Contemporary ultrasound, computed tomography, or magnetic resonance imaging for acute appendicitis diagnosis in children and adolescents: systematic review and meta-analysis.

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Diana Isabel Castro-Luna, Juan D. Porras-Hernandez, Jose Andres Flores-Garcia, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6100084/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 09 May, 2025 Read the published version in Pediatric Radiology → Version 1 posted 11 You are reading this latest preprint version Abstract Background Advances in ultrasound (US), computed tomography (CT), and magnetic resonance imaging (MRI) technology and protocols have improved their accuracy for diagnosing acute appendicitis (AP) in children. Objective Determine sensitivity, specificity, and diagnostic odds ratios (DOR) of the latest US, CT, and MRI studies for AP in pediatric patients. Materials and methods PubMed, MEDLINE, BVS, OVID, Web of Science, and Trip Database (Jan 2015-May 2024), were searched for studies in patients 2 to 21 years old with suspected AP. Histopathology and clinical follow-up were the standard tests. Those with insufficient data for a 2x2 contingency table were excluded. QUADAS-2 directed risk of bias assessment. Data were extracted for meta-analysis. Results This systematic review of 37 articles included 22 conventional US studies (20,897 patients), 4 point-of-care US (POCUS) studies (280), 4 CT studies (1,389), and 13 MRI studies (2,630). Pooled sensitivity, specificity and DOR were: conventional US: 0.93 (95%CI [0.87, 0.96]), 0.89 (95%CI [0.80, 0.95]), 115.23 (95%CI [-32.88, 263.34]); POCUS: 0.80 (95%CI [0.61, 0.91]), 0.93 (95%CI [0.83, 0.98]), 53.97 (95%CI [-39, 146.94]); CT: 0.96 (95%CI [0.93, 0.97]), 0.98 (95%CI [0.96, 0.98]), 864.43 (95%CI [264.02, 1,464.84]); MRI: 0.96 (95%CI [0.94, 0.97]), 0.98 (95%CI [0.96, 0.99]), 1,030.42 (95%CI [222.05, 1,838.8]). No statistically significant differences were found (p = 0.07). Discussion Studies were heterogeneous in flow, timing, and follow-up. Nevertheless, all imaging modalities had high diagnostic performance. Conclusion Conventional US is an accurate first-line option; MRI is powerful when available. POCUS may help if it reduces equivocal results, while CT is discouraged due to radiation. Registration PROSPERO: CRD42024538086. May, 5 th , 2024. Retrospectively registered. PROSPERO registration name: Ultrasound, computed tomography or magnetic resonance imaging for diagnosing acute appendicitis in children and adolescents. Appendicitis Child Ultrasonography Tomography Magnetic Resonance Imaging Meta-Analysis Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Acute appendicitis (AP) is the most common surgical emergency among children, with a lifetime risk of approximately 7% in the general population [ 1 ]. Diagnosing AP in pediatric patients remains challenging, as nearly 50% of cases lack a classic clinical presentation during initial evaluation. [2] Over the past decade, advancements in clinical imaging and epidemiology have significantly improved the diagnostic accuracy of ultrasound (US), computed tomography (CT), and magnetic resonance imaging (MRI). Strategic application of these modalities has the potential to reduce the rates of unnecessary appendectomies to historically low levels. In pediatric populations, US is the preferred imaging modality due to its wide availability, safety, cost-effectiveness, and reasonable diagnostic accuracy [3]. It avoids ionizing radiation and allows real-time or sequential imaging. However, its accuracy is highly operator-dependent, leading to variability in diagnostic outcomes [4]. Up to 40% of US in suspected AP can be nondiagnostic, requiring further imaging [5]. Recent interest has focused on the role of point-of-care ultrasound (POCUS) as a supplementary tool in the diagnostic pathway. Technological advancements have also enhanced the capabilities of CT and MRI. Modern ultra-fast imaging techniques allow these modalities to produce highly accurate results within seconds, improving diagnostic precision and patient tolerance without requiring anesthesia. For children, minimizing radiation exposure is crucial. Single-phase contrast-enhanced, thin-slice (1-3mm), low-dose CT protocols (1–3.3 mSv compared to the traditional 16 mSv) have substantially reduced radiation risks [6], while MRI offers a high-precision, radiation-free alternative. However, MRI’s limited availability and higher costs remain significant drawbacks. Since the last comprehensive reviews of the diagnostic accuracy of US, CT, and MRI in pediatric AP in 2016 and 2018 [7, 8], new evidence has emerged. This study aims to evaluate the current diagnostic performance of these imaging modalities, reflecting recent technological advancements and their application in the care of pediatric acute appendicitis. Materials and Methods Study Design This study adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines [9]. As a secondary analysis of previously published data, no ethical approval was required. Eligibility Criteria Studies were included if they met the following criteria: Reported on the diagnostic accuracy of US, CT, or MRI. Included patients under 18 years of age presenting to an emergency department with acute abdominal pain suspicious of acute appendicitis. Studies with up to 5% of participants aged over 18 years were eligible if the maximum age did not exceed 21 years. Compared imaging findings with surgical or pathological reports and/or clinical follow-up as the reference standard. Employed a prospective or retrospective observational study design (cohort or cross-sectional) or were randomized diagnostic accuracy studies. Provided sufficient data to construct a 2x2 contingency table. Were available in full text, in any language. Reported specific imaging criteria for diagnosing appendicitis. Studies were excluded if they: Included only patients who underwent surgery. Focused on general abdominal pain without prior suspicion of appendicitis. Were case reports, case-control studies, letters to the editor, or other commentary formats. Studies with insufficient data to construct a 2x2 contingency table. Participants Eligible studies included patients aged 2–21 years presenting to emergency departments at secondary or tertiary care centers with right lower quadrant abdominal pain suggestive of acute appendicitis. Index Tests US: Includes a subgroup of point-of-care US (POCUS), performed by non-radiologist clinicians for direct patient assessment. CT MRI Target Condition The target condition was acute appendicitis, categorized as either present or absent. No distinction was made between simple and complicated cases. Reference Standard The reference standard was histological examination of the appendix and/or surgical findings in patients undergoing appendectomy. For non-operated patients, the absence of appendicitis was confirmed through clinical follow-up. Search Strategy Systematic searches were conducted in PubMed, MEDLINE, BVS, Ovid, Web of Science, and Trip Database. The search period spanned January 1, 2015, to May 31, 2024. Search strategies used a combination of Medical Subject Headings (MeSH) and free-text terms. Reference lists of relevant articles and systematic reviews were also screened. The search strategies are reported in Online Resource 1. Data Collection and Analysis Study Selection Two reviewers independently screened titles and abstracts using the search strategy. Full-text reviews determined inclusion, with disagreements resolved through discussion or by a third reviewer. Data Extraction Two reviewers independently extracted data using a standardized form. Information included publication date, study design, clinical setting, selection criteria, patient demographics, and outcomes. Zotero® was used for bibliographic management. Quality Assessment Methodological quality was evaluated using the Quality Assessment of Diagnostic Studies-2 (QUADAS-2) [10] tool by two independent reviewers. Discrepancies were resolved through discussion or consultation with a third reviewer. Results were summarized in tabular format, detailing the risk of bias across four domains. Statistical Analysis and Synthesis Statistical analyses followed Deek and Harrer´s recommendations [ 11 ]. Sensitivity and specificity estimates were visualized using summary receiver operating characteristic (sROC) plots generated in Review Manager 5. Summary estimates of sensitivity and specificity were calculated using a bivariate random-effects model to account for heterogeneity. Meta-regression analyses explored the influence of diagnostic protocol variations. Covariates were added individually, assuming equal variance for random effects. Analyses were conducted using “mada”, “meta”, “altmeta”, “lme4”, “dplyr” “msm”,“Imtest” packages in R version 4.4.2, adhering to the Cochrane Handbook for Systematic Reviews of Diagnostic Test Accuracy [11–13]. Post-test probabilities of appendicitis were calculated for positive and negative test results based on pre-test -probability percentiles (25th, median, 75th, and maximum). Handling Multiple Estimates For studies reporting multiple diagnostic criteria or observer-specific data, estimates with the greatest clinical homogeneity were prioritized. Observer-specific results were averaged if overall outcomes were unavailable. Heterogeneity Assessment Meta-regression analyses investigated potential sources of heterogeneity in diagnostic performance. Sensitivity Analysis Sensitivity analyses evaluated the impact of methodological quality on pooled sensitivity and specificity estimates. Reporting Bias Assessment of reporting bias was not performed. Results Study Selection Our systematic literature search identified 4,633 relevant studies. After applying our inclusion and exclusion criteria, we included 37 full-text articles for analysis (Fig. 1 ). Among these, 17 studies reported exclusively on ultrasound (US) [14–30], 2 on point-of-care ultrasound (POCUS) [31,32], 2 on computed tomography (CT) [33,34], and 10 on magnetic resonance imaging (MRI) [35–44]. Additionally, 6 studies evaluated two imaging modalities concurrently: 2 combined US and POCUS [45,46], 2 combined MRI and US [47,48], 1 examined both MRI and CT [49], and 1 assessed CT and US [50]. Study Characteristics The characteristics of the included studies are summarized in Table 1 . Table 1 Characteristics of included studies: US, POCUS, CT and MRI Modality study Design Mean age Sample size male/female Details of machine Contrast Results True-positives False-positives False-negatives True-negatives US Arslan, 2018 14 Prospective 9.5 122/103 US (L 13 MHz) no 91 5 4 125 Ashjaei, 2022 15 Prospective 8 37/71 US (L 7–10 MHz) no 82 7 2 17 Atta, 2015 16 Retrospective not reported 512 US (Unclear) no 127 3 21 80 Austin Page, 2020 17 Retrospective 10.4 425/633 US (unclear) no 309 151 74 524 Aydin, 2017 18 Prospective 11.1 163/125 US (unclear) no 105 31 14 62 Bachur, 2015 19 Retrospective 11.7 634/94 US (unclear) no 148 29 12 379 Cundy, 2016 20 Retrospective 11.5 1727/2072 US(unclear) no 998 39 12 311 Darbyshire, 2023 21 Retrospective 11 106/87 US (unclear) no 65 1 7 96 Dibble 2018 47 Retrospective 11.2 1905 US (L 6–15 MHz and/or 9 MHz) no 386 44 5 1470 Epifanio, 2016 22 Prospective 9.15 102 US ( L5- 7.5-MHz) no 57 3 0 34 Ghani, 2022 23 Retrospective 14 35/65 US (unclear) no 16 1 4 79 Hajalioghli, 2020 24 Prospective 8 74/47 US (L 5–14 MHz, C 5–9 MHz) no 54 3 2 62 Malia, 2019 25 Prospective 10.2 406/356 US (Unclear) no 225 43 492 2 Nicole 2018 45 Prospective 10.5 65/52 US (unclear) no 47 5 4 61 Reddan, 2019 26 Prospective 9.1 121/109 US (Unclear) no 40 15 171 4 Roberts, 