UNASSIGNED: To evaluate the diagnostic accuracy of artificial intelligence-based algorithms in identifying neck of femur fracture on a plain radiograph.
UNASSIGNED: Systematic review and meta-analysis.
UNASSIGNED: PubMed, Web of science, Scopus, IEEE, and the Science direct databases were searched from inception to 30 July 2023.
UNASSIGNED: Eligible article types were descriptive, analytical, or trial studies published in the English language providing data on the utility of artificial intelligence (AI) based algorithms in the detection of the neck of the femur (NOF) fracture on plain X-ray.
UNASSIGNED: The prespecified primary outcome was to calculate the sensitivity, specificity, accuracy, Youden index, and positive and negative likelihood ratios. Two teams of reviewers (each consisting of two members) extracted the data from available information in each study. The risk of bias was assessed using a mix of the CLAIM (the Checklist for AI in Medical Imaging) and QUADAS-2 (A Revised Tool for the Quality Assessment of Diagnostic Accuracy Studies) criteria.
UNASSIGNED: Of the 437 articles retrieved, five were eligible for inclusion, and the pooled sensitivity of AIs in diagnosing the fracture NOF was 85%, with a specificity of 87%. For all studies, the pooled Youden index (YI) was 0.73. The average positive likelihood ratio (PLR) was 19.88, whereas the negative likelihood ratio (NLR) was 0.17. The random effects model showed an overall odds of 1.16 (0.84-1.61) in the forest plot, comparing the AI system with those of human diagnosis. The overall heterogeneity of the studies was marginal (I2 = 51%). The CLAIM criteria for risk of bias assessment had an overall >70% score.
UNASSIGNED: Artificial intelligence (AI)-based algorithms can be used as a diagnostic adjunct, benefiting clinicians by taking less time and effort in neck of the femur (NOF) fracture diagnosis.
UNASSIGNED: PROSPERO CRD42022375449.
UNASSIGNED: The online version contains supplementary material available at 10.1007/s43465-024-01130-6.

Background A precise preoperative imaging classification system for pertrochanteric fractures is imperative due to the reported unreliability of the current classification system, which relies solely on plain radiographs. This study aims to achieve two primary objectives: (i) elucidate the reproducibility of pertrochanteric fracture evaluation based on the Revised Arbeitsgemeinschaft für Osteosynthesefragen/Orthopedic Trauma Association (AO/OTA) Classification, comparing plain radiographs and computed tomography (CT) scan images, and (ii) investigate the consistency of fracture classification between both imaging modalities. Methods A total of 523 patients (112 males and 411 females, mean age 85 years) who had both preoperative plain radiographic and three-dimensional CT images were enrolled in this study. Following the Revised AO/OTA Classification, three individual observers initially classified the fractures in plain radiograph images as either Stable (A1) or Unstable (A2). Subsequently, they further categorized them into five sub-categories (A1.1, A1.2, A1.3, A2.2, and A2.3). The same classification system was applied to the CT scan images. Inter-observer agreement and consistency of fracture classification between plain radiographs and CT scan images were assessed. Results The inter-observer agreement for fractures classified as stable or unstable using only plain radiographs was found to be fair among the three observers, with a mean κ of 0.397 (95% CI: 0.316-0.478). However, inter-observer agreement improved significantly when using CT scans, with a mean κ of 0.590 (95% CI: 0.518-0.662). Our results demonstrated a consistency level between two graphical modalities ranging from fair to moderate, with κ values of 0.581, 0.383, and 0.335, respectively. It\'s worth noting that plain radiographic classification occasionally resulted in underestimations, with each observer identifying 16.1%, 34.0%, and 37.9%, respectively, of cases as A1 in plain radiographs that were classified as A2 in CT scans. Conclusions This study reveals a moderate to substantial level of inter-observer agreement for fracture classification when using CT scan images, in contrast to plain radiographs. Fracture evaluation relying solely on plain radiographs sometimes underestimates fracture classification and exhibits less consistency compared to using CT scan images.

