F. Binczyk

DALSA: Domain Adaptation for Supervised Learning From Sparsely Annotated MR Images

We propose a new method that employs transfer learning techniques to effectively correct sampling selection errors introduced by sparse annotations during supervised learning for automated tumor segmentation. The practicality of current learning-based automated tissue classification approaches is severely impeded by their dependency on manually segmented training databases that need to be recreated for each scenario of application, site, or acquisition setup. The comprehensive annotation of reference datasets can be highly labor-intensive, complex, and error-prone. The proposed method derives high-quality classifiers for the different tissue classes from sparse and unambiguous annotations and employs domain adaptation techniques for effectively correcting sampling selection errors introduced by the sparse sampling. The new approach is validated on labeled, multi-modal MR images of 19 patients with malignant gliomas and by comparative analysis on the BraTS 2013 challenge data sets. Compared to training on fully labeled data, we reduced the time for labeling and training by a factor greater than 70 and 180 respectively without sacrificing accuracy. This dramatically eases the establishment and constant extension of large annotated databases in various scenarios and imaging setups and thus represents an important step towards practical applicability of learning-based approaches in tissue classification.

Strategies for optimizing the phase correction algorithms in Nuclear Magnetic Resonance spectroscopy

Nuclear Magnetic Resonance (NMR) spectroscopy is a popular medical diagnostic technique. NMR is also the favourite tool of chemists/biochemists to elucidate the molecular structure of small or big molecules; it is also a widely used tool in material science, in food science etc. In the case of medical diagnosis it allows for determining a metabolic composition of analysed tissue which may support the identification of tumour cells. Precession signal, that is a crucial part of MR phenomenon, contains distortions that must be filtered out before signal analysis. One of such distortions is phase error.Five popular algorithms: Automics, Shanons entropy minimization, Ernsts method, Dispa and eDispa are presented and discussed. A novel adaptive tuning algorithm for Automics method was developed and numerically optimal solutions to automatic tuning of the other four algorithms were proposed. To validate the performance of the proposed techniques, two experiments were performed - the first one was done with the use of in silico generated data. For all presented methods, the fine tuning strategies significantly increased the correction accuracy. The highest improvement was observed for Automics algorithm, independently of noise level, with relative phase error dropping by average from 10.25% to 2.40% for low noise level and from 12.45% to 2.66% for high noise level. The second validation experiment, done with the use of phantom data, confirmed the in silico results. The obtained accuracy of the estimation of metabolite concentration was at 99.5%.ConclusionsThe proposed strategies for optimizing the phase correction algorithms significantly improve the accuracy of Nuclear Magnetic Resonance spectroscopy signal analysis.

Serum lipid profile discriminates patients with early lung cancer from healthy controls

OBJECTIVESnThe role of a low-dose computed tomography lung cancer screening remains a matter of controversy due to its low specificity and high costs. Screening complementation with blood-based biomarkers may allow a more efficient pre-selection of candidates for imaging tests or discrimination between benign and malignant chest abnormalities detected by low-dose computed tomography (LD-CT). We searched for a molecular signature based on a serum lipid profile distinguishing individuals with early lung cancer from healthy participants of the lung cancer screening program.nnnMATERIALS AND METHODSnBlood samples were collected from 100 patients with early stage lung cancer (including 31 screen-detected cases) and from a matched group of 300 healthy participants of the lung cancer screening program. MALDI-ToF mass spectrometry was used to analyze the molecular profile of lipid-containing organic extract of serum samples in the 320-1000Da range.nnnRESULTSnSeveral components of the serum lipidome were detected, with abundances discriminating patients with early lung cancer from high-risk smokers. An effective cancer classifier was built with an area under the curve of 0.88. Corresponding negative predictive value was 98% and a positive predictive value was 42% when the classifier was tuned for maximum negative predictive value. Furthermore, the downregulation of a few lysophosphatidylcholines (LPC18:2, LPC18:1 and LPC18:0) in samples from cancer patients was confirmed using a complementary LC-MS approach (a reasonable cancer discrimination was possible based on LPC18:2 alone with 25% total weighted error of classification).nnnCONCLUSIONSnLipid-based serum signature showed potential usefulness in discriminating early lung cancer patients from healthy individuals.

The Effect of Heat Treatment on Creep Resistance of Castings from the Modified Superalloy MAR-247

mpact of heat treatment on durability has been evaluated in this study in conditions of high-temperature creep of castings made from nickel superalloy MAR-247 post production rejects. Castings made in the processes of modification and filtration when pouring into moulds were subject to solubilization (1185°C/2 h) with subsequent ageing (870°C/20 h). It has been found on the basis of performed tests that in conditions of high-temperature creep at temperature 980°C with stress σ = 150 MPa the resistance of specimens of coarse-grain structure was significantly higher when compared to fine-grain material. The conditions of initiation and propagation of cracks in these specimens were analysed with consideration of morphological properties of material macro-, micro-and substructure. Moreover, it has been proven that creep resistance of heat treated MAR-247 superalloy significantly improves when compared to its condition after the process of modification only. Macrostructural changes in the MAR-247 superalloy that determine the increase of superalloy creep resistance after solubilization and ageing, as observed in the tests, were also examined.

Analysis of Cracking Process in Conditions of High-Temperature Creep of Castings Form the Modified Superalloy IN-713C

mpact of complex modification and filtration during pouring into moulds on durability has been evaluated in this study in conditions of high-temperature creep of castings made from nickel superalloy IN-713C post production rejects. The conditions of initiation and propagation of cracks in the specimens were analysed with consideration of morphological properties of material macro-, micro-and substructure. It has been demonstrated that in conditions of high-temperature creep at temperature 980°C with stress σ =150 MPa creep resistance of the IN-713C superalloy increases significantly with the increase of macrograin size. Creep resistance of specimens made of coarse grain material was significantly higher than the resistance of fine grain material.

