Distance deviation measure of contouring variability

Background. Several methods that are currently used for contouring analysis have problems providing reliable and/ or meaningful results. In this paper a solution to these problems is proposed in a form of a novel measure, which was developed based on requirements defined for contouring studies. Materials and methods. The proposed distance deviation measure can be understood as an extension of the closest point measures in such a way that it does not measure only distances between points on contours but rather analyse deviation of distances to both/all contours from each image point/voxel. The obtained result is information rich, reliable and provided in a form of an image, enabling detailed topographic analysis. In addition to image representation, results can be further processed into angular representation for compact topographic analysis or into overall scalar estimates for quick assessment of contour disagreement. Results. Distance deviation method is demonstrated on a multi observer contouring example with complex contour shapes, i.e., with pronounced extremes and void interior. The results are presented using the three proposed methods. Conclusions. The proposed method can detect and measure contour variation irrespective of contour complexity and number of contour segments, while the obtained results are easy to interpret. It can be used in various situations, regarding the presence of reference contour or multiple test contours

Inclusion of geometric uncertainties in treatment plan evaluation

PURPOSE: To correctly evaluate realistic treatment plans in terms of absorbed dose to the clinical target volume (CTV), equivalent uniform dose (EUD), and tumor control probability (TCP) in the presence of execution (random) and preparation (systematic) geometric errors. MATERIALS AND METHODS: The dose matrix is blurred with all execution errors to estimate the total dose distribution of all fractions. To include preparation errors, the CTV is randomly displaced (and optionally rotated) many times with respect to its planned position while computing the dose, EUD, and TCP for the CTV using the blurred dose matrix. Probability distributions of these parameters are computed by combining the results with the probability of each particular preparation error. We verified the method by comparing it with an analytic solution. Next, idealized and realistic prostate plans were tested with varying margins and varying execution and preparation error levels. RESULTS: Probability levels for the minimum dose, computed with the new method, are within 1% of the analytic solution. The impact of rotations depends strongly on the CTV shape. A margin of 10 mm between the CTV and planning target volume is adequate for three-field prostate treatments given the accuracy level in our department; i.e., the TCP in a population of patients, TCP(pop), is reduced by less than 1% due to geometric errors. When reducing the margin to 6 mm, the dose must be increased from 80 to 87 Gy to maintain the same TCP(pop). Only in regions with a high-dose gradient does such a margin reduction lead to a decrease in normal tissue dose for the same TCP(pop). Based on a rough correspondence of 84% minimum dose with 98% EUD, a margin recipe was defined. To give 90% of patients at least 98% EUD, the planning target volume margin must be approximately 2.5 Sigma + 0.7 sigma - 3 mm, where Sigma and sigma are the combined standard deviations of the preparation and execution errors. This recipe corresponds accurately with 1% TCP(pop) loss for prostate plans with clinically reasonable values of Sigma and sigma. CONCLUSION: The new method computes in a few minutes the influence of geometric errors on the statistics of target dose and TCP(pop) in clinical treatment plans. Too small margins lead to a significant loss of TCP(pop) that is difficult to compensate for by dose escalatio

3D surface imaging for monitoring intrafraction motion in frameless stereotactic body radiotherapy of lung cancer

To investigate the accuracy of surface imaging for monitoring intrafraction motion purposes in frameless stereotactic body radiotherapy (SBRT) of lung cancer by comparison with cone-beam computed tomography (CBCT). Thirty-six patients (18 males, 18 females) were included. During each fraction, three CBCT scans were acquired; CBCT1: before treatment, CBCT2: after correction for tumor misalignment, and CBCT3: after treatment. Intrafraction motion was derived by registering CBCT2 and CBCT3 to the mid-ventilation planning CT scan. Surfaces were captured concurrently with CBCT acquisitions. Retrospectively, for each set of surfaces, an average surface was created: Surface1, Surface2, and Surface3. Subsequently, Surface3 was registered to Surface2 to assess intrafraction motion. For the differences between CBCT- and surface-imaging-derived 3D intrafraction motions, group mean, systematic error, random error and limits of agreement (LOA) were calculated. Group mean, systematic and random errors were smaller for females than for males: 0.4 vs. 1.3, 1.3 vs. 3.1, and 1.7 vs. 3.3mm respectively. For female patients deviations between CBCT-tumor- and 3D-surface-imaging-derived intrafraction motions were between -3.3 and 4.3mm (95% LOA). For male patients these were substantially larger: -5.9-9.5mm. Surface imaging is a promising technology for monitoring intrafraction motion purposes in SBRT for female patient

Respiratory correlated cone beam CT.

