this interest, practical clinical implementation of machine learning as part of the day-to-day clinical operations is still lagging. The aim of this white paper is to further promote progress in this new field of machine learning in radiation oncology by highlighting its untapped advantages and potentials for clinical advancement, while also presenting current challenges and open questions for future research. The targeted audience of this paper includes newcomers as well as practitioners in the field of medical physics/radiation oncology. The paper also provides general recommendations to avoid common pitfalls when applying these powerful data analytic tools to medical physics and radiation oncology problems and suggests some guidelines for transparent and informative reporting of machine learning results.

Published
2018

8. Evaluation of Dose Accuracy in the Near-Surface Region for Whole Breast Irradiation Techniques in a Multi-institutional Consortium

Author

Moncion, Alexander, Wilson, Melissa, Ma, Ruimei, Marsh, Robin, Burmeister, Jay, Dryden, Daniel, Lack, Danielle, Grubb, Margaret, Mayville, Alan, Jursinic, Paul, Dess, Kathryn, Kamp, Justin, Young, Kellen, Dilworth, Joshua T., Kestin, Larry, Jagsi, Reshma, Mietzel, Melissa, Vicini, Frank, Pierce, Lori J., and Moran, Jean M.

Published
2022
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11. Comparative Effectiveness Analysis of 3D-Conformal Radiation Therapy Versus Intensity Modulated Radiation Therapy (IMRT) in a Prospective Multicenter Cohort of Patients With Breast Cancer

Author

Jagsi, Reshma, Griffith, Kent A., Moran, Jean M., Matuszak, Martha M., Marsh, Robin, Grubb, Margaret, Abu-Isa, Eyad, Dilworth, Joshua T., Dominello, Michael M., Heimburger, David, Lack, Danielle, Walker, Eleanor M., Hayman, James A., Vicini, Frank, and Pierce, Lori J.

Published
2022
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13. American Association of Physicists in Medicine Task Group 263: Standardizing Nomenclatures in Radiation Oncology

Author

Mayo, Charles S, Moran, Jean M, Bosch, Walter, Xiao, Ying, McNutt, Todd, Popple, Richard, Michalski, Jeff, Feng, Mary, Marks, Lawrence B, Fuller, Clifton D, Yorke, Ellen, Palta, Jatinder, Gabriel, Peter E, Molineu, Andrea, Matuszak, Martha M, Covington, Elizabeth, Masi, Kathryn, Richardson, Susan L, Ritter, Timothy, Morgas, Tomasz, Flampouri, Stella, Santanam, Lakshmi, Moore, Joseph A, Purdie, Thomas G, Miller, Robert C, Hurkmans, Coen, Adams, Judy, Wu, Qing-Rong Jackie, Fox, Colleen J, Siochi, Ramon Alfredo, Brown, Norman L, Verbakel, Wilko, Archambault, Yves, Chmura, Steven J, Dekker, Andre L, Eagle, Don G, Fitzgerald, Thomas J, Hong, Theodore, Kapoor, Rishabh, Lansing, Beth, Jolly, Shruti, Napolitano, Mary E, Percy, James, Rose, Mark S, Siddiqui, Salim, Schadt, Christof, Simon, William E, Straube, William L, St. James, Sara T, Ulin, Kenneth, Yom, Sue S, and Yock, Torunn I

Subjects
Medical and Biological Physics, Biomedical and Clinical Sciences, Clinical Sciences, Physical Sciences, Oncology and Carcinogenesis, Cancer, Clinical Research, Clinical Trials and Supportive Activities, Networking and Information Technology R&D (NITRD), Advisory Committees, Clinical Trials as Topic, Humans, Radiation Oncology, Radiotherapy Dosage, Radiotherapy Planning, Computer-Assisted, Reference Standards, Societies, Scientific, Software, Terminology as Topic, United States, Other Physical Sciences, Oncology & Carcinogenesis, Oncology and carcinogenesis, Theoretical and computational chemistry, Medical and biological physics
Abstract

