Purpose Many radiomics features were originally developed for non-medical imaging applications and therefore original assumptions may need to be reexamined. In this study, we investigated the impact of slice thickness and pixel spacing (or pixel size) on radiomics features extracted from Computed Tomography (CT) phantom images acquired with different scanners as well as different acquisition and reconstruction parameters. The dependence of CT texture features on gray level discretization was also evaluated. Methods and Materials A texture phantom composed of 10 different cartridges of different materials was scanned on eight different CT scanners from three different manufacturers. The images were reconstructed for various slice thicknesses. For each slice thickness, the reconstruction Field Of View (FOV) was varied to render pixel sizes ranging from 0.39 to 0.98 mm. A fixed spherical region of interest (ROI) was contoured on the images of the shredded rubber cartridge and the 3D printed, 20% fill, acrylonitrile butadiene styrene plastic cartridge (ABS20) for all phantom imaging sets. Radiomics features were extracted from the ROIs using an in-house program. Features categories were: shape (10), intensity (16), GLCM (24), GLZSM (11), GLRLM (11), and NGTDM (5), fractal dimensions (8) and first order wavelets (128), for a total of 213 features. Voxel size resampling was performed to investigate the usefulness of extracting features using a suitably chosen voxel size. Acquired phantom image sets were resampled to a voxel size of 1 × 1 × 2 mm3 using linear interpolation. Image features were therefore extracted from resampled and original data sets and the absolute value of the percent coefficient of variation (%COV) for each feature was calculated. Based on %COV values, features were classified in 3 groups: 1) features with large variations before and after resampling (%COV > 50); 2) features with diminished variation (%COV < 30) after resampling; and 3) features that had originally moderate variation (%COV < 50%) and were negligibly affected by resampling. Group 2 features were further studied by modifying feature definitions to include voxel size. Original and voxel-size normalized features were used for interscanner comparisons. A subsequent analysis investigated feature dependency on gray level discretization by extracting 51 texture features from ROIs from each of the 10 different phantom cartridges using 16, 32, 64, 128 and 256 gray levels. Results Out of the 213 features extracted, 150 were reproducible across voxel sizes, 42 improved significantly (%COV < 30, Group 2) after resampling, and 21 had large variations before and after resampling (Group 1). Ten features improved significantly after definition modification effectively removed their voxel size dependency. Interscanner comparison indicated that feature variability among scanners nearly vanished for 8 of these 10 features. Furthermore, 17 out of 51 texture features were found to be dependent on the number of gray levels. These features were redef...

No abstract

IntroductionMacrophage migration inhibitory factor (MIF), a pro-inflammatory cytokine, is constitutively expressed in urothelial cells that also express protease-activated receptors (PAR). Urothelial PAR1 receptors were shown to mediate bladder inflammation. We showed that PAR1 and PAR4 activator, thrombin, also mediates urothelial MIF release. We hypothesized that stimulation of urothelial PAR1 or PAR4 receptors elicits release of urothelial MIF that acts on MIF receptors in the urothelium to mediate bladder inflammation and pain. Thus, we examined the effect of activation of specific bladder PAR receptors on MIF release, bladder pain, micturition and histological changes.MethodsMIF release was measured in vitro after exposing immortalized human urothelial cells (UROtsa) to PAR1 or PAR4 activating peptides (AP). Female C57BL/6 mice received intravesical PAR1- or PAR4-AP for one hour to determine: 1) bladder MIF release in vivo within one hour; 2) abdominal hypersensitivity (allodynia) to von Frey filament stimulation 24 hours after treatment; 3) micturition parameters 24 hours after treatment; 4) histological changes in the bladder as a result of treatment; 5) changes in expression of bladder MIF and MIF receptors using real-time RT-PCR; 6) changes in urothelial MIF and MIF receptor, CXCR4, protein levels using quantitative immunofluorescence; 7) effect of MIF or CXCR4 antagonism.ResultsPAR1- or PAR4-AP triggered MIF release from both human urothelial cells in vitro and mouse urothelium in vivo. Twenty-four hours after intravesical PAR1- or PAR4-AP, we observed abdominal hypersensitivity in mice without changes in micturition or bladder histology. PAR4-AP was more effective and also increased expression of bladder MIF and urothelium MIF receptor, CXCR4. Bladder CXCR4 localized to the urothelium. Antagonizing MIF with ISO-1 eliminated PAR4- and reduced PAR1-induced hypersensitivity, while antagonizing CXCR4 with AMD3100 only partially prevented PAR4-induced hypersensitivity.ConclusionsBladder PAR activation elicits urothelial MIF release and urothelial MIF receptor signaling at least partly through CXCR4 to result in abdominal hypersensitivity without overt bladder inflammation. PAR-induced bladder pain may represent an interesting pre-clinical model of Interstitial Cystitis/Painful Bladder Syndrome (IC/PBS) where pain occurs without apparent bladder injury or pathology. MIF is potentially a novel therapeutic target for bladder pain in IC/PBS patients.

