The impact of electronic versus paper-based data capture on data collection logistics and on missing scores in thyroid cancer patients.

PURPOSE: The purpose of this study was to investigate the impact of the type of data capture on the time and help needed for collecting patient-reported outcomes as well as on the proportion of missing scores. METHODS: In a multinational prospective study, thyroid cancer patients from 17 countries completed a validated questionnaire measuring quality of life. Electronic data capture was compared to the paper-based approach using multivariate logistic regression. RESULTS: A total of 437 patients were included, of whom 13% used electronic data capture. The relation between data capture and time needed was modified by the emotional functioning of the patients. Those with clinical impairments in that respect needed more time to complete the questionnaire when they used electronic data capture compared to paper and pencil (ORadj 24.0; p = 0.006). This was not the case when patients had sub-threshold emotional problems (ORadj 1.9; p = 0.48). The odds of having the researcher reading the questions out (instead of the patient doing this themselves) (ORadj 0.1; p = 0.01) and of needing any help (ORadj 0.1; p = 0.01) were lower when electronic data capture was used. The proportion of missing scores was equivalent in both groups (ORadj 0.4, p = 0.42). CONCLUSIONS: The advantages of electronic data capture, such as real-time assessment and fewer data entry errors, may come at the price of more time required for data collection when the patients have mental health problems. As this is not uncommon in thyroid cancer, researchers need to choose the type of data capture wisely for their particular research question.

Investigating the value of radiomics stemming from DSC quantitative biomarkers in IDH mutation prediction in gliomas.

Objective: This study aims to assess the value of biomarker based radiomics to predict IDH mutation in gliomas. The patient cohort consists of 160 patients histopathologicaly proven of primary glioma (WHO grades 2-4) from 3 different centers. Methods: To quantify the DSC perfusion signal two different mathematical modeling methods were used (Gamma fitting, leakage correction algorithms) considering the assumptions about the compartments contributing in the blood flow between the extra- and intra vascular space. Results: The Mean slope of increase (MSI) and the K1 parameter of the bidirectional exchange model exhibited the highest performance with (ACC 74.3% AUROC 74.2%) and (ACC 75% AUROC 70.5%) respectively. Conclusion: The proposed framework on DSC-MRI radiogenomics in gliomas has the potential of becoming a reliable diagnostic support tool exploiting the mathematical modeling of the DSC signal to characterize IDH mutation status through a more reproducible and standardized signal analysis scheme for facilitating clinical translation.

International Phase IV Field Study for the Reliability and Validity of the European Organisation for Research and Treatment of Cancer Thyroid Cancer Module EORTC QLQ-THY34.

Purpose: The aim of this study was to validate the new European Organisation for Research and Treatment of Cancer Quality of Life Thyroid Cancer Module (EORTC QLQ-THY34). Methods: We enrolled 437 thyroid cancer patients from 17 countries. One group (n = 303), undergoing treatment or best supportive care, completed the questionnaires at three time points (before therapy [t1], 6 weeks later [t2], and 6 months after t2 [t3]). A second group (survivors ≥2 years after diagnosis, n = 134) completed it at a random baseline time point and a second time 1 week later. We determined internal consistency (using Cronbach's alpha), the scale structure (with confirmatory factor analysis), and discriminant validity (using known-group comparisons). Group 1 data were used to assess responsiveness and group 2 data to determine test-retest reliability using intra-class correlations (ICC). Results: All 34 items fulfilled the criteria to be kept in the questionnaire. Cronbach's alpha was >0.70 in 8 of the 9 multi-item scales. All standardized factor loadings exceeded 0.40, confirming the proposed scale structure. The ICC was >0.70 in all scales expressing good test-retest reliability. Differences in scale scores between patients with different histology were >5 points in all scales. In all but one of the pre-specified scales (Dry Mouth), changes over time were ≥|4| points between at least two time points. Conclusion: The EORTC QLQ-THY34 with its 9 multi-item and 8 single-item scales is a reliable and valid tool to measure quality of life in thyroid cancer patients and can be used in future trials and studies.

Diffusion Weighted Imaging in the Assessment of Tumor Grade in Endometrial Cancer Based on Intravoxel Incoherent Motion MRI.