A substantial barrier to the single- and multi-institutional aggregation of data to supporting clinical trials, practice quality improvement efforts, and development of big data analytics resource systems is the lack of standardized nomenclatures for expressing dosimetric data. To address this issue, the American Association of Physicists in Medicine (AAPM) Task Group 263 was charged with providing nomenclature guidelines and values in radiation oncology for use in clinical trials, data-pooling initiatives, population-based studies, and routine clinical care by standardizing: (1) structure names across image processing and treatment planning system platforms; (2) nomenclature for dosimetric data (eg, dose-volume histogram [DVH]-based metrics); (3) templates for clinical trial groups and users of an initial subset of software platforms to facilitate adoption of the standards; (4) formalism for nomenclature schema, which can accommodate the addition of other structures defined in the future. A multisociety, multidisciplinary, multinational group of 57 members representing stake holders ranging from large academic centers to community clinics and vendors was assembled, including physicists, physicians, dosimetrists, and vendors. The stakeholder groups represented in the membership included the AAPM, American Society for Radiation Oncology (ASTRO), NRG Oncology, European Society for Radiation Oncology (ESTRO), Radiation Therapy Oncology Group (RTOG), Children's Oncology Group (COG), Integrating Healthcare Enterprise in Radiation Oncology (IHE-RO), and Digital Imaging and Communications in Medicine working group (DICOM WG); A nomenclature system for target and organ at risk volumes and DVH nomenclature was developed and piloted to demonstrate viability across a range of clinics and within the framework of clinical trials. The final report was approved by AAPM in October 2017. The approval process included review by 8 AAPM committees, with additional review by ASTRO, European Society for Radiation Oncology (ESTRO), and American Association of Medical Dosimetrists (AAMD). This Executive Summary of the report highlights the key recommendations for clinical practice, research, and trials.

Published
2018

14. Contemporary Practice Patterns for Palliative Radiation Therapy of Bone Metastases: Impact of a Quality Improvement Project on Extended Fractionation

Author

Jaworski, Elizabeth M., Yin, Huiying, Griffith, Kent A., Pandya, Raveena, Mancini, Brandon R., Jolly, Shruti, Boike, Thomas P., Moran, Jean M., Dominello, Michael M., Wilson, Melissa, Parker, Jan, Burmeister, Jay, Fraser, Correen, Miller, Lynne, Baldwin, Kaitlyn, Mietzel, Melissa A., Grubb, Margaret, Kendrick, Danielle, Spratt, Daniel E., and Hayman, James A.

Published
2021
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15. Toward quantitative intrafractional monitoring in paraspinal SBRT using a proprietary software application: clinical implementation and patient results

Author

Fan, Qiyong, primary, Pham, Hai, additional, Li, Xiang, additional, Zhang, Pengpeng, additional, Zhang, Lei, additional, Fu, Yabo, additional, Huang, Bohong, additional, Li, Cindy, additional, Cuaron, John, additional, Cervino, Laura, additional, Moran, Jean M, additional, and Li, Tianfang, additional

Published
2024
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25. Enhancing the target visibility with synthetic target specific digitally reconstructed radiograph for intrafraction motion monitoring: A proof‐of‐concept study.

Author

Fu, Yabo, Fan, Qiyong, Cai, Weixing, Li, Feifei, He, Xiuxiu, Cuaron, John, Cervino, Laura, Moran, Jean M., Li, Tianfang, and Li, Xiang

Subjects
LUNGS, STEREOTACTIC radiotherapy, EXTERNAL beam radiotherapy, GENERATIVE adversarial networks, RADIOGRAPHS, CONE beam computed tomography
Abstract

