630 research outputs found
Diffusion and utilization of magnetic resonance imaging in Asia.
No full textOBJECTIVES: An assessment of the current status of magnetic resonance imaging (MRI) was undertaken to provide input for future government decisions on the introduction of new technologies in Asia. The objective of the study is to describe and explain the diffusion pattern of this costly technology in several Asian settings. METHODS: Data on the diffusion pattern of MRI for different Asian countries (the Republic of Korea, Malaysia, Indonesia, the Philippines and Thailand) and regions (the cities of Shanghai and Hong Kong in China and the state of Tamil Nadu in India) were obtained from national representatives of professional bodies by using standardized questionnaires for the year 1997-98. In addition, utilization data were collected at the hospital level in three countries before and after the economic crisis in the region. For four countries plus Hong Kong, background information on the legal framework for "big ticket" technologies was collected. RESULTS: Since the introduction of the first MRI in the region in 1987, the number of MRIs has gradually increased both in public and private facilities in Asia. In 1998 the average number of MRI machines installed varied from less than 0.5 machine per million population to more than 5 machines per million population. The maintenance and operating costs, and not the absence of regulation, account for the low number of MRIs in the Philippines and Malaysia. Overall, installed MRIs have low magnetic field strength, vary with respect to brand and type, and are mostly in the private sector and in the urban areas of the region. The diffusion pattern of MRIs in countries of the Asian region appears to follow two types of patterns of diffusion: one set of countries seems to be composed of mostly early adopters and another set of countries appears to be composed mostly of late adopters. CONCLUSIONS: Total number of MRIs per population in this region, though quite small compared to most OECD countries, reflects a higher share of the country's health-resource devoted to expensive high-technology devices. It is difficult to state the appropriate number of MRIs for each country; however, the study shows that there are observable problems in terms of efficiency, equity, and quality of MRI services. The research team proposes a few key recommendations to counteract these problems. Purchasing and regulatory bodies must be empowered with skill and knowledge of health technology assessment. Likewise, the fundamental problems resulting from inefficient and unfair health financing should not be overlooked, so that there is more equitable use of the technology
Robust automated detection of microstructural white matter degeneration in Alzheimer’s disease using machine learning classification of multicenter DTI data
No full textDiffusion tensor imaging (DTI) based assessment of white matter fiber tract integrity can support the diagnosis of Alzheimer’s disease (AD). The use of DTI as a biomarker, however, depends on its applicability in a multicenter setting accounting for effects of different MRI scanners. We applied multivariate machine learning (ML) to a large multicenter sample from the recently created framework of the European DTI study on Dementia (EDSD). We hypothesized that ML approaches may amend effects of multicenter acquisition. We included a sample of 137 patients with clinically probable AD (MMSE 20.6±5.3) and 143 healthy elderly controls, scanned in nine different scanners. For diagnostic classification we used the DTI indices fractional anisotropy (FA) and mean diffusivity (MD) and, for comparison, gray matter and white matter density maps from anatomical MRI. Data were classified using a Support Vector Machine (SVM) and a Naïve Bayes (NB) classifier. We used two cross-validation approaches, (i) test and training samples randomly drawn from the entire data set (pooled cross-validation) and (ii) data from each scanner as test set, and the data from the remaining scanners as training set (scanner-specific cross-validation). In the pooled cross-validation, SVM achieved an accuracy of 80% for FA and 83% for MD. Accuracies for NB were significantly lower, ranging between 68% and 75%. Removing variance components arising from scanners using principal component analysis did not significantly change the classification results for both classifiers. For the scanner-specific cross-validation, the classification accuracy was reduced for both SVM and NB. After mean correction, classification accuracy reached a level comparable to the results obtained from the pooled cross-validation. Our findings support the notion that machine learning classification allows robust classification of DTI data sets arising from multiple scanners, even if a new data set comes from a scanner that was not part of the training sample
Cerebral atrophy in mild cognitive impairment and Alzheimer disease: rates and acceleration.
