Growth Front Research Articles

Co-deposition of MoS2 films by reactive sputtering and formation of tree-like structures

Transition metal dichalcogenides are versatile layered materials with potential applications ranging from optoelectronic devices to water splitting. Top-down fabrication methods such as exfoliation are not practical for a large-scale production of high-quality devices: a bottom-up approach such as sputtering, a low-temperature deposition method, is more suitable. However, due to its anisotropic nature, the growth mechanism of molybdenum disulfide (MoS2) via sputtering is complex and remains to be investigated in detail. In this paper, we study the growth of MoS2 films co-deposited by using a sulfur (S) hot-lip cell and a molybdenum (Mo) sputtering target via reactive sputtering. The impact of S partial pressure on the structure and morphology of MoS2 films was systematically characterized, and it was observed that the growth is dominated by vertically-oriented sheets with horizontal branches, resulting in a tree-like structure. The growth front of the structures is ascribed to the anisotropic incorporation of adatoms with regards to the orientation of MoS2.

Discovery of AMBRA1 and SQSTM1 (p62) as putative biomarkers to identify high risk subsets of patients with cutaneous squamous cell carcinoma.

e21541 Background: While surgical excision is largely curative, small subsets of patients with cSCC develop metastatic disease for which current AJCC/Brigham and Women’s Hospital staging criteria are unable to reliably identify. There is hence an unmet need for credible prognostic biomarkers to stratify patients based on personalised risk, guide the use of emerging therapeutic intervention for advanced disease and the rationalisation of current/future dermatological healthcare. AMBRA1 and SQSTM1 (p62) play a key role in autophagy and sustained keratinocyte differentiation; two vital processes disrupted in cSCC tumorigenesis, resulting in deregulated cell proliferation and autophagy-mediated tumour cell survival. While AMBRA1 expression is maintained in the normal epidermis its expression is lost in the tumour growth front of cSCCs. Conversely, p62 expression is maintained in basal keratinocytes within the normal epidermis but is lost in the peritumoural epidermis. Collectively these observations suggest tumoural AMBRA1 and peritumoural epidermal p62 expression as biomarkers of cSCC progression. The aim of the present study was to assess the immunohistochemical (IHC) expression of AMBRA1 and p62 in a retrospective cohort of localised or metastatic cSCCs and correlate expression with clinical outcome over 5 years. Methods: Automated IHC analysis of AMBRA1 and p62 expression was performed in a retrospective cohort of well, moderately or poorly differentiated non or metastatic cSCCs. Digital images were annotated prior to H-score expression analysis using optimised cytoplasmic algorithms within Aperio ImageScope software. Results: Receiving Operating Characteristic (ROC) curve analysis revealed an H score of < 20 for peritumoural epidermal p62 and < 60 for expression of AMBRA1 in the cSCC growth front defined cSCCs at high risk of progression while tumours with a p62 H score of ≥ 20 and/or ≥ 60 for AMBRA1 were defined as low risk. Subsequent Kaplan Meier analysis of 51 moderately/poorly differentiated cSCCs demonstrated loss of peritumoural p62 and tumour AMBRA1 expression in 7 tumours correlated with a significantly increased risk of metastasis of 85.7 % compared to 25% for 44 tumours defined as low risk (P < 0.0001, HR 30.07, 95% CI 5.48-165) with an assay specificity of 97%, positive predictive value of 75%, and a negative predictive value of 86%. Conclusions: Overall these data suggest the combined use of tumoural AMBRA1 and peritumoural p62 expression as a putative prognostic biomarker for cSCC metastasis, the future validation of which may provide a valuable stratification tool to guide clinical management, therapeutic intervention and the rationalisation of healthcare resources.