The aim of this study is to investigate the possibility of predicting histological grade in patients with endometrial cancer on the basis of intravoxel incoherent motion (IVIM)-related histogram analysis parameters. This prospective study included 52 women with endometrial cancer (EC) who underwent MR imaging as initial staging in our hospital, allocated into low-grade (G1 and G2) and high-grade (G3) tumors according to the pathology reports. Regions of interest (ROIs) were drawn on the diffusion weighted images and apparent diffusion coefficient (ADC), true diffusivity (D), and perfusion fraction (f) using diffusion models were computed. Mean, median, skewness, kurtosis, and interquartile range (IQR) were calculated from the whole-tumor histogram. The IQR of the diffusion coefficient (D) was significantly lower in the low-grade tumors from that of the high-grade group with an adjusted p-value of less than 5% (0.048). The ROC curve analysis results of the statistically significant IQR of the D yielded an accuracy, sensitivity, and specificity of 74.5%, 70.1%, and 76.5% respectively, for discriminating low from high-grade tumors, with an optimal cutoff of 0.206 (×10-3 mm2/s) and an AUC of 75.4% (95% CI: 62.1 to 88.8). The IVIM modeling coupled with histogram analysis techniques is promising for preoperative differentiation between low- and high-grade EC tumors.

Quantification and Classification of Contrast Enhanced Ultrasound Breast Cancer Data: A Preliminary Study.

This study aimed to investigate which of the two frequently adopted perfusion models better describes the contrast enhanced ultrasound (CEUS) perfusion signal in order to produce meaningful imaging markers with the goal of developing a machine-learning model that can classify perfusion curves as benign or malignant in breast cancer data. Twenty-five patients with high suspicion of breast cancer were analyzed with exponentially modified Gaussian (EMG) and gamma variate functions (GVF). The adjusted R2 metric was the criterion for assessing model performance. Various classifiers were trained on the quantified perfusion curves in order to classify the curves as benign or malignant on a voxel basis. Sensitivity, specificity, geometric mean, and AUROC were the validation metrics. The best quantification model was EMG with an adjusted R2 of 0.60 ± 0.26 compared to 0.56 ± 0.25 for GVF. Logistic regression was the classifier with the highest performance (sensitivity, specificity, Gmean, and AUROC = 89.2 ± 10.7, 70.0 ± 18.5, 77.1 ± 8.6, and 91.0 ± 6.6, respectively). This classification method obtained similar results that are consistent with the current literature. Breast cancer patients can benefit from early detection and characterization prior to biopsy.

Computational Fluid Dynamic Analysis Supports the Hemodynamic Stability of Hybrid Combinations With the AFX Bifurcate and Nitinol-Based Proximal Segments in Solutions of Failed Endovascular Aneurysm Repair.

Hybrid endograft combinations of two or more different types of covered stents are rarely reported to treat complex abdominal aortic aneurysm cases or primary and secondary endoleaks. Clinical and laboratory data regarding the clinical efficacy and mechanical stability of such combinations are lacking. Based on a recently published case report, we describe and comment on the hemodynamic profile of a representative simulated hybrid case of AFX and Nitinol-based proximal cuff and support the stability of this combination in non-angulated cases.

Multicenter DSC-MRI-Based Radiomics Predict IDH Mutation in Gliomas.

To address the current lack of dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI)-based radiomics to predict isocitrate dehydrogenase (IDH) mutations in gliomas, we present a multicenter study that featured an independent exploratory set for radiomics model development and external validation using two independent cohorts. The maximum performance of the IDH mutation status prediction on the validation set had an accuracy of 0.544 (Cohen's kappa: 0.145, F1-score: 0.415, area under the curve-AUC: 0.639, sensitivity: 0.733, specificity: 0.491), which significantly improved to an accuracy of 0.706 (Cohen's kappa: 0.282, F1-score: 0.474, AUC: 0.667, sensitivity: 0.6, specificity: 0.736) when dynamic-based standardization of the images was performed prior to the radiomics. Model explainability using local interpretable model-agnostic explanations (LIME) and Shapley additive explanations (SHAP) revealed potential intuitive correlations between the IDH-wildtype increased heterogeneity and the texture complexity. These results strengthened our hypothesis that DSC-MRI radiogenomics in gliomas hold the potential to provide increased predictive performance from models that generalize well and provide understandable patterns between IDH mutation status and the extracted features toward enabling the clinical translation of radiogenomics in neuro-oncology.