No full textOBJECTIVE: To quantify the regional and global cerebral atrophy rates and assess acceleration rates in healthy controls, subjects with mild cognitive impairment (MCI), and subjects with mild Alzheimer disease (AD). METHODS: Using 0-, 6-, 12-, 18-, 24-, and 36-month MRI scans of controls and subjects with MCI and AD from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database, we calculated volume change of whole brain, hippocampus, and ventricles between all pairs of scans using the boundary shift integral. RESULTS: We found no evidence of acceleration in whole-brain atrophy rates in any group. There was evidence that hippocampal atrophy rates in MCI subjects accelerate by 0.22%/year2 on average (p = 0.037). There was evidence of acceleration in rates of ventricular enlargement in subjects with MCI (p = 0.001) and AD (p < 0.001), with rates estimated to increase by 0.27 mL/year2 (95% confidence interval 0.12, 0.43) and 0.88 mL/year2 (95% confidence interval 0.47, 1.29), respectively. A post hoc analysis suggested that the acceleration of hippocampal loss in MCI subjects was mainly driven by the MCI subjects that were observed to progress to clinical AD within 3 years of baseline, with this group showing hippocampal atrophy rate acceleration of 0.50%/year2 (p = 0.003). CONCLUSIONS: The small acceleration rates suggest a long period of transition to the pathologic losses seen in clinical AD. The acceleration in hippocampal atrophy rates in MCI subjects in the ADNI seems to be driven by those MCI subjects who concurrently progressed to a clinical diagnosis of AD
Short-interval observational data to inform clinical trial design in Huntington's disease.
No full textOBJECTIVES: To evaluate candidate outcomes for disease-modifying trials in Huntington's disease (HD) over 6-month, 9-month and 15-month intervals, across multiple domains. To present guidelines on rapid efficacy readouts for disease-modifying trials. METHODS: 40 controls and 61 patients with HD, recruited from four EU sites, underwent 3 T MRI and standard clinical and cognitive assessments at baseline, 6 and 15 months. Neuroimaging analysis included global and regional change in macrostructure (atrophy and cortical thinning), and microstructure (diffusion metrics). The main outcome was longitudinal effect size (ES) for each outcome. Such ESs can be used to calculate sample-size requirements for clinical trials for hypothesised treatment efficacies. RESULTS: Longitudinal changes in macrostructural neuroimaging measures such as caudate atrophy and ventricular expansion were significantly larger in HD than controls, giving rise to consistently large ES over the 6-month, 9-month and 15-month intervals. Analogous ESs for cortical metrics were smaller with wide CIs. Microstructural (diffusion) neuroimaging metrics ESs were also typically smaller over the shorter intervals, although caudate diffusivity metrics performed strongly over 9 and 15 months. Clinical and cognitive outcomes exhibited small longitudinal ESs, particularly over 6-month and 9-month intervals, with wide CIs, indicating a lack of precision. CONCLUSIONS: To exploit the potential power of specific neuroimaging measures such as caudate atrophy in disease-modifying trials, we propose their use as (1) initial short-term readouts in early phase/proof-of-concept studies over 6 or 9 months, and (2) secondary end points in efficacy studies over longer periods such as 15 months
Academic authorship: who, why and in what order?
No full textWe are frequently asked by our colleagues and students for advice on authorship for scientific articles. This short paper outlines some of the issues that we have experienced and the advice we usually provide. This editorial follows on from our work on submitting a paper1 and also on writing an academic paper for publication.2 We should like to start by noting that, in our view, there exist two separate, but related issues: (a) authorship and (b) order of authors. The issue of authorship centres on the notion of who can be an author, who should be an author and who definitely should not be an author, and this is partly discipline specific. The second issue, the order of authors, is usually dictated by the academic tradition from which the work comes. One can immediately envisage disagreements within a multi-disciplinary team of researchers where members of the team may have different approaches to authorship order
The clinical importance of white matter hyperintensities on brain magnetic resonance imaging: systematic review and meta-analysis.
No full textObjectives: To review the evidence for an association of white matter hyperintensities with risk of stroke, cognitive decline, dementia, and death.
Design: Systematic review and meta-analysis.
Data sources: PubMed from 1966 to 23 November 2009.
Study selection: Prospective longitudinal studies that used magnetic resonance imaging and assessed the impact of white matter hyperintensities on risk of incident stroke, cognitive decline, dementia, and death, and, for the meta-analysis, studies that provided risk estimates for a categorical measure of white matter hyperintensities, assessing the impact of these lesions on risk of stroke, dementia, and death.
Data extraction: Population studied, duration of follow-up, method used to measure white matter hyperintensities, definition of the outcome, and measure of the association of white matter hyperintensities with the outcome.