Observation of banded spherulite in a pure compound by rhythmic growth

Banded spherulitic growth of crystals is observed in some materials with spherically symmetric growth front and periodic radial variation of birefringence. This variation of birefringence in quasi-two-dimensional geometry produces concentric interference color bands when viewed through crossed polarizers. In most materials, the banded spherulites are found to be formed by radially oriented periodically twisted fibrillar crystallites. Here, we report the formation of banded spherulites due to the rhythmic growth of concentric crystallite-rich and crystallite-poor bands for a pure compound consisting of strongly polar rodlike molecules. The compound exhibits coexistence of untwisted fibrillar crystallites and an amorphous phase in its most stable solid state. On sufficient supercooling of the sample from its melting point, the banded spherulites are formed with a periodic variation of composition of untwisted radially aligned fibrillar crystallites and an amorphous solid phase. We have developed a time-dependent Ginzburg-Landau model to account for the observed banded spherulitic growth.

Radiomics and Machine Learning Analysis Based on Magnetic Resonance Imaging in the Assessment of Colorectal Liver Metastases Growth Pattern.

To assess Radiomics and Machine Learning Analysis in Liver Colon and Rectal Cancer Metastases (CRLM) Growth Pattern, we evaluated, retrospectively, a training set of 51 patients with 121 liver metastases and an external validation set of 30 patients with a single lesion. All patients were subjected to MRI studies in pre-surgical setting. For each segmented volume of interest (VOI), 851 radiomics features were extracted using PyRadiomics package. Nonparametric test, univariate, linear regression analysis and patter recognition approaches were performed. The best results to discriminate expansive versus infiltrative front of tumor growth with the highest accuracy and AUC at univariate analysis were obtained by the wavelet_LHH_glrlm_ShortRunLowGray Level Emphasis from portal phase of contrast study. With regard to linear regression model, this increased the performance obtained respect to the univariate analysis for each sequence except that for EOB-phase sequence. The best results were obtained by a linear regression model of 15 significant features extracted by the T2-W SPACE sequence. Furthermore, using pattern recognition approaches, the diagnostic performance to discriminate the expansive versus infiltrative front of tumor growth increased again and the best classifier was a weighted KNN trained with the 9 significant metrics extracted from the portal phase of contrast study, with an accuracy of 92% on training set and of 91% on validation set. In the present study, we have demonstrated as Radiomics and Machine Learning Analysis, based on EOB-MRI study, allow to identify several biomarkers that permit to recognise the different Growth Patterns in CRLM.

Flux Pinning Properties of Single-Grain Bulk GdBCO Superconductors Processed by Different Thicknesses of Y123 Liquid Source.

The performance of critical current density of GdBa2Cu3O7−δ (GdBCO or Gd123) superconductor bulk has an important influence on its practical applications. In this work, four single-domain GdBCO superconductor bulks were successfully processed by the modified top-seeded melt-texture growth method. The addition of a YBa2Cu3O7−δ (Y123) liquid source with different thicknesses, 0 mm (S0), 3 mm (S3), 5 mm (S5), 7 mm (S7), was introduced to study the influence on the superconducting properties. GdBCO bulk with the addition of the Y123 liquid source with a 3-mm thickness shows the best superconducting properties. The addition of the Y123 liquid source results in a decrease in the Gd3+ ion concentration required for Gd123 growth; thus, Gd2BaCuO5 (Gd211) particles in the liquid source need a larger self-decomposition to diffuse Gd3+ ions to Gd123 growth front, which refines the size and leads to a homogenous distribution of the Gd211 particles in the bulks. Thus, the more pinning centers of fined Gd211 particles improve the superconducting properties of GdBCO bulk. With increases in the thickness of Y123 liquid source to 5 mm and 7 mm, high RE3+ (Gd3+ and Y3+) concentration can coarsen Gd211 particles and fuse with Gd211 liquid source. The superconducting properties apparently drop. Therefore, the addition of a Y123 liquid source with a suitable thickness is a positive modification to obtain high-performance GdBCO bulk.

