Interobserver Analysis of Albertoni Classification for Mallet Finger, Using Plain Radiography: Importance of the Goniometer.
Ontology highlight
ABSTRACT:
SUBMITTER: Barros TSV
PROVIDER: S-EPMC7186065 | biostudies-literature | 2020 Apr
REPOSITORIES: biostudies-literature
Publications
Interobserver Analysis of Albertoni Classification for Mallet Finger, Using Plain Radiography: Importance of the Goniometer.
Barros Tomás Santos Vasconcelos TSV Jeha Antônio José AJ Ribeiro Guilherme Vieira Borchio GVB
Revista brasileira de ortopedia 20200128 2
<b>Objectives</b> The objective of the present study is to evaluate the intraobserver and interobserver reliability of the Albertoni classification for mallet finger. Evaluation of goniometer device application is also an objective. <b>Methods</b> A total of 10 lateral radiographs of patients with mallet finger were selected and measured by 60 orthopedic surgeons with and without the use of goniometer. <b>Results</b> The intra- and interobserver reliability coefficients found were high. With ...[more]
Similar Datasets
Project description:Currently, research based on the technology and applications of 3D printing is being actively pursued. 3D printing technology, also called additive manufacturing, is widely and increasingly used in the medical field. This study produced custom casts for the treatment of mallet finger using plaster of Paris, which was traditionally used in clinical practice, and 3D printing technology, and evaluated their advantages and disadvantages for patients by conducting a wearability assessment. Mallet finger casts produced using plaster of Paris, when incorrectly made, can result in skin necrosis and other problems for patients. These problems can be mitigated, however, by creating casts using 3D printing technology. Additionally, plaster casts or ready-made alternatives can be inconvenient with respect to rapid treatment of patients. In contrast, 3D-printed casts appear to provide patients with appropriate treatment and increase their satisfaction because they are small in size, custom-made for each patient, and can be quickly made and immediately applied in clinical practice.
| S-EPMC6636505 | biostudies-literature
Project description:BackgroundRecently, innovative attempts have been made to identify moyamoya disease (MMD) by focusing on the morphological differences in the head of MMD patients. Following the recent revolution in the development of deep learning (DL) algorithms, we designed this study to determine whether DL can distinguish MMD in plain skull radiograph images.MethodsThree hundred forty-five skull images were collected as an MMD-labeled dataset from patients aged 18 to 50 years with definite MMD. As a control-labeled data set, 408 skull images of trauma patients were selected by age and sex matching. Skull images were partitioned into training and test datasets at a 7:3 ratio using permutation. A total of six convolution layers were designed and trained. The accuracy and area under the receiver operating characteristic (AUROC) curve were evaluated as classifier performance. To identify areas of attention, gradient-weighted class activation mapping was applied. External validation was performed with a new dataset from another hospital.FindingsFor the institutional test set, the classifier predicted the true label with 84·1% accuracy. Sensitivity and specificity were both 0·84. AUROC was 0·91. MMD was predicted by attention to the lower face in most cases. Overall accuracy for external validation data set was 75·9%.InterpretationDL can distinguish MMD cases within specific ages from controls in plain skull radiograph images with considerable accuracy and AUROC. The viscerocranium may play a role in MMD-related skull features. FUND: This work was supported by grant no. 18-2018-029 from the Seoul National University Bundang Hospital Research Fund.
| S-EPMC6413674 | biostudies-literature
Project description:The use of hip arthroscopy to treat various forms of hip pathology continues to grow. As part of a standard evaluation for eligibility for hip arthroscopy, we routinely obtain standard radiographs to assess the hip joint. These include orthogonal projections of the acetabulum and proximal femur, which can be obtained with a standing false profile, supine anteroposterior pelvis, and a lateral view of the proximal femur (either Dunn 45° or 90°, frog-leg lateral, or cross-table lateral). A comprehensive analysis of the radiographs is of utmost importance in order to indicate a patient for hip arthroscopy, for preoperative planning, and to determine prognosis. The purpose of this Technical Note is to provide a comprehensive guide of how our group performs qualitative and quantitative analysis of hip radiographs in a potential candidate for hip arthroscopy.
| S-EPMC5794674 | biostudies-literature
Project description:BackgroundA high false-negative rate has been reported for the diagnosis of ossification of the posterior longitudinal ligament (OPLL) using plain radiography. We investigated whether deep learning (DL) can improve the diagnostic performance of radiologists for cervical OPLL using plain radiographs.Materials and methodsThe training set consisted of 915 radiographs from 207 patients diagnosed with OPLL. For the test set, we used 200 lateral cervical radiographs from 100 patients with cervical OPLL and 100 patients without OPLL. An observer performance study was conducted over two reading sessions. In the first session, we compared the diagnostic performance of the DL-model and the six observers. The diagnostic performance was evaluated using the area under the receiver operating characteristic curve (AUC) at the vertebra and patient level. The sensitivity and specificity of the DL model and average observers were calculated in per-patient analysis. Subgroup analysis was performed according to the morphologic classification of OPLL. In the second session, observers evaluated the radiographs by referring to the results of the DL-model.ResultsIn the vertebra-level analysis, the DL-model showed an AUC of 0.854, which was higher than the average AUC of observers (0.826), but the difference was not significant (p = 0.292). In the patient-level analysis, the performance of the DL-model had an AUC of 0.851, and the average AUC of observers was 0.841 (p = 0.739). The patient-level sensitivity and specificity were 91% and 69% in the DL model, and 83% and 68% for the average observers, respectively. Both the DL-model and observers showed decreases in overall performance in the segmental and circumscribed types. With knowledge of the results of the DL-model, the average AUC of observers increased to 0.893 (p = 0.001) at the vertebra level and 0.911 (p < 0.001) at the patient level. In the subgroup analysis, the improvement was largest in segmental-type (AUC difference 0.087; p = 0.002).ConclusionsThe DL-based OPLL detection model can significantly improve the diagnostic performance of radiologists on cervical radiographs.
