Pub Date : 2026-02-28DOI: 10.1007/s10140-026-02444-8
Mitchel Misfeldt, Samuel Hund, Luke Frager, John Waddell, Bradley Estes, Tevyn Pak, Kate Young, Carissa Walter, Jamie Crist
Purpose: To determine if there is a comparative measurement on bilateral sunrise view radiographs that can help predict acute transient patellar dislocation (ATPD).
Methods: A retrospective chart review from a single institution was conducted of two patient groups, a case group with ATPD diagnosed by MRI, and a control group with knee injury not involving the patella or medial retinaculum. Three readers blinded to the MRI diagnosis reviewed the sunrise view radiographs and reported three values for both knees: (1) medial trochlea - medial patella distance (MT-MP); (2) lateral trochlea -medial patella distance (LT-MP); and (3) medial patellofemoral angle (MPFA), (Image 2). Diagnostic accuracy was assessed utilizing empirical ROC curves and their corresponding area under the curves (AUC). Inter-reader reliability was determined using intraclass correlation coefficients (ICC). Sensitivity and specificity were calculated for varying differences in MPFA and MT-MP between affected knee and unaffected knee.
Results: Of the three measurements, increased MPFA measured on the injured knee was the most accurate predictor of ATPD with substantial inter-reader reliability (AUC 0.765, ICC 0.681). MT-MP (AUC 0.707, ICC 0.586) and LT-MP (AUC 0.593, 0.189) distances were less accurate and less reliable predictors. Asymmetric difference in the MPFA or MT-MP between affected knee and unaffected knee was a very specific, albeit not sensitive indicator of ATPD.
Conclusion: Comparative sunrise view knee radiographs can help predict the diagnosis of ATPD with high specificity, prompting early MRI evaluation for definitive diagnosis, helping expedite treatment planning.
{"title":"Using sunrise to surmise acute transient patellar dislocation.","authors":"Mitchel Misfeldt, Samuel Hund, Luke Frager, John Waddell, Bradley Estes, Tevyn Pak, Kate Young, Carissa Walter, Jamie Crist","doi":"10.1007/s10140-026-02444-8","DOIUrl":"https://doi.org/10.1007/s10140-026-02444-8","url":null,"abstract":"<p><strong>Purpose: </strong>To determine if there is a comparative measurement on bilateral sunrise view radiographs that can help predict acute transient patellar dislocation (ATPD).</p><p><strong>Methods: </strong>A retrospective chart review from a single institution was conducted of two patient groups, a case group with ATPD diagnosed by MRI, and a control group with knee injury not involving the patella or medial retinaculum. Three readers blinded to the MRI diagnosis reviewed the sunrise view radiographs and reported three values for both knees: (1) medial trochlea - medial patella distance (MT-MP); (2) lateral trochlea -medial patella distance (LT-MP); and (3) medial patellofemoral angle (MPFA), (Image 2). Diagnostic accuracy was assessed utilizing empirical ROC curves and their corresponding area under the curves (AUC). Inter-reader reliability was determined using intraclass correlation coefficients (ICC). Sensitivity and specificity were calculated for varying differences in MPFA and MT-MP between affected knee and unaffected knee.</p><p><strong>Results: </strong>Of the three measurements, increased MPFA measured on the injured knee was the most accurate predictor of ATPD with substantial inter-reader reliability (AUC 0.765, ICC 0.681). MT-MP (AUC 0.707, ICC 0.586) and LT-MP (AUC 0.593, 0.189) distances were less accurate and less reliable predictors. Asymmetric difference in the MPFA or MT-MP between affected knee and unaffected knee was a very specific, albeit not sensitive indicator of ATPD.</p><p><strong>Conclusion: </strong>Comparative sunrise view knee radiographs can help predict the diagnosis of ATPD with high specificity, prompting early MRI evaluation for definitive diagnosis, helping expedite treatment planning.</p>","PeriodicalId":11623,"journal":{"name":"Emergency Radiology","volume":" ","pages":""},"PeriodicalIF":1.3,"publicationDate":"2026-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147316755","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-25DOI: 10.1007/s10140-026-02445-7
