Postoperative Stability in Displaced Ankle Fractures with Concomitant Ligamentous Injuries.

Ankle instability, which can be attributed to either the deltoid or lateral ligamentous complex, may be both a cause and a consequence of ankle fractures. This study aimed to assess postoperative ankle instability in patients with displaced ankle fractures. A total of 54 patients with displaced ankle fractures were included. Malleolar fractures were surgically reduced and fixated, and if necessary, the syndesmosis was stabilized. Concomitant deltoid injuries were left unrepaired. Ankle stress radiographs were taken approximately 25.4 months after surgery, with a standard deviation of 20.5 months. Radiographic measurements included the tibiotalar tilt angle (TT) on varus stress view, anterior translation of the talus (AT) on the anterior drawer view, and the medial clear space (MC) and tibiotalar tilt angle on the valgus stress view. These measurements were compared between the injured and the noninjured contralateral ankle for all patients as well as in a subgroup of 19 patients with concomitant deltoid and syndesmosis injuries. There were no significant differences in Varus TT (p = 0.675, p = 0.394), AT (p = 0.516, p = 0.967), Valgus MC (p = 0.190, p = 0.498), and Valgus TT (p = 0.173, p = 0.442) between the injured and noninjured ankles in the whole group of patients as well as in the subgroup of patients with concomitant deltoid and syndesmosis injuries. Patients with displaced ankle fractures exhibited radiographically stable ankles postoperatively. Syndesmosis fixation without deltoid ligament repair is a viable treatment option for achieving ankle stability postoperatively in fractures with both ligament injuries.

Utility of artificial intelligence for detection of pneumothorax on chest radiopgraphs done after transthoracic percutaneous transthoracic biopsy guided by computed tomography.

OBJETIVE: To assess the ability of an artificial intelligence software to detect pneumothorax in chest radiographs done after percutaneous transthoracic biopsy. MATERIAL AND METHODS: We included retrospectively in our study adult patients who underwent CT-guided percutaneous transthoracic biopsies from lung, pleural or mediastinal lesions from June 2019 to June 2020, and who had a follow-up chest radiograph after the procedure. These chest radiographs were read to search the presence of pneumothorax independently by an expert thoracic radiologist and a radiodiagnosis resident, whose unified lecture was defined as the gold standard, and the result of each radiograph after interpretation by the artificial intelligence software was documented for posterior comparison with the gold standard. RESULTS: A total of 284 chest radiographs were included in the study and the incidence of pneumothorax was 14.4%. There were no discrepancies between the two readers' interpretation of any of the postbiopsy chest radiographs. The artificial intelligence software was able to detect 41/41 of the present pneumothorax, implying a sensitivity of 100% and a negative predictive value of 100%, with a specificity of 79.4% and a positive predictive value of 45%. The accuracy was 82.4%, indicating that there is a high probability that an individual will be adequately classified by the software. It has also been documented that the presence of Port-a-cath is the cause of 8 of the 50 of false positives by the software. CONCLUSIONS: The software has detected 100% of cases of pneumothorax in the postbiopsy chest radiographs. A potential use of this software could be as a prioritisation tool, allowing radiologists not to read immediately (or even not to read) chest radiographs classified as non-pathological by the software, with the confidence that there are no pathological cases.

Surgical complications after fixation of minimally displaced lateral compression type 1 pelvic ring injuries.

PURPOSE: To review surgical complications after fixation of stress-positive minimally displaced (< 1 cm) lateral compression type 1 (LC1) pelvic ring injuries. METHODS: A retrospective study at a level one trauma center identified patients who received surgical fixation of isolated LC1 pelvic ring injuries. Surgical complications and additional procedures were reviewed. RESULTS: Sixty patients were included. The median age was 61 years (Interquartile range 40-70), 65% (n = 39) were women, and 57% (n = 34) had high-energy mechanisms. Anterior-posterior, posterior-only, and anterior-only fixation constructs were used in 77% (n = 46), 15% (n = 9), and 8% (n = 5) of patients. Anterior fixation was performed with rami screw fixation in 82% (49/60), external fixation in 2% (1/60), and open reduction and plate fixation in 2% (1/60). There were 15 surgical complications in 23% (14/60), and 12 additional procedures in 17% (10/60). Complications included loss of reduction ≥ 1 cm (8%), symptomatic hematomas (8%), symptomatic backout of unicortical retrograde rami screws (5%), deep infection of the pelvic space after a retrograde rami screw (1.6%), and iatrogenic L5 nerve injury (1.6%). All losses of reduction involved geriatric females with distal rami fractures sustained in ground-level falls. Loss of reduction was found to be more likely in patients with low energy mechanisms (proportional difference (PD) 62%, 95% confidence interval (CI) 18% to 76%; p = 0.01) and 2 versus 1 posterior pelvic screws (PD 36%; CI 0.4% to 75%; p = 0.03). CONCLUSIONS: Surgical complications and additional procedures routinely occurred after fixation of LC1 injuries. Patients should be appropriately counseled on the risks of surgical fixation of these controversial injuries. LEVEL OF EVIDENCE: Diagnostic, Level III.

