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Purpose <p>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.</p> Methods and materials <p>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 (<i>δ</i>) evaluated at three discrete values (12, 15, and 18&#xa0;mm), where <i>δ</i> serves as a geometric surrogate for dose coverage, together with a geometric coverage-ratio threshold (<i>γ</i> = 98%) and a collision-free margin (<i>d</i>) 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.</p> Results <p>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 <i>δ</i> settings, <i>δ</i> = 15&#xa0;mm was selected for 16 patients and <i>δ</i> = 18&#xa0;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% (<i>P</i> = 0.024), consistently exceeding the 90% clinical threshold. The OAR sparing was no significant difference to manual planning: D<sub>2cc</sub> for the rectum (66.11 ± 3.99&#xa0;Gy vs. 66.46 ± 4.00&#xa0;Gy, <i>P</i> = 0.542), bladder (78.28 ± 5.16&#xa0;Gy vs. 79.45 ± 4.47&#xa0;Gy, <i>P</i> = 0.201), and sigmoid (63.30 ± 4.86&#xa0;Gy vs. 62.33 ± 6.84&#xa0;Gy, <i>P</i> = 0.916). The algorithm significantly reduced the average number of needles from 5.40 ± 0.94 to 4.25 ± 0.55 (<i>P</i> &lt; 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&#xa0;h (manual) to 8.2 ± 1.4&#xa0;min (GANTP), with algorithm execution taking less than 190&#xa0;s across all <i>δ</i> settings.</p> Conclusion <p>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.</p>

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A rapid semi-automated trajectory planning method for non-coplanar interstitial brachytherapy in cervical cancer using a greedy algorithm

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年6月23日

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  • Jiuling Shen,
  • Shaoxing Sun,
  • Zhiwei Xu,
  • Xiaoyong Wang,
  • Conghua Xie,
  • Hui Qiu,
  • Hui Liu

摘要

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.