Clinical acceptability of fully automated external beam radiotherapy for cervical cancer with three different beam delivery techniques. Issue 9 (26th July 2022)

• Record Type: Journal Article
• Authors: Rhee, Dong Joo; Jhingran, Anuja; Huang, Kai; Netherton, Tucker J.; Fakie, Nazia; White, Ingrid; Sherriff, Alicia; Cardenas, Carlos E.; Zhang, Lifei; Prajapati, Surendra; Kry, Stephen F.; Beadle, Beth M.; Shaw, William; O'Reilly, Frederika; Parkes, Jeannette; Burger, Hester; Trauernicht, Chris; Simonds, Hannah; Court, Laurence E.
• Is Part Of: Medical physics. Volume 49:Issue 9(2022)
• Page Start: 5742
• Page End: 5751
• Publication Date: 2022-07-26
• Subjects: auto‐contouring -- auto‐planning -- cervical cancer -- field‐in‐field; Medical physics -- Periodicals; Medical physics; Geneeskunde; Natuurkunde; Toepassingen; Biophysics; Periodicals; Periodicals; Electronic journals; 610.153
• DOI: 10.1002/mp.15868
• Languages: English
• ISSNs: 0094-2405

Abstract

Abstract: Purpose: To fully automate CT‐based cervical cancer radiotherapy by automating contouring and planning for three different treatment techniques. Methods: We automated three different radiotherapy planning techniques for locally advanced cervical cancer: 2D 4‐field‐box (4‐field‐box), 3D conformal radiotherapy (3D‐CRT), and volumetric modulated arc therapy (VMAT). These auto‐planning algorithms were combined with a previously developed auto‐contouring system. To improve the quality of the 4‐field‐box and 3D‐CRT plans, we used an in‐house, field‐in‐field (FIF) automation program. Thirty‐five plans were generated for each technique on CT scans from multiple institutions and evaluated by five experienced radiation oncologists from three different countries. Every plan was reviewed by two of the five radiation oncologists and scored using a 5‐point Likert scale. Results: Overall, 87%, 99%, and 94% of the automatically generated plans were found to be clinically acceptable without modification for the 4‐field‐box, 3D‐CRT, and VMAT plans, respectively. Some customizations of the FIF configuration were necessary on the basis of radiation oncologist preference. Additionally, in some cases, it was necessary to renormalize the plan after it was generated to satisfy radiation oncologist preference. Conclusion: Approximately, 90% of the automatically generated plans were clinically acceptable for all three planning techniques. This fully automated planning system has been implemented into the radiation planning assistant for further testing in resource‐constrained radiotherapy departments in low‐ and middle‐income countries.