Collimation and Exposure Parameter Influence Image Quality and Potential Radiation Dose to the Eye Lens of Personnel in Computed Radiography of the Canine Pelvis

Introduction: The purpose of this study was to evaluate the effect of collimation on image quality and radiation dose to the eye lenses of the personnel involved in computed radiography of the canine pelvis.Materials and Methods: A retrospective study of canine pelvic radiographs (N = 54) was undertaken to evaluate the relationship between image quality and the degree of field the collimation used. This was followed by a prospective cadaver study (N = 18) that assessed the effects on image quality and on scattered radiation dose of different collimation field areas and exposure parameters. All radiographs were analyzed for image quality using a Visual Grading Analysis (VGA) with three observers. Finally, the potential scattered radiation dose to the eye lens of personnel restraining a dog for pelvic radiographs was measured.Results: The retrospective study showed a slightly better (statistically non-significant) VGA score for the radiographs with optimal collimation. Spatial and contrast resolution and image sharpness showed the greatest improvement in response to minimizing the collimation field. The prospective study showed slightly better VGA scores (improved image quality) with the optimal collimation. Increasing the exposure factors especially the tube current and exposure time (mAs) resulted in improved low contrast resolution and less noise in the radiographs. The potential eye lens radiation dose increased by 14, 28, and 40% [default exposures, increased the tube peak potential (kVp), increased mAs, respectively] as a result of reduced collimation (increased beam size).Conclusion: The degree of collimation has no statistically significant on image quality in canine pelvic radiology for the range of collimation used but does have an impact on potential radiation dose to personnel in the x-ray room. With regard to radiation safety, increases in kVp are associated with less potential scatter radiation exposure compared to comparable increases in mAs.

Deep Learning Methods in the Diagnosis of Sacroiliitis from Plain Pelvic Radiographs

Objectives The aim of this study is to develop a computer-aided diagnosis method to assist physicians in evaluating sacroiliac radiographs. Methods Convolutional neural networks, a deep learning method, were used in this retrospective study. Transfer learning was implemented with pre-trained VGG-16, ResNet-101 and Inception-v3 networks. Normal pelvic radiographs (n = 290) and pelvic radiographs with sacroiliitis (n = 295) were used for the training of networks. Results The training results were evaluated with the criteria of accuracy, sensitivity, specificity and precision calculated from the confusion matrix and AUC (Area under the ROC curve) calculated from ROC (receiver operating characteristic) curve. Pre-trained VGG-16 model revealed accuracy, sensitivity, specificity, precision and AUC figures of 89.9%, 90.9%, 88.9%, 88.9% and 0.96 with test images, respectively. These results were 84.3%, 91.9%, 78.8%, 75.6 and 0.92 with pre-trained ResNet-101, and 82.0%, 79.6%, 85.0%, 86.7% and 0.90 with pre-trained inception-v3, respectively. Conclusions Successful results were obtained with all three models in this study where transfer learning was applied with pre-trained VGG-16, ResNet-101 and Inception-v3 networks. This method can assist clinicians in the diagnosis of sacroiliitis, provide them with a second objective interpretation, and also reduce the need for advanced imaging methods such as magnetic resonance imaging (MRI).

Repeated Pelvic Radiographs in Infants, After Harness Treatment for Developmental Dysplasia of the Hip, Carry Very Low Radiation Risk

Objective There are no data on the effect of X-Ray irradiation to the vulnerable pelvic organs of babies during DDH follow-up. This study aims to calculate, for the first time, the radiation exposure to infants during follow-up for DDH harness treatment, and thus quantify the lifetime risk of malignancy. Methods Patients who had completed 5 years’ follow-up following successful Pavlik harness treatment were identified from the hospital DDH database. The radiation dose was extracted from the Computerised Radiology Information System database for every radiograph of every patient. The effective dose (ED) was calculated using conversion coefficients for age, sex and body region irradiated. Cumulative ED was compared to Health Protection Agency standards to calculate lifetime risk of malignancy from the radiographs. Results All radiographs of 40 infants, successfully treated in Pavlik harness for DDH, were assessed. The mean number of AP pelvis radiographs was 7.00 (range: 6–9, mode: 7). The mean cumulative ED was 0.25 mSv (Range: 0.11–0.46, SD: 0.07). This is far lower than the annual ‘safe’ limit for healthcare workers of 20 mSv and is categorised as “Very Low Risk”. Conclusion Clinicians involved in the treatment DDH can be re-assured that the cumulative radiation exposure from pelvic radiographs following Pavlik harness treatment is “Very Low Risk”. Whilst being mindful of any radiation exposure in children, this study provides a scientific answer that help addresses parental concerns.