| S-EPMC9045646 | biostudies-literature
Project description:The purpose of this study was to compare measurements of anterior wall index (AWI) and posterior wall index (PWI) on computed tomography (CT) to those on radiographs (XR). A consecutive cohort of 33 patients (45 hips total) being evaluated for hip pain with both XR and CT was examined. Preoperative measurements of AWI and PWI were performed utilizing supine anteroposterior pelvic XR and coronal and swiss axial CT scans by two independent raters. Mean differences between XR and CT measurements were compared, and agreement between measurements was assessed using the concordance correlation coefficient (rc ) and Bland-Altman analysis. A total of 39 hips in 28 patients were analyzed. The mean patient age was 31.1 ± 9.0 years, and 50% were female. Mean AWI and PWI on XR was 0.50 ± 0.14 and 0.91 ± 0.12, respectively. Measured values of AWI were consistently larger (0.08 ± 0.10, P < 0.01) on XR compared with both coronal and swiss axial CT, with moderate agreement between XR and CT measurements (rc = 0.68-0.70). Measured values of PWI were consistently smaller (0.15 ± 0.12, P < 0.05) on XR compared with both coronal and swiss axial CT, with poor agreement between XR and CT measurements (rc = 0.37-0.45). Measured values of acetabular wall indices on XR were consistently larger for AWI and smaller for PWI relative to CT. Agreement between XR and CT measures of the indices were moderate to poor. This highlights the need for standardization of XR- and CT-based measurements to improve assessment of acetabular coverage and subsequent clinical decision-making.
| S-EPMC8460168 | biostudies-literature
Project description:Mallet finger deformity is a common and debilitating injury of the fingertip, accounting for 10% of all tendon and ligament injuries. It involves a disruption of the terminal extensor mechanism of the distal phalanx. Patients can experience significant pain and swelling of the fingertip and have significant morbidity without treatment. Nonoperative treatment using joint immobilization with splints is the mainstay of management. Traditionally, prefabricated and thermoplastic splints have been utilized; however, issues with comfort and skin complications such as maceration can lead to patient noncompliance and eventually, poor outcomes. To address this, we demonstrate our experience with the design, manufacture, and application of individualized 3D printed mallet finger splints. The splints were found to provide advantages akin to traditional thermoplastic splints, with the addition of being low cost, easy to manufacture, and environmentally friendly.
| S-EPMC8062141 | biostudies-literature
Project description:BACKGROUND:Plain abdominal radiography (PAR) is routinely performed in emergency departments (EDs). This study aimed to (1) identify the indications for PAR in EDs and compare them against international guidelines, (2) uncover predictors of non-compliance with guidelines, and (3) describe the use of additional radiological examinations in EDs. METHODS:Retrospective cohort study in the EDs of two hospitals in Geneva, Switzerland, including all adult patients who underwent PAR in the EDs. Indications were considered "appropriate" if complying with guidelines. Predictors of non-compliance were identified by univariate and multivariate analyses. RESULTS:Over 1?year, PAR was performed in 1997 patients (2.2% of all admissions). Their mean age was 59.7?years, with 53.1% of female patients. The most common indications were constipation (30.8%), suspected ileus (28.9%), and abdominal pain (15.3%). According to the French and American guidelines, only 11.8% of the PARs were indicated, while 46.2% of them complied with the Australian and British guidelines. On multivariate analysis, admission to the private hospital ED (odds ratio [OR] 3.88, 95% CI 1.78-8.45), female gender (OR 1.95, 95% CI 1.46-2.59), and an age?>? 65?years (OR 2.41, 95%CI 1.74-3.32) were associated with a higher risk of inappropriate PAR. Additional radiological examinations were performed in 73.7% of patients. CONCLUSIONS:Most indications for PAR did not comply with guidelines and elderly women appeared particularly at risk of being exposed to inappropriate examination. PAR did not prevent the need for additional examinations. Local guidelines should be developed, and initiatives should be implemented to reduce unnecessary PARs. TRIAL REGISTRATION:ClinicalTrials.gov , identifier NCT02980081 .