Strongly out-of-equilibrium growth morphologies in fast solidifying eutectics

In metal printing processes such as laser-based additive manufacturing, typical solidification velocities yield a strongly out-of-equilibrium (SOE) growth regime that is intermediate between the slow solidification in conventional metal casting and rapid solidification regimes characterized by severe solute trapping. Using phase-field simulations supported by experimental observations, we provide evidence for an inherent growth mode of the SOE regime in slightly hypereutectic Al-Ni, leading to the destabilization of the planar eutectic coupled growth front and the development of a protruded state. We interpret this scenario theoretically in terms of a concomitant growth of different solidification modes, here the coupled eutectic together with $\ensuremath{\alpha}$ primary phase. As another example of concomitant growth under SOE conditions, we present simulation results for single-phase solidification of a Ni fcc-phase exhibiting dendrites and doublons.

Manipulation of thin metal film morphology on weakly interacting substrates via selective deployment of alloying species

We demonstrate a versatile concept for manipulating morphology of thin (≤25 nm) noble-metal films on weakly interacting substrates using growth of Ag on SiO2 as a model system. The concept entails deployment of minority metallic (Cu, Au, Al, Ti, Cr, and Mo) alloying species at the Ag-layer growth front. Data from in situ and real-time monitoring of the deposition process show that all alloying agents—when deployed together with Ag vapor throughout the entire film deposition—favor two-dimensional (2D) growth morphology as compared to pure Ag film growth. This is manifested by an increase in the substrate area coverage for a given amount of deposited material in discontinuous layers and a decrease of the thickness at which a continuous layer is formed, though at the expense of a larger electrical resistivity. Based on ex situ microstructural analyses, we conclude that 2D morphological evolution under the presence of alloying species is predominantly caused by a decrease of the rate of island coalescence completion during the initial film-formation stages. Guided by this realization, alloying species are released with high temporal precision to selectively target growth stages before and after coalescence completion. Pre-coalescence deployment of all alloying agents yields a more pronounced 2D growth morphology, which for the case of Cu, Al, and Au is achieved without compromising the Ag-layer electrical conductivity. A more complex behavior is observed when alloying atoms are deposited during the post-coalescence growth stages: Cu, Au, Al, and Cr favor 2D morphology, while Ti and Mo yield a more pronounced three-dimensional morphological evolution. The overall results presented herein show that targeted deployment of alloying agents constitutes a generic platform for designing bespoken heterostructures between metal layers and technologically relevant weakly interacting substrates.

Tuning the structural and optical properties of GeSiSn/Si multiple quantum wells and GeSn nanostructures using annealing and a faceted surface as a substrate

The optical properties of GeSiSn/Si multiple quantum wells (MQWs) and GeSn nanostructures are studied in the range of 1.3–4 µm. An annealing at the temperature of 650 °C leads to the concentration decrease of vacancy complexes and the intensity increase of the radiative recombination proceeding through the interband luminescence. The energy diagram calculation showed that the transitions occur between the heavy hole subband of the GeSiSn solid solution and the silicon X-valley. A several-fold increase in the photoluminescence was observed in structures containing a nanostructured faceted surface with a (113) facet in the lower part of the MQW structure. The analysis of the reciprocal space map of such structures indicates the bending of the (001) flat growth front during the layer deposition at the faceted pit edges within the (113) facet. The GeSn cross-structure and nanoisland array were first obtained using the nanostructured faceted surface on top of the MQW structure. The regularities of the GeSn nanostructure formation on the deposition rate, the layer thickness, as well as the growth temperature, were investigated. The cross-structures on top of the GeSiSn/Si MQW structure are considered promising as plasmonic nanoantennas amplifying the signal from the multilayer periodic structures.