UNASSIGNED: Anatomic restoration of the humeral head is critical for successful shoulder replacement. Accurate measurements of the humeral head are essential for anatomic substitution.
UNASSIGNED: To evaluate whether a best-fit circle of the humeral head, as determined from different projections of plain radiographs, can predict the humeral head implant size for either the left or right shoulder.
UNASSIGNED: Descriptive laboratory study.
UNASSIGNED: Bilateral shoulder radiographs of 200 patients without arthropathy or other abnormal findings of the humeral head were evaluated. The best-fit circle was obtained based on 3 points: the medial and lateral endpoints of the anatomic neck and the lateral cortex below the greater tuberosity. This circle was drawn on 5 different radiographic projections (shoulder anteroposterior [AP], glenoid AP, outlet, axillary, and 30° caudal tilt) of the left and right shoulders of each patient, and the radius of each circle was measured. Agreement in the best-fit circle radius between the left and right shoulders was statistically analyzed using the intraclass correlation coefficient (ICC). There were 2 independent blinded observers who performed each measurement twice to evaluate inter- and intraobserver reliability.
UNASSIGNED: Overall agreement in the radius between the right and left shoulders was excellent (all ICCs ≥0.990). The ICCs according to the radiographic view were 0.990 (95% CI, 0.986-0.993) for shoulder AP, 0.992 (95% CI, 0.989-0.995) for glenoid AP, 0.996 (95% CI, 0.994-0.997) for outlet, 0.994 (95% CI, 0.991-0.996) for axillary, and 0.993 (95% CI, 0.990-0.995) for 30° caudal tilt. Interobserver ICCs demonstrated a high level of precision: 0.987 (95% CI, 0.978-0.993) for shoulder AP, 0.986 (95% CI, 0.974-0.992) for glenoid AP, 0.974 (95% CI, 0.954-0.985) for outlet, 0.991 (95% CI, 0.984-0.995) for axillary, and 0.987 (95% CI, 0.977-0.993) for 30° caudal tilt. Intraobserver ICCs demonstrated excellent test-retest reliability: 0.983 (95% CI, 0.970-0.991) for shoulder AP, 0.989 (95% CI, 0.980-0.994) for glenoid AP, 0.987 (95% CI, 0.978-0.993) for outlet, 0.985 (95% CI, 0.973-0.991) for axillary, and 0.970 (95% CI, 0.947-0.983) for 30° caudal tilt.
UNASSIGNED: The best-fit circle to calculate the ideal size of a humeral head implant was able to be determined from different projections of plain radiographs.
UNASSIGNED: Anatomic restoration of a deformed humeral head can be achieved using the best-fit circle of the contralateral humeral head as obtained from plain radiographs. This method can facilitate preoperative planning and postoperative evaluation in the anatomic restoration of the shoulder to avoid the problems of overstuffing.

UNASSIGNED: The aim of our study is to evaluate artificial intelligence (AI) support in pelvic fracture diagnosis on X-rays, focusing on performance, workflow integration and radiologists\' feedback in a spoke emergency hospital.
UNASSIGNED: Between August and November 2021, a total of 235 sites of fracture or suspected fracture were evaluated and enrolled in the prospective study. Radiologist\'s specificity, sensibility accuracy, positive and negative predictive values were compared to AI. Cohen\'s kappa was used to calculate the agreement between AI and radiologist. We also reviewed the AI workflow integration process, focusing on potential issues and assessed radiologists\' opinion on AI via a survey.
UNASSIGNED: The radiologist performance in accuracy, sensitivity and specificity was better than AI but McNemar test demonstrated no statistically significant difference between AI and radiologist\'s performance (p = 0.32). Calculated Cohen\'s K of 0.64.
UNASSIGNED: Contrary to expectations, our preliminary results did not prove a real improvement of patient outcome nor in reporting time but demonstrated AI high NPV (94,62%) and non-inferiority to radiologist performance. Moreover, the commercially available AI algorithm used in our study automatically learn from data and so we expect a progressive performance improvement. AI could be considered as a promising tool to rule-out fractures (especially when used as a \"second reader\") and to prioritize positive cases, especially in increasing workload scenarios (ED, nightshifts) but further research is needed to evaluate the real impact on the clinical practice.

Plain abdominal radiographs and gastrointestinal contrast studies remain the first line of investigation for the evaluation of several conditions due to their easy availability and ease of use in pediatric patients. A systematic approach to evaluating the plain radiograph for pediatric abdomen can lead the radiologist to a relevant differential diagnosis in most cases. In other cases, it leads the radiologist to the next line of investigation. The plain radiograph of the abdomen is requested for several conditions ranging from abdominal pain, vomiting, failure to pass meconium, abdominal distension, perforation, mass or for suspected obstruction. The radiation dose involved in abdominal radiography, although significant, the diagnostic information provided outweighs the risk. Dose reduction techniques should be employed to reduce the radiation dose to infants and children. Spectrum of atresias and stenosis from the esophagus up to the rectum, Hirschsprung disease, small left colon syndrome, and anorectal malformations can be identified with a detailed and systematic contrast study. They act as an adjunct in the diagnosis of conditions such as intussusception and hypertrophic pyloric stenosis. Inflammatory conditions such as acute appendicitis, necrotizing enterocolitis, and acute conditions such as pneumoperitoneum are also well appreciated on plain abdominal radiographs.

