Accurate PET quantitation requires a matched attenuation map. Obtaining matched CT attenuation maps in the thorax is difficult due to the respiratory cycle which causes both motion and density ...changes. Unlike with motion, little attention has been given to the effects of density changes in the lung on PET quantitation. This work aims to explore the extent of the errors caused by pulmonary density attenuation map mismatch on dynamic and static parameter estimates. Dynamic XCAT phantoms were utilised using clinically relevant 18F-FDG and 18F-FMISO time activity curves for all organs within the thorax to estimate the expected parameter errors. The simulations were then validated with PET data from 5 patients suffering from idiopathic pulmonary fibrosis who underwent PET/Cine-CT. The PET data were reconstructed with three gates obtained from the Cine-CT and the average Cine-CT. The lung TACs clearly displayed differences between true and measured curves with error depending on global activity distribution at the time of measurement. The density errors from using a mismatched attenuation map were found to have a considerable impact on PET quantitative accuracy. Maximum errors due to density mismatch were found to be as high as 25% in the XCAT simulation. Differences in patient derived kinetic parameter estimates and static concentration between the extreme gates were found to be as high as 31% and 14%, respectively. Overall our results show that respiratory associated density errors in the attenuation map affect quantitation throughout the lung, not just regions near boundaries. The extent of this error is dependent on the activity distribution in the thorax and hence on the tracer and time of acquisition. Consequently there may be a significant impact on estimated kinetic parameters throughout the lung.
Pharmacokinetic modelling on dynamic positron emission tomography (PET) data is a quantitative technique. However, the long acquisition time is prohibitive for routine clinical use. Instead, the ...semi-quantitative standardised uptake value ratio (SUVR) from a shorter static acquisition is used, despite its sensitivity to blood flow confounding longitudinal analysis. A method has been proposed to reduce the dynamic acquisition time for quantification by incorporating cerebral blood flow (CBF) information from arterial spin labelling (ASL) magnetic resonance imaging (MRI) into the pharmacokinetic modelling. In this work, we optimise and validate this framework for a study of ageing and preclinical Alzheimer's disease. This methodology adapts the simplified reference tissue model (SRTM) for a reduced acquisition time (RT-SRTM) and is applied to 18F-florbetapir PET data for amyloid-β quantification. Evaluation shows that the optimised RT-SRTM can achieve amyloid burden estimation from a 30-min PET/MR acquisition which is comparable with the gold standard SRTM applied to 60 min of PET data. Conversely, SUVR showed a significantly higher error and bias, and a statistically significant correlation with tracer delivery due to the influence of blood flow. The optimised RT-SRTM produced amyloid burden estimates which were uncorrelated with tracer delivery indicating its suitability for longitudinal studies.
Although many aspects of systematic reviews use computational tools, systematic reviewers have been reluctant to adopt machine learning tools.
We discuss that the potential reason for the slow ...adoption of machine learning tools into systematic reviews is multifactorial. We focus on the current absence of trust in automation and set-up challenges as major barriers to adoption. It is important that reviews produced using automation tools are considered non-inferior or superior to current practice. However, this standard will likely not be sufficient to lead to widespread adoption. As with many technologies, it is important that reviewers see "others" in the review community using automation tools. Adoption will also be slow if the automation tools are not compatible with workflows and tasks currently used to produce reviews. Many automation tools being developed for systematic reviews mimic classification problems. Therefore, the evidence that these automation tools are non-inferior or superior can be presented using methods similar to diagnostic test evaluations, i.e., precision and recall compared to a human reviewer. However, the assessment of automation tools does present unique challenges for investigators and systematic reviewers, including the need to clarify which metrics are of interest to the systematic review community and the unique documentation challenges for reproducible software experiments.
We discuss adoption barriers with the goal of providing tool developers with guidance as to how to design and report such evaluations and for end users to assess their validity. Further, we discuss approaches to formatting and announcing publicly available datasets suitable for assessment of automation technologies and tools. Making these resources available will increase trust that tools are non-inferior or superior to current practice. Finally, we identify that, even with evidence that automation tools are non-inferior or superior to current practice, substantial set-up challenges remain for main stream integration of automation into the systematic review process.