Molecular beam epitaxy of PtSe2 using a co-deposition approach

The structural properties of co-deposited ultrathin PtSe2 films grown at low temperatures by molecular beam epitaxy on c-plane Al2O3 are studied. By simultaneously supplying a Se flux from a Knudsen cell and Pt atoms from an electron-beam evaporator, crystalline (001)-oriented PtSe2 films were formed between 200 °C and 300 °C. The long separation between substrate and electron beam evaporator of about 60 cm ensured minimal thermal load. At optimum deposition temperatures, a ten times or even higher supply rate of Se compared to Pt ensured that the pronounced volatility of the Se was compensated and the PtSe2 phase was formed and stabilized at the growth front. Postgrowth anneals under a Se flux was found to dramatically improve the crystalline quality of the films. Even before the postgrowth anneal in Se, the crystallinity of PtSe2 films grown with the co-deposition method was superior to films realized by thermal assisted conversion. Postgrowth annealed films showed Raman modes with narrower peaks and more than twice the intensity. Transmission electron microscopy investigations revealed that the deposited material transitioned to a two-dimensional layered structure only after the postgrowth anneal. PtSe2 growth was found to start as single layer islands that preferentially nucleated at atomic steps of the substrate and progressed in a layer-by-layer like fashion. A close to ideal wetting behavior resulted in coalesced PtSe2 films after depositing about 1.5 PtSe2 layers. Detailed Raman investigation of the observed PtSe2 layer breathing modes of films grown under optimized co-deposition conditions revealed an interlayer coupling force constant of 5.0–5.6 × 1019 N m−3.

Radiomics textural features by MR imaging to assess clinical outcomes following liver resection in colorectal liver metastases.

To assess the efficacy of radiomics features obtained by T2-weighted sequences to predict clinical outcomes following liver resection in colorectal liver metastases patients. This retrospective analysis was approved by the local Ethical Committee board and radiological databases were interrogated, from January 2018 to May 2021, to select patients with liver metastases with pathological proof and MRI study in pre-surgical setting. The cohort of patients included a training set and an external validation set. The internal training set included 51 patients with 61years of median age and 121 liver metastases. The validation cohort consisted a total of 30 patients with single lesion with 60years of median age. For each volume of interest, 851 radiomics features were extracted as median values using PyRadiomics. Nonparametric test, intraclass correlation, receiver operating characteristic (ROC) analysis, linear regression modelling and pattern recognition methods (support vector machine (SVM), k-nearest neighbours (KNN), artificial neural network (NNET) and decision tree (DT)) were considered. The best predictor to discriminate expansive versus infiltrative front of tumour growth was obtained by wavelet_LHL_gldm_DependenceNonUniformityNormalized with an accuracy of 82%; to discriminate high grade versus low grade or absent was the wavelet_LLH_glcm_Imc1 with accuracy of 88%; to differentiate the mucinous type of tumour was the wavelet_LLH_glcm_JointEntropy with accuracy of 92% while to identify tumour recurrence was the wavelet_LLL_glcm_Correlation with accuracy of 85%. Linear regression model increased the performance obtained with respect to the univariate analysis exclusively in the discrimination of expansive versus infiltrative front of tumour growth reaching an accuracy of 90%, a sensitivity of 95% and a specificity of 80%. Considering significant texture metrics tested with pattern recognition approaches, the best performance was reached by the KNN in the discrimination of the tumour budding considering the four textural predictors obtaining an accuracy of 93%, a sensitivity of 81% and a specificity of 97%. Ours results confirmed the capacity of radiomics to identify as biomarkers, several prognostic features that could affect the treatment choice in patients with liver metastases, in order to obtain a more personalized approach.

CT-Based Radiomics Analysis to Predict Histopathological Outcomes Following Liver Resection in Colorectal Liver Metastases.

