Imaging phantom

About: Imaging phantom is a research topic. Over the lifetime, 28170 publications have been published within this topic receiving 510003 citations. The topic is also known as: phantom.

Quantitative SPECT reconstruction using CT-derived corrections.

Abstract: A method for achieving quantitative single-photon emission computed tomography (SPECT) based upon corrections derived from x-ray computed tomography (CT) data is presented. A CT-derived attenuation map is used to perform transmission-dependent scatter correction (TDSC) in conjunction with non-uniform attenuation correction. The original CT data are also utilized to correct for partial volume effects in small volumes of interest. The accuracy of the quantitative technique has been evaluated with phantom experiments and clinical lung ventilation/perfusion SPECT/CT studies. A comparison of calculated values with the known total activities and concentrations in a mixed-material cylindrical phantom, and in liver and cardiac inserts within an anthropomorphic torso phantom, produced accurate results. The total activity in corrected ventilation-subtracted perfusion images was compared to the calibrated injected dose of [(99m)Tc]-MAA (macro-aggregated albumin). The average difference over 12 studies between the known and calculated activities was found to be -1%, with a range of +/-7%.

Imaging pH using the chemical exchange saturation transfer (CEST) MRI: Correction of concomitant RF irradiation effects to quantify CEST MRI for chemical exchange rate and pH

Abstract: Chemical exchange saturation transfer (CEST) MRI has been shown capable of detecting dilute labile protons and abnormal tissue glucose/oxygen metabolism, and thus, may serve as a complementary imaging technique to the conventional MRI methods. CEST imaging, however, is also dependent on experimental parameters such as the power, duration, and waveform of the irradiation RF pulse. As a result, its sensitivity and specificity for microenvironment properties such as pH is not optimal. In this study, the dependence of CEST contrast on experimental parameters was solved and an iterative compensation algorithm was proposed that corrects the experimentally measured CEST contrast from the concomitant RF irradiation effects. The proposed algorithm was verified with both numerical simulation and experimental measurements from a tissue-like pH phantom, and showed that pH derived from the compensated CEST imaging agrees reasonably well with pH-electrode measurements within 0.1 pH unit. In sum, our study validates the use of a correction algorithm to compensate CEST imaging from concomitant RF irradiation effects for accurate calibration of the chemical exchange rate, and demonstrates the feasibility of pH imaging with CEST MRI.

Correction for scatter in 3D brain PET using a dual energy window method

Abstract: A method for scatter correction using dual energy window acquisition has been developed and implemented on data collected with a brain-PET tomograph operated in the septa retracted, 3D mode. Coincidence events are assigned to (i) an upper energy window where both photons deposit energy between 380 keV and 850 keV or (ii) a lower energy window where one or both photons deposit within 200 keV and 380 keV. Scaling parameters are derived from measurements of the ratios of counts from line sources due to scattered and unscattered events in the two energy windows in head-sized phantoms. A scaled subtraction of the two energy windows produces a distribution of scatter which is smoothed prior to subtraction from the upper energy window. In phantoms, the correction was found to restore the uniformity, contrast and linearity of activity concentration. Relative activity concentrations were restored to within 7% of their true values in a multicompartment phantom. The method was found to provide accurate correction for scattered events arising from activity outside the direct detector field of view. In a three-compartment phantom containing water, and scanned in dynamic, multiframe mode, the half-lives of the two isotopes were restored to within 2% of their true value.

Voxel size and gray level normalization of CT radiomic features in lung cancer.

Abstract: Radiomic features are potential imaging biomarkers for therapy response assessment in oncology. However, the robustness of features with respect to imaging parameters is not well established. Previously identified potential imaging biomarkers were found to be intrinsically dependent on voxel size and number of gray levels (GLs) in a recent texture phantom investigation. Here, we validate the voxel size and GL in-phantom normalizations in lung tumors. Eighteen patients with non-small cell lung cancer of varying tumor volumes were analyzed. To compare with patient data, phantom scans were acquired on eight different scanners. Twenty four previously identified features were extracted from lung tumors. The Spearman rank (rs) and interclass correlation coefficient (ICC) were used as metrics. Eight out of 10 features showed high (rs > 0.9) and low (rs 0.8) before and after GL normalizations, respectively. We conclude that voxel size and GL normalizations derived from a texture phantom study also apply to lung tumors. This study highlights the importance and utility of investigating the robustness of radiomic features with respect to CT imaging parameters in radiomic phantoms.