Study to compare the effect of different registration methods on patient setup uncertainties in cone-beam computed tomography during volumetric modulated arc therapy for breast cancer patients

Mohandass, P; Khanna, D.; Kumar, T.; Thiyagaraj, T.; Saravanan, Chandra; Bhalla, Narendra Kumar; Puri, Abhishek

doi:10.4103/jmp.jmp_67_18

Cited by 7 publications

(8 citation statements)

References 24 publications

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“…In VMAT breast cases, all registration methods exhibited an insignificant difference in patient setup error. 8 According to Mohandas et al, 8 automatic CBR matching ensured easy target position verification. The insignificant difference in bony and ST matching for head-neck patients provided similar inference as Mohandas et al for breast patients.…”

Section: Discussionmentioning

confidence: 99%

“…There were various methods available for registration of cone beam CT to planning CT. 4,7,8 The choice available to the user depended on the make and model of the equipment and the licences available for the equipment. Users must evaluate the benefits and drawbacks of each technique and establish an institution-specific protocol for patient setup image registration.…”

Section: Introductionmentioning

confidence: 99%

“…There were clip box registration (CBR), mask-based registration, and dual registration (DR). 7,8 (1) CBR: In this method, an region of interest (ROI) was defined on the CT image in the form of a box drawn on any of the three orthogonal views around the ROI. Users can use the three registration methods for patient setup verification per the requirements.…”

Section: Introductionmentioning

confidence: 99%

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Comparative analysis of setup margin calculation in cone beam CT, by van Herk formula, using two different image registration methods

2023

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Introduction: This study aimed to quantify the difference in setup margin in cone beam computed tomography (CBCT) setup imaging, utilising the van Herk formula for two different image registration methods. Two alternative techniques of registration, bony landmark (BL) matching and soft tissue matching (ST) for head and neck cancer patients, were investigated. Methods: This study included 30 head and neck cancer patients who received a simultaneous integrated boost of 54–60–66 Gy in 30 fractions, using volumetric modulated arc treatment. A total of 867 CBCT images were acquired during patient setup and further analysed for setup margin calculation. A region of interest was described using a clip box between the reference and CBCT image to calculate the patient’s positional inaccuracy in three translational directions, X, Y and Z, where X was mediolateral, Y was the cranial-caudal, and Z was the anterior-posterior direction in the patient-based coordinate system, respectively. The shifts were captured by altering the BL and ST matching, and the setup margin was calculated using the van Herk formula (=2·5Σ + 0·7σ where Σ was the systematic and σ was the random error). Results: The difference between bony and ST matching in most cases was observed to be 1·4 mm in all translational directions at a 95% confidence interval and <1° in all rotational directions. The rotational error was found to be below the action level (±3°); hence, no corrections related to rotational error were made. The translational setup margin for bone and ST-based registration was X (BL) = 4·6 mm, X (ST) = 4·4 mm, Y (BL) = 6·3 mm, Y (ST) = 4·7 mm, Z (BL) = 3·0 mm, Z (ST) = 3·6mm. Conclusion: Two distinct registration approaches for head-neck patient setup did not yield any significant difference in the setup margin calculation. A suitable approach for CBCT and reference CT registration technique was required for the setup margin calculation. Confusion in selecting the correct image registration procedure can result in incorrect treatment execution. The compatibility of the two registration approaches was established in this study. Image fusion was neutralised before the second match (ST) to avoid hysteresis. For setup verification using CBCT for the head and neck region, both bone and ST registration were compatible for setup verification.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Comparative analysis of setup margin calculation in cone beam CT, by van Herk formula, using two different image registration methods

2023

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“…There are several methods for CBCT image registration, all of them based on matching grey values between CBCT and CT images; differences are in the volume of interest (VOI) used for image registration. Considering whole-breast radiotherapy, literature results show no significant differences between several registration methods in their ability to detect patient setup uncertainties, 5 but no precise data are available about evaluation of different registration methods on 3D-CBCT images, when only a small part of breast is considered, like in breast boost treatment.…”

Section: Introductionmentioning

confidence: 99%

Comparison of different registration methods in cone-beam computed tomography for breast boost radiation therapy