Simple SummaryThe objective of the study was to assess the radiomic features obtained by computed tomography (CT) examination as prognostic biomarkers in patients with colorectal liver metastases, in order to predict histopathological outcomes following liver resection. We obtained good performance considering the single significant textural metric in the identification of the front of tumor growth (expansive versus infiltrative) and tumor budding (high grade versus low grade or absent), in the recognition of mucinous type, and in the detection of recurrences.Purpose: We aimed to assess the efficacy of radiomic features extracted by computed tomography (CT) in predicting histopathological outcomes following liver resection in colorectal liver metastases patients, evaluating recurrence, mutational status, histopathological characteristics (mucinous), and surgical resection margin. Methods: This retrospectively approved study included a training set and an external validation set. The internal training set included 49 patients with a median age of 60 years and 119 liver colorectal metastases. The validation cohort consisted of 28 patients with single liver colorectal metastasis and a median age of 61 years. Radiomic features were extracted using PyRadiomics on CT portal phase. Nonparametric Kruskal–Wallis tests, intraclass correlation, receiver operating characteristic (ROC) analyses, linear regression modeling, and pattern recognition methods (support vector machine (SVM), k-nearest neighbors (KNN), artificial neural network (NNET), and decision tree (DT)) were considered. Results: The median value of intraclass correlation coefficients for the features was 0.92 (range 0.87–0.96). The best performance in discriminating expansive versus infiltrative front of tumor growth was wavelet_HHL_glcm_Imc2, with an accuracy of 79%, a sensitivity of 84%, and a specificity of 67%. The best performance in discriminating expansive versus tumor budding was wavelet_LLL_firstorder_Mean, with an accuracy of 86%, a sensitivity of 91%, and a specificity of 65%. The best performance in differentiating the mucinous type of tumor was original_firstorder_RobustMeanAbsoluteDeviation, with an accuracy of 88%, a sensitivity of 42%, and a specificity of 100%. The best performance in identifying tumor recurrence was the wavelet_HLH_glcm_Idmn, with an accuracy of 85%, a sensitivity of 81%, and a specificity of 88%. The best linear regression model was obtained with the identification of recurrence considering the linear combination of the 16 significant textural metrics (accuracy of 97%, sensitivity of 94%, and specificity of 98%). The best performance for each outcome was reached using KNN as a classifier with an accuracy greater than 86% in the training and validation sets for each classification problem; the best results were obtained with the identification of tumor front growth considering the seven significant textural features (accuracy of 97%, sensitivity of 90%, and specificity of 100%). Conclusions: This study confirmed the capacity of radiomics data to identify several prognostic features that may affect the treatment choice in patients with liver metastases, in order to obtain a more personalized approach.

Strong suppression of graphene growth by sulfur superstructure on a nickel substrate

The formation of multilayer graphene on a nickel substrate is usually unavoidable due to the precipitation of carbon upon cooling after the growth of the single layer of graphene. We found that the growth rate of graphene on a Ni(110) surface was markedly reduced when the surface was covered by sulfur atoms arranged in a c($2\ifmmode\times\else\texttimes\fi{}2$) periodicity. An atomistic survey by scanning tunneling microscopy revealed a compression of the sulfur superstructure as a result of the growth of graphene-covered regions. Photoelectron emission microscopy showed that the growth rate of graphene is linear with time, which indicates that carbon atoms are supplied only at the growth front of graphene islands. Density functional theory calculations rationalized these experimental results and suggested a mechanism for suppressing the growth of graphene. Sulfur atoms might extend the utility of nickel substrates for the production of single-layer graphene or nanographenes.

Accelerated crystal growth in a lithia aluminosilicate glass

No viscosity change in the vicinity of the crystal/melt interface is to be expected for crystal growth in silicate systems at constant temperature in a deeply undercooled isochemical melt. In most experimental studies, however, absolute chemical conformity is not realized and the formation of an interfacial zone with presumably strongly altered viscosity will occur. In the present investigation isolated Li2O⋅Al2O3⋅4SiO2 (LAS4) single crystals grew in a slightly alumina deficient base glass at temperatures above glass transition. Due to the depletion of alumina and the enrichment of excess components and impurities of the continuously growing interfacial zone (“shell”), its viscosity will change. Dedicated experiments showed that the viscosity of the interfacial zone is up to 7 orders of magnitude lower than the viscosity of the base glass. The decreased viscosity at the crystal growth front is assumed to cause the experimentally observed increase of the crystallisation velocity with the crystal radius. This behaviour can be quantitatively modelled introducing a linear decrease of the activation enthalpy with the crystal radius. Obviously, the proposed model can be likewise used in the opposite case, i.e. for an increasing viscosity of the interfacial zone during crystal growth. According to the standard concept of a fractional viscosity relation, a coupling factor can formally be extracted from the comparison between the experimentally determined activation enthalpies of the crystal growth velocity and of the base glass viscosity. The resulting unrealistically low numerical value indicates that it is not the high viscosity of the base glass, but the lower viscosity of the interfacial zone that must be considered for the determination of a physically meaningful coupling factor.

