Objective We demonstrate the feasibility of direct generation of attenuation and scatter-corrected images from uncorrected images (PET-nonASC) using deep residual networks in whole-body 18 F-FDG PET imaging. Methods Two-and three-dimensional deep residual networks using 2D successive slices (DL-2DS), 3D slices (DL-3DS) and 3D patches (DL-3DP) as input were constructed to perform joint attenuation and scatter correction on uncorrected whole-body images in an end-to-end fashion. We included 1150 clinical whole-body 18 F-FDG PET/CT studies, among which 900, 100 and 150 patients were randomly partitioned into training, validation and independent validation sets, respectively. The images generated by the proposed approach were assessed using various evaluation metrics, including the root-mean-squared-error (RMSE) and absolute relative error (ARE %) using CT-based attenuation and scatter-corrected (CTAC) PET images as reference. PET image quantification variability was also assessed through voxel-wise standardized uptake value (SUV) bias calculation in different regions of the body (head, neck, chest, liver-lung, abdomen and pelvis). Results Our proposed attenuation and scatter correction (Deep-JASC) algorithm provided good image quality, comparable with those produced by CTAC. Across the 150 patients of the independent external validation set, the voxel-wise REs (%) were − 1.72 ± 4.22%, 3.75 ± 6.91% and − 3.08 ± 5.64 for DL-2DS, DL-3DS and DL-3DP, respectively. Overall, the DL-2DS approach led to superior performance compared with the other two 3D approaches. The brain and neck regions had the highest and lowest RMSE values between Deep-JASC and CTAC images, respectively. However, the largest ARE was observed in the chest (15.16 This article is part of the Topical Collection on Advanced Image Analyses (Radiomics and Artificial Intelligence)

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Purpose: Xtrim-PET is a newly designed Silicon Photomultipliers (SiPMs)-based prototype PET scanner dedicated for small laboratory animal imaging. We present the performance evaluation of the Xtrim-PET scanner following NEMA NU-4 2008 standards to help optimizing scanning protocols which can be achieved through standard and reliable system performance characterization. Methods: The performance assessment was conducted according to the National Electrical Manufacturers Association (NEMA) NU-4 2008 standards in terms of spatial resolution, sensitivity, counting rate performance, scatter fraction and image quality. The in vivo imaging capability of the scanner is also showcased through scanning a normal mouse injected with 18 F-FDG. Furthermore, the performance characteristics of the developed scanner are compared with commercially available systems and current prototypes. Results: The volumetric spatial resolution at 5 mm radial offset from the central axis of the scanner is 6.81 µl, whereas a peak absolute sensitivity of 2.99% was achieved using a 250-650 keV energy window and a 10 ns timing window. The peak noise-equivalent count rate (NECR) using a mouselike phantom is 113.18 kcps at 0.34 KBq/cc with 12.5% scatter fraction, whereas the NECR peaked at 82.76 kcps for an activity concentration level of 0.048 KBq/cc with a scatter fraction of 25.8% for rat-like phantom. An excellent uniformity (3.8%) was obtained using NEMA image quality phantom. Recovery coefficients of 90%, 86%, 68%, 40% and 12% were calculated for rod diameters of 5, 4, 3, 2 and 1 mm, respectively. Spill-over ratios for air-filled and water-filled chambers were 35% and 25% without applying any correction for attenuation and Compton scattering effects. Conclusion: Our findings revealed that beyond compactness, lightweight, easy installation and good energy resolution, the Xtrim-PET prototype presents a reasonable performance making it suitable for preclinical molecular imaging-based research.

The respiratory motion-induced errors in tumor quantification and delineation are highly dependent upon the motion amplitude, tumor location, tumor size, and choice of the attenuation map for PET image attenuation correction.

Results indicate that STE/Dixon-MRI data in combination with FCM-based segmentation yields precise MR-based μ-maps for PET attenuation correction in hybrid PET/MRI systems.