Alexis R Chow, Jonathan Elias, Kunal Shah, Robert Ablove, Sean Mcmillan
{"title":"Identifying the diagnostic utility of artificial intelligence for elbow effusion detection: A systematic review and meta-analysis.","authors":"Alexis R Chow, Jonathan Elias, Kunal Shah, Robert Ablove, Sean Mcmillan","doi":"10.1007/s10140-026-02445-7","DOIUrl":"https://doi.org/10.1007/s10140-026-02445-7","url":null,"abstract":"","PeriodicalId":11623,"journal":{"name":"Emergency Radiology","volume":" ","pages":""},"PeriodicalIF":1.3,"publicationDate":"2026-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147282953","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-24DOI: 10.1007/s10140-026-02442-w
Cade A Johnson, Catherine M Pivalizza, Hei Kit Chan, Hannah Smith, Megan K Long, Robert Lapus, KuoJen Tsao, Susan John, Irma T Ugalde
{"title":"Diagnosis of acute appendicitis at a pediatric emergency department within a general hospital.","authors":"Cade A Johnson, Catherine M Pivalizza, Hei Kit Chan, Hannah Smith, Megan K Long, Robert Lapus, KuoJen Tsao, Susan John, Irma T Ugalde","doi":"10.1007/s10140-026-02442-w","DOIUrl":"https://doi.org/10.1007/s10140-026-02442-w","url":null,"abstract":"","PeriodicalId":11623,"journal":{"name":"Emergency Radiology","volume":" ","pages":""},"PeriodicalIF":1.3,"publicationDate":"2026-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147282987","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-21DOI: 10.1007/s10140-025-02435-1
Ruba Khasawneh, Ammar Hajij, Nour Abdo, Yazan O Alzu'bi, Bashar Al-Shalabi, Ahmed H Al Sharie, Firas A Khasawneh, Mohammad Z Mohaidat
Objective: Globe rupture presents a diagnostic challenge because of potentially vision-threatening outcomes. Although computed tomography (CT) is critical for assessment, a structured interpretation approach is often lacking. This study introduces the novel "FLAP CONE" mnemonic to assist radiologists in evaluating globe rupture.
Methods: This was a retrospective study of 143 patients (151 eyes) with suspected globe rupture between January 2015 and December 2020. The male-to-female ratio was 3:1, with a median age of 22 years. Demographics and mechanisms of injury were recorded. CT scans were independently reviewed by two radiologists using the FLAP CONE mnemonic, encompassing Fractures/Foreign bodies, scleral Lacerations/Lens abnormalities, Anterior chamber changes, Posterior segment abnormalities, eye Contour distortion, Orbital apex hematoma, Neurovascular bundle abnormalities, and Extraocular muscles (EOM)/Emphysema. Findings were documented as binary variables. The diagnostic accuracy, sensitivity, specificity, and interobserver agreement (κ) were calculated.
Results: Sharp objects (39%) and falls (25%) were the leading causes of penetrating and blunt trauma, respectively. Use of the mnemonic achieved 91.9% diagnostic accuracy, with 88.3% sensitivity and 98.5% specificity. Orbital emphysema (43%) was the most frequent finding. Postseptal foreign body and the "flat tire" sign were associated with the highest diagnostic performance (sensitivity of 100% and 97.2%, respectively; specificity, 100%; and PPV, 100%). Kappa values ranged from 0.15 (orbital apex hematoma) to 1.0 (postseptal foreign body), with an overall κ = 0.85. Four clinically confirmed ruptures were missed because of subtle scleral defects and the presence of intraocular gas.
Conclusion: The FLAP CONE mnemonic demonstrates excellent diagnostic accuracy and interobserver reliability, providing a systematic and efficient approach to the CT evaluation of globe rupture.
