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W. Jeffrey Zabel Jessica L. Conway Adam Gladwish Julia Skliarenko Giulio Didiodato Leah Goorts-Matthews Adam Michalak Sarah Reistetter Jenna King Keith Nakonechny Kyle Malkoske Muoi N. Tran Nevin McVicar 《Practical radiation oncology》2021,11(1):e80-e89
PurposeAuto-contouring may reduce workload, interobserver variation, and time associated with manual contouring of organs at risk. Manual contouring remains the standard due in part to uncertainty around the time and workload savings after accounting for the review and editing of auto-contours. This preliminary study compares a standard manual contouring workflow with 2 auto-contouring workflows (atlas and deep learning) for contouring the bladder and rectum in patients with prostate cancer.Methods and MaterialsThree contouring workflows were defined based on the initial contour-generation method including manual (MAN), atlas-based auto-contour (ATLAS), and deep-learning auto-contour (DEEP). For each workflow, initial contour generation was retrospectively performed on 15 patients with prostate cancer. Then, radiation oncologists (ROs) edited each contour while blinded to the manner in which the initial contour was generated. Workflows were compared by time (both in initial contour generation and in RO editing), contour similarity, and dosimetric evaluation.ResultsMean durations for initial contour generation were 10.9 min, 1.4 min, and 1.2 min for MAN, DEEP, and ATLAS, respectively. Initial DEEP contours were more geometrically similar to initial MAN contours. Mean durations of the RO editing steps for MAN, DEEP, and ATLAS contours were 4.1 min, 4.7 min, and 10.2 min, respectively. The geometric extent of RO edits was consistently larger for ATLAS contours compared with MAN and DEEP. No differences in clinically relevant dose-volume metrics were observed between workflows.ConclusionAuto-contouring software affords time savings for initial contour generation; however, it is important to also quantify workload changes at the RO editing step. Using deep-learning auto-contouring for bladder and rectum contour generation reduced contouring time without negatively affecting RO editing times, contour geometry, or clinically relevant dose–volume metrics. This work contributes to growing evidence that deep-learning methods are a clinically viable solution for organ-at-risk contouring in radiation therapy. 相似文献
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Sarah J. Schrauben Haochang Shou Xiaoming Zhang Amanda Hyre Anderson Joseph V. Bonventre Jing Chen Steven Coca Susan L. Furth Jason H. Greenberg Orlando M. Gutierrez Joachim H. Ix James P. Lash Chirag R. Parikh Casey M. Rebholz Venkata Sabbisetti Mark J. Sarnak Michael G. Shlipak Sushrut S. Waikar Paul L. Kimmel Ramachandran S. Vasan Harold I. Feldman Jeffrey R. Schelling 《Journal of the American Society of Nephrology : JASN》2021,32(1):115
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Cheryl L. Rock PhD RD Cynthia A. Thomson PhD RD Kristen R. Sullivan MS MPH Carol L. Howe MD MLS Lawrence H. Kushi ScD Bette J. Caan DrPH Marian L. Neuhouser PhD RD Elisa V. Bandera MD PhD Ying Wang PhD Kimberly Robien PhD RD Karen M. Basen-Engquist PhD MPH Justin C. Brown PhD Kerry S. Courneya PhD Tracy E. Crane PhD RDN David O. Garcia PhD FACSM Barbara L. Grant MS RDN CSO FAND Kathryn K. Hamilton MA RDN CSO CDN FAND Sheri J. Hartman PhD Stacey A. Kenfield ScD Maria Elena Martinez PhD Jeffrey A. Meyerhardt MD MPH Larissa Nekhlyudov MD MPH Linda Overholser MD Alpa V. Patel PhD Bernardine M. Pinto PhD Mary E. Platek PhD RD CDN Erika Rees-Punia PhD MPH Colleen K. Spees PhD MEd RD LD FAND Susan M. Gapstur PhD Marjorie L. McCullough ScD RD 《CA: a cancer journal for clinicians》2022,72(3):230-262
The overall 5-year relative survival rate for all cancers combined is now 68%, and there are over 16.9 million survivors in the United States. Evidence from laboratory and observational studies suggests that factors such as diet, physical activity, and obesity may affect risk for recurrence and overall survival after a cancer diagnosis. The purpose of this American Cancer Society guideline is to provide evidence-based, cancer-specific recommendations for anthropometric parameters, physical activity, diet, and alcohol intake for reducing recurrence and cancer-specific and overall mortality. The audiences for this guideline are health care providers caring for cancer survivors as well as cancer survivors and their families. The guideline is intended to serve as a resource for informing American Cancer Society programs, health policy, and the media. Sources of evidence that form the basis of this guideline are systematic literature reviews, meta-analyses, pooled analyses of cohort studies, and large randomized clinical trials published since 2012. Recommendations for nutrition and physical activity during cancer treatment, informed by current practice, large cancer care organizations, and reviews of other expert bodies, are also presented. To provide additional context for the guidelines, the authors also include information on the relationship between health-related behaviors and comorbidities, long-term sequelae and patient-reported outcomes, and health disparities, with attention to enabling survivors' ability to adhere to recommendations. Approaches to meet survivors' needs are addressed as well as clinical care coordination and resources for nutrition and physical activity counseling after a cancer diagnosis. 相似文献
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