Data synthesis: 46 longitudinal studies evaluated the association of white matter hyperintensities with risk of stroke (n=12), cognitive decline (n=19), dementia (n=17), and death (n=10). 22 studies could be included in a meta-analysis (nine of stroke, nine of dementia, eight of death). White matter hyperintensities were associated with an increased risk of stroke (hazard ratio 3.3, 95% confidence interval 2.6 to 4.4), dementia (1.9, 1.3 to 2.8), and death (2.0, 1.6 to 2.7). An association of white matter hyperintensities with a faster decline in global cognitive performance, executive function, and processing speed was also suggested.
Conclusion: White matter hyperintensities predict an increased risk of stroke, dementia, and death. Therefore white matter hyperintensities indicate an increased risk of cerebrovascular events when identified as part of diagnostic investigations, and support their use as an intermediate marker in a research setting. Their discovery should prompt detailed screening for risk factors of stroke and dementia
Mismatch-based delayed thrombolysis: a meta-analysis
No full text<p><b>Background and Purpose</b>: Clinical benefit from thrombolysis is reduced as stroke onset to treatment time increases. The use of "mismatch" imaging to identify patients for delayed treatment has face validity and has been used in case series and clinical trials. We undertook a meta-analysis of relevant trials to examine whether present evidence supports delayed thrombolysis among patients selected according to mismatch criteria.</p>
<p><b>Methods</b>: We collated outcome data for patients who were enrolled after 3 hours of stroke onset in thrombolysis trials and had mismatch on pretreatment imaging. We selected the trials on the basis of a systematic search of the Web of Knowledge. We compared favorable outcome, reperfusion and/or recanalization, mortality, and symptomatic intracerebral hemorrhage between the thrombolyzed and nonthrombolyzed groups of patients and the probability of a favorable outcome among patients with successful reperfusion and clinical findings for 3 to 6 versus 6 to 9 hours from poststroke onset. Results are expressed as adjusted odds ratios (a-ORs) with 95% CIs. Heterogeneity was explored by test statistics for clinical heterogeneity, I2 (inconsistency), and L’Abbé plot.</p>
<p><b>Results</b>: We identified articles describing the DIAS, DIAS II, DEDAS, DEFUSE, and EPITHET trials, giving a total of 502 mismatch patients thrombolyzed beyond 3 hours. The combined a-ORs for favorable outcomes were greater for patients who had successful reperfusion (a-OR=5.2; 95% CI, 3 to 9; I2=0%). Favorable clinical outcome was not significantly improved by thrombolysis (a-OR=1.3; 95% CI, 0.8 to 2.0; I2=20.9%). Odds for reperfusion/recanalization were increased among patients who received thrombolytic therapy (a-OR=3.0; 95% CI, 1.6 to 5.8; I2=25.7%). The combined data showed a significant increase in mortality after thrombolysis (a-OR=2.4; 95% CI, 1.2 to 4.9; I2=0%), but this was not confirmed when we excluded data from desmoteplase doses that were abandoned in clinical development (a-OR=1.6; 95% CI, 0.7 to 3.7; I2=0%). Symptomatic intracerebral hemorrhage was significantly increased after thrombolysis (a-OR=6.5; 95% CI, 1.2 to 35.4; I2=0%) but not significant after exclusion of abandoned doses of desmoteplase (a-OR=5.4; 95% CI, 0.9 to 31.8; I2=0%).</p>
<p><b>Conclusions</b>: Delayed thrombolysis amongst patients selected according to mismatch imaging is associated with increased reperfusion/recanalization. Recanalization/reperfusion is associated with improved outcomes. However, delayed thrombolysis in mismatch patients was not confirmed to improve clinical outcome, although a useful clinical benefit remains possible. Thrombolysis carries a significant risk of symptomatic intracerebral hemorrhage and possibly increased mortality. Criteria to diagnose mismatch are still evolving. Validation of the mismatch selection paradigm is required with a phase III trial. Pending these results, delayed treatment, even according to mismatch selection, cannot be recommended as part of routine care.</p>
Quantitative muscle MRI to follow up late onset Pompe patients: A prospective study
No full text\ua9 2018 The Author(s).Late onset Pompe disease (LOPD) is a slow, progressive disorder characterized by skeletal and respiratory muscle weakness. Enzyme replacement therapy (ERT) slows down the progression of muscle symptoms. Reliable biomarkers are needed to follow up ERT-treated and asymptomatic LOPD patients in clinical practice. In this study, 32 LOPD patients (22 symptomatic and 10 asymptomatic) underwent muscle MRI using 3-point Dixon and were evaluated at the time of the MRI with several motor function tests and patient-reported outcome measures, and again after one year. Muscle MRI showed a significant increase of 1.7% in the fat content of the thigh muscles in symptomatic LOPD patients. In contrast, there were no noteworthy differences between muscle function tests in the same period of time. We did not observe any significant changes either in muscle MRI or in muscle function tests in asymptomatic patients over the year. We conclude that 3-point Dixon muscle MRI is a useful tool for detecting changes in muscle structure in symptomatic LOPD patients and could become part of the current follow-up protocol in daily clinics
