Quantitative 3D imaging parameters improve prediction of hip osteoarthritis outcome.
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ABSTRACT:
SUBMITTER: Turmezei TD
PROVIDER: S-EPMC7058047 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:To assess the relationship between proximal femoral cortical bone thickness and radiological hip osteoarthritis using quantitative 3D analysis of clinical computed tomography (CT) data.Image analysis was performed on clinical CT imaging data from 203 female volunteers with a technique called cortical bone mapping (CBM). Colour thickness maps were created for each proximal femur. Statistical parametric mapping was performed to identify statistically significant differences in cortical bone thickness that corresponded with the severity of radiological hip osteoarthritis. Kellgren and Lawrence (K&L) grade, minimum joint space width (JSW) and a novel CT-based osteophyte score were also blindly assessed from the CT data.For each increase in K&L grade, cortical thickness increased by up to 25 % in distinct areas of the superolateral femoral head-neck junction and superior subchondral bone plate. For increasing severity of CT osteophytes, the increase in cortical thickness was more circumferential, involving a wider portion of the head-neck junction, with up to a 7 % increase in cortical thickness per increment in score. Results were not significant for minimum JSW.These findings indicate that quantitative 3D analysis of the proximal femur can identify changes in cortical bone thickness relevant to structural hip osteoarthritis.• CT is being increasingly used to assess bony involvement in osteoarthritis • CBM provides accurate and reliable quantitative analysis of cortical bone thickness • Cortical bone is thicker at the superior femoral head-neck with worse osteoarthritis • Regions of increased thickness co-locate with impingement and osteophyte formation • Quantitative 3D bone analysis could enable clinical disease prediction and therapy development.
| S-EPMC4902845 | biostudies-other
Project description:The aim of this work is to apply an integrated systems approach to understand the biological underpinnings of hip osteoarthritis that culminates in the need for total joint replacement (TJR). This study is a feasibility pilot that integrates functional genomics data from diseased and non-diseased tissues of OA patients who have undergone TJR. For each tissue, we characterised epigenetic marks (methylation), gene transcription (RNASeq) and expression (quantitative proteomics). We also generated genotype data on the HumanCoreExome array for each individual. This data is part of a pre-publication release.
2018-05-14 | PXD006673 | Pride
Project description:BACKGROUND:The Hip disability and Osteoarthritis Outcome Score (HOOS) is a frequently used patient-reported outcome measure (PROM) for assessment of hip disorders and treatment effects following hip surgery. The objective of the study was to translate and adapt the Hip disability and Osteoarthritis Outcome Score (HOOS) into Polish and to investigate the psychometric properties of the HOOS in patients with osteoarthritis undergoing total hip replacement (THR). MATERIALS AND METHODS:The Polish version of the HOOS was developed according to current guidelines. Patients completed the HOOS, Short Form 36 Health Survey (SF-36), the visual analogue scale (VAS) for pain and the global perceived effect (GPE) scale. Psychometric properties including interpretability (floor/ceiling effects), internal consistency (Cronbach's alpha), test-retest reliability (intra-class correlation coefficient, ICC), convergent construct validity (a priori hypothesized Spearman's correlations between the HOOS subscales, the generic SF-36 measure and the VAS for pain) and responsiveness (effect size, association between the HOOS and GPE scores) were analyzed. RESULTS:The study included 157 patients (mean age 66.8?years, 54% women). Floor effects were found prior to THR for the HOOS subscales Sports and Recreation and Quality of Life. The Cronbach's alpha was over 0.7 for all subscales indicating satisfactory internal consistency. The test-retest reliability was good for the HOOS subscale Pain (0.82) and excellent for all other subscales with ICCs ranging from 0.91 to 0.96. The minimal detectable change ranged from 12.0 to 26.2 on an individual level and from 1.4 to 3.0 on a group level. Seven out of eight a priori hypotheses were confirmed indicating good construct validity. Responsiveness was high since the expected pattern of effect sizes in all subscales was found. CONCLUSIONS:The Polish version of the HOOS demonstrated good reliability, validity and responsiveness for use in patient groups having THR.
| S-EPMC7216355 | biostudies-literature
Project description:Hip arthroscopy has continued to expand its horizons in treating many conditions other than femoroacetabular impingement (FAI). However, the results of hip arthroscopy are known to be poor if the degree of articular cartilage damage is significant. We wanted to assess, whether the procedure might have a role in the management of young and active patients with advanced osteoarthritis (OA) and whether it should be offered as a treatment modality. 77 consecutive patients with Tönnis grade 2 and 3 osteoarthritis of the hip who had undergone hip arthroscopy were included in the study. Patients' medical notes, plain radiographs and outcome scores (modified Harris hip score (mHHS), non-arthritic hip score (NAHS)) preoperatively and postoperatively at six weeks, six months, one year and annually thereafter, were analysed. 77 patients consisted of 63 men and 14 women with mean follow-up of 2.8 years (2.2 to 4.2) and mean age at surgery of 43 years (19 to 64). The mean preoperative mHHS and NAHS scores were 58 (28 to 87) and 64 (27 to 93) respectively. The mean improvements in both the mHHS and NAHS scores were significant (p = 0.003 and p = 0.0001 for mHHS at one and two years, p = 0.002 and p = 0.0003 for NAHS at one and two years, respectively). There were 34 patients (44%) who required a total hip replacement at mean of 18 months (6 to 48) after hip arthroscopy. We conclude that hip arthroscopy improves outcome scores in 56% of patients with severe OA of the hip (Tönnis grade 2 and 3) for at least two years after surgery. We thus consider the procedure to be a reasonable option for patients with hip OA, although success of the procedure will be less than if undertaken for certain other conditions.