{"title":"Computed tomography scan evaluation of Globe rupture using a novel mnemonic : a single center experience.","authors":"Ruba Khasawneh, Ammar Hajij, Nour Abdo, Yazan O Alzu'bi, Bashar Al-Shalabi, Ahmed H Al Sharie, Firas A Khasawneh, Mohammad Z Mohaidat","doi":"10.1007/s10140-025-02435-1","DOIUrl":"https://doi.org/10.1007/s10140-025-02435-1","url":null,"abstract":"<p><strong>Objective: </strong>Globe rupture presents a diagnostic challenge because of potentially vision-threatening outcomes. Although computed tomography (CT) is critical for assessment, a structured interpretation approach is often lacking. This study introduces the novel \"FLAP CONE\" mnemonic to assist radiologists in evaluating globe rupture.</p><p><strong>Methods: </strong>This was a retrospective study of 143 patients (151 eyes) with suspected globe rupture between January 2015 and December 2020. The male-to-female ratio was 3:1, with a median age of 22 years. Demographics and mechanisms of injury were recorded. CT scans were independently reviewed by two radiologists using the FLAP CONE mnemonic, encompassing Fractures/Foreign bodies, scleral Lacerations/Lens abnormalities, Anterior chamber changes, Posterior segment abnormalities, eye Contour distortion, Orbital apex hematoma, Neurovascular bundle abnormalities, and Extraocular muscles (EOM)/Emphysema. Findings were documented as binary variables. The diagnostic accuracy, sensitivity, specificity, and interobserver agreement (κ) were calculated.</p><p><strong>Results: </strong>Sharp objects (39%) and falls (25%) were the leading causes of penetrating and blunt trauma, respectively. Use of the mnemonic achieved 91.9% diagnostic accuracy, with 88.3% sensitivity and 98.5% specificity. Orbital emphysema (43%) was the most frequent finding. Postseptal foreign body and the \"flat tire\" sign were associated with the highest diagnostic performance (sensitivity of 100% and 97.2%, respectively; specificity, 100%; and PPV, 100%). Kappa values ranged from 0.15 (orbital apex hematoma) to 1.0 (postseptal foreign body), with an overall κ = 0.85. Four clinically confirmed ruptures were missed because of subtle scleral defects and the presence of intraocular gas.</p><p><strong>Conclusion: </strong>The FLAP CONE mnemonic demonstrates excellent diagnostic accuracy and interobserver reliability, providing a systematic and efficient approach to the CT evaluation of globe rupture.</p>","PeriodicalId":11623,"journal":{"name":"Emergency Radiology","volume":" ","pages":""},"PeriodicalIF":1.3,"publicationDate":"2026-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146257891","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-20DOI: 10.1007/s10140-026-02439-5
Rawan Hosny, Maha Saad, Rana Shebl, Taha Mokdad, Mohamed Hosny, Mohamed Anis
{"title":"Is pre-operative computed tomography mandatory in the workup of open globe injuries?","authors":"Rawan Hosny, Maha Saad, Rana Shebl, Taha Mokdad, Mohamed Hosny, Mohamed Anis","doi":"10.1007/s10140-026-02439-5","DOIUrl":"https://doi.org/10.1007/s10140-026-02439-5","url":null,"abstract":"","PeriodicalId":11623,"journal":{"name":"Emergency Radiology","volume":" ","pages":""},"PeriodicalIF":1.3,"publicationDate":"2026-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146225191","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-16DOI: 10.1007/s10140-026-02440-y
Laura Tello Arnas, José Carlos Romero Carmona, Jorge Rey Porras, Silvia Osaba Velez, Aurea Díez Tascón, Maria Luz Parra Gordo, Felipe Munera, Milagros Martí de Gracia
{"title":"Acute thoracic aortic dissection, A radiological approach from a surgical perspective.","authors":"Laura Tello Arnas, José Carlos Romero Carmona, Jorge Rey Porras, Silvia Osaba Velez, Aurea Díez Tascón, Maria Luz Parra Gordo, Felipe Munera, Milagros Martí de Gracia","doi":"10.1007/s10140-026-02440-y","DOIUrl":"https://doi.org/10.1007/s10140-026-02440-y","url":null,"abstract":"","PeriodicalId":11623,"journal":{"name":"Emergency Radiology","volume":" ","pages":""},"PeriodicalIF":1.3,"publicationDate":"2026-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146200409","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-10DOI: 10.1007/s10140-026-02443-9
Zahra F Rahmatullah, Satomi Kawamoto, Elliot K Fishman
Primary small bowel malignancies are rare, often presenting with nonspecific symptoms or as acute emergencies, which can delay diagnosis. Contrast-enhanced CT is the primary imaging modality in the emergency setting, but detection and characterization of small bowel tumors remain challenging. Cinematic rendering (CR) is a recently developed three-dimensional post-processing technique that produces photorealistic images from CT data, enhancing visualization of small bowel pathology. This pictorial review outlines the CT imaging features of major small bowel malignancies, including adenocarcinoma, carcinoid tumor, gastrointestinal stromal tumor, lymphoma, and sarcoma, and describes features that highlight the utility of CR in augmenting traditional imaging. CR offers improved visualization of mucosal abnormalities, tumor extent, vascular involvement, and textural differences, potentially increasing diagnostic confidence, supporting presurgical planning, and facilitating communication among clinicians and patients. By emphasizing the added value of CR, we aim to provide radiologists with practical guidance for identifying small bowel neoplasms and suggest that integrating advanced 3D visualization into routine CT evaluation can support timely diagnosis and management in acute care settings.
