Emergency Radiology最新文献

{"title":"Diagnostic yield of an abbreviated MRI protocol in the evaluation of dizziness in the emergency department, a single institutional experience.","authors":"Faryal Shareef, Long Tu, Anish Neupane, Zaid Siddique, Rudra Joshi, Edward Melnick, Charles Wira, Amit Mahajan","doi":"10.1007/s10140-025-02349-y","DOIUrl":"https://doi.org/10.1007/s10140-025-02349-y","url":null,"abstract":"<p><strong>Purpose: </strong>MRI is the preferred imaging modality for patients with acute dizziness when a central etiology is possible. Abbreviated protocols may improve access in urgent settings. This study assesses the diagnostic yield and utility of an abbreviated MRI protocol for patients presenting with dizziness to the emergency department (ED).</p><p><strong>Method: </strong>This retrospective study included 613 adult patients presenting to the ED with dizziness from August 1, 2019 to August 31, 2023. The protocol included 3 mm coronal and axial DWI, axial FLAIR, and SWI sequences, with a duration of approximately 11 min. MRI findings were categorized as negative or positive for intracranial pathology; etiology and location were recorded. Charts were reviewed for concurrent CTA during the ED visit, and findings were assessed for correlation with MRI results.</p><p><strong>Results: </strong>Of the 613 patients, clinically significant intracranial pathology was identified in 52 cases (8%), including 42 (7%) acute infarcts. Of these infarcts, 19 (45%) were infratentorial, 16 (38%) supratentorial, and 7 (17%) involved both regions. The cerebellum was the most common infratentorial site (38%), followed by the brainstem (24%). Infarcts ranged from 1-84 mm, with 48% measuring less than 1 cm. TOAST classification revealed strokes as cardioembolic (36%), large vessel (26%), cryptogenic (19%), and lacunar (19%). Statistical analysis showed no significant relationship between vertigo and infarct characteristics (P > 0.05).</p><p><strong>Conclusion: </strong>Abbreviated protocol MRI demonstrated a 8% diagnostic yield for detecting intracranial pathology and more often positive than concurrent CT/CTA in identifying acute findings. Supratentorial pathology can present with symptoms of dizziness as well. The abbreviated protocol offers a rapid, efficient diagnostic tool for urgent care settings and MRI identifies more acute findings than concurrent CT/CTA.</p>","PeriodicalId":11623,"journal":{"name":"Emergency Radiology","volume":" ","pages":""},"PeriodicalIF":1.7,"publicationDate":"2025-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144224760","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}

{"title":"Fine-tuned large Language model for extracting newly identified acute brain infarcts based on computed tomography or magnetic resonance imaging reports.","authors":"Nana Fujita, Koichiro Yasaka, Shigeru Kiryu, Osamu Abe","doi":"10.1007/s10140-025-02354-1","DOIUrl":"https://doi.org/10.1007/s10140-025-02354-1","url":null,"abstract":"<p><strong>Purpose: </strong>This study aimed to develop an automated early warning system using a large language model (LLM) to identify acute to subacute brain infarction from free-text computed tomography (CT) or magnetic resonance imaging (MRI) radiology reports.</p><p><strong>Methods: </strong>In this retrospective study, 5,573, 1,883, and 834 patients were included in the training (mean age, 67.5 ± 17.2 years; 2,831 males), validation (mean age, 61.5 ± 18.3 years; 994 males), and test (mean age, 66.5 ± 16.1 years; 488 males) datasets. An LLM (Japanese Bidirectional Encoder Representations from Transformers model) was fine-tuned to classify the CT and MRI reports into three groups (group 0, newly identified acute to subacute infarction; group 1, known acute to subacute infarction or old infarction; group 2, without infarction). The training and validation processes were repeated 15 times, and the best-performing model on the validation dataset was selected to further evaluate its performance on the test dataset.</p><p><strong>Results: </strong>The best fine-tuned model exhibited sensitivities of 0.891, 0.905, and 0.959 for groups 0, 1, and 2, respectively, in the test dataset. The macrosensitivity (the average of sensitivity for all groups) and accuracy were 0.918 and 0.923, respectively. The model's performance in extracting newly identified acute brain infarcts was high, with an area under the receiver operating characteristic curve of 0.979 (95% confidence interval, 0.956-1.000). The average prediction time was 0.115 ± 0.037 s per patient.</p><p><strong>Conclusion: </strong>A fine-tuned LLM could extract newly identified acute to subacute brain infarcts based on CT or MRI findings with high performance.</p>","PeriodicalId":11623,"journal":{"name":"Emergency Radiology","volume":" ","pages":""},"PeriodicalIF":1.7,"publicationDate":"2025-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144198558","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}

