Automatic quantitation of multiple sclerosis lesions on MR images

A two-pronged approach for the automatic quantitation of multiple sclerosis (MS) lesions on magnetic resonance (MR) images has been developed. This method includes the design and use of a pulse sequence for improved lesion-to-tissue contrast (LTC) and seeks to identify and minimize the sources of false lesion classifications in segmented images. The new pulse sequence, referred to as AFFIRMATIVE (Attenuation of Fluid by Fast Inversion Recovery with MAgnetization Transfer Imaging with Variable Echoes), improves the LTC, relative to spin-echo images, by combining Fluid-Attenuated Inversion Recovery (FLAIR) and Magnetization Transfer Contrast (MTC). In addition to acquiring fast FLAIR/MTC images, the AFFIRMATIVE sequence simultaneously acquires fast spin-echo (FSE) images for spatial registration of images, which is necessary for accurate lesion quantitation. Flow has been found to be a primary source of false lesion classifications. Therefore, an imaging protocol and reconstruction methods are developed to generate "flow images" which depict both coherent (vascular) and incoherent (CSF) flow. An automatic technique is designed for the removal of extra-meningeal tissues, since these are known to be sources of false lesion classifications. A retrospective, three-dimensional (3D) registration algorithm is implemented to correct for patient movement which may have occurred between AFFIRMATIVE and flow imaging scans. Following application of these pre-processing steps, images are segmented into white matter, gray matter, cerebrospinal fluid, and MS lesions based on AFFIRMATIVE and flow images using an automatic algorithm. All algorithms are seamlessly integrated into a single MR image analysis software package. Lesion quantitation has been performed on images from 15 patient volunteers. The total processing time is less than two hours per patient on a SPARCstation 20. The automated nature of this approach should provide an objective means of monitoring the progression, stabilization, and/or regression of MS lesions in large-scale, multi-center clinical trials. ^

EVALUATION OF THE QUANTITATIVE ACCURACY OF A COMMERCIALLY-AVAILABLE POSITRON EMISSION MAMMOGRAPHY SCANNER

Objective: The PEM Flex Solo II (Naviscan, Inc., San Diego, CA) is currently the only commercially-available positron emission mammography (PEM) scanner. This scanner does not apply corrections for count rate effects, attenuation or scatter during image reconstruction, potentially affecting the quantitative accuracy of images. This work measures the overall quantitative accuracy of the PEM Flex system, and determines the contributions of error due to count rate effects, attenuation and scatter. Materials and Methods: Gelatin phantoms were designed to simulate breasts of different sizes (4 – 12 cm thick) with varying uniform background activity concentration (0.007 – 0.5 μCi/cc), cysts and lesions (2:1, 5:1, 10:1 lesion-to-background ratios). The overall error was calculated from ROI measurements in the phantoms with a clinically relevant background activity concentration (0.065 μCi/cc). The error due to count rate effects was determined by comparing the overall error at multiple background activity concentrations to the error at 0.007 μCi/cc. A point source and cold gelatin phantoms were used to assess the errors due to attenuation and scatter. The maximum pixel values in gelatin and in air were compared to determine the effect of attenuation. Scatter was evaluated by comparing the sum of all pixel values in gelatin and in air. Results: The overall error in the background was found to be negative in phantoms of all thicknesses, with the exception of the 4-cm thick phantoms (0%±7%), and it increased with thickness (-34%±6% for the 12-cm phantoms). All lesions exhibited large negative error (-22% for the 2:1 lesions in the 4-cm phantom) which increased with thickness and with lesion-to-background ratio (-85% for the 10:1 lesions in the 12-cm phantoms). The error due to count rate in phantoms with 0.065 μCi/cc background was negative (-23%±6% for 4-cm thickness) and decreased with thickness (-7%±7% for 12 cm). Attenuation was a substantial source of negative error and increased with thickness (-51%±10% to -77% ±4% in 4 to 12 cm phantoms, respectively). Scatter contributed a relatively constant amount of positive error (+23%±11%) for all thicknesses. Conclusion: Applying corrections for count rate, attenuation and scatter will be essential for the PEM Flex Solo II to be able to produce quantitatively accurate images.

Thoracic target volume delineation using various maximum-intensity projection computed tomography image sets for stereotactic body radiation therapy

The motion of lung tumors during respiration makes the accurate delivery of radiation therapy to the thorax difficult because it increases the uncertainty of target position. The adoption of four-dimensional computed tomography (4D-CT) has allowed us to determine how a tumor moves with respiration for each individual patient. Using information acquired during a 4D-CT scan, we can define the target, visualize motion, and calculate dose during the planning phase of the radiotherapy process. One image data set that can be created from the 4D-CT acquisition is the maximum-intensity projection (MIP). The MIP can be used as a starting point to define the volume that encompasses the motion envelope of the moving gross target volume (GTV). Because of the close relationship that exists between the MIP and the final target volume, we investigated four MIP data sets created with different methodologies (3 using various 4D-CT sorting implementations, and one using all available cine CT images) to compare target delineation. It has been observed that changing the 4D-CT sorting method will lead to the selection of a different collection of images; however, the clinical implications of changing the constituent images on the resultant MIP data set are not clear. There has not been a comprehensive study that compares target delineation based on different 4D-CT sorting methodologies in a patient population. We selected a collection of patients who had previously undergone thoracic 4D-CT scans at our institution, and who had lung tumors that moved at least 1 cm. We then generated the four MIP data sets and automatically contoured the target volumes. In doing so, we identified cases in which the MIP generated from a 4D-CT sorting process under-represented the motion envelope of the target volume by more than 10% than when measured on the MIP generated from all of the cine CT images. The 4D-CT methods suffered from duplicate image selection and might not choose maximum extent images. Based on our results, we suggest utilization of a MIP generated from the full cine CT data set to ensure a representative inclusive tumor extent, and to avoid geometric miss.