Beam hardening filters have long been employed in X-ray Computed Tomography (CT) to preferentially absorb soft and low-energy X-rays having no or little contribution to image formation, thus allowing the reduction of patient dose and beam hardening artefacts. In this work, we studied the influence of additional copper (Cu) and aluminium (Al) flat filters on patient dose and image quality and seek an optimum filter thickness for the GE LightSpeed VCT 64-slice CT scanner using experimental phantom measurements. Different thicknesses of Cu and Al filters (0.5-1.6mm Cu, 0.5-4mm Al) were installed on the scanner's collimator. A planar phantom consisting of 13 slabs of Cu having different thicknesses was designed and scanned to assess the impact of beam filtration on contrast in the intensity domain (CT detector's output). To assess image contrast and image noise, a cylindrical phantom consisting of a polyethylene cylinder having 16 holes filled with different concentrations of K2HPO4 solution mimicking different tissue types was used. The GE performance and the standard head CT dose index (CTDI) phantoms were also used to assess image resolution characterized by the modulation transfer function (MTF) and patient dose defined by the weighted CTDI. A 100mm pencil ionization chamber was used for CTDI measurement. Finally, an optimum filter thickness was determined from an objective figure of merit (FOM) metric. The results show that the contrast is somewhat compromised with filter thickness in both the planar and cylindrical phantoms. The contrast of the K2HPO4 solutions in the cylindrical phantom was degraded by up to 10% for a 0.68mm Cu filter and 6% for a 4.14mm Al filter. It was shown that additional filters increase image noise which impaired the detectability of low density K2HPO4 solutions. It was found that with a 0.48mm Cu filter the 50% MTF value is shifted by about 0.77lp/cm compared to the case where the filter is not used. An added Cu filter with approximately 0.5mm thickness accounts for 50% reduction in radiation-absorbed dose as measured by the weighted CTDI. The FOM results indicate that with an additional filter of 0.5mm Cu or minimum 4mm Al, a good compromise between image quality and patient dose is achieved for CT images acquired at tube voltages of 120 and 140kVp. The results seem to indicate that an optimum filter for high kVp acquisitions, routinely used in cardiovascular imaging, should be 0.5mm copper or 4mm aluminium minimum.

Small‐animal single‐photon emission computed tomography (SPECT) system plays an important role in the field of drug development and investigation of potential drugs in the preclinical phase. The small‐animal High‐Resolution SPECT (HiReSPECT) scanner has been recently designed and developed based on compact and high‐resolution detectors. The detectors are based on a high‐resolution parallel hole collimator, a cesium iodide (sodium‐activated) pixelated crystal array and two H8500 position‐sensitive photomultiplier tubes. In this system, a full set of data corrections such as energy, linearity, and uniformity, together with resolution recovery option in reconstruction algorithms, are available. In this study, we assessed the performance of the system based on NEMA‐NU1–2007 standards for pixelated detector cameras. Characterization of the HiReSPECT was performed by measurement of the physical parameters including planar and tomographic performance. The planar performance of the system was characterized with flood‐field phantom for energy resolution and uniformity. Spatial resolution and sensitivity were evaluated as functions of distance with capillary tube and cylindrical source, respectively. Tomographic spatial resolution was characterized as a function of radius of rotation (ROR). A dedicated hot rod phantom and image quality phantom was used for the evaluation of overall tomographic quality of the HiReSPECT. The results showed that the planar spatial resolution was ~1.6.15emmm and ~.15em2.3.15emmm in terms of full‐width at half‐maximum (FWHM) along short‐ and long‐axis dimensions, respectively, when the source was placed on the detector surface. The integral uniformity of the system after uniformity correction was 1.7% and 1.2% in useful field of view (UFOV) and central field of view (CFOV), respectively. System sensitivity on the collimator surface was 1.31.15emcps/μCi and didn't vary significantly with distance. Mean tomographic spatial resolution was measured ∼1.7 mm FWHM at the radius of rotation of 25 mm with dual‐head configuration.The measured performance demonstrated that the HiReSPECT scanner has acceptable image quality and, hence, is well suited for preclinical molecular imaging research.PACS number: 87.57.U

Objectives This study is aimed at examining the synergistic impact of motion and acquisition/reconstruction parameters on 18F‐FDG PET image radiomic features in non‐small cell lung cancer (NSCLC) patients, and investigating the robustness of features performance in differentiating NSCLC histopathology subtypes. Methods An in‐house developed thoracic phantom incorporating lesions with different sizes was used with different reconstruction settings, including various reconstruction algorithms, number of subsets and iterations, full‐width at half‐maximum of post‐reconstruction smoothing filter and acquisition parameters, including injected activity and test–retest with and without motion simulation. To simulate motion, a special motor was manufactured to simulate respiratory motion based on a normal patient in two directions. The lesions were delineated semi‐automatically to extract 174 radiomic features. All radiomic features were categorized according to the coefficient of variation (COV) to select robust features. A cohort consisting of 40 NSCLC patients with adenocarcinoma (n = 20) and squamous cell carcinoma (n = 20) was retrospectively analyzed. Statistical analysis was performed to discriminate robust features in differentiating histopathology subtypes of NSCLC lesions. Results Overall, 29% of radiomic features showed a COV ≤5% against motion. Forty‐five percent and 76% of the features showed a COV ≤ 5% against the test–retest with and without motion in large lesions, respectively. Thirty‐three percent and 45% of the features showed a COV ≤ 5% against different reconstruction parameters with and without motion, respectively. For NSCLC histopathological subtype differentiation, statistical analysis showed that 31 features were significant (p‐value < 0.05). Two out of the 31 significant features, namely, the joint entropy of GLCM (AUC = 0.71, COV = 0.019) and median absolute deviation of intensity histogram (AUC = 0.7, COV = 0.046), were robust against the motion (same reconstruction setting). Conclusions Motion, acquisition, and reconstruction parameters significantly impact radiomic features, just as their synergies. Radiomic features with high predictive performance (statistically significant) in differentiating histopathological subtype of NSCLC may be eliminated due to non‐reproducibility.