Unsupervised learning for cross-domain medical image synthesis using deformation invariant cycle consistency networks

Recently, the cycle-consistent generative adversarial networks (CycleGAN) has been widely used for synthesis of multi-domain medical images. The domain-specific nonlinear deformations captured by CycleGAN make the synthesized images difficult to be used for some applications, for example, generating pseudo-CT for PET-MR attenuation correction. This paper presents a deformation-invariant CycleGAN (DicycleGAN) method using deformable convolutional layers and new cycle-consistency losses. Its robustness dealing with data that suffer from domain-specific nonlinear deformations has been evaluated through comparison experiments performed on a multi-sequence brain MR dataset and a multi-modality abdominal dataset. Our method has displayed its ability to generate synthesized data that is aligned with the source while maintaining a proper quality of signal compared to CycleGAN-generated data. The proposed model also obtained comparable performance with CycleGAN when data from the source and target domains are alignable through simple affine transformations

Why Does Synthesized Data Improve Multi-sequence Classification?

The classification and registration of incomplete multi-modal medical images, such as multi-sequence MRI with missing sequences, can sometimes be improved by replacing the missing modalities with synthetic data. This may seem counter-intuitive: synthetic data is derived from data that is already available, so it does not add new information. Why can it still improve performance? In this paper we discuss possible explanations. If the synthesis model is more flexible than the classifier, the synthesis model can provide features that the classifier could not have extracted from the original data. In addition, using synthetic information to complete incomplete samples increases the size of the training set. We present experiments with two classifiers, linear support vector machines (SVMs) and random forests, together with two synthesis methods that can replace missing data in an image classification problem: neural networks and restricted Boltzmann machines (RBMs). We used data from the BRATS 2013 brain tumor segmentation challenge, which includes multi-modal MRI scans with T1, T1 post-contrast, T2 and FLAIR sequences. The linear SVMs appear to benefit from the complex transformations offered by the synthesis models, whereas the random forests mostly benefit from having more training data. Training on the hidden representation from the RBM brought the accuracy of the linear SVMs close to that of random forests

HeMIS: Hetero-Modal Image Segmentation

We introduce a deep learning image segmentation framework that is extremely robust to missing imaging modalities. Instead of attempting to impute or synthesize missing data, the proposed approach learns, for each modality, an embedding of the input image into a single latent vector space for which arithmetic operations (such as taking the mean) are well defined. Points in that space, which are averaged over modalities available at inference time, can then be further processed to yield the desired segmentation. As such, any combinatorial subset of available modalities can be provided as input, without having to learn a combinatorial number of imputation models. Evaluated on two neurological MRI datasets (brain tumors and MS lesions), the approach yields state-of-the-art segmentation results when provided with all modalities; moreover, its performance degrades remarkably gracefully when modalities are removed, significantly more so than alternative mean-filling or other synthesis approaches.Comment: Accepted as an oral presentation at MICCAI 201

Effectiveness of Surgery for Lumbar Spinal Stenosis : A Systematic Review and Meta-Analysis

Peer reviewedPublisher PD

Predicting chronic low-back pain based on pain trajectories in patients in an occupational setting: an exploratory analysis.

OBJECTIVE: This study aimed to (i) identify subpopulations of patients in an occupational setting who will still have or develop chronic low-back pain (LBP) and (ii) evaluate a previously developed prediction model based on the determined subpopulations. METHOD: In this prospective cohort, study data were analyzed from three merged randomized controlled trials, conducted in an occupational setting (N=622). Latent class growth analysis (LCGA) was used to distinguish patients with a different course of pain intensity measured over 12 months. The determined subpopulations were used to derive a definition for chronic LBP and evaluate an existing model to predict chronic LBP. RESULTS: The LCGA model identified three subpopulations of LBP patients. These were used to define recovering (353) and chronic (269) patients. None of the interventions showed a relevant treatment effect over another but the rate of decline in symptoms during the first months of the intervention seems to predict recovery. The prediction model, based on this dichotomous outcome, with the variables pain intensity, kinesiophobia and a clinically relevant change in pain intensity and functional status in the first three months, showed a bootstrap-corrected performance with an area under the operating characteristic curve (AUC) of 0.75 and explained variance of 0.26. CONCLUSION: In an occupational setting, different subpopulations of chronic LBP patients could be identified using LCGA. The prediction model based on these subpopulations showed a promising predictive performance

