Oral self-care among dependent older New Zealanders.

OBJECTIVES: The objective of the study was to describe the occurrence and associations of oral self-care by dependent older New Zealanders. BACKGROUND: Dependent older adults who require some level of assisted daily care have been shown to have poorer oral health than their independent counterparts, yet national estimates are lacking. MATERIALS AND METHODS: A secondary analysis was conducted of data from New Zealand's 2012 Older People's Oral Health Survey, a national survey that interviewed and examined a representative sample of 2,218 dependent older adults living in aged residential care or receiving home-based care. Survey data were weighted for statistical analyses, and modelling was carried out using a modified Poisson approach. RESULTS: Overall, 59.5% (95% CI: 55.1, 63.7) of participants brushed their teeth twice a day, with this rate higher among women, Asians and those without cognitive or physical impairment. Cleaning interdentally at least once a week was less common than brushing, at 25.9% (95% CI: 21.5, 30.9), and that proportion was significantly lower among those with higher dependency or who were cognitively or physically impaired. Almost 9 in 10 (87.8%; 95% CI 83.1, 91.4) used fluoride toothpaste, and adults of high socio-economic status had lower rates of fluoride toothpaste use. Only 15.0% (95% CI 12.4, 18.0) used mouthwash, with this being most prevalent in Pasifika. More than half of those who wore dentures also wore them at night. CONCLUSION: Oral self-care was sub-optimal among dependent older New Zealanders. Improving the situation should be a high priority.

Evaluation of the Reliability and the Performance of Magnetic Resonance Imaging Radiomics in the Presence of Randomly Generated Irrelevant Features for Prostate Cancer.

Radiomics has the potential to aid prostate cancer (PC) diagnoses and prediction by analyzing and modeling quantitative features extracted from clinical imaging. However, its reliability has been a concern, possibly due to its high-dimensional nature. This study aims to quantitatively investigate the impact of randomly generated irrelevant features on MRI radiomics feature selection, modeling, and performance by progressively adding randomly generated features. Two multiparametric-MRI radiomics PC datasets were used (dataset 1 (n = 260), dataset 2 (n = 100)). The endpoint was to differentiate pathology-confirmed clinically significant (Gleason score (GS) ≥ 7) from insignificant (GS < 7) PC. Random features were generated at 12 levels with a 10% increment from 0% to 100% and an additional 5%. Three feature selection algorithms and two classifiers were used to build the models. The area under the curve and accuracy were used to evaluate the model's performance. Feature importance was calculated to assess features' contributions to the models. The metrics of each model were compared using an ANOVA test with a Bonferroni correction. A slight tendency to select more random features with the increasing number of random features introduced to the datasets was observed. However, the performance of the radiomics-built models was not significantly affected, which was partially due to the higher contribution of radiomics features toward the models compared to the random features. These reliability effects also vary among datasets. In conclusion, while the inclusion of additional random features may still slightly impact the performance of the feature selection, it may not have a substantial impact on the MRI radiomics model performance.

Determining the reliable feature change in longitudinal radiomics studies: A methodological approach using the reliable change index.