Acute abdominal pain is a common complaint in children. We came across several unusual causes of acute abdomen including jejunal haematoma, perforation and abdominal abscess following hydrostatic intussusception reduction, twisting of mesenteric cyst, perforation of sigmoid colon and Meckel\'s diverticulum presenting with intussusception. In this article, we aim to present imaging features of these entities so that paediatric surgeons, radiologists and other health-care providers are aware of these unusual manifestations of acute abdomen.

Investigating the correlation between the interlaminar space size on plain radiograph and lumbar spinal stenosis (LSS).
100 Patients with LSS and 100 normal participants without LSS were included in this study. Lumbar interlaminar parameters were measured on plain radiographs. Spinal canal parameters were measure on CT and MRI. These image parameters were compared between LSS and control group. The linear correlation among interlaminar parameters, spinal canal parameters and Oswestry Disability Index (ODI) were analyzed. The cut-off values of interlaminar parameters for diagnosing L3/4 and L4/5 symptomatic LSS were analyzed.
Excepting for L1/2 interlaminar width, all interlaminar and spinal canal related parameters in LSS group were significantly smaller than those in control group. Excepting for L1/2 interlaminar width and L5/S1 interlaminar height, all interlaminar parameters had significantly positive linear correlation with spinal canal parameters accordingly in each lumbar level. For diagnosis of symptomatic LSS, The cut off values of L4/5 interlaminar width, height and area were 18.46 mm, 11.37 mm and 134.05 mm2 while 15.78 mm, 13.59 mm and 157.98 mm2 in L3/4. Both spinal canal size and interlaminar size had no linear correlation with ODI in cases of L4/5 LSS.
Lumbar interlaminar space size on plain radiograph has positive linear correlation with developmental and degenerative LSS, excepting for L1/2 interlaminar width and L5/S1 interlaminar height. Lumbar plain radiograph can be a feasible way for predicting and helping to diagnose LSS through evaluating the interlaminar space size.
III.

Introduction A demographic survey of femoral pertrochanteric fractures provides several important information for the healthcare system of a country since this fracture is commonly seen in the elderly and has a poor postoperative functional prognosis that is a burden on society. The importance of accurately classifying pertrochanteric fractures as stable or unstable cannot be understated. However, the use of plain radiograph images alone is known to underestimate fracture severity with low inter- or intra-observer agreement. Computed tomography (CT) images offer information for a more accurate classification of pertrochanteric fractures. With this three-dimensional (3D) CT-based study using the revised Arbeitsgemeinschaft für Osteosynthesefragen/Orthopedic Trauma Association (AO/OTA) classification, the purpose of this study is to elucidate the epidemiological demography of patients with pertrochanteric fractures. Material and methods We retrospectively collected 808 patients from five hospitals, classified into two groups: stable (A1) or unstable (A2). Age, gender, fracture laterality, and surgery timing were identified as epidemiological variables. Patients with both preoperative plain radiographs and 3D CT scans were included in the study. The exclusion criteria were AO/OTA A3 type fractures, pathological fractures, previous ipsilateral surgery, 60 years old or younger, and conservatively treated patients. The primary outcome involved detailing the total number of fractures based on classification (A1 or A2) and variables. The secondary outcome involved a comparison between the A1 and A2 groups. Results The mean age of patients at the time of surgery was 85 years (range: 61-103 years). There were 637 female and 171 male patients. There were 463 left-sided fractures and 345 right-sided fractures. Of the 808 patients, 371 (45.9%) were classified to have A1 fractures, and 437 (54.1%) had A2 fractures. The age at surgery, gender, fracture laterality, and surgery timing between the A1 and A2 groups were compared. The mean and standard deviation of the age at surgery for patients in the A1 and A2 groups were 84.9±7.7 and 86.9±6.8, respectively. The number of patients for each age distribution of 61-69, 70-74, 75-79, 80-84, 85-89, 90-94, and 95 or older for the A1 and A2 groups was 18 and 7, 18 and 12, 43 and 44, 76 and 82, 107 and 132, 79 and 110, and 30 and 50, respectively, showing that the difference in categorial distribution was statistically significant (p=0.002). Overall, 278 females and 93 males were classified to have A1 fractures compared with 359 females and 78 males with A2 fractures (p=0.01). There were 166 right-sided and 205 left-sided stable A1 fractures and 179 right-sided and 258 left-sided A2 fractures (not significant (NS)). Among the total number of A1 and A2 surgeries by month, the most were in December with 77 surgeries (37 and 40, respectively), and the least was in June with 37 (18 and 19, respectively). The seasonal classification for A1 and A2 surgeries is as follows: spring with 172 (74 and 98, respectively), summer with 150 (70 and 80, respectively), autumn with 193 (90 and 103, respectively), and winter with 208 (97 and 111, respectively) (NS). Conclusion In this demographic study of 808 patients with pertrochanteric fractures classified by 3D CT images, 371 had A1 fractures and 437 had A2 fractures. A2 fractures were significantly more in females with an age peak of 85-89 years.

