Effects of Respiratory Motion on Y-90 PET Dosimetry for SIRT

Respiratory motion degrades the quantification accuracy of PET imaging by blurring the radioactivity distribution. In the case of post-SIRT PET-CT verification imaging, respiratory motion can lead to inaccuracies in dosimetric measures. Using an anthropomorphic phantom filled with 90Y at a range of clinically relevant activities, together with a respiratory motion platform performing realistic motions (10–15 mm amplitude), we assessed the impact of respiratory motion on PET-derived post-SIRT dosimetry. Two PET scanners at two sites were included in the assessment. The phantom experiments showed that device-driven quiescent period respiratory motion correction improved the accuracy of the quantification with statistically significant increases in both the mean contrast recovery (+5%, p = 0.003) and the threshold activities corresponding to the dose to 80% of the volume of interest (+6%, p < 0.001). Although quiescent period gating also reduces the number of counts and hence increases the noise in the PET image, its use is encouraged where accurate quantification of the above metrics is desired.

Determination of 18 Intact Glucosinolates in Brassicaceae Vegetables by UHPLC-MS/MS: Comparing Tissue Disruption Methods for Sample Preparation

Glucosinolates (GSLs) are important precursor compounds with anticancer activities in Brassicaceae vegetables and are readily hydrolyzed by myrosinase. Given the diversity of these species, establishing an accurate and universal method to quantify intact GSLs in different plant tissues is necessary. Here, we compared and optimized three tissue disruption methods for sample preparation. After microwave treatment for 90 s, 13 GSLs in homogenized Chinese cabbage samples were recovered at 73–124%. However, a limitation of this method was that different tissues could not be processed under the same microwave conditions. Regarding universality, GSLs in Brassicaceae vegetables could be extracted from freeze-dried sample powder with 70% methanol (v/v) or frozen-fresh sample powder with 80% methanol (v/v). Moreover, heating extraction is necessary for GSLs extracted from frozen-fresh sample powder. Average recoveries of the two optimized methods were 74–119% with relative standard deviations ≤15%, with the limits of quantification 5.72–17.40 nmol/g dry weight and 0.80–1.43 nmol/g fresh weight, respectively. Notably, the method for analyzing intact GSLs was more efficient than that for desulfo-GSLs regarding operational complexity, detection speed and quantification accuracy. The developed method was applied to identify the characteristic GSLs in 15 Brassicaceae vegetables, providing a foundation for further research on GSLs.

Technique development of high-throughput and high-sensitivity sample preparation and separation for proteomics

Sample preparation and separation methods determine the sensitivity and the quantification accuracy of the proteomics analysis. This article covers a comprehensive review of the recent technique development of high-throughput and high-sensitivity sample preparation and separation methods in proteomics research.

Image quality and quantification accuracy dependence on patient body mass in 89Zr PET/CT imaging

Background This study was conducted to clarify how patient body mass affects the image quality and quantification accuracy of images obtained using 89Zr PET/CT. 89Zr PET/CT images from time-of-flight (TOF) PET/CT and semiconductor (SC) PET/CT were obtained using three types (M, L, LL; corresponding to increasing patient body weight) of custom-made body phantoms designed similarly to the National Electrical Manufacturers Association (NEMA) IEC body phantom. The phantom data were analyzed visually and quantitatively to derive image quality metrics, namely detectability of the 10-mm-diameter hot sphere, percent contrast for the 10-mm-diameter hot sphere (QH,10 mm), percent background variability (N10mm), contrast-to-noise ratio (QH,10 mm/N10mm), and coefficient of variation of the background area (CVBG). Results Visual assessment revealed that all the 10-mm-diameter hot spheres of the three types of phantoms were identifiable on both SC and TOF PET/CT images. The N10mm and CVBG values were within the proposed reference levels, and decreased with acquisition duration for both PET/CT types. At 10-min acquisition, the QH,10 mm/N10mm of SC PET/CT was greater than the proposed reference level in all phantoms. However, the QH,10 mm/N10mm of TOF PET/CT was greater than the proposed reference level in M-type phantom alone. All the SUVBG values were within 1.00 ± 0.05 for both PET/CT types. Conclusions This study showed that the image quality and quantification accuracy depend on the patient’s body mass, suggesting that acquisition time on 89Zr PET/CT should be changed according to the patient’s body mass.