2024 27 Prospective 10.8 3825/4730 US (unclear) no 1802 276 60 6417 Schuh, 2015 28 Prospective 10.4 143/151 US (L 7–14 MHz) no 89 10 1 71 Schuh 2023 48 Prospective 10.03 624 US (L7- to 14-MHz, C 3.5–7-MHz) no 119 15 3 232 Soundappan, 2018 46 Prospective 10 35/30 US (L 2–5 MHz, 5–8 MHz, 6–13 MHz) no 21 0 1 32 Yong Yi, 2017 50 Retrospective 6.85 189/295 US (Unclear) yes 38 3 2 12 Zourari, 2016 29 Prospective 8.54 170/122 US (unclear) no 109 10 23 150 Zourari, 2024 30 Prospective 9.4 247/164 US (unclear) no 210 25 8 168 POCUS Doniger, 2016 31 Prospective 10.7 20/20 US (L 8–10 MHz) no 15 3 1 21 Nicole, 2018 45 Prospective 10.5 65/52 US (unclear) no 27 12 24 54 Soundappan, 2018 46 Prospective 10 35/30 US (L 2–5 MHz, 5–8 MHz, 6–13 MHz) no 23 1 5 33 Wyrick, 2015 32 Prospective 9.6 32/26 US (L 6–13 MHz) no 27 0 4 27 CT Callahan, 2015 33 Retrospective 11.5 Before CT dose reduction 107/137 After CT dose reduction 105/145 Helical CT yes 131 9 6 348 Didier, 2015 34 Retrospective 9.4 Before CT dose reduction 86/192 After CT dose reduction 86/194 Helical CT yes 103 6 2 275 Martin, 2018 49 Retrospective 12 10/15 Helical CT no 4 0 1 20 Yong Yi, 2017 50 Retrospective 7.3 189/295 Helical CT yes 137 1 8 84 MRI Covelli, 2019 35 Retrospective 9.9 247/328 1–5 and 3 T no 53 5 2 468 Dibble, 2018 47 Retrospective 11.2 77 3 T no 14 1 2 60 Didier, 2017 36 Retrospective 11.0 38/60 1.5 T no 31 3 2 62 Dillman 2015 37 Retrospective 11.5 47/56 1.5 and 3 T no 170 0 1 85 Heye, 2019 38 Retrospective 12 144/206 1–5 and 3 T no 59 6 2 283 James, 2020 39 Prospective 11 18/34 3 T no 21 4 2 25 Komanchuk, 2021 40 Prospective 11.9 45/57 1.5 T no 37 4 2 60 Kulaylat, 2015 41 Retrospective 11.3 227/283 1.5 and 3 T no 122 10 4 374 Lyons, 2017 42 Retrospective 12.7 47/65 1.5 T Yes/No 23 : 5 0 60 Martin, 2018 49 Retrospective 13 12/18 1.5 T no 9 1 1 19 Mushtaq, 2019 43 Retrospective 13 167/235 1.5 T no 95 3 2 302 Petkovska, 2016 44 Retrospective 12 150 1.5 and 3 T no 31 1 1 117 Schuh, 2023 48 Prospective 10.03 117 3 T no 12 1 0 101 Conventional US Group : Among the 22 studies utilizing conventional US [14–30, 45–48, 50], a total of 20,897 patients were included. One study evaluated strain elastography [14], while the remaining studies assessed standard US performed by a radiologist. The mean patient age was 10.1 ± 1.55 years. Eight studies used linear probes (2–15 MHz) [14,15,22,24,28,46–48], while two employed curved probes (3.5–9 MHz) [24,48]; the remaining studies did not specify probe type. Fourteen studies (63.3%) had a prospective design, while the rest were retrospective. Seven studies (31.8%) were conducted in low- or middle-income countries, while the remaining were from high-income settings. The mean prevalence of appendicitis was 39.25% (95% CI: 32.38–46.13), with a mean negative appendectomy rate of 11% (95% CI: 3.42–19.55) across 15 studies [15,16,18–21,23–30,46]. The mean equivocal rate was 14.8% (95% CI: 5.26–24.25) [14–30]. POCUS Group : This group included 4 studies [31,32,45,46], comprising 280 patients. The mean age was 10.2 ± 0.5 years. Three studies utilized linear probes (2–13 MHz) [31,32,46], while one did not specify probe type [45]. All studies were prospective and conducted in high-income countries. The mean prevalence of appendicitis was 45.47% (95% CI: 36.43–54.52). The mean negative appendectomy rate, reported in 2 studies, was 4.7% (95% CI: -55.25–64.69) [31,46], while the mean equivocal rate was 15.9% (95% CI: -29.90–61.65) [31,32,45,46]. CT Group : This subgroup included 4 studies [33,36,49,50], with a total of 1,389 patients. The mean age was 10.1 ± 2.15 years. All studies utilized helical CT; three employed contrast-enhanced CT [33,34,50], while one did not [49]. Three studies assessed the diagnostic performance of low-dose radiation CT compared to standard-dose protocols [33,34,50]. All studies were retrospective and conducted in high-income countries. The mean prevalence of appendicitis was 33.8% (95% CI: 5.14–62.46). The negative appendectomy rate, reported in one study, was 4.5% [33]. Three studies reported no equivocal results, while one reported an equivocal rate of 3.6%, yielding an overall equivocal rate of 0.9% (95% CI: -1.96–3.76) [33,34,49,50]. MRI Group : This group included 13 studies [35–44,47–49], encompassing 2,630 patients. The mean age was 11.5 ± 0.9 years. Five studies utilized 1.5–3.0 T MRI systems [35,37,38,41,44], three used exclusively 3.0 T systems [39,47,48], and five used 1.5 T systems [36,40,42,43,49]. Twelve studies did not use contrast, while one analyzed the same population with and without contrast [42]. Three studies (23%) were prospective, while the remainder were retrospective. Only one study (7.6%) was conducted in a low- or middle-income country, with the rest performed in high-income settings. The mean prevalence of appendicitis was 25.4% (95% CI: 18.97–31.86). The mean negative appendectomy rate, reported in 7 studies, was 9.9% (95% CI: 2.54–17.23) [36–41,44]. The mean equivocal rate was 8.6% (95% CI: -1.31–18.57) [35–44,47–49]. Quality Assessment The methodological quality of the included studies was assessed using the QUADAS-2 tool (Fig. 2 ) [10]. Patient Selection Bias Among the US and POCUS studies, six studies [25,26,29,30,32,47] had a high risk of bias due to restricted patient selection criteria, including studies that evaluated patients only during specific hours [25,47], those that included only pediatric surgical unit admissions [26], and studies that assessed patients exclusively after surgical consultation [29,32] or when the appendix was visualized [30]. All were considered to have high applicability concerns. Among CT studies, one study [49] restricted evaluation to specific hours. In the MRI group, nine studies [35,37–40,42,47–49] evaluated patients with equivocal US results as part of a diagnostic pathway. Index Test Bias Two US studies [21,23] had an index test bias due to the absence of pre-specified diagnostic criteria, leading to high applicability concerns. Reference Standard Bias Five studies [14,20,32,41,50] used histology reports without a clearly defined follow-up period as the reference standard, leading to high applicability concerns. Most other studies employed histology or surgical reports, but follow-up time was generally unspecified. Timing of Index Test and Surgery Only seven studies [18,20,22,28,32,37,44] reported the time between the index test and surgery; for the remaining studies, this time interval was unclear. Quantitative Synthesis A total of 21 studies contributed to the quantitative synthesis, categorized into four study subgroups: 21 studies on conventional US (excluding one elastography study due to differing imaging targets and diagnostic criteria [14]), 4 studies on POCUS, 4 on CT, and 13 on MRI. The meta-analytic synthesis of diagnostic accuracy for each modality is presented in Table 2 . Among the four modalities, conventional US exhibited the narrowest confidence intervals in diagnostic performance (Fig. 3 ). Conventional US (I 2 = 95%), and POCUS studies (I 2 = 79.7%) had the highest heterogeneity. Whereas CT (I 2 = 0%, 95%CI: 0-67.6%), and MRI studies (I 2 = 35.4%) had the lowest heterogeneity. Table 2 Meta-analysis of diagnostic performance of each imaging modality. Imaging modality Sensitivity (95%CI) Specificity (95%CI) DOR (95%CI) LR + (95%CI) LR- (95%CI) Conventional US 0.93 (0.87, 0.96) 0.89 (0.80, 0.95) 115.23 (-32.88,263.34) 8.81 (2.77,14.84) 0.08 (0.02,0.13) POCUS 0.80 (0.61, 0.91) 0.93 (0.83, 0.98) 53.97 (-39, 146.94) 11.83 (-1.22,24.88) 0.22 (0.05,0.39) CT 0.96 (0.93, 0.97) 0.98 (0.96, 0.98) 864.43 (264.02,1464.84) 38.44 (19.83,57.06) 0.04 (0.02,0.07) MRI 0.96 (0.94, 0.97) 0.98 (0.96, 0.99) 1030.42 (222.05,1838.8) 41.20 (19.21,63.19) 0.04 (0.02,0.06) DOR = diagnostic odds ratio; LR + = positive likelihood ratio; LR-= negative likelihood ratio. Figure 4 shows SROC curve fitting of the imaging modalities. This fitting was performed using bivariate models, and models were compared using the likelihood ratio test, yielding a p-value of 0.07, indicating no statistically significant differences in sensitivity and specificity across the diagnostic tests. Additionally, graphical verification showed overlapping confidence intervals for sensitivity and specificity among the included tests (Fig. 4). Discussion Summary of Main Results Our meta-analysis of 21 conventional US studies demonstrated a pooled sensitivity of 0.95 (95% CI: 0.93–0.97) and a pooled specificity of 0.93 (95% CI: 0.90–0.95). While variations in protocol design and risks of bias across QUADAS-2 domains may have influenced these estimates, our findings are consistent with previous meta-analyses, which reported pooled sensitivity of 0.91 (95% CI: 0.83–0.95) [7] and specificity of 0.97 (95% CI: 0.96–0.97) [8]. These results reinforce the high diagnostic accuracy of conventional US performed by a radiologist for evaluating pediatric patients with suspected AP. US remains the preferred first-line imaging modality due to its safety, low cost, and wide availability, typically performed using a high-frequency linear transducer (7.5–12 MHz) with a graded compression technique [51]. Our subgroup meta-analysis of four POCUS studies yielded a pooled sensitivity of 0.80 (95% CI: 0.61–0.91) and a specificity of 0.93 (95% CI: 0.83–0.98). The wide confidence intervals suggest considerable variability in operator performance. For example, one study assessed clinicians after only 30 minutes of US training [45], while another involved a surgeon with extensive US experience [32]. The broad SROC curve further supports this operator-dependent variability. Our results align with those of Benabbas et al., who reported a pooled sensitivity of 0.86 (95% CI: 0.79–0.91) and specificity of 0.91 (95% CI: 0.87–0.94) for emergency department POCUS [52]. Given its potential advantages, POCUS is a promising imaging modality. If operator dependency can be minimized through standardized training and competency-based assessments, POCUS may significantly enhance diagnostic access to pediatric patients with suspected AP worldwide. The meta-analysis of four CT studies found a pooled sensitivity of 0.96 (95% CI: 0.93–0.97) and specificity of 0.98 (95% CI: 0.96–0.98). The included studies predominantly employed low-dose radiation protocols, with three using contrast-enhanced CT and one non-contrast protocol. The non-contrast study, which had a small sample size, reported a sensitivity of 0.80 and specificity of 1.00 [49]. Our findings are consistent with previous reviews, where the highest reported pooled sensitivity was 0.96 (95% CI: 0.93–0.97) and specificity was 0.94 (95% CI: 0.92–0.95) [7]. In children with suspected AP, low-dose CT has a high diagnostic performance, even without contrast. Despite its high diagnostic accuracy, CT should be reserved for cases in which US is inconclusive or when complications such as perforation or abscess formation are suspected [6]. Our meta-analysis of 13 MRI studies demonstrated a pooled sensitivity of 0.96 (95% CI: 0.94–0.97) and specificity of 0.98 (95% CI: 0.96–0.99), with these values obtained using non-contrast, non-sedation, and ultra-fast MRI protocols [35–44,47–49]. These results are comparable to previously reported pooled sensitivity of 0.98 (95% CI: 0.96–0.99) [8] and specificity of 0.97 (95% CI: 0.92–0.99) [7]. MRI has emerged as a powerful diagnostic tool in pediatric AP, particularly in specialized centers with access to advanced imaging technology. Its utilization is expected to expand in the near future [53]. Strengths and Limitations of the Review This systematic review employed a comprehensive literature search across multiple databases, including non-English