Kinetics of Polymer Crystallization with Aggregating Small Crystallites.

The isothermal crystallization near the glass transition temperature from the melt state of poly(trimethylene terephthalate) has been studied by wide-angle x-ray diffraction (WAXD), small-angle x-ray scattering (SAXS), and optical microscopy. The SAXS and WAXD results show the crystallization mechanism in which the crystalline nodules cover the entire sample with the formation of aggregation regions. The analysis of the SAXS results using Kolmogorov-Johnson-Mehl-Avrami theory indicates that the formation kinetics of the aggregation regions is of three-dimensional homogeneous nucleation type. The analysis of the SAXS profiles using Sekimoto's theory provides the growth velocity and the nucleation rate of the aggregation region. The temperature dependence of the growth velocity of the aggregation region is a natural extrapolation of that of spherulite to the high supercooling region. The temperature dependence of the nucleation rate of the aggregation region is also represented by the parameters of the spherulitic growth rate. The result of the growth velocities of the aggregation region and the spherulite suggests the existence of precursors at the front of the crystal growth.

Microstructure and Texture in Copper Filled Millimeter Scale Through Silicon Vias

The microstructure and crystallographic texture of copper electrodeposits in millimeter scale through silicon vias are characterized using electron backscatter diffraction. The deposits obtained from additive-containing CuSO4-H2SO4 electrolytes are characteristic of the superconformal deposition process, with growth textures and columnar grains consistent with previous findings in smaller TSV. The microstructure, like the filling evolution it records, changes substantially with chloride concentration for the concentrations of polymer suppressor used. With chloride concentrations of 80 μmol·l−1 and less, columnar grains of Cu capture the linear motion of the local growth front during filling with a strong 〈110〉 orientation along the elongated grain axes typical of deposition in chloride-containing Cu electrolytes. In the mid- and upper- via locations these columnar grains are angled upward from the sidewalls toward the center of the v-shaped growth front. In a limited region adjacent to the via bottom they extend vertically from the bottom surface. With millimolar chloride concentration, deposition also exhibits columnar grains with preferred 〈110〉 growth orientation in the lower region of the via and adjacent to the sidewalls. However, separation of the central deposit from the sidewalls results in a convex geometry of the growth front and spatially varying texture in most of the deposit.

Polarity controlled epitaxial growth of 111-layers in CVD-ZnS proven by EBSD

Polycrystalline, chemical vapor deposited (CVD) ZnS deposited on a hot isostatically pressed ZnS substrate is studied using scanning electron microscopy (SEM) including electron backscatter diffraction (EBSD) to gain new insights into the growth mechanism during production. The orientations of polar Zn-S-double layers in the zincblende structure of cubic ZnS are analyzed using a recently developed method to determine the polar 〈111〉 axes by EBSD. Here the Hough transform is utilized to find a preferred polar axis in twinned lamellae of industrial CVD-ZnS. The results verify an epitaxial stacking of {111}-layers at the growth front. They furthermore show that the Zn-layer of the analyzed {111}- double layers always points away from the substrate, independent of the polarity of the substrate crystals. If a substrate grain contains a S-layer positioned towards the surface, the polarity in the adjacent CVD grain is inverted, meaning the epitaxial relationship is not perfect.

EOB-MR Based Radiomics Analysis to Assess Clinical Outcomes following Liver Resection in Colorectal Liver Metastases.

