Dataset Information

Comparison of Diagnostic Performance of Semi-Quantitative Knee Ultrasound and Knee Radiography with MRI: Oulu Knee Osteoarthritis Study.

ABSTRACT: Osteoarthritis (OA) is a common degenerative musculoskeletal disease highly prevalent in aging societies worldwide. Traditionally, knee OA is diagnosed using conventional radiography. However, structural changes of articular cartilage or menisci cannot be directly evaluated using this method. On the other hand, ultrasound is a promising tool able to provide direct information on soft tissue degeneration. The aim of our study was to systematically determine the site-specific diagnostic performance of semi-quantitative ultrasound grading of knee femoral articular cartilage, osteophytes and meniscal extrusion, and of radiographic assessment of joint space narrowing and osteophytes, using MRI as a reference standard. Eighty asymptomatic and 79 symptomatic subjects with mean age of 57.7 years were included in the study. Ultrasound performed best in the assessment of femoral medial and lateral osteophytes, and medial meniscal extrusion. In comparison to radiography, ultrasound performed better or at least equally well in identification of tibio-femoral osteophytes, medial meniscal extrusion and medial femoral cartilage morphological degeneration. Ultrasound provides relevant additional diagnostic information on tissue-specific morphological changes not depicted by conventional radiography. Consequently, the use of ultrasound as a complementary imaging tool along with radiography may enable more accurate and cost-effective diagnostics of knee osteoarthritis at the primary healthcare level.

SUBMITTER: Podlipska J

PROVIDER: S-EPMC4772126 | biostudies-literature | 2016 Mar

REPOSITORIES: biostudies-literature

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Comparison of Diagnostic Performance of Semi-Quantitative Knee Ultrasound and Knee Radiography with MRI: Oulu Knee Osteoarthritis Study.

Podlipská Jana J Guermazi Ali A Lehenkari Petri P Niinimäki Jaakko J Roemer Frank W FW Arokoski Jari P JP Kaukinen Päivi P Liukkonen Esa E Lammentausta Eveliina E Nieminen Miika T MT Tervonen Osmo O Koski Juhani M JM Saarakkala Simo S

Scientific reports 20160301

Osteoarthritis (OA) is a common degenerative musculoskeletal disease highly prevalent in aging societies worldwide. Traditionally, knee OA is diagnosed using conventional radiography. However, structural changes of articular cartilage or menisci cannot be directly evaluated using this method. On the other hand, ultrasound is a promising tool able to provide direct information on soft tissue degeneration. The aim of our study was to systematically determine the site-specific diagnostic performanc ...[more]

PMID: 26926836

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Project description:BackgroundThe IMI-APPROACH cohort is an exploratory, 5-centre, 2-year prospective follow-up study of knee osteoarthritis (OA). Aim was to describe baseline multi-tissue semiquantitative MRI evaluation of index knees and to describe change for different MRI features based on number of subregion-approaches and change in maximum grades over a 24-month period.MethodsMRIs were acquired using 1.5 T or 3 T MRI systems and assessed using the semi-quantitative MRI OA Knee Scoring (MOAKS) system. MRIs were read at baseline and 24-months for cartilage damage, bone marrow lesions (BML), osteophytes, meniscal damage and extrusion, and Hoffa- and effusion-synovitis. In descriptive fashion, the frequencies of MRI features at baseline and change in these imaging biomarkers over time are presented for the entire sample in a subregional and maximum score approach for most features. Differences between knees without and with structural radiographic (R) OA are analyzed in addition.ResultsTwo hundred eighty-nine participants had readable baseline MRI examinations. Mean age was 66.6 ± 7.1 years and participants had a mean BMI of 28.1 ± 5.3 kg/m2. The majority (55.3%) of included knees had radiographic OA. Any change in total cartilage MOAKS score was observed in 53.1% considering full-grade changes only, and in 73.9% including full-grade and within-grade changes. Any medial cartilage progression was seen in 23.9% and any lateral progression on 22.1%. While for the medial and lateral compartments numbers of subregions with improvement and worsening of BMLs were very similar, for the PFJ more improvement was observed compared to worsening (15.5% vs. 9.0%). Including within grade changes, the number of knees showing BML worsening increased from 42.2% to 55.6%. While for some features 24-months change was rare, frequency of change was much more common in knees with vs. without ROA (e.g. worsening of total MOAKS score cartilage in 68.4% of ROA knees vs. 36.7% of no-ROA knees, and 60.7% vs. 21.8% for an increase in maximum BML score per knee).ConclusionsA wide range of MRI-detected structural pathologies was present in the IMI-APPROACH cohort. Baseline prevalence and change of features was substantially more common in the ROA subgroup compared to the knees without ROA.Trial registrationClinicaltrials.gov identification: NCT03883568.

