Novel penalised likelihood reconstruction of PET in the assessment of histologically verified small pulmonary nodules

OBJECTIVES: Investigate the effect of a novel Bayesian penalised likelihood (BPL) reconstruction algorithm on analysis of pulmonary nodules examined with 18F-FDG PET/CT, and to determine its effect on small, sub-10-mm nodules. METHODS: 18F-FDG PET/CTs performed for nodule evaluation in 104 patients (121 nodules) were retrospectively reconstructed using the new algorithm, and compared to time-of-flight ordered subset expectation maximisation (OSEM) reconstruction. Nodule and background parameters were analysed semi-quantitatively and visually. RESULTS: BPL compared to OSEM resulted in statistically significant increases in nodule SUV(max) (mean 5.3 to 8.1, p < 0.00001), signal-to-background (mean 3.6 to 5.3, p < 0.00001) and signal-to-noise (mean 24 to 41, p < 0.00001). Mean percentage increase in SUV(max) (%ΔSUV(max)) was significantly higher in nodules ≤10 mm (n = 31, mean 73 %) compared to >10 mm (n = 90, mean 42 %) (p = 0.025). Increase in signal-to-noise was higher in nodules ≤10 mm (224 %, mean 12 to 27) compared to >10 mm (165 %, mean 28 to 46). When applying optimum SUV(max) thresholds for detecting malignancy, the sensitivity and accuracy increased using BPL, with the greatest improvements in nodules ≤10 mm. CONCLUSION: BPL results in a significant increase in signal-to-background and signal-to-noise compared to OSEM. When semi-quantitative analyses to diagnose malignancy are applied, higher SUV(max) thresholds may be warranted owing to the SUV(max) increase compared to OSEM. KEY POINTS: • Novel Bayesian penalised likelihood PET reconstruction was applied for lung nodule evaluation. • This was compared to current standard of care OSEM reconstruction. • The novel reconstruction generated significant increases in lung nodule signal-to-background and signal-to-noise. • These increases were highest in small, sub-10-mm pulmonary nodules. • Higher SUV(max)thresholds may be warranted when using semi-quantitative analyses to diagnose malignancy

18F-FDG PET/CT assessment of histopathologically confirmed mediastinal lymph nodes in non-small cell lung cancer using a penalised likelihood reconstruction

Purpose To investigate whether using a Bayesian penalised likelihood reconstruction (BPL) improves signal-to-background (SBR), signal-to-noise (SNR) and SUVmax when evaluating mediastinal nodal disease in non-small cell lung cancer (NSCLC) compared to ordered subset expectation maximum (OSEM) reconstruction. Materials and methods 18F-FDG PET/CT scans for NSCLC staging in 47 patients (112 nodal stations with histopathological confirmation) were reconstructed using BPL and compared to OSEM. Node and multiple background SUV parameters were analysed semi-quantitatively and visually. Results Comparing BPL to OSEM, there were significant increases in SUVmax (mean 3.2–4.0, p<0.0001), SBR (mean 2.2–2.6, p<0.0001) and SNR (mean 27.7–40.9, p<0.0001). Mean background SNR on OSEM was 10.4 (range 7.6–14.0), increasing to 12.4 (range 8.2–16.7, p<0.0001). Changes in background SUVs were minimal (largest mean difference 0.17 for liver SUVmean, p<0.001). There was no significant difference between either algorithm on receiver operating characteristic analysis (p=0.26), although on visual analysis, there was an increase in sensitivity and small decrease in specificity and accuracy on BPL. Conclusion BPL increases SBR, SNR and SUVmax of mediastinal nodes in NSCLC compared to OSEM, but did not improve the accuracy for determining nodal involvement