PURPOSE: Determination of reliable change of radiomics feature over time is essential and vital in delta-radiomics, but has not yet been rigorously examined. This study attempts to propose a methodological approach using reliable change index (RCI), a statistical metric to determine the reliability of quantitative biomarker changes by accounting for the baseline measurement standard error, in delta-radiomics. The use of RCI was demonstrated with the MRI data acquired from a group of prostate cancer (PCa) patients treated by 1.5 T MRI-guided radiotherapy (MRgRT). METHODS: Fifty consecutive PCa patients who underwent five-fractionated MRgRT were retrospectively included, and 1023 radiomics features were extracted from the clinical target volume (CTV) and planning target volume (PTV). The two MRI datasets acquired at the first fraction (MRI11 and MRI21) were used to calculate the baseline feature reliability against image acquisition using intraclass correlation coefficient (ICC). The RCI was constructed based on the baseline feature measurement standard deviation, ICC, and feature value differences at two time points between the fifth (MRI51) and the first fraction MRI (MRI11). The reliable change of features was determined in each patient only if the calculated RCI was over 1.96 or smaller than -1.96. The feature changes between MRI51 and MRI11 were correlated to two patient-reported quality-of-life clinical endpoints of urinary domain summary score (UDSS) and bowel domain summary score (BDSS) in 35 patients using the Spearman correlation test. Only the significant correlations between a feature that was reliably changed in ≥7 patients (20%) by RCI and an endpoint were considered as true significant correlations. RESULTS: The 352 (34.4%) and 386 (37.7%) features among all 1023 features were determined by RCI to be reliably changed in more than five (10%) patients in the CTV and PTV, respectively. Nineteen features were found reliably changed in the CTV and 31 features in the PTV, respectively, in 10 (20%) or more patients. These features were not necessarily associated with significantly different longitudinal feature values (group p-value < 0.05). Most reliably changed features in more than 10 patients had excellent or good baseline test-retest reliability ICC, while none showed poor reliability. The RCI method ruled out the features to be reliably changed when substantial feature measurement bias was presented. After applying the RCI criterion, only four and five true significant correlations were confirmed with UDSS and BDSS in the CTV, respectively, with low true significance correlation rates of 10.8% (4/37) and 17.9% (5/28). No true significant correlations were found in the PTV. CONCLUSIONS: The RCI method was proposed for delta-radiomics and demonstrated using PCa MRgRT data. The RCI has advantages over some other statistical metrics commonly used in the previous delta-radiomics studies, and is useful to reliably identify the longitudinal radiomics feature change on an individual basis. This proposed RCI method should be helpful for the development of essential feature selection methodology in delta-radiomics.

A pilot study of MRI radiomics for high-risk prostate cancer stratification in 1.5 T MR-guided radiotherapy.

PURPOSE: To investigate the potential value of MRI radiomics obtained from a 1.5 T MRI-guided linear accelerator (MR-LINAC) for D'Amico high-risk prostate cancer (PC) classification in MR-guided radiotherapy (MRgRT). METHODS: One hundred seventy-six consecutive PC patients underwent 1.5 T MRgRT treatment were retrospectively enrolled. Each patient received one or two pretreatment T2 -weighted MRI scans on a 1.5 T MR-LINAC. The endpoint was to differentiate high-risk from low/intermediate-risk PC based on D'Amico criteria using MRI-radiomics. Totally 1023 features were extracted from clinical target volume (CTV) and planning target volume (PTV). Intraclass correlation coefficient of scan-rescan repeatability, feature correlation, and recursive feature elimination were used for feature dimension reduction. Least absolute shrinkage and selection operator regression was employed for model construction. Receiver operating characteristic area under the curve (AUC) analysis was used for model performance assessment in both training and testing data. RESULTS: One hundred and eleven patients fulfilled all criteria were finally included: 76 for training and 35 for testing. The constructed MRI-radiomics models extracted from CTV and PTV achieved the AUC of 0.812 and 0.867 in the training data, without significant difference (P = 0.083). The model performances remained in the testing. The sensitivity, specificity, and accuracy were 85.71%, 64.29%, and 77.14% for the PTV-based model; and 71.43%, 71.43%, and 71.43% for the CTV-based model. The corresponding AUCs were 0.718 and 0.750 (P = 0.091) for CTV- and PTV-based models. CONCLUSION: MRI-radiomics obtained from a 1.5 T MR-LINAC showed promising results in D'Amico high-risk PC stratification, potentially helpful for the future PC MRgRT. Prospective studies with larger sample sizes and external validation are warranted for further verification.

Acquisition repeatability of MRI radiomics features in the head and neck: a dual-3D-sequence multi-scan study.