{"title":"Investigating clinical indicators for neuroimaging abnormalities in acute headache cases: insights from a retrospective study.","authors":"Felipe Mejía-Herrera, Roger Figueroa-Paz, Jaime Quintero-Ramirez, Luis Alfonso Bustamante-Cristancho","doi":"10.1007/s10140-025-02347-0","DOIUrl":"10.1007/s10140-025-02347-0","url":null,"abstract":"<p><strong>Purpose: </strong>Headache is common at emergency services and neuroimaging can help in timely diagnosis of life-threatening pathologies. We evaluated clinical indicators associated with abnormal neuroimaging in patients with acute headache, aiming to develop a scoring system with reliable diagnostic performance.</p><p><strong>Methods: </strong>This analytical and retrospective study was conducted at a teaching tertiary care hospital in Cali, Colombia, from January 2011 to December 2019. Patients aged 18 years or older with non-traumatic headaches who attended the emergency department and underwent neuroimaging were included. Demographic and clinical data were recorded, including headache associated signs and symptoms, imaging diagnosis and disposition. Statistically significant variables and clinically relevant variables were selected. Data was analyzed using a combination of logistic regression and Receiver Operator Characteristic (ROC) curves, leading to the derivation of three models.</p><p><strong>Results: </strong>626 patients were included, 15.5% with abnormal neuroimaging. The variables with the highest odds ratio (OR) were: age > 40 years (OR 3.2 CI 1.86-5.56), motor deficit (OR 5.4 CI 2.62-11.18), visual deficit (OR 3.2 CI 1.56-6.63) and gait disturbance (OR 2.27 CI 0.87-5.96). Three abnormal neuroimaging prediction logistic regression models have been derived. The better scale is performed with model 1, which is validated internally and a cut-off point of 0.179, the Area Under the Curve (AUC) of 0.757 is obtained with a diagnostic accuracy of 0.79 (0.73-0.85).</p><p><strong>Conclusion: </strong>Our straightforward scale incorporates clinical factors associated with abnormal neuroimaging, with the aim of improving diagnostic performance and predictive capacity to distinguish patients who require neuroimaging.</p>","PeriodicalId":11623,"journal":{"name":"Emergency Radiology","volume":" ","pages":"351-360"},"PeriodicalIF":1.7,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143973302","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}

{"title":"Imaging of acute small bowel pathologies in oncology patients in the ER part I: the role of Computed Tomography (CT) for the evaluation of Tumor and infections.","authors":"Hajra Arshad, Satomi Kawamoto, Linda C Chu, Elliot K Fishman","doi":"10.1007/s10140-025-02341-6","DOIUrl":"10.1007/s10140-025-02341-6","url":null,"abstract":"<p><p>Acute abdominal complaints constitute up to 40% of all emergency department (ED) presentations in oncology patients due to a multitude of causes. Small bowel pathologies present a diagnostic challenge due to their diverse range and frequently overlapping clinical presentation. In oncology patients, structural changes resulting from tumor growth, surgery and treatment effects can further complicate the diagnostic process. Due to a weakened immune system, oncology patients are also highly susceptible to infections of the gastrointestinal tract (GIT). Traditional computed tomography (CT) scans are used as the gold standard diagnostic modality. However, three-dimensional (3D) postprocessing techniques including maximal intensity projection (MIP), volume rendering (VR) and cinematic rendering (CR) have been employed to aid image evaluation. For a balanced and organized approach to describe diagnostic challenges in this complex population, we have divided the pictorial essay into two parts. The first part focuses on tumor- and infection-associated causes, as summarized below in the visual abstract. The second part will address treatment-related complications, including chemotherapy, radiotherapy, immunotherapy, graft-versus-host disease and post-surgical complications.</p>","PeriodicalId":11623,"journal":{"name":"Emergency Radiology","volume":" ","pages":"463-474"},"PeriodicalIF":1.7,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143971923","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}