Inter-rater and Intra-rater Reliability of a Mobile App Method to Measure Lumbar Lordosis.

Background Measuring the exact quantitative values of lordotic curves is a vital factor in clinical settings to prevent musculoskeletal deformities in the future. Existing lordotic assessment methods are very diverse, expensive, inaccurate, and not handy, and their availability cannot be maintained in every clinic setup. Aim The purpose of this research was to study the reliability of a mobile app as a feasible method to measure lumbar lordosis angle using a lateral view radiograph. Methodology A lateral view low back region radiograph of 58 participants was taken based on the criteria, and the experienced physiotherapists uploaded the X-ray to the mobile app and measured the lordotic angles with the support of machine learning algorithms. Descriptive statistics were used to calculate the average and dispersion of the data of the lumbar lordosis angle measured using the mobile app method (Statistical Package for the Social Sciences (IBM SPSS Statistics for Windows, IBM Corp., Version 23, Armonk, NY)). Results Associations between and within raters were assessed using the Karl Pearson coefficient of correlation (1.000). Inter-rater and intra-rater reliability were determined by using Cronbach's alpha (.966) and the split-half method. The internal consistency of the mobile app was found to be good. Conclusions Based on our findings, we conclude that the mobile app method is reliable and useful in measuring lumbar lordosis objectively with less effort. Since the app is handy on smartphones, physiotherapists can conduct an objective lumbar lordosis assessment in clinical settings.

Radiological diagnosis of prevalent osteoporotic vertebral fracture on radiographs: an interim consensus from a group of experts of the ESSR osteoporosis and metabolism subcommittee.

When a low-energy trauma induces an acute vertebral fracture (VF) with clinical symptoms, a definitive diagnosis of osteoporotic vertebral fracture (OVF) can be made. Beyond that, a "gold" radiographic standard to distinguish osteoporotic from non-osteoporotic VFs does not exist. Fracture-shaped vertebral deformity (FSVD) is defined as a deformity radiographically indistinguishable from vertebral fracture according to the best of the reading radiologist's knowledge. FSVD is not uncommon among young populations with normal bone strength. FSVD among an older population is called osteoporotic-like vertebral fracture (OLVF) when the FSVD is likely to be associated with compromised bone strength. In more severe grade deformities or when a vertebra is collapsed, OVF diagnosis can be made with a relatively high degree of certainty by experienced readers. In "milder" cases, OVF is often diagnosed based on a high probability rather than an absolute diagnosis. After excluding known mimickers, singular vertebral wedging in older women is statistically most likely an OLVF. For older women, three non-adjacent minimal grade OLVF (< 20% height loss), one minimal grade OLVF and one mild OLVF (20-25% height loss), or one OLVF with ≥ 25% height loss, meet the diagnosis of osteoporosis. For older men, a single OLVF with < 40% height loss may be insufficient to suggest the subject is osteoporotic. Common OLVF differential diagnoses include X-ray projection artifacts and scoliosis, acquired and developmental short vertebrae, osteoarthritic wedging, oncological deformities, deformity due to high-energy trauma VF, lateral hyperosteogeny of a vertebral body, Cupid's bow, and expansive endplate, among others.

Radiographic findings in patients suspected of subacromial impingement syndrome: prevalence and reliability.

