OSCAR: Optimal subset cardinality regression using the L0-pseudonorm with applications to prognostic modelling of prostate cancer.

In many real-world applications, such as those based on electronic health records, prognostic prediction of patient survival is based on heterogeneous sets of clinical laboratory measurements. To address the trade-off between the predictive accuracy of a prognostic model and the costs related to its clinical implementation, we propose an optimized L0-pseudonorm approach to learn sparse solutions in multivariable regression. The model sparsity is maintained by restricting the number of nonzero coefficients in the model with a cardinality constraint, which makes the optimization problem NP-hard. In addition, we generalize the cardinality constraint for grouped feature selection, which makes it possible to identify key sets of predictors that may be measured together in a kit in clinical practice. We demonstrate the operation of our cardinality constraint-based feature subset selection method, named OSCAR, in the context of prognostic prediction of prostate cancer patients, where it enables one to determine the key explanatory predictors at different levels of model sparsity. We further explore how the model sparsity affects the model accuracy and implementation cost. Lastly, we demonstrate generalization of the presented methodology to high-dimensional transcriptomics data.

Optimized reference spectrum for rating the façade sound insulation.

Objectively determined single-number-quantities (SNQs) describing the airborne sound insulation of a façade should correspond to the subjective perception of annoyance to road traffic sounds transmitted through a façade. The reference spectra for spectrum adaptation terms C and Ctr in standard ISO 717-7 (International Organization for Standardization, 2013) are not based on psycho-acoustic evidence. The aim of this study is to develop reference spectra which result in SNQs that explain the subjective annoyance of road traffic sounds transmitted through a façade well. Data from a psycho-acoustic experiment by Hongisto, Oliva, and Rekola [J. Acoust. Soc. Am. 144(2), 1100-1112 (2018)] were used. The data included annoyance ratings for road traffic sounds (five different spectrum alternatives) attenuated by the façade (twelve different sound insulation spectrum alternatives), rated by 43 participants. The reference spectrum for each road traffic spectrum was found using mathematical optimization. The performance of the acquired SNQs was estimated with nested cross-validation. The SNQs determined with the optimized reference spectra performed better than the existing SNQs for two road traffic spectra out of five and for an aggregate of the five road traffic sound types. The results can be exploited in the development of standardized SNQs.

Comparison of end-expiratory respiratory gating methods for PET/CT.

BACKGROUND: Respiratory motion in positron emission tomography/computed tomography (PET/CT) causes underestimation of standardized uptake value (SUV) and variation of lesion volume, while PET and CT attenuation correction (CTAC) mismatch may introduce artefacts. The aim was to compare end-expiratory gating methods of PET and CTAC. MATERIAL AND METHODS: Three methods named the minimum-constant, slope-based and amplitude-median were developed and evaluated on gating efficiency. Method evaluation and optimization was performed on 23 simulated and 23 recorded signals from a mixed patient group. The optimized methods were applied in PET/CT imaging of seven patients, consisting of non-gated CTAC, whole-body PET and four-dimensional (4D) PET/CT. Gating efficiency was evaluated by preservation of the respiratory signal, PET-CTAC alignment, image noise and measurement of lesion SUV maximum (SUVmax), SUV mean (SUVmean) and volume. The methods were evaluated with non-gated PET and end-expiratory phase of five-bin phase-gated PET. End-expiratory gated 4D-CTAC and averaged CTAC were compared for attenuation correction of end-expiratory gated PET. RESULTS: Mean fraction of data preserved was larger (23-34%) with end-expiratory gating compared to phase-gated PET. End-expiratory gating showed increased SUVmax (8.2-8.4 g/ml), SUVmean (5.7-5.8 g/ml) and decreased lesion volume (-11.3-16.8%) compared to non-gated PET (SUVmax 6.2 g/ml, SUVmean 4.7 g/ml) and phase-gated PET (SUVmax 8.0 g/ml, SUVmean 5.6 g/ml). Using averaged CTAC and end-expiratory 4D-CTAC produced similar results concerning SUVmax, with less than 5% difference. Additionally, CTAC-PET-mismatch was minimal when end-expiratory 4D-CTAC was used. CONCLUSION: End-expiratory gating in PET/CT results in SUVmax and SUVmean increase and reduced lesion volume compared to non-gated PET and phase-gated PET. End-expiratory 4D-CTAC or averaged CTAC will offer similar accuracy for attenuation correction of end-expiratory gated PET.