Favourable outcomes in patients with early-stage non-small-cell lung cancer operated on by video-assisted thoracoscopic surgery: a propensity score-matched analysis†

OBJECTIVESnThe video-assisted thoracoscopic surgery (VATS) approach has become a standard for the treatment of early-stage non-small-cell lung cancer (NSCLC). Recently published meta-analyses proved the benefit of VATS versus thoracotomy for overall survival (OS) and reduction of postoperative complications. The aim of this study was to compare early outcomes, long-term survival and rate of postoperative complications of the VATS approach versus thoracotomy.nnnMETHODSnIn this retrospective cohort study, we analysed 982 individuals who underwent surgical resection for Stage I-IIA NSCLC between 2007 and 2015. Thirty- and 90-day mortality rates, length of hospital stay, rate of complications and OS were assessed. Propensity score matching was performed to compare 2 groups of patients. Two hundred and twenty-five individuals from the thoracotomy group and 225 patients from the VATS group were matched regarding pTNM, sex, the Charlson comorbidity index, type of resection and histological diagnosis.nnnRESULTSnIn the propensity score-matched patient group, the VATS approach was associated with a significant benefit regarding OS (Pu2009=u20090.042). Although no significant difference was observed (Pu2009=u20090.14) in the 3-year survival rate of patients who had a thoracotomy versus VATS, the 5-year survival rate among patients with VATS increased significantly (61% vs 78%, Pu2009=u20090.0081). The adjusted VATS-related hazard ratio for pTNM, sex and age was 0.63 (95% confidence interval 0.40-0.98). The VATS surgical approach also reduced both the rate of postoperative atelectasis (4% for VATS vs 10% for open thoracotomy; Pu2009=u20090.0052) and the need for blood transfusions (4% vs 12% respectively, Pu2009=u20090.0054) and significantly shortened the postoperative length of stay (mean 7.25 vs 9.34u2009days, Pu2009<u20090.0001). No significant differences in the 30-day mortality (1% vs 1%, Pu2009=u20090.66) and 90-day mortality (1% vs 1%, Pu2009=u20090.48) rates were observed.nnnCONCLUSIONSnPatients with early-stage NSCLC operated on with VATS had fewer complications, shorter postoperative length of stay and better OS compared to those who were operated on by thoracotomy.

Comparison of Black Box Implementations of Two Algorithms of Processing of NMR Spectra, Gaussian Mixture Model and Singular Value Decomposition

Analysis of NMR spectra is a multi-stage computational process performed with the use of appropriately n nchosen sequence of algorithms. Initial stages of this process, called pre-processing, including filtering, baseline n ncorrection, phase correction and removal of unwanted components, are aimed at improving the quality n nof NMR spectral signal by rejection of noise, removing unnecessary spectral components and irregularities. n nAfter pre-processing the basic operations on NMR spectra are aimed at estimation of levels of certain n nmetabolites by analysis of appropriate structural properties of NMR spectral signals. In this paper authors n npresent design and implementation of two signals modelling methods. The first one is based on singular n nvalue decomposition of the induction decay signal. The second is done with use of mixture model n nconstructed for frequency spectrum. Authors present all assumption that need to be satisfied and processing n nsteps that must be performed before final analysis. The methods studied in the paper are implemented under n nthe black - box assumption; i.e., prior knowledge of parameters of metabolites in the spectra is not used. As n na second part of the project authors present a comparison of obtained result with popular modelling n ntechniques and software LCmodel and Tarquin, based on experimental phantom dataset. Comparisons n nbetween different methods are based on the commonly used quality indexes, mean squared errors n ncorresponding to levels of detected metabolites and specificities and sensitivities of the process of detection n nof metabolites. Using the presented comparisons we authors are able to characterize advantages and n ndrawbacks of the studied approaches.

Metallurgical Quality of Feed Ingots and Castings Made from Nickel and Cobalt Superalloys

The paper presents the results of ATD thermal analysis of feed ingots (master heat) and castings made from IN-713C, MAR-247 and MAR-509 superalloys. Metallurgical quality assessment was made based on the analysis of dT/dt curve in rage from Teut to Tsol. Furthermore, impurities (oxides of Al, Zr, Hf, Cr etc.) have been identified inside the shrinkage cavities of feed ingots and castings. Significant similarities has been observed between impurities found in ingots, ATD test samples and finished castings. It has been demonstrated that ATD analysis of samples taken from different parts of feed ingot can be effective method of metallurgical quality assessment for these ingots.

Solidification Process, Microstructure, Density and Hardness of the Mg-Al Alloys with Zn, Cu, Ni and AlTiB Additions

The paper presents the results of the investigations of the solidification process of magnesium alloys containing 5 and 10 wt.% Al, the additions of Zn, Cu, Ni, and of an AlTiB master alloy. The plotted DTA (derivative thermal analysis) curves were used for the determination of solidification parameters Tliq, Teut and Tsol. Knowledge of these parameters is very important in determination of alloy pouring temperature and maximum casting operating temperature. On samples taken from the area of temperature measurements, the chemical composition and microstructure were determined. The density and hardness HB were measured as well. Applying the method of multiple regression analysis at the significance level α = 0.1, the intensity and direction of the effect of alloying elements on the solidification parameters, density and hardness HB of castings were evaluated.