A Feature-Pooling and Signature-Pooling Method for Feature Selection for Quantitative Image Analysis: Application to a Radiomics Model for Survival in Glioma

We proposed a pooling-based radiomics feature selection method and showed how it would be applied to the clinical question of predicting one-year survival in 130 patients treated for glioma by radiotherapy. The method combines filter, wrapper and embedded selection in a comprehensive process to identify useful features and build them into a potentially predictive signature. The results showed that non-invasive CT radiomics were able to moderately predict overall survival and predict WHO tumour grade. This study reveals an associative inter-relationship between WHO tumour grade, CT-based radiomics and survival, that could be clinically relevant

Fast and Accurate Lung Tumor Spotting and Segmentation for Boundary Delineation on CT Slices In A Coarse-To-Fine Framework

Label noise and class imbalance are two of the critical challenges when training image-based deep neural networks, especially in the biomedical image processing domain. Our work focuses on how to address the two challenges effectively and accurately in the task of lesion segmentation from biomedical/medical images. To address the pixel-level label noise problem, we propose an advanced transfer training and learning approach with a detailed DICOM pre-processing method. To address the tumor/non-tumor class imbalance problem, we exploit a self-adaptive fully convolutional neural network with an automated weight distribution mechanism to spot the Radiomics lung tumor regions accurately. Furthermore, an improved conditional random field method is employed to obtain sophisticated lung tumor contour delineation and segmentation. Finally, our approach has been evaluated using several well-known evaluation metrics on the Lung Tumor segmentation dataset used in the 2018 IEEE VIP-CUP Challenge. Experimental results show that our weakly supervised learning algorithm outperforms other deep models and state-of-the-art approache

Retinoblastoma

Retinoblastoma is a rare eye tumor of childhood that arises in the retina. It is the most common intraocular malignancy of infancy and childhood; with an incidence of 1/15,000–20,000 live births. The two most frequent symptoms revealing retinoblastoma are leukocoria and strabismus. Iris rubeosis, hypopyon, hyphema, buphthalmia, orbital cellulites and exophthalmia may also be observed. Sixty per cent of retinoblastomas are unilateral and most of these forms are not hereditary (median age at diagnosis two years). Retinoblastoma is bilateral in 40% of cases (median age at diagnosis one year). All bilateral and multifocal unilateral forms are hereditary. Hereditary retinoblastoma constitutes a cancer predisposition syndrome: a subject constitutionally carrying an RB1 gene mutation has a greater than 90% risk of developing retinoblastoma but is also at increased risk of developing other types of cancers. Diagnosis is made by fundoscopy. Ultrasound, magnetic resonance imaging (MRI) and computed tomography (CT) scans may contribute to diagnosis. Management of patients with retinoblastoma must take into account the various aspects of the disease: the visual risk, the possibly hereditary nature of the disease, the life-threatening risk. Enucleation is still often necessary in unilateral disease; the decision for adjuvant treatment is taken according to the histological risk factors. Conservative treatment for at least one eye is possible in most of the bilateral cases. It includes laser alone or combined with chemotherapy, cryotherapy and brachytherapy. The indication for external beam radiotherapy should be restricted to large ocular tumors and diffuse vitreous seeding because of the risk of late effects, including secondary sarcoma. Vital prognosis, related to retinoblastoma alone, is now excellent in patients with unilateral or bilateral forms of retinoblastoma. Long term follow-up and early counseling regarding the risk of second primary tumors and transmission should be offered to retinoblastoma patients

DCE-MRI perfusion and permeability parameters as predictors of tumor response to CCRT in patients with locally advanced NSCLC

In this prospective study, 36 patients with stage III non-small cell lung cancers (NSCLC), who underwent dynamic contrast-enhanced MRI (DCE-MRI) before concurrent chemo-radiotherapy (CCRT) were enrolled. Pharmacokinetic analysis was carried out after non-rigid motion registration. The perfusion parameters including Blood Flow (BF), Blood Volume (BV), Mean Transit Time (MTT) and permeability parameters including endothelial transfer constant (Ktrans), reflux rate (Kep), fractional extravascular extracellular space volume (Ve), fractional plasma volume (Vp) were calculated, and their relationship with tumor regression was evaluated. The value of these parameters on predicting responders were calculated by receiver operating characteristic (ROC) curve. Multivariate logistic regression analysis was conducted to find the independent variables. Tumor regression rate is negatively correlated with V e and its standard variation V e-SD and positively correlated with K trans and Kep. Significant differences between responders and non-responders existed in Ktrans, Kep, Ve, Ve-SD, MTT, BV-SD and MTT-SD (P < 0.05). ROC indicated that Ve < 0.24 gave the largest area under curve of 0.865 to predict responders. Multivariate logistic regression analysis also showed Ve was a significant predictor. Baseline perfusion and permeability parameters calculated from DCE-MRI were seen to be a viable tool for predicting the early treatment response after CCRT of NSCLC. © 2016 The Author(s)

Increased Hepatic Insulin Action in Diet-Induced Obese Mice Following Inhibition of Glucosylceramide Synthase