Simple SummaryThe aim of this study was to assess the efficacy of radiomics features obtained by EOB-MRI phase in order to predict clinical outcomes following liver resection in Colorectal Liver Metastases Patients, and evaluate recurrence, mutational status, pathological characteristic (mucinous) and surgical resection margin. Ours results confirmed the capacity of radiomics to identify, as biomarkers, several prognostic features that could affect the treatment choice in patients with liver metastases, in order to obtain a more personalized approach. These results were confirmed by external validation dataset. We obtained a good performance considering the single textural significant metric in the identification of front of tumor growth (expansive versus infiltrative) and tumor budding (high grade versus low grade or absent), in the recognition of mucinous type and in the detection of recurrences.The aim of this study was to assess the efficacy of radiomics features obtained by EOB-MRI phase in order to predict clinical outcomes following liver resection in Colorectal Liver Metastases Patients, and evaluate recurrence, mutational status, pathological characteristic (mucinous) and surgical resection margin. This retrospective analysis was approved by the local Ethical Committee board of National Cancer of Naples, IRCCS “Fondazione Pascale”. Radiological databases were interrogated from January 2018 to May 2021 in order to select patients with liver metastases with pathological proof and EOB-MRI study in pre-surgical setting. The cohort of patients included a training set (51 patients with 61 years of median age and 121 liver metastases) and an external validation set (30 patients with single lesion with 60 years of median age). For each segmented volume of interest by 2 expert radiologists, 851 radiomics features were extracted as median values using PyRadiomics. non-parametric test, intraclass correlation, receiver operating characteristic (ROC) analysis, linear regression modelling and pattern recognition methods (support vector machine (SVM), k-nearest neighbors (KNN), artificial neural network (NNET), and decision tree (DT)) were considered. The best predictor to discriminate expansive versus infiltrative front of tumor growth was HLH_glcm_MaximumProbability extraxted on VIBE_FA30 with an accuracy of 84%, a sensitivity of 83%, and a specificity of 82%. The best predictor to discriminate tumor budding was Inverse Variance obtained by the original GLCM matrix extraxted on VIBE_FA30 with an accuracy of 89%, a sensitivity of 96% and a specificity of 65%. The best predictor to differentiate the mucinous type of tumor was the HHL_glszm_ZoneVariance extraxted on VIBE_FA30 with an accuracy of 85%, a sensitivity of 46% and a specificity of 95%. The best predictor to identify tumor recurrence was the LHL_glcm_Correlation extraxted on VIBE_FA30 with an accuracy of 86%, a sensitivity of 52% and a specificity of 97%. The best linear regression model was obtained in the identification of the tumor growth front considering the height textural significant metrics by VIBE_FA10 (an accuracy of 89%; sensitivity of 93% and a specificity of 82%). Considering significant texture metrics tested with pattern recognition approaches, the best performance for each outcome was reached by a KNN in the identification of recurrence with the 3 textural significant features extracted by VIBE_FA10 (AUC of 91%, an accuracy of 93%; sensitivity of 99% and a specificity of 77%). Ours results confirmed the capacity of radiomics to identify as biomarkers, several prognostic features that could affect the treatment choice in patients with liver metastases, in order to obtain a more personalized approach.

Contrast MR-Based Radiomics and Machine Learning Analysis to Assess Clinical Outcomes following Liver Resection in Colorectal Liver Metastases: A Preliminary Study.