Lastrucci

Fedeli²,

Marciello³

et al. 2022

J Radiother Pract

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Introduction: The aim of this study is to compare patient geometrical uncertainties in the treatment of breast boost three-dimensional conformal radiation therapy (3D-CRT) considering both manual alignment and automatic different registration methods in cone-beam computed tomography (CBCT). Methods: A total of 85 patients were chosen for this study. A total of 254 registrations of CBCT vs planning computed tomography (CT) were retrospectively performed using automatic registration algorithms from Elekta XVI system (Clipbox and Mask) to detect patient setup uncertainties. All CBCTs were also matched manually by three health professionals. Mean shift values obtained with manual registration performed by health professionals were used as reference. Absolute value of difference between automatic algorithm shifts and reference values shifts was collected for each enrolled patient considering the three different spatial directions (x, y ,z), and the magnitude was calculated (δm for Mask and δc for Clipbox). Results: Data analysis showed a significant difference in δm and δc. t-Test statistics showed a high difference between Mask and Clipbox, in particular mean δm = (1.3 ± 0.1) mm and δc = (3.3 ± 1.2) mm (p-value <0.0001). Mask algorithm was performed in a very similar way with respect to the reference alignment, and the differences between these two procedures were of the order of 1 mm. Clipbox algorithm showed larger differences with manual registration. Conclusions: These results suggest that the Mask algorithm may be the optimal choice for patient setup verification in clinical practice for breast boost treatment in 3D-CRT.

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“…Among these radiotherapy methods, CBCT provides three-dimensional (3D) or four-dimensional (4D) reconstructed images for improving patient position accuracy [6]. Notably, CBCT has been widely used to detect prostate cancer [7], breast cancer [8], primary oesophageal cancer [9], cervical cancer [10] and colon cancer [11]. 4D CBCT of the lung is proved to be an effective tool for motion management in radiotherapy but presents a challenge because of slow gantry rotation times [12].…”

Section: Introductionmentioning

confidence: 99%

Comparative evaluation of image registration methods with different interest regions in lung cancer radiotherapy

et al. 2019

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Background: Lung cancer is a leading cause of morbidity and mortality worldwide. Radiotherapy for lung cancer is beneficial in both the radical and palliative settings, and technologic advances in recent years now afford an opportunity for this treatment to be more targeted than ever before. Although the delivery of more accurate forms of radiotherapy has minimized the risks of side-effects, how to utilize this treatment to optimize outcomes remains questionable. This study aimed to evaluate the accuracy of cone beam computed tomography (CBCT) image registration used in image-guided radiotherapy, providing reasonable guidance for clinic application of CBCT in lung cancer. Methods: A total of 53 patients with lung carcinoma including 34 central and 19 peripheral lesions were collected in this study. Varian-IX linear accelerator on-board imaging (OBI) system was used to acquire CBCT scans in threedimensional (3D) conformal radiotherapy before delivery. Different regions (whole lung/target/vertebrae/ipsilateral structure) were manually registered, and the position deviation and the registration time were analyzed. Results: It was suggested that 34 cases belonged to central type and 19 cases belonged to peripheral type. The volume of left lung and right lung was 1242.98 ± 452.46 cc, 1689.69 ± 574.31 cc, respectively. Tumor size was 6.65 ± 3.87 cm in diameter, and 129.67 ± 136.48 cc in volume. The percentage of left lung and right lung was 6.17 ± 1.24%, 4.74 ± 0.38%, respectively. The position deviation value and absolute value of image registration methods of X, Y and Z axis were not significant (P > 0.05). However, registration time (s) between whole lung registration group, tumor registration group, vertebral body registration group, affected lung registration group, and artificial registration group, was 3.651 ± 0.867 s, 1.144 ± 0.129 s, 1.226 ± 0.126 s, 2.081 ± 0.427 s, 179.491 ± 71.975 s, respectively. The differences were significant (P < 0.05). The registration differences between small tumor group and large tumor group were not statistically significant (P > 0.05). Conclusion: The automatic image matching of OBI is accuracy and high reliability in recognition of offset error. Registering body or ipsilateral structure is recommended to be used in CBCT for lung cancer.

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Study to compare the effect of different registration methods on patient setup uncertainties in cone-beam computed tomography during volumetric modulated arc therapy for breast cancer patients

Cited by 7 publications

References 24 publications

Comparative analysis of setup margin calculation in cone beam CT, by van Herk formula, using two different image registration methods

Comparative analysis of setup margin calculation in cone beam CT, by van Herk formula, using two different image registration methods

Comparison of different registration methods in cone-beam computed tomography for breast boost radiation therapy

Comparative evaluation of image registration methods with different interest regions in lung cancer radiotherapy

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