Accuracy in automatic image registration between MV cone beam computed tomography and planning kV computed tomography in image guided radiotherapy

Kanakavelu, Nithya; Samuel, E. James Jebaseelan

doi:10.1016/j.rpor.2016.07.001

Cited by 8 publications

(8 citation statements)

References 9 publications

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“…Most of the data points fell within the ±2 mm bound lines, which represented the upper range of the typical inter‐observer variation of manual image registration in lung SBRT. 8 , 16 , 17 Two patients (6.3%) had translational uncertainty > 2 mm (max = 3.1 mm), and both occurred in the longitudinal direction. Meanwhile, corresponding errors from the direct HCT–CBCTtx auto‐registration, represented by blue colors, were −0.4±2.6, −0.2±7.4, −1.4±3.6 mm, respectively, with 11 patients (34.4%) had translation error > 2 mm (max = 26.2 mm) in at least one direction.…”

Section: Resultsmentioning

confidence: 99%

Using previously registered cone beam computerized tomography images to facilitate online computerized tomography to cone beam computerized tomography image registration in lung stereotactic body radiation therapy

Liang

Liu

Grills

et al. 2022

J Applied Clin Med Phys

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Purpose In our conventional image registration workflow, the four‐dimensional (4D) CBCT was directly registered to the reference helical CT (HCT) using a dual registration approach within the Elekta XVI software. In this study, we proposed a new HCT–CBCT auto‐registration strategy using a previously registered CBCT (CBCTpre) as the reference image and tested its clinical feasibility. Methods From a previous CBCT session, the registered average 4D CBCT was selected as CBCTpre and the HCT–CBCTpre registration vector from the clinician's manual registration result was recorded. In the new CBCT session, auto‐registration was performed between the new average 4D CBCT (CBCTtx) and CBCTpre (CBCTpre‐CBCTtx). The overall HCT–CBCTtx registration result was then derived by combing the results from two registrations (i.e., HCT–CBCTpre + CBCTpre–CBCTtx). The results from the proposed method were compared with clinician's manually adjusted HCT–CBCTtx registration results (“ground truth”) to evaluate its accuracy using a test dataset consisting of 32 challenging registration cases. Results The uncertainty of the proposed auto‐registration method was −0.1 ± 0.5, 0.1 ± 1.0, and −0.1 ± 0.7 mm in three translational directions (lateral, longitudinal, and vertical) and 0.0° ± 0.9°, 0.3° ± 0.9°, and 0.4° ± 0.7° in three rotation directions, respectively. Two patients (6.3%) had translational uncertainty > 2 mm (max = 3.1 mm) and both occurred in the longitudinal direction. Meanwhile, the uncertainty of the conventional direct HCT–CBCTtx auto‐registration was −0.4 ± 2.6, −0.2 ± 7.4, −1.4 ± 3.6 mm for translations and −0.3° ± 1.2°, 0.0° ± 1.6°, and 0.1 ± 1.1° for rotations. Eleven patients (34.4%) had translation uncertainty > 2 mm (max = 26.2 mm) in at least one direction. Accuracy in translation was improved with the new method, while rotation accuracy stayed in the same order. Conclusion We demonstrated the feasibility of incorporating prior clinical registration knowledge into the online HCT–CBCT registration process. The proposed auto‐registration method provides a quick and reliable starting solution for online HCT–CBCT registration.

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Section: Resultsmentioning

confidence: 99%

Using previously registered cone beam computerized tomography images to facilitate online computerized tomography to cone beam computerized tomography image registration in lung stereotactic body radiation therapy

Liang

Liu

Grills

et al. 2022

J Applied Clin Med Phys

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“…were used because they are significantly different compared to the density of the surrounding tissues and do not change significantly with the passage of treatment. The analysis of 160 sets of registration data of 8 patients with lung cancer using different registration methods suggested that thoracic vertebrae can be used for the image guidance of lung cancer images guided radiotherapy [24]. The study of CBCT image registration in 25 patients with lung cancer found that the results of central type and peripheral type registration are different.…”

Section: Methodsmentioning

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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“…The manual matching required significantly more time as compared to automatic matching. [15] The gray value ( T + R ) registration algorithm used gray value “correction ratio” procedure for automatic registration. The gray value intensity matching of the voxels in the registration volume was performed during the registration process.…”

Section: Methodsmentioning

confidence: 99%

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

et al. 2018

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Purpose:This study compared three different methods used in registering cone-beam computed tomography (CBCT) image set with planning CT image set for determining patient setup uncertainties during volumetric modulated arc therapy (VMAT) for breast cancer patients.Materials and Methods:Seven breast cancer patients treated with 50 Gy in 25 fractions using VMAT technique were chosen for this study. A total of 105 CBCT scans were acquired by image guidance protocol for patient setup verification. Approved plans’ CT images were used as the reference image sets for registration with their corresponding CBCT image sets. Setup errors in mediolateral, craniocaudal, and anteroposterior direction were determined using gray-scale matching between the reference CT images and onboard CBCT images. Patient setup verification was performed using clip-box registration (CBR) method during online imaging. Considering the CBR method as the reference, two more registrations were performed using mask registration (MR) method and dual registration (DR) (CBR + MR) method in the offline mode. For comparison, systematic error (∑), random error (σ), mean displacement vector (R), mean setup error (M), and registration time (Rt) were analyzed. Post hoc Tukey's honest significant difference test was performed for multiple comparisons.Results:Systematic and random errors were less in CBR as compared to MR and DR (P > 0.05). The mean displacement error and mean setup errors were less in CBR as compared to MR and DR (P > 0.05). Increased Rt was observed in DR as compared to CBR and MR (P < 0.05). In addition, multiple comparisons did not show any significant difference in patient setup error (P > 0.05).Conclusion:For breast VMAT plan delivery, all three registration methods show insignificant variation in patient setup error. One can use any of the three registration methods for patient setup verification.

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Accuracy in automatic image registration between MV cone beam computed tomography and planning kV computed tomography in image guided radiotherapy

Abstract: This study shows that the automatic IR is accurate within 2 mm and provides confidence in performing them between planning kV CT and MV CBCT image datasets for online image guided radiotherapy.

Cited by 8 publications

References 9 publications

Using previously registered cone beam computerized tomography images to facilitate online computerized tomography to cone beam computerized tomography image registration in lung stereotactic body radiation therapy

Using previously registered cone beam computerized tomography images to facilitate online computerized tomography to cone beam computerized tomography image registration in lung stereotactic body radiation therapy

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

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

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