| S-EPMC6332516 | biostudies-literature
Project description:Background Classification of lung cancer screening CT scans depends on measurement of lung nodule size. Information about interobserver agreement is limited. Purpose To assess interobserver agreement in the measurements and American College of Radiology Lung CT Screening Reporting and Data System (Lung-RADS) classifications of solid lung nodules detected at lung cancer screening using manual measurements of average diameter and computer-aided semiautomated measurements of average diameter and volume (CT volumetry). Materials and Methods Two radiologists and one radiology resident retrospectively measured lung nodules from screening CT scans obtained between September 2016 and June 2018 with a Lung-RADS (version 1.0) classification of 2, 3, 4A, or 4B in the clinical setting. Average manual diameter and semiautomated computer-aided diameter and volume measurements were converted to the corresponding Lung-RADS categories. Interobserver agreement in raw measurements was assessed using intraclass correlation and Bland-Altman indexes, and interobserver agreement in Lung-RADS classification was assessed using bi-rater κ. Results One hundred twenty patients (mean age, 63 years ± 6 [standard deviation]; 67 women) were evaluated. All manual, semiautomated diameter, and semiautomated volume measurements were obtained by all three readers in 120 of 147 nodules (82%). Intraclass correlation coefficients were greater than or equal to 0.95 for all reader pairs using all measurement methods and were highest using volumetry. Bias and 95% limits of agreement for average diameter were smaller with semiautomated measurements than with manual measurements. κ values across all Lung-RADS classifications were greater than or equal to 0.81, with the lowest being for manual measurements and the highest being for volumetric measurements. Forty-three of 120 (36%) of the nodules were classified into a lower Lung-RADS category on the basis of volumetry compared with using manual diameter measurements by at least one reader, whereas the reverse occurred for four of 120 (3%) of the nodules. Conclusion Interobserver agreement was high with manual diameter measurements and increased with semiautomated CT volumetric measurements. Semiautomated CT volumetry enabled classification of more nodules into lower Lung CT Screening Reporting and Data System categories than manual or semiautomated diameter measurements. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Nishino in this issue.
| S-EPMC7706890 | biostudies-literature
Project description:Breast cancers can be classified by hierarchical clustering using an "intrinsic" gene list into one of at least five molecular subtypes: basal-like, HER2, luminal A, luminal B, and normal breast-like. Five different intrinsic gene lists composed of varying numbers of genes have been used for molecular subtype identification and classification of breast cancers. The aim of this study was to determine the objectivity and interobserver reproducibility of the assignment of molecular subtype classes by hierarchical cluster analysis. Three publicly available breast cancer datasets (n = 779) were subjected to two-way average-linkage hierarchical cluster analysis using five distinct intrinsic gene lists. We used free-marginal Kappa statistics to analyze interobserver agreement among five breast cancer researchers for the whole classification and for each molecular subtype separately according to each intrinsic gene list for each breast cancer dataset. None of the classification systems tested produced almost perfect agreement (Kappa ≥ 0.81) among observers. However, substantial interobserver agreement (70.8% to 76.1% of the samples and free-marginal Kappa scores from 0.635 to 0.701) was consistently observed in all datasets for four molecular subtypes (luminal, basal-like, HER2, and normal breast-like). When luminal cancers were subdivided (luminal A, B, and C), none of the classification systems produced substantial agreement (Kappa ≥ 0.61) in all the datasets analyzed. Analysis of each subtype separately revealed that only two (basal-like and HER2) could be reproducibly identified by independent observers (Kappa ≥ 0.81). Assignment of molecular subtype classes of breast cancer based on the analysis of dendrograms obtained with hierarchical cluster analysis is subjective and shows modest interobserver reproducibility. For the development of a molecular taxonomy, objective definitions for each molecular subtype and standardized methods for their identification are required.
| S-EPMC3079850 | biostudies-literature
Project description:The effectiveness of night splinting after treatment of mallet finger is unknown. We tested the hypothesis that there is no difference in extensor lag between patients with mallet finger that wear a night splint for an additional month after 6 to 8 weeks of continuous splinting and patients that do not wear a night splint.Fifty-one patients were enrolled in this randomized controlled trial. At enrollment, range of motion was measured for the injured and contralateral uninjured finger. The follow-up was conducted approximately 4 weeks later in person (41 patients) or by phone (10 patients). Analysis was by intention to treat.There were no significant differences in final extensor lag between patients that did and did not receive a night splint. Among the 41 patients with a final in-person evaluation, the final average extensor lag was 14°, and 34 % (14 of 41 patients) had a lag of 20° or greater. Final extensor lag correlated significantly with age, enrollment distal interphalangeal joint (DIP) flexion and extensor lag, and final DIP flexion, with the latter two accounting for 28 % of the variation in final lag in the final multivariable model (p?<?0.001). There were no differences in disability (p?=?0.67) or treatment satisfaction (p?=?0.48) between patients that did and did not use night splints.Supplemental night splinting does not improve the outcome of mallet finger in terms of extensor lag, disability, or satisfaction with treatment. Patients with worse initial extensor lags should expect worse final lags; residual lags of 20° or greater are commonplace.
| S-EPMC4022962 | biostudies-literature