OBJECTIVE: Aims were to (i) report prevalence and (ii) evaluate reliability of the radiographic findings in examinations of patients suspected of subacromial impingement syndrome (SIS), performed before a patient's first consultation at orthopaedic department. MATERIALS AND METHODS: This cross-sectional study examined radiographs from 850 patients, age 18 to 63 years, referred to orthopaedic clinic on suspicion of SIS. Prevalence (%) of radiographic findings were registered. Inter- and intrarater reliability was analysed using expected and observed agreement (%), kappa coefficients, Bland-Altman plots, or intraclass coefficients. RESULTS: A total of 850 patients with a mean age of 48.2 years (SD = 8.8) were included. Prevalence of the radiographic findings was as follows: calcification 24.4%, Bigliani type III (hooked) acromion 15.8%, lateral/medial acromial spurs 11.1%/6.6%, acromioclavicular osteoarthritis 12.0%, and Bankart/Hill-Sachs lesions 7.1%. Inter- and intrarater Kappa values for most radiographic findings ranged between 0.40 and 0.89; highest values for the presence of calcification (0.85 and 0.89) and acromion type (0.63 and 0.66). The inter- and intrarater intraclass coefficients ranged between 0.41 and 0.83; highest values for acromial tilt (0.79 and 0.83) and calcification area (0.69 and 0.81). CONCLUSION: Calcification, Bigliani type III (hooked) acromion, and acromioclavicular osteoarthritis were prevalent findings among patients seen in orthopaedic departments on suspicion of SIS. Spurs and Bankart/Hill-Sachs lesions were less common. Optimal reliabilities were found for the presence of calcification, calcification area, and acromial tilt. Calcification qualities, acromion type, lateral spur, and acromioclavicular osteoarthritis showed suboptimal reliabilities. Newer architectural measures (acromion index and lateral acromial angle) performed well with respect to reliability.

Temporal and geographical variations in diagnostic imaging in Norway.

BACKGROUND: Unwarranted temporal and geographical variations are acknowledged as a profound problem for equal access and justice in the provision of health services. Even more, they challenge the quality, safety, and efficiency of such services. This is highly relevant for imaging services. OBJECTIVE: To analyse the temporal and geographical variation in the number of diagnostic images in Norway from 2013 to 2021. METHODS: Data on outpatient imaging provided by the Norwegian Health Economics Administration (HELFO) and inpatient data afforded by fourteen hospital trusts and hospitals in Norway. Data include the total number of imaging examinations according to the Norwegian Classification of Radiological Procedures (NCRP). Analyses were performed with descriptive statistics. RESULTS: More than 37 million examinations were performed in Norway during 2013-2021 giving an average of 4.2 million examinations per year. In 2021 there was performed and average of 0.8 examinations per person and 2.2 examinations per person for the age group > 80. There was a 9% increase in the total number of examinations from 2013 to 2015 and a small and stable decrease of 0.5% per year from 2015 to 2021 (with the exception of 2020 due to the pandemic). On average 71% of all examinations were outpatient examinations and 32% were conducted at private imaging centres. There were substantial variations between the health regions, with Region South-East having 53.1% more examinations per inhabitant than Region West. The geographical variation was even more outspoken when comparing catchment areas, where Oslo University Hospital Trust had twice as many examinations per inhabitant than Finnmark Hospital Trust. CONCLUSION: As the population in Norway is homogeneous it is difficult to attribute the variations to socio-economic or demographic factors. Unwarranted and supply-sensitive variations are challenging for healthcare systems where equal access and justice traditionally are core values.

Doctor's Orders-Why Radiologists Should Consider Adjusting Commercial Machine Learning Applications in Chest Radiography to Fit Their Specific Needs.