Background: Intrafraction motion monitoring in External Beam Radiation Therapy (EBRT) is usually accomplished by establishing a correlation between the tumor and the surrogates such as an external infrared reflector, implanted fiducial markers, or patient skin surface. These techniques either have unstable surrogate‐tumor correlation or are invasive. Markerless real‐time onboard imaging is a noninvasive alternative that directly images the target motion. However, the low target visibility due to overlapping tissues along the X‐ray projection path makes tumor tracking challenging. Purpose: To enhance the target visibility in projection images, a patient‐specific model was trained to synthesize the Target Specific Digitally Reconstructed Radiograph (TS‐DRR). Methods: Patient‐specific models were built using a conditional Generative Adversarial Network (cGAN) to map the onboard projection images to TS‐DRR. The standard Pix2Pix network was adopted as our cGAN model. We synthesized the TS‐DRR based on the onboard projection images using phantom and patient studies for spine tumors and lung tumors. Using previously acquired CT images, we generated DRR and its corresponding TS‐DRR to train the network. For data augmentation, random translations were applied to the CT volume when generating the training images. For the spine, separate models were trained for an anthropomorphic phantom and a patient treated with paraspinal stereotactic body radiation therapy (SBRT). For lung, separate models were trained for a phantom with a spherical tumor insert and a patient treated with free‐breathing SBRT. The models were tested using Intrafraction Review Images (IMR) for the spine and CBCT projection images for the lung. The performance of the models was validated using phantom studies with known couch shifts for the spine and known tumor deformation for the lung. Results: Both the patient and phantom studies showed that the proposed method can effectively enhance the target visibility of the projection images by mapping them into synthetic TS‐DRR (sTS‐DRR). For the spine phantom with known shifts of 1 mm, 2 mm, 3 mm, and 4 mm, the absolute mean errors for tumor tracking were 0.11 ± 0.05 mm in the x direction and 0.25 ± 0.08 mm in the y direction. For the lung phantom with known tumor motion of 1.8 mm, 5.8 mm, and 9 mm superiorly, the absolute mean errors for the registration between the sTS‐DRR and ground truth are 0.1 ± 0.3 mm in both the x and y directions. Compared to the projection images, the sTS‐DRR has increased the image correlation with the ground truth by around 83% and increased the structural similarity index measure with the ground truth by around 75% for the lung phantom. Conclusions: The sTS‐DRR can greatly enhance the target visibility in the onboard projection images for both the spine and lung tumors. The proposed method could be used to improve the markerless tumor tracking accuracy for EBRT. [ABSTRACT FROM AUTHOR]

Published
2023
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35. Development and Clinical Implementation of an Automated Virtual Integrative Planner for Radiation Therapy of Head and Neck Cancer

Author

Jaworski, Elizabeth M., primary, Mierzwa, Michelle L., additional, Vineberg, Karen A., additional, Yao, John, additional, Shah, Jennifer L., additional, Schonewolf, Caitlin A., additional, Litzenberg, Dale, additional, Gharzai, Laila A., additional, Matuszak, Martha M., additional, Paradis, Kelly C., additional, Dougherty, Ashley, additional, Burger, Pamela, additional, Tatro, Daniel, additional, Arnould, George Spencer, additional, Moran, Jean M., additional, Lee, Choonik, additional, Eisbruch, Avraham, additional, and Mayo, Charles S., additional

Published
2023
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40. Women in Medical Physics.

Author

Paradis, Kelly C., Moran, Jean M., and Hendrickson, Kristi R. G.

Subjects
*WOMEN in physics, *MEDICAL physics, *WOMEN in science, *PHYSICS education, *WORK environment
Abstract

An increasing number of bachelor's degrees in physics were awarded over the period shown in the figure, with 9283 total physics bachelor's degrees awarded in 2018. In my introductory physics courses in my small, liberal arts college, there were many women, but fewer than 20% of them graduated with a physics major in my cohort year. I was the first and only woman hired as physics faculty in my first position after graduate school, which I left to transition to a medical physics career. The bachelor's degree in physics is an entry-level degree into the field of medical physics, along with other science, technology, engineering, and mathematics (STEM) majors. [Extracted from the article]

Published
2023
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43. Multi-Institutional Stereotactic Body Radiation Therapy Incident Learning: Evaluation of Safety Barriers Using a Human Factors Analysis and Classification System

Author

McGurk, Ross, primary, Woch Naheedy, Katherine, additional, Kosak, Tara, additional, Hobbs, Amy, additional, Mullins, Brandon T., additional, Paradis, Kelly C., additional, Kearney, Meghan, additional, Roback, Donald, additional, Durney, Jeffrey, additional, Adapa, Karthik, additional, Chera, Bhishamjit S., additional, Marks, Lawrence B., additional, Moran, Jean M., additional, Mak, Raymond H., additional, and Mazur, Lukasz M., additional

Published
2022
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45. Erratum: “Report of AAPM Task Group 219 on independent calculation‐based dose/MU verification for IMRT”

Author

Zhu, Timothy C., primary, Stathakis, Sotiris, additional, Clark, Jennifer R., additional, Feng, Wenzheng, additional, Georg, Dietmar, additional, Holmes, Shannon M., additional, Kry, Stephen F., additional, Charlie Ma, Chang‐Ming, additional, Miften, Moyed, additional, Mihailidis, Dimitris, additional, Moran, Jean M., additional, Papanikolaou, Niko, additional, Poppe, Bjorn, additional, and Xiao, Ying, additional

Published
2022
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