Linda Rossi

Rule-based AI automated adaptive treatment planning for image guided cervical cancer brachytherapy

A rule-based AI system for automated adaptive treatment planning for image guided adaptive brachytherapy (IGABT) of locally advanced cervical cancer (LACC) was developed at Erasmus MC, and internally and externally validated by Erasmus MC and Tata Memorial Centre (TMC), respectively. The BiCycle system generates automated plans with adapted requirements for each fraction, considering previously delivered external beam radiotherapy (EBRT) and BT doses, according EMBRACE-II protocol. It optimizes dosimetric parameters and loading patterns for available radioactive source positions. The system's effectiveness was validated by comparing automatically generated plans (AUTO) with manually generated, clinically delivered plans (MANUAL) of (1) dosimetry parameters and loading pattern visual inspection of 15 previously treated patients, for internal validation and (2) dosimetry and qualitative comparison by two TMC physicians of 20 previously treated patients, for external validation. With comparable target doses, AUTO plans had reduced D A novel AI-system for fully automated IGABT treatment planning for LACC allowed high-quality plan optimization in on average 1.6 min. AUTO plans were considered superior in quality compared to MANUAL plans in both internal and external validations, even without optimizing the system's configuration for the external center.

Prospective evaluation of AI-based BiCycle autoplanning for advanced cervical cancer brachytherapy

Rule-based AI BiCycle autoplanning compared favorably with manual planning in retrospective planning studies. In this study, we prospectively evaluated BiCycle's 'real life' impact by running it in parallel to current manual planning. Apart from dosimetric evaluations, treating physicians scored plans, and planning times were recorded. Following clinical routine, in each brachytherapy fraction, an RTT manually generated a plan which was then optionally adjusted by the treating physician, yielding the Man_Adj plan that was delivered. After treatment, a plan was automatically generated using BiCycle, followed by optional adjustment by the treating physician in the clinical TPS (Auto_Adj plan). Man_Adj and Auto_Adj plans were mutually compared and all planning time recorded. Physicians scored plan quality differences. For 28 of 37 evaluated fractions, the treating physician scored a higher quality for the Auto_Adj plan, in 7 fractions there was parity, and for 2 fractions Man_Adj was preferred. With comparable CTV For 95% of fractions, the treatment plan based on autoplanning was either preferred by the involved physician (76% of fractions) or considered similar in quality as the clinical plan (19%). Planning time reduced from 44.1 min for the manual workflow to 9.4 min. The system has recently been clinically introduced, following with the EU Medical Device Regulation.

Automated planning of curved needle channels in 3D printed patient-tailored applicators for cervical cancer brachytherapy

Abstract Purpose. Patient-tailored intracavitary/interstitial (IC/IS) brachytherapy (BT) applicators may increase dose conformity in cervical cancer patients. Current configuration planning methods in these custom applicators rely on manual specification or a small set of (straight) needles. This work introduces and validates a two-stage approach for establishing channel configurations in the 3D printed patient-tailored ARCHITECT applicator. Methods. For each patient, the patient-tailored applicator shape was based on the first BT application with a commercial applicator and integrated connectors to a commercial (Geneva) intrauterine tube and two lunar ring channels. First, a large candidate set was generated of channels that steer the needle to desired poses in the target region and are contained in the applicator. The channels’ centrelines were represented by Bézier curves. Channels running between straight target segments and entry points were optimised and refined to ensure (dynamic) feasibility. Second, channel configurations were selected using geometric coverage optimisation. This workflow was applied to establish patient-tailored geometries for twenty-two patients previously treated using the Venezia applicator. Treatment plans were automatically generated using the in-house developed algorithm BiCycle. Plans for the clinically used configuration, T P clin , and patient-tailored configuration, T P arch , were compared. Results. Channel configurations could be generated in clinically feasible time (median: 2651 s, range 1826–3812 s). All T P arch and T P clin plans were acceptable, but planning aims were more frequently attained with patient-tailored configurations (115/132 versus 100/132 instances). Median CTVIR D 98 and bladder D 2 c m 3 doses significantly improved ( p < 0.001 and p < 0.01 respectively) in T P arch plans in comparison with T P clin plans, and in approximately half of the patients dosimetric indices improved. Conclusion. Automated patient-tailored BT channel configuration planning for 3D printed applicators is clinically feasible. A treatment planning study showed that all plans met planning limits for the patient-tailored configurations, and in selected cases improved the plan quality in comparison with commercial applicator configurations.

Clinical Feasibility of the ARCHITECT Applicator in Cervical Cancer Brachytherapy

This prospective, non-randomised, single centre, phase I trial assesses the clinical feasibility of the use of the patient-tailored ARCHITECT applicator in locally advanced cervical cancer brachytherapy.