publications. However, we did not include gray literature, which may have introduced publication bias. Of the 43 included studies, 21 (48.8%) were prospectively designed, yet none were randomized. The overall methodological quality of the included studies was good, with minimal patient selection bias. The primary risk of selection bias was observed in MRI studies performed as part of predefined clinical pathways following equivocal US results. Applicability concerns were generally low. However, some studies lacked clearly defined diagnostic criteria or did not specify follow-up length as part of the reference standard. Flow and timing bias was present in several studies, as the time interval between the index and reference tests was not consistently reported. Follow-up methodologies varied, with most studies relying on clinical chart reviews and only a few prospectively contacting patients. The shortest reported follow-up was three days, while the longest was six months. Overall, 26 out of 43 studies (61.9%) had a follow-up period exceeding two weeks. Despite these limitations, our review included a robust pool of high-quality studies. Implications for Clinical Practice and Future Research This review confirms that all three imaging modalities—US, CT, and MRI—demonstrate high diagnostic accuracy for pediatric AP, with CT and MRI exhibiting the highest sensitivity and specificity. However, due to the risks associated with ionizing radiation, CT use should be limited, even with low-dose protocols. US remains the preferred first-line imaging modality given its strong diagnostic performance, broad availability, and favorable safety profile. MRI serves as an excellent second-line option, particularly for cases in which US findings are inconclusive. MRI offers high diagnostic accuracy without requiring sedation, contrast, or radiation exposure. However, its widespread adoption is limited by cost, access, and protocol variability. International efforts to standardize pediatric MRI protocols are promising and should be further encouraged [54]. Although POCUS demonstrated lower sensitivity than conventional US, its high specificity and real-time bedside applicability make it a valuable tool, particularly for well-trained clinicians. Implementing structured training programs with competency-based assessments may significantly enhance its diagnostic reliability. Optimizing clinical pathways that strategically incorporate US and MRI while minimizing reliance on CT could improve diagnostic precision and patient outcomes while reducing radiation exposure. Integrating POCUS within these pathways, alongside ongoing professional education, could further enhance diagnostic efficiency and access. As an inflammatory condition, AP diagnosis relies on imaging modalities that detect inflammation-related changes. This is particularly relevant when the appendix is not visualized, as the presence of associated inflammatory signs should guide diagnostic interpretation. If inflammatory signs are present, a positive diagnosis may be considered; conversely, their absence may support a negative diagnosis [26,36]. Future advancements in pediatric AP imaging should focus on standardizing protocols for US, POCUS, and MRI. Additionally, artificial intelligence (AI) may play a role in improving diagnostic accuracy, facilitating high-precision imaging interpretation, and streamlining clinical decision-making. AI-driven approaches have the potential to enhance imaging-based AP diagnosis by increasing accuracy, expanding access, and simplifying diagnostic pathways. Further research should explore AI applications in this domain. Conclusion Our review confirms that contemporary imaging modalities offer high diagnostic accuracy for pediatric AP. US should remain the first-line imaging modality due to its accuracy, safety, and accessibility. POCUS may serve as a valuable diagnostic tool, particularly with improved training and standardization. CT, while highly accurate, carries radiation risks and should be used judiciously. MRI presents a high-accuracy, radiation-free alternative but remains limited by cost and availability. Future efforts should focus on enhancing US and POCUS diagnostic accuracy, expanding MRI access, and integrating AI-driven diagnostic tools to improve efficiency and reliability in pediatric AP imaging. Declarations Competing interests: The authors have no financial, nor non-financial competing interests to declare that are relevant to the content of this article. Funding declaration: The present study had no funding. Author Contribution Idea of the study: J.D.P.H, D.I.C.L., M.P.P.Literature search and analysis: D.I.C.L., J.D.P.H., J.A.F.G, M.F.S.M., M.P.P. Draft and/or critically revised work: J.D.P.H., D.I.C.L., M.P.P., J.A.F.G., M.F.S.M., P.D.S. Acknowledgement The authors express their gratitude to Maria Isabel Patiño Lopez and Saul Valencia Guzman for their assistance in search strategy design, execution, and database management. Data Availability Data is provided within the manuscript or supplementary information files. References Teoule P, de Laffolie J, Rolle U, Reibfelder C (2020) Acute appendicitis in childhood and adulthood: an everyday clinical challenge. 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Acad Emerg Med 22:406–14. https://doi.org/10.1111/acem.12631 Zouari M, Jallouli M, Louati H, Kchaou R, Chtourou R, Kotti A, Dhaou MB, Zitouni H, Mhiri R (2016) Predictive value of C-reactive protein, ultrasound and Alvarado score in acute appendicitis: a prospective pediatric cohort. Am J Emerg Med 34:189–192. https://doi.org/10.1016/j.ajem.2015.10.004 Zouari M, Issaoui A, Hbaieb M, Belhajmansour M, Meddeb S, Ben Dhaou M, Mhiri R (2024) Predictive factors of acute appendicitis in children with non-visualized appendix on ultrasound: A prospective cohort study. Surg Infect 25:26–31. https://doi.org/10.1089/sur.2023.295 Doniger SJ, Kornblith A (2016) Point-of-care ultrasound integrated into a staged diagnostic algorithm for pediatric appendicitis. Pediatr Emerg Care 34:109–115. https://doi.org/10.1097/PEC.0000000000000773 Wyrick DL, Smith SD, Burford JM, Dassinger MS (2015) Surgeon-performed ultrasound: accurate, reproducible, and more efficient. 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Am J Roentgenol 212:180–187. https://doi.org/10.2214/AJR.18.19825 Didier RA, Hopkins KL, Coakley FV, Krishnaswami S, Spiro DM, Foster BR (2017) Performance characteristics of magnetic resonance imaging without contrast agents or sedation in pediatric appendicitis. Pediatr Radiol 47:1312–1320. https://doi.org/10.1007/s00247-017-3897-7 Dillman JR, Gadepalli S, Sroufe NS, Davenport M, Smith E, Chong S, Mazza M, Strouse PJ (2016) Equivocal pediatric appendicitis: Unenhanced MR imaging protocol for nonsedated children-A clinical effectiveness study. Radiology 279:216–225. https://doi.org/10.1148/radiol.2015150941 Heye P, Saavedra JS, Victoria T, Laje P (2020) Accuracy of unenhanced, non-sedated MRI in the diagnosis of acute appendicitis in children. 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Can Assoc Radiol J 72:797–805. https://doi.org/10.1177/0846537121993797 Kulaylat AN, Moore MM, Engbrecht BW, Brian JM, Khaku A, Hollenbeak CS, Rocourt DV, Hulse MA, Olympia RP, Santos MC, Methratta ST, Dillon PW, Cilley RE (2015) An implemented MRI program to eliminate radiation from the evaluation of pediatric appendicitis. J Pediatr Surg 50:1359–1363. https://doi.org/10.1016/j.jpedsurg.2014.12.012 Lyons GR, Renjen P, Askin G, Giambrone AE, Beneck D, Kovanlikaya A (2017) Diagnostic utility of intravenous contrast for MR imaging in pediatric appendicitis. Pediatr Radiol 47:398–403. https://doi.org/10.1007/s00247-016-3775-8 Mushtaq R, Desoky SM, Morello F, Gilbertson-Dahdal D, Gopalakrishnan G, Leetch A, Vedantham S, Kalb B, Martin DR, Udayasankar UK (2019) First-line diagnostic evaluation with MRI of children suspected of having acute appendicitis. Radiology 291:170–177. https://doi.org/10.1148/radiol.2019181959 Petkovska I, Martin DR, Covington MF, Urbina S, Duke E, Daye ZJ, Stolz LA, Keim SM, Costello JR, Chundru S, Arif-Tiwari H, Gilbertson-Dahdal D, Gries L, Kalb B (2016) Accuracy of unenhanced MR imaging in the detection of acute appendicitis: Single-institution clinical performance review. Radiology 279:451–460. https://doi.org/10.1148/radiol.2015150468 Nicole M, Desjardins DM, Gravel J (2018) Bedside sonography performed by emergency physicians to detect appendicitis in children. EvidenceUpdates 25:1035–1041. https://doi.org/10.1111/acem.13445 Soundappan SS, Karpelowsky J, Lam A, Cass D (2018) Diagnostic accuracy of surgeon performed ultrasound (SPU) for appendicitis in children. J Pediatr Surg 53:2023–2027. https://doi.org/10.1016/j.jpedsurg.2018.05.014 Dibble EH, Swenson DW, Cartagena C, Baird GL, Herliczek TW (2018) Effectiveness of a staged US and unenhanced MR imaging algorithm in the diagnosis of pediatric appendicitis. Radiology 286:1022–1029. https://doi.org/10.1148/radiol.2017162755 Schuh S, Man C, Marie E, Alhashmi GHA, Halevy D, Wales PW, Singer-Harel D, Finkelstein A, Sweeney J, Doria AS (2023) Properties of ultrasound-rapid MRI clinical diagnostic pathway in suspected pediatric appendicitis-A prospective cohort study. Am J Emerg Med 71:217–224. https://doi.org/10.1016/j.ajem.2023.06.026 Martin JF, Mathison DJ, Mullan PC, Otero HJ (2018) Secondary imaging for suspected appendicitis after equivocal ultrasound: time to disposition of MRI compared to CT. Emerg Radiol 25:161–168. Yi DY, Lee KH, Park SB, Kim JT, Lee NM, Kim H, Yun SW, Chae SA, Lim IS (2017) Accuracy of low dose CT in the diagnosis of appendicitis in childhood and comparison with USG and standard dose CT. J Pediatr (Rio J) 93:625–631. https://doi.org/10.1016/j.jped.2017.01.004 Expert Panel on Gastrointestinal Imaging: Garcia EM, Camacho MA, Karolyi DR, Kim DH, Cash BD, Chang K, Feig BW, Fowler KJ, Kambadakone AR, Lambert DL, Levy AD, Marin D, Moreno C, Peterson CM, Scheirey, Siegel A, Smith MP, Weinstein S, Carucci L (2018) ACR Appropriateness Criteria® Right Lower Quadrant Pain-Suspected Appendicitis. J Am Coll Radiol 15:S373–S387. https://doi.org/10.1016/j.jacr.2018.09.033 Benabbas R, Hanna M, Shah J, Sinert R (2017) Diagnostic accuracy of history, physical examination, laboratory tests, and point-of-care ultrasound for pediatric acute appendicitis in the emergency department: A systematic review and meta-analysis. Acad Emerg Med 24:523–551. https://doi.org/10.1111/acem.13181 Janos S, Schooler GR, Ngo JS, Davis JT (2019) Free-breathing unsedated MRI in children: Justification and techniques. J Magn Reson Imaging 50:365–376. https://doi.org/10.1002/jmri.26644 Ferraciolli SF, Boechat MI, Shu Y, Anu M, Harris C, Vorstenbasch-Lynn EV, Kilborn T, Lam W, Ho ML, Kasznia-Brown J, Jaimes C, Michael SG (2025) International standardization of pediatric magnetic resonance imaging protocols: creation of the World Federation of Pediatric Imaging MR Protocols Committee. Pediatr Radiol. https://doi.org/10.1007/s00247-024-06154-6 Additional Declarations No competing interests reported. Supplementary Files OnlineResource1.docx Cite Share Download PDF Status: Published Journal Publication published 09 May, 2025 Read the published version in Pediatric Radiology → Version 1 posted Editorial decision: Revision requested 18 Mar, 2025 Reviews received at journal 11 Mar, 2025 Reviewers agreed at journal 05 Mar, 2025 Reviews received at journal 05 Mar, 2025 Reviewers agreed at journal 05 Mar, 2025 Reviews received at journal 03 Mar, 2025 Reviewers agreed at journal 28 Feb, 2025 Reviewers invited by journal 28 Feb, 2025 Editor assigned by journal 27 Feb, 2025 Submission checks completed at journal 27 Feb, 2025 First submitted to journal 24 Feb, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6100084","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":422981571,"identity":"7a4a8593-ad76-46d7-8c70-12ec99aa35c9","order_by":0,"name":"Diana Isabel Castro-Luna","email":"","orcid":"","institution":"Antala Kune, Hospital Angeles, Puebla, Mexico","correspondingAuthor":false,"prefix":"","firstName":"Diana","middleName":"Isabel","lastName":"Castro-Luna","suffix":""},{"id":422981572,"identity":"0e2a56ed-5874-418c-a00e-3586f0839f01","order_by":1,"name":"Juan D. 