We evaluated a commercial positron emission mammography (PEM) camera, the PEM Flex Solo II. This system comprises two 6 · 16.4 cm detectors that scan together covering up to a 24 · 16.4 cm field of view (FOV). There are no specific standards for testing this detector configuration. We performed several tests important to breast imaging, and we propose tests that should be included in standardized testing of PEM systems. Methods: We measured spatial resolution, uniformity, countingrate linearity, recovery coefficients, and quantification accuracy using the system's software. Image linearity and coefficient of variation at the edge of the FOV were also characterized. Anecdotal examples of clinical patient data are presented. Results: The spatial resolution was 2.4 mm in full width at half maximum for image planes parallel to the detector faces. The background variability was approximately 5%, and quantification accuracy and recovery coefficients varied within the FOV. Positioning linearity began at approximately 13 mm from the edge of the detector housing. The coefficient of variation was significantly higher close to the edge of the FOV because of limited sensitivity in these image planes. Conclusion: A reconstructed spatial resolution of 2.4 mm represented a significant improvement over conventional whole-body PET scanners and should reduce the lower threshold on lesion size and tracer uptake for detection in the breast. Limited-angle tomography and a lack of data corrections result in spatially variable quantitative results. PEM acquisition geometry limits sampling statistics at the chest-wall edge of the camera, resulting in high variance in that portion of the image. Example patient images demonstrate that lesions can be detected at the chest-wall edge despite variance artifacts, and fine structure is visualized routinely throughout the FOV in the focal plane. The PEM Flex camera should enable the functional imaging of breast cancer earlier in the disease process than whole-body PET. Posi tron emission mammography (PEM) is a technique using 2 annihilation-photon detectors and limited-angle tomographic reconstruction to image radiotracer distributions within the breast. Because of their smaller size and closer proximity to the source, dedicated PEM cameras can provide better spatial resolution and count sensitivity than whole-body PET (WB PET). PEM is undergoing clinical trials and has been suggested for breast cancer detection, characterization, treatment planning, and assessment of response to therapy. PEM, like WB PET, provides functional imaging information. Radiographic mammography, ultrasound, and MRI primarily provide anatomic information. PEM can thus provide complementary information to conventional breast imaging modalities. Screening mammography is believed to be an important factor in recent declines in breast cancer mortality (1). Despite the successes of earlier detection by mammography, however, breast cancer is the second-leading cause of cancer-related deaths in North American women. This stat...

Purpose: The goal of this work was to investigate the effects of MRI surface coils on attenuationcorrected PET emission data. The authors studied the cases where either an MRI or a CT scan would be used to provide PET attenuation correction (AC). Combined MR/PET scanners that use the MRI for PET AC (MR-AC) face the challenge of absent surface coils in MR images and thus cannot directly account for attenuation in the coils. Combining MR and PET images could be achieved by transporting the subject on a stereotactically registered table between independent MRI and PET scanners. In this case, conventional PET CT-AC methods could be used. A challenge here is that high atomic number materials within MR coils cause artifacts in CT images and CT based AC is typically not validated for coil materials. Methods: The authors evaluated PET artifacts when MR coils were absent from AC data (MR-AC), or when coil attenuation was measured by CT scanning (CT-AC). They scanned PET phantoms with MR surface coils on a clinical PET/CT system and used CT-AC to reconstruct PET data. The authors then omitted the coil from the CT-AC image to mimic the MR-AC scenario. Images were acquired using cylinder and anthropomorphic phantoms. They evaluated and compared the following five scenarios: (1) A uniform cylinder phantom and head coil scanned and reconstructed using CT-AC; (2) similar emission data (with head coil present) were reconstructed without the head coil in the AC data; (3) the same cylinder scanned without the head coil present (reference scan); (4) a PET torso phantom with a full MR torso coil present in both PET and CT; (5) only half of the separable torso coil present in the PET/CT acquisition. The authors also performed analytic simulations of the first three scenarios. Results: Streak artifacts were present in CT images containing MR surface coils due to metal components. These artifacts persisted after the CT images were converted for PET AC. The artifacts were significantly reduced when half of the separable coil was removed during the scan. CT scans tended to over-estimate the linear attenuation coefficient (l) of the metal components when using conventional methods for converting from CT number to l(511 keV). Artifacts were visible outside the phantom in some of the PET emission images, corresponding to the MRI coil geometry. However, only subtle artifacts were apparent in the emission images inside the phantoms. On the other hand, the PET emission image quantitative accuracy was significantly affected: the activity was underestimated by 19% when AC did not include the head coil, and overestimated by 28% when the CT-AC included the head coil. Conclusions: The presence of MR coils during PET or PET/CT scanning can cause subtle artifacts and potentially important quantification errors. Alternative CT techniques that mitigate artifacts should be used to improve AC accuracy. When possible, removing segments of an MR coil prior to the PET/CT exam is recommended. Further, MR coils could be redesigned to reduce artifacts by rear...

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Purpose:To quantify the concentration of soft-tissue components of water, fat, and calcium through the decomposition of the x-ray spectral signatures in multi-energy CT images. Methods: Decomposition of dual-energy and multi-energy x-ray data into basis materials can be performed in the projection domain, image domain, or during image reconstruction. In this work, the authors present methodology for the decomposition of multi-energy x-ray data in the image domain for the application of soft-tissue characterization. To demonstrate proof-of-principle, the authors apply several previously proposed methods and a novel content-aware method to multi-energy images acquired with a prototype photon counting CT system. Data from phantom and ex vivo specimens are evaluated. Results:The number and type of materials in a region can be limited based on a priori knowledge or classification strategies. The proposed difference classifier successfully classified the image into air only, water+fat, water+fat+iodine, and water+calcium regions. Then, the content-aware material decomposition based on weighted least-square optimization generated quantitative maps of concentration. Bias in the estimation of the concentration of water and oil components in a phantom study was <0.10 ± 0.15 g/cc on average. Decomposition of ex vivo carotid endarterectomy specimens suggests the presence of water, lipid, and calcium deposits in the plaque walls. Conclusions: Initial application of the proposed methodology suggests that it can decompose multienergy CT images into quantitative maps of water, adipose, iodine, and calcium concentrations.

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