| S-EPMC4312088 | biostudies-other
Project description:Amplified MRI (aMRI) is a promising new technique that can visualize pulsatile brain tissue motion by amplifying sub-voxel motion in cine MRI data, but it lacks the ability to quantify the sub-voxel motion field in physical units. Here, we introduce a novel post-processing algorithm called 3D quantitative amplified MRI (3D q-aMRI). This algorithm enables the visualization and quantification of pulsatile brain motion. 3D q-aMRI was validated and optimized on a 3D digital phantom and was applied in vivo on healthy volunteers for its ability to accurately measure brain parenchyma and CSF voxel displacement. Simulation results show that 3D q-aMRI can accurately quantify sub-voxel motions in the order of 0.01 of a voxel size. The algorithm hyperparameters were optimized and tested on in vivo data. The repeatability and reproducibility of 3D q-aMRI were shown on six healthy volunteers. The voxel displacement field extracted by 3D q-aMRI is highly correlated with the displacement measurements estimated by phase contrast (PC) MRI. In addition, the voxel displacement profile through the cerebral aqueduct resembled the CSF flow profile reported in previous literature. Differences in brain motion was observed in patients with dementia compared with age-matched healthy controls. In summary, 3D q-aMRI is a promising new technique that can both visualize and quantify pulsatile brain motion. Its ability to accurately quantify sub-voxel motion in physical units holds potential for the assessment of pulsatile brain motion as well as the indirect assessment of CSF homeostasis. While further research is warranted, 3D q-aMRI may provide important diagnostic information for neurological disorders such as Alzheimer's disease.
| S-EPMC11352018 | biostudies-literature
Project description:IntroductionMalignant cerebral edema develops in a small subset of patients with hemispheric strokes, precipitating deterioration and death if decompressive hemicraniectomy (DHC) is not performed in a timely manner. Predicting which stroke patients will develop malignant edema is imprecise based on clinical data alone. Head computed tomography (CT) imaging is often performed at baseline and 24-h. We determined the incremental value of incorporating imaging-derived features from serial CTs to enhance prediction of malignant edema.MethodsWe identified hemispheric stroke patients at three sites with NIHSS ≥ 7 who had baseline as well as 24-h clinical and CT imaging data. We extracted quantitative imaging features from baseline and follow-up CTs, including CSF volume, intracranial reserve (CSF/cranial volume), as well as midline shift (MLS) and infarct-related hypodensity volume. Potentially lethal malignant edema was defined as requiring DHC or dying with MLS over 5-mm. We built machine-learning models using logistic regression first with baseline data and then adding 24-h data including reduction in CSF volume (ΔCSF). Model performance was evaluated with cross-validation using metrics of recall (sensitivity), precision (predictive value), as well as area under receiver-operating-characteristic and precision-recall curves (AUROC, AUPRC).ResultsTwenty of 361 patients (6%) died or underwent DHC. Baseline clinical variables alone had recall of 60% with low precision (7%), AUROC 0.59, AUPRC 0.15. Adding baseline intracranial reserve improved recall to 80% and AUROC to 0.82 but precision remained only 16% (AUPRC 0.28). Incorporating ΔCSF improved AUPRC to 0.53 (AUROC 0.91) while all imaging features further improved prediction (recall 90%, precision 38%, AUROC 0.96, AUPRC 0.66).ConclusionIncorporating quantitative CT-based imaging features from baseline and 24-h CT enhances identification of patients with malignant edema needing DHC. Further refinements and external validation of such imaging-based machine-learning models are required.
| S-EPMC7738418 | biostudies-literature
Project description:In total, 70 samples on macroscopically preserved and lesioned OA cartilage from the same patient was taken for RNA-seq. Subsequently, paired-end 2×100 bp RNA library sequencing (Illumina TruSeq RNA Library Prep Kit, Illumina HiSeq 2000 and TruSeq Stranded Total RNA LT Sample Prep Kit, Illumina HiSeq 4000) was performed.