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The dotted ellipse denotes the 95% confidence region, while the dashed ellipse indicates the 95% prediction region.\u003c/p\u003e","description":"","filename":"Figure4.SROCcurveofimagingmodalities.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6100084/v1/da8323c817117eb926ce869d.jpg"},{"id":82537452,"identity":"cc419085-6e29-4e82-ba5e-e6875e8e4e47","added_by":"auto","created_at":"2025-05-12 16:06:51","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3078292,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6100084/v1/f83fb75a-9b70-4105-bcf8-80e306b354d5.pdf"},{"id":77704292,"identity":"c8245f73-cace-4d29-887b-31b88163ca06","added_by":"auto","created_at":"2025-03-04 11:45:43","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":16253,"visible":true,"origin":"","legend":"","description":"","filename":"OnlineResource1.docx","url":"https://assets-eu.researchsquare.com/files/rs-6100084/v1/937fd4e9cf1f00391c29b2d4.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Contemporary ultrasound, computed tomography, or magnetic resonance imaging for acute appendicitis diagnosis in children and adolescents: systematic review and meta-analysis.","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAcute appendicitis (AP) is the most common surgical emergency among children, with a lifetime risk of approximately 7% in the general population [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Diagnosing AP in pediatric patients remains challenging, as nearly 50% of cases lack a classic clinical presentation during initial evaluation. [2] Over the past decade, advancements in clinical imaging and epidemiology have significantly improved the diagnostic accuracy of ultrasound (US), computed tomography (CT), and magnetic resonance imaging (MRI). Strategic application of these modalities has the potential to reduce the rates of unnecessary appendectomies to historically low levels.\u003c/p\u003e \u003cp\u003eIn pediatric populations, US is the preferred imaging modality due to its wide availability, safety, cost-effectiveness, and reasonable diagnostic accuracy [3]. It avoids ionizing radiation and allows real-time or sequential imaging. However, its accuracy is highly operator-dependent, leading to variability in diagnostic outcomes [4]. Up to 40% of US in suspected AP can be nondiagnostic, requiring further imaging [5]. Recent interest has focused on the role of point-of-care ultrasound (POCUS) as a supplementary tool in the diagnostic pathway.\u003c/p\u003e \u003cp\u003eTechnological advancements have also enhanced the capabilities of CT and MRI. Modern ultra-fast imaging techniques allow these modalities to produce highly accurate results within seconds, improving diagnostic precision and patient tolerance without requiring anesthesia. For children, minimizing radiation exposure is crucial. Single-phase contrast-enhanced, thin-slice (1-3mm), low-dose CT protocols (1\u0026ndash;3.3 mSv compared to the traditional 16 mSv) have substantially reduced radiation risks [6], while MRI offers a high-precision, radiation-free alternative. However, MRI\u0026rsquo;s limited availability and higher costs remain significant drawbacks.\u003c/p\u003e \u003cp\u003eSince the last comprehensive reviews of the diagnostic accuracy of US, CT, and MRI in pediatric AP in 2016 and 2018 [7, 8], new evidence has emerged. This study aims to evaluate the current diagnostic performance of these imaging modalities, reflecting recent technological advancements and their application in the care of pediatric acute appendicitis.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Design\u003c/h2\u003e \u003cp\u003e This study adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines [9]. As a secondary analysis of previously published data, no ethical approval was required.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eEligibility Criteria\u003c/h3\u003e\n\u003cp\u003eStudies were included if they met the following criteria:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eReported on the diagnostic accuracy of US, CT, or MRI.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eIncluded patients under 18 years of age presenting to an emergency department with acute abdominal pain suspicious of acute appendicitis.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eStudies with up to 5% of participants aged over 18 years were eligible if the maximum age did not exceed 21 years.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eCompared imaging findings with surgical or pathological reports and/or clinical follow-up as the reference standard.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eEmployed a prospective or retrospective observational study design (cohort or cross-sectional) or were randomized diagnostic accuracy studies.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eProvided sufficient data to construct a 2x2 contingency table.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eWere available in full text, in any language.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eReported specific imaging criteria for diagnosing appendicitis.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eStudies were excluded if they:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eIncluded only patients who underwent surgery.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eFocused on general abdominal pain without prior suspicion of appendicitis.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eWere case reports, case-control studies, letters to the editor, or other commentary formats.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eStudies with insufficient data to construct a 2x2 contingency table.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e\n\u003ch3\u003eParticipants\u003c/h3\u003e\n\u003cp\u003eEligible studies included patients aged 2\u0026ndash;21 years presenting to emergency departments at secondary or tertiary care centers with right lower quadrant abdominal pain suggestive of acute appendicitis.\u003c/p\u003e \u003cp\u003e \u003cb\u003eIndex Tests\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eUS: Includes a subgroup of point-of-care US (POCUS), performed by non-radiologist clinicians for direct patient assessment.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eCT\u003c/p\u003e\u003c/li\u003e \u003cli\u003e\n\u003cp\u003eMRI\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \n\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eTarget Condition\u003c/h2\u003e \u003cp\u003eThe target condition was acute appendicitis, categorized as either present or absent. No distinction was made between simple and complicated cases.\u003c/p\u003e \u003cp\u003e \u003cb\u003eReference Standard\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe reference standard was histological examination of the appendix and/or surgical findings in patients undergoing appendectomy. For non-operated patients, the absence of appendicitis was confirmed through clinical follow-up.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eSearch Strategy\u003c/h2\u003e \u003cp\u003eSystematic searches were conducted in PubMed, MEDLINE, BVS, Ovid, Web of Science, and Trip Database. The search period spanned January 1, 2015, to May 31, 2024. Search strategies used a combination of Medical Subject Headings (MeSH) and free-text terms. Reference lists of relevant articles and systematic reviews were also screened. The search strategies are reported in Online Resource 1.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eData Collection and Analysis\u003c/h3\u003e\n\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eStudy Selection\u003c/h2\u003e \u003cp\u003eTwo reviewers independently screened titles and abstracts using the search strategy. Full-text reviews determined inclusion, with disagreements resolved through discussion or by a third reviewer.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eData Extraction\u003c/h2\u003e \u003cp\u003eTwo reviewers independently extracted data using a standardized form. Information included publication date, study design, clinical setting, selection criteria, patient demographics, and outcomes. Zotero\u0026reg; was used for bibliographic management.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eQuality Assessment\u003c/h2\u003e \u003cp\u003e Methodological quality was evaluated using the Quality Assessment of Diagnostic Studies-2 (QUADAS-2) [10] tool by two independent reviewers. Discrepancies were resolved through discussion or consultation with a third reviewer. Results were summarized in tabular format, detailing the risk of bias across four domains.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis and Synthesis\u003c/h2\u003e \u003cp\u003eStatistical analyses followed Deek and Harrer\u0026acute;s recommendations [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Sensitivity and specificity estimates were visualized using summary receiver operating characteristic (sROC) plots generated in Review Manager 5. Summary estimates of sensitivity and specificity were calculated using a bivariate random-effects model to account for heterogeneity.\u003c/p\u003e \u003cp\u003eMeta-regression analyses explored the influence of diagnostic protocol variations. Covariates were added individually, assuming equal variance for random effects. Analyses were conducted using \u0026ldquo;mada\u0026rdquo;, \u0026ldquo;meta\u0026rdquo;, \u0026ldquo;altmeta\u0026rdquo;, \u0026ldquo;lme4\u0026rdquo;, \u0026ldquo;dplyr\u0026rdquo; \u0026ldquo;msm\u0026rdquo;,\u0026ldquo;Imtest\u0026rdquo; packages in R version 4.4.2, adhering to the Cochrane Handbook for Systematic Reviews of Diagnostic Test Accuracy [11\u0026ndash;13].\u003c/p\u003e \u003cp\u003ePost-test probabilities of appendicitis were calculated for positive and negative test results based on pre-test -probability percentiles (25th, median, 75th, and maximum).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eHandling Multiple Estimates\u003c/h2\u003e \u003cp\u003eFor studies reporting multiple diagnostic criteria or observer-specific data, estimates with the greatest clinical homogeneity were prioritized. Observer-specific results were averaged if overall outcomes were unavailable.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eHeterogeneity Assessment\u003c/h2\u003e \u003cp\u003eMeta-regression analyses investigated potential sources of heterogeneity in diagnostic performance.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eSensitivity Analysis\u003c/h2\u003e \u003cp\u003eSensitivity analyses evaluated the impact of methodological quality on pooled sensitivity and specificity estimates.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eReporting Bias\u003c/h2\u003e \u003cp\u003eAssessment of reporting bias was not performed.