Weightbearing anteroposterior pelvic radiographs are recommended in DDH assessment.
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ABSTRACT:
SUBMITTER: Troelsen A
PROVIDER: S-EPMC2504653 | biostudies-other | 2008 Apr
REPOSITORIES: biostudies-other
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Project description:OBJECTIVES:To derive conversions of antiquated exposure data into modern equivalents and to apply these in the assessment of the skin dose of pelvic radiographs since 1896. METHODS:The literature 1896-2018 was searched for implicit and explicit dose information. The early implicit dose data contained now obsolete descriptions of radiation quality and quantity for long since disappeared X-ray systems of limited efficiency. Converting the old information into modern specifications was achieved using contemporary data and computer simulations. Final dose calculations were done with modern software. Explicit radiation doses of later date reported in old quantities and units were adapted according to current recommendations. RESULTS:For the period before 1927 conversion algorithms for spark gap data and penetrometer hardnesses to high voltage could be derived. Electrical and X-ray efficiencies of several old röntgen systems were determined. Together they allowed reconstruction of 53 doses. After 1927 doses were generally explicitly specified; 114 were retrieved. Although an enormous spread was observed, the average skin dose was reduced by a factor of about 400. CONCLUSIONS:Antiquated exposure data were successfully used for dose reconstruction. Extreme dose variability was a constant. Efforts to cut down doses were effective as skin doses went down from sub-erythema values to about one milligray.
| S-EPMC6439109 | biostudies-literature
Project description:UNLABELLED: We asked whether radiographic angles and signs of hip osteoarthrosis differ between radiographs of the pelvis taken in standing and supine positions. We retrospectively reviewed the radiographs of 61 patients (72 hips) with developmental dislocation of the hip. The minimum followup after closed reduction was 15 years (mean, 44 years; range, 15-64 years). We used pelvic radiographs in supine and standing positions taken at the same time and determined the following parameters: minimal joint space width, acetabular roof obliquity (AC angle), depth of the acetabulum (ACM angle), and center-edge angle. Osteoarthrosis was assessed according to Kellgren and Lawrence. Two independent observers measured all radiographs manually with a goniometer. AC angle, center-edge angle, and minimum joint space width differed between the radiographs taken in supine and standing positions at followup, whereas osteoarthrosis grading and the ACM angle did not. The AC angle depended on patient position and predicted development of osteoarthrosis. The minimum joint space width was influenced by the radiographic position with greater values in the supine position. ACM angle and the osteoarthrosis grade according to Kellgren and Lawrence were unaffected by the patient's position. LEVEL OF EVIDENCE: Level II, prognostic study. See the Guidelines for Authors for a complete description of levels of evidence.
| S-EPMC2504670 | biostudies-other
Project description:Pelvic radiograph (PXR) is essential for detecting proximal femur and pelvis injuries in trauma patients, which is also the key component for trauma survey. None of the currently available algorithms can accurately detect all kinds of trauma-related radiographic findings on PXRs. Here, we show a universal algorithm can detect most types of trauma-related radiographic findings on PXRs. We develop a multiscale deep learning algorithm called PelviXNet trained with 5204 PXRs with weakly supervised point annotation. PelviXNet yields an area under the receiver operating characteristic curve (AUROC) of 0.973 (95% CI, 0.960-0.983) and an area under the precision-recall curve (AUPRC) of 0.963 (95% CI, 0.948-0.974) in the clinical population test set of 1888 PXRs. The accuracy, sensitivity, and specificity at the cutoff value are 0.924 (95% CI, 0.912-0.936), 0.908 (95% CI, 0.885-0.908), and 0.932 (95% CI, 0.919-0.946), respectively. PelviXNet demonstrates comparable performance with radiologists and orthopedics in detecting pelvic and hip fractures.
| S-EPMC7887334 | biostudies-literature
Project description:ObjectivesTo compare ultra-low-dose CT (ULD-CT) of the osseous pelvis with tin filtration to standard clinical CT (CT), and to assess the quality of computed virtual pelvic radiographs (VRs).MethodsCT protocols were optimized in a phantom and three pelvic cadavers. Thirty prospectively included patients received both standard CT (automated tube voltage selection and current modulation) and tin-filtered ULD-CT of the pelvis (Sn140kV/50mAs). VRs of ULD-CT data were computed using an adapted cone beam-based projection algorithm and were compared to digital radiographs (DRs) of the pelvis. CT and DR dose parameters and quantitative and qualitative measures (1 = worst, 4 = best) were compared. CT and ULD-CT were assessed for osseous pathologies.ResultsDose reduction of ULD-CT was 84% compared to CT, with a median effective dose of 0.38 mSv (quartile 1-3: 0.37-0.4 mSv) versus 2.31 mSv (1.82-3.58 mSv; p < .001), respectively. Mean dose of DR was 0.37 mSv (± 0.14 mSv). The median signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of bone were significantly higher for CT (64.3 and 21.5, respectively) compared to ULD-CT (50.4 and 18.8; p ≤ .01), while ULD-CT was significantly more dose efficient (figure of merit (FOM) 927.6) than CT (FOM 167.6; p < .001). Both CT and ULD-CT were of good image quality with excellent depiction of anatomy, with a median score of 4 (4-4) for both methods (p = .1). Agreement was perfect between both methods regarding the prevalence of assessed osseous pathologies (p > .99). VRs were successfully calculated and were equivalent to DRs.ConclusionTin-filtered ULD-CT of the pelvis at a dose equivalent to standard radiographs is adequate for assessing bone anatomy and osseous pathologies and had a markedly superior dose efficiency than standard CT.Key points• Ultra-low-dose pelvic CT with tin filtration (0.38 mSv) can be performed at a dose of digital radiographs (0.37 mSv), with a dose reduction of 84% compared to standard CT (2.31 mSv). • Tin-filtered ultra-low-dose CT had lower SNR and CNR and higher image noise than standard CT, but showed clear depiction of anatomy and accurate detection of osseous pathologies. • Virtual pelvic radiographs were successfully calculated from ultra-low-dose CT data and were equivalent to digital radiographs.
