Medical Dosimetry最新文献

Background/objectives: The advantages of intensity modulated radiotherapy (IMRT) in target coverage and organ at risk (OAR) sparing come with a low- and intermediate-dose bath effect. To control this unwanted dose dumping, planners use helping structures in the plan optimization. We hypothesized that using an anatomic definition of the posterior neck would result in reduced doses to the posterior neck muscles without compromising target coverage or increasing doses to organs at risk.

Methods: We randomly selected twelve head and neck cancer patients treated with volume modulated arc therapy (VMAT). For each case, we generated 3 plans with different optimization methods: first, with a dummy volume behind the spinal vertebrae; second, a volume with the posterior neck and upper shoulder muscles according to anatomic criteria; and third, a plan without any helping structure.

Results: There was no statistically significant difference between the 3 plans in terms of coverage, conformity index or homogeneity index. All the OAR dose constraints were respected, and there was no significant increase of the dose to these organs when the anatomic definition for the posterior neck was used. However, the posterior neck muscles and upper shoulder muscles received significantly lower mean doses, 31.9 Gy vs 36.8 Gy vs 37.6 Gy, p = 0.0004.

Conclusions: Using an anatomically defined posterior neck avoidance volume in the plan optimization significantly reduces doses to the posterior neck and upper shoulder muscles, potentially with less severe neck fibrosis, without compromising target volume coverage or increasing doses to other organs at risk.

We have trained and externally validated a knowledge-based planning model for radiation therapy planning in the setting of high-grade glioma. Model performance and utility in the context of clinical trial radiotherapy quality assurance (RTQA) are presented. A RapidPlan (RP) model was trained on 65 cases and tested on an additional 20 cases that were manually optimized and delivered within our institution. The model was externally validated on 34 cases that were manually optimized and treated at four outside institutions. These cases were selected to have target overlap with the brainstem or optic pathways. RapidPlan-generated plans were evaluated against planning objectives and manually optimized clinical plans. Cases were classified as (1) Clinical plan was superior, (2) Clinical plan was within 5 % of RP, or (3) Clinical plan could be improved. The clinical plan was characterized as superior for an objective if the metric was >5 % better than in the RP plan or if the clinical plan met the objective but the RP plan did not. Possible clinical plan improvement was indicated for an objective if the metric was >5 % better in the RP plan, or if the RP plan met the objective but the clinical plan did not. A Wilcoxon signed-rank test with a p < 0.05 significance threshold was used to determine if differences in PTV coverage, OAR doses and MU were statistically significant. Eight of 34 RP plans met all planning objectives in a single optimization, while an additional six met all normal tissue objectives while compromising target coverage. In more than 80 % of cases, when an objective was not achieved by RP, it was also not achieved in the manually optimized plan. Comparisons of clinical plans and RapidPlan indicated that statistically significant improvement was possible for Optic Nerve D_max and Optics PRV V₅₄; however, RP also introduced a statistically significant increase in D_max overall. Clinical plans could have been improved for individual planning objectives 24 to 68 % of the time, while the clinical plans were considered superior to RP for individual planning objectives 9 to 51 % of the time. Improvement in PTV coverage was possible for 18 % of clinical plans. The presented RapidPlan model for high-grade glioma performs well for cases both within and outside our institution. The model has demonstrated the capacity to reduce normal tissue dose to optic structures and to provide feedback in the context of clinical trial plan RTQA.

This study evaluated knowledge-based planning (KBP) models for prostate cancer, focusing on cases where the bowel lies close to the planning target volume excluding the rectum (PTV-R). Such proximity increases toxicity risk, raising the question of whether a Special Model (Model-S) is required. Although General Models are widely applicable, their performance in bowel proximity cases remains uncertain. A General Model (Model-G) was trained with 30 standard cases and a Model-S with 30 bowel proximity cases. Thirteen additional proximity cases were used for independent evaluation. RapidPlan-generated plans (Plan-G and Plan-S) were compared with clinically used manual plans (Plan-M). Plan quality was evaluated using D98% and D2% for targets, dose-volume indices for the rectum and bladder, and D0.1/D1 cc for the bowel. Statistical analyses employed the Mann-Whitney U and paired t-tests (p < 0.05). In the independent evaluation, Plan-M achieved significantly lower D2% than Plan-G (p < 0.001), while Plan-S showed no significant difference (P = 0.069). Organ-at-risk sparing was comparable across all plans (p > 0.05). Among the 13 evaluation cases, one Plan-G slightly exceeded the bowel D1 cc constraint of 60 Gy, indicating that in such bowel-descended cases, manual re-optimization or use of the Special Model may be required, defining the boundary where General Models remain reliable. Both models yielded clinically acceptable plans, and no clear dosimetric advantage was observed for the Special Model. These findings demonstrate the robustness of KBP against anatomical variability and highlight its potential as a foundation for future AI-assisted adaptive radiotherapy frameworks.

Linear accelerators (linac) with embedded magnetic resonance (MR) imaging involves a specific workflow that includes systematically a deformable image registration (DIR) with computed tomography images for the management of electron densities. Poor quality registration outputs could cause suboptimal dose calculations and planning treatments. The treatment planning system of the 0.35 T MR-linac MRIdian (ViewRay Inc., Oakwood Village) includes such a multimodal DIR tool with several adjustable parameters. To assist Viewray's users, this work investigates the influence of each parameter from the DIR tool. The default set of DIR parameters has been questioned through body locations (Thorax, Abdomen, Pelvis) and two quantitative metrics (the mutual information and mean absolute error). While the iterations number could be higher defined by default, the pyramidal number parameters (or control grid with a low impact) should be more carefully escalated. The default regularization parameters are consistent; both ways ensure optimal results, and the stiffness default value should be considered as a safeguard against unrealistic deformations. Depending on the location considered, the same variation in a specific parameter can have different effects on the registration results. Although the quantitative metrics are not directly correlated with the quality of the registrations, this work should help users manage and optimize the DIR step.