{"title":"Augmenting CT evaluation of primary small bowel malignancies: The role of cinematic rendering.","authors":"Zahra F Rahmatullah, Satomi Kawamoto, Elliot K Fishman","doi":"10.1007/s10140-026-02443-9","DOIUrl":"https://doi.org/10.1007/s10140-026-02443-9","url":null,"abstract":"<p><p>Primary small bowel malignancies are rare, often presenting with nonspecific symptoms or as acute emergencies, which can delay diagnosis. Contrast-enhanced CT is the primary imaging modality in the emergency setting, but detection and characterization of small bowel tumors remain challenging. Cinematic rendering (CR) is a recently developed three-dimensional post-processing technique that produces photorealistic images from CT data, enhancing visualization of small bowel pathology. This pictorial review outlines the CT imaging features of major small bowel malignancies, including adenocarcinoma, carcinoid tumor, gastrointestinal stromal tumor, lymphoma, and sarcoma, and describes features that highlight the utility of CR in augmenting traditional imaging. CR offers improved visualization of mucosal abnormalities, tumor extent, vascular involvement, and textural differences, potentially increasing diagnostic confidence, supporting presurgical planning, and facilitating communication among clinicians and patients. By emphasizing the added value of CR, we aim to provide radiologists with practical guidance for identifying small bowel neoplasms and suggest that integrating advanced 3D visualization into routine CT evaluation can support timely diagnosis and management in acute care settings.</p>","PeriodicalId":11623,"journal":{"name":"Emergency Radiology","volume":" ","pages":""},"PeriodicalIF":1.3,"publicationDate":"2026-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146149319","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-07DOI: 10.1007/s10140-026-02437-7
Julius Husarek, Anika M C Fuchss, Thomas D Ruder, Stavroula Mougiakakou, Aristomenis Exadaktylos, Katharina Wahedi, Martin Müller
<p><p>Rising patient volumes, the increasing use of computed tomography (CT) imaging in emergency departments and the resulting prolonged waiting times highlight the urgent need for efficient and accurate diagnostic tools, especially given that the number of experienced healthcare professionals is not increasing at the same pace. Artificial intelligence (AI) has emerged as a promising tool to support fracture detection on CT scans, with the potential to streamline diagnostic workflows in emergency care. However, concerns exist regarding dataset bias, limited external testing, and methodological variability. This systematic review and diagnostic test accuracy (DTA) meta-analysis aimed to comprehensively assess the diagnostic accuracy of AI-driven fracture detection solutions, with a particular focus on the effect of the testing strategy, cohort composition and commercial availability on diagnostic accuracy. The Cochrane Handbook for Systematic Reviews of DTA and reported according to PRISMA-DTA guidelines were followed. We systematically searched Embase, MEDLINE, Cochrane Library, Web of Science, and Google Scholar for studies published from January 2010 onward, complemented by citation chasing and manual searches for commercial AI fracture detection solutions (CAAI-FDS). Two reviewers independently conducted study selection, data extraction, and risk of bias assessment using a modified QUADAS-2 tool. Statistical analysis was conducted using STATA 18.1 and the -metadta- command. Primary analyses evaluated diagnostic accuracy (sensitivity and specificity) of stand-alone AI based on (1) cohort type (selected vs. unselected), (2) test dataset origin (internal vs. external), and (3) level of analysis (patient-wise, vertebra-wise, rib-wise). Secondary analyses explored accuracy differences according to (1) CAAI-FDS, (2) anatomical region and (3) reader type (stand-alone AI, human unaided, human aided by AI). Forest plots visualized results, and heterogeneity was measured using generalized I<sup>2</sup> statistics. Out of 7683 identified articles, 44 studies were included for meta-analysis. 14 CAAI-FDS were identified. Primary analyses of stand-alone AI showed moderate sensitivity (0.85, 95% CI: 0.77, 0.90) and good specificity (0.92, 95% CI: 0.87, 0.95) in unselected patient cohorts, whereas selected cohorts achieved slightly higher sensitivity (0.89, 95% CI: 0.80, 0.94). Diagnostic accuracy was higher when studies used internal test datasets (sensitivity 0.94, 95% CI: 0.88, 0.97; specificity 0.91, 95% CI: 0.86, 0.94) compared to external test datasets (sensitivity 0.85, 95% CI: 0,77, 0.91; specificity 0.92, 95% CI: 0.89, 0.95). Vertebra- and rib-wise analyses achieved higher specificity (0.98) compared to patient-wise analysis (0.92, 95% CI: 0.89, 0.95), although sensitivity remained moderate across all levels (0.85-0.89). Secondary analyses showed variability among CAAI-FDS (sensitivities 0.68-0.80; specificities 0.87-0.97) and by anatomical region,
