Analysis of components of variance determining probability of setup errors in CBCT-guided stereotactic radiotherapy of lung tumors

A prospective observational study evaluating two patient immobilisation methods in lung stereotactic radiotherapy

PURPOSE

The main objective of this study was to assess inter- and intrafraction errors for two patient immobilisation devices in the context of lung stereotactic body radiation therapy: a vacuum cushion and a simple arm support.

MATERIALS AND METHODS

Twenty patients who were treated with lung stereotactic body radiation therapy in supine position with arms above their head were included in the study. Ten patients were setup in a vacuum cushion (Bluebag™, Elekta) and ten other patients with a simple arm support (Posirest™, Civco). A pretreatment four-dimensional cone-beam computed tomography and a post-treatment three-dimensional cone-beam computed tomography were acquired to compare positioning and immobilisation accuracy. Based on a rigid registration with the planning computed tomography on the spine at the target level, translational and rotational errors were reported.

RESULTS

The median number of fractions per treatment was 5 (range: 3-10). Mean interfraction errors based on 112 four-dimensional cone-beam computed tomographies were similar for both setups with deviations less than or equal to 1.3mm in lateral and vertical direction and 1.2° in roll and yaw. For longitudinal translational errors, mean interfraction errors were 0.7mm with vacuum cushion and -3.9mm with arm support. Based on 111 three-dimensional cone-beam computed tomographies, mean lateral, longitudinal and vertical intrafraction errors were -0.1mm, -0.2mm and 0.0mm respectively (SD: 1.0, 1.2 and 1.0mm respectively) for the patients setup with vacuum cushion, and mean vertical, longitudinal and lateral intrafraction errors were -0.3mm, -0.7mm and 0.1mm respectively (SD: 2.3, 1.8 and 1.4mm respectively) for the patients setup with arm support. Intrafraction errors means were not statistically different between both positions but standard deviations were statistically larger with arm support.

CONCLUSION

The results of our study showed similar inter and intrafraction mean deviations between both positioning but a large variability in intrafraction observed with arm support suggested a more accurate immobilization with vacuum cushion.

Machine-learning-based prediction of the effectiveness of the delivered dose by exhale-gated radiotherapy for locally advanced lung cancer: The additional value of geometric over dosimetric parameters alone

Purpose

This study aimed to assess interfraction stability of the delivered dose distribution by exhale-gated volumetric modulated arc therapy (VMAT) or intensity-modulated arc therapy (IMAT) for lung cancer and to determine dominant prognostic dosimetric and geometric factors.

Methods

Clinical target volume (CTV_Plan) from the planning CT was deformed to the exhale-gated daily CBCT scans to determine CTV_i, treated by the respective dose fraction. The equivalent uniform dose of the CTV_i was determined by the power law (gEUD_i) and cell survival model (EUD_iSF) as effectiveness measure for the delivered dose distribution. The following prognostic factors were analyzed: (I) minimum dose within the CTV_i (D_{min_i}), (II) Hausdorff distance (HDD_i) between CTV_i and CTV_Plan, (III) doses and deformations at the point in CTV_Plan at which the global minimum dose over all fractions per patient occurs (PD_{min_global_i}), and (IV) deformations at the point over all CTV_i margins per patient with the largest Hausdorff distance (HDPw_orst). Prognostic value and generalizability of the prognostic factors were examined using cross-validated random forest or multilayer perceptron neural network (MLP) classifiers. Dose accumulation was performed using back deformation of the dose distribution from CTV_i to CTV_Plan.