This retrospective study evaluated a commercial deep learning (DL) software for chest radiographs and explored its performance in different scenarios. A total of 477 patients (284 male, 193 female, mean age 61.4 (44.7-78.1) years) were included. For the reference standard, two radiologists performed independent readings on seven diseases, thus reporting 226 findings in 167 patients. An autonomous DL reading was performed separately and evaluated against the gold standard regarding accuracy, sensitivity and specificity using ROC analysis. The overall average AUC was 0.84 (95%-CI 0.76-0.92) with an optimized DL sensitivity of 85% and specificity of 75.4%. The best results were seen in pleural effusion with an AUC of 0.92 (0.885-0.955) and sensitivity and specificity of each 86.4%. The data also showed a significant influence of sex, age, and comorbidity on the level of agreement between gold standard and DL reading. About 40% of cases could be ruled out correctly when screening for only one specific disease with a sensitivity above 95% in the exploratory analysis. For the combined reading of all abnormalities at once, only marginal workload reduction could be achieved due to insufficient specificity. DL applications like this one bear the prospect of autonomous comprehensive reporting on chest radiographs but for now require human supervision. Radiologists need to consider possible bias in certain patient groups, e.g., elderly and women. By adjusting their threshold values, commercial DL applications could already be deployed for a variety of tasks, e.g., ruling out certain conditions in screening scenarios and offering high potential for workload reduction.

Radiographic Diagnostic Choices of Palestinian Dentists for Implant Therapy.

Aim: To report the radiographic preferences during dental implant therapy in Palestine. Materials and Methods: Fourteen multiple-choice questions were delivered in electronic and hardcopy formats questionnaires during the Sixth International Implantology Conference (Palestine). The questions investigated the radiographic techniques that are mostly used based on various clinical scenarios and treatment phases. Results: One hundred and thirty-seven responses were captured. The majority of the participants were general dentists with implant experience (79.6%). Less than a third of the participants (27.2%) were members of the Palestinian Association of Dental Implantology. The majority (85.9%) of them have their practice in a city zone. Panoramic radiograph (PAN) combined with cone beam computed tomography (CBCT) was the most preferred radiographic technique during the planning stage. Conclusion: PAN and CBCT was the preferred choice during the planning stages. A PAN was preferred postoperatively and if no complications were associated. In the case of symptomatic patients, CBCT was the radiograph of choice.

Sex estimation from maxillofacial radiographs using a deep learning approach.

The purpose of this study was to construct deep learning models for more efficient and reliable sex estimation. Two deep learning models, VGG16 and DenseNet-121, were used in this retrospective study. In total, 600 lateral cephalograms were analyzed. A saliency map was generated by gradient-weighted class activation mapping for each output. The two deep learning models achieved high values in each performance metric according to accuracy, sensitivity (recall), precision, F1 score, and areas under the receiver operating characteristic curve. Both models showed substantial differences in the positions indicated in saliency maps for male and female images. The positions in saliency maps also differed between VGG16 and DenseNet-121, regardless of sex. This analysis of our proposed system suggested that sex estimation from lateral cephalograms can be achieved with high accuracy using deep learning.

Respiratory symptoms due to a twisted nasogastric tube: A case report.

Insertion of a nasogastric tube (NGT) is generally considered safe; however, it is not without risk, and in cases of misplacement, complications and even death may occur. In this article, we reported a case of NGT misplacement in a 75-year-old male, which resulted in aspiration pneumonia. We also reviewed published cases of NGT misplacement. Clinicians should pay enough attention to the confirmation of the proper placement of an NGT. A systematic approach for NGT insertion and confirmation is required to prevent misplacement.

The chest X-ray score baseline in predicting continuous oxygen therapy failure in low-risk aged patients after thoracic surgery.

Background: Radiographic severity assessment can be instrumental in diagnosing postoperative pulmonary complications (PPCs) and guiding oxygen therapy. The radiographic assessment of lung edema (RALE) and Brixia scores correlate with disease severity, but research on low-risk elderly patients is lacking. This study aimed to assess the efficacy of two chest X-ray scores in predicting continuous oxygen therapy (COT) treatment failure in patients over 70 years of age after thoracic surgery. Methods: From January 2019 to December 2021, we searched for patients aged 70 years and above who underwent thoracic surgery and received COT treatment, with a focus on those at low risk of respiratory complications. Bedside chest X-rays, RALE, Brixia scores, and patient data were collected. Univariate, multivariate analyses, and 1:2 matching identified risk factors. Receiver operating characteristic (ROC) curves determined score sensitivity, specificity, and predictive values. Results: Among the 242 patients surviving to discharge, 19 (7.9%) patients experienced COT failure. COT failure correlated with esophageal cancer surgeries, thoracotomies (36.8% vs. 9%, P=0.003; 26.3% vs. 9.4%, P=0.004), and longer operation time (3.4 vs. 2.8 h, P=0.003). Surgical approach and RALE score were independent risk factors. The prediction model had an area under the curve (AUC) of 0.839 [95% confidence interval (CI), 0.740-0.938]. Brixia and RALE scores predicted COT failure with AUCs of 0.764 (95% CI, 0.650-0.878) with a cut-off value of 6.027 and 0.710 (95% CI, 0.588-0.832) with a cut-off value of 17.134, respectively, after 1:2 matching. Conclusions: The RALE score predict the risk of COT failure in elderly, low-risk thoracic patients better than the Brixia score. This simple, cheap, and noninvasive method helps evaluate postoperative lung damage, monitor treatment response, and provide early warning for oxygen therapy escalation. Further studies are required to confirm the validity and applicability of this model in different settings and populations.

