The aim of this study was to evaluate the physical performance of the Vereos whole-body PET/CT system according to the National Electrical Manufacturers Association (NEMA) NU2-2012 standard and to compare it with other state-of-the-art PET/CT systems. Methods: Spatial resolution, sensitivity, count-rate performance, count rate accuracy, and image quality were assessed. Specifically, spatial resolution was measured using an 18 F point-source. System sensitivity was calculated from acquisitions of an 18 F line source inside aluminum tubes of varying thickness. Assessment of count rate performance and count rate accuracy was based on measurements of an 18 F line source inside a 20-cm-diameter polyethylene cylinder. PET image quality was assessed using a NEMA IQ phantom. All measurements were performed according to the predefined and implemented NEMA NU2-2012 acquisition protocols at a clinical installation of a Vereos PET/CT system. Evaluation was performed using the software provided by the vendor. Results: The average (radial and tangential) transverse spatial resolution was 4.2, 4.5, and 5.5 mm in full width at half maximum for a 1-, 10-, and 20-cm radial offset, respectively, from the center of the field of view. Axial spatial resolution varied between 4.2 and 4.6 mm in full width at half maximum, depending on the radial source position. The average sensitivity was 5.2 cps/kBq. A peak noise-equivalent count (NEC) rate of 153.4 kcps was measured at an activity concentration of 54.9 kBq/mL. The scatter fraction at peak NEC rate was 33.9%, and the maximum count rate error at and below peak NEC rate was 6.8%. Contrast recovery coefficients varied from 54.3% (10-mm sphere) to 83.9% (22-mm sphere) for the hot spheres, and between 81.4% (28-mm sphere) and 87% (37-mm sphere) for the cold spheres for a given sphere-to-background ratio of 4:1. Conclusion: The overall performance characteristics of the Vereos PET/CT system are comparable to state-of-the-art wholebody PET/CT systems with the exception that the peak NEC rate occurs at a higher activity concentration, thus indicating the ability of the Vereos PET/CT system to cover a wider range of activities.

BackgroundThe purpose of the study is to evaluate the physical performance of a Biograph mCT Flow 64-4R PET/CT system (Siemens Healthcare, Germany) and to compare clinical image quality in step-and-shoot (SS) and continuous table motion (CTM) acquisitions.MethodsThe spatial resolution, sensitivity, count rate curves, and Image Quality (IQ) parameters following the National Electrical Manufactures Association (NEMA) NU2-2012 standard were evaluated. For resolution measurements, an 18F point source inside a glass capillary tube was used. Sensitivity measurements were based on a 70-cm-long polyethylene tube, filled with 4.5 MBq of FDG. Scatter fraction and count rates were measured using a 70-cm-long polyethylene cylinder with a diameter of 20 cm and a line source (1.04 GBq of FDG) inserted axially into the cylinder 4.5 cm off-centered. A NEMA IQ phantom containing six spheres (10- to 37-mm diameter) was used for the evaluation of the image quality. First, a single-bed scan was acquired (NEMA standard), followed by a two-bed scan (4 min each) of the IQ phantom with the image plane containing the spheres centered in the overlap region of the two bed positions. In addition, a scan of the same region in CTM mode was performed with a table speed of 0.6 mm/s. Furthermore, two patient scans were performed in CTM and SS mode. Image contrasts and patient images were compared between SS and CTM acquisitions.ResultsFull Width Half Maximum (FWHM) of the spatial resolution ranged from 4.3 to 7.8 mm (radial distance 1 to 20 cm). The measured sensitivity was 9.6 kcps/MBq, both at the center of the FOV and 10 cm off-center. The measured noise equivalent count rate (NECR) peak was 185 kcps at 29.0 kBq/ml. The scatter fraction was 33.5 %. Image contrast recovery values (sphere-to-background of 8:1) were between 42 % (10-mm sphere) to 79 % (37-mm sphere). The background variability was between 2.1 and 5.3 % (SS) and between 2.4 and 6.9 % (CTM). No significant difference in image quality was observed between SS and CTM mode.ConclusionsThe spatial resolution, sensitivity, scatter fraction, and count rates were in concordance with the published values for the predecessor system, the Biograph mCT. Contrast recovery values as well as image quality obtained in SS and CTM acquisition modes were similar.

