Dataset Information

Clinical validation of the normalized mutual information method for registration of CT and MR images in radiotherapy of brain tumors.

ABSTRACT: Image registration integrates information of different imaging modalities and has the potential to improve target volume determination in radiotherapy planning. This paper describes the implementation and validation of a 3D fully automated registration procedure in the process of radiotherapy treatment planning of brain tumors. 15 Patients with various brain tumors received CT and MR brain imaging before the start of radiotherapy. The normalized mutual information (NMI) method was used for image registration. Registration accuracy was estimated by performing statistical analysis of coordinate differences between CT and MR anatomical landmarks along the x-, y- and z-axes. Second, a visual validation protocol was developed to validate the quality of individual registration solutions and this protocol was tested in a series of 36 CT-MR registration procedures with intentionally applied registration errors. The mean coordinate differences between CT and MR landmarks along the x- and y-axes were in general within 0.5 mm. The mean coordinate differences along the z-axis were within 1.0 mm, which is of the same magnitude as the applied slice thickness in scanning. Second, the detection of intentionally applied registration errors by employment of a standardized visual validation protocol resulted in low false-negative and low false-positive rates. Application of the NMI method for the brain results in excellent automatic registration accuracy and the method has been incorporated in daily routine within our institute. A standardized validation protocol is proposed that ensures the quality of individual registrations by detecting registration errors with high sensitivity and specificity. This protocol is proposed for the validation of other linear registration methods.

SUBMITTER: Veninga T

PROVIDER: S-EPMC5723487 | biostudies-literature | 2004

REPOSITORIES: biostudies-literature

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Clinical validation of the normalized mutual information method for registration of CT and MR images in radiotherapy of brain tumors.

Veninga Theo T Huisman Henkjan H van der Maazen Richard W M RW Huizenga Henk H

Journal of applied clinical medical physics 20040701 3

Image registration integrates information of different imaging modalities and has the potential to improve target volume determination in radiotherapy planning. This paper describes the implementation and validation of a 3D fully automated registration procedure in the process of radiotherapy treatment planning of brain tumors. 15 Patients with various brain tumors received CT and MR brain imaging before the start of radiotherapy. The normalized mutual information (NMI) method was used for image ...[more]

PMID: 15753941

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Project description:PURPOSE:To automate the estimation of swallowing motion from 2D MR cine images using deformable registration for future applications of personalized margin reduction in head and neck radiotherapy and outcome assessment of radiation-associated dysphagia. METHODS:Twenty-one patients with serial 2D FSPGR-MR cine scans of the head and neck conducted through the course of definitive radiotherapy for oropharyngeal cancer. Included patients had at least one cine scan before, during, or after radiotherapy, with a total of 52 cine scans. Contours of 7 swallowing related regions-of-interest (ROIs), including pharyngeal constrictor, epiglottis, base of tongue, geniohyoid, hyoid, soft palate, and larynx, were manually delineated from consecutive frames of the cine scan covering at least one swallowing cycle. We applied a modified thin-plate-spline robust-point-matching algorithm to register the point sets of each ROI automatically over frames. The deformation vector fields from the registration were then used to estimate the motion during swallowing for each ROI. Registration errors were estimated by comparing the deformed contours with the manual contours. RESULTS:On average 22 frames of each cine scan were contoured. The registration for one cine scan (7 ROIs over 22 frames) on average took roughly 22 minutes. A number of 8018 registrations were successfully batch processed without human interaction after the contours were drawn. The average registration error for all ROIs and all patients was 0.36 mm (range: 0.06 mm- 2.06 mm). Larynx had the average largest motion in superior direction of all structures under consideration (range: 0.0 mm- 58.7 mm). Geniohyoid had the smallest overall motion of all ROIs under consideration and the superior-inferior motion was larger than the anterior-posterior motion for all ROIs. CONCLUSION:We developed and validated a deformable registration framework to automate the estimation of swallowing motion from 2D MR cine scans.

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Dataset Information

Clinical validation of the normalized mutual information method for registration of CT and MR images in radiotherapy of brain tumors.

Publications

Clinical validation of the normalized mutual information method for registration of CT and MR images in radiotherapy of brain tumors.

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