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

Assessment of set-up variability during deep inspiration breath hold radiotherapy for breast cancer patients by 3D-surface imaging

To quantify set-up uncertainties during voluntary deep inspiration breath hold (DIBH) radiotherapy using 3D-surface imaging in patients with left sided breast cancer. Nineteen patients were included. Cone-beam CT-scan (CBCT) was used for online set-up correction while patients were instructed to perform a voluntary DIBH. The reproducibility of the DIBH during treatment was monitored with 2D-fluoroscopy and portal imaging. Simultaneously, a surface imaging system was used to capture 3D-surfaces throughout CBCT acquisition and delivery of treatment beams. Retrospectively, all captured surfaces were registered to the planning-CT surface. Interfraction, intra-fraction and intra-beam set-up variability were quantified in left-right, cranio-caudal and anterior-posterior direction. Inter-fraction systematic (Σ) and random (σ) translational errors (1SD) before and after set-up correction were between 0.20-0.50 cm and 0.09-0.22 cm, respectively, whereas rotational Σ and σ errors were between 0.08 and 1.56°. The intra-fraction Σ and σ errors were ≤ 0.14 cm and ≤ 0.47°. The intra-beam SD variability was ≤ 0.08 cm and ≤ 0.28° in all directions. Quantification of 3D set-up variability in DIBH RT showed that patients are able to perform a very stable and reproducible DIBH within a treatment fraction. However, relatively large inter-fraction variability requires online image guided set-up correction

Accuracy evaluation of a 3-dimensional surface imaging system for guidance in deep-inspiration breath-hold radiation therapy

To investigate the applicability of 3-dimensional (3D) surface imaging for image guidance in deep-inspiration breath-hold radiation therapy (DIBH-RT) for patients with left-sided breast cancer. For this purpose, setup data based on captured 3D surfaces was compared with setup data based on cone beam computed tomography (CBCT). Twenty patients treated with DIBH-RT after breast-conserving surgery (BCS) were included. Before the start of treatment, each patient underwent a breath-hold CT scan for planning purposes. During treatment, dose delivery was preceded by setup verification using CBCT of the left breast. 3D surfaces were captured by a surface imaging system concurrently with the CBCT scan. Retrospectively, surface registrations were performed for CBCT to CT and for a captured 3D surface to CT. The resulting setup errors were compared with linear regression analysis. For the differences between setup errors, group mean, systematic error, random error, and 95% limits of agreement were calculated. Furthermore, receiver operating characteristic (ROC) analysis was performed. Good correlation between setup errors was found: R(2)=0.70, 0.90, 0.82 in left-right, craniocaudal, and anterior-posterior directions, respectively. Systematic errors were ≤0.17 cm in all directions. Random errors were ≤0.15 cm. The limits of agreement were -0.34-0.48, -0.42-0.39, and -0.52-0.23 cm in left-right, craniocaudal, and anterior-posterior directions, respectively. ROC analysis showed that a threshold between 0.4 and 0.8 cm corresponds to promising true positive rates (0.78-0.95) and false positive rates (0.12-0.28). The results support the application of 3D surface imaging for image guidance in DIBH-RT after BC

Kilo-voltage cone-beam computed tomography setup measurements for lung cancer patients;:First clinical results and comparison with electronic portal-imaging device.

PURPOSE: Kilovoltage cone-beam computed tomography (CBCT) has been developed to provide accurate soft-tissue and bony setup information. We evaluated clinical CBCT setup data and compared CBCT measurements with electronic portal imaging device (EPID) images for lung cancer patients. METHODS AND MATERIALS: The setup error for CBCT scans at the treatment unit relative to the planning CT was measured for 62 patients (524 scans). For 19 of these patients (172 scans) portal images were also made. The mean, systematic setup error (Sigma), and random setup error (sigma) were calculated for the CBCT and the EPID. The differences between CBCT and EPID and the rotational setup error derived from the CBCT were also evaluated. An offline shrinking action level correction protocol, based on the CBCT measurements, was used to reduce systematic setup errors and the impact of this protocol was evaluated. RESULTS: The CBCT setup errors were significantly larger than the EPID setup errors for the cranial-caudal and anterior-posterior directions (p < 0.05). The mean overall setup errors after correction measured with the CBCT were 0.2 mm (Sigma = 1.6 mm, sigma = 2.9 mm) in the left-right, -0.8 mm (Sigma = 1.7 mm, sigma = 4.0 mm) in cranial-caudal and 0.0 mm (Sigma = 1.5 mm, sigma = 2.0 mm) in the anterior-posterior direction. Using our correction protocol only 2 patients had mean setup errors larger than 5 mm, without this correction protocol 51% of the patients would have had a setup error larger than 5 mm. CONCLUSION: Use of CBCT scans provided more accurate information concerning the setup of lung cancer patients than did portal imagin

Automatic prostate localization on cone-beam CT scans for high precision image-guided radiotherapy.

