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A rapid semi-automated trajectory planning method for non-coplanar interstitial brachytherapy in cervical cancer
Jiuling Shen1, Shaoxing Sun1, Zhiwei Xu2
1Department of Radiation and Medical Oncology, Hubei Key Laboratory of Tumor Biological Behaviors, Hubei Cancer Clinical Study Center, Zhongnan Hospital of Wuhan University, Wuhan, 430071, China.
Purpose:
Precise spatial distribution of interstitial needles is critical for 3D-printing-assisted brachytherapy in cervical cancer. This study proposes a greedy algorithm-based needle trajectory planning (GANTP) framework to generate patient-specific needle configurations while ensuring needle collision avoidance and achieving clinically acceptable high-risk clinical target volume (HR-CTV) coverage in compliance with OAR dose constraints.
Methods And Materials:
The GANTP framework comprises three core steps: (1) Generation of candidate trajectories anchored within clinically viable entry zones; (2) Parameter-driven greedy selection of needle trajectories based on a geometric influence radius (δ) evaluated at three discrete values (12, 15, and 18 mm), where δ serves as a geometric surrogate for dose coverage, together with a geometric coverage-ratio threshold (γ = 98%) and a collision-free margin (d) relative to the tandem; and (3) Dosimetric evaluation and inverse planning with dwell-time optimization. The framework was evaluated using CT datasets from 20 cervical cancer patients. Performance metrics, including HR-CTV coverage, organs-at-risk (OAR) doses (D2cc), needle counts, and efficiency, were compared against manual planning.
Results:
GANTP was able to generate clinically acceptable plans for all 20 cases. Based on a final-selection strategy that prioritized clinically acceptable HR-CTV coverage (≥ 90%) and the lowest needle count among the evaluated δ settings, δ = 15 mm was selected for 16 patients and δ = 18 mm for 4 patients as the final selected configurations. Compared to manual planning (HR-CTV coverage: 92.62 ± 1.51%), these Final Selected plans achieved clinically acceptable coverage of 91.96 ± 1.24% (P = 0.024), consistently exceeding the 90% clinical threshold. The OAR sparing was no significant difference to manual planning: D2cc for the rectum (66.11 ± 3.99 Gy vs. 66.46 ± 4.00 Gy, P = 0.542), bladder (78.28 ± 5.16 Gy vs. 79.45 ± 4.47 Gy, P = 0.201), and sigmoid (63.30 ± 4.86 Gy vs. 62.33 ± 6.84 Gy, P = 0.916). The algorithm significantly reduced the average number of needles from 5.40 ± 0.94 to 4.25 ± 0.55 (P < 0.001). The most substantial improvement was observed in one case (Patient 2), where the needle count was reduced from 7 to 4 while maintaining a coverage of 91.7%. The total planning workflow time was substantially reduced from 2 to 3 h (manual) to 8.2 ± 1.4 min (GANTP), with algorithm execution taking less than 190 s across all δ settings.
Conclusion:
GANTP establishes a semi-automated, patient-specific framework for generating collision-free, non-coplanar trajectories that meet clinical dosimetric goals with a reduced mean number of needles. Integrated with 3D-printed templates, this approach demonstrates significant potential for improving the precision and efficiency of interstitial brachytherapy. Future work will include phantom experiments for physical validation.

