Devices for the gastrointestinal tract are widely available and constantly advancing with less invasive techniques. They play a crucial role in diagnostic and therapeutic interventions and are commonly placed by interventional radiologists, gastroenterologists, and surgeons. These devices frequently appear in imaging studies, which verify their proper placement, identify any complications, or may be incidentally detected. Radiologists must be able to identify these devices at imaging and understand their intended purpose to assess their efficacy, detect complications such as incorrect positioning, and avoid misinterpreting them as abnormalities. Furthermore, many patients with these devices may require MRI, making assessing compatibility essential for safe patient care. This review seeks to provide a succinct and practical handbook for radiologists regarding both common and uncommon gastrointestinal devices. In addition to textual descriptions of clinical indications, imaging findings, complications, and MRI compatibility, the review incorporates a summary table as a quick reference point for key information and illustrative images for each device.

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.

BACKGROUND: Traumatic cervical spine (c-spine) injuries account for 10% of all spinal injuries. The c-spine is prone to injury by blunt acceleration/deceleration traumas. The Canadian C-Spine rule and NEXUS criteria guide clinical decision-making but lack consensus on imaging modality when necessary. This study aims to evaluate the sensitivity and specificity of CT, MRI, X-Ray, and, for the first time, LODOX-Statscan in identifying c-spine injuries in patients with blunt trauma and neck pain.
METHODS: We conducted a retrospective monocenter cohort study using patient data from the emergency department at Inselspital, Bern, Switzerland\'s largest level one trauma center. We identified patients presenting with trauma and neck pain during the recruitment period from 01.01.2012 to 31.12.2017. We included all patients that required a radiographic c-spine evaluation according to the NEXUS criteria. Certified spine surgeons reviewed each case, analyzed patient demographics, injury classification, trauma mechanism, and emergency management. The retrospective full case review was established as gold standard to decide whether the c-spine was injured. Sensitivity and specificity were calculated for CT, MRI, LODOX, and X-Ray imaging methods.
RESULTS: We identified 4996 patients, of which 2321 met the inclusion criteria. 91.3% (n = 2120) patients received a CT scan, 8.9% (n = 206) a MRI, 9.3% (n = 215) an X-ray, and 21.5% (n = 498) a LODOX scan. By retrospective case review, 186 participants were classified as injured. The sensitivity of CT was 88.6% (specificity 99%), and 89.8% (specificity 99.2%) with orthopedic surgeon consultation. MRI had a sensitivity of 88.5% (specificity of 96.9%); highlighting 14 cases correctly diagnosed as injured by MRI and misdiagnosed by CT. Projection radiography (36.4% sensitivity, 95.1% specificity) and LODOX (5.3% sensitivity, 100% specificity) were unsuitable for ruling out spinal injury.
CONCLUSIONS: While CT offers high sensitivity for detecting traumatic c-spine injury, MRI holds clinical significance in revealing injuries not recognized by CT in symptomatic patients. LODOX and projection radiography are insufficient for accurately ruling out c-spine injury. For patients with neurological symptoms, we recommend extended MRI use when CT scans are negative.

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.

Chondrosarcomas can be classified into various forms according to the presence or absence of a precursor lesion, location, and histological subtype. The new 2020 World Health Organization (WHO) Classification of Tumors of Soft Tissue and Bone classifies chondrogenic bone tumors as benign, intermediate (locally aggressive), or malignant, and separates atypical cartilaginous tumors (ACTs) and chondrosarcoma grade 1 (CS1) as intermediate and malignant tumors. respectively. Furthermore, the classification categorizes chondrosarcomas (including ACT) into eight subtypes: central conventional (grade 1 vs. 2-3), secondary peripheral (grade 1 vs. 2-3), periosteal, dedifferentiated, mesenchymal, and clear cell chondrosarcoma. Most chondrosarcomas are the low-grade, primary central conventional type. The rarer subtypes include clear cell, mesenchymal, and dedifferentiated chondrosarcomas. Comprehensive analysis of the characteristic imaging findings can help differentiate various forms of chondrosarcomas. However, distinguishing low-grade chondrosarcomas from enchondromas or high-grade chondrosarcomas is radiologically and histopathologically challenging, even for experienced radiologists and pathologists.

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.