| 31. |
- Ali, Muhaddisa Barat, 1986, et al.
(författare)
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Multi-stream Convolutional Autoencoder and 2D Generative Adversarial Network for Glioma Classification
- 2019
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Ingår i: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). - Cham : Springer International Publishing. - 1611-3349 .- 0302-9743. ; 11678 LNCS, s. 234-245
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Konferensbidrag (refereegranskat)abstract
- Diagnosis and timely treatment play an important role in preventing brain tumor growth. Deep learning methods have gained much attention lately. Obtaining a large amount of annotated medical data remains a challenging issue. Furthermore, high dimensional features of brain images could lead to over-fitting. In this paper, we address the above issues. Firstly, we propose an architecture for Generative Adversarial Networks to generate good quality synthetic 2D MRIs from multi-modality MRIs (T1 contrast-enhanced, T2, FLAIR). Secondly, we propose a deep learning scheme based on 3-streams of Convolutional Autoencoders (CAEs) followed by sensor information fusion. The rational behind using CAEs is that it may improve glioma classification performance (as comparing with conventional CNNs), since CAEs offer noise robustness and also efficient feature reduction hence possibly reduce the over-fitting. A two-round training strategy is also applied by pre-training on GAN augmented synthetic MRIs followed by refined-training on original MRIs. Experiments on BraTS 2017 dataset have demonstrated the effectiveness of the proposed scheme (test accuracy 92.04%). Comparison with several exiting schemes has provided further support to the proposed scheme.
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| 32. |
- Ohlsson Nevö, Emma, 1960-, et al.
(författare)
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Effects of a psycho-educational programme on health-related quality of life in patients treated for colorectal and anal cancer : a feasibility trial
- 2016
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Ingår i: European Journal of Oncology Nursing. - : Elsevier. - 1462-3889 .- 1532-2122. ; 21, s. 181-188
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Tidskriftsartikel (refereegranskat)abstract
- Purpose: Colorectal cancer (CRC) may have a negative impact on a person's quality of life. Psycho-educational interventions for patients with CRC are rarely studied. The purpose of this feasibility trial was to evaluate the effect of a psycho-educational programme (PEP) on the health-related quality of life (HRQL) of patients treated for CRC and anal cancer.Methods: Patients with CRC and anal cancer were randomly assigned to a PEP (n = 47) or standard treatment (n = 39). The PEP included informative lectures, discussion, and reflection. HRQL was evaluated using the SF-36 at baseline and 1, 6, and 12 months after the end of the PEP.Results: Patients in the PEP group had significantly better Mental Health scores after 1 month and significantly better Bodily Pain scores after 6 months compared with patients who received standard care.Conclusion: The results of this study indicate that a PEP can have a short-term effect on the mental health and bodily pain of patients treated for CRC and anal cancer when comparing with a control group. The article discusses the methodological difficulties of evaluating an intervention such as this PEP in a clinical setting.
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| 33. |
- Dahm-Kähler, Pernilla, 1964, et al.
(författare)
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Population-based study of survival for women with serous cancer of the ovary, fallopian tube, peritoneum or undesignated origin - on behalf of the Swedish gynecological cancer group (SweGCG)
- 2017
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Ingår i: Gynecologic Oncology. - : Elsevier BV. - 0090-8258 .- 1095-6859. ; 144:1, s. 167-173
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Tidskriftsartikel (refereegranskat)abstract
- Objective. The aim of the study was to determine survival outcome in patients with serous cancer in the ovary, fallopian tube, peritoneum and of undesignated origin. Methods. Nation-wide population-based study of women 18 years with histologically verified non-uterine serous cancer, included in the Swedish Quality Registry for primary cancer of the ovary, fallopian tube and peritoneum diagnosed 2009-2013. Relative survival (RS) was estimated using the Ederer II method. Simple and multivariable analyses were estimated by Poisson regression models. Results. Of 5627 women identified, 1246 (22%) had borderline tumors and 4381 had malignant tumors. In total, 2359 women had serous cancer; 71% originated in the ovary (OC), 9% in the fallopian tube (FTC), 9% in the peritoneum (PPC) and 11% at an undesignated primary site (UPS). Estimated RS at 5-years was 37%; for FTC 54%, 40% for OC, 34% for PPC and 13% for UPS. In multivariable regression analyses restricted to women who had undergone primary or interval debulldng surgery for OC, FTC and PPC, site of origin was not independently associated with survival. Significant associations with worse survival were found for advanced stages (RR 2.63, P<0.001), moderate (RR 1.90, P<0.047) and poor differentiation (RR 2.20, P<0.009), neoadjuvant chemotherapy (RR1.33, P<0.022), residual tumor (RR 2.65, P<0.001) and platinum single (2.34, P<0.001) compared to platinum combination chemotherapy. Conclusion. Survival was poorer for serous cancer at UPS than for ovarian, fallopian tube and peritoneal cancer. Serous cancer at UPS needs to be addressed when reporting and comparing survival rates of ovarian cancer. (C) 2016 Elsevier Inc. All rights reserved.