Progression of proximal caries in primary molars using the radiographic ICDAS: a retrospective cohort study.

PURPOSE: To evaluate the proximal caries progression in primary molars using the radiographic International Caries Detection and Assessment System (ICDAS). METHODS: A study was conducted on 196 children aged 3-9 years old who underwent the clinical examination and bitewing radiography during baseline and 6-month (and over) follow-up visits. The primary molars bitewing radiographs with initial enamel caries (RA1 and RA2) or outer dentine caries (RA3) of proximal surfaces were included. Caries advancement was scored using ICDAS criteria and statistical analyses with the chi-square test. Median survival time was evaluated using Kaplan-Meier survival curves and log-rank tests. RESULTS: A total of 439 surfaces of primary molars were included in this study and an averaged follow-up period of enamel and dentine caries group were 18.3 ± 9.6 months and 16.5 ± 9.5 months respectively. The progression of proximal enamel lesions significantly differed between primary maxillary and mandibular molars (p = 0.002) and among each patient's primary mandibular second molar and the others (p = 0.002). On the contrary, the outer dentine caries of each group of primary molars was not different. The median survival time of the initial enamel proximal caries (23.30 months) was non-significantly longer than that of the dentine (20.80 months). CONCLUSIONS: Progressions of the initial enamel proximal caries were significantly different among primary molars at the average 18.3-month follow-up. The median survival period of the enamel proximal caries was more extended than that of dentine but without statistical difference. These results provide essential information for dentists regarding an appropriate appointment for bitewing examinations.

Routine follow-up imaging is not necessary in uneventful early recovery after distal radius fractures treated with volar locking plate in working-aged patients: A retrospective single-center cohort study.

BACKGROUND AND OBJECTIVE: The purpose of our study was to evaluate whether routine follow-up radiographs after distal radius fracture (DRF) treated with volar locking plate (VLP) influenced clinical decision-making and treatment in working-aged patients (18-65 years). We evaluated the possible correlation between clinical status and problems with follow-up radiographs and analyzed the overall reoperation rate. METHODS: The study population of this retrospective cohort study consisted of working-aged (18-65 years) patients with DRF who were treated with VLP between January 2010 and December 2020. Baseline data, follow-up visits, and radiographs were collected. Radiographs were classified as either routinely assigned or according to clinical findings. Patients were divided into four groups based on abnormal radiographic findings or major symptoms leading to reoperation. Patients also received patient-rated wrist evaluation (PRWE) questionnaire, which were analyzed. RESULTS: A total of 861 patients were included in this study. Routine follow-up radiographs were available for 844 (98%) patients. In 7.0% of patients, 6-week radiographs led to a change of standard treatment protocol, most commonly additional imaging and/or clinical follow-up. Nine (1.1%) patients underwent an urgent reoperation, and 15 (1.8%) patients underwent reoperation later in the follow-up period. All these patients were exceptionally painful/symptomatic. In addition, 33 (3.9%) patients who underwent additional imaging and follow-up after abnormal radiograph, but did not undergo reoperation, were asymptomatic or suffered only mild pain. A total of 89 (10.5%) patients had reoperation for any reason during the follow-up period. CONCLUSIONS: Routine follow-up radiographs after the treatment of DRF with VLP in the working-aged population rarely leads to changes in treatment strategy or reoperation in asymptomatic patients suggesting that it would be safe and cost-effective to reduce routine follow-up radiographs and focus instead on those patients with moderate-to-severe symptoms.