A neural pathomics framework for classifying colorectal cancer histopathology images based on wavelet multi-scale texture analysis.

Colorectal cancer (CRC) constitutes the third most commonly diagnosed cancer in males and the second in females. Precise histopathological classification of CRC tissue pathology is the cornerstone not only for diagnosis but also for patients' management decision making. An automated system able to accurately classify different CRC tissue regions may increase diagnostic precision and alleviate clinical workload. However, tissue classification is a challenging task due to the variability in morphological and textural characteristics present in histopathology images. In this study, an artificial neural network was trained to classify between eight classes of CRC tissue image patches derived from a public dataset with 5000 CRC histopathology image tiles. A total of 532 multi-level pathomics features examined at different scales were extracted by visual descriptors such as local binary patterns, wavelet transforms and Gabor filters. An exhaustive evaluation involving a variety of wavelet families and parameters was performed in order to shed light on the impact of scale on pathomics based CRC tissue differentiation. Our model achieved a performance accuracy of 95.3% with tenfold cross validation demonstrating superior performance compared to 87.4% reported in recent studies. Furthermore, we experimentally showed that the first and the second levels of the wavelet approximations can be used without compromising classification performance.

Cerebral CT Perfusion in Acute Stroke: The Effect of Lowering the Tube Load and Sampling Rate on the Reproducibility of Parametric Maps.

The aim of this study was to define lower dose parameters (tube load and temporal sampling) for CT perfusion that still preserve the diagnostic efficiency of the derived parametric maps. Ninety stroke CT examinations from four clinical sites with 1 s temporal sampling and a range of tube loads (mAs) (100-180) were studied. Realistic CT noise was retrospectively added to simulate a CT perfusion protocol, with a maximum reduction of 40% tube load (mAs) combined with increased sampling intervals (up to 3 s). Perfusion maps from the original and simulated protocols were compared by: (a) similarity using a voxel-wise Pearson's correlation coefficient r with in-house software; (b) volumetric analysis of the infarcted and hypoperfused volumes using commercial software. Pearson's r values varied for the different perfusion metrics from 0.1 to 0.85. The mean slope of increase and cerebral blood volume present the highest r values, remaining consistently above 0.7 for all protocol versions with 2 s sampling interval. Reduction of the sampling rate from 2 s to 1 s had only modest impacts on a TMAX volume of 0.4 mL (IQR -1-3) (p = 0.04) and core volume of -1.1 mL (IQR -4-0) (p < 0.001), indicating dose savings of 50%, with no practical loss of diagnostic accuracy. The lowest possible dose protocol was 2 s temporal sampling and a tube load of 100 mAs.

Modeling and Computational Comparison of the Displacement Forces Exerted between the AFX Unibody Aortic Stent Graft and its Hybrid Combination with a Nitinol-based Proximal Aortic Cuff.

BACKGROUND: The bifurcated AFX (Endologix, Inc, Irvine, CA, USA) aortic stent-graft is the sole unibody endograft for the management of Abdominal Aortic Aneurysms (AAA). In order to improve the AFX central sealing and clinical efficacy in challenging cases, a replacement of the central chromium-cobaltium AFX extension with a Nitinol-based proximal aortic cuff has been suggested. Yet, comparative data regarding the hemodynamic performance of this design is missing. Aim of this study was to compare the displacement forces (DF) acting on the hybrid AFX-Endurant design, with the classic AFX and Endurant endografts, in angulated and non-angulated cases based on patient-specific Computational Fluid Dynamics (CFD) simulations. METHODS: 3D endograft models of 11 treated AAA cases were reconstructed from Computed Tomography Angiography (CTA) imaging data: 5 cases of AFX, 3 cases of the combination AFX-Endurant and 3 cases of the classic Endurant design. The DF on the main-body, the iliac limbs, and the entire stent-graft was calculated by processing the velocity and pressure fields generated by pulsatile CFD simulations. RESULTS: The range of total DF (acting on the whole endograft structure) in the AFX, hybrid AFX-Endurant and Endurant group was 2.5-5.2N, 2.0-5.9N and 1.9-2.9N respectively, with the maximum total DF being lower for Endurant. The DF on the main-body of the classic and hybrid AFX cases were higher than the right and left iliac limbs (2.5-4.9N vs. 0.6-5.3N and 0.7-3.6N respectively). Conversely, the DF on the main-body of the Endurant cases was comparable to the force exerted on the right and left limbs. When separating the cases with respect to their neck angulation, the DF on all endograft parts (main-body, limbs) and on the endograft as a whole were lower for the hybrid AFX-Endurant group compared to the classic AFX and Endurant groups, for cases with almost straight neck. CONCLUSION: The off-label use of the hybrid AFX-Endurant stent-graft does not seem superior to the conventional AFX or Endurant endografts in angulated cases but was associated with lower DF than AFX or Endurant in non-angulated cases. The clinical value and utility of these findings remain to be elucidated.