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| 34. |
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| 35. |
- Asplund, Dan, et al.
(författare)
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Pretreatment quality of life in patients with rectal cancer is associated with intrusive thoughts and sense of coherence
- 2017
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Ingår i: International Journal of Colorectal Disease. - : Springer Science and Business Media LLC. - 0179-1958 .- 1432-1262. ; 32:11, s. 1639-1647
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Tidskriftsartikel (refereegranskat)abstract
- Purpose Quality of life may predict survival. In addition to clinical variables, it may be influenced by psychological factors, some of which may be accessible for intervention. The primary objective of this study was to investigate the association of intrusive thoughts and the patients' sense of coherence with pretreatment quality of life in patients with newly diagnosed rectal cancer. Methods Patients were prospectively included in 16 hospitals in Sweden and Denmark. They answered an extensive questionnaire after receiving their treatment plan. Clinical data were retrieved from national quality registries for rectal cancer. Results Of 1248 included patients, a total of 1085 were evaluable. Pretreatment global health-related and overall quality of life was lower in patients planned for palliative compared with curative treatment (median 53 vs. 80 on the EuroQoL visual analogue scale, p < 0.001 and odds ratio 0.56, 95% confidence interval 0.36-0.88, respectively). Quality of life was associated with intrusive thoughts (odds ratio 0.33, 95% confidence interval 0.24-0.45) and sense of coherence (odds ratio 0.44, 95% confidence interval 0.370.52) irrespective of the treatment plan. Conclusions Pretreatment quality of life was influenced by the intent of treatment as well as by intrusive thoughts and the patients' sense of coherence. Interventions could modify these psychological factors, and future studies should focus on initiatives to improve quality of life for this group of patients.
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| 36. |
- Spjuth, Ola, 1977-, et al.
(författare)
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E-Science technologies in a workflow for personalized medicine using cancer screening as a case study
- 2017
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Ingår i: JAMIA Journal of the American Medical Informatics Association. - : Oxford University Press. - 1067-5027 .- 1527-974X. ; 24:5, s. 950-957
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Tidskriftsartikel (refereegranskat)abstract
- Objective: We provide an e-Science perspective on the workflow from risk factor discovery and classification of disease to evaluation of personalized intervention programs. As case studies, we use personalized prostate and breast cancer screenings.Materials and Methods: We describe an e-Science initiative in Sweden, e-Science for Cancer Prevention and Control (eCPC), which supports biomarker discovery and offers decision support for personalized intervention strategies. The generic eCPC contribution is a workflow with 4 nodes applied iteratively, and the concept of e-Science signifies systematic use of tools from the mathematical, statistical, data, and computer sciences.Results: The eCPC workflow is illustrated through 2 case studies. For prostate cancer, an in-house personalized screening tool, the Stockholm-3 model (S3M), is presented as an alternative to prostate-specific antigen testing alone. S3M is evaluated in a trial setting and plans for rollout in the population are discussed. For breast cancer, new biomarkers based on breast density and molecular profiles are developed and the US multicenter Women Informed to Screen Depending on Measures (WISDOM) trial is referred to for evaluation. While current eCPC data management uses a traditional data warehouse model, we discuss eCPC-developed features of a coherent data integration platform.Discussion and Conclusion: E-Science tools are a key part of an evidence-based process for personalized medicine. This paper provides a structured workflow from data and models to evaluation of new personalized intervention strategies. The importance of multidisciplinary collaboration is emphasized. Importantly, the generic concepts of the suggested eCPC workflow are transferrable to other disease domains, although each disease will require tailored solutions.