Radiomics has increasingly been investigated as a potential biomarker in quantitative imaging to facilitate personalized diagnosis and treatment of head and neck cancer (HNC), a group of malignancies associated with high heterogeneity. However, the feature reliability of radiomics is a major obstacle to its broad validity and generality in application to the highly heterogeneous head and neck (HN) tissues. In particular, feature repeatability of radiomics in magnetic resonance imaging (MRI) acquisition, which is considered a crucial confounding factor of radiomics feature reliability, is still sparsely investigated. This study prospectively investigated the acquisition repeatability of 93 MRI radiomics features in ten HN tissues of 15 healthy volunteers, aiming for potential magnetic resonance-guided radiotherapy (MRgRT) treatment of HNC. Each subject underwent four MRI acquisitions with MRgRT treatment position and immobilization using two pulse sequences of 3D T1-weighed turbo spin-echo and 3D T2-weighed turbo spin-echo on a 1.5 T MRI simulator. The repeatability of radiomics feature acquisition was evaluated in terms of the intraclass correlation coefficient (ICC), whereas within-subject acquisition variability was evaluated in terms of the coefficient of variation (CV). The results showed that MRI radiomics features exhibited heterogeneous acquisition variability and uncertainty dependent on feature types, tissues, and pulse sequences. Only a small fraction of features showed excellent acquisition repeatability (ICC > 0.9) and low within-subject variability. Multiple MRI scans improved the accuracy and confidence of the identification of reliable features concerning MRI acquisition compared to simple test-retest repeated scans. This study contributes to the literature on the reliability of radiomics features with respect to MRI acquisition and the selection of reliable radiomics features for use in modeling in future HNC MRgRT applications.

3D-T2W-TSE radiotherapy treatment planning MRI using compressed sensing acceleration for prostate cancer: Image quality and delineation value.

PURPOSE: To assess the image quality and delineation value of compressed sensing (CS)-accelerated 3D T2W turbo-spin-echo (TSE) sequence for radiotherapy treatment planning (RTP) of prostate cancer. METHODS: An optimized CS-accelerated 3D-T2W-TSE was determined by volunteer imaging and applied for clinical RTP-MRI. This optimized CS-accelerated planning MRI and the standardized adaptive MRI acquired at 1.5T were retrospectively analyzed in 26 prostate cancer patients who were to receive MR-guided radiotherapy. Signal-to-noise ratio (SNR) and relative contrast ratio (CR) were quantitatively assessed. Image quality and artifacts were qualitatively assessed using a five-point scale rating. Delineation value in the prostate and organs-at-risk (OARs) was also rated and compared. Wilcoxon signed-rank test was used for SNR, relative CR, and rating comparisons. The interobserver rating agreement was evaluated by percent agreement. RESULTS: Significantly better SNR and relative CR in the prostate, rectum, bowel, penis, and penile bulb, while significantly worse in the cauda equina, were observed on the planning MRI. Significantly better ratings of image quality and artifacts were given to the planning MRI, with much less Gibbs ringing and reconstruction artifacts. Significantly better delineation value rating was achieved on the planning MRI in the prostate, seminal vesicle, rectum, penis, penile bulb, and testes, while significantly worse in the cauda equina. A strong to almost perfect interobserver rating agreement was obtained. CONCLUSION: This study suggested that CS acceleration is applicable and valuable in prostate RTP-MRI. CS-accelerated 3D-T2W-TSE images should benefit the delineation of prostate and many OARs.

3D T1-weighted turbo spin echo contrast-enhanced MRI at 1.5 T for frameless brain metastases radiotherapy.