{"title":"Predicting hemorrhagic transformation in acute ischemic stroke: a systematic review, meta-analysis, and methodological quality assessment of CT/MRI-based deep learning and radiomics models.","authors":"Mohsen Salimi, Pouria Vadipour, Amir Reza Bahadori, Shakiba Houshi, Ali Mirshamsi, Hossein Fatemian","doi":"10.1007/s10140-025-02336-3","DOIUrl":"10.1007/s10140-025-02336-3","url":null,"abstract":"<p><p>Acute ischemic stroke (AIS) is a major cause of mortality and morbidity, with hemorrhagic transformation (HT) as a severe complication. Accurate prediction of HT is essential for optimizing treatment strategies. This review assesses the accuracy and utility of deep learning (DL) and radiomics in predicting HT through imaging, regarding clinical decision-making for AIS patients. A literature search was conducted across five databases (Pubmed, Scopus, Web of Science, Embase, IEEE) up to January 23, 2025. Studies involving DL or radiomics-based ML models for predicting HT in AIS patients were included. Data from training, validation, and clinical-combined models were extracted and analyzed separately. Pooled sensitivity, specificity, and AUC were calculated with a random-effects bivariate model. For the quality assessment of studies, the Methodological Radiomics Score (METRICS) and QUADAS-2 tool were used. 16 studies consisting of 3,083 individual participants were included in the meta-analysis. The pooled AUC for training cohorts was 0.87, sensitivity 0.80, and specificity 0.85. For validation cohorts, AUC was 0.87, sensitivity 0.81, and specificity 0.86. Clinical-combined models showed an AUC of 0.93, sensitivity 0.84, and specificity 0.89. Moderate to severe heterogeneity was noted and addressed. Deep-learning models outperformed radiomics models, while clinical-combined models outperformed deep learning-only and radiomics-only models. The average METRICS score was 62.85%. No publication bias was detected. DL and radiomics models showed great potential in predicting HT in AIS patients. However, addressing methodological issues-such as inconsistent reference standards and limited external validation-is essential for the clinical implementation of these models.</p>","PeriodicalId":11623,"journal":{"name":"Emergency Radiology","volume":" ","pages":"409-433"},"PeriodicalIF":1.7,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143709141","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}