Project description:BACKGROUND. Potential approaches for abbreviated knee MRI, including prospective acceleration with deep learning, have achieved limited clinical implementation. OBJECTIVE. The objective of this study was to evaluate the interreader agreement between conventional knee MRI and a 5-minute 3D quantitative double-echo steady-state (qDESS) sequence with automatic T2 mapping and deep learning super-resolutionaugmentation and to compare the diagnostic performance of the two methods regarding findings from arthroscopic surgery. METHODS. Fifty-one patients with knee pain underwent knee MRI that included an additional 3D qDESS sequence with automatic T2 mapping. Fourier interpolation was followed by prospective deep learning super resolution to enhance qDESS slice resolution twofold. A musculoskeletal radiologist and a radiology resident performed independent retrospective evaluations of articular cartilage, menisci, ligaments, bones, extensor mechanism, and synovium using conventional MRI. Following a 2-month washout period, readers reviewed qDESS images alone followed by qDESS with the automatic T2 maps. Interreader agreement between conventional MRI and qDESS was computed using percentage agreement and Cohen kappa. The sensitivity and specificity of conventional MRI, qDESS alone, and qDESS plus T2 mapping were compared with arthroscopic findings using exact McNemar tests. RESULTS. Conventional MRI and qDESS showed 92% agreement in evaluating all tissues. Kappa was 0.79 (95% CI, 0.76-0.81) across all imaging findings. In 43 patients who underwent arthroscopy, sensitivity and specificity were not significantly different (p = .23 to > .99) between conventional MRI (sensitivity, 58-93%; specificity, 27-87%) and qDESS alone (sensitivity, 54-90%; specificity, 23-91%) for cartilage, menisci, ligaments, and synovium. For grade 1 cartilage lesions, sensitivity and specificity were 33% and 56%, respectively, for conventional MRI; 23% and 53% for qDESS (p = .81); and 46% and 39% for qDESS with T2 mapping (p = .80). For grade 2A lesions, values were 27% and 53% for conventional MRI, 26% and 52% for qDESS (p = .02), and 58% and 40% for qDESS with T2 mapping (p < .001). CONCLUSION. The qDESS method prospectively augmented with deep learning showed strong interreader agreement with conventional knee MRI and near-equivalent diagnostic performance regarding arthroscopy. The ability of qDESS to automatically generate T2 maps increases sensitivity for cartilage abnormalities. CLINICAL IMPACT. Using prospective artificial intelligence to enhance qDESS image quality may facilitate an abbreviated knee MRI protocol while generating quantitative T2 maps.

Project description:ObjectiveThe chest X-ray (CXR) is the most readily available and common imaging modality for the assessment of pneumonia. However, detecting pneumonia from chest radiography is a challenging task, even for experienced radiologists. An artificial intelligence (AI) model might help to diagnose pneumonia from CXR more quickly and accurately. We aim to develop an AI model for pneumonia from CXR images and to evaluate diagnostic performance with external dataset.MethodsTo train the pneumonia model, a total of 157,016 CXR images from the National Institutes of Health (NIH) and the Korean National Tuberculosis Association (KNTA) were used (normal vs. pneumonia = 120,722 vs.36,294). An ensemble model of two neural networks with DenseNet classifies each CXR image into pneumonia or not. To test the accuracy of the models, a separate external dataset of pneumonia CXR images (n = 212) from a tertiary university hospital (Gachon University Gil Medical Center GUGMC, Incheon, South Korea) was used; the diagnosis of pneumonia was based on both the chest CT findings and clinical information, and the performance evaluated using the area under the receiver operating characteristic curve (AUC). Moreover, we tested the change of the AI probability score for pneumonia using the follow-up CXR images (7 days after the diagnosis of pneumonia, n = 100).ResultsWhen the probability scores of the models that have a threshold of 0.5 for pneumonia, two models (models 1 and 4) having different pre-processing parameters on the histogram equalization distribution showed best AUC performances of 0.973 and 0.960, respectively. As expected, the ensemble model of these two models performed better than each of the classification models with 0.983 AUC. Furthermore, the AI probability score change for pneumonia showed a significant difference between improved cases and aggravated cases (Δ = -0.06 ± 0.14 vs. 0.06 ± 0.09, for 85 improved cases and 15 aggravated cases, respectively, P = 0.001) for CXR taken as a 7-day follow-up.ConclusionsThe ensemble model combined two different classification models for pneumonia that performed at 0.983 AUC for an external test dataset from a completely different data source. Furthermore, AI probability scores showed significant changes between cases of different clinical prognosis, which suggest the possibility of increased efficiency and performance of the CXR reading at the diagnosis and follow-up evaluation for pneumonia.

