Impact of delivery time factor on treatment time and plan quality in tomotherapy

Yagihashi, Takayuki; Inoue, Tatsuya; Shiba, Shintaro; Yamano, Akihiro; Minagawa, Yumiko; Omura, Motoko; Inoue, Kazumasa; Nagata, Hironori

doi:10.1038/s41598-023-39047-z

Cited by 3 publications

(3 citation statements)

References 44 publications

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“…Although the A-TOMO plan improved work efficiency, the treatment delivery time was longer compared to M-TOMO plans. This could be due to several reasons, including more stringent dose constraints and the DTF parameter in A-TOMO plans being set to 1.7, which made the execution time of each rotation approximately 20 s. A previous study indicated that increasing the DTF, while improving plan quality, also led to longer dose delivery times [ 37 ]. However, this did not increase the modulation of the A-TOMO plan.…”

Section: Discussionmentioning

confidence: 99%

Development and validation of an automated Tomotherapy planning method for cervical cancer

Han,

Xue,

Huang

et al. 2024

Radiat Oncol

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Purpose This study aimed to develop an automated Tomotherapy (TOMO) planning method for cervical cancer treatment, and to validate its feasibility and effectiveness. Materials and methods The study enrolled 30 cervical cancer patients treated with TOMO at our center. Utilizing scripting and Python environment within the RayStation (RaySearch Labs, Sweden) treatment planning system (TPS), we developed automated planning methods for TOMO and volumetric modulated arc therapy (VMAT) techniques. The clinical manual TOMO (M-TOMO) plans for the 30 patients were re-optimized using automated planning scripts for both TOMO and VMAT, creating automated TOMO (A-TOMO) and automated VMAT (A-VMAT) plans. We compared A-TOMO with M-TOMO and A-VMAT plans. The primary evaluated relevant dosimetric parameters and treatment plan efficiency were assessed using the two-sided Wilcoxon signed-rank test for statistical analysis, with a P-value < 0.05 indicating statistical significance. Results A-TOMO plans maintained similar target dose uniformity compared to M-TOMO plans, with improvements in target conformity and faster dose drop-off outside the target, and demonstrated significant statistical differences (P+ < 0.01). A-TOMO plans also significantly outperformed M-TOMO plans in reducing V50Gy, V40Gy and Dmean for the bladder and rectum, as well as Dmean for the bowel bag, femoral heads, and kidneys (all P+ < 0.05). Additionally, A-TOMO plans demonstrated better consistency in plan quality. Furthermore, the quality of A-TOMO plans was comparable to or superior than A-VMAT plans. In terms of efficiency, A-TOMO significantly reduced the time required for treatment planning to approximately 20 min. Conclusion We have successfully developed an A-TOMO planning method for cervical cancer. Compared to M-TOMO plans, A-TOMO plans improved target conformity and reduced radiation dose to OARs. Additionally, the quality of A-TOMO plans was on par with or surpasses that of A-VMAT plans. The A-TOMO planning method significantly improved the efficiency of treatment planning.

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Section: Discussionmentioning

confidence: 99%

Development and validation of an automated Tomotherapy planning method for cervical cancer

Han,

Xue,

Huang

et al. 2024

Radiat Oncol

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“…The PTV plans were optimized using the same prescription as the robust plans; however, the target was the PTV. The calculation parameters were as follows: a 2.5-cm field width, 0.287 pitch, 1.8 delivery time factor (16), and collapsed cone convolution algorithm with a 2-mm dose grid size. Treatment planning details, such as dose optimization parameters, were as described previously (10).…”

Section: Methodsmentioning

confidence: 99%

Comparing Efficacy Between Robust and PTV Margin-based Optimizations for Interfractional Anatomical Variations in Prostate Tomotherapy

YAGIHASHI,

INOUE,

SHIBA

et al. 2023

In Vivo

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Background/Aim: Interfractional anatomical variations cause considerable differences between planned and actual radiotherapy doses. This study aimed to investigate the efficacy of robust and planning target volume (PTV) margin-based optimizations for the anatomical variations in helical tomotherapy for prostate cancer. Patients and Methods: Ten patients underwent treatment-planning kilovolt computed tomography (kVCT) and daily megavolt computed tomography (MVCT). Two types of nominal plans, with a prescription of 60 Gy/20 fractions, were created using robust and PTV margin-based optimizations on kVCT for each patient. Subsequently, the daily estimated doses were recalculated using nominal plans, and all available MVCTs modified the daily patient-setup errors. Due to the difference in dose calculation accuracy between kVCT and MVCT, three scenarios with dose corrections of 1, 2, and 3% were considered in the recalculation process. The dosimetric metrics, including target coverage with the prescription dose, Paddick's conformity index, homogeneity index, and mean dose to the rectum, were analyzed. Results: A dosimetric comparison of the nominal plans demonstrated that the robust plans had better dose conformity, lower target coverage, and dose homogeneity than the PTV plans. In the daily estimated doses of any dose-corrected scenario, the target coverage and dose sparing to the rectum in the robust plans were significantly higher than those in the PTV plans, whereas dose conformity and homogeneity were identical to those of the nominal case. Conclusion: Robust optimization is recommended as it accounts for anatomical variations during treatment regarding target coverage in helical tomotherapy plans for prostate cancer.

