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Your search keyword '"Beriwal, Sushil"' showing total 1,117 results
Start Over Author "Beriwal, Sushil" Publication Type Academic Journals
1,117 results on '"Beriwal, Sushil"'

1. Prognostic Effect of Mismatch Repair Status in Early-Stage Endometrial Cancer Treated With Adjuvant Radiation: A Multi-institutional Analysis

Author

Hathout, Lara, Sherwani, Zohaib K., Alegun, Josephine, Ohri, Nisha, Fields, Emma C., Shah, Shubhangi, Beriwal, Sushil, Horne, Zachary D., Kidd, Elizabeth A., Leung, Eric W., Song, Jiheon, Taunk, Neil K., Chino, Junzo, Huang, Christina, Russo, Andrea L., Dyer, Michael, Li, Jessie, Albuquerque, Kevin V., and Damast, Shari

Published
2024
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9. Dose Summation Strategies for External Beam Radiation Therapy and Brachytherapy in Gynecologic Malignancy: A Review from the NRG Oncology and NCTN Medical Physics Subcommittees

Author

Kim, Hayeon, Lee, Yongsook C, Benedict, Stanley H, Dyer, Brandon, Price, Michael, Rong, Yi, Ravi, Ananth, Leung, Eric, Beriwal, Sushil, Bernard, Mark E, Mayadev, Jyoti, Leif, Jessica RL, and Xiao, Ying

Subjects
Clinical Research, Clinical Trials and Supportive Activities, Cancer, Biological Products, Brachytherapy, Female, Humans, Physics, Radiotherapy Dosage, Uterine Cervical Neoplasms, Other Physical Sciences, Clinical Sciences, Oncology and Carcinogenesis, Oncology & Carcinogenesis
Abstract

Definitive, nonsurgical management of gynecologic malignancies involves external beam radiation therapy (EBRT) and/or brachytherapy (BT). Summation of the cumulative dose is critical to assess the total biologic effective dose to targets and organs at risk. Cumulative dose calculation from EBRT and BT can be performed with or without image registration (IR) and biologic dose summation. Among these dose summation strategies, linear addition of dose-volume histogram (DVH) parameters without IR is the global standard for composite dose reporting. This approach stems from an era without image guidance and simple external beam and brachytherapy treatment approaches. With technological advances, EBRT and high-dose-rate BT have evolved to allow for volume-based treatment planning and delivery. Modern conformal therapeutic radiation involves volumetric or intensity modulated EBRT, capable of simultaneously treating multiple targets at different specified dose levels. Therefore, given the complexity of modern radiation treatment, the linear addition of DVH parameters from EBRT and high-dose-rate BT is challenging to represent the combined dose distribution. Deformable image registration (DIR) between EBRT and image guided brachytherapy (IGBT) data sets may provide a more nuanced calculation of multimodal dose accumulation. However, DIR is still nascent in this regard, and needs further development for accuracy and efficiency for clinical use. Biologic dose summation can combine physical dose maps from EBRT and each IGBT fraction, thereby generating a composite DVH from the biologic effective dose. However, accurate radiobiologic parameters are tissue-dependent and not well characterized. A combination of voxel-based DIR and biologic weighted dose maps may be the best approximation of dose accumulation but remains invalidated. The purpose of this report is to review dose summation strategies for EBRT and BT, including conventional equivalent dose in 2-Gy fractions dose summation without image registration, physical dose summation using 3-dimensional rigid IR and DIR, and biologic dose summation. We also provide general clinical workflows for IGBT with a focus on cervical cancer.

Published
2021

12. Is Substantial Lymphovascular Space Invasion Prognostic in Patients With Pathologically Lymph Node-Negative Endometrial Cancer?