Absolute quantification of PET brain imaging requires the measurement of an arterial input function (AIF), typically obtained invasively via an arterial cannulation. We present an approach to automatically calculate an image-derived input function (IDIF) and cerebral metabolic rates of glucose (CMRGlc) from the [18F]FDG PET data using an integrated PET/MRI system. Ten healthy controls underwent test-retest dynamic [18F]FDG-PET/MRI examinations. The imaging protocol consisted of a 60-min PET list-mode acquisition together with a time-of-flight MR angiography scan for segmenting the carotid arteries and intermittent MR navigators to monitor subject movement. AIFs were collected as the reference standard. Attenuation correction was performed using a separate low-dose CT scan. Assessment of the percentage difference between area-under-the-curve of IDIF and AIF yielded values within ±5%. Similar test-retest variability was seen between AIFs (9 ± 8) % and the IDIFs (9 ± 7) %. Absolute percentage difference between CMRGlc values obtained from AIF and IDIF across all examinations and selected brain regions was 3.2% (interquartile range: (2.4-4.3) %, maximum < 10%). High test-retest intravariability was observed between CMRGlc values obtained from AIF (14%) and IDIF (17%). The proposed approach provides an IDIF, which can be effectively used in lieu of AIF.

Purpose Risk classification of primary prostate cancer in clinical routine is mainly based on prostate-specific antigen (PSA) levels, Gleason scores from biopsy samples, and tumor-nodes-metastasis (TNM) staging. This study aimed to investigate the diagnostic performance of positron emission tomography/magnetic resonance imaging (PET/MRI) in vivo models for predicting low-vs-high lesion risk (LH) as well as biochemical recurrence (BCR) and overall patient risk (OPR) with machine learning. Methods Fifty-two patients who underwent multi-parametric dual-tracer [18F]FMC and [68Ga]Ga-PSMA-11 PET/MRI as well as radical prostatectomy between 2014 and 2015 were included as part of a single-center pilot to a randomized prospective trial (NCT02659527). Radiomics in combination with ensemble machine learning was applied including the [68Ga]Ga-PSMA-11 PET, the apparent diffusion coefficient, and the transverse relaxation time-weighted MRI scans of each patient to establish a low-vs-high risk lesion prediction model (MLH). Furthermore, MBCR and MOPR predictive model schemes were built by combining MLH, PSA, and clinical stage values of patients. Performance evaluation of the established models was performed with 1000-fold Monte Carlo (MC) cross-validation. Results were additionally compared to conventional [68Ga]Ga-PSMA-11 standardized uptake value (SUV) analyses. Results The area under the receiver operator characteristic curve (AUC) of the MLH model (0.86) was higher than the AUC of the [68Ga]Ga-PSMA-11 SUVmax analysis (0.80). MC cross-validation revealed 89% and 91% accuracies with 0.90 and 0.94 AUCs for the MBCR and MOPR models respectively, while standard routine analysis based on PSA, biopsy Gleason score, and TNM staging resulted in 69% and 70% accuracies to predict BCR and OPR respectively. Conclusion Our results demonstrate the potential to enhance risk classification in primary prostate cancer patients built on PET/MRI radiomics and machine learning without biopsy sampling.

Phantom-based quality control of PET/MR systems in a multicenter, multivendor setting may be performed with sufficient accuracy, but only when dedicated phantom acquisition and processing protocols are used for attenuation correction.