{"title":"Artificial intelligence for fracture detection on computed tomography: a comprehensive systematic review and meta-analysis of diagnostic test accuracy in non-commercial and commercial solutions.","authors":"Julius Husarek, Anika M C Fuchss, Thomas D Ruder, Stavroula Mougiakakou, Aristomenis Exadaktylos, Katharina Wahedi, Martin Müller","doi":"10.1007/s10140-026-02437-7","DOIUrl":"https://doi.org/10.1007/s10140-026-02437-7","url":null,"abstract":"<p><p>Rising patient volumes, the increasing use of computed tomography (CT) imaging in emergency departments and the resulting prolonged waiting times highlight the urgent need for efficient and accurate diagnostic tools, especially given that the number of experienced healthcare professionals is not increasing at the same pace. Artificial intelligence (AI) has emerged as a promising tool to support fracture detection on CT scans, with the potential to streamline diagnostic workflows in emergency care. However, concerns exist regarding dataset bias, limited external testing, and methodological variability. This systematic review and diagnostic test accuracy (DTA) meta-analysis aimed to comprehensively assess the diagnostic accuracy of AI-driven fracture detection solutions, with a particular focus on the effect of the testing strategy, cohort composition and commercial availability on diagnostic accuracy. The Cochrane Handbook for Systematic Reviews of DTA and reported according to PRISMA-DTA guidelines were followed. We systematically searched Embase, MEDLINE, Cochrane Library, Web of Science, and Google Scholar for studies published from January 2010 onward, complemented by citation chasing and manual searches for commercial AI fracture detection solutions (CAAI-FDS). Two reviewers independently conducted study selection, data extraction, and risk of bias assessment using a modified QUADAS-2 tool. Statistical analysis was conducted using STATA 18.1 and the -metadta- command. Primary analyses evaluated diagnostic accuracy (sensitivity and specificity) of stand-alone AI based on (1) cohort type (selected vs. unselected), (2) test dataset origin (internal vs. external), and (3) level of analysis (patient-wise, vertebra-wise, rib-wise). Secondary analyses explored accuracy differences according to (1) CAAI-FDS, (2) anatomical region and (3) reader type (stand-alone AI, human unaided, human aided by AI). Forest plots visualized results, and heterogeneity was measured using generalized I<sup>2</sup> statistics. Out of 7683 identified articles, 44 studies were included for meta-analysis. 14 CAAI-FDS were identified. Primary analyses of stand-alone AI showed moderate sensitivity (0.85, 95% CI: 0.77, 0.90) and good specificity (0.92, 95% CI: 0.87, 0.95) in unselected patient cohorts, whereas selected cohorts achieved slightly higher sensitivity (0.89, 95% CI: 0.80, 0.94). Diagnostic accuracy was higher when studies used internal test datasets (sensitivity 0.94, 95% CI: 0.88, 0.97; specificity 0.91, 95% CI: 0.86, 0.94) compared to external test datasets (sensitivity 0.85, 95% CI: 0,77, 0.91; specificity 0.92, 95% CI: 0.89, 0.95). Vertebra- and rib-wise analyses achieved higher specificity (0.98) compared to patient-wise analysis (0.92, 95% CI: 0.89, 0.95), although sensitivity remained moderate across all levels (0.85-0.89). Secondary analyses showed variability among CAAI-FDS (sensitivities 0.68-0.80; specificities 0.87-0.97) and by anatomical region, ","PeriodicalId":11623,"journal":{"name":"Emergency Radiology","volume":" ","pages":""},"PeriodicalIF":1.3,"publicationDate":"2026-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146131422","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-07DOI: 10.1007/s10140-026-02441-x