Author

Pifer, Phillip M., Jaishankar, Sruthi, Bhargava, Rohit, Schad, Michael D., Keller, Andrew, Musunuru, Hima Bindu, Cohen, Michael, Sukumvanich, Paniti, Courtney-Brooks, Madeleine, Boisen, Michelle, Berger, Jessica L., Olawaiye, Alexander, Lesnock, Jamie, Edwards, Robert, Taylor, Sarah, Vargo, John Austin, and Beriwal, Sushil

Published
2023
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14. GEC-ESTRO (ACROP)–ABS–CBG Consensus Brachytherapy Target Definition Guidelines for Recurrent Endometrial and Cervical Tumors in the Vagina

Author

Kamrava, Mitchell, Leung, Eric, Bachand, Francois, Beriwal, Sushil, Chargari, Cyrus, D'Souza, David, Erickson, Beth, Fokdal, Lars, Han, Kathy, Harkenrider, Matthew, Lin, Lilie, Mahantshetty, Umesh, Nesvacil, Nicole, Ravi, Ananth, Schmid, Max, Vigneault, Eric, Westerveld, Henrike, Yashar, Catheryn, and Nout, Remi

Published
2023
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16. Contemporary image-guided cervical cancer brachytherapy: Consensus imaging recommendations from the Society of Abdominal Radiology and the American Brachytherapy Society

Author

Jacobsen, Megan C., Beriwal, Sushil, Dyer, Brandon A., Klopp, Ann H., Lee, Susanna I., McGinnis, Gwendolyn J., Robbins, Jessica B., Rauch, Gaiane M., Sadowski, Elizabeth A., Simiele, Samantha J., Stafford, R. Jason, Taunk, Neil K., Yashar, Catheryn M., and Venkatesan, Aradhana M.

Published
2022
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20. Does Prophylactic Paraortic Lymph Node Irradiation Improve Outcomes in Women With Stage IIIC1 Endometrial Carcinoma?

Author

Yoon, Jennifer, Fitzgerald, Halle, Wang, Yaqun, Wang, Qingyang, Vergalasova, Irina, Elshaikh, Mohamed A., Dimitrova, Irina, Damast, Shari, Li, Jessie Y., Fields, Emma C., Beriwal, Sushil, Keller, Andrew, Kidd, Elizabeth A., Usoz, Melissa, Jolly, Shruti, Jaworski, Elizabeth, Leung, Eric W., Donovan, Elysia, Taunk, Neil K., Chino, Junzo, Natesan, Divya, Russo, Andrea L., Lea, Jayanthi S., Albuquerque, Kevin V., Lee, Larissa J., and Hathout, Lara

Published
2022
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32. A Multi-Institutional Analysis of Adjuvant Chemotherapy and Radiation Sequence in Women With Stage IIIC Endometrial Cancer

Author

Hathout, Lara, Wang, Yaqun, Wang, Qingyang, Vergalasova, Irina, Elshaikh, Mohamed A., Dimitrova, Irina, Damast, Shari, Li, Jessie Y., Fields, Emma C., Beriwal, Sushil, Keller, Andrew, Kidd, Elizabeth A., Usoz, Melissa, Jolly, Shruti, Jaworski, Elizabeth, Leung, Eric W., Donovan, Elysia, Taunk, Neil K., Chino, Junzo, Natesan, Divya, Russo, Andrea L., Lea, Jayanthi S., Albuquerque, Kevin V., and Lee, Larissa J.

Published
2021
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37. Do air gaps with image-guided vaginal cuff brachytherapy impact failure rates in patients with high-intermediate risk FIGO Stage I endometrial cancer?

Author

Richman, Adam H., Patel, Ankur K., Rodríguez-López, Joshua L., Keller, Andrew, Vargo, John A., Kim, Hayeon, Sukumvanich, Paniti, Berger, Jessica L., Boisen, Michelle M., Edwards, Robert, Taylor, Sarah E., Courtney-Brooks, Madeleine B., Olawaiye, Alexander, Orr, Brian C., Lesnock, Jamie L., and Beriwal, Sushil

Published
2021
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39. NRG Oncology/RTOG Consensus Guidelines for Delineation of Clinical Target Volume for Intensity Modulated Pelvic Radiation Therapy in Postoperative Treatment of Endometrial and Cervical Cancer: An Update

Author

Small, William, Jr., Bosch, Walter R., Harkenrider, Mathew M., Strauss, Jonathan B., Abu-Rustum, Nadeem, Albuquerque, Kevin V., Beriwal, Sushil, Creutzberg, Carien L., Eifel, Patricia J., Erickson, Beth A., Fyles, Anthony W., Hentz, Courtney L., Jhingran, Anuja, Klopp, Ann H., Kunos, Charles A., Mell, Loren K., Portelance, Lorraine, Powell, Melanie E., Viswanathan, Akila N., Yacoub, Joseph H., Yashar, Catheryn M., Winter, Kathryn A., and Gaffney, David K.

