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PURPOSE: The purpose of this study was to compare the diagnostic performance of an artificial intelligence (AI) solution for the detection of fractures of pelvic, proximal femur or extremity fractures in adults with radiologist interpretation of radiographs, using standard dose CT examination as the standard of reference. MATERIALS AND METHODS: This retrospective study included 94 adult patients with suspected bone fractures who underwent a standard dose CT examination and radiographs of the pelvis and/or hip and extremities at our institution between January 2022 and August 2023. For all patients, an AI solution was used retrospectively on the radiographs to detect and localize bone fractures of the pelvis and/or hip and extremities. Results of the AI solution were compared to the reading of each radiograph by a radiologist using McNemar test. The results of standard dose CT examination as interpreted by a senior radiologist were used as the standard of reference. RESULT: A total of 94 patients (63 women; mean age, 56.4 ± 22.5 [standard deviation] years) were included. Forty-seven patients had at least one fracture, and a total of 71 fractures were deemed present using the standard of reference (25 hand/wrist, 16 pelvis, 30 foot/ankle). Using the standard of reference, the analysis of radiographs by the AI solution resulted in 58 true positive, 13 false negative, 33 true negative and 15 false positive findings, yielding 82 % sensitivity (58/71; 95 % confidence interval [CI]: 71-89 %), 69 % specificity (33/48; 95 % CI: 55-80 %), and 76 % accuracy (91/119; 95 % CI: 69-84 %). Using the standard of reference, the reading of the radiologist resulted in 65 true positive, 6 false negative, 42 true negative and 6 false positive findings, yielding 92 % sensitivity (65/71; 95 % CI: 82-96 %), 88 % specificity (42/48; 95 % CI: 75-94 %), and 90 % accuracy (107/119; 95 % CI: 85-95 %). The radiologist outperformed the AI solution in terms of sensitivity (P = 0.045), specificity (P = 0.016), and accuracy (P < 0.001). CONCLUSION: In this study, the radiologist outperformed the AI solution for the diagnosis of pelvic, hip and extremity fractures of the using radiographs. This raises the question of whether a strong standard of reference for evaluating AI solutions should be used in future studies comparing AI and human reading in fracture detection using radiographs.
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Background: Ultra-low dose computed tomography (ULD-CT) was shown to be a good alternative to digital radiographs in various locations. This study aimed to assess the diagnostic sensitivity and specificity of ULD-CT versus digital radiographs in patients consulting for extremity traumas in emergency room. Methods: Digital radiography and ULD-CT scan were performed in patients consulting at the emergency department (February-August 2018) for extremity traumas. Fracture detection was evaluated retrospectively by two blinded independent radiologists. Sensitivity and specificity were evaluated using best value comparator (BVC) and a Bayesian latent class model (LCM) approaches and clinical follow-up. Image quality, quality diagnostic and diagnostic confidence level were evaluated (Likert scale). The effective dose received was calculated. Results: Seventy-six consecutive patients (41 men, mean age: 35.2±13.2 years), with 31 wrists/hands and 45 ankles/feet traumas were managed by emergency physicians. According to clinical data, radiography had 3 false positive and 10 false negative examinations, and ULD-CT, 2 of each. Radiography and ULD-CT specificities were similar; sensitivities were lower for radiography, with BVC and Bayesian. With Bayesian, ULD-CT and radiography sensitivities were 90% (95% CI: 87-93%) and 76% (95% CI: 71-81%, P<0.0001) and specificities 96% (95% CI: 93-98%) and 93% (95% CI: 87-97%, P=0.84). The inter-observer agreement was higher for ULD-CT for all subjective indexes. The effective dose for ULD-CT and radiography was 0.84±0.14 and 0.58±0.27 µSv (P=0.002) for hand/wrist, and 1.50±0.32 and 1.44±0.78 µSv (P=NS) for foot/ankle. Conclusions: With an effective dose level close to radiography, ULD-CT showed better detection of extremities fractures in the emergency room and may allow treatment adaptation. Further studies need to be performed to assess impact of such examination in everyday practice. Trial Registration: ClinicalTrials.gov Identifier: NCT04832490.
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PURPOSE: To compare the organ-dose and effective-dose (E) delivered to the patient during percutaneous vertebroplasty (PVP) of one thoracic or lumbar vertebra performed under CT guidance or using a fixed C-arm. METHODS: Consecutive adult patients undergoing PVP of one vertebra under CT-guidance, with optimized protocol and training of physicians, or using a fixed C-arm were retrospectively included from January 2016 to June 2017. Organ-doses were computed on 16 organs using CT Expo 2.4 software for the CT procedures and PCXMC 2.0 for the fixed C-arm procedures. E was also computed with both software. Dosimetric values per anatomic locations for all procedures were compared using the paired Mann-Whitney-Wilcoxon test. RESULTS: In total, 73 patients were analysed (27 men and 46 women, mean age 78 ± 10 years) among whom 35 (48%) underwent PVP under CT guidance and 38 (52%) PVP using a fixed C-arm. The median E was 11.31 [6.54; 15.82] mSv for all PVPs performed under CT guidance and 5.58 [3.33; 8.71] mSv for fixed C-arm and the differences was significant (p<0.001). For lumbar PVP, the organ doses of stomach, liver and colon were significantly higher with CT-scan than with the fixed C-arm: 97% (p=0.02); 21% (p=0.099) and 375% (p=0.002), respectively. For thoracic PVP, the lung organ dose was significantly higher with CT-scan than with the fixed C-arm (127%; p<0.001) and the oesophagus organ doses were not significantly different (p = 0.626). CONCLUSION: This study showed that the E and the organ dose on directly exposed organs were both higher for PVP performed under CT-guidance than with the fixed C-arm.