Stereotactic radiosurgery for brain AVMs: role of interobserver variation in target definition on digital subtraction angiography.

PURPOSE: We evaluated the extent of interobserver variation in contouring arteriovenous malformations (AVMs) on digital subtraction angiography (DSA) with respect to volume, spatial localization, and dosimetry and correlated our findings with the clinical outcome. METHODS AND MATERIALS: Thirty-one patients who had undergone radiosurgery for brain AVMs were studied. Six clinicians independently contoured the nidus on the original DSA. As a measure of variation, the ratio between the volumes of agreement and the corresponding encompassing volumes, as well as the absolute positional shift between the individual target volumes were derived. Using the original treatment plan, the dosimetric coverage of the individually contoured volumes with standard collimators was compared with a similar plan using dynamic conformal arcs. RESULTS: The mean contoured nidus volume was 3.6 +/- 5.6 cm3. The mean agreement ratio was 0.45 +/- 0.18 for all possible pairs of observers. The mean absolute positional shift between individually contoured volumes was 2.8 +/- 2.6 mm. These differences were more marked in previously treated groups and tended to be more pronounced in those with treatment failure. The mean coverage of the individual volumes by the 80% prescription isodose was 88.1% +/- 3.2% using conventional collimators and 78.9% +/- 4.4% using dynamic conformal arcs (p = 0.001). CONCLUSION: Substantial interobserver variations exist when contouring brain AVMs on DSA for the purpose of radiosurgical planning. Such variations may result in underdosage to the AVM and, thereby, contribute to treatment failure. The consequences of contouring variations may increase with the use of more conformal radiosurgical techniques.

Matching PET and CT scans of the head and neck area: development of method and validation.

Positron emission tomography (PET) provides important information on tumor biology, but lacks detailed anatomical information. Our aim in the present study was to develop and validate an automatic registration method for matching PET and CT scans of the head and neck. Three difficulties in achieving this goal are (1) nonrigid motions of the neck can hamper the use of automatic ridged body transformations; (2) emission scans contain too little anatomical information to apply standard image fusion methods; and (3) no objective way exists to quantify the quality of the match results. These problems are solved as follows: accurate and reproducible positioning of the patient was achieved by using a radiotherapy treatment mask. The proposed method makes use of the transmission rather than the emission scan. To obtain sufficient (anatomical) information for matching, two bed positions for the transmission scan were included in the protocol. A mutual information-based algorithm was used as a registration technique. PET and CT data were obtained in seven patients. Each patient had two CT scans and one PET scan. The datasets were used to estimate the consistency by matching PET to CT1, CT1 to CT2, and CT2 to PET using the full circle consistency test. It was found that using our method, consistency could be obtained of 4 mm and 1.3 degrees on average. The PET voxels used for registration were 5.15 mm, so the errors compared quite favorably with the voxel size. Cropping the images (removing the scanner bed from images) did not improve the consistency of the algorithm. The transmission scan, however, could potentially be reduced to a single position using this approach. In conclusion, the represented algorithm and validation technique has several features that are attractive from both theoretical and practical point of view, it is a user-independent, automatic validation technique for matching CT and PET scans of the head and neck, which gives the opportunity to compare different image enhancements.