In this paper, authors introduce the basic prerequisite for rational, targeted, and above all, child-oriented diagnosis of fractures and dislocations in children and adolescents is in-depth prior knowledge of the special features of trauma in the growth age group. This review summarizes the authors\' many years of experience and the state of the current pediatric traumatology literature. It aims to provide recommendations for rational, child-specific diagnostics appropriate to the child, especially for the area of extremity injuries in the growth age. The plain radiograph remains the indispensable standard in diagnosing fractures and dislocations of the musculoskeletal system in childhood and adolescence. Plain radiographs in two planes are the norm, but in certain situations, one plane is sufficient. X-rays of the opposite side in acute diagnostics are obsolete. Images to show consolidation after conservative treatment is rarely necessary. Before metal removal, however, they are indispensable. The upcoming diagnostical tool in pediatric trauma is ultrasound. More and more studies show that in elected injuries and using standardized protocols, fracture ultrasound is as accurate as plain radiographs to detect and control osseous and articular injuries. In acute trauma, CT scans have only a few indications, especially in epiphyseal fractures in adolescents, such as transitional fractures of the distal tibia or coronal shear fractures of the distal humerus. CT protocols must be adapted to children and adolescents to minimize radiation exposure. MRI has no indication in the detection or understanding of acute fractures in infants and children. It has its place in articular injuries of the knee and shoulder to show damage to ligaments, cartilage, and other soft tissues. Furthermore, MRI is useful in cases of remaining pain after trauma without radiological proof of a fracture and in the visualization of premature closure of growth plates after trauma to plan therapy. Several everyday examples of rational diagnostic workflows, as the authors recommend them, are mentioned. The necessity of radiation protection must be taken into consideration.

Introduction The absence of a precise fracture classification system that classifies pertrochanteric fractures into either stable or unstable contributes to a burden on healthcare and has several major implications. We propose an innovative graphical index, which we refer to as posterior protrusion measures (PPM), using plain lateral view radiograph images for the revised AO Foundation (Arbeitsgemeinschaft für Osteosynthesesfragen)/Orthopedic Trauma Association (AO/OTA) classification system. This study aims to: (i) introduce the use of PPM for classifying fractures into stable or unstable under the revised AO/OTA classification system and set the threshold numeric value, (ii) elucidate the reproducibility of inter and intra-observer agreement, and investigate the consistency of fracture classification using PPM versus computed tomography (CT) scan images. Materials and methods Out of 146 patients identified from the database, a total of 126 patients were enrolled in the study. Pertrochanteric fractures were classified as either stable or unstable. Three surgeons were assigned for PPM determination. Regarding the demographical data, the chi-square test was used to assess the significance of each parameter on a categorical scale between the two groups. The independent sample t-test or the Mann-Whitney U test was used to compare the two independent groups. Interclass correlation coefficient (ICC) values for continuous variables and kappa values (κ) for categorical variables were calculated to assess inter-observer and intra-observer agreement. Receiver-operating characteristic (ROC) analysis was used to determine optimal cut-off points of PPM to predict consistency between separate fracture classification groups, one using PPM values with a threshold derived from plain radiograph images, and the other using CT scan images. Results Among a total of 126 pertrochanteric fractures, the A1 (stable) group consisted of 39 patients (10 males, 29 females), whereas the A2 (unstable) group consisted of 87 patients (14 males, 73 females) (not significant, NS). Intraclass correlation coefficient (ICC) values of PPM for the inter-observer agreement were 0.796 (0.723-0.852), 0.664 (0.554-0.751), and 0.702 (0.601-0.781) at first examination and 0.729 (0.635-0.801) at the second. The intra-observer agreement was 0.869 (0.819-0.906) and 0.603 (0.480-0.703). We examined for consistency of fracture classification group of PPM values with a threshold of 0.4 (A1<0.4, A2=0.4 or more) and CT-based group. For the first examination, there was mostly \"moderate\" agreement in fracture classification (stable or unstable) between plain radiograph and CT scan images, κ (95%CI): 0.427 (0.266-0.588), 0.493 (0.335-0.651), and 0.359 (0.176-0.544), and for the second, 0.418 (0.251-0.585), and 0.451 (0.284-0.620), respectively. Conclusion We propose a supplementary tool, namely PPM that allows for possible alternative classification of pertrochanteric fractures into A1 (stable) and A2 (unstable) using plain radiograph images under the revised AO/OTA classification system. In this study, a PPM threshold value of 0.4 demonstrated a moderate inter- and intra-observer agreement. It is noteworthy to mention that there was a satisfactory consistency of fracture classification using PPM derived from plain radiograph images when compared to classification using CT scan images. In addition, the PPM method provides a numerical score.