Assessment of the comparative agreement between chest radiographs and CT scans in intensive care units.

PURPOSE: Chest radiographs in critically ill patients can be difficult to interpret due to technical and clinical factors. We sought to determine the agreement of chest radiographs and CT scans, and the inter-observer variation of chest radiograph interpretation, in intensive care units (ICUs). METHODS: Chest radiographs and corresponding thoracic computerised tomography (CT) scans (as reference standard) were collected from 45 ICU patients. All radiographs were analysed by 20 doctors (radiology consultants, radiology trainees, ICU consultants, ICU trainees) from 4 different centres, blinded to CT results. Specificity/sensitivity were determined for pleural effusion, lobar collapse and consolidation/atelectasis. Separately, Fleiss' kappa for multiple raters was used to determine inter-observer variation for chest radiographs. RESULTS: The median sensitivity and specificity of chest radiographs for detecting abnormalities seen on CTs scans were 43.2% and 85.9% respectively. Diagnostic sensitivity for pleural effusion was significantly higher among radiology consultants but no specialty/experience distinctions were observed for specificity. Median inter-observer kappa coefficient among assessors was 0.295 ("fair"). CONCLUSIONS: Chest radiographs commonly miss important radiological features in critically ill patients. Inter-observer agreement in chest radiograph interpretation is only "fair". Consultant radiologists are least likely to miss thoracic radiological abnormalities. The consequences of misdiagnosis by chest radiographs remain to be determined.

Full-length radiograph based automatic musculoskeletal modeling using convolutional neural network.

Full-length radiographs contain information from which many anatomical parameters of the pelvis, femur, and tibia may be derived, but only a few anatomical parameters are used for musculoskeletal modeling. This study aimed to develop a fully automatic algorithm to extract anatomical parameters from full-length radiograph to generate a musculoskeletal model that is more accurate than linear scaled one. A U-Net convolutional neural network was trained to segment the pelvis, femur, and tibia from the full-length radiograph. Eight anatomic parameters (six for length and width, two for angles) were automatically extracted from the bone segmentation masks and used to generate the musculoskeletal model. Sørensen-Dice coefficient was used to quantify the consistency of automatic bone segmentation masks with manually segmented labels. Maximum distance error, root mean square (RMS) distance error and Jaccard index (JI) were used to evaluate the geometric accuracy of the automatically generated pelvis, femur and tibia models versus CT bone models. Mean Sørensen-Dice coefficients for the pelvis, femur and tibia 2D segmentation masks were 0.9898, 0.9822 and 0.9786, respectively. The algorithm-driven bone models were closer to the 3D CT bone models than the scaled generic models in geometry, with significantly lower maximum distance error (28.3 % average decrease from 24.35 mm) and RMS distance error (28.9 % average decrease from 9.55 mm) and higher JI (17.2 % average increase from 0.46) (P < 0.001). The algorithm-driven musculoskeletal modeling (107.15 ± 10.24 s) was faster than the manual process (870.07 ± 44.79 s) for the same full-length radiograph. This algorithm provides a fully automatic way to generate a musculoskeletal model from full-length radiograph that achieves an approximately 30 % reduction in distance errors, which could enable personalized musculoskeletal simulation based on full-length radiograph for large scale OA populations.

Prediction of postoperative curve correction based on the supine radiographs for adult idiopathic scoliosis (AdIS) patients.