PURPOSE: Performance of 3D-T1W-TSE has been proven superior to 3D-MP-GRE at 3 T on brain metastases (BM) contrast-enhanced (CE) MRI. However, its performance at 1.5 T is largely unknown and sparsely reported. This study aims to assess image quality, lesion detectability and conspicuity of 1.5 T 3D-T1W-TSE on planning MRI of frameless BM radiotherapy. METHODS: 94 BM patients to be treated by frameless brain radiotherapy were scanned using 3D-T1W-TSE with immobilization on multi-vendor 1.5 T MRI-simulators. BMs were jointly diagnosed by 4 reviewers. Enhanced lesion conspicuity was quantitatively assessed by calculating contrast ratio (CR) and contrast-to-noise ratio (CNR). Signal-to-noise ratio (SNR) reduction of white matter due to the use of flexible coil was assessed. Lesion detectability and conspicuity were compared between 1.5 T planning MRI and 3 T diagnostic MRI by an oncologist and a radiologist in 10 patients. RESULTS: 497 BMs were jointly diagnosed. The CR and CNR were 75.2 ± 39.9% and 14.2 ± 8.1, respectively. SNR reduced considerably from 31.7 ± 8.3 to 21.9 ± 5.4 with the longer distance to coils. 3 T diagnostic MRI and 1.5 T planning MRI yielded exactly the same detection of 84 BMs. Qualitatively, lesion conspicuity at 1.5 T was not inferior to that at 3 T. Quantitatively, lower brain SNR and lesion CNR were found at 1.5 T, while lesion CR at 1.5 T was highly comparable to that at 3 T. CONCLUSION: 1.5 T 3D-T1W-TSE planning MRI of frameless BM radiotherapy was comprehensively assessed. Highly comparable BM detectability and conspicuity were achieved by 1.5 T planning MRI compared to 3 T diagnostic MRI. 1.5 T 3D-T1W-TSE should be valuable for frameless brain radiotherapy planning.

Radiomics feature reliability assessed by intraclass correlation coefficient: a systematic review.

Radiomics research is rapidly growing in recent years, but more concerns on radiomics reliability are also raised. This review attempts to update and overview the current status of radiomics reliability research in the ever expanding medical literature from the perspective of a single reliability metric of intraclass correlation coefficient (ICC). To conduct this systematic review, Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed. After literature search and selection, a total of 481 radiomics studies using CT, PET, or MRI, covering a wide range of subject and disease types, were included for review. In these highly heterogeneous studies, feature reliability to image segmentation was much more investigated than reliability to other factors, such as image acquisition, reconstruction, post-processing, and feature quantification. The reported ICCs also suggested high radiomics feature reliability to image segmentation. Image acquisition was found to introduce much more feature variability than image segmentation, in particular for MRI, based on the reported ICC values. Image post-processing and feature quantification yielded different levels of radiomics reliability and might be used to mitigate image acquisition-induced variability. Some common flaws and pitfalls in ICC use were identified, and suggestions on better ICC use were given. Due to the extremely high study heterogeneities and possible risks of bias, the degree of radiomics feature reliability that has been achieved could not yet be safely synthesized or derived in this review. More future researches on radiomics reliability are warranted.

Reliability of MRI radiomics features in MR-guided radiotherapy for prostate cancer: Repeatability, reproducibility, and within-subject agreement.

PURPOSE: The MR-guided radiotherapy (MRgRT) images on the integrated MRI and linear accelerator (MR-LINAC) might facilitate radiomics analysis for longitudinal treatment response assessment. However, the reliability of MRgRT radiomics features is largely unknown. This study aims to investigate MRgRT radiomics feature reliability acquired using a standardized 3D-T2W-TSE sequence in terms of repeatability, reproducibility, and within-subject feature agreement on a 1.5T MR-simulator and a 1.5T MR-LINAC for prostate cancer (PC). METHODS: Twenty-six consecutive PC patients who underwent one MRI-simulator scan and two MR-LINAC scans before dose delivery were retrospectively included. The three MRI datasets were rigidly co-registered. 1023 first-order and texture radiomics features were extracted with different intensity bin widths for each scan in the manually segmented clinical target volume (CTV) and planning target volume (PTV) by an experienced radiation oncologist. Intraclass correlation coefficient (ICC) was used to evaluate feature repeatability between MR-LINAC scans and reproducibility between MRI-simulator and MR-LINAC scans. The within-subject feature value agreements were evaluated using Bland-Altman analysis. The impact of inter-observer segmentation on the radiomics feature reliability was also examined based on the second manual segmentation of CTV and PTV by an MRI researcher. RESULTS: Based on the segmentation by the radiation oncologist and the default bin width of 25, 9.6%, 24.1%, 49.6%, and 16.8% of the total 1023 features exhibited excellent (ICC > 0.9), good (0.9 > ICC > 0.75), moderate (0.75 > ICC > 0.5), and poor (ICC < 0.5) repeatability in the CTV, and 9.2%, 26.8%, 50.5%, and 13.5% in the PTV, respectively. For reproducibility, the corresponding feature percentages were 8.9%, 19.7%, 41.9%, and 29.6% in the CTV, and 8.4%, 17.8%, 47.9%, and 26% in the PTV. Feature reliability was not notably influenced by intensity bin width for discretization. BA analysis revealed wide 95% limit-of-agreements and substantial biases of feature values between CTV and PTV and between any two MRI scans. The features even with excellent ICC were still subjected to considerable inter-scan feature variations in each individual subject. The analysis on the second segmentation by the MRI researcher showed insignificantly different feature repeatability and reproducibility in terms of ICC values. CONCLUSIONS: Only a small proportion of features exhibited excellent/good repeatability and reproducibility, highlighting the importance of reliable MRgRT feature selection. The within-subject feature values were subjected to considerable inter-scan variations, imposing a challenge on the determination of the smallest detectable change in future MRgRT delta-radiomics studies.

