Purpose The purpose of this study was to validate a fully automatic treatment planning system for conventional radiotherapy of cervical cancer. This system was developed to mitigate staff shortages in low-resource clinics. Methods In collaboration with hospitals in South Africa and the United States, we have developed the Radiation Planning Assistant (RPA), which includes algorithms for automating every step of planning: delineating the body contour, detecting the marked isocenter, designing the treatment-beam apertures, and optimizing the beam weights to minimize dose heterogeneity. First, we validated the RPA retrospectively on 150 planning computed tomography (CT) scans. We then tested it remotely on 14 planning CT scans at two South African hospitals. Finally, automatically planned treatment beams were clinically deployed at our institution. Results The automatically and manually delineated body contours agreed well (median mean surface distance, 0.6 mm; range, 0.4 to 1.9 mm). The automatically and manually detected marked isocenters agreed well (mean difference, 1.1 mm; range, 0.1 to 2.9 mm). In validating the automatically designed beam apertures, two physicians, one from our institution and one from a South African partner institution, rated 91% and 88% of plans acceptable for treatment, respectively. The use of automatically optimized beam weights reduced the maximum dose significantly (median, −1.9%; P < .001). Of the 14 plans from South Africa, 100% were rated clinically acceptable. Automatically planned treatment beams have been used for 24 patients with cervical cancer by physicians at our institution, with edits as needed, and its use is ongoing. Conclusion We found that fully automatic treatment planning is effective for cervical cancer radiotherapy and may provide a reliable option for low-resource clinics. Prospective studies are ongoing in the United States and are planned with partner clinics.

Implementing new online adaptive radiation therapy technologies is challenging because extra clinical resources are required particularly expert contour review. Here, we provide the first assessment of Varian's Ethos™ adaptive platform for prostate cancer using no manual edits after auto-segmentation to minimize this impact on clinical efficiency. Methods: Twenty-five prostate patients previously treated at our clinic were re-planned using an Ethos™ emulator. Clinical target volumes (CTV) included intact prostate and proximal seminal vesicles. The following clinical margins were used: 3 mm posterior, 5 mm left/right/anterior, and 7 mm superior/inferior. Adapted plans were calculated for 10 fractions per patient using Ethos's autosegmentation and auto-planning workflow without manual contouring edits. Doses and auto-segmented structures were exported to our clinical treatment planning system where contours were modified as needed for all 250 CTVs and organs-at-risk. Dose metrics from adapted plans were compared to unadapted plans to evaluate CTV and OAR dose changes. Results: Overall 96% of fractions required auto-segmentation edits, although corrections were generally minor (<10% of the volume for 70% of CTVs, 88% of bladders, and 90% of rectums). However, for one patient the autosegmented CTV failed to include the superior portion of prostate that extended into the bladder at all 10 fractions resulting in under-contouring of the CTV by 31.3% ± 6.7%. For the 24 patients with minor auto-segmentation corrections, adaptation improved CTV D98% by 2.9% ± 5.3%. For non-adapted fractions where bladder or rectum V90% exceeded clinical thresholds, adaptation reduced them by 13.1% ± 1.0% and 6.5% ± 7.3%, respectively. Conclusion: For most patients, Ethos's online adaptive radiation therapy workflow improved CTV D98% and reduced normal tissue dose when structures would otherwise exceed clinical thresholds, even without time-consuming manual edits. However, for one in 25 patients, large contour edits were required and thus scrutiny of the daily auto-segmentation is necessary and not all patients will be good candidates for adaptation.

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Online adaptive radiotherapy platforms present a unique challenge for commissioning as guidance is lacking and specialized adaptive equipment, such as deformable phantoms, are rare. We designed a novel adaptive commissioning process consisting of end‐to‐end tests using standard clinical resources. These tests were designed to simulate anatomical changes regularly observed at patient treatments. The test results will inform users of the magnitude of uncertainty from on‐treatment changes during the adaptive workflow and the limitations of their systems. We implemented these tests for the cone‐beam computed tomography (CT)‐based Varian Ethos online adaptive platform. Many adaptive platforms perform online dose calculation on a synthetic CT (synCT). To assess the impact of the synCT generation and online dose calculation on dosimetric accuracy, we conducted end‐to‐end tests using commonly available equipment: a CIRS IMRT Thorax phantom, PinPoint ionization chamber, Gafchromic film, and bolus. Four clinical scenarios were evaluated: weight gain and weight loss were simulated by adding and removing bolus, internal target shifts were simulated by editing the CTV during the adaptive workflow to displace it, and changes in gas were simulated by removing and reinserting rods in varying phantom locations. The effect of overriding gas pockets during planning was also assessed. All point dose measurements agreed within 2.7% of the calculated dose, with one exception: a scenario simulating gas present in the planning CT, not overridden during planning, and dissipating at treatment. Relative film measurements passed gamma analysis (3%/3 mm criteria) for all scenarios. Our process validated the Ethos dose calculation for online adapted treatment plans. Based on our results, we made several recommendations for our clinical adaptive workflow. This commissioning process used commonly available equipment and, therefore, can be applied in other clinics for their respective online adaptive platforms.

Purpose: To develop and test two independent algorithms that automatically create the photon treatment fields for a four‐field box beam arrangement, a common treatment technique for cervical cancer in low‐ and middle‐income countries. Methods: Two algorithms were developed and integrated into Eclipse using its Advanced Programming Interface:3D Method: We automatically segment bony anatomy on CT using an in‐house multi‐atlas contouring tool and project the structures into the beam's‐eye‐view. We identify anatomical landmarks on the projections to define the field apertures. 2D Method: We generate DRRs for all four beams. An atlas of DRRs for six standard patients with corresponding field apertures are deformably registered to the test patient DRRs. The set of deformed atlas apertures are fitted to an expected shape to define the final apertures. Both algorithms were tested on 39 patient CTs, and the resulting treatment fields were scored by a radiation oncologist. We also investigated the feasibility of using one algorithm as an independent check of the other algorithm. Results: 96% of the 3D‐Method‐generated fields and 79% of the 2D‐method‐generated fields were scored acceptable for treatment (“Per Protocol” or “Acceptable Variation”). The 3D Method generated more fields scored “Per Protocol” than the 2D Method (62% versus 17%). The 4% of the 3D‐Method‐generated fields that were scored “Unacceptable Deviation” were all due to an improper L5 vertebra contour resulting in an unacceptable superior jaw position. When these same patients were planned with the 2D method, the superior jaw was acceptable, suggesting that the 2D method can be used to independently check the 3D method. Conclusion: Our results show that our 3D Method is feasible for automatically generating cervical treatment fields. Furthermore, the 2D Method can serve as an automatic, independent check of the automatically‐generated treatment fields. These algorithms will be implemented for fully automated cervical treatment planning.