Developing Symptom Lists for People with Cancer Treated with Targeted Therapies.

BACKGROUND: Targeted therapies (TTs) have revolutionised cancer treatment with their enhanced specificity of action. Compared with conventional therapies, TTs are delivered over a longer period and often have unusual symptom profiles. Patient-reported outcome measures such as symptom side-effect lists need to be developed in a time-efficient manner to enable a rapid and full evaluation of new treatments and effective clinical management OBJECTIVE: The aim of this study was to develop a set of TT-related symptoms and identify the optimal method for developing symptom lists. PATIENTS AND METHODS: Symptoms from TT treatment in the context of Chronic Myeloid Leukaemia (CML), HER2-positive breast cancer, or Gastrointestinal Stromal Tumours (GIST) were identified through literature reviews, interviews with healthcare professionals (HCPs) and patients, and patient focus groups. The symptom set was then pilot tested in patients across the three cancer diagnoses: The number of items derived from each source (literature, patients, or HCPs) were compared. RESULTS: A total of 316 patients and 86 HCPs from 16 countries participated. An initial set of 209 symptoms was reduced to 61 covering 12 symptom categories. Patient interviews made the greatest contribution to the item set. CONCLUSIONS: Symptom lists should be created based on input from patients. The item set described will be applicable to the assessment of new TTs, and in monitoring treatment.

Quality of Life in Patients With Hypoparathyroidism After Treatment for Thyroid Cancer.

PURPOSE: Surgical complications such as hypoparathyroidism (HPT) or vocal cord palsy are seldom assessed when the quality of life (QOL) in thyroid cancer patients is investigated. The aim of this study was to measure the QOL difference in thyroid cancer survivors with and without HPT. METHODS: Participants for this analysis were enrolled in 13 countries from a study that pilot-tested a thyroid cancer-specific QOL instrument. They were included if they had been diagnosed with thyroid cancer at least 9 months previously. QOL was measured using the European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire Core (EORTC QLQ-C30) and some items on HPT symptoms (eg, tingling in fingers or toes). HPT status and other clinical data were extracted from the patients' medical charts. Comparisons of QOL domains between patients with and without HPT were performed using Mann-Whitney U test. The occurrence of HPT-related symptoms was compared using chi-square tests. Multiple ordinal regression analysis was performed to evaluate factors that might affect QOL. RESULTS: Eighty-nine patients participated in this study, 17 of whom were considered to have HPT. Patients in the HPT group reported significantly reduced QOL in 9 of the 15 scales of the EORTC QLQ-C30 compared to patients without HPT. Regression analysis showed that HPT was independently negatively associated with various scales of the QLQ-C30. Both groups showed a high prevalence of typical HPT symptoms. CONCLUSION: Thyroid cancer patients with HPT report significantly impaired QOL compared to thyroid cancer survivors without HPT. The assessment of HPT should be considered when measuring QOL in thyroid cancer patients.

Gender effects on quality of life and symptom burden in patients with lung cancer: results from a prospective, cross-cultural, multi-center study.