Quantitative assessment of acquisition imaging parameters on MRI radiomics features: a prospective anthropomorphic phantom study using a 3D-T2W-TSE sequence for MR-guided-radiotherapy.

BACKGROUND: MRI pulse sequences and imaging parameters substantially influence the variation of MRI radiomics features, thus impose a critical challenge on MRI radiomics reproducibility and reliability. This study aims to prospectively investigate the impact of various imaging parameters on MRI radiomics features in a 3D T2-weighted (T2W) turbo-spin-echo (TSE) pulse sequence for MR-guided-radiotherapy (MRgRT). METHODS: An anthropomorphic phantom was scanned using a 3D-T2W-TSE MRgRT sequence at 1.5T under a variety of acquisition imaging parameter changes. T1 and T2 relaxation times of the phantom were also measured. 93 first-order and texture radiomics features in the original and 14 transformed images, yielding 1,395 features in total, were extracted from 10 volumes-of-interest (VOIs). The percentage deviation (d%) of radiomics feature values from the baseline values and intra-class correlation coefficient (ICC) with the baseline were calculated. Robust radiomics features were identified based on the excellent agreement of radiomics feature values with the baseline, i.e., the averaged d% <5% and ICC >0.90 in all VOIs for all imaging parameter variations. RESULTS: The radiomics feature values changed considerably but to different degrees with different imaging parameter adjustments, in the ten VOIs. The deviation d% ranged from 0.02% to 321.3%, with a mean of 12.5% averaged for all original features in all ten VOIs. First-order and GLCM features were generally more robust to imaging parameters than other features in the original images. There were also significantly different radiomics feature values (ANOVA, P<0.001) between the original and the transformed images, exhibiting quite different robustness to imaging parameters. 330 out of 1395 features (23.7%) robust to imaging parameters were identified. GLCM and GLSZM features had the most (42.5%, 153/360) and least (3.8%, 9/240) robust features in the original and transformed images, respectively. CONCLUSIONS: This study helps better understand the quantitative dependence of radiomics feature values on imaging parameters in a 3D-T2W-TSE sequence for MRgRT. Imaging parameter heterogeneity should be considered as a significant source of radiomics variability and uncertainty, which must be well harmonized for reliable clinical use. The identified robust features to imaging parameters are helpful for the pre-selection of radiomics features for reliable radiomics modeling.

Emergency physician perspectives on initiating buprenorphine/naloxone in the emergency department: A qualitative study.