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“…Furthermore, there have been limited studies reporting on the performance of sCTs for H&N RT plans, which tend to be very highly modulated. 13 , 33 , 34 , 35 Characterizing the effect of voxel misassignments in highly modulated treatment plans developed on sCT could allow for the development of QA criteria for the clinical implementation of H&N MRI‐only radiotherapy.…”

Section: Introductionmentioning

confidence: 99%

Evaluating the Hounsfield unit assignment and dose differences between CT‐based standard and deep learning‐based synthetic CT images for MRI‐only radiation therapy of the head and neck

Singhrao,

Dugan,

Calvin

et al. 2023

J Applied Clin Med Phys

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BackgroundMagnetic resonance image only (MRI‐only) simulation for head and neck (H&N) radiotherapy (RT) could allow for single‐image modality planning with excellent soft tissue contrast. In the MRI‐only simulation workflow, synthetic computed tomography (sCT) is generated from MRI to provide electron density information for dose calculation. Bone/air regions produce little MRI signal which could lead to electron density misclassification in sCT. Establishing the dosimetric impact of this error could inform quality assurance (QA) procedures using MRI‐only RT planning or compensatory methods for accurate dosimetric calculation.PurposeThe aim of this study was to investigate if Hounsfield unit (HU) voxel misassignments from sCT images result in dosimetric errors in clinical treatment plans.MethodsFourteen H&N cancer patients undergoing same‐day CT and 3T MRI simulation were retrospectively identified. MRI was deformed to the CT using multimodal deformable image registration. sCTs were generated from T1w DIXON MRIs using a commercially available deep learning‐based generator (MRIplanner, Spectronic Medical AB, Helsingborg, Sweden). Tissue voxel assignment was quantified by creating a CT‐derived HU threshold contour. CT/sCT HU differences for anatomical/target contours and tissue classification regions including air (<250 HU), adipose tissue (–250 HU to –51 HU), soft tissue (–50 HU to 199 HU), spongy (200 HU to 499 HU) and cortical bone (>500 HU) were quantified. t‐test was used to determine if sCT/CT HU differences were significant. The frequency of structures that had a HU difference > 80 HU (the CT window‐width setting for intra‐cranial structures) was computed to establish structure classification accuracy. Clinical intensity modulated radiation therapy (IMRT) treatment plans created on CT were retrospectively recalculated on sCT images and compared using the gamma metric.ResultsThe mean ratio of sCT HUs relative to CT for air, adipose tissue, soft tissue, spongy and cortical bone were 1.7 ± 0.3, 1.1 ± 0.1, 1.0 ± 0.1, 0.9 ± 0.1 and 0.8 ± 0.1 (value of 1 indicates perfect agreement). T‐tests (significance set at t = 0.05) identified differences in HU values for air, spongy and cortical bone in sCT images compared to CT. The structures with sCT/CT HU differences > 80 HU of note were the left and right (L/R) cochlea and mandible (>79% of the tested cohort), the oral cavity (for 57% of the tested cohort), the epiglottis (for 43% of the tested cohort) and the L/R TM joints (occurring > 29% of the cohort). In the case of the cochlea and TM joints, these structures contain dense bone/air interfaces. In the case of the oral cavity and mandible, these structures suffer the additional challenge of being positionally altered in CT versus MRI simulation (due to a non‐MR safe immobilizing bite block requiring absence of bite block in MR). Finally, the epiglottis HU assignment suffers from its small size and unstable positionality. Plans recalculated on sCT yielded global/local gamma pass rates of 95.5% ± 2% (3 mm, 3%) and 92.7% ± 2.1% (2 mm, 2%). The largest mean differences in D95, Dmean, D50 dose volume histogram (DVH) metrics for organ‐at‐risk (OAR) and planning tumor volumes (PTVs) were 2.3% ± 3.0% and 0.7% ± 1.9% respectively.ConclusionsIn this cohort, HU differences of CT and sCT were observed but did not translate into a reduction in gamma pass rates or differences in average PTV/OAR dose metrics greater than 3%. For sites such as the H&N where there are many tissue interfaces we did not observe large scale dose deviations but further studies using larger retrospective cohorts are merited to establish the variation in sCT dosimetric accuracy which could help to inform QA limits on clinical sCT usage.

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Impact of delivery time factor on treatment time and plan quality in tomotherapy

Cited by 3 publications

References 44 publications

Development and validation of an automated Tomotherapy planning method for cervical cancer

Development and validation of an automated Tomotherapy planning method for cervical cancer

Comparing Efficacy Between Robust and PTV Margin-based Optimizations for Interfractional Anatomical Variations in Prostate Tomotherapy

Evaluating the Hounsfield unit assignment and dose differences between CT‐based standard and deep learning‐based synthetic CT images for MRI‐only radiation therapy of the head and neck

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