Automatic Hip Detection in Anteroposterior Pelvic Radiographs—A Labelless Practical Framework

Automated detection of the region of interest (ROI) is a critical step in the two-step classification system in several medical image applications. However, key information such as model parameter selection, image annotation rules, and ROI confidence score are essential but usually not reported. In this study, we proposed a practical framework of ROI detection by analyzing hip joints seen on 7399 anteroposterior pelvic radiographs (PXR) from three diverse sources. We presented a deep learning-based ROI detection framework utilizing a single-shot multi-box detector with a customized head structure based on the characteristics of the obtained datasets. Our method achieved average intersection over union (IoU) = 0.8115, average confidence = 0.9812, and average precision with threshold IoU = 0.5 (AP50) = 0.9901 in the independent testing set, suggesting that the detected hip regions appropriately covered the main features of the hip joints. The proposed approach featured flexible loose-fitting labeling, customized model design, and heterogeneous data testing. We demonstrated the feasibility of training a robust hip region detector for PXRs. This practical framework has a promising potential for a wide range of medical image applications.

481 Improving the Quality of Pelvic Radiographs - Making A Difference One Picture at A Time

Inadequate pelvic radiographs can lead to missed pathology, necessitate repeat imaging, and subsequently compromise patient safety. The audit conducted aimed to assess and improve the quality of pelvic radiographs at our Trust against local and international guidelines. Retrospective analysis of pelvic radiographs over a one-month period using PACS at Colchester General Hospital was conducted. All pelvic radiographs were assessed according to International Guidelines (EUR 16250EN). Postoperative radiographs were measured against local guidelines. The results were then presented in the departmental meeting and a re-audit was performed in June 2020. A total of 190 pelvic radiographs were collected in September 2019. From the 23 postoperative radiographs, 9 did not include distal end of prosthesis. During the re-audit in June 2020 the same number of pelvic images were collected. Data showed that only 2 out of 29 postoperative images did not include the distal end of the prosthesis. The audit demonstrated need for improvement at our Trust. This was carried out through a presentation in the departmental meeting, highlighting areas that needed improvement. The re-audited results from June 2020 have shown an improvement in the quality of pelvic radiographs and have had direct implications in clinical outcomes.

The trochanteric double contour is a valuable landmark for assessing femoral offset underestimation on standard radiographs: a retrospective study

Background Inaccurate projection on standard pelvic radiographs leads to the underestimation of femoral offset—a critical determinant of postoperative hip function—during total hip arthroplasty (THA) templating. We noted that the posteromedial facet of the greater trochanter and piriformis fossa form a double contour on radiographs, which may be valuable in determining the risk of underestimating femoral offset. We evaluate whether projection errors can be predicted based on the double contour width. Methods Plain anteroposterior (AP) pelvic radiographs and magnetic resonance images (MRIs) of 64 adult hips were evaluated retrospectively. Apparent femoral offset, apparent femoral head diameter and double contour widths were evaluated from the radiographs. X-ray projection errors were estimated by comparison to the true neck length measured on MRIs after calibration to the femoral heads. Multivariate analysis with backward elimination was used to detect associations between the double contour width and radiographic projection errors. Femoral offset underestimation below 10% was considered acceptable for templating. Results The narrowest width of the double line between the femoral neck and piriformis fossa is significantly associated with projection error. When double line widths exceed 5 mm, the risk of projection error greater than 10% is significantly increased compared to narrower double lines, and the acceptability rate for templating drops below 80% (p = 0.02). Conclusion The double contour width is a potential landmark for excluding pelvic AP radiographs unsuitable for THA templating due to inaccurate femoral rotation.

Pelvic bone CT: can tin-filtered ultra-low-dose CT and virtual radiographs be used as alternative for standard CT and digital radiographs?

Objectives To 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). Methods CT 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. Results Dose 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. Conclusion Tin-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.