A cone beam computed tomography (CBCT) scanner integrated with a linear accelerator is a powerful tool for image guided radiotherapy. Respiratory motion, however, induces artifacts in CBCT, while the respiratory correlated procedures, developed to reduce motion artifacts in axial and helical CT are not suitable for such CBCT scanners. We have developed an alternative respiratory correlated procedure for CBCT and evaluated its performance. This respiratory correlated CBCT procedure consists of retrospective sorting in projection space, yielding subsets of projections that each corresponds to a certain breathing phase. Subsequently, these subsets are reconstructed into a four-dimensional (4D) CBCT dataset. The breathing signal, required for respiratory correlation, was directly extracted from the 2D projection data, removing the need for an additional respiratory monitor system. Due to the reduced number of projections per phase, the contrast-to-noise ratio in a 4D scan reduced by a factor 2.6-3.7 compared to a 3D scan based on all projections. Projection data of a spherical phantom moving with a 3 and 5 s period with and without simulated breathing irregularities were acquired and reconstructed into 3D and 4D CBCT datasets. The positional deviations of the phantoms center of gravity between 4D CBCT and fluoroscopy were small: 0.13 +/- 0.09 mm for the regular motion and 0.39 +/- 0.24 mm for the irregular motion. Motion artifacts, clearly present in the 3D CBCT datasets, were substantially reduced in the 4D datasets, even in the presence of breathing irregularities, such that the shape of the moving structures could be identified more accurately. Moreover, the 4D CBCT dataset provided information on the 3D trajectory of the moving structures, absent in the 3D data. Considerable breathing irregularities, however, substantially reduces the image quality. Data presented for three different lung cancer patients were in line with the results obtained from the phantom study. In conclusion, we have successfully implemented a respiratory correlated CBCT procedure yielding a 4D dataset. With respiratory correlated CBCT on a linear accelerator, the mean position, trajectory, and shape of a moving tumor can be verified just prior to treatment. Such verification reduces respiration induced geometrical uncertainties, enabling safe delivery of 4D radiotherapy such as gated radiotherapy with small margin

Estimation of heart-position variability in 3D-surface-image-guided deep-inspiration breath-hold radiation therapy for left-sided breast cancer

To investigate the heart position variability in deep-inspiration breath-hold (DIBH) radiation therapy (RT) for breast cancer when 3D surface imaging would be used for monitoring the BH depth during treatment delivery. For this purpose, surface setup data were compared with heart setup data. Twenty patients treated with DIBH-RT after breast-conserving surgery were included. Retrospectively, heart registrations were performed for cone-beam computed tomography (CBCT) to planning CT. Further, breast-surface registrations were performed for a surface, captured concurrently with CBCT, to planning CT. The resulting setup errors were compared with linear regression analysis. Furthermore, geometric uncertainties of the heart (systematic [Σ] and random [σ]) were estimated relative to the surface registration. Based on these uncertainties planning organ at risk volume (PRV) margins for the heart were calculated: 1.3Σ-0.5σ. Moderate correlation between surface and heart setup errors was found: R(2)=0.64, 0.37, 0.53 in left-right (LR), cranio-caudal (CC), and in anterior-posterior (AP) direction, respectively. When surface imaging would be used for monitoring, the geometric uncertainties of the heart (cm) are [Σ=0.14, σ=0.14]; [Σ=0.66, σ=0.38]; [Σ=0.27, σ=0.19] in LR; CC; AP. This results in PRV margins of 0.11; 0.67; 0.25cm in LR; CC; AP. When DIBH-RT after breast-conserving surgery is guided by the breast-surface position then PRV margins should be used to take into account the heart-position variability relative to the breast-surfac

Local interfractional setup reproducibility for 2 individual head and neck supports in head and neck cancer patients

In radiation therapy, head and neck (H&N) supports and thermoplastic masks are used to reproduce the setup of patients for H&N treatment. Individualized supports that include the shoulders may improve the immobilization of the upper thorax region. The purpose of this study was to compare the local misalignment of the supraclavicular region using a vacuum cushion H&N support to a more simple in-house modified, clinically standard H&N support. Two groups of 15 patients were evaluated: the first group of patients was positioned using a vacuum cushion as an individual head support and the second group with a modified Posifix headrest (MPH). A total of 316 cone beam computed tomography (CBCTs; ~ 10 scans per patient) were evaluated using a multiple region of interest registration protocol. Local setup errors were measured using chamfer matching on the CBCT scan to the planning CT scan for 9 bony structures (cervical vertebrae 1, 3, 5, and 7 [C7], lower jaw, hyoid bone, larynx, skull, and jugular notch). In this study, we compared the local residual misalignments of the bony structures and in particular those of the jugular notch and C7 as surrogates of the shoulders and thorax region. The workload was qualitatively evaluated on the basis of open interviews. The significant differences in group mean, systematic error, and random error of the local residual misalignments between the 2 groups for jugular notch and C7 were equal or smaller than 0.5 mm and 0.1 degrees, and for the other 7 bony structures were equal to or smaller than 0.6 mm and 1.2 degrees (larynx). There were no large differences in workload. No clinically relevant differences were found between a modified Posifix headrest and an individual vacuum cushion for H&N cancer patients in local posture change at the level of the clavicle and upper thora