Cannabis legalization has enabled increased consumption in older adults. Age-related mental, physical, and physiological changes may lead to differences in effects of cannabis in older adults ...compared to younger individuals.
To perform a scoping review to map the evidence regarding the health effects of cannabis use for medical and non-medical purposes in older adults.
Electronic databases (MEDLINE, Embase, PsycINFO, Cochrane Library) were searched for systematic reviews (SRs), randomized controlled trials (RCTs) and non-randomized/observational studies (NRSs) assessing the health effects and associations of cannabis use (medical or non-medical) in adults ≥ 50 years of age. Included studies met age-related inclusion criteria or involved a priori identified health conditions common among older adults. Records were screened using a liberal accelerated approach and data charting was performed independently by two reviewers. Descriptive summaries, structured tables, effect direction plots and bubble plots were used to synthesize study findings.
From 31,393 citations, 133 publications describing 134 unique studies (26 SRs, 36 RCTs, 72 NRSs) were included. Medical cannabis had inconsistent therapeutic effects in specific patient conditions (e.g., end-stage cancer, dementia), with a number of studies suggesting possible benefits while others found no benefit. For medical cannabis, harmful associations outnumbered beneficial, and RCTs reported more negative effects than NRSs. Cannabis use was associated with greater frequencies of depression, anxiety, cognitive impairment, substance use and problematic substance use, accidents/injuries, and acute healthcare use. Studies often were small, did not consistently assess harms, and did not adjust for confounding.
The effects of medical cannabis are inconsistent within specific patient conditions. For older adults, generally, the available evidence suggests cannabis use may be associated with greater frequencies of mental health issues, substance use, and acute healthcare use, and the benefit-to-risk ratio is unclear. Studies with a balanced assessment of benefits and harms may guide appropriate public health messaging to balance the marketing pressures of cannabis to older adults.
Hearing loss is one of the leading causes of disability worldwide. Patients with hearing loss experience impaired quality of life, as well as emotional and financial consequences that affect both ...themselves and their families. Idiopathic sudden sensorineural hearing loss (ISSNHL) is a common but difficult to treat condition that has a sudden onset of ≤ 72 hour associated with various etiologies, with the majority of cases being idiopathic. There exists a wide range of therapeutic options, however, the uncertainty surrounding their comparative efficacy and safety makes selection of treatment difficult. This systematic review and network meta-analysis (NMA) assessed the relative effects of competing treatments for management of ISSNHL.
A protocol for this review was registered with PROSPERO (CRD42017073756). A detailed search of MEDLINE, Embase and the Cochrane Library from inception to February 8th, 2018 was carried out by an experienced information specialist. Grey literature was also searched. Screening full-text records, and risk of bias assessment were carried out independently by two reviewers, and disagreements were resolved through consensus or third party adjudication, while data was collected by one reviewer and verified by a second reviewer. Bayesian network meta-analyses (NMA) were performed to inform comparisons between interventions for a priori specified outcomes that included pure tone average (PTA) improvement and hearing recovery.
The search identified a total of 1,138 citations, of which 613 remained for review after removal of duplicates. Of these, 23 publications describing 19 unique studies (total sample size of 1,527) met our a priori eligibility criteria, that were assessed to be at unclear or high risk of bias on several domains. We identified data on several interventions for ISSNHL therapy and were able to construct treatment networks consisting of six intervention groups that included placebo; intratympanic (IT) steroid; IT plus systemic steroid; per oral (PO) steroid; intravenous (IV) steroid; and IV plus PO steroid for our NMAs. IT plus systemic steroids demonstrated the largest difference in PTA improvement compared to placebo (25.85 dB, 95% CrI 7.18-40.58), followed by IV plus PO steroids (22.06 dB, 95% CrI 1.24-39.17), IT steroids (18.24 dB, 95% CrI 3.00-29.81). We observed that the difference of PTA improvement between each intervention and placebo diminished over time, attributed to spontaneous recovery. The binary outcomes of hearing recovery demonstrated similar relative ordering of interventions but were less sensitive than PTA improvement to capture the significant differences between interventions and placebo.