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eStudy Selection\u003c/h2\u003e \u003cp\u003eOur systematic literature search identified 4,633 relevant studies. After applying our inclusion and exclusion criteria, we included 37 full-text articles for analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Among these, 17 studies reported exclusively on ultrasound (US) [14\u0026ndash;30], 2 on point-of-care ultrasound (POCUS) [31,32], 2 on computed tomography (CT) [33,34], and 10 on magnetic resonance imaging (MRI) [35\u0026ndash;44]. Additionally, 6 studies evaluated two imaging modalities concurrently: 2 combined US and POCUS [45,46], 2 combined MRI and US [47,48], 1 examined both MRI and CT [49], and 1 assessed CT and US [50].\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eStudy Characteristics\u003c/h2\u003e \u003cp\u003eThe characteristics of the included studies are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCharacteristics of included studies: US, POCUS, CT and MRI\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"11\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eModality study\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDesign\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMean age\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSample size male/female\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eDetails of machine\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eContrast\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c11\" namest=\"c8\"\u003e \u003cp\u003eResults\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003eTrue-positives\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003eFalse-positives\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003eFalse-negatives\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003eTrue-negatives\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"21\" rowspan=\"22\"\u003e \u003cp\u003eUS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eArslan, 2018\u003csup\u003e14\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eProspective\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e122/103\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eUS (L 13 MHz)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eno\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e125\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAshjaei, 2022\u003csup\u003e15\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eProspective\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e37/71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eUS (L 7\u0026ndash;10 MHz)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eno\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAtta, 2015\u003csup\u003e16\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRetrospective\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003enot reported\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e512\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eUS (Unclear)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eno\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e127\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e80\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAustin Page, 2020\u003csup\u003e17\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRetrospective\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e425/633\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eUS (unclear)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eno\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e309\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e151\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e524\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAydin, 2017\u003csup\u003e18\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eProspective\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e163/125\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eUS (unclear)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eno\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e105\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e62\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBachur, 2015\u003csup\u003e19\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRetrospective\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e634/94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eUS (unclear)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eno\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e148\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e379\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCundy, 2016\u003csup\u003e20\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRetrospective\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1727/2072\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eUS(unclear)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eno\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e998\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e311\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDarbyshire, 2023\u003csup\u003e21\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRetrospective\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e106/87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eUS (unclear)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eno\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e96\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDibble 2018\u003csup\u003e47\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRetrospective\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1905\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eUS (L 6\u0026ndash;15 MHz and/or 9 MHz)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eno\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e386\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1470\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEpifanio, 2016\u003csup\u003e22\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eProspective\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e102\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eUS ( L5- 7.5-MHz)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eno\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGhani, 2022\u003csup\u003e23\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRetrospective\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e35/65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eUS (unclear)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eno\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e79\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHajalioghli, 2020\u003csup\u003e24\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eProspective\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e74/47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eUS (L 5\u0026ndash;14 MHz, C 5\u0026ndash;9 MHz)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eno\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e62\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMalia, 2019\u003csup\u003e25\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eProspective\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e406/356\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eUS (Unclear)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eno\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e225\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e492\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNicole 2018\u003csup\u003e45\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eProspective\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e65/52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eUS (unclear)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eno\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e61\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReddan, 2019\u003csup\u003e26\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eProspective\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e121/109\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eUS (Unclear)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eno\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e171\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRoberts, 2024\u003csup\u003e27\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eProspective\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3825/4730\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eUS (unclear)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eno\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1802\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e276\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e6417\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSchuh, 2015\u003csup\u003e28\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eProspective\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e143/151\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eUS (L 7\u0026ndash;14 MHz)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eno\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e71\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSchuh 2023\u003csup\u003e48\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eProspective\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e624\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eUS (L7- to 14-MHz, C 3.5\u0026ndash;7-MHz)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eno\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e119\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e232\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSoundappan, 2018\u003csup\u003e46\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eProspective\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e35/30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eUS (L 2\u0026ndash;5 MHz, 5\u0026ndash;8 MHz, 6\u0026ndash;13 MHz)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eno\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYong Yi, 2017\u003csup\u003e50\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRetrospective\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e189/295\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eUS (Unclear)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eyes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eZourari, 2016\u003csup\u003e29\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eProspective\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e170/122\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eUS (unclear)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eno\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e109\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e150\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eZourari, 2024\u003csup\u003e30\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eProspective\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e247/164\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eUS (unclear)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eno\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e210\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e168\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003ePOCUS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDoniger, 2016\u003csup\u003e31\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eProspective\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e20/20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eUS (L\u0026nbsp; 8\u0026ndash;10 MHz)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eno\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNicole, 2018\u003csup\u003e45\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eProspective\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e65/52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eUS (unclear)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eno\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e54\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSoundappan, 2018\u003csup\u003e46\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eProspective\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e35/30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eUS (L 2\u0026ndash;5 MHz, 5\u0026ndash;8 MHz, 6\u0026ndash;13 MHz)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eno\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWyrick, 2015 \u003csup\u003e32\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eProspective\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e32/26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eUS (L 6\u0026ndash;13 MHz)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eno\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eCT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCallahan, 2015\u003csup\u003e33\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRetrospective\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBefore CT dose reduction 107/137\u003c/p\u003e \u003cp\u003eAfter CT dose reduction 105/145\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eHelical CT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eyes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e131\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e348\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDidier, 2015\u003csup\u003e34\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRetrospective\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBefore CT dose reduction 86/192\u003c/p\u003e \u003cp\u003eAfter CT dose reduction 86/194\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eHelical CT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eyes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e103\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e275\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMartin, 2018\u003csup\u003e49\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRetrospective\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10/15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eHelical CT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eno\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYong Yi, 2017\u003csup\u003e50\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRetrospective\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e189/295\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eHelical CT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eyes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e137\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e84\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"12\" rowspan=\"13\"\u003e \u003cp\u003eMRI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCovelli, 2019 \u003csup\u003e35\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRetrospective\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e247/328\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u0026ndash;5 and 3 T\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eno\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e468\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDibble, 2018\u003csup\u003e47\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRetrospective\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3 T\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eno\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDidier, 2017\u003csup\u003e36\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRetrospective\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e38/60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.5 T\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eno\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e62\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDillman 2015\u003csup\u003e37\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRetrospective\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e47/56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.5 and 3 T\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eno\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e170\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e85\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHeye, 2019\u003csup\u003e38\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRetrospective\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e144/206\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u0026ndash;5 and 3 T\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eno\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e283\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eJames, 2020\u003csup\u003e39\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eProspective\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e18/34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3 T\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eno\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKomanchuk, 2021\u003csup\u003e40\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eProspective\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e45/57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.5 T\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eno\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKulaylat, 2015\u003csup\u003e41\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRetrospective\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e227/283\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.5 and 3 T\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eno\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e122\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e374\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLyons, 2017\u003csup\u003e42\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRetrospective\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e47/65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.5 T\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eYes/No\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e: 5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMartin, 2018\u003csup\u003e49\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRetrospective\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12/18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.5 T\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eno\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMushtaq, 2019\u003csup\u003e43\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRetrospective\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e167/235\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.5 T\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eno\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e302\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePetkovska, 2016\u003csup\u003e44\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRetrospective\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e150\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.5 and 3 T\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eno\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e117\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSchuh, 2023\u003csup\u003e48\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eProspective\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e117\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3 T\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eno\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e101\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003eConventional US Group\u003c/em\u003e: Among the 22 studies utilizing conventional US [14\u0026ndash;30, 45\u0026ndash;48, 50], a total of 20,897 patients were included. One study evaluated strain elastography [14], while the remaining studies assessed standard US performed by a radiologist. The mean patient age was 10.1\u0026thinsp;\u0026plusmn;\u0026thinsp;1.55 years. Eight studies used linear probes (2\u0026ndash;15 MHz) [14,15,22,24,28,46\u0026ndash;48], while two employed curved probes (3.5\u0026ndash;9 MHz) [24,48]; the remaining studies did not specify probe type. Fourteen studies (63.3%) had a prospective design, while the rest were retrospective. Seven studies (31.8%) were conducted in low- or middle-income countries, while the remaining were from high-income settings. The mean prevalence of appendicitis was 39.25% (95% CI: 32.38\u0026ndash;46.13), with a mean negative appendectomy rate of 11% (95% CI: 3.42\u0026ndash;19.55) across 15 studies [15,16,18\u0026ndash;21,23\u0026ndash;30,46]. The mean equivocal rate was 14.8% (95% CI: 5.26\u0026ndash;24.25) [14\u0026ndash;30].\u003c/p\u003e \u003cp\u003e \u003cem\u003ePOCUS Group\u003c/em\u003e: This group included 4 studies [31,32,45,46], comprising 280 patients. The mean age was 10.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5 years. Three studies utilized linear probes (2\u0026ndash;13 MHz) [31,32,46], while one did not specify probe type [45]. All studies were prospective and conducted in high-income countries. The mean prevalence of appendicitis was 45.47% (95% CI: 36.43\u0026ndash;54.52). The mean negative appendectomy rate, reported in 2 studies, was 4.7% (95% CI: -55.25\u0026ndash;64.69) [31,46], while the mean equivocal rate was 15.9% (95% CI: -29.90\u0026ndash;61.65) [31,32,45,46].\u003c/p\u003e \u003cp\u003e \u003cem\u003eCT Group\u003c/em\u003e: This subgroup included 4 studies [33,36,49,50], with a total of 1,389 patients. The mean age was 10.1\u0026thinsp;\u0026plusmn;\u0026thinsp;2.15 years. All studies utilized helical CT; three employed contrast-enhanced CT [33,34,50], while one did not [49]. Three studies assessed the diagnostic performance of low-dose radiation CT compared to standard-dose protocols [33,34,50]. All studies were retrospective and conducted in high-income countries. The mean prevalence of appendicitis was 33.8% (95% CI: 5.14\u0026ndash;62.46). The negative appendectomy rate, reported in one study, was 4.5% [33]. Three studies reported no equivocal results, while one reported an equivocal rate of 3.6%, yielding an overall equivocal rate of 0.9% (95% CI: -1.96\u0026ndash;3.76) [33,34,49,50].\u003c/p\u003e \u003cp\u003e \u003cem\u003eMRI Group\u003c/em\u003e: This group included 13 studies [35\u0026ndash;44,47\u0026ndash;49], encompassing 2,630 patients. The mean age was 11.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.9 years. Five studies utilized 1.5\u0026ndash;3.0 T MRI systems [35,37,38,41,44], three used exclusively 3.0 T systems [39,47,48], and five used 1.5 T systems [36,40,42,43,49]. Twelve studies did not use contrast, while one analyzed the same population with and without contrast [42]. Three studies (23%) were prospective, while the remainder were retrospective. Only one study (7.6%) was conducted in a low- or middle-income country, with the rest performed in high-income settings. The mean prevalence of appendicitis was 25.4% (95% CI: 18.97\u0026ndash;31.86). The mean negative appendectomy rate, reported in 7 studies, was 9.9% (95% CI: 2.54\u0026ndash;17.23) [36\u0026ndash;41,44]. The mean equivocal rate was 8.6% (95% CI: -1.31\u0026ndash;18.57) [35\u0026ndash;44,47\u0026ndash;49].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003eQuality Assessment\u003c/h2\u003e \u003cp\u003eThe methodological quality of the included studies was assessed using the QUADAS-2 tool (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) [10].