BACKGROUND CONTEXT: Preoperative supine radiographs are mandatory in the new adult idiopathic scoliosis (AdIS) classification. Supine radiographs are easily reproducible and highly predictive of side bending radiographs. However, few studies evaluated the use of supine radiographs in predicting postoperative curve correction after posterior spinal fusion (PSF) in AdIS. PURPOSE: To investigate the use of supine and side bending (SB) radiographs in predicting postoperative curve correction in AdIS patients who underwent PSF. STUDY DESIGN: Retrospective study. PATIENT SAMPLE: 93 AdIS patients who underwent PSF between 2022 and 2023 were included. OUTCOME MEASURES: Demographic data were age, gender, height, weight, body mass index (BMI), Risser grade, Lenke curve types and Cobb angles. Main outcome measures were preoperative and immediate postoperative Cobb angle (proximal thoracic [PT], main thoracic [MT] and thoracolumbar/lumbar [TL/L] curves), Supine Cobb angle and Flexibility rate (PT, MT and TL/L), and Correction rate (PT, MT and TL/L). METHODS: Correlation study was performed between Supine Cobb angle vs. postoperative Cobb angle for PT, MT and TL/L curves. A predictive formula was derived from the correlation plots. RESULTS: A total of 93 subjects were included in our study with a median age of 24.7 years and comprised of 80 females (86.0%). Preoperative Supine Cobb angle (r=0.835, r=0.881, r=0.767, p<.001) and preoperative SB Cobb angle (r=0.815, r=0.872, r=0.801, p<.001) showed similar strong positive correlation with postoperative PT, MT and TL/L Cobb angle, but preoperative Supine Cobb angle had slightly stronger correlation in PT and MT, whereas preoperative SB Cobb angle had stronger correlation in TL/L curve. Using the derived predictive formulae, there was a significant, strong, positive correlation between the predicted value and actual value of postoperative standing Cobb angle, (r=0.852, p<.001), with 71.0% of the patients had predicted postoperative Cobb angle from the supine radiographs within 5 degrees of the actual value. CONCLUSION: Both supine radiographs and side bending radiographs had strong predictability of the postoperative Cobb angle for PT, MT and TL/L curves. In 71.0% of patients, the actual postoperative Cobb angle was within 5 degrees of the predicted postoperative Cobb angle using the predictive formulae.

Automated analysis of knee joint alignment using detailed angular values in long leg radiographs based on deep learning.

Malalignment in the lower limb structure occurs due to various causes. Accurately evaluating limb alignment in situations where malalignment needs correction is necessary. To create an automated support system to evaluate lower limb alignment by quantifying mechanical tibiofemoral angle (mTFA), mechanical lateral distal femoral angle (mLDFA), medial proximal tibial angle (MPTA), and joint line convergence angle (JLCA) on full-length weight-bearing radiographs of both lower extremities. In this retrospective study, we analysed 404 radiographs from one hospital for algorithm development and testing and 30 radiographs from another hospital for external validation. The performance of segmentation algorithm was compared to that of manual segmentation using the dice similarity coefficient (DSC). The agreement of alignment parameters was assessed using the intraclass correlation coefficient (ICC) for internal and external validation. The time taken to load the data and measure the four alignment parameters was recorded. The segmentation algorithm demonstrated excellent agreement with human-annotated segmentation for all anatomical regions (average similarity: 89-97%). Internal validation yielded good to very good agreement for all the alignment parameters (ICC ranges: 0.7213-0.9865). Interobserver correlations between manual and automatic measurements in external validation were good to very good (ICC scores: 0.7126-0.9695). The computer-aided measurement was 3.44 times faster than was the manual measurement. Our deep learning-based automated measurement algorithm accurately quantified lower limb alignment from radiographs and was faster than manual measurement.

Performance of Radiological and Biochemical Biomarkers in Predicting Radio-Symptomatic Knee Osteoarthritis Progression.

Imaging biomarkers permit improved approaches to identify the most at-risk patients encountering knee osteoarthritis (KOA) progression. This study aimed to investigate the utility of trabecular bone texture (TBT) extracted from plain radiographs, associated with a set of clinical, biochemical, and radiographic data, as a predictor of long-term radiographic KOA progression. We used data from the Foundation for the National Institutes of Health (FNIH) Biomarkers Consortium dataset. The reference model made use of baseline TBT parameters adjusted for clinical covariates and radiological scores. Several models based on a combination of baseline and 24-month TBT variations (TBT∆TBT) were developed using logistic regression and compared to those based on baseline-only TBT parameters. All models were adjusted for baseline clinical covariates, radiological scores, and biochemical descriptors. The best overall performances for the prediction of radio-symptomatic, radiographic, and symptomatic progression were achieved using TBT∆TBT parameters solely, with area under the ROC curve values of 0.658 (95% CI: 0.612-0.705), 0.752 (95% CI: 0.700-0.804), and 0.698 (95% CI: 0.641-0.756), respectively. Adding biochemical markers did not significantly improve the performance of the TBT∆TBT-based model. Additionally, when TBT values were taken from the entire subchondral bone rather than just the medial, lateral, or central compartments, better results were obtained.