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| 37. |
- Marcisauskas, Simonas, 1988, et al.
(författare)
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Univariate and classification analysis reveals potential diagnostic biomarkers for early stage ovarian cancer Type 1 and Type 2
- 2019
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Ingår i: Journal of Proteomics. - : Elsevier BV. - 1874-3919 .- 1876-7737. ; 196, s. 57-68
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Tidskriftsartikel (refereegranskat)abstract
- Biomarkers for early detection of ovarian tumors are urgently needed. Tumors of the ovary grow within cysts and most are benign. Surgical sampling is the only way to ensure accurate diagnosis, but often leads to morbidity and loss of female hormones. The present study explored the deep proteome in well-defined sets of ovarian tumors, FIGO stage I, Type 1 (low-grade serous, mucinous, endometrioid; n = 9), Type 2 (high-grade serous; n = 9), and benign serous (n = 9) using TMT–LC–MS/MS. Data are available via ProteomeXchange with identifier PXD010939. We evaluated new bioinformatics tools in the discovery phase. This innovative selection process involved different normalizations, a combination of univariate statistics, and logistic model tree and naive Bayes tree classifiers. We identified 142 proteins by this combined approach. One biomarker panel and nine individual proteins were verified in cyst fluid and serum: transaldolase-1, fructose-bisphosphate aldolase A (ALDOA), transketolase, ceruloplasmin, mesothelin, clusterin, tenascin-XB, laminin subunit gamma-1, and mucin-16. Six of the proteins were found significant (p <.05) in cyst fluid while ALDOA was the only protein significant in serum. The biomarker panel achieved ROC AUC 0.96 and 0.57 respectively. We conclude that classification algorithms complement traditional statistical methods by selecting combinations that may be missed by standard univariate tests. Significance: In the discovery phase, we performed deep proteome analyses of well-defined histology subgroups of ovarian tumor cyst fluids, highly specified for stage and type (histology and grade). We present an original approach to selecting candidate biomarkers combining several normalization strategies, univariate statistics, and machine learning algorithms. The results from validation of selected proteins strengthen our prior proteomic and genomic data suggesting that cyst fluids are better than sera in early stage ovarian cancer diagnostics.
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| 38. |
- Beiranvand, Samira, et al.
(författare)
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Ten years incidence of cancer in Iran : a systematic review and meta-analysis
- 2018
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Ingår i: Clinical Epidemiology and Global Health. - : Elsevier. - 2452-0918 .- 2213-3984. ; 6:2, s. 94-102
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Tidskriftsartikel (refereegranskat)abstract
- BackgroundDesigning and implementation of screening programs depend on greatly epidemiologic basic data in every country. Also Variation in the incidence of various cancers in our country has been a favorite topic.ObjectivesThis systematic review was conducted to provide an overall perspective about incidence, geographical and age distribution of cancers in Iran.MethodsA comprehensive search were done according to MOOSE guideline criteria in national and international databases for selecting eligible articles from 2005 to 2015. After screening titles and abstracts, duplicated and irrelevant studies were excluded. Selected papers are written in Persian or English. The standard error of the cancer incidence was calculated based on the binomial distribution. Because of the significant heterogeneity observed among the results, we used a random-effects model combine the results of the primary studies. Moreover, a sensitivity analysis was undertaken to explore the effects of the risk of bias and other sources of heterogeneity.ResultsOverall 16 articles met eligibility criteria for inclusion. The total incidence of cancer was 19.4 and 17.2 per hundred thousand of people in males and females respectively. The five most common cancers in male were: Lymphoma, leukemia, esophagus, stomach, colorectal and in the female are: breast, colorectal, stomach, thyroid and esophagus. The highest incidence rate was seen in Golestan Province and in the age group over 65 years.ConclusionAccording to increasing incidence rate of cancers in Iran, Development, holding and accomplish of universal public cancer control program should be the first precedence for health policy.