Cross-Platform Evaluation of Commercially Targeted and Untargeted Metabolomics Approaches to Optimize the Investigation of Psychiatric Disease

Metabolomics methods often encounter trade-offs between quantification accuracy and coverage, with truly comprehensive coverage only attainable through a multitude of complementary assays. Due to the lack of standardization and the variety of metabolomics assays, it is difficult to integrate datasets across studies or assays. To inform metabolomics platform selection, with a focus on posttraumatic stress disorder (PTSD), we review platform use and sample sizes in psychiatric metabolomics studies and then evaluate five prominent metabolomics platforms for coverage and performance, including intra-/inter-assay precision, accuracy, and linearity. We found performance was variable between metabolite classes, but comparable across targeted and untargeted approaches. Within all platforms, precision and accuracy were highly variable across classes, ranging from 0.9–63.2% (coefficient of variation) and 0.6–99.1% for accuracy to reference plasma. Several classes had high inter-assay variance, potentially impeding dissociation of a biological signal, including glycerophospholipids, organooxygen compounds, and fatty acids. Coverage was platform-specific and ranged from 16–70% of PTSD-associated metabolites. Non-overlapping coverage is challenging; however, benefits of applying multiple metabolomics technologies must be weighed against cost, biospecimen availability, platform-specific normative levels, and challenges in merging datasets. Our findings and open-access cross-platform dataset can inform platform selection and dataset integration based on platform-specific coverage breadth/overlap and metabolite-specific performance.

Fast myocardial T1ρ mapping in mice using k-space weighted image contrast and a Bloch simulation-optimized radial sampling pattern

Purpose T1ρ dispersion quantification can potentially be used as a cardiac magnetic resonance index for sensitive detection of myocardial fibrosis without the need of contrast agents. However, dispersion quantification is still a major challenge, because T1ρ mapping for different spin lock amplitudes is a very time consuming process. This study aims to develop a fast and accurate T1ρ mapping sequence, which paves the way to cardiac T1ρ dispersion quantification within the limited measurement time of an in vivo study in small animals. Methods A radial spin lock sequence was developed using a Bloch simulation-optimized sampling pattern and a view-sharing method for image reconstruction. For validation, phantom measurements with a conventional sampling pattern and a gold standard sequence were compared to examine T1ρ quantification accuracy. The in vivo validation of T1ρ mapping was performed in N = 10 mice and in a reproduction study in a single animal, in which ten maps were acquired in direct succession. Finally, the feasibility of myocardial dispersion quantification was tested in one animal. Results The Bloch simulation-based sampling shows considerably higher image quality as well as improved T1ρ quantification accuracy (+ 56%) and precision (+ 49%) compared to conventional sampling. Compared to the gold standard sequence, a mean deviation of − 0.46 ± 1.84% was observed. The in vivo measurements proved high reproducibility of myocardial T1ρ mapping. The mean T1ρ in the left ventricle was 39.5 ± 1.2 ms for different animals and the maximum deviation was 2.1% in the successive measurements. The myocardial T1ρ dispersion slope, which was measured for the first time in one animal, could be determined to be 4.76 ± 0.23 ms/kHz. Conclusion This new and fast T1ρ quantification technique enables high-resolution myocardial T1ρ mapping and even dispersion quantification within the limited time of an in vivo study and could, therefore, be a reliable tool for improved tissue characterization.

Comparison of LFQ and IPTL for Protein Identification and Relative Quantification

(1) Background: Mass spectrometry-based quantitative proteome profiling is most commonly performed by label-free quantification (LFQ), stable isotopic labeling with amino acids in cell culture (SILAC), and reporter ion-based isobaric labeling methods (TMT and iTRAQ). Isobaric peptide termini labeling (IPTL) was described as an alternative to these methods and is based on crosswise labeling of both peptide termini and MS2 quantification. High quantification accuracy was assumed for IPTL because multiple quantification points are obtained per identified MS2 spectrum. A direct comparison of IPTL with other quantification methods has not been performed yet because IPTL commonly requires digestion with endoproteinase Lys-C. (2) Methods: To enable tryptic digestion of IPTL samples, a novel labeling for IPTL was developed that combines metabolic labeling (Arg-0/Lys-0 and Arg-d4/Lys-d4, respectively) with crosswise N-terminal dimethylation (d4 and d0, respectively). (3) Results: The comparison of IPTL with LFQ revealed significantly more protein identifications for LFQ above homology ion scores but not above identity ion scores. (4) Conclusions: The quantification accuracy was superior for LFQ despite the many quantification points obtained with IPTL.