A systematic review of evidence on malignant spinal metastases : natural history and technologies for identifying patients at high risk of vertebral fracture and spinal cord compression
No full textBackground: Spinal metastases can lead to significant morbidity and reduction in quality of life due to spinal cord compression (SCC). Between 5% and 20% of patients with spinal metastases develop metastatic spinal cord compression during the course of their disease. An early study estimated average survival for patients with SCC to be between 3 and 7 months, with a 36% probability of survival to 12 months. An understanding of the natural history and early diagnosis of spinal metastases and prediction of collapse of the metastatic vertebrae are important.
Objective: To undertake a systematic review to examine the natural history of metastatic spinal lesions and to identify patients at high risk of vertebral fracture and SCC.
Data sources: The search strategy covered the concepts of metastasis, the spine and adults. Searches were undertaken from inception to June 2011 in 13 electronic databases [MEDLINE; MEDLINE In-Process & Other Non-Indexed Citations; EMBASE; Cochrane Database of Systematic Reviews; Cochrane Central Register of Controlled Trials (CENTRAL); Database of Abstracts of Reviews of Effects (DARE), NHS Economic Evaluation Database (NHS EED), HTA databases (NHS Centre for Reviews and Dissemination); Science Citation Index and Conference Proceedings (Web of Science); UK Clinical Research Network (UKCRN) Portfolio Database; Current Controlled Trials; ClinicalTrials.gov].
Review methods: Titles and abstracts of retrieved studies were assessed by two reviewers independently. Disagreement was resolved by consensus agreement. Full data were extracted independently by one reviewer. All included studies were reviewed by a second researcher with disagreements resolved by discussion. A quality assessment instrument was used to assess bias in six domains: study population, attrition, prognostic factor measurement, outcome measurement, confounding measurement and account, and analysis. Data were tabulated and discussed in a narrative review. Each tumour type was looked at separately.
Results: In all, 2425 potentially relevant articles were identified, of which 31 met the inclusion criteria. No study examined natural history alone. Seventeen studies reported retrospective data, 10 were prospective studies, and three were other study designs. There was one systematic review. There were no randomised controlled trials (RCTs). Approximately 5782 participants were included. Sample sizes ranged from 41 to 859. The age of participants ranged between 7 and 92 years. Types of cancers reported on were lung alone (n= 3), prostate alone (n= 6), breast alone (n= 7), mixed cancers (n= 13) and unclear (n= 1). A total of 93 prognostic factors were identified as potentially significant in predicting risk of SCC or collapse. Overall findings indicated that the more spinal metastases present and the longer a patient was at risk, the greater the reported likelihood of development of SCC and collapse. There was an increased risk of developing SCC if a cancer had already spread to the bones. In the prostate cancer studies, tumour grade, metastatic load and time on hormone therapy were associated with increased risk of SCC. In one study, risk of SCC before death was 24%, and 2.37 times greater with a Gleason score 7 than with a score of < 7 (p= 0.003). Other research found that patients with six or more bone lesions were at greater risk of SCC than those with fewer than six lesions [odds ratio (OR) 2.9, 95% confidence interval (CI) 1.012 to 8.35, p= 0.047]. For breast cancer patients who received a computerised tomography (CT) scan for suspected SCC, multiple logistic regression in one study identified four independent variables predictive of a positive test: bone metastases 2 years (OR 3.0 95% CI 1.2 to 7.6; p= 0.02); metastatic disease at initial diagnosis (OR 3.4, 95% CI 1.0 to 11.4; p= 0.05); objective weakness (OR 3.8, 95% CI 1.5 to 9.5; p= 0.005); and vertebral compression fracture on spine radiograph (OR 2.6, 95% CI 1.0 to 6.5; p= 0.05). A further study on mixed cancers, among patients who received surgery for SCC, reported that vertebral body compression fractures were associated with presurgery chemotherapy (OR 2.283, 95% CI 1.064 to 4.898; p= 0.03), cancer type [primary breast cancer (OR 4.179, 95% CI 1.457 to 11.983; p= 0.008)], thoracic involvement (OR 3.505, 95% CI 1.343 to 9.143; p= 0.01) and anterior cord compression (OR 3.213, 95% CI 1.416 to 7.293; p= 0.005).