PURPOSE: Previously, we developed an automatic three-dimensional gray-value registration (GR) method for fast prostate localization that could be used during online or offline image-guided radiotherapy. The method was tested on conventional computed tomography (CT) scans. In this study, the performance of the algorithm to localize the prostate on cone-beam CT (CBCT) scans acquired on the treatment machine was evaluated. METHODS AND MATERIALS: Five to 17 CBCT scans of 32 prostate cancer patients (332 scans in total) were used. For 18 patients (190 CBCT scans), the CBCT scans were acquired with a collimated field of view (FOV) (craniocaudal). This procedure improved the image quality considerably. The prostate (i.e., prostate plus seminal vesicles) in each CBCT scan was registered to the prostate in the planning CT scan by automatic 3D gray-value registration (normal GR) starting from a registration on the bony anatomy. When these failed, registrations were repeated with a fixed rotation point locked at the prostate apex (fixed apex GR). Registrations were visually assessed in 3D by one observer with the help of an expansion (by 3.6 mm) of the delineated prostate contours of the planning CT scan. The percentage of successfully registered cases was determined from the combined normal and fixed apex GR assessment results. The error in gray-value registration for both registration methods was determined from the position of one clearly defined calcification in the prostate gland (9 patients, 71 successful registrations). Results: The percentage of successfully registered CBCT scans that were acquired with a collimated FOV was about 10% higher than for CBCT scans that were acquired with an uncollimated FOV. For CBCT scans that were acquired with a collimated FOV, the percentage of successfully registered cases improved from 65%, when only normal GR was applied, to 83% when the results of normal and fixed apex GR were combined. Gray-value registration mainly failed (or registrations were difficult to assess) because of streaks in the CBCT scans caused by moving gas pockets in the rectum during CBCT image acquisition (i.e., intrafraction motion). The error in gray-value registration along the left-right, craniocaudal, and anteroposterior axes was 1.0, 2.4, and 2.3 mm (1 SD) for normal GR, and 1.0, 2.0, and 1.7 mm (1 SD) for fixed apex GR. The systematic and random components of these SDs contributed approximately equally to these SDs, for both registration methods. Conclusions: The feasibility of automatic prostate localization on CBCT scans acquired on the treatment machine using an adaptation of the previously developed three-dimensional gray-value registration algorithm, has been validated in this study. Collimating the FOV during CBCT image acquisition improved the CBCT image quality considerably. Artifacts in the CBCT images caused by large moving gas pockets during CBCT image acquisition were the main cause for unsuccessful registration. From this study, we can conclude that CBCT scans are suitable for online and offline position verification of the prostate, as long as the amount of nonstationary gas is limite

Benchmarking daily adaptation using fully automated radiotherapy treatment plan optimization for rectal cancer

Background/purpose: In daily plan adaptation the radiotherapy treatment plan is adjusted just prior to delivery. A simple approach is taking the planning objectives of the reference plan and directly applying these in re-optimization. Here we present a tested method to verify whether daily adaptation without tweaking of the objectives can maintain the plan quality throughout treatment. Materials/methods: For fifteen rectal cancer patients, automated treatment planning was used to generate plans mimicking manual reference plans on the planning scans. For 74 fraction scans (4–5 per patient) an automated plan and a daily adapted plan were generated, where the latter re-optimizes the reference plan objectives without any tweaking. To evaluate the robustness of the daily adaptation, the adapted plans were compared to the autoplanning plans. Results: Median differences between the autoplanning plans on the planning scans and the reference plans were between −1 and 0.2 Gy. The largest interquartile range (1 Gy) was seen for the Lumbar Skin D2%. For the daily scans the PTV D2% and D98% differences between autoplanning and adapted plans were within ±0.7 Gy, with mean differences within ±0.3 Gy. Positive differences indicate higher values were obtained using autoplanning. For the Bowelarea + Bladder and the Lumbar Skin the D2% and Dmean differences were all within ±2.6 Gy, with mean differences between −0.9 and 0.1 Gy. Conclusion: Automated treatment planning can be used to benchmark daily adaptation techniques. The investigated adaptation workflow can robustly perform high quality adaptations without daily adjusting of the patient-specific planning objectives for rectal cancer radiotherapy