Results

Altogether, 218 dose fractions (10 patients) were evaluated. There was a significant interpatient heterogeneity between the distributions of the normalized gEUD_i values (p<0.0001, Kruskal-Wallis tests). Accumulated gEUD over all fractions per patient was 1.004-1.023 times of the prescribed dose. Accumulation led to tolerance of ~20% of fractions with gEUD_i <93% of the prescribed dose. Normalized D_min >60% was associated with predicted gEUD values above 95%. D_min had the highest importance for predicting the gEUD over all analyzed prognostic parameters by out-of-bag loss reduction using the random forest procedure. Cross-validated random forest classifier based on D_min as the sole input had the largest Pearson correlation coefficient (R=0.897) in comparison to classifiers using additional input variables. The neural network performed better than the random forest classifier, and the gEUD values predicted by the MLP classifier with D_min as the sole input were correlated with the gEUD values characterized by R=0.933 (95% CI, 0.913-0.948). The performance of the full MLP model with all geometric input parameters was slightly better (R=0.952) than that based on D_min (p=0.0034, Z-test).

Conclusion

Accumulated dose distributions over the treatment series were robust against interfraction CTV deformations using exhale gating and online image guidance. D_min was the most important parameter for gEUD prediction for a single fraction. All other parameters did not lead to a markedly improved generalizable prediction. Dosimetric information, especially location and value of D_min within the CTV _i , are vital information for image-guided radiation treatment.

Compare of Interfractional Setup Reproducibility Between Vacuum-Lock Bag and Thermoplastic Mask in Radiotherapy for Breast Cancer

Background: This study aimed to analyze the difference of setup reproducibility between Vacuum-lock bag and Thermoplastic mask in the radiotherapy for breast cancer. Methods: A total of 100 invasive breast carcinoma patients were collected, among whom 50 patients were immobilized with Vacuum-lock bag (VB group), and the other 50 patients were immobilized with Thermoplastic mask (TM group). Set up reproducibility in different axes and comfort levels between two groups at three treatment progress points during the radiation therapy were collected and analyzed. Results: The linear regression model showed that fixed device was an independent factor of radiotherapy setup error (SE). Further subgroup analysis based on different axes showed that the SE caused by the fixed device was obvious in all directions. The comfort level in the VB group was significantly larger than that in the TM group at the beginning of treatment, reduced as the treatment progress going on, and finally disappeared within three weeks. Conclusions: Thermoplastic mask could significantly reduce positioning errors in the radiotherapy of breast cancer. Although more discomfort was found in the TM group, it could be eliminated as the treatment progresses.

Psychosomatic symptoms affect radiotherapy setup errors in early breast cancer patients

Objective

To examine the trajectory of psychosomatic symptoms and to explore the impact of psychosomatic symptoms on setup error in patients undergoing breast cancer radiotherapy.

Methods

A total of 102 patients with early breast cancer who received initial radiotherapy were consecutively recruited. The M.D. Anderson Symptom Inventory (MDASI) and three different anxiety scales, i.e., the Self-Rating Anxiety Scale (SAS), State-Trait Anxiety Inventory (STAI), and Anxiety Sensitivity Index (ASI), were used in this study. The radiotherapy setup errors were measured in millimetres by comparing the real-time isocratic verification film during radiotherapy with the digitally reconstructed radiograph (DRR). Patients completed the assessment at three time points: before the initial radiotherapy (T1), before the middle radiotherapy (T2), and before the last radiotherapy (T3).

Results

The SAS and STAI-State scores of breast cancer patients at T1 were significantly higher than those at T2 and T3 (F=24.44, P<0.001; F=30.25, P<0.001). The core symptoms of MDASI were positively correlated with anxiety severity. The setup errors of patients with high SAS scores were greater than those of patients with low anxiety levels at T1 (Z=-2.01, P=0.044). We also found that higher SAS scores were associated with a higher risk of radiotherapy setup errors at T1 (B=0.458, P<0.05).

Conclusions

This study seeks to identify treatment-related psychosomatic symptoms and mitigate their impact on patients and treatment. Patients with early breast cancer experienced the highest level of anxiety before the initial radiotherapy, and then, anxiety levels declined. Patients with high somatic symptoms of anxiety may have a higher risk of radiotherapy setup errors.