| S-EPMC8379132 | biostudies-literature
Project description:Radiographs of the abdomen and pelvis are routinely obtained as a standard part of clinical care for the abdomen and pelvis. Brisk advances in technology over the last few decades have resulted in a multitude of medical devices and materials. Recognizing and evaluating these devices on abdominal and pelvic radiographs are critical, yet increasingly a difficult endeavor. In addition, multiple devices serving different purposes may have a similar radiographic appearance and position causing confusion for the interpreting radiologist. The role of the radiologist is to not only identify accurately these medical objects, but also to confirm for their accurate placement and to recognize any complications that could affect patient care, management or even be potentially life threatening. An extensive online search of literature showed our review article to be the most comprehensive work on medical devices and materials of the abdomen and pelvis, and in this second part of our two-part series, we discuss in depth about the neurologic and genitourinary devices seen on abdominal and pelvic radiographs.
| S-EPMC7239358 | biostudies-literature
Project description:Measuring acetabular anteversion is relevant to routine follow-up of total hip arthroplasties (THAs) and for malfunctioning THAs. Imageless navigation facilitates acetabular component orientation relative to the anterior pelvic plane (APP) or to the APP adjusted for sagittal pelvic tilt (PT). The optimal plain radiographic method for the postoperative assessment of anteversion is not agreed upon.(1) Do anteversion measurements on plain radiographs correlate more with APP anteversion or PT-adjusted anteversion? (2) Do measurements of anteversion performed on supine anteroposterior (AP) radiographs more accurately reflect intraoperative anteversion values for navigated THA compared to anteversion measured on cross-table lateral (CL) radiographs?Seventy patients receiving primary navigated THA were included. APP and PT-adjusted anteversion were recorded; the latter defined the intraoperative target for anteversion. Postoperative anteversion was measured on supine AP pelvis radiographs with computer software and CL radiographs with conventional methods. Intraoperative measurements were used as the reference standards for comparisons.Mean intraoperative APP anteversion was 20.6°?±?5.6°. Mean intraoperative PT-adjusted anteversion was 22.9°?±?4.5°. Mean anteversion was 22.7°?±?4.7° on AP radiographs and 27.2°?±?4.2° on CL radiographs (p?<?0.001). Only correlations between PT-adjusted anteversion and radiographic assessments of anteversion were significant. The mean difference between PT-adjusted anteversion and anteversion on AP radiographs was -0.2°?±?4.3°, while the mean difference between the PT-adjusted anteversion and anteversion measured on CL radiographs was 4.3?±?5.1° (p?<?0.001).Plain film assessment of anteversion was more accurate on supine AP radiographs than on CL radiographs, which overestimated acetabular anteversion.
| S-EPMC4733699 | biostudies-other
Project description:Purpose To assess the ability of convolutional neural networks (CNNs) to enable high-performance automated binary classification of chest radiographs. Materials and Methods In a retrospective study, 216 431 frontal chest radiographs obtained between 1998 and 2012 were procured, along with associated text reports and a prospective label from the attending radiologist. This data set was used to train CNNs to classify chest radiographs as normal or abnormal before evaluation on a held-out set of 533 images hand-labeled by expert radiologists. The effects of development set size, training set size, initialization strategy, and network architecture on end performance were assessed by using standard binary classification metrics; detailed error analysis, including visualization of CNN activations, was also performed. Results Average area under the receiver operating characteristic curve (AUC) was 0.96 for a CNN trained with 200 000 images. This AUC value was greater than that observed when the same model was trained with 2000 images (AUC = 0.84, P < .005) but was not significantly different from that observed when the model was trained with 20 000 images (AUC = 0.95, P > .05). Averaging the CNN output score with the binary prospective label yielded the best-performing classifier, with an AUC of 0.98 (P < .005). Analysis of specific radiographs revealed that the model was heavily influenced by clinically relevant spatial regions but did not reliably generalize beyond thoracic disease. Conclusion CNNs trained with a modestly sized collection of prospectively labeled chest radiographs achieved high diagnostic performance in the classification of chest radiographs as normal or abnormal; this function may be useful for automated prioritization of abnormal chest radiographs. © RSNA, 2018 Online supplemental material is available for this article. See also the editorial by van Ginneken in this issue.