Limitations: Many of the included studies provided limited information about patient populations and selection criteria and they varied in methodological quality, rigour and transparency. Several studies identified type of cancer (e.g. breast, lung or prostate cancer) as a significant factor in predicting SCC, but it remains difficult to determine the risk differential partly because of residual bias. Consideration of quantitative results from the studies does not easily allow generation of a coherent numerical summary, studies were heterogeneous especially with regard to population, results were not consistent between studies, and study results almost universally lacked corroboration from other independent studies.
Conclusion: No studies were found which examined natural history. Overall burden of metastatic disease, confirmed metastatic bone involvement and immediate symptomatology suggestive of spinal column involvement are already well known as factors for metastatic SCC, vertebral collapse or progression of vertebral collapse. Although we identified a large number of additional possible prognostic factors, those which currently offer the most potential are unclear. Current clinical consensus favours magnetic resonance imaging and CT imaging modalities for the investigation of SCC and vertebral fracture. Future research should concentrate on: (1) prospective randomised designs to establish clinical and quality-of-life outcomes and cost-effectiveness of identification and treatment of patients at high risk of vertebral collapse and SCC; (2) Service Delivery and Organisation research on magnetic resonance imaging (MRI) scans and scanning (in tandem with research studies on use of MRI to monitor progression) in order to understand best methods for maximising use of MRI scanners; and (3) investigation of prognostic algorithms to calculate probability of a specified event using high-quality prospective studies, involving defined populations, randomly selected and clearly identified samples, and with blinding of investigators
A Body shape index significantly predicts MRI-defined abdominal adipose tissue depots in non-obese Asian Indians with type 2 diabetes mellitus
No full textIntroduction We aimed to determine the correlations of volumes of subcutaneous abdominal adipose tissue (SCAT) (anterior, posterior, superficial and deep), total SCAT, intraperitoneal adipose tissue, retroperitoneal abdominal adipose tissue (RPAT), total intra-abdominal adipose tissue (IAAT), pancreatic volume, liver span, total body fat (TBF) and truncal fat mass (TFM) with anthropometric indices, viz., A Body Shape Index (ABSI), Hip Index, their Z scores and Anthropometric Risk Index in non-obese (body mass index (BMI) <25 kg/m2) Asian Indians with type 2 diabetes mellitus (T2DM).Research design and methods Non-obese patients with T2DM (cases; n, 85) and BMI-matched, healthy subjects (controls; n, 38) underwent anthropometry, dual energy X ray absorptiometry (DXA) for estimation of TBF, TFM and 1.5 T MRI for estimation of volumes of abdominal adipose tissue depots, pancreas and liver span. Spearman’s correlation analysis and Receiver Operator Characteristic curve analysis were applied.Results The Z score of ABSI (Z_ABSI) showed significantly positive correlation with volumes of all depots of abdominal SCAT, total IAAT and RPAT in cases. Area under the curve for Z_ABSI (0.87) showed higher sensitivity: 82.0 %, specificity: 81.5 %, at a predictive cut-off value of 0.49 for abdominal adiposity.Conclusion In non-obese Asian Indians with T2DM, the Z_ABSI showed significant correlation with IAAT and SCAT and higher predictive accuracy for abdominal adiposity.Highlights of the study This is the first MRI-based study in the context of ABSI in non-obese (BMI <25 kg/m2) Asian Indians with T2DM. Findings indicate that Z_ABSI has high predictive accuracy for abdominal adiposity in non-obese Asian Indians. The Z_ABSI index showed significantly positive correlation with volumes of adipose tissue depots, viz., abdominal SCAT, total IAAT and RPAT in cases
- …