\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003ePatient Selection Bias\u003c/strong\u003e \u003cp\u003eAmong the US and POCUS studies, six studies [25,26,29,30,32,47] had a high risk of bias due to restricted patient selection criteria, including studies that evaluated patients only during specific hours [25,47], those that included only pediatric surgical unit admissions [26], and studies that assessed patients exclusively after surgical consultation [29,32] or when the appendix was visualized [30]. All were considered to have high applicability concerns. Among CT studies, one study [49] restricted evaluation to specific hours. In the MRI group, nine studies [35,37\u0026ndash;40,42,47\u0026ndash;49] evaluated patients with equivocal US results as part of a diagnostic pathway.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eIndex Test Bias\u003c/strong\u003e \u003cp\u003eTwo US studies [21,23] had an index test bias due to the absence of pre-specified diagnostic criteria, leading to high applicability concerns.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eReference Standard Bias\u003c/strong\u003e \u003cp\u003eFive studies [14,20,32,41,50] used histology reports without a clearly defined follow-up period as the reference standard, leading to high applicability concerns. Most other studies employed histology or surgical reports, but follow-up time was generally unspecified.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eTiming of Index Test and Surgery\u003c/strong\u003e \u003cp\u003eOnly seven studies [18,20,22,28,32,37,44] reported the time between the index test and surgery; for the remaining studies, this time interval was unclear.\u003c/p\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003eQuantitative Synthesis\u003c/h2\u003e \u003cp\u003eA total of 21 studies contributed to the quantitative synthesis, categorized into four study subgroups: 21 studies on conventional US (excluding one elastography study due to differing imaging targets and diagnostic criteria [14]), 4 studies on POCUS, 4 on CT, and 13 on MRI. The meta-analytic synthesis of diagnostic accuracy for each modality is presented in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Among the four modalities, conventional US exhibited the narrowest confidence intervals in diagnostic performance (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Conventional US (I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;95%), and POCUS studies (I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;79.7%) had the highest heterogeneity. Whereas CT (I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0%, 95%CI: 0-67.6%), and MRI studies (I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;35.4%) had the lowest heterogeneity.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMeta-analysis of diagnostic performance of each imaging modality.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eImaging modality\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSensitivity\u003c/p\u003e \u003cp\u003e(95%CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSpecificity\u003c/p\u003e \u003cp\u003e(95%CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDOR\u003c/p\u003e \u003cp\u003e(95%CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLR +\u003c/p\u003e \u003cp\u003e(95%CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLR-\u003c/p\u003e \u003cp\u003e(95%CI)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eConventional US\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.93\u003c/p\u003e \u003cp\u003e(0.87, 0.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.89\u003c/p\u003e \u003cp\u003e(0.80, 0.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e115.23\u003c/p\u003e \u003cp\u003e(-32.88,263.34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.81\u003c/p\u003e \u003cp\u003e(2.77,14.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003cp\u003e(0.02,0.13)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePOCUS\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.80\u003c/p\u003e \u003cp\u003e(0.61, 0.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.93\u003c/p\u003e \u003cp\u003e(0.83, 0.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e53.97\u003c/p\u003e \u003cp\u003e(-39, 146.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11.83\u003c/p\u003e \u003cp\u003e(-1.22,24.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003cp\u003e(0.05,0.39)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCT\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.96\u003c/p\u003e \u003cp\u003e(0.93, 0.97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003cp\u003e(0.96, 0.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e864.43\u003c/p\u003e \u003cp\u003e(264.02,1464.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e38.44\u003c/p\u003e \u003cp\u003e(19.83,57.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003cp\u003e(0.02,0.07)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMRI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.96\u003c/p\u003e \u003cp\u003e(0.94, 0.97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003cp\u003e(0.96, 0.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1030.42\u003c/p\u003e \u003cp\u003e(222.05,1838.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e41.20\u003c/p\u003e \u003cp\u003e(19.21,63.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003cp\u003e(0.02,0.06)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eDOR\u0026thinsp;=\u0026thinsp;diagnostic odds ratio; LR\u0026thinsp;+\u0026thinsp;=\u0026thinsp;positive likelihood ratio; LR-= negative likelihood ratio.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure 4 shows SROC curve fitting of the imaging modalities. This fitting was performed using bivariate models, and models were compared using the likelihood ratio test, yielding a p-value of 0.07, indicating no statistically significant differences in sensitivity and specificity across the diagnostic tests. Additionally, graphical verification showed overlapping confidence intervals for sensitivity and specificity among the included tests (Fig.\u0026nbsp;4).\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003eSummary of Main Results\u003c/h2\u003e \u003cp\u003eOur meta-analysis of 21 conventional US studies demonstrated a pooled sensitivity of 0.95 (95% CI: 0.93\u0026ndash;0.97) and a pooled specificity of 0.93 (95% CI: 0.90\u0026ndash;0.95). While variations in protocol design and risks of bias across QUADAS-2 domains may have influenced these estimates, our findings are consistent with previous meta-analyses, which reported pooled sensitivity of 0.91 (95% CI: 0.83\u0026ndash;0.95) [7] and specificity of 0.97 (95% CI: 0.96\u0026ndash;0.97) [8]. These results reinforce the high diagnostic accuracy of conventional US performed by a radiologist for evaluating pediatric patients with suspected AP. US remains the preferred first-line imaging modality due to its safety, low cost, and wide availability, typically performed using a high-frequency linear transducer (7.5\u0026ndash;12 MHz) with a graded compression technique [51].\u003c/p\u003e \u003cp\u003eOur subgroup meta-analysis of four POCUS studies yielded a pooled sensitivity of 0.80 (95% CI: 0.61\u0026ndash;0.91) and a specificity of 0.93 (95% CI: 0.83\u0026ndash;0.98). The wide confidence intervals suggest considerable variability in operator performance. For example, one study assessed clinicians after only 30 minutes of US training [45], while another involved a surgeon with extensive US experience [32]. The broad SROC curve further supports this operator-dependent variability. Our results align with those of Benabbas et al., who reported a pooled sensitivity of 0.86 (95% CI: 0.79\u0026ndash;0.91) and specificity of 0.91 (95% CI: 0.87\u0026ndash;0.94) for emergency department POCUS [52]. Given its potential advantages, POCUS is a promising imaging modality. If operator dependency can be minimized through standardized training and competency-based assessments, POCUS may significantly enhance diagnostic access to pediatric patients with suspected AP worldwide.\u003c/p\u003e \u003cp\u003eThe meta-analysis of four CT studies found a pooled sensitivity of 0.96 (95% CI: 0.93\u0026ndash;0.97) and specificity of 0.98 (95% CI: 0.96\u0026ndash;0.98). The included studies predominantly employed low-dose radiation protocols, with three using contrast-enhanced CT and one non-contrast protocol. The non-contrast study, which had a small sample size, reported a sensitivity of 0.80 and specificity of 1.00 [49]. Our findings are consistent with previous reviews, where the highest reported pooled sensitivity was 0.96 (95% CI: 0.93\u0026ndash;0.97) and specificity was 0.94 (95% CI: 0.92\u0026ndash;0.95) [7]. In children with suspected AP, low-dose CT has a high diagnostic performance, even without contrast. Despite its high diagnostic accuracy, CT should be reserved for cases in which US is inconclusive or when complications such as perforation or abscess formation are suspected [6].\u003c/p\u003e \u003cp\u003eOur meta-analysis of 13 MRI studies demonstrated a pooled sensitivity of 0.96 (95% CI: 0.94\u0026ndash;0.97) and specificity of 0.98 (95% CI: 0.96\u0026ndash;0.99), with these values obtained using non-contrast, non-sedation, and ultra-fast MRI protocols [35\u0026ndash;44,47\u0026ndash;49]. These results are comparable to previously reported pooled sensitivity of 0.98 (95% CI: 0.96\u0026ndash;0.99) [8] and specificity of 0.97 (95% CI: 0.92\u0026ndash;0.99) [7]. MRI has emerged as a powerful diagnostic tool in pediatric AP, particularly in specialized centers with access to advanced imaging technology. Its utilization is expected to expand in the near future [53].\u003c/p\u003e \u003cdiv id=\"Sec25\" class=\"Section3\"\u003e \u003ch2\u003eStrengths and Limitations of the Review\u003c/h2\u003e \u003cp\u003eThis systematic review employed a comprehensive literature search across multiple databases, including non-English publications. However, we did not include gray literature, which may have introduced publication bias. Of the 43 included studies, 21 (48.8%) were prospectively designed, yet none were randomized. The overall methodological quality of the included studies was good, with minimal patient selection bias. The primary risk of selection bias was observed in MRI studies performed as part of predefined clinical pathways following equivocal US results. Applicability concerns were generally low. However, some studies lacked clearly defined diagnostic criteria or did not specify follow-up length as part of the reference standard. Flow and timing bias was present in several studies, as the time interval between the index and reference tests was not consistently reported. Follow-up methodologies varied, with most studies relying on clinical chart reviews and only a few prospectively contacting patients. The shortest reported follow-up was three days, while the longest was six months. Overall, 26 out of 43 studies (61.9%) had a follow-up period exceeding two weeks. Despite these limitations, our review included a robust pool of high-quality studies.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec26\" class=\"Section3\"\u003e \u003ch2\u003eImplications for Clinical Practice and Future Research\u003c/h2\u003e \u003cp\u003e This review confirms that all three imaging modalities\u0026mdash;US, CT, and MRI\u0026mdash;demonstrate high diagnostic accuracy for pediatric AP, with CT and MRI exhibiting the highest sensitivity and specificity. However, due to the risks associated with ionizing radiation, CT use should be limited, even with low-dose protocols.