Background: In oncology, lesion characterization is essential for tumor grading, treatment planning, and follow-up of cancer patients. Hybrid imaging systems, such as Single Photon Emission Computed Tomography (SPECT)/CT, Positron Emission Tomography (PET)/CT, or PET/magnetic resonance imaging (MRI), play an essential role for the noninvasive quantification of tumor characteristics. However, most of the existing approaches are challenged by intra-and intertumor heterogeneity. Novel quantitative imaging parameters that can be derived from textural feature analysis (as part of radiomics) are promising complements for improved characterization of tumor heterogeneity, thus, supporting clinically relevant implementations of personalized medicine concepts. Nevertheless, establishing new quantitative parameters for tumor characterization requires the use of standardized imaging objects to test the reliability of results prior to their implementation in patient studies. Methods: In this review, we summarize existing reports on heterogeneous phantoms with a focus on simulating tumor heterogeneity. We discuss the techniques, materials, advantages, and limitations of the existing phantoms for PET, CT, and MR imaging modalities. Conclusions: Finally, we outline the future directions and requirements for the design of cross modality imaging phantoms.

PurposePET/MRI has recently been introduced into clinical practice. We prospectively investigated the clinical impact of PET/MRI compared with PET/CT, in a mixed population of cancer patients, and performed an economic evaluation of PET/MRI.MethodsCancer patients referred for routine staging or follow-up by PET/CT underwent consecutive PET/CT and PET/MRI, using single applications of [18F]FDG, [68Ga]Ga-DOTANOC, or [18F]FDOPA, depending on tumor histology. PET/MRI and PET/CT were rated separately, and lesions were assessed per anatomic region; based on regions, per-examination and per-patient accuracies were determined. A simulated, multidisciplinary team meeting served as reference standard and determined whether differences between PET/CT and PET/MRI affected patient management. The McNemar tests were used to compare accuracies, and incremental cost-effectiveness ratios (ICERs) for PET/MRI were calculated.ResultsTwo hundred sixty-three patients (330 same-day PET/CT and PET/MRI examinations) were included. PET/MRI was accurate in 319/330 examinations and PET/CT in 277/330 examinations; the respective accuracies of 97.3% and 83.9% differed significantly (P < 0.001). The additional findings on PET/MRI—mainly liver and brain metastases—had implications for patient management in 21/263 patients (8.0%). The per-examination cost was 596.97 EUR for PET/MRI and 405.95 EUR for PET/CT. ICERs for PET/MRI were 14.26 EUR per percent of diagnostic accuracy and 23.88 EUR per percent of correctly managed patients.ConclusionsPET/MRI enables more appropriate management than PET/CT in a nonnegligible fraction of cancer patients. Since the per-examination cost is about 50% higher for PET/MRI than for PET/CT, a histology-based triage of patients to either PET/MRI or PET/CT may be meaningful.

Radiomics analysis of 18 F-FDG PET/CT images promises well for an improved in vivo disease characterization. To date, several studies have reported significant variations in textural features due to differences in patient preparation, imaging protocols, lesion delineation, and feature extraction. Our objective was to study variations in features before a radiomics analysis of 18 F-FDG PET data and to identify those feature extraction and imaging protocol parameters that minimize radiomic feature variations across PET imaging systems. Methods: A whole-body National Electrical Manufacturers Association image-quality phantom was imaged with 13 PET/CT systems at 12 different sites following local protocols. We selected 37 radiomic features related to the 4 largest spheres (17-37 mm) in the phantom. On the basis of a combined analysis of voxel size, bin size, and lesion volume changes, feature and imaging system ranks were established. A 1-way ANOVA was performed over voxel size, bin size, and lesion volume subgroups to identify the dependency and the trend change in feature variations across these parameters. Results: Feature ranking revealed that the gray-level cooccurrence matrix and shape features are the least sensitive to PET imaging system variations. Imaging system ranking illustrated that the use of point-spread function, small voxel sizes, and narrow gaussian postfiltering helped minimize feature variations. ANOVA subgroup analysis indicated that variations in each of the 37 features and for a given voxel size and bin size can be minimized. Conclusion: Our results provide guidance to selecting optimized features from 18 F-FDG PET/CT studies. We were able to demonstrate that feature variations can be minimized for selected image parameters and imaging systems. These results can help imaging specialists and feature engineers in increasing the quality of future radiomics studies involving PET/CT.