Median based absolute quantification of proteins using Fully Unlabelled Generic Internal Standard

By reporting molar abundances of proteins, absolute quantification determines their stoichiometry in complexes, pathways or networks and also relates them to abundances of non-protein biomolecules. Typically, absolute quantification relies either on protein- specific isotopically labelled peptide standards or on a semiempirical calibration against the average abundance of peptides chosen from arbitrary selected standard proteins. Here we developed a generic protein standard FUGIS (Fully unlabelled Generic Internal Standard) that requires no isotopic labelling, synthesis of standards or external calibration and is applicable to proteins of any organismal origin. FUGIS is co-digested with analysed proteins and enables their absolute quantification in the same LC-MS/MS run. By using FUGIS, median based absolute quantification (MBAQ) workflow provides similar quantification accuracy compared to isotopically-labelled peptide standards and outperforms methods based on external calibration or selection of best ionized reporter peptides (e.g. Top3 quantification) with a median quantification error below 20%

Comparative evaluation of full-length isoform quantification from RNA-Seq

Background Full-length isoform quantification from RNA-Seq is a key goal in transcriptomics analyses and has been an area of active development since the beginning. The fundamental difficulty stems from the fact that RNA transcripts are long, while RNA-Seq reads are short. Results Here we use simulated benchmarking data that reflects many properties of real data, including polymorphisms, intron signal and non-uniform coverage, allowing for systematic comparative analyses of isoform quantification accuracy and its impact on differential expression analysis. Genome, transcriptome and pseudo alignment-based methods are included; and a simple approach is included as a baseline control. Conclusions Salmon, kallisto, RSEM, and Cufflinks exhibit the highest accuracy on idealized data, while on more realistic data they do not perform dramatically better than the simple approach. We determine the structural parameters with the greatest impact on quantification accuracy to be length and sequence compression complexity and not so much the number of isoforms. The effect of incomplete annotation on performance is also investigated. Overall, the tested methods show sufficient divergence from the truth to suggest that full-length isoform quantification and isoform level DE should still be employed selectively.

Phantom and clinical assessment of small pulmonary nodules using Q.Clear reconstruction on a silicon-photomultiplier-based time-of-flight PET/CT system

To evaluate the quantification accuracy of different positron emission tomography-computed tomography (PET/CT) reconstruction algorithms, we measured the recovery coefficient (RC) and contrast recovery (CR) in phantom studies. The results played a guiding role in the partial-volume-effect correction (PVC) for following clinical evaluations. The PET images were reconstructed with four different methods: ordered subsets expectation maximization (OSEM), OSEM with time-of-flight (TOF), OSEM with TOF and point spread function (PSF), and Bayesian penalized likelihood (BPL, known as Q.Clear in the PET/CT of GE Healthcare). In clinical studies, SUVmax and SUVmean (the maximum and mean of the standardized uptake values, SUVs) of 75 small pulmonary nodules (sub-centimeter group: < 10 mm and medium-size group: 10–25 mm) were measured from 26 patients. Results show that Q.Clear produced higher RC and CR values, which can improve quantification accuracy compared with other methods (P < 0.05), except for the RC of 37 mm sphere (P > 0.05). The SUVs of sub-centimeter fludeoxyglucose (FDG)-avid pulmonary nodules with Q.Clear illustrated highly significant differences from those reconstructed with other algorithms (P < 0.001). After performing the PVC, highly significant differences (P < 0.001) still existed in the SUVmean measured by Q.Clear comparing with those measured by the other algorithms. Our results suggest that the Q.Clear reconstruction algorithm improved the quantification accuracy towards the true uptake, which potentially promotes the diagnostic confidence and treatment response evaluations with PET/CT imaging, especially for the sub-centimeter pulmonary nodules. For small lesions, PVC is essential.