Aim: This study investigates the clinical performance and efficacy of generalized Equivalent Uniform Dose (gEUD) objectives in Volumetric Modulated Arc Therapy (VMAT) planning for Head and Neck Cancer (HNC) using the Halcyon LINAC Photon Optimizer (PO) engine.

Materials and methods: 50 HNC patients previously treated with Dose Volume (DV) based Halcyon VMAT plans were retrospectively selected. gEUD based plans were generated by re-planning the DV plans using gEUD objectives for organs at risk (OARs) and a combination of gEUD and DV objectives for PTVs, while maintaining consistent beam geometry and other optimization parameters. Target coverage (D95%, D98%, Dmean, D2%, V105%, CI, HI), OAR doses (mean and maximum), and treatment delivery parameters (MU, MF, BOT, PD gamma pass rate) were compared between the 2 planning strategies. A 2-tailed paired Student's t-test was used for statistical analysis, and box-and-whisker plots were generated.

Results: The gEUD based planning achieved comparable PTV coverage and homogeneity to DV based planning. Critically, gEUD optimization significantly reduced mean parotid doses (p < 0.05). Substantial reductions in spinal cord and mandible doses were also observed with gEUD planning (p < 0.001). While small increases in brain dose were noted with gEUD, they remained below clinical tolerance limits. No significant differences were found in treatment delivery parameters or PD QA pass rates.

Conclusion: The gEUD based VMAT planning for HNC using the Halcyon LINAC demonstrates significant OAR sparing, particularly for parotids, spinal cord, and mandible, without compromising target coverage or delivery efficiency. These findings support the clinical implementation of gEUD optimization for HNC to potentially reduce treatment-related toxicity and improve the therapeutic window.

To perform a comprehensive dosimetric comparison between the ZAP-X gyroscopic radiosurgery system and the CyberKnife (CK) robotic platform for the treatment of uveal melanoma (UM), with a focus on target coverage, organ at risk (OAR) sparing, plan quality metrics and treatment delivery efficiency. A total of 45 uveal melanoma patients previously treated with the CK system were retrospectively analyzed. For each patient, treatment plans were generated for both the ZAP-X and CK platforms using identical contouring datasets, shell structures, optimization parameters and dose calculation algorithms. Dosimetric parameters related to target coverage and OARs were compared, along with conformity index (CI), new conformity index (nCI), homogeneity index (HI), gradient indices (GI50% and GI25%), monitor units (MU) and estimated treatment times. Both systems achieved adequate target coverage with no significant difference in PTV D98% values. ZAP-X demonstrated significantly higher D_max, lower CI and nCI, and steeper dose gradients (GI50%, GI25%) compared to CK (p < 0.001 for all), indicating better conformity and dose fall-off. ZAP-X also delivered significantly lower doses to several OARs (p < 0.05 for all), including the optic nerves, contralateral eye, lenses, vitreous humor, lacrimal gland and brain. Although ZAP-X required more MUs per fraction, it achieved shorter treatment times. ZAP-X offers superior dose conformity, sharper dose gradients, and improved OAR sparing for uveal melanoma treatment without increasing treatment duration. While further clinical validation is required, these results support the potential of ZAP-X as a promising stereotactic radiosurgery platform for ocular tumors.

This study aimed to investigate the variable relative biological effectiveness with respect to the fixed RBE (1.1) on the prostate intensity-modulated-proton-therapy (IMPT), specifically focusing on normal tissue complication probabilities (NTCPs) in organs-at-risk (OARs) surrounding prostate tumors. The primary objective was to compare NTCP values between plans with fixed RBE (1.1) and plans with variable RBEs, considering the potential implications on treatment outcomes and normal tissue toxicity. Twelve prostate cancer patients undergoing simultaneous-integrated-boost treatments on a focal intraprostatic tumor (IPT) were studied. A linear function of the dose-averaged linear-energy-transfer (LET_d) was utilized to generate variable RBEs. IMPT plans with fixed RBE (1.1) and variable RBEs were generated with the same beam and spot parameters. Dosimetric evaluations, including dose-volume histograms (DVHs) with RBE weighted doses, were performed to assess the impact of RBE variations on dose distribution. NTCP calculations were conducted using the Lyman-Kutcher-Burman (LKB) Probit model to quantify the risk of normal tissue complications in the bladder wall and rectal wall. The analysis revealed notable differences in NTCP values between plans with fixed and variable RBEs. The bladder wall and rectal wall showed increased NTCP values in plans with variable RBEs compared to fixed RBE plans. The average NTCP differences were 5.7% for the bladder wall and 4.6% for the rectal wall, with maximum differences reaching 9.5%. These variations were attributed to the doses lying in the steep region, where even slight dose increases resulted in significant NTCP elevations. Incorporating variable RBEs in proton therapy treatment planning leads to higher NTCP values in OARs, indicating an increased risk of normal tissue complications. This highlights the importance of accurately accounting for RBE variations to optimize treatment outcomes and minimize the potential for radiation-induced toxicities in surrounding organs.