BACKGROUND: Lung cancer causes impairment of health-related quality of life (QoL), but little is known about gender aspects in QoL and symptom burden of lung cancer patients. The aim of this study was to investigate gender differences in QoL as assessed by the European Organization for Research and Treatment of Cancer (EORTC) QLQ-C30 and the updated lung cancer module. METHODS: In a prospective, international, cross-cultural, multicenter study that was undertaken to update the lung cancer-specific module EORTC QLQ-LC13, patients filled in the core questionnaire EORTC QLQ-C30 and the updated lung cancer module. Gender differences were calculated for all QoL scores using ANCOVAs that controlled for known and suspected confounders. Comparisons with historic data were drawn. RESULTS: A total of 200 patients (82 female and 118 male, median age 65 years) were recruited. With the exception of coughing (estimated marginal means: women 33.86 and men 43.52, P=0.022) and diarrhea (estimated marginal means: women 26.01 and men 17.93, P=0.038) there were no significant QoL gender differences. Fatigue was the most pronounced symptom in both, men and women, outpacing typical respiratory symptoms. Quite generally, our sample of lung cancer patients showed considerably worse QoL in all scores when compared to EORTC reference data (lung cancer and combined cancer diagnoses, mean differences up to 13.70 and 21.54 score points, respectively) and to a German norm reference sample (up to 35.37 score points). CONCLUSIONS: This study adds to the literature in showing that the typical QoL gender difference effect (women doing worse than men) may not be generalizable across all patient samples.

Multiexponential T2 relaxometry of benign and malignant adipocytic tumours.

BACKGROUND: We investigated a recently proposed multiexponential (Mexp) fitting method applied to T2 relaxometry magnetic resonance imaging (MRI) data of benign and malignant adipocytic tumours and healthy subcutaneous fat. We studied the T2 distributions of the different tissue types and calculated statistical metrics to differentiate benign and malignant tumours. METHODS: Twenty-four patients with primary benign and malignant adipocytic tumours prospectively underwent 1.5-T MRI with a single-slice T2 relaxometry (Carr-Purcell-Meiboom-Gill sequence, 25 echoes) prior to surgical excision and histopathological assessment. The proposed method adaptively chooses a monoexponential or biexponential model on a voxel basis based on the adjusted R2 goodness of fit criterion. Linear regression was applied on the statistical metrics derived from the T2 distributions for the classification. RESULTS: Healthy subcutaneous fat and benign lipoma were better described by biexponential fitting with a monoexponential and biexponential prevalence of 0.0/100% and 0.2/99.8% respectively. Well-differentiated liposarcomas exhibit 17.6% monoexponential and 82.4% biexponential behaviour, while more aggressive liposarcomas show larger degree of monoexponential behaviour. The monoexponential/biexponential prevalence was 47.6/52.4% for myxoid tumours, 52.8/47.2% for poorly differentiated parts of dedifferentiated liposarcomas, and 24.9/75.1% pleomorphic liposarcomas. The percentage monoexponential or biexponential model prevalence per patient was the best classifier distinguishing between malignant and benign adipocytic tumours with a 0.81 sensitivity and a 1.00 specificity. CONCLUSIONS: Healthy adipose tissue and benign lipomas showed a pure biexponential behaviour with similar T2 distributions, while decreased adipocytic cell differentiation characterising aggressive neoplasms was associated with an increased rate of monoexponential decay curves, opening a perspective adipocytic tumour classification.

Inverse Laplace transform and multiexponential fitting analysis of T2 relaxometry data: a phantom study with aqueous and fat containing samples.

BACKGROUND: The inverse Laplace transform (ILT) is the most widely used method for T2 relaxometry data analysis. This study examines the qualitative agreement of ILT and a proposed multiexponential (Mexp method) regarding the number of T2 components. We performed a feasibility study for the voxelwise characterisation of heterogeneous tissue with T2 relaxometry. METHODS: Eleven samples of aqueous, fatty and mixed composition were analysed using ILT and Mexp. The phantom was imaged using a 1.5-T system with a single slice T2 relaxometry 25-echo Carr-Purcell-Meiboom-Gill sequence in order to obtain the T2 decay curve with 25 equidistant echo times. The adjusted R2 goodness of fit criterion was used to determine the number of T2 components using the Mexp method on a voxel-based analysis. Comparison of mean and standard deviation of T2 values for both methods was performed by fitting a Gaussian function to the ILT resulting vector. RESULTS: Phantom results showed pure monoexponential decay for acetone and water and pure biexponential behaviour for corn oil, egg yolk, and 35% fat milk cream, while mixtures of egg whites and yolks as well as milk creams with 12-20% fatty composition exhibit mixed monoexponential and biexponential behaviour at different fractions. The number of T2 components by the Mexp method was compared to the ILT-derived spectrum as ground truth. CONCLUSIONS: Mexp analysis with the adjusted R2 criterion can be used for the detection of the T2 distribution of aqueous, fatty and mixed samples with the added advantage of voxelwise mapping.