Obesity is characterized by the accumulation of fat in the liver and other tissues, leading to insulin resistance. We have previously shown that a specific inhibitor of glucosylceramide synthase, which inhibits the initial step in the synthesis of glycosphingolipids (GSLs), improved glucose metabolism and decreased hepatic steatosis in both ob/ob and diet-induced obese (DIO) mice. Here we have determined in the DIO mouse model the efficacy of a related small molecule compound, Genz-112638, which is currently being evaluated clinically for the treatment of Gaucher disease, a lysosomal storage disorder.DIO mice were treated with the Genz-112638 for 12 to 16 weeks by daily oral gavage. Genz-112638 lowered HbA1c levels and increased glucose tolerance. Whole body adiposity was not affected in normal mice, but decreased in drug-treated obese mice. Drug treatment also significantly lowered liver triglyceride levels and reduced the development of hepatic steatosis. We performed hyperinsulinemic-euglycemic clamps on the DIO mice treated with Genz-112638 and showed that insulin-mediated suppression of hepatic glucose production increased significantly compared to the placebo treated mice, indicating a marked improvement in hepatic insulin sensitivity.These results indicate that GSL inhibition in obese mice primarily results in an increase in insulin action in the liver, and suggests that GSLs may have an important role in hepatic insulin resistance in conditions of obesity

Finished Genome of the Fungal Wheat Pathogen Mycosphaerella graminicola Reveals Dispensome Structure, Chromosome Plasticity, and Stealth Pathogenesis.

The plant-pathogenic fungus Mycosphaerella graminicola (asexual stage: Septoria tritici) causes septoria tritici blotch, a disease that greatly reduces the yield and quality of wheat. This disease is economically important in most wheat-growing areas worldwide and threatens global food production. Control of the disease has been hampered by a limited understanding of the genetic and biochemical bases of pathogenicity, including mechanisms of infection and of resistance in the host. Unlike most other plant pathogens, M. graminicola has a long latent period during which it evades host defenses. Although this type of stealth pathogenicity occurs commonly in Mycosphaerella and other Dothideomycetes, the largest class of plant-pathogenic fungi, its genetic basis is not known. To address this problem, the genome of M. graminicolawas sequenced completely. The finished genome contains 21 chromosomes, eight of which could be lost with no visible effect on the fungus and thus are dispensable. This eight-chromosome dispensome is dynamic in field and progeny isolates, is different from the core genome in gene and repeat content, and appears to have originated by ancient horizontal transfer from an unknown donor. Synteny plots of the M. graminicola chromosomes versus those of the only other sequenced Dothideomycete, Stagonospora nodorum, revealed conservation of gene content but not order or orientation, suggesting a high rate of intra-chromosomal rearrangement in one or both species. This observed “mesosynteny” is very different from synteny seen between other organisms. A surprising feature of the M. graminicolagenome compared to other sequenced plant pathogens was that it contained very few genes for enzymes that break down plant cell walls, which was more similar to endophytes than to pathogens. The stealth pathogenesis of M. graminicola probably involves degradation of proteins rather than carbohydrates to evade host defenses during the biotrophic stage of infection and may have evolved from endophytic ancestors

Comparative Plasma Lipidome between Human and Cynomolgus Monkey: Are Plasma Polar Lipids Good Biomarkers for Diabetic Monkeys?

10.1371/journal.pone.0019731PLoS ONE65

Towards Endometriosis Diagnosis by Gadofosveset-Trisodium Enhanced Magnetic Resonance Imaging

Endometriosis is defined as the presence of endometrial tissue outside the uterus. It affects 10–15% of women during reproductive age and has a big personal and social impact due to chronic pelvic pain, subfertility, loss of work-hours and medical costs. Such conditions are exacerbated by the fact that the correct diagnosis is made as late as 8–11 years after symptom presentation. This is due to the lack of a reliable non-invasive diagnostic test and the fact that the reference diagnostic standard is laparoscopy (invasive, expensive and not without risks). High-molecular weight gadofosveset-trisodium is used as contrast agent in Magnetic Resonance Imaging (MRI). Since it extravasates from hyperpermeable vessels more easily than from mature blood vessels, this contrast agent detects angiogenesis efficiently. Endometriosis has high angiogenic activity. Therefore, we have tested the possibility to detect endometriosis non-invasively using Dynamic Contrast-Enhanced MRI (DCE-MRI) and gadofosveset-trisodium as a contrast agent in a mouse model. Endometriotic lesions were surgically induced in nine mice by autologous transplantation. Three weeks after lesion induction, mice were scanned by DCE-MRI. Dynamic image analysis showed that the rates of uptake (inwash), persistence and outwash of the contrast agent were different between endometriosis and control tissues (large blood vessels and back muscle). Due to the extensive angiogenesis in induced lesions, the contrast agent persisted longer in endometriotic than control tissues, thus enhancing the MRI signal intensity. DCE-MRI was repeated five weeks after lesion induction, and contrast enhancement was similar to that observed three weeks after endometriosis induction. The endothelial-cell marker CD31 and the pericyte marker α-smooth-muscle-actin (mature vessels) were detected with immunohistochemistry and confirmed that endometriotic lesions had significantly higher prevalence of new vessels (CD31 only positive) than the uterus and control tissues. The diagnostic value of gadofosveset-trisodium to detect endometriosis should be tested in human settings

Frequency-resolved Monte Carlo

We adapt the Quantum Monte Carlo method to the cascaded formalism of quantum optics, allowing us to simulate the emission of photons of known energy. Statistical processing of the photon clicks thus collected agrees with the theory of frequency-resolved photon correlations, extending the range of applications based on correlations of photons of prescribed energy, in particular those of a photon-counting character. We apply the technique to autocorrelations of photon streams from a two-level system under coherent and incoherent pumping, including the Mollow triplet regime where we demonstrate the direct manifestation of leapfrog processes in producing an increased rate of two-photon emission events