Effectiveness of multifaceted implementation strategies for the implementation of back and neck pain guidelines in health care: a systematic review

Background: For the optimal use of clinical guidelines in daily practice, mere distribution of guidelines and materials is not enough, and active implementation is needed. This review investigated the effectiveness of multifaceted implementation strategies compared to minimal, single, or no implementation strategy for the implementation of non-specific low back and/or neck pain guidelines in health care. Methods: The following electronic databases were searched from inception to June 1, 2015: MEDLINE, Embase, PsycInfo, the Cochrane Library, and CINAHL. The search strategy was restricted to low back pain, neck pain, and implementation research. Studies were included if their design was a randomized controlled trial, reporting on patients (age ≥18years) with non-specific low back pain or neck pain (with or without radiating pain). Trials were eligible if they reported patient outcomes, measures of healthcare professional behaviour, and/or outcomes on healthcare level. The primary outcome was professional behaviour. Guidelines that were evaluated in the studies had to be implemented in a healthcare setting. No language restrictions were applied, and studies had to be published full-text in peer-reviewed journals, thus excluding abstract only publications, conference abstracts, and dissertation articles. Two researchers independently screened titles and abstract, extracted data from included studies, and performed risk of bias assessments. Results: After removal of duplicates, the search resulted in 4750 abstracts to be screened. Of 43 full-text articles assessed for eligibility, 12 were included in this review, reporting on 9 individual studies, and separate cost-effectiveness analyses of 3 included studies. Implementation strategies varied between studies. Meta-analyses did not reveal any differences in effect between multifaceted strategies and controls. Conclusion: This review showed that multifaceted strategies for the implementation of neck and/or back pain guidelines in health care do not significantly improve professional behaviour outcomes. No effects on patient outcomes or cost of care could be found. More research is necessary to determine whether multifaceted implementation strategies are conducted as planned and whether these strategies are effective in changing professional behaviour and thereby clinical practice

Motivational interviewing and problem solving treatment to reduce type 2 diabetes and cardiovascular disease risk in real life: a randomized controlled trial

BACKGROUND: Intensive lifestyle interventions in well-controlled settings are effective in lowering the risk of chronic diseases such as type 2 diabetes (T2DM) and cardiovascular diseases (CVD), but there are still no effective lifestyle interventions for everyday practice. In the Hoorn Prevention Study we aimed to assess the effectiveness of a primary care based lifestyle intervention to reduce the estimated risk of developing T2DM and for CVD mortality, and to motivate changes in lifestyle behaviors. METHODS: The Hoorn Prevention Study is a parallel group randomized controlled trial, implemented in the region of West-Friesland, the Netherlands. 622 adults with ≥10% estimated risk of T2DM and/or CVD mortality were randomly assigned and monitored over a period of 12 months. The intervention group (n=314) received a theory-based lifestyle intervention based on an innovative combination of motivational interviewing and problem solving treatment, provided by trained practice nurses in 12 general practices. The control group (n=308) received existing health brochures. Primary outcomes was the estimated diabetes risk according to the formula of the Atherosclerosis Risk In Communities (ARIC) Study, and the estimated risk for CVD mortality according to the Systematic COronary Risk Evaluation (SCORE) formula. Secondary outcomes included lifestyle behavior (diet, physical activity and smoking). The research assistants, the principal investigator and the general practitioners were blinded to group assignment. Linear and logistic regression analysis was applied to examine the between-group differences in each outcome measure, adjusted for baseline values. RESULTS: 536 (86.2%) of the 622 participants (age 43.5 years) completed the 6-month follow-up, and 502 (81.2%) completed the 12-month follow-up. The mean baseline T2DM risk was 18.9% (SD 8.2) and the mean CVD mortality risk was 3.8% (SD 3.0). The intervention group participated in a median of 2 sessions. Intention-to-treat analyses showed no significant differences in outcomes between the two groups at 6 or 12-months follow-up. CONCLUSIONS: The lifestyle intervention was not more effective than health brochures in reducing risk scores for T2DM and CVD or improving lifestyle behavior in an at-risk population. TRIAL REGISTRATION: Current Controlled Trials: ISRCTN59358434