OBJECTIVES: The objective of this study was to examine the perspectives of Canadian emergency physicians on the care of patients with opioid use disorders in the emergency department (ED), in particular the real-world facilitators to prescribing buprenorphine/naloxone (BUP) in the ED. METHODS: We conducted semistructured qualitative interviews using a multi-site-focused ethnographic design. Purposive sampling via an existing national research network was used to recruit ED physicians. Interviews were conducted by phone using an interview guide and continued until theoretical data saturation was reached. Interviews were transcribed and analyzed using latent content analysis. Interviews took place between June 21, 2019, and February 11, 2020. RESULTS: A total of 32 physicians were included in the analysis. Participants had a median of 10 years of experience, and most (29/32) worked in urban settings. Clinical care of patients with opioid use disorder was found to be variable and physician dependent. Although some physicians reported routinely prescribing BUP, others felt that this was outside the clinical scope of emergency medicine. Access to clinical pathways, incentivized training, dedicated human resources, and follow-up care were identified as critical facilitators for supporting BUP prescribing. Participants also identified a shared responsibility between patients and the ED, including the importance of a patient-centered approach that enhanced patient autonomy. ED BUP prescribing became self-reinforcing over time. CONCLUSIONS: Although there remains practice variability among Canadian emergency physicians, successful implementation of ED BUP prescribing has occurred in some locations. Jurisdictions wanting to facilitate BUP uptake should consider providing incentivized training, treatment protocols, dedicated human resources, and streamlined access to follow-up care.

Reliability of radiomics features due to image reconstruction using a standardized T2 -weighted pulse sequence for MR-guided radiotherapy: An anthropomorphic phantom study.

PURPOSE: To prospectively investigate the impact of image reconstruction on MRI radiomics features. METHODS: An anthropomorphic phantom was scanned at 1.5 T using a standardized sequence for MR-guided radiotherapy under SENSE and compressed-SENSE reconstruction settings. A total of 93 first-order and texture radiomics features in 10 volumes of interest were assessed based on (1) accuracy measured by the percentage deviation from the reference, (2) robustness on reconstruction in all volumes of interest measured by the intraclass correlation coefficient, and (3) repeatability measured by the coefficient of variance over the repetitive acquisitions. Finally, reliable and unreliable radiomics features were comprehensively determined based on their accuracy, robustness, and repeatability. RESULTS: Better accuracy and robustness of the radiomics features were achieved under SENSE than compressed-SENSE reconstruction. The feature accuracy under SENSE reconstruction was more affected by acceleration factor than direction, whereas under compressed-SENSE reconstruction, accuracy was substantially impacted by the increasing denoising levels. Feature repeatability was dependent more on feature types than on reconstruction. A total of 45 reliable features and 13 unreliable features were finally determined for SENSE, compared with 22 reliable and 26 unreliable features for compressed SENSE. First-order and gray-level co-occurrence matrix features were generally more reliable than other features. CONCLUSION: Radiomics features could be substantially affected by MRI reconstruction, so precautions need to be taken regarding their reliability for clinical use. This study helps the guidance of the preselection of reliable radiomics features and the preclusion of unreliable features in MR-guided radiotherapy.

Extracting extensor digitorum communis activation patterns using high-density surface electromyography.

The extensor digitorum communis muscle plays an important role in hand dexterity during object manipulations. This multi-tendinous muscle is believed to be controlled through separate motoneuron pools, thereby forming different compartments that control individual digits. However, due to the complex anatomical variations across individuals and the flexibility of neural control strategies, the spatial activation patterns of the extensor digitorum communis compartments during individual finger extension have not been fully tracked under different task conditions. The objective of this study was to quantify the global spatial activation patterns of the extensor digitorum communis using high-density (7 × 9) surface electromyogram (EMG) recordings. The muscle activation map (based on the root mean square of the EMG) was constructed when subjects performed individual four finger extensions at the metacarpophalangeal joint, at different effort levels and under different finger constraints (static and dynamic). Our results revealed distinct activation patterns during individual finger extensions, especially between index and middle finger extensions, although the activation between ring and little finger extensions showed strong covariance. The activation map was relatively consistent at different muscle contraction levels and for different finger constraint conditions. We also found that distinct activation patterns were more discernible in the proximal-distal direction than in the radial-ulnar direction. The global spatial activation map utilizing surface grid EMG of the extensor digitorum communis muscle provides information for localizing individual compartments of the extensor muscle during finger extensions. This is of potential value for identifying more selective control input for assistive devices. Such information can also provide a basis for understanding hand impairment in individuals with neural disorders.