Persistent hypokalemia due to a rare mutation in gitelman's syndrome.

Chronic hypokalemia is the main finding in patients with Gitelman's syndrome (GS). GS, a variant of Bartter's syndrome, is an autosomal recessive renal disorder characterized by hypokalemia, hypomagnesemia, metabolic alkalosis, and hypocalciuria. GS is caused by inactivating mutations in the thiazide-sensitive sodium-chloride cotransporter gene. It is also called the "milder" form of Bartter's syndrome, as patients with GS are usually diagnosed in adulthood during routine investigation. Our objective is to highlight the impact of correct distinction between the causes of hypokalemia on management and the need of long-term follow- up after the restoration of normokalemic status. Herein, we report an asymptomatic 40-year-old male, whose persistent hypokalemia was due to GS. The diagnosis was first established by laboratory tests, and he was treated with low-dose aldosterone antagonists (spironolactone), angiotensin-converting enzyme inhibitors, and potassium and magnesium supplements. Genetic testing confirmed the diagnosis of GS and revealed a rare mutation. We conclude that GS is a rare and real diagnostic and therapeutic challenge, for which a close collaboration between endocrinologists and nephrologists is mandatory, as also the thorough genetic investigation of the mutations associated with this syndrome.

Psychometric properties of the updated EORTC module for assessing quality of life in patients with lung cancer (QLQ-LC29): an international, observational field study.

BACKGROUND: The European Organisation for Research and Treatment of Cancer (EORTC) Quality of Life Questionnaire-Lung Cancer 13 (QLQ-LC13) assesses quality of life (QOL) in patients with lung cancer and was the first EORTC module developed for use in international clinical trials. Since its publication in 1994, major treatment advances with possible effects on QOL have occurred. These changes called for an update of the module and its international psychometric validation. We aimed to investigate the scale structure and psychometric properties of the updated lung cancer module, QLQ-LC29, in patients with lung cancer. METHODS: This international, observational field study was done in 19 hospitals across 12 countries. Patients aged older than 18 years with a confirmed diagnosis of lung cancer and no other previous primary tumour, and who were mentally fit with sufficient language skills to understand and complete the questionnaire were included. Patients were asked during a hospital visit to fill in the paper versions of the core questionnaire EORTC QLQ-C30 plus QLQ-LC29, and investigators selected half of these patients to complete the questionnaire again 2-4 weeks later. Our primary aim was to assess the scale structure and psychometric properties of EORTC QLQ-LC29. We analysed scale structure using confirmatory factor analysis; reliability using Cronbach's α value (internal consistency) and intra-class coefficient (test-retest reliability); sensitivity using independent t tests stratified by Karnofsky performance status; and responsiveness to change over time by ANOVA. This study is registered with ClinicalTrials.gov, NCT02745691. FINDINGS: Between April 12, 2016, and Sept 26, 2018, 523 patients with a confirmed diagnosis of either non-small-cell lung cancer (n=442) or small-cell lung cancer (n=81) were recruited. Confirmatory factor analysis provided a solution composed of five multi-item scales (coughing, shortness of breath, fear of progression, hair problems, and surgery-related symptoms) plus 15 single symptom or side-effect items: χ2=370·233, root mean square error of approximation=0·075, and comparative-fit index=0·901. Cronbach's α for internal consistencies of all multi-item scales were above the threshold of 0·70. Intra-class coefficients for test-retest reliabilities ranged between 0·82 and 0·97. Three (shortness of breath, fear of progression, and hair problems) of the five multi-item scales showed responsiveness to change over time (p values <0·05), as did nine of 15 single symptom items. Four (coughing, shortness of breath, fear of progression, and surgery-related symptoms) of the five multi-item scales and ten of the 15 single symptom items were sensitive to known group differences (ie, lower vs higher Karnofsky performance status). INTERPRETATION: Results determined the psychometric properties of the updated lung cancer module, which is ready for use in international clinical studies. FUNDING: EORTC Quality of Life Group.