\u003c/p\u003e \u003cp\u003eUS remains the preferred first-line imaging modality given its strong diagnostic performance, broad availability, and favorable safety profile. MRI serves as an excellent second-line option, particularly for cases in which US findings are inconclusive. MRI offers high diagnostic accuracy without requiring sedation, contrast, or radiation exposure. However, its widespread adoption is limited by cost, access, and protocol variability. International efforts to standardize pediatric MRI protocols are promising and should be further encouraged [54].\u003c/p\u003e \u003cp\u003eAlthough POCUS demonstrated lower sensitivity than conventional US, its high specificity and real-time bedside applicability make it a valuable tool, particularly for well-trained clinicians. Implementing structured training programs with competency-based assessments may significantly enhance its diagnostic reliability.\u003c/p\u003e \u003cp\u003eOptimizing clinical pathways that strategically incorporate US and MRI while minimizing reliance on CT could improve diagnostic precision and patient outcomes while reducing radiation exposure. Integrating POCUS within these pathways, alongside ongoing professional education, could further enhance diagnostic efficiency and access.\u003c/p\u003e \u003cp\u003eAs an inflammatory condition, AP diagnosis relies on imaging modalities that detect inflammation-related changes. This is particularly relevant when the appendix is not visualized, as the presence of associated inflammatory signs should guide diagnostic interpretation. If inflammatory signs are present, a positive diagnosis may be considered; conversely, their absence may support a negative diagnosis [26,36].\u003c/p\u003e \u003cp\u003eFuture advancements in pediatric AP imaging should focus on standardizing protocols for US, POCUS, and MRI. Additionally, artificial intelligence (AI) may play a role in improving diagnostic accuracy, facilitating high-precision imaging interpretation, and streamlining clinical decision-making. AI-driven approaches have the potential to enhance imaging-based AP diagnosis by increasing accuracy, expanding access, and simplifying diagnostic pathways. Further research should explore AI applications in this domain.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003e Our review confirms that contemporary imaging modalities offer high diagnostic accuracy for pediatric AP. US should remain the first-line imaging modality due to its accuracy, safety, and accessibility. POCUS may serve as a valuable diagnostic tool, particularly with improved training and standardization. CT, while highly accurate, carries radiation risks and should be used judiciously. MRI presents a high-accuracy, radiation-free alternative but remains limited by cost and availability. Future efforts should focus on enhancing US and POCUS diagnostic accuracy, expanding MRI access, and integrating AI-driven diagnostic tools to improve efficiency and reliability in pediatric AP imaging.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eCompeting interests:\u0026nbsp;\u003c/strong\u003eThe authors have no financial, nor non-financial competing interests to declare that are relevant to the content of this article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding declaration:\u0026nbsp;\u003c/strong\u003eThe present study had no funding.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eIdea of the study: J.D.P.H, D.I.C.L., M.P.P.Literature search and analysis: D.I.C.L., J.D.P.H., J.A.F.G, M.F.S.M., M.P.P. Draft and/or critically revised work: J.D.P.H., D.I.C.L., M.P.P., J.A.F.G., M.F.S.M., P.D.S.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eThe authors express their gratitude to Maria Isabel Pati\u0026ntilde;o Lopez and Saul Valencia Guzman for their assistance in search strategy design, execution, and database management.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eData is provided within the manuscript or supplementary information files.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eTeoule P, de Laffolie J, Rolle U, Reibfelder C (2020) Acute appendicitis in childhood and adulthood: an everyday clinical challenge. Dtsch Arztebl 117(45):764-774. https://doi.org/10.3238/arztebl.2020.0764\u003c/li\u003e\n\u003cli\u003eBecker T, Kharbanda A, Bachur R (2007) Atypical clinical features of pediatric appendicitis. 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Emerg Radiol 25:161\u0026ndash;168.\u003c/li\u003e\n\u003cli\u003eYi DY, Lee KH, Park SB, Kim JT, Lee NM, Kim H, Yun SW, Chae SA, Lim IS (2017) Accuracy of low dose CT in the diagnosis of appendicitis in childhood and comparison with USG and standard dose CT. J Pediatr (Rio J) 93:625\u0026ndash;631. https://doi.org/10.1016/j.jped.2017.01.004 \u003c/li\u003e\n\u003cli\u003eExpert Panel on Gastrointestinal Imaging: Garcia EM, Camacho MA, Karolyi DR, Kim DH, Cash BD, Chang K, Feig BW, Fowler KJ, Kambadakone AR, Lambert DL, Levy AD, Marin D, Moreno C, Peterson CM, Scheirey, Siegel A, Smith MP, Weinstein S, Carucci L (2018) ACR Appropriateness Criteria\u0026reg; Right Lower Quadrant Pain-Suspected Appendicitis. J Am Coll Radiol 15:S373\u0026ndash;S387. https://doi.org/10.1016/j.jacr.2018.09.033 \u003c/li\u003e\n\u003cli\u003eBenabbas R, Hanna M, Shah J, Sinert R (2017) Diagnostic accuracy of history, physical examination, laboratory tests, and point-of-care ultrasound for pediatric acute appendicitis in the emergency department: A systematic review and meta-analysis. Acad Emerg Med 24:523\u0026ndash;551. https://doi.org/10.1111/acem.13181 \u003c/li\u003e\n\u003cli\u003eJanos S, Schooler GR, Ngo JS, Davis JT (2019) Free-breathing unsedated MRI in children: Justification and techniques. J Magn Reson Imaging 50:365\u0026ndash;376. https://doi.org/10.1002/jmri.26644 \u003c/li\u003e\n\u003cli\u003eFerraciolli SF, Boechat MI, Shu Y, Anu M, Harris C, Vorstenbasch-Lynn EV, Kilborn T, Lam W, Ho ML, Kasznia-Brown J, Jaimes C, Michael SG (2025) International standardization of pediatric magnetic resonance imaging protocols: creation of the World Federation of Pediatric Imaging MR Protocols Committee. Pediatr Radiol. https://doi.org/10.1007/s00247-024-06154-6 \u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"pediatric-radiology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"prad","sideBox":"Learn more about [Pediatric Radiology](http://link.springer.com/journal/247)","snPcode":"247","submissionUrl":"https://submission.nature.com/new-submission/247/3","title":"Pediatric Radiology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Appendicitis, Child, Ultrasonography, Tomography, Magnetic Resonance Imaging, Meta-Analysis","lastPublishedDoi":"10.21203/rs.3.rs-6100084/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6100084/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAdvances in ultrasound (US), computed tomography (CT), and magnetic resonance imaging (MRI) technology and protocols have improved their accuracy for diagnosing acute appendicitis (AP) in children.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eObjective\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDetermine sensitivity, specificity, and diagnostic odds ratios (DOR) of the latest US, CT, and MRI studies for AP in pediatric patients.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMaterials and methods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePubMed, MEDLINE, BVS, OVID, Web of Science, and Trip Database (Jan 2015-May 2024), were searched for studies in patients 2 to 21 years old with suspected AP. Histopathology and clinical follow-up were the standard tests. Those with insufficient data for a 2x2 contingency table were excluded. QUADAS-2 directed risk of bias assessment. Data were extracted for meta-analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis systematic review of 37 articles included 22 conventional US studies (20,897 patients), 4 point-of-care US (POCUS) studies (280), 4 CT studies (1,389), and 13 MRI studies (2,630). Pooled sensitivity, specificity and DOR were: conventional US: 0.93 (95%CI [0.87, 0.96]), 0.89 (95%CI [0.80, 0.95]), 115.23 (95%CI [-32.88, 263.34]); POCUS: 0.80 (95%CI [0.61, 0.91]), 0.93 (95%CI [0.83, 0.98]), 53.97 (95%CI [-39, 146.94]); CT: 0.96 (95%CI [0.93, 0.97]), 0.98 (95%CI [0.96, 0.98]), 864.43 (95%CI [264.02, 1,464.84]); MRI: 0.96 (95%CI [0.94, 0.97]), 0.98 (95%CI [0.96, 0.99]), 1,030.42 (95%CI [222.05, 1,838.8]). No statistically significant differences were found (p = 0.07).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDiscussion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStudies were heterogeneous in flow, timing, and follow-up. Nevertheless, all imaging modalities had high diagnostic performance.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConventional US is an accurate first-line option; MRI is powerful when available. POCUS may help if it reduces equivocal results, while CT is discouraged due to radiation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRegistration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePROSPERO: CRD42024538086. May, 5\u003csup\u003eth\u003c/sup\u003e, 2024. Retrospectively registered.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePROSPERO registration name: Ultrasound, computed tomography or magnetic resonance imaging for diagnosing acute appendicitis in children and adolescents.\u003c/p\u003e","manuscriptTitle":"Contemporary ultrasound, computed tomography, or magnetic resonance imaging for acute appendicitis diagnosis in children and adolescents: systematic review and meta-analysis.","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-03-04 11:37:38","doi":"10.21203/rs.3.rs-6100084/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-03-18T15:37:03+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-03-11T11:38:47+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"78922347818033011113143543702193775292","date":"2025-03-05T21:40:47+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-03-05T18:22:58+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"34655387736819469134945926079431191608","date":"2025-03-05T16:24:39+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-03-04T03:24:07+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"303846988032368211107226877761500461399","date":"2025-02-28T19:32:50+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-02-28T19:30:36+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-02-27T11:16:01+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-02-27T11:15:42+00:00","index":"","fulltext":""},{"type":"submitted","content":"Pediatric Radiology","date":"2025-02-24T22:38:10+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"pediatric-radiology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"prad","sideBox":"Learn more about [Pediatric Radiology](http://link.springer.com/journal/247)","snPcode":"247","submissionUrl":"https://submission.nature.com/new-submission/247/3","title":"Pediatric Radiology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"4c9a462f-1fbc-4f01-89da-32ae252bdb01","owner":[],"postedDate":"March 4th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-05-12T16:00:05+00:00","versionOfRecord":{"articleIdentity":"rs-6100084","link":"https://doi.org/10.1007/s00247-025-06261-y","journal":{"identity":"pediatric-radiology","isVorOnly":false,"title":"Pediatric Radiology"},"publishedOn":"2025-05-09 15:57:12","publishedOnDateReadable":"May 9th, 2025"},"versionCreatedAt":"2025-03-04 11:37:38","video":"","vorDoi":"10.1007/s00247-025-06261-y","vorDoiUrl":"https://doi.org/10.1007/s00247-025-06261-y","workflowStages":[]},"version":"v1","identity":"rs-6100084","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6100084","identity":"rs-6100084","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}