Ludolf G A De Kock, Ronan J Lee, David O Adebayo, Patrick D Mclaughin, Eanna MacSuibhne, Michael M Maher, David J Ryan
Medical imaging plays a central role in the management of trauma patients. Analytic morphomics (AM) through enabling measurement of specific biological markers of body composition from medical images is emerging as a potential tool to predict patient outcomes across multiple medical and surgical disciplines. We sought to provide a comprehensive review of the utility of AM in predicting outcomes in trauma patients. A systematic review with a narrative synthesis was conducted following the Preferred Reporting Items for Systematic Review and Meta-analyses (PRISMA) guidelines and checklists. PubMed, Embase, Scopus, The Cochrane Library as well as Web of Science and Trip database were searched for studies that assessed the relationship between computed tomography-based AM parameters and clinical outcomes in patients from a trauma cohort. Multiple AM domains, including lumbar muscle quantity and quality, adiposity, craniofacial measurements, and opportunistic bone mineral density (BMD), were consistently associated with adverse outcomes including mortality, length of stay, complications, and functional recovery. CT-derived AM metrics provide valuable prognostic information in trauma populations, extending beyond conventional measures such as chronological age and injury severity scores.Registration: PROSPERO Registration ID: CRD420251112652.
医学影像在创伤患者的治疗中起着核心作用。分析形态组学(AM)通过从医学图像中测量身体成分的特定生物标记物,正在成为预测多个医学和外科学科患者预后的潜在工具。我们试图对AM在预测创伤患者预后方面的应用进行全面回顾。按照系统评价和荟萃分析的首选报告项目(PRISMA)指南和清单进行了系统评价和叙述性综合评价。检索PubMed, Embase, Scopus, Cochrane Library以及Web of Science和Trip数据库,以评估基于计算机断层扫描的AM参数与创伤队列患者临床结果之间关系的研究。多个AM域,包括腰肌数量和质量、肥胖、颅面测量和机会性骨矿物质密度(BMD),始终与包括死亡率、住院时间、并发症和功能恢复在内的不良结果相关。ct衍生的AM指标在创伤人群中提供了有价值的预后信息,超出了传统的测量方法,如实足年龄和损伤严重程度评分。注册:普洛斯彼罗注册号:CRD420251112652。
{"title":"Computed tomography derived analytic morphomics as predictors of clinical outcomes in trauma: a systematic narrative review.","authors":"Ludolf G A De Kock, Ronan J Lee, David O Adebayo, Patrick D Mclaughin, Eanna MacSuibhne, Michael M Maher, David J Ryan","doi":"10.1007/s10140-026-02441-x","DOIUrl":"https://doi.org/10.1007/s10140-026-02441-x","url":null,"abstract":"<p><p>Medical imaging plays a central role in the management of trauma patients. Analytic morphomics (AM) through enabling measurement of specific biological markers of body composition from medical images is emerging as a potential tool to predict patient outcomes across multiple medical and surgical disciplines. We sought to provide a comprehensive review of the utility of AM in predicting outcomes in trauma patients. A systematic review with a narrative synthesis was conducted following the Preferred Reporting Items for Systematic Review and Meta-analyses (PRISMA) guidelines and checklists. PubMed, Embase, Scopus, The Cochrane Library as well as Web of Science and Trip database were searched for studies that assessed the relationship between computed tomography-based AM parameters and clinical outcomes in patients from a trauma cohort. Multiple AM domains, including lumbar muscle quantity and quality, adiposity, craniofacial measurements, and opportunistic bone mineral density (BMD), were consistently associated with adverse outcomes including mortality, length of stay, complications, and functional recovery. CT-derived AM metrics provide valuable prognostic information in trauma populations, extending beyond conventional measures such as chronological age and injury severity scores.Registration: PROSPERO Registration ID: CRD420251112652.</p>","PeriodicalId":11623,"journal":{"name":"Emergency Radiology","volume":" ","pages":""},"PeriodicalIF":1.3,"publicationDate":"2026-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146131576","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-06DOI: 10.1007/s10140-025-02433-3
Ritika Revoori, Joel Kevin Raj Samuel, Ajay K Singh
Purpose: Intracranial dermoid cysts are rare, benign congenital lesions that can rupture spontaneously, leading to dissemination of fatty contents within the subarachnoid or ventricular spaces. Though often asymptomatic, rupture can produce a range of neurological symptoms and distinct imaging features. We aim to evaluate the clinical presentation, imaging characteristics, and outcomes of patients with ruptured intracranial dermoid cysts.