Messenger-RNA Expression of Five Gemcitabine Sensitivity-related Genes Predicting Outcome in Advanced-stage Non-small Cell Lung Cancer.

BACKGROUND/AIM: Tumoural transcriptional levels of RRM1, RRM2, CDA, dCK and hENT1 genes are potential biomarkers for gemcitabine's efficacy in non-small cell lung cancer (NSCLC). PATIENTS AND METHODS: We retrospectively analysed each gene's relative mRNA expression by quantitative, real-time polymerase chain reaction in microdissected, formalin-fixed, paraffin-embedded primary-tumour specimens from 219 chemonaïve patients with advanced-stage NSCLC, treated with gemcitabine-based regimens within clinical trials. The five genes' transcriptional patterns were integrated into an ordinal, five-level gemcitabine-susceptibility classifier (5L-GSC). RESULTS: Treatment efficacy increased progressively across the five susceptibility levels, with the very-high chemosensitivity cases obtaining the most clinical benefit. 5L-GSC emerged as an independent prognosticator for overall response and disease control rates, time to progression and overall survival at p-values of 0.03, 0.004, <0.001 and <0.001, respectively, with results remaining significant after bootstrapping. Penalised, optimally-scaled, categorical-regression modelling of overall response identified 5L-GSC as the most stable predictor. CONCLUSION: The proposed composite biomarker is promising for customising front-line chemotherapy in NSCLC.

Τhe AFX unibody bifurcated unibody aortic endograft for the treatment of abdominal aortic aneurysms: current evidence and future perspectives.

Introduction: AFX is a bifurcated unibody aortic endograft for the treatment of Abdominal Aortic aneurysms. It consists of an inner metallic endoskeleton with multiple metallic struts covered by a polytetrafluoroethylene graft fabric. The endoskeleton is sutured to the outer fabric only at the proximal and distal ends. The unique design of AFX aims at fixation onto the aortic bifurcation while a proximal cuff ensures sealing at the infrarenal level.Areas covered: Since this endograft design by Endologix has undergone significant changes over the last years, the aim of this article is to present its unique structure and deployment method and discuss the relevant clinical results as well as reported complications and associated concerns.Expert commentary: the AFX stent-graft exhibits very satisfactory clinical mid-term results in abdominal aortic aneurysms treated within the instructions-for-use. Its 'active-seal' concept of infrarenal fixation stemming from the loose conjugation of the fabric material to the endoskeleton can accommodate efficiently to challenging necks with thrombus or morphological irregularities, thereby extending the anatomical sealing zone without exerting significant radial outward force. Long-term results are needed to validate the promising performance of AFX.

A novel deep learning architecture outperforming 'off­the­shelf' transfer learning and feature­based methods in the automated assessment of mammographic breast density.

Potentially suspicious breast neoplasms could be masked by high tissue density, thus increasing the probability of a false­negative diagnosis. Furthermore, differentiating breast tissue type enables patient pre­screening stratification and risk assessment. In this study, we propose and evaluate advanced machine learning methodologies aiming at an objective and reliable method for breast density scoring from routine mammographic images. The proposed image analysis pipeline incorporates texture [Gabor filters and local binary pattern (LBP)] and gradient­based features [histogram of oriented gradients (HOG) as well as speeded­up robust features (SURF)]. Additionally, transfer learning approaches with ImageNet trained weights were also used for comparison, as well as a convolutional neural network (CNN). The proposed CNN model was fully trained on two open mammography datasets and was found to be the optimal performing methodology (AUC up to 87.3%). Thus, the findings of this study indicate that automated density scoring in mammograms can aid clinical diagnosis by introducing artificial intelligence­powered decision­support systems and contribute to the 'democratization' of healthcare by overcoming limitations, such as the geographic location of patients or the lack of expert radiologists.