Unclear to high risk of bias trials rated IT plus systemic steroid treatment as the best among the six interventions compared, and all active treatments were better than placebo in improving PTA. However, it should be noted that certain comparisons were based on indirect evidence only or few studies of small sample size, and analyses were unable to control for steroid type and dosage. Given these limitations, further data originating from methodologically sound and rigorous trials with adequate reporting are needed to confirm our findings.
Systematic reviews are the cornerstone of evidence-based medicine. However, systematic reviews are time consuming and there is growing demand to produce evidence more quickly, while maintaining ...robust methods. In recent years, artificial intelligence and active-machine learning (AML) have been implemented into several SR software applications. As some of the barriers to adoption of new technologies are the challenges in set-up and how best to use these technologies, we have provided different situations and considerations for knowledge synthesis teams to consider when using artificial intelligence and AML for title and abstract screening.
We retrospectively evaluated the implementation and performance of AML across a set of ten historically completed systematic reviews. Based upon the findings from this work and in consideration of the barriers we have encountered and navigated during the past 24 months in using these tools prospectively in our research, we discussed and developed a series of practical recommendations for research teams to consider in seeking to implement AML tools for citation screening into their workflow.
We developed a seven-step framework and provide guidance for when and how to integrate artificial intelligence and AML into the title and abstract screening process. Steps include: (1) Consulting with Knowledge user/Expert Panel; (2) Developing the search strategy; (3) Preparing your review team; (4) Preparing your database; (5) Building the initial training set; (6) Ongoing screening; and (7) Truncating screening. During Step 6 and/or 7, you may also choose to optimize your team, by shifting some members to other review stages (e.g., full-text screening, data extraction).
Artificial intelligence and, more specifically, AML are well-developed tools for title and abstract screening and can be integrated into the screening process in several ways. Regardless of the method chosen, transparent reporting of these methods is critical for future studies evaluating artificial intelligence and AML.
Introduction One of the current challenges in long-term care homes (LTCH) is to identify the optimal model of care, which may include specialty physicians, nursing staff, person support workers, ...among others. There is currently no consensus on the complement or scope of care delivered by these providers, nor is there a repository of studies that evaluate the various models of care. We conducted a rapid scoping review to identify and map what care provider models and interventions in LTCH have been evaluated to improve quality of life, quality of care, and health outcomes of residents. Methods We conducted this review over 10-weeks of English language, peer-reviewed studies published from 2010 onward. Search strategies for databases (e.g., MEDLINE) were run on July 9, 2020. Studies that evaluated models of provider care (e.g., direct patient care), or interventions delivered to facility, staff, and residents of LTCH were included. Study selection was performed independently, in duplicate. Mapping was performed by two reviewers, and data were extracted by one reviewer, with partial verification by a second reviewer. Results A total of 7,574 citations were screened based on the title/abstract, 836 were reviewed at full text, and 366 studies were included. Studies were classified according to two main categories: healthcare service delivery (n = 92) and implementation strategies (n = 274). The condition/ focus of the intervention was used to further classify the interventions into subcategories. The complex nature of the interventions may have led to a study being classified in more than one category/subcategory. Conclusion Many healthcare service interventions have been evaluated in the literature in the last decade. Well represented interventions (e.g., dementia care, exercise/mobility, optimal/appropriate medication) may present opportunities for future systematic reviews. Areas with less research (e.g., hearing care, vision care, foot care) have the potential to have an impact on balance, falls, subsequent acute care hospitalization.