{"title":"Prognostic value of a new computed tomography severity score in hemorrhagic fever with renal syndrome.","authors":"Se Woo Kim, Cheong-Il Shin, Min Woo Kang, Min Cheol Kim, Donghwan Kim","doi":"10.1007/s10140-025-02322-9","DOIUrl":"10.1007/s10140-025-02322-9","url":null,"abstract":"<p><strong>Purpose: </strong>To develop of a novel computed tomography (CT) severity score for hemorrhagic fever with renal syndrome (HFRS) and evaluate its correlation with disease severity and adverse outcomes.</p><p><strong>Methods: </strong>This retrospective study included 37 patients diagnosed with HFRS from January 2012 to December 2023 who had available clinical laboratory and abdominal CT data during the acute phase. The CT severity score (range 0-5) was based on perirenal fat stranding, pararenal fascia thickening, anterior pararenal space fat stranding, ascites, and pleural effusion. Correlations between the score and markers of inflammation, thrombocytopenia, proteinuria, and adverse outcomes-including nephrotic range proteinuria and renal replacement therapy (RRT)-were analyzed.</p><p><strong>Results: </strong>The CT severity score exhibited moderate to strong correlations with markers of inflammation (white blood cell count, ρ = 0.65, p < 0.001), thrombocytopenia (platelet count, ρ = -0.54, p < 0.001), and proteinuria (urine protein-to-creatinine ratio, ρ = 0.56, p < 0.001). Higher scores were associated with increased nephrotic range proteinuria in Chi-squared test for trend (p-for-trend = 0.001). A one-point increase in the score significantly increased odds of requiring RRT in logistic regression analysis (odds ratio: 9.89, p = 0.047). The score achieved an area under the receiver operating characteristics curve of 0.819 for predicting RRT.</p><p><strong>Conclusion: </strong>The CT severity score correlates well with disease severity and adverse outcomes in HFRS and can be assessed using noncontrast CT, making it a valuable prognostic tool in young male population. Further validation in diverse populations is warranted.</p>","PeriodicalId":11623,"journal":{"name":"Emergency Radiology","volume":" ","pages":"377-385"},"PeriodicalIF":1.7,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12133915/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143613967","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Imaging of acute small bowel pathologies in oncology patients in the ER part II: the role of computed tomography (CT) in detection of treatment-related small bowel complications.","authors":"Hajra Arshad, Satomi Kawamoto, Linda C Chu, Elliot K Fishman","doi":"10.1007/s10140-025-02342-5","DOIUrl":"10.1007/s10140-025-02342-5","url":null,"abstract":"<p><p>There is a high burden of acute abdomen presentations in oncology patients, stemming from tumor development, surgical interventions, and the side effects of treatments on the gastrointestinal tract. Chemotherapy, radiotherapy and postsurgical complications have previously been shown to affect the small bowel; however, newer modalities of cancer treatment including immunotherapy and antiangiogenic therapy have also been seen to cause bowel injury. Traditional computed tomography (CT) scans are used as the gold standard diagnostic modality. However, three-dimensional (3D) postprocessing techniques including maximal intensity projection (MIP), volume rendering (VR) and cinematic rendering (CR) have been utilized for image interpretation. For a more organized approach to describe diagnostic challenges in this complex population, we have divided the pictorial essay into two parts. The first part focused on tumor- and infection-associated causes. This second part will address treatment-related complications, including chemotherapy, radiotherapy, immunotherapy, graft-versus-host disease and post-surgical complications as summarized below.</p>","PeriodicalId":11623,"journal":{"name":"Emergency Radiology","volume":" ","pages":"475-482"},"PeriodicalIF":1.7,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143974627","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}

{"title":"Rapid abdominal MRI for appendicitis for evaluation of ovarian torsion in children.","authors":"Sharon W Gould, Tejal Mody, Mary D Gould, Heidi Kecskemethy, Simone Veale, Jobayer Hossain, Arabinda K Choudhary","doi":"10.1007/s10140-025-02346-1","DOIUrl":"10.1007/s10140-025-02346-1","url":null,"abstract":"<p><strong>Purpose: </strong>Diagnosing adnexal torsion is challenging due to non-specific presentation and ultrasound findings. MRI may provide alternative assessment of adnexal torsion. We evaluated an MRI appendicitis protocol for torsion identification.</p><p><strong>Methods: </strong>Retrospective chart and image review was performed for girls with appendicitis MRI exams from 2013 to 2019. Ovarian volumes, stromal T2 signal, and apparent diffusion coefficient (ADC) ratios were tabulated. Ovarian and paratubal cysts' size and location were recorded as well as presence or absence of torsion. Statistical analysis was performed.</p><p><strong>Results: </strong>Six hundred-fifty cases were included, eight with torsion. Higher ovarian volumes and volume ratios were found with torsion (p < 0.0001 and p < 0.0001, respectively). Ovarian volume ratio less than 4:1 had 99.7% negative predictive value (NPV). Ovarian volume less than 20 mL had 99.8% NPV. Five of six cases with 7 cm or larger adnexal cysts were torsed. T2 signal and ADC ratios overlapped between torsed and untorsed groups. No torsed adnexa appeared normal on MRI.</p><p><strong>Conclusion: </strong>Torsed cases tended to have larger ovaries and higher volume ratios. Adnexal cysts greater than 7 cm diameter were likely to be torsed. No torsion cases had normal adnexae on MRI. Normal appearing adnexae on MRI are very unlikely to be torsed.</p>","PeriodicalId":11623,"journal":{"name":"Emergency Radiology","volume":" ","pages":"339-349"},"PeriodicalIF":1.7,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143992354","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}

