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    Acceptance test of a commerciallly available software for automatic image registration of computed tomography (CT), magnetic resonance imaging (MRI) and 99mTc-methoxyisobutylisonitrile (MIBI) single-photon emission computed tomography (SPECT) brain images.

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    This note describes a method to characterize the performances of image fusion software (Syntegra) with respect to accuracy and robustness. Computed tomography (CT), magnetic resonance imaging (MRI), and single-photon emission computed tomography (SPECT) studies were acquired from two phantoms and 10 patients. Image registration was performed independently by two couples composed of one radiotherapist and one physicist by means of superposition of anatomic landmarks. Each couple performed jointly and saved the registration. The two solutions were averaged to obtain the gold standard registration. A new set of estimators was defined to identify translation and rotation errors in the coordinate axes, independently from point position in image field of view (FOV). Algorithms evaluated were local correlation (LC) for CT-MRI, normalized mutual information (MI) for CT-MRI, and CT-SPECT registrations. To evaluate accuracy, estimator values were compared to limiting values for the algorithms employed, both in phantoms and in patients. To evaluate robustness, different alignments between images taken from a sample patient were produced and registration errors determined. LC algorithm resulted accurate in CT-MRI registrations in phantoms, but exceeded limiting values in 3 of 10 patients. MI algorithm resulted accurate in CT-MRI and CT-SPECT registrations in phantoms; limiting values were exceeded in one case in CT-MRI and never reached in CT-SPECT registrations. Thus, the evaluation of robustness was restricted to the algorithm of MI both for CT-MRI and CT-SPECT registrations. The algorithm of MI proved to be robust: limiting values were not exceeded with translation perturbations up to 2.5 cm, rotation perturbations up to 10 degrees and roto-translational perturbation up to 3 cm and 5 degrees

    Delineation of target volume for radiotherapy of high-grade gliomas by 99m Tc-MIBI SPECT and MRI fusion

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    BACKGROUND AND PURPOSE: Computed tomography (CT) and magnetic resonance imaging (MRI) are traditionally used for treatment planning of high-grade glioma. 99m Tc-methoxy-isobutyl-isonitrile (MIBI) single-photon emission computed tomography (SPECT) showed high sensitivity and specificity in literature series. In the present study, it was investigated how the information provided by 99m Tc-MIBI SPECT and MRI fusion could affect target delineation for radiotherapy of high-grade glioma. PATIENTS AND METHODS: 21 patients with high-grade glioma were studied by MRI and 99m Tc-MIBI SPECT imaging. The gross tumor volume (GTV) was outlined on MRI (MRI-GTV) and SPECT images (SPECT-GTV). Three additional volumes were analyzed: the (MRI+SPECT)-GTV representing the whole amount of MRI-GTV plus SPECT-GTV, the (MRI&SPECT)-GTV identified by the overlapping region of MRI-GTV and SPECT-GTV, and the (SPECT/MRI)-GTV identified by the extension of SPECT-GTV outside MRI-GTV. RESULTS: MRI contrast-enhanced and 99m Tc-MIBI SPECT-positive lesions were found in all 21 patients. The average SPECT-GTV was slightly larger than the average MRI-GTV, with greater difference for resected than for unresected cases. The average increment of (MRI+SPECT)-GTV compared to MRI-GTV was 33%, being significantly higher for resected than for unresected cases (p = 0.006). CONCLUSION: The fusion of 99m Tc-MIBI SPECT and MRI significantly affected the delineation of the target volume identified by MRI alon
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