Systematic reviews of complementary therapies - an annotated bibliography. Part 1: Acupuncture

Background Complementary therapies are widespread but controversial. We aim to provide a comprehensive collection and a summary of systematic reviews of clinical trials in three major complementary therapies (acupuncture, herbal medicine, homeopathy). This article is dealing with acupuncture. Potentially relevant reviews were searched through the register of the Cochrane Complementary Medicine Field, the Cochrane Library, Medline, and bibliographies of articles and books. To be included articles had to review prospective clinical trials of acupuncture; had to describe review methods explicitly; had to be published; and had to focus on treatment effects. Information on conditions, interventions, methods, results and conclusions was extracted using a pretested form and summarized descriptively. Results From a total of 48 potentially relevant reviews preselected in a screeening process 39 met the inclusion criteria. 22 were on various pain syndromes or rheumatic diseases. Other topics addressed by more than one review were addiction, nausea, asthma and tinnitus. Almost unanimously the reviews state that acupuncture trials include too few patients. Often included trials are heterogeneous regarding patients, interventions and outcome measures, are considered to have insufficient quality and contradictory results. Convincing evidence is available only for postoperative nausea, for which acupuncture appears to be of benefit, and smoking cessation, where acupuncture is no more effective than sham acupuncture. Conclusions A large number of systematic reviews on acupuncture exists. What is most obvious from these reviews is the need for (the funding of) well-designed, larger clinical trials

Patient versus general population health state valuations:a case study of non-specific low back pain

PURPOSE: The purpose of this study was twofold: (1) to compare non-specific low back pain (LBP) patients' health state valuations with those of the general population, and (2) to explore how aspects of health-related quality of life as measured by the EQ-5D-3L impact non-specific LBP patient valuations. METHODS: Data were used of a randomized controlled trial, including 483 non-specific LBP patients. Outcomes included the EQ-VAS and the EQ-5D-3L. Patient valuations were derived from the EQ-VAS. Population valuations were derived from the EQ-5D-3L using a Dutch VAS-based tariff. The difference between patient and population valuations was assessed using t tests. An OLS linear regression model was constructed to explore how various aspects of health-related quality of life as measured by the ED-5D-3L impact non-specific LBP patient valuations. RESULTS: Non-specific LBP patients valued their health states 0.098 (95% CI 0.082-0.115) points higher than the general population. Only 22.2% of the variance in patient valuations was explained by the patients' EQ-5D-3L health states (R (2) = 0.222). Non-specific LBP patients gave the most weight to the anxiety/depression dimension. CONCLUSIONS: This study demonstrated that non-specific LBP patients value their health states higher than members of the general population and that the choice of valuation method could have important implications for cost-effectiveness analyses and thus for clinical practice

Partnering capacities for inclusive development in food provisioning

_Context_ This paper focuses on partnerships working on inclusive development and food security in agri‐food chains and agribusiness clusters that may feature institutional arrangements reinforcing inequality or inducing exclusion. _Research question_ The paper develops a theory‐driven capacity framework for investigating how intervention strategies related to partnering generate developmental outcomes. _Methods_ Building on action research and drawing on complementary literature streams, the framework distinguishes four specific capacities that individually and in configuration contribute to processes of inclusive development triggered by partnering processes. The framework is applied to two case examples targeting inclusive development in agri‐food chains and agribusiness clusters in domestic food markets in Benin and Nigeria. _Res