Simple SummaryThe objective of the study was to evaluate the radiomics features obtained by contrast MRI studies as prognostic biomarkers in colorectal liver metastases patients to predict clinical outcomes following liver resection. We demonstrated a good performance considering the single textural significant metric in the identification of front of tumor growth (expansive versus infiltrative) and tumor budding (high grade versus low grade or absent), in the recognition of mucinous type and in the detection of recurrences. Moreover, considering linear regression models or neural network classifiers in a multivariate approach was possible to increase the performance in terms of accuracy, sensitivity, and specificity.Purpose: To assess radiomics features efficacy obtained by arterial and portal MRI phase in the prediction of clinical outcomes in the colorectal liver metastases patients, evaluating recurrence, mutational status, pathological characteristic (mucinous and tumor budding) and surgical resection margin. Methods: This retrospective analysis was approved by the local Ethical Committee board, and radiological databases were used to select patients with colorectal liver metastases with pathological proof and MRI study in a pre-surgical setting after neoadjuvant chemotherapy. The cohort of patients included a training set (51 patients with 61 years of median age and 121 liver metastases) and an external validation set (30 patients with single lesion with 60 years of median age). For each segmented volume of interest on MRI by two expert radiologists, 851 radiomics features were extracted as median values using the PyRadiomics tool. Non-parametric Kruskal-Wallis test, intraclass correlation, receiver operating characteristic (ROC) analysis, linear regression modelling and pattern recognition methods (support vector machine (SVM), k-nearest neighbors (KNN), artificial neural network (NNET), and decision tree (DT)) were considered. Results: The best predictor to discriminate expansive versus infiltrative tumor growth front was wavelet_LHH_glrlm_ShortRunLowGrayLevelEmphasis extracted on portal phase with accuracy of 82%, sensitivity of 84%, and specificity of 77%. The best predictor to discriminate tumor budding was wavelet_LLH_firstorder_10Percentile extracted on portal phase with accuracy of 92%, a sensitivity of 96%, and a specificity of 81%. The best predictor to differentiate the mucinous type of tumor was the wavelet_LLL_glcm_ClusterTendency extracted on portal phase with accuracy of 88%, a sensitivity of 38%, and a specificity of 100%. The best predictor to identify the recurrence was the wavelet_HLH_ngtdm_Complexity extracted on arterial phase with accuracy of 90%, a sensitivity of 71%, and a specificity of 95%. The best linear regression model was obtained in the identification of mucinous type considering the 13 textural significant metrics extracted by arterial phase (accuracy of 94%, sensitivity of 77% and a specificity of 99%). The best results were obtained in the identification of tumor budding with the eleven textural significant features extracted by arterial phase using a KNN (accuracy of 95%, sensitivity of 84%, and a specificity of 99%). Conclusions: Our results confirmed the capacity of radiomics to identify as biomarkers and several prognostic features that could affect the treatment choice in patients with liver metastases in order to obtain a more personalized approach.

Unique Periodic Rings Composed of Fractal-Growth Dendritic Branching in Poly(p-dioxanone).

Amorphous poly(p-vinyl phenol) (PVPh) was added into semicrystalline poly(p-dioxanone) (PPDO) to induce a uniquely novel dendritic/ringed morphology. Polarized-light optical, atomic-force and scanning electron microscopy (POM, AFM, and SEM) techniques were used to observe the crystal arrangement of a uniquely peculiar cactus-like dendritic PPDO spherulite, with periodic ring bands not continuingly circular such as those conventional types reported in the literature, but discrete and detached to self-assemble on each of the branches of the lobs. Correlations and responsible mechanisms for the formation of this peculiar banded-dendritic structure were analyzed. The periodic bands on the top surface and interior of each of the cactus-like lobs were discussed. The banded pattern was composed of feather-like lamellae in random fractals alternately varying their orientations from the radial direction to the tangential one. The tail ends of lamellae at the growth front spawned nucleation cites for new branches; in cycles, the feather-like lamellae self-divided into multiple branches following the Fibonacci sequence to fill the ever-expanding space with the increase of the radius. The branching fractals in the sequence and the periodic ring-banded assembly on each of the segregated lobs of cactus-like dendrites were the key characteristics leading to the formation of this unique dendritic/ringed PPDO spherulite.

Interface Motion of β-Silicon Nitride in a Liquid Phase

Abstract Morphology evolution of β-Si3N4 grains on the end caps has shown significant dynamical features. It has been observed the (0001) growth front experiencing a shape transition on the caps from semisphere to negative-curved configuration. After our previous simplified solution, in this paper, the finite element analysis method has been used to further simulate the tip evolution for the hexagonal β-Si3N4 grains.