Project description:BACKGROUND:In sub-Saharan Africa, a third of people starting antiretroviral therapy and majority of patients returning to HIV-care after disengagement, present with advanced HIV disease (ADH), and are at high risk of mortality. Simplified and more affordable point-of-care (POC) diagnostics are required to increase access to prompt CD4 cell count screening for ambulatory and asymptomatic patients. The Visitect CD4 Lateral Flow Assay (LFA) is a disposable POC test, providing a visually interpreted result of above or below 200 CD4cells/mm3. This study evaluated the diagnostic performance of this index test. METHODS:Consenting patients above 18years of age and eligible for CD4 testing were enrolled in Nsanje district hospital (Malawi), Gutu mission hospital (Zimbabwe) and Centre hopitalier de Kabinda (DRC). A total of 708 venous blood samples were tested in the index test and in the BD FACSCount assay (reference test method) in the laboratories (Phase 1) to determine diagnostic accuracy. A total of 433 finger-prick (FP) samples were tested on the index test at POC by clinicians (Phase 2) and a self-completed questionnaire was administered to all testers to explore usability of the index test. RESULTS:Among 708 patients, 67.2% were female and median CD4 was 297cells/mm3. The sensitivity of the Visitect CD4 LFA using venous blood in the laboratory was 95.0% [95% CI: 91.3-97.5] and specificity was 81.9% [95% CI: 78.2-85.2%]. Using FP samples, the sensitivity of the Visitect CD4 LFA was 98.3% [95% CI: 95.0-99.6] and specificity was 77.2% [95% CI: 71.6-82.2%]. Usability of the Visitect CD4 LFA was high across the study sites with 97% successfully completed tests. Due to the required specific multiple incubation and procedural steps during the Visitect CD4 LFA testing, few health workers (7/26) were not confident to manage testing whilst multi-tasking in their clinical work. CONCLUSIONS:Visitect CD4 LFA is a promising test for decentralized CD4 screening in resource-limited settings, without access to CD4 testing and and it can trigger prompt management of patients with AHD. Lay health cadres should be considered to conduct Visitect CD4 LFA testing in PHCs as well as coordinating all other POC quality assurance.

Project description:BackgroundRespiratory pathology is a major driver of mortality in the intensive care unit (ICU), even in the absence of a primary respiratory diagnosis. Prior work has demonstrated that a visual scoring system applied to chest radiographs (CXR) is associated with adverse outcomes in ICU patients with Acute Respiratory Distress Syndrome (ARDS). We hypothesized that a simple, semi-quantitative CXR score would be associated with clinical outcomes for the general ICU population, regardless of underlying diagnosis.MethodsAll individuals enrolled in the Registry of Critical Illness at Brigham and Women's Hospital between June 2008 and August 2018 who had a CXR within 24 h of admission were included. Each patient's CXR was assigned an opacification score of 0-4 in each of four quadrants with the total score being the sum of all four quadrants. Multivariable negative binomial, logistic, and Cox regression, adjusted for age, sex, race, immunosuppression, a history of chronic obstructive pulmonary disease, a history of congestive heart failure, and APACHE II scores, were used to assess the total score's association with ICU length of stay (LOS), duration of mechanical ventilation, in-hospital mortality, 60-day mortality, and overall mortality, respectively.ResultsA total of 560 patients were included. Higher CXR scores were associated with increased mortality; for every one-point increase in score, in-hospital mortality increased 10% (OR 1.10, CI 1.05-1.16, p < 0.001) and 60-day mortality increased by 12% (OR 1.12, CI 1.07-1.17, p < 0.001). CXR scores were also independently associated with both ICU length of stay (rate ratio 1.06, CI 1.04-1.07, p < 0.001) and duration of mechanical ventilation (rate ratio 1.05, CI 1.02-1.07, p < 0.001).ConclusionsHigher values on a simple visual score of a patient's CXR on admission to the medical ICU are associated with increased in-hospital mortality, 60-day mortality, overall mortality, length of ICU stay, and duration of mechanical ventilation.

Dataset Information

Comparison of Diagnostic Performance of Semi-Quantitative Knee Ultrasound and Knee Radiography with MRI: Oulu Knee Osteoarthritis Study.

Publications

Comparison of Diagnostic Performance of Semi-Quantitative Knee Ultrasound and Knee Radiography with MRI: Oulu Knee Osteoarthritis Study.

Similar Datasets

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