2019-01-07 | E-MTAB-7313 | biostudies-arrayexpress
Project description:Several neurobiological factors have been found to correlate with functional recovery after brain lesions. However, predicting the individual potential of recovery remains difficult. Here we used multivariate support vector machine (SVM) classification to explore the prognostic value of functional magnetic resonance imaging (fMRI) to predict individual motor outcome at 4-6 months post-stroke. To this end, 21 first-ever stroke patients with hand motor deficits participated in an fMRI hand motor task in the first few days post-stroke. Motor impairment was quantified assessing grip force and the Action Research Arm Test. Linear SVM classifiers were trained to predict good versus poor motor outcome of unseen new patients. We found that fMRI activity acquired in the first week post-stroke correctly predicted the outcome for 86% of all patients. In contrast, the concurrent assessment of motor function provided 76% accuracy with low sensitivity (<60%). Furthermore, the outcome of patients with initially moderate impairment and high outcome variability could not be predicted based on motor tests. In contrast, fMRI provided 87.5% prediction accuracy in these patients. Classifications were driven by activity in ipsilesional motor areas and contralesional cerebellum. The accuracy of subacute fMRI data (two weeks post-stroke), age, time post-stroke, lesion volume, and location were at 50%-chance-level. In conclusion, multivariate decoding of fMRI data with SVM early after stroke enables a robust prediction of motor recovery. The potential for recovery is influenced by the initial dysfunction of the active motor system, particularly in those patients whose outcome cannot be predicted by behavioral tests.
| S-EPMC4619153 | biostudies-literature
Project description:(1) Background: Respiratory insufficiency with acute respiratory distress syndrome (ARDS) and multi-organ dysfunction leads to high mortality in COVID-19 patients. In times of limited intensive care unit (ICU) resources, chest CTs became an important tool for the assessment of lung involvement and for patient triage despite uncertainties about the predictive diagnostic value. This study evaluated chest CT-based imaging parameters for their potential to predict in-hospital mortality compared to clinical scores. (2) Methods: 89 COVID-19 ICU ARDS patients requiring mechanical ventilation or continuous positive airway pressure mask ventilation were included in this single center retrospective study. AI-based lung injury assessment and measurements indicating pulmonary hypertension (PA-to-AA ratio) on admission CT, oxygenation indices, lung compliance and sequential organ failure assessment (SOFA) scores on ICU admission were assessed for their diagnostic performance to predict in-hospital mortality. (3) Results: CT severity scores and PA-to-AA ratios were not significantly associated with in-hospital mortality, whereas the SOFA score showed a significant association (p < 0.001). In ROC analysis, the SOFA score resulted in an area under the curve (AUC) for in-hospital mortality of 0.74 (95%-CI 0.63-0.85), whereas CT severity scores (0.53, 95%-CI 0.40-0.67) and PA-to-AA ratios (0.46, 95%-CI 0.34-0.58) did not yield sufficient AUCs. These results were consistent for the subgroup of more critically ill patients with moderate and severe ARDS on admission (oxygenation index <200, n = 53) with an AUC for SOFA score of 0.77 (95%-CI 0.64-0.89), compared to 0.55 (95%-CI 0.39-0.72) for CT severity scores and 0.51 (95%-CI 0.35-0.67) for PA-to-AA ratios. (4) Conclusions: Severe COVID-19 disease is not limited to lung (vessel) injury but leads to a multi-organ involvement. The findings of this study suggest that risk stratification should not solely be based on chest CT parameters but needs to include multi-organ failure assessment for COVID-19 ICU ARDS patients for optimized future patient management and resource allocation.
| S-EPMC8775048 | biostudies-literature
Project description:We aimed to determine the characteristics of quantitative pupillary response parameters other than amplitude of pupillary light reflex (PLR) early after return of spontaneous circulation (ROSC) and their implications for predicting neurological outcomes early after cardiac arrest (CA). Fifty adults resuscitated after non-traumatic out-of-hospital CA from four emergency hospitals were enrolled. Pupil diameters, PLR, constriction velocity (CV), maximum CV (MCV), dilation velocity (DV), latency of constriction, and Neurological Pupil index (NPi) were quantitatively measured at 0, 6, 12, 24, 48, and 72 h post-ROSC using an automated pupillometer. Change over time of each parameter was compared between favorable (Cerebral Performance Category [CPC] 1 or 2) and unfavorable neurological outcome (CPC 3-5) groups. Prognostic values of 90-day favorable outcome by these parameters and when combined with clinical predictors (witness status, bystander cardiopulmonary resuscitation, initial shockable rhythm, implementation of target temperature management) were tested. Thirteen patients achieved favorable outcome. CV, MCV, DV (P < 0.001), and NPi (P = 0.005) were consistently greater in the favorable group than in the unfavorable outcome group. Change over time was not statistically different between the groups in all parameters. CV, MCV, DV (ρ = 0.96 to 0.97, P < 0.001, respectively), and NPi (ρ = 0.65, P < 0.001) positively correlated with PLR. The prognostic value of 0-hour CV (area under the curve, AUC [95% confidence interval]: 0.92 [0.80-1.00]), DV (0.84 [0.68-0.99]), and NPi (0.88 [0.74-1.00]) was equivalent to that of PLR (0.84 [0.69-0.98]). Prognostic values improved to AUC of 0.95-0.96 when 0-hour PLR, CV, DV, or NPi was combined with clinical predictors. The 0-hour CV, MCV, and NPi showed equivalent prognostic values to PLR alone/in combination with clinical predictors. Using PLR among several quantitative pupillary response parameters for early neurological prognostication of post-CA patients is a simple and effective strategy.
| S-EPMC7082023 | biostudies-literature