Methods: We conducted a retrospective review of patients diagnosed with ruptured intracranial dermoid cysts at a tertiary academic medical center from July 1997 to July 2024. Rupture was confirmed by the presence of fat droplets in the CSF spaces on CT and/or MRI. Imaging findings were independently reviewed by two radiologists.
Results: Twenty-two patients (14 female, 8 male; mean age 51.7 years) met inclusion criteria. The most common presenting symptoms were headaches (31.8%). Imaging revealed intraventricular fat in 72.7% of cases and subarachnoid fat in 81.8%, with visible primary cysts in 31.8%. MRI findings included T1 hyperintense fat droplets in all cases, hypointense rims on T2 in 35% of cases, and susceptibility signal loss on SWI in 71%. Follow-up imaging (available in 14 cases) did not show complete resolution of fat droplets, though a reduction in the number of droplets was observed over time.
Conclusion: Ruptured intracranial dermoid cysts are rare but recognizable by their characteristic imaging features, particularly on T1-weighted MRI. While symptoms often improve, residual fat globules persist for years.
{"title":"Ruptured intracranial dermoid cysts: Imaging at acute presentation and follow-up.","authors":"Ritika Revoori, Joel Kevin Raj Samuel, Ajay K Singh","doi":"10.1007/s10140-025-02433-3","DOIUrl":"https://doi.org/10.1007/s10140-025-02433-3","url":null,"abstract":"<p><strong>Purpose: </strong>Intracranial dermoid cysts are rare, benign congenital lesions that can rupture spontaneously, leading to dissemination of fatty contents within the subarachnoid or ventricular spaces. Though often asymptomatic, rupture can produce a range of neurological symptoms and distinct imaging features. We aim to evaluate the clinical presentation, imaging characteristics, and outcomes of patients with ruptured intracranial dermoid cysts.</p><p><strong>Methods: </strong>We conducted a retrospective review of patients diagnosed with ruptured intracranial dermoid cysts at a tertiary academic medical center from July 1997 to July 2024. Rupture was confirmed by the presence of fat droplets in the CSF spaces on CT and/or MRI. Imaging findings were independently reviewed by two radiologists.</p><p><strong>Results: </strong>Twenty-two patients (14 female, 8 male; mean age 51.7 years) met inclusion criteria. The most common presenting symptoms were headaches (31.8%). Imaging revealed intraventricular fat in 72.7% of cases and subarachnoid fat in 81.8%, with visible primary cysts in 31.8%. MRI findings included T1 hyperintense fat droplets in all cases, hypointense rims on T2 in 35% of cases, and susceptibility signal loss on SWI in 71%. Follow-up imaging (available in 14 cases) did not show complete resolution of fat droplets, though a reduction in the number of droplets was observed over time.</p><p><strong>Conclusion: </strong>Ruptured intracranial dermoid cysts are rare but recognizable by their characteristic imaging features, particularly on T1-weighted MRI. While symptoms often improve, residual fat globules persist for years.</p>","PeriodicalId":11623,"journal":{"name":"Emergency Radiology","volume":" ","pages":""},"PeriodicalIF":1.3,"publicationDate":"2026-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146124293","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}