{"title":"Computed tomographic pulmonary angiography using low tube voltage and slow contrast medium injection.","authors":"Keisuke Takiguchi, Atsushi Urikura, Tsukasa Yoshida, Kazuaki Nakashima, Koiku Asakura, Masahiro Endo","doi":"10.1007/s10140-025-02326-5","DOIUrl":"10.1007/s10140-025-02326-5","url":null,"abstract":"<p><strong>Purpose: </strong>The diagnosis of acute pulmonary thromboembolism (PTE) is often performed by computed tomographic pulmonary angiography (CTPA). This study investigated the effects of a CTPA protocol combining slow contrast medium injection and low tube voltage on radiation exposure and image quality.</p><p><strong>Methods: </strong>We retrospectively analyzed 82 patients undergoing CT scans for cancer treatment efficacy or follow-up, and simultaneous PTE exclusion. Patients were divided into two groups. Those in Group A (n = 43) received slow contrast injection (0.7-1.5 mL/s), and those in Group B (n = 39) received rapid injection (2.6-4.2 mL/s). All CT scans were performed using a multi-detector row CT scanner with optimized tube voltage and current settings. Contrast medium doses were adjusted based on the patient's body weight.</p><p><strong>Results: </strong>Group A had significantly lower radiation exposure compared with Group B. PTE was diagnosed in eight patients in Group A and seven in Group B, with no significant difference in prevalence rates. While Group B indicated higher mean CT values in the CTPA phase, the difference in the mean CT value of the pulmonary artery was only 29.6 Hounsfield units. Group A demonstrated superior contrast enhancement in parenchymal organs during the second phase.</p><p><strong>Conclusion: </strong>The slow-injection CTPA method proved effective for simultaneous PTE exclusion and cancer treatment evaluation, maintaining diagnostic accuracy with reduced risks associated with rapid injection.</p>","PeriodicalId":11623,"journal":{"name":"Emergency Radiology","volume":" ","pages":"369-376"},"PeriodicalIF":1.7,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143514961","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}

{"title":"Imaging in penetrating neck injuries.","authors":"Snehal Ishwar Kose","doi":"10.1007/s10140-025-02345-2","DOIUrl":"10.1007/s10140-025-02345-2","url":null,"abstract":"<p><p>The neck is a close compartment wherein many vital structures like carotid and vertebral vessels, larynx, trachea, pharynx, oesophagus and spinal cord are packed closely. As a result penetrating neck injury with either sharp objects like knife or projectile injury can result in significant morbidity and mortality. There have been considerable changes in management strategies of penetrating neck injuries time to time with most of injuries managed conservatively in hemodynamically stable patients. CT angiography plays an important role in detecting injuries to structure which require immediate surgery/ endovascular intervention and helps to avoid unnecessary surgical exploration in stable patients. This article intends to familiarize radiologists with imaging features of injuries to various structures of neck which shouldn't be missed and highlight stepwise approach for evaluation of neck structures in penetrating injury.</p>","PeriodicalId":11623,"journal":{"name":"Emergency Radiology","volume":" ","pages":"395-408"},"PeriodicalIF":1.7,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143985325","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}