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| 39. |
- Senkowski, Wojciech
(författare)
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High-throughput screening using multicellular tumor spheroids to reveal and exploit tumor-specific vulnerabilities
- 2017
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- High-throughput drug screening (HTS) in live cells is often a vital part of the preclinical anticancer drug discovery process. So far, two-dimensional (2D) monolayer cell cultures have been the most prevalent model in HTS endeavors. However, 2D cell cultures often fail to recapitulate the complex microenvironments of in vivo tumors. Monolayer cultures are highly proliferative and generally do not contain quiescent cells, thought to be one of the main reasons for the anticancer therapy failure in clinic. Thus, there is a need for in vitro cellular models that would increase predictive value of preclinical research results. The utilization of more complex three-dimensional (3D) cell cultures, such as multicellular tumor spheroids (MCTS), which contain both proliferating and quiescent cells, has therefore been proposed. However, difficult handling and high costs still pose significant hurdles for application of MCTS for HTS.In this work, we aimed to develop novel assays to apply MCTS for HTS and drug evaluation. We also set out to identify cellular processes that could be targeted to selectively eradicate quiescent cancer cells. In Paper I, we developed a novel MCTS-based HTS assay and found that nutrient-deprived and hypoxic cancer cells are selectively vulnerable to treatment with inhibitors of mitochondrial oxidative phosphorylation (OXPHOS). We also identified nitazoxanide, an FDA-approved anthelmintic agent, to act as an OXPHOS inhibitor and to potentiate the effects of standard chemotherapy in vivo. Subsequently, in Paper II we applied the high-throughput gene-expression profiling method for MCTS-based drug screening. This led to discovery that quiescent cells up-regulate the mevalonate pathway upon OXPHOS inhibition and that the combination of OXPHOS inhibitors and mevalonate pathway inhibitors (statins) results in synergistic toxicity in this cell population. In Paper III, we developed a novel spheroid-based drug combination-screening platform and identified a set of molecules that synergize with nitazoxanide to eradicate quiescent cancer cells. Finally, in Paper IV, we applied our MCTS-based methods to evaluate the effects of phosphodiesterase (PDE) inhibitors in PDE3A-expressing cell lines.In summary, this work illustrates how MCTS-based HTS yields potential to reveal and exploit previously unrecognized tumor-specific vulnerabilities. It also underscores the importance of cell culture conditions in preclinical drug discovery endeavors.
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| 40. |
- Ge, Chenjie, 1991, et al.
(författare)
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Cross-Modality Augmentation of Brain Mr Images Using a Novel Pairwise Generative Adversarial Network for Enhanced Glioma Classification
- 2019
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Ingår i: Proceedings - International Conference on Image Processing, ICIP. - 1522-4880.
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Konferensbidrag (refereegranskat)abstract
- © 2019 IEEE. Brain Magnetic Resonance Images (MRIs) are commonly used for tumor diagnosis. Machine learning for brain tumor characterization often uses MRIs from many modalities (e.g., T1-MRI, Enhanced-T1-MRI, T2-MRI and FLAIR). This paper tackles two issues that may impact brain tumor characterization performance from deep learning: insufficiently large training dataset, and incomplete collection of MRIs from different modalities. We propose a novel pairwise generative adversarial network (GAN) architecture for generating synthetic brain MRIs in missing modalities by using existing MRIs in other modalities. By improving the training dataset, we aim to mitigate the overfitting and improve the deep learning performance. Main contributions of the paper include: (a) propose a pairwise generative adversarial network (GAN) for brain image augmentation via cross-modality image generation; (b) propose a training strategy to enhance the glioma classification performance, where GAN-augmented images are used for pre-training, followed by refined-training using real brain MRIs; (c) demonstrate the proposed method through tests and comparisons of glioma classifiers that are trained from mixing real and GAN synthetic data, as well as from real data only. Experiments were conducted on an open TCGA dataset, containing 167 subjects for classifying IDH genotypes (mutation or wild-type). Test results from two experimental settings have both provided supports to the proposed method, where glioma classification performance has consistently improved by using mixed real and augmented data (test accuracy 81.03%, with 2.57% improvement).
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