Total body irradiation (TBI) is used as a preconditioning regimen prior to bone marrow transplant for treatment of hematologic malignancies. During TBI, large volumes of normal tissue are irradiated, and this can lead to toxicities, most significantly in the lungs. Intensity modulated total marrow irradiation (IMTMI) may be able to reduce these toxicities by directly targeting the bone marrow while minimizing the dose to critical structures. The goal of this study was to assess the feasibility of IMTMI by following the planning and delivery process for a Rando phantom. A three isocenter technique was used to provide a full body plan for treatment on a linear accelerator. Thermoluminescent detectors (TLDs) were placed at 22 positions throughout the phantom to compare the delivered doses to the planned doses. Individual intensity modulated radiation therapy verification plans were delivered to a solid water phantom for the three isocenters, and doses measured from an ion chamber and film were compared to the planned doses. The treatment plan indicated that target coverage was achieved with this IMTMI technique, and that the doses to critical structures were reduced by 29%-65% compared to conventional TBI. TLD readings demonstrated accurate dose delivery, with an average difference of 3.5% from the calculated dose. Ion chamber readings for the verification plans were all within 3% of the expected dose, and film measurements showed accurate dose distributions. Results from this study suggest that IMTMI using the three isocenter technique can be accurately delivered and may result in substantial dose reductions to critical structures.

We have evaluated the performance of an automated classifier applied to the task of differentiating malignant and benign lung nodules in low-dose helical computed tomography (CT) scans acquired as part of a lung cancer screening program. The nodules classified in this manner were initially identified by our automated lung nodule detection method, so that the output of automated lung nodule detection was used as input to automated lung nodule classification. This study begins to narrow the distinction between the "detection task" and the "classification task." Automated lung nodule detection is based on two- and three-dimensional analyses of the CT image data. Gray-level-thresholding techniques are used to identify initial lung nodule candidates, for which morphological and gray-level features are computed. A rule-based approach is applied to reduce the number of nodule candidates that correspond to non-nodules, and the features of remaining candidates are merged through linear discriminant analysis to obtain final detection results. Automated lung nodule classification merges the features of the lung nodule candidates identified by the detection algorithm that correspond to actual nodules through another linear discriminant classifier to distinguish between malignant and benign nodules. The automated classification method was applied to the computerized detection results obtained from a database of 393 low-dose thoracic CT scans containing 470 confirmed lung nodules (69 malignant and 401 benign nodules). Receiver operating characteristic (ROC) analysis was used to evaluate the ability of the classifier to differentiate between nodule candidates that correspond to malignant nodules and nodule candidates that correspond to benign lesions. The area under the ROC curve for this classification task attained a value of 0.79 during a leave-one-out evaluation.

Osteoporosis is a disease that results in an increased risk of bone fracture due to a loss of bone mass and deterioration of bone structure. Bone mineral density (BMD) provides a measure of bone mass and is frequently measured by bone densitometry systems to diagnose osteoporosis. In addition, computerized radiographic texture analysis (RTA) is currently being investigated as a measure of bone structure and as an additional diagnostic predictor of osteoporosis. In this study, we assessed the ability of a peripheral bone densitometry (PD) system to yield images useful for RTA. The benefit of such a system is that it measures BMD by dual-energy x-ray absorptiometry and therefore provides high- and low-energy digital radiographic images. The bone densitometry system investigated was the GE/Lunar PIXI, which provides 512 x 512 digital images of the heel or forearm (0.2 mm pixels). We compared texture features of heel images obtained with this PD system to those obtained on a Fuji computed radiography (CR) system (0.1 mm pixels). Fourier and fractal-based texture features of images from 24 subjects who had both CR and BMD exams were calculated, and correlation between the two systems was analyzed. Fourier-based texture features characterize the magnitude, frequency content, and orientation of the trabecular bone pattern. Good correlation was found between the two modalities for the first moment (FMP) with r=0.71 (p value<0.0001) and for minimum FMP with r=0.52 (p value=0.008). Root-mean-square (RMS) did not correlate with r=0.31 (p value>0.05), while the standard deviation of the RMS did correlate with r=0.79 (p value<0.0001). Good correlation was also found between the two modalities for the fractal-based texture features with r=0.79 (p value<0.0001) for the global Minkowski dimension and r=0.63 (p value=0.0007) for the fractal dimension from a box counting method. The PD system therefore may have the potential for yielding heel images suitable for RTA.

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Osteoporosis is a disease characterized by a loss of bone mass and a deterioration of bone structure. Bone mineral density (BMD) measures bone mass and is currently the method used to diagnose osteoporosis, while computerized radiographic texture analysis (RTA) is being investigated as a measure of bone structure. The GE/Lunar PIXI peripheral bone densitometer (PD) system, which uses dual-energy subtraction to measure BMD, also provides a digital image of the heel or forearm. The goal of our current research was to evaluate the physical imaging properties of the PIXI system (pixel size of 0.2 mm) compared to a Fuji computed radiography (CR) system (pixel size of 0.1 mm) to determine its suitability for texture analysis from image data. Contrast was measured using a series of uniform images covering the useful clinical exposure range. Spatial resolution was characterized by the presampling modulation transfer function (MTF) determined by an edge method. Noise power spectra (NPS) for different exposures were calculated using a two-dimensional Fourier analysis method. The expectation modulation transfer function was measured and combined with the NPS data to calculate the noise-equivalent number of quanta. The slope of the characteristic curve of the peripheral densitometer (PD) system was found to be position dependent across the image, although this dependence was substantially reduced by use of the system's clinical-settings corrections. An MTF value of 0.5 was found at 0.5 cycles/mm for the densitometry system compared to the same value at 1.6 cycles/mm for the CR system. Unlike the CR system, the NPS of the densitometry system was found not to be directionally dependent and did not drop off at higher spatial frequencies.

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