Scaling of the distribution of fluctuations of financial market indices

We study the distribution of fluctuations over a time scale $\Delta t$ (i.e., the returns) of the S&P 500 index by analyzing three distinct databases. Database (i) contains approximately 1 million records sampled at 1 min intervals for the 13-year period 1984-1996, database (ii) contains 8686 daily records for the 35-year period 1962-1996, and database (iii) contains 852 monthly records for the 71-year period 1926-1996. We compute the probability distributions of returns over a time scale $\Delta t$, where $\Delta t$ varies approximately over a factor of 10^4 - from 1 min up to more than 1 month. We find that the distributions for $\Delta t \leq$ 4 days (1560 mins) are consistent with a power-law asymptotic behavior, characterized by an exponent $\alpha \approx 3$, well outside the stable L\'evy regime $0 < \alpha < 2$. To test the robustness of the S&P result, we perform a parallel analysis on two other financial market indices. Database (iv) contains 3560 daily records of the NIKKEI index for the 14-year period 1984-97, and database (v) contains 4649 daily records of the Hang-Seng index for the 18-year period 1980-97. We find estimates of $\alpha$ consistent with those describing the distribution of S&P 500 daily-returns. One possible reason for the scaling of these distributions is the long persistence of the autocorrelation function of the volatility. For time scales longer than $(\Delta t)_{\times} \approx 4$ days, our results are consistent with slow convergence to Gaussian behavior.Comment: 12 pages in multicol LaTeX format with 27 postscript figures (Submitted to PRE May 20, 1999). See http://polymer.bu.edu/~amaral/Professional.html for more of our work on this are

Genome and Environmental Activity of a Chrysochromulina parva Virus and Its Virophages

Some giant viruses are ecological agents that are predicted to be involved in the top-down control of single-celled eukaryotic algae populations in aquatic ecosystems. Despite an increased interest in giant viruses since the discovery and characterization of Mimivirus and other viral giants, little is known about their physiology and ecology. In this study, we characterized the genome and functional potential of a giant virus that infects the freshwater haptophyte Chrysochromulina parva, originally isolated from Lake Ontario. This virus, CpV-BQ2, is a member of the nucleo-cytoplasmic large DNA virus (NCLDV) group and possesses a 437 kb genome encoding 503 ORFs with a GC content of 25%. Phylogenetic analyses of core NCLDV genes place CpV-BQ2 amongst the emerging group of algae-infecting Mimiviruses informally referred to as the “extended Mimiviridae,” making it the first virus of this group to be isolated from a freshwater ecosystem. During genome analyses, we also captured and described the genomes of three distinct virophages that co-occurred with CpV-BQ2 and likely exploit CpV for their own replication. These virophages belong to the polinton-like viruses (PLV) group and encompass 19–23 predicted genes, including all of the core PLV genes as well as several genes implicated in genome modifications. We used the CpV-BQ2 and virophage reference sequences to recruit reads from available environmental metatranscriptomic data to estimate their activity in fresh waters. We observed moderate recruitment of both virus and virophage transcripts in samples obtained during Microcystis aeruginosa blooms in Lake Erie and Lake Tai, China in 2013, with a spike in activity in one sample. Virophage transcript abundance for two of the three isolates strongly correlated with that of the CpV-BQ2. Together, the results highlight the importance of giant viruses in the environment and establish a foundation for future research on the physiology and ecology CpV-BQ2 as a model system for algal Mimivirus dynamics in freshwaters

Gerschenkron revisited: The new corporate Russia

© 2015, Journal of Economic Issues / Association for Evolutionary Economics. Our analysis is based on firm-specific data compiled from the Russian Trading System stock exchange and SKRIN (CKP-H in Russian) database. We seek to identify the factors behind Russias dramatically improved corporate sector performance from the beginning of the 2000s to December 2007. We argue that improved long-term corporate performance was a consequence of several policy initiatives associated with the state-dominated banking sector, which enabled statesubsidized investment funds to be channeled from a structurally reengineered energy sector to targeted investment projects located in other industries. We claim that Russias industrial strategy closely conforms to Alexander Gerschenkrons catch-up theory