Published
2021
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45. Evaluation of a deep image-to-image network (DI2IN) auto-segmentation algorithm across a network of cancer centers.

Author

Rayn, Kareem, Gupta, Vibhor, Mulinti, Suneetha, Clark, Ryan, Magliari, Anthony, Chaudhari, Suresh, Garima, Gokhroo, and Beriwal, Sushil

Subjects
DEEP reinforcement learning, REINFORCEMENT learning, SUBMANDIBULAR gland, OPTIC nerve, SEMINAL vesicles
Abstract

Purpose/Objective (s): Due to manual OAR contouring challenges, various automatic contouring solutions have been introduced. Historically, common clinical auto-segmentation algorithms used were atlas-based, which required maintaining a library of self-made contours. Searching the collection was computationally intensive and could take several minutes to complete. Deep learning approaches have shown significant benefits compared to atlas-based methods in improving segmentation accuracy and efficiency in auto-segmentation algorithms. This work represents the first multi-institutional study to describe and evaluate an AI algorithm for the auto-segmentation of organs at risk (OARs) based on a deep image-to-image network (DI2IN). Materials/Methods: The AI-Rad Companion Organs RT (AIRC) algorithm(Siemens Healthineers, Erlangen, Germany) uses a two-step approach for segmentation. In the first step, the target organ region in the optimal input image is extracted using a trained deep reinforcement learning network (DRL), which is then used as input to create the contours in the second step based on DI2IN. The study was initially designed as a prospective single-center evaluation. The automated contours generated by AIRC were evaluated by three experienced board-certified radiation oncologists using a four-point scale where 4 is clinically usable and 1 requires re-contouring. After seeing favorable results in a single-center pilot study, we decided to expand the study to six additional institutions, encompassing eight additional evaluators for a total of 11 physician evaluators across seven institutions. Results: One hundred and fifty-six patients and 1366 contours were prospectively evaluated. The five most commonly contoured organs were the lung (136 contours, average rating = 4.0), spinal cord (106 contours, average rating = 3.1), eye globe (80 contours, average rating = 3.9), lens (77 contours, average rating = 3.9), and optic nerve (75 contours, average rating = 4.0). The average rating per evaluator per contour was 3.6. On average, 124 contours were evaluated by each evaluator. 65% of the contours were rated as 4, and 31% were rated as 3. Only 4% of contours were rated as 1 or 2. Thirty-three organs were evaluated in the study, with 19 structures having a 3.5 or above average rating (ribs, abdominopelvic cavity, skeleton, larynx, lung, aorta, brachial plexus, lens, eye globe, glottis, heart, parotid glands, bladder, kidneys, supraglottic larynx, submandibular glands, esophagus, optic nerve, oral cavity) and the remaining organs having a rating of 3.0 or greater (female breast, proximal femur, seminal vesicles, rectum, sternum, brainstem, prostate, brain, lips, mandible, liver, optic chiasm, spinal cord, spleen). No organ had an average rating below 3. Conclusion: AIRC performed well with greater than 95% of contours accepted by treating physicians with no or minor edits. It supported a fully automated workflow with the potential for time savings and increased standardization with the use of AI-powered algorithms for high-quality OAR contouring. [ABSTRACT FROM AUTHOR]

Published
2024
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46. Optimizing Radiation Therapy to Boost Systemic Immune Responses in Breast Cancer: A Critical Review for Breast Radiation Oncologists

Author

Ho, Alice Y., Wright, Jean L., Blitzblau, Rachel C., Mutter, Robert W., Duda, Dan G., Norton, Larry, Bardia, Aditya, Spring, Laura, Isakoff, Steven J., Chen, Jonathan H., Grassberger, Clemens, Bellon, Jennifer R., Beriwal, Sushil, Khan, Atif J., Speers, Corey, Dunn, Samantha A., Thompson, Alastair, Santa-Maria, Cesar A., Krop, Ian E., Mittendorf, Elizabeth, King, Tari A., and Gupta, Gaorav P.

Published
2020
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