Positron emission tomography/magnetic resonance imaging (PET/MRI) potentially offers several advantages over positron emission tomography/computed tomography (PET/CT), for example, no CT radiation ...dose and soft tissue images from MR acquired at the same time as the PET. However, obtaining accurate linear attenuation correction (LAC) factors for the lung remains difficult in PET/MRI. LACs depend on electron density and in the lung, these vary significantly both within an individual and from person to person. Current commercial practice is to use a single‐valued population‐based lung LAC, and better estimation is needed to improve quantification. Given the under‐appreciation of lung attenuation estimation as an issue, the inaccuracy of PET quantification due to the use of single‐valued lung LACs, the unique challenges of lung estimation, and the emerging status of PET/MRI scanners in lung disease, a review is timely. This paper highlights past and present methods, categorizing them into segmentation, atlas/mapping, and emission‐based schemes. Potential strategies for future developments are also presented.
Characterization of the mesenchymal stromal cell (MSC) safety profile is important as this novel therapy continues to be evaluated in clinical trials for various inflammatory conditions. Due to an ...increase in published randomized controlled trials (RCTs) from 2012–2019, we performed an updated systematic review to further characterize the MSC safety profile.
MEDLINE, EMBASE, Cochrane Central Register of Controlled Trials and Web of Science (to May 2018) were searched. RCTs that compared intravascular delivery of MSCs to controls in adult populations were included. Pre-specified adverse events were grouped according to: (1) immediate, (2) infection, (3) thrombotic/embolic, and (4) longer-term events (mortality, malignancy). Adverse events were pooled and meta-analyzed by fitting inverse-variance binary random effects models. Primary and secondary clinical efficacy endpoints were summarized descriptively.
7473 citations were reviewed and 55 studies met inclusion criteria (n = 2696 patients). MSCs as compared to controls were associated with an increased risk of fever (Relative Risk (RR) = 2·48, 95% Confidence Interval (CI) = 1·27–4·86; I2 = 0%), but not non-fever acute infusional toxicity, infection, thrombotic/embolic events, death, or malignancy (RR = 1·16, 0·99, 1·14, 0·78, 0·93; 95% CI = 0·70–1·91, 0·81–1·21, 0·67–1·95, 0·65–0·94, 0·60–1·45; I2 = 0%, 0%, 0%, 0%, 0%). No included trials were ended prematurely due to safety concerns.
MSC therapy continues to exhibit a favourable safety profile. Future trials should continue to strengthen study rigor, reporting of MSC characterization, and adverse events.
Stem Cell Network, Ontario Institute for Regenerative Medicine and Ontario Research Fund
PET/CT quantification of lung tissue is limited by several difficulties: the lung density and local volume changes during respiration, the anatomical mismatch between PET and CT and the relative ...contributions of tissue, air and blood to the PET signal (the tissue fraction effect). Air fraction correction (AFC) has been shown to improve PET image quantification in the lungs. Methods to correct for the movement and anatomical mismatch involve respiratory gating and image registration techniques. While conventional registration methods only account for spatial mismatch, the Jacobian determinant of the deformable registration transformation field can be used to estimate local volume changes and could therefore potentially be used to correct (i.e. Jacobian Correction, JC) the PET signal for changes in concentration due to local volume changes. This work aims to investigate the relationship between variations in the lung due to respiration, specifically density, tracer concentration and local volume changes. In particular, we study the effect of AFC and JC on PET quantitation after registration of respiratory gated PET/CT patient data. Six patients suffering from lung cancer with solitary pulmonary nodules underwent Formula: see textF-FDG PET/cine-CT. The PET data were gated into six respiratory gates using displacement gating based on a real-time position management (RPM) signal and reconstructed with matched gated CT. The PET tracer concentration and tissue density were extracted from registered gated PET and CT images before and after corrections (AFC or JC) and compared to the values from the reference images. Before correction, we observed a linear correlation between the PET tracer concentration values and density. Across all gates and patients, the maximum relative change in PET tracer concentration before (after) AFC was found to be 16.2% (4.1%) and the maximum relative change in tissue density and PET tracer concentration before (after) JC was found to be 17.1% (5.5%) and 16.2% (6.8%) respectively. Overall our results show that both AFC or JC largely explain the observed changes in PET tracer activity over the respiratory cycle. We also speculate that a second order effect is related to change in fluid content but this needs further investigation. Consequently, either AFC or JC is recommended when combining lung PET images from different gates to reduce noise.
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