Evaluating the impact of possible interobserver variability in CBCT-based soft-tissue matching using TCP/NTCP models for prostate cancer radiotherapy

Zhang, Xiangbin; Wang, Xin; Li, Xiaoyu; Zhou, Li; Nie, Shihong; Li, Changhu; Wang, Xuetao; Dai, Guyu; Deng, Zhonghua; Xiang, Zhongyuan

doi:10.1186/s13014-022-02034-1

Cited by 5 publications

(9 citation statements)

References 39 publications

(28 reference statements)

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“…With respect to rotation, the standard deviation exceeded 3° for 6% of the entire dataset, regardless of the axis. This study also observed inter‐observer variability, consistent with findings from previous studies 3,8,9,17–19 . These findings emphasize the need for auto‐matching techniques to minimize inter‐observer variability and achieve consistent soft‐tissue matching.…”

Section: Discussionsupporting

confidence: 90%

“…This study also observed inter-observer variability, consistent with findings from previous studies. 3,8,9,[17][18][19] These findings emphasize the need for auto-matching techniques to minimize inter-observer variability and achieve consistent soft-tissue matching.…”

Section: Inter-observer Variabilitymentioning

confidence: 78%

“…8 Furthermore, Zhang et al conducted an analysis of the impact of inter-observer variability, underscoring its greater influence on organs at risk (OARs) than on the target in prostate cancer. 9 Current radiotherapy systems are unable to overcome the well-acknowledged challenges associated with softtissue matching. To address these issues, automation must be implemented.…”

Section: Introductionmentioning

confidence: 99%

“…However, soft‐tissue matching faces several difficulties. Previous studies have consistently identified inter‐ and intra‐observer variability as great issues in soft‐tissue matching 3,8,9 . Hirose et al emphasized the importance of considering inter‐observer variability when determining the clinical target volume for PTV margins 3 .…”

Section: Introductionmentioning

confidence: 99%

“…Sasaki et al demonstrated substantial inter‐observer variability and increased time requirements for soft‐tissue matching in pancreatic cancer, particularly among trainees with limited experience in IGRT 8 . Furthermore, Zhang et al conducted an analysis of the impact of inter‐observer variability, underscoring its greater influence on organs at risk (OARs) than on the target in prostate cancer 9 …”

Section: Introductionmentioning

confidence: 99%

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Organ‐contour‐driven auto‐matching algorithm in image‐guided radiotherapy

Kishigami,

Nakamura,

Okamoto

et al. 2023

J Applied Clin Med Phys

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PurposeThis study aimed to demonstrate the potential clinical applicability of an organ‐contour‐driven auto‐matching algorithm in image‐guided radiotherapy.MethodsThis study included eleven consecutive patients with cervical cancer who underwent radiotherapy in 23 or 25 fractions. Daily and reference magnetic resonance images were converted into mesh models. A weight‐based algorithm was implemented to optimize the distance between the mesh model vertices and surface of the reference model during the positioning process. Within the cost function, weight parameters were employed to prioritize specific organs for positioning. In this study, three scenarios with different weight parameters were prepared. The optimal translation and rotation values for the cervix and uterus were determined based on the calculated translations alone or in combination with rotations, with a rotation limit of ±3°. Subsequently, the coverage probabilities of the following two planning target volumes (PTV), an isotropic 5 mm and anisotropic margins derived from a previous study, were evaluated.ResultsThe percentage of translations exceeding 10 mm varied from 9% to 18% depending on the scenario. For small PTV sizes, more than 80% of all fractions had a coverage of 80% or higher. In contrast, for large PTV sizes, more than 90% of all fractions had a coverage of 95% or higher. The difference between the median coverage with translational positioning alone and that with both translational and rotational positioning was 1% or less.ConclusionThis algorithm facilitates quantitative positioning by utilizing a cost function that prioritizes organs for positioning. Consequently, consistent displacement values were algorithmically generated. This study also revealed that the impact of rotational corrections, limited to ±3°, on PTV coverage was minimal.

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Section: Discussionsupporting

confidence: 90%

Section: Inter-observer Variabilitymentioning

confidence: 78%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Organ‐contour‐driven auto‐matching algorithm in image‐guided radiotherapy

Kishigami,

Nakamura,

Okamoto

et al. 2023

J Applied Clin Med Phys

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A retrospective comparison of setup accuracy from CBCT and SGRT data in breast cancer patients

Lastrucci,

Serventi,

Francolini

et al. 2024

Journal of Medical Imaging and Radiation Sciences

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Advantages and robustness of partial VMAT with prone position for neoadjuvant rectal cancer evaluated by CBCT-based offline adaptive radiotherapy

Zhang

Peng

et al. 2023

Radiat Oncol

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Background and purpose This study aims to explore the advantages and robustness of the partial arc combined with prone position planning technique for radiotherapy in rectal cancer patients. Adaptive radiotherapy is recalculated and accumulated on the synthesis CT (sCT) obtained by deformable image registration between planning CT and cone beam CT (CBCT). Full and partial volume modulation arc therapy (VMAT) with the prone position on gastrointestinal and urogenital toxicity, based on the probability of normal tissue complications (NTCP) model in rectal cancer patients were evaluated. Materials and methods Thirty-one patients were studied retrospectively. The contours of different structures were outlined in 155 CBCT images. First, full VMAT (F-VMAT) and partial VMAT (P-VMAT) planning techniques were designed and calculated using the same optimization constraints for each individual patient. The Acuros XB (AXB) algorithm was used in order to generate more realistic dose distributions and DVH, considering the air cavities. Second, the Velocity 4.0 software was used to fuse the planning CT and CBCT to obtain the sCT. Then, the AXB algorithm was used in the Eclipse 15.6 software to conduct re-calculation based on the sCT to obtain the corresponding dose. Furthermore, the NTCP model was used to analyze its radiobiological side effects on the bladder and the bowel bag. Results With a CTV coverage of 98%, when compared with F-VMAT, P-VMAT with the prone position technique can effectively reduce the mean dose of the bladder and the bowel bag. The NTCP model showed that the P-VMAT combined with the prone planning technique resulted in a significantly lower complication probability of the bladder (1.88 ± 2.08 vs 1.62 ± 1.41, P = 0.041) and the bowel bag (1.28 ± 1.70 vs 0.95 ± 1.52, P < 0.001) than the F-VMAT. In terms of robustness, P-VMAT was more robust than F-VMAT, considering that less dose and NTCP variation was observed in the CTV, bladder and bowel bag. Conclusion This study analyzed the advantages and robustness of the P-VMAT in the prone position from three aspects, based on the sCT fused by CBCT. Whether it is in regards to dosimetry, radiobiological effects or robustness, P-VMAT in the prone position has shown comparative advantages.

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Evaluating the impact of possible interobserver variability in CBCT-based soft-tissue matching using TCP/NTCP models for prostate cancer radiotherapy

Cited by 5 publications

References 39 publications

Organ‐contour‐driven auto‐matching algorithm in image‐guided radiotherapy

Organ‐contour‐driven auto‐matching algorithm in image‐guided radiotherapy

A retrospective comparison of setup accuracy from CBCT and SGRT data in breast cancer patients

Advantages and robustness of partial VMAT with prone position for neoadjuvant rectal cancer evaluated by CBCT-based offline adaptive radiotherapy

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