The imaging performance of an amorphous selenium (a-Se) flat-panel detector for digital fluoroscopy was experimentally evaluated using the spatial frequency dependent modulation transfer function (MTF), noise power spectrum (NPS), and detective quantum efficiency (DQE). These parameters were investigated at beam qualities and exposures within the range typical of gastrointestinal fluoroscopic imaging (approximately 0.1 - 10 microR, 75 kV). The investigation does not take into consideration the detector cover, which in clinical use will lower the DQE measured here by its percent attenuation. The MTF was found to be less than the expected aperture response and the NPS was not white which together indicate presampling blurring. The cause of this blurring was attributed to charge trapping at the interface between two different layers of the a-Se. The effect on the DQE was also consistent with presampling blur, which reduces the aliasing in the NPS and thereby reduces the spatial frequency dependence of the DQE. (The DQE was independent of spatial frequency from 0.12 to 0.73 mm(-1) due to antialiasing of the NPS.) Moreover, the first zero of the measured MTF and the aperture response appeared at the same spatial frequency (6.66 mm(-1) for a pixel of 150 microm). Hence, the geometric fill factor (77%) was increased to an effective fill factor of 99 +/- 1%. A large scale ( approximately 32 pixels) correlation in the noise due to the configuration of the readout electronics caused increased noise power in the gate line NPS at low spatial frequency (< 0.1 mm(-1)). The DQE (f = 0) was exposure independent over a large range of exposures but became exposure dependent at low exposures due to the electronic noise.

Site‐specific investigations of the role of radiomics in cancer diagnosis and therapy are emerging. We evaluated the reproducibility of radiomic features extracted from 18Flourine–fluorodeoxyglucose (18F‐FDG) PET images for three parameters: manual versus computer‐aided segmentation methods, gray‐level discretization, and PET image reconstruction algorithms. Our cohort consisted of pretreatment PET/CT scans from 88 cervical cancer patients. Two board‐certified radiation oncologists manually segmented the metabolic tumor volume (MTV1 and MTV2) for each patient. For comparison, we used a graphical‐based method to generate semiautomated segmented volumes (GBSV). To address any perturbations in radiomic feature values, we down‐sampled the tumor volumes into three gray‐levels: 32, 64, and 128 from the original gray‐level of 256. Finally, we analyzed the effect on radiomic features on PET images of eight patients due to four PET 3D‐reconstruction algorithms: maximum likelihood‐ordered subset expectation maximization (OSEM) iterative reconstruction (IR) method, fourier rebinning‐ML‐OSEM (FOREIR), FORE‐filtered back projection (FOREFBP), and 3D‐Reprojection (3DRP) analytical method. We extracted 79 features from all segmentation method, gray‐levels of down‐sampled volumes, and PET reconstruction algorithms. The features were extracted using gray‐level co‐occurrence matrices (GLCM), gray‐level size zone matrices (GLSZM), gray‐level run‐length matrices (GLRLM), neighborhood gray‐tone difference matrices (NGTDM), shape‐based features (SF), and intensity histogram features (IHF). We computed the Dice coefficient between each MTV and GBSV to measure segmentation accuracy. Coefficient values close to one indicate high agreement, and values close to zero indicate low agreement. We evaluated the effect on radiomic features by calculating the mean percentage differences (d¯) between feature values measured from each pair of parameter elements (i.e. segmentation methods: MTV1‐MTV2, MTV1‐GBSV, MTV2‐GBSV; gray‐levels: 64‐32, 64‐128, and 64‐256; reconstruction algorithms: OSEM‐FORE‐OSEM, OSEM‐FOREFBP, and OSEM‐3DRP). We used false|normald¯false| as a measure of radiomic feature reproducibility level, where any feature scored false|normald¯false| ±SD ≤ |25|% ± 35% was considered reproducible. We used Bland–Altman analysis to evaluate the mean, standard deviation (SD), and upper/lower reproducibility limits (U/LRL) for radiomic features in response to variation in each testing parameter. Furthermore, we proposed U/LRL as a method to classify the level of reproducibility: High— ±1% ≤ U/LRL ≤ ±30%; Intermediate— ±30% < U/LRL ≤ ±45%; Low— ±45 < U/LRL ≤ ±50%. We considered any feature below the low level as nonreproducible (NR). Finally, we calculated the interclass correlation coefficient (ICC) to evaluate the reliability of radiomic feature measurements for each parameter. The segmented volumes of 65 patients (81.3%) scored Dice coefficient >0.75 for all three volumes. The result outcomes revealed a tendency of higher radiomic fe...