| S-EPMC6358056 | biostudies-literature
Project description:Catheters are the second most common abnormal finding on radiographs. The position of catheters must be assessed on all radiographs because serious complications can arise if catheters are malpositioned. However, due to the large number of radiographs obtained each day, there can be substantial delays between the time a radiograph is obtained and when it is interpreted by a radiologist. Computer-aided approaches hold the potential to assist in prioritizing radiographs with potentially malpositioned catheters for interpretation and automatically insert text indicating the placement of catheters in radiology reports, thereby improving radiologists' efficiency. After 50 years of research in computer-aided diagnosis, there is still a paucity of study in this area. With the development of deep learning approaches, the problem of catheter assessment is far more solvable. This review provides an overview of current algorithms and identifies key challenges in building a reliable computer-aided diagnosis system for assessment of catheters on radiographs. This review may serve to further the development of machine learning approaches for this important use case. Supplemental material is available for this article. © RSNA, 2020.
| S-EPMC8017400 | biostudies-literature
Project description:Developmental dysplasia of the hip (DDH) is common, and features a widened Sharp's angle as observed on pelvic x-ray images. Determination of Sharp's angle, essential for clinical decisions, can overwhelm the workload of orthopedic surgeons. To aid diagnosis of DDH and reduce false negative diagnoses, a simple and cost-effective tool is proposed. The model was designed using artificial intelligence (AI), and evaluated for its ability to screen anteroposterior pelvic radiographs automatically, accurately, and efficiently.Orthotopic anterior pelvic x-ray images were retrospectively collected (n = 11574) from the PACS (Picture Archiving and Communication System) database at Second Hospital of Jilin University. The Mask regional convolutional neural network (R-CNN) model was utilized and finely modified to detect 4 key points that delineate Sharp's angle. Of these images, 11,473 were randomly selected, labeled, and used to train and validate the modified Mask R-CNN model. A test dataset comprised the remaining 101 images. Python-based utility software was applied to draw and calculate Sharp's angle automatically. The diagnoses of DDH obtained via the model or the traditional manual drawings of 3 orthopedic surgeons were compared, each based on the degree of Sharp's angle, and these were then evaluated relative to the final clinical diagnoses (based on medical history, symptoms, signs, x-ray films, and computed tomography images).Sharp's angles on the left and right measured via the AI model (40.07° ± 4.09° and 40.65° ± 4.21°), were statistically similar to that of the surgeons' (39.35° ± 6.74° and 39.82° ± 6.99°). The measurement time required by the AI model (1.11 ± 0.00 s) was significantly less than that of the doctors (86.72 ± 1.10, 93.26 ± 1.12, and 87.34 ± 0.80 s). The diagnostic sensitivity, specificity, and accuracy of the AI method for diagnosis of DDH were similar to that of the orthopedic surgeons; the diagnoses of both were moderately consistent with the final clinical diagnosis.The proposed AI model can automatically measure Sharp's angle with a performance similar to that of orthopedic surgeons, but requires far less time. The AI model may be a viable auxiliary to clinical diagnosis of DDH.
| S-EPMC6946459 | biostudies-literature
Project description:PurposeDetermining the magnitude of displacement in pediatric lateral humeral condyle fractures can be difficult. The purpose of this study was to (1) assess the effect of forearm rotation on true fracture displacement using a cadaver model and to (2) determine the accuracy of radiographic measurements of the fracture gap.MethodsA non-displaced fracture was created in three human cadaveric arms. The specimens were mounted on a custom apparatus allowing forearm rotation with the humerus fixed. First, the effect of pure rotation on fracture displacement was simulated by rotating the forearm from supination to pronation about the central axis of the forearm, to isolate the effects of muscle pull. Then, the clinical condition of obtaining a lateral oblique radiograph was simulated by rotating the forearm about the medial aspect of the forearm. Fracture displacements were measured using a motion-capture system (true-displacement) and clinical radiographs (apparent-displacement).ResultsDuring pure rotation of the forearm, there were no significant differences in fracture displacement between supination and pronation, with changes in displacement of <1.0 mm. During rotation about the medial aspect of the forearm, there was a significant difference in true displacements between supination and pronation at the posterior edge (p < 0.05).ConclusionOverall, true fracture displacement measurements were larger than apparent radiographic displacement measurements, with differences from 1.6 to 6.0 mm, suggesting that the current clinical methods may not be sensitive enough to detect a displacement of 2.0 mm, especially when positioning the upper